Outcomes Research in Review

Study Overview

Objective. To determine whether the use of imaging tests following primary treatment of differentiated thyroid cancer is associated with an increase in treatment for recurrence and improved survival.

Design. Population-based retrospective cohort study.

Setting and participants. Participants were patients from the Surveillance, Epidemiology, and End Results (SEER) Medicare-linked cancer registry who were diagnosed with differentiated thyroid cancer between 1 January 1998 and 31 December 2011. The study cohort included 28,220 patients. Patient follow up continued to 2013.

Main outcome measures. The primary outcome measures were treatment of differentiated thyroid cancer and deaths due to differentiated thyroid cancer. Number of diagnoses, imaging tests (neck ultrasounds, radioiodine scans, and PET scans), treatments for recurrence (repeat neck surgery, further radioactive iodine treatment, and radiotherapy), and disease-specific deaths were obtained for each year between 1998 and 2011. Propensity score analyses were performed to assess the relation between imaging and treatment for recurrence (logistic model) and death (Cox proportional hazards model).

Main results. Between 1998 and 2011, there was a significant increase in incident thyroid cancer (rate ratio 1.05; 95% confidence interval [CI] 1.05 to 1.06), imaging (rate ratio 1.13; 95% CI 1.12 to 1.13), and treatment for recurrence (rate ratio 1.01, 95% CI 1.01 to 1.02), but the overall death rate from thyroid cancer did not change. 56.7% of patients underwent surveillance ultrasound, 23.9% radioiodine scan, and 14.9% PET scan. After controlling for patient and tumor characteristics, patients who under-went ultrasound were more likely to have additional surgery (odds ratio [OR] 2.3, 95% CI 2.05 to 2.58) and additional radioactive iodine treatment (OR 1.45, 95% CI 1.26 to 1.69) but not radiotherapy (OR 1.08; 95% CI 0.97 to 1.20). Patients who underwent radioiodine scans and PET scans were more likely to have surgery (OR 3.39, 95% CI 3.06 to 3.76 and OR 2.31, 95% CI 2.09 to 2.55), radioactive iodine treatment (OR 17.83, 95% CI 14.49 to 22.16 and OR 2.13, 95% CI 1.89 to 2.40), and radiotherapy (OR 1.89, 95% CI 1.71 to 2.10 and OR 4.98, 95% CI 4.52 to 5.49). Thyroid cancer was the cause of death in 4.1% of the cohort. Disease-specific survival was increased in patients who had radioiodine scans (hazard ratio [HR] 0.70, 95% CI 0.60 to 0.82) but not in those who underwent ultrasound (HR 1.14, 95% CI 0.98 to 1.27) or PET scans (HR 0.91, 95% CI 0.77 to 1.07).

Conclusion. Increased use of imaging after primary treatment of thyroid cancer is associated with increased treatment for recurrence but not with improved disease-specific survival, except for radioiodine scans in presumed iodine-avid disease.

Commentary

Thyroid cancer is the most rapidly increasing cancer in the United States. An estimated 64,000 new cases will be diagnosed in 2016, which represents a tripling in thyroid cancer incidenceover the past 30 years [1]. During this time, mortality from thyroid cancer has remained stable. Most of the increase incidence is attributable to enhanced detection and diagnosis of low-risk disease (ie, papillary tumors) [2]. Although long-term survival following treatment of low-risk thyroid cancer is excellent, with 10-year survival ranging from 96% to 100% [3], concern about risk for recurrence appears to be driving an increased use of imaging in post-treatment surveillance. It is not clear, however, if the benefits of more imaging outweigh its associated costs, which include increased patient anxiety and financial costs, radiation exposure, and the potential for harm from additional treatment.

This retrospective observational study by Banerjee et al evaluated how frequently imaging is used after patients undergo primary treatment of thyroid cancer and whether post-treatment surveillance imaging affects disease-specific survival. The authors used SEERS-Medicare data from 28,220 patients diagnosed with differentiated thyroid cancer. They found a high rate of imaging after primary treatment of thyroid cancer, and all 3 imaging modalities—ultrasound, radioiodine scans, and PET scan—were associated with a higher likelihood that patients would undergo treatment for recurrence. However, only use of radioiodine scans was associated with improved survival. Radioiodine scans are recommended only for persons who have had iodine-avid disease and have evidence of recurrence on biochemical testing. This form of testing may be associated with improved survival because radioactive iodine itself frequently is effective treatment for iodine-avid disease, and iodine-avid disease is usually well differentiated and has a good prognosis. The findings of this study suggest that more imaging following primary treatment is detecting more recurrences but without having a beneficial impact on patient survival.

This study has several limitations. The study’s retrospective, observational design allows it to demonstrate only associations between imaging and treatment for recurrence or survival without providing insight into causes. The SEER-Medicare database lacks data on patient-specific variables, such as iodine avidity, patient preference, and indications for imaging, which could provide alternative explanations for the observed associations. The median age of patients in this study was 65 years, which could limit the applicability of the findings to other populations.

Applications for Clinical Practice

The approach to surveillance following treatment of differentiated thyroid cancer continues to evolve, but evidence to guide the use of imaging in recurrence monitoring is lacking. This study provides an evidence base for strategies that reduce unnecessary testing and that base surveillance plans on individual patient risk. Future studies should explore the cost-effectiveness of imaging tests and the role of physicians and patients in determining when imaging is done. Randomized controlled trials that compare outcomes when small recurrences are followed rather than treated are also needed.

Study Overview

Objective. To determine whether the use of imaging tests following primary treatment of differentiated thyroid cancer is associated with an increase in treatment for recurrence and improved survival.

Design. Population-based retrospective cohort study.

Setting and participants. Participants were patients from the Surveillance, Epidemiology, and End Results (SEER) Medicare-linked cancer registry who were diagnosed with differentiated thyroid cancer between 1 January 1998 and 31 December 2011. The study cohort included 28,220 patients. Patient follow up continued to 2013.

Main outcome measures. The primary outcome measures were treatment of differentiated thyroid cancer and deaths due to differentiated thyroid cancer. Number of diagnoses, imaging tests (neck ultrasounds, radioiodine scans, and PET scans), treatments for recurrence (repeat neck surgery, further radioactive iodine treatment, and radiotherapy), and disease-specific deaths were obtained for each year between 1998 and 2011. Propensity score analyses were performed to assess the relation between imaging and treatment for recurrence (logistic model) and death (Cox proportional hazards model).

Main results. Between 1998 and 2011, there was a significant increase in incident thyroid cancer (rate ratio 1.05; 95% confidence interval [CI] 1.05 to 1.06), imaging (rate ratio 1.13; 95% CI 1.12 to 1.13), and treatment for recurrence (rate ratio 1.01, 95% CI 1.01 to 1.02), but the overall death rate from thyroid cancer did not change. 56.7% of patients underwent surveillance ultrasound, 23.9% radioiodine scan, and 14.9% PET scan. After controlling for patient and tumor characteristics, patients who under-went ultrasound were more likely to have additional surgery (odds ratio [OR] 2.3, 95% CI 2.05 to 2.58) and additional radioactive iodine treatment (OR 1.45, 95% CI 1.26 to 1.69) but not radiotherapy (OR 1.08; 95% CI 0.97 to 1.20). Patients who underwent radioiodine scans and PET scans were more likely to have surgery (OR 3.39, 95% CI 3.06 to 3.76 and OR 2.31, 95% CI 2.09 to 2.55), radioactive iodine treatment (OR 17.83, 95% CI 14.49 to 22.16 and OR 2.13, 95% CI 1.89 to 2.40), and radiotherapy (OR 1.89, 95% CI 1.71 to 2.10 and OR 4.98, 95% CI 4.52 to 5.49). Thyroid cancer was the cause of death in 4.1% of the cohort. Disease-specific survival was increased in patients who had radioiodine scans (hazard ratio [HR] 0.70, 95% CI 0.60 to 0.82) but not in those who underwent ultrasound (HR 1.14, 95% CI 0.98 to 1.27) or PET scans (HR 0.91, 95% CI 0.77 to 1.07).

Conclusion. Increased use of imaging after primary treatment of thyroid cancer is associated with increased treatment for recurrence but not with improved disease-specific survival, except for radioiodine scans in presumed iodine-avid disease.

Commentary

Thyroid cancer is the most rapidly increasing cancer in the United States. An estimated 64,000 new cases will be diagnosed in 2016, which represents a tripling in thyroid cancer incidenceover the past 30 years [1]. During this time, mortality from thyroid cancer has remained stable. Most of the increase incidence is attributable to enhanced detection and diagnosis of low-risk disease (ie, papillary tumors) [2]. Although long-term survival following treatment of low-risk thyroid cancer is excellent, with 10-year survival ranging from 96% to 100% [3], concern about risk for recurrence appears to be driving an increased use of imaging in post-treatment surveillance. It is not clear, however, if the benefits of more imaging outweigh its associated costs, which include increased patient anxiety and financial costs, radiation exposure, and the potential for harm from additional treatment.

This retrospective observational study by Banerjee et al evaluated how frequently imaging is used after patients undergo primary treatment of thyroid cancer and whether post-treatment surveillance imaging affects disease-specific survival. The authors used SEERS-Medicare data from 28,220 patients diagnosed with differentiated thyroid cancer. They found a high rate of imaging after primary treatment of thyroid cancer, and all 3 imaging modalities—ultrasound, radioiodine scans, and PET scan—were associated with a higher likelihood that patients would undergo treatment for recurrence. However, only use of radioiodine scans was associated with improved survival. Radioiodine scans are recommended only for persons who have had iodine-avid disease and have evidence of recurrence on biochemical testing. This form of testing may be associated with improved survival because radioactive iodine itself frequently is effective treatment for iodine-avid disease, and iodine-avid disease is usually well differentiated and has a good prognosis. The findings of this study suggest that more imaging following primary treatment is detecting more recurrences but without having a beneficial impact on patient survival.

This study has several limitations. The study’s retrospective, observational design allows it to demonstrate only associations between imaging and treatment for recurrence or survival without providing insight into causes. The SEER-Medicare database lacks data on patient-specific variables, such as iodine avidity, patient preference, and indications for imaging, which could provide alternative explanations for the observed associations. The median age of patients in this study was 65 years, which could limit the applicability of the findings to other populations.

Applications for Clinical Practice

The approach to surveillance following treatment of differentiated thyroid cancer continues to evolve, but evidence to guide the use of imaging in recurrence monitoring is lacking. This study provides an evidence base for strategies that reduce unnecessary testing and that base surveillance plans on individual patient risk. Future studies should explore the cost-effectiveness of imaging tests and the role of physicians and patients in determining when imaging is done. Randomized controlled trials that compare outcomes when small recurrences are followed rather than treated are also needed.

Study Overview

Objective. To determine whether the use of imaging tests following primary treatment of differentiated thyroid cancer is associated with an increase in treatment for recurrence and improved survival.

Design. Population-based retrospective cohort study.

Setting and participants. Participants were patients from the Surveillance, Epidemiology, and End Results (SEER) Medicare-linked cancer registry who were diagnosed with differentiated thyroid cancer between 1 January 1998 and 31 December 2011. The study cohort included 28,220 patients. Patient follow up continued to 2013.

Main outcome measures. The primary outcome measures were treatment of differentiated thyroid cancer and deaths due to differentiated thyroid cancer. Number of diagnoses, imaging tests (neck ultrasounds, radioiodine scans, and PET scans), treatments for recurrence (repeat neck surgery, further radioactive iodine treatment, and radiotherapy), and disease-specific deaths were obtained for each year between 1998 and 2011. Propensity score analyses were performed to assess the relation between imaging and treatment for recurrence (logistic model) and death (Cox proportional hazards model).

Main results. Between 1998 and 2011, there was a significant increase in incident thyroid cancer (rate ratio 1.05; 95% confidence interval [CI] 1.05 to 1.06), imaging (rate ratio 1.13; 95% CI 1.12 to 1.13), and treatment for recurrence (rate ratio 1.01, 95% CI 1.01 to 1.02), but the overall death rate from thyroid cancer did not change. 56.7% of patients underwent surveillance ultrasound, 23.9% radioiodine scan, and 14.9% PET scan. After controlling for patient and tumor characteristics, patients who under-went ultrasound were more likely to have additional surgery (odds ratio [OR] 2.3, 95% CI 2.05 to 2.58) and additional radioactive iodine treatment (OR 1.45, 95% CI 1.26 to 1.69) but not radiotherapy (OR 1.08; 95% CI 0.97 to 1.20). Patients who underwent radioiodine scans and PET scans were more likely to have surgery (OR 3.39, 95% CI 3.06 to 3.76 and OR 2.31, 95% CI 2.09 to 2.55), radioactive iodine treatment (OR 17.83, 95% CI 14.49 to 22.16 and OR 2.13, 95% CI 1.89 to 2.40), and radiotherapy (OR 1.89, 95% CI 1.71 to 2.10 and OR 4.98, 95% CI 4.52 to 5.49). Thyroid cancer was the cause of death in 4.1% of the cohort. Disease-specific survival was increased in patients who had radioiodine scans (hazard ratio [HR] 0.70, 95% CI 0.60 to 0.82) but not in those who underwent ultrasound (HR 1.14, 95% CI 0.98 to 1.27) or PET scans (HR 0.91, 95% CI 0.77 to 1.07).

Conclusion. Increased use of imaging after primary treatment of thyroid cancer is associated with increased treatment for recurrence but not with improved disease-specific survival, except for radioiodine scans in presumed iodine-avid disease.

Commentary

Thyroid cancer is the most rapidly increasing cancer in the United States. An estimated 64,000 new cases will be diagnosed in 2016, which represents a tripling in thyroid cancer incidenceover the past 30 years [1]. During this time, mortality from thyroid cancer has remained stable. Most of the increase incidence is attributable to enhanced detection and diagnosis of low-risk disease (ie, papillary tumors) [2]. Although long-term survival following treatment of low-risk thyroid cancer is excellent, with 10-year survival ranging from 96% to 100% [3], concern about risk for recurrence appears to be driving an increased use of imaging in post-treatment surveillance. It is not clear, however, if the benefits of more imaging outweigh its associated costs, which include increased patient anxiety and financial costs, radiation exposure, and the potential for harm from additional treatment.

This retrospective observational study by Banerjee et al evaluated how frequently imaging is used after patients undergo primary treatment of thyroid cancer and whether post-treatment surveillance imaging affects disease-specific survival. The authors used SEERS-Medicare data from 28,220 patients diagnosed with differentiated thyroid cancer. They found a high rate of imaging after primary treatment of thyroid cancer, and all 3 imaging modalities—ultrasound, radioiodine scans, and PET scan—were associated with a higher likelihood that patients would undergo treatment for recurrence. However, only use of radioiodine scans was associated with improved survival. Radioiodine scans are recommended only for persons who have had iodine-avid disease and have evidence of recurrence on biochemical testing. This form of testing may be associated with improved survival because radioactive iodine itself frequently is effective treatment for iodine-avid disease, and iodine-avid disease is usually well differentiated and has a good prognosis. The findings of this study suggest that more imaging following primary treatment is detecting more recurrences but without having a beneficial impact on patient survival.

This study has several limitations. The study’s retrospective, observational design allows it to demonstrate only associations between imaging and treatment for recurrence or survival without providing insight into causes. The SEER-Medicare database lacks data on patient-specific variables, such as iodine avidity, patient preference, and indications for imaging, which could provide alternative explanations for the observed associations. The median age of patients in this study was 65 years, which could limit the applicability of the findings to other populations.

Applications for Clinical Practice

The approach to surveillance following treatment of differentiated thyroid cancer continues to evolve, but evidence to guide the use of imaging in recurrence monitoring is lacking. This study provides an evidence base for strategies that reduce unnecessary testing and that base surveillance plans on individual patient risk. Future studies should explore the cost-effectiveness of imaging tests and the role of physicians and patients in determining when imaging is done. Randomized controlled trials that compare outcomes when small recurrences are followed rather than treated are also needed.

Study Overview

Objective. To evaluate if exercise during pregnancy has an effect on the risk of preterm birth.

Design. Systematic review and meta-analysis of randomized controlled trials.

Study selection. The authors followed the protocol for conducting meta-analyses recommended by the Cochrane Collaboration. MEDLINE, EMBASE, Web of Science, Scopus, ClinicalTrials.gov, OVID, and the Cochrane Library were searched from the inception of each database to April 2016. Selection criteria included randomized clinical trials that examined the effect of aerobic exercise on preterm birth. Keywords included exercise or physical activity and pregnancy and preterm birth or preterm delivery. Studies were included only if women were randomized to an aerobic exercise program prior to 23 weeks, participants had uncomplicated singleton pregnancies and no contraindication to exercise, and preterm birth was an outcome.

Nine studies met the inclusion criteria and were included in the meta-analysis. The quality of included studies was good overall, with most studies having low risk of selection or attrition bias and low or unclear risk of reporting bias. Most of the studies did not include blinding of participants and research personnel or of the outcome assessment. Sample sizes ranged from 14 to 697, with 2 studies with < 100 participants, 3 with 100 to 200 participants, and 3 with 290 to 687 participants. All of the women randomized to the experimental group began an exercise program by 22 weeks’ gestation. The types of physical activity used in the experimental group included strength and flexibility training, cycling, stretching, resistance, dance, joint mobilization, walking, and toning. Participants engaged in the activity for 35 to 90 minutes (mean, 57 minutes) 3 times a week in 8 studies and 4 times a week in 1 study. The intensity of the aerobic activities ranged from less than 60% to less than 80% of age-predicted maximum heart rate. Participants in 3 control groups were explicitly told not to engage in exercise while those in the others were neither encouraged or discouraged from doing so.

Main outcome measure. Incidence of preterm birth (birth prior to 37 weeks’ gestation).

Main results. A total of 2059 women were included in the meta-analysis, with 1022 in the exercise group and 1037 in the control group. The incidence of preterm birth was similar in the experimental and the control groups (4.5% vs 4.4% respectively, 95% confidence interval [CI], –0.07 to 0.17). The mean gestational age at delivery was also similar, with a mean difference of 0.05 (95% CI, –0.07 to 0.17). Women in the exercise group had a decreased risk of cesarean delivery (0.82%), with 17.9% having a cesarean delivery compared to 22% in the control group ( 95% CI, 0.69 to 0.97).

Conclusion. Exercise during pregnancy in women with singleton, uncomplicated pregnancy is not associated with increased risk of preterm delivery. Additionally, it is associated with a decreased risk of cesarean delivery.

Commentary

Preterm birth accounts for most perinatal deaths in the United States and places surviving infants at risk for serious short- and long-term health problems [1]. Though the rate of preterm births in the United States has been slowly declining in recent years, at 9.57% it continues to be one of the highest among high-income countries [2]. Determining factors that contribute to incidence of preterm birth is critical to reducing this unacceptably high rate. According to the authors of this meta-analysis, the role of exercise related to preterm birth remains controversial due to past beliefs that the increased release of catecholamines during exercise would stimulate myometrial activity and ongoing concerns about possible adverse effects. The health benefits of regular exercise are well-known, including in pregnancy where it has been shown to lower the risk of gestational diabetes and preeclampsia.

Researchers have investigated exercise during pregnancy in earlier reviews; however, this appears to be the first with both preterm birth as the primary outcome and an adequate number of clinical trials in the sample. Prior reviews that examined the effects of exercise on preterm birth, either specifically or as one of a number of pregnancy outcomes, included only 3 to 5 studies pertaining to preterm birth [3–5].

The strengths of this review were the low statistical heterogeneity and high quality of the included studies, lack of publication bias, and the large sample of 2059 participants. As noted by the authors, however, lack of stratification by body mass (underweight, overweight, obese), differences in the types and intensity of exercise among interventions, as well as possible differences in adherence may have affected outcomes. In addition, in 6 studies women in the control group were not specifically instructed to refrain from exercise and there is no information about their exercise habits. The risk of contamination bias exists because some of these women may have engaged in a regular program of exercise. However, considering that levels of regular exercise in pregnant women are low, it is unlikely that this would occur at a rate that would have a significant effect on the outcomes [6].

Applications for Clinical Practice

The results of this meta-analysis provide strong support for the American College of Obstetrics and Gynecology recommendation that women with uncomplicated pregnancies be encouraged to engage in moderate-intensity exercise 20 to 30 minutes per day during pregnancy [7]. Clinicians should advise all women with uncomplicated singleton pregnancies and no medical contraindications to engage in regular aerobic and strength-conditioning exercise throughout their pregnancy.

—Karen Roush, PhD, RN

Study Overview

Objective. To evaluate if exercise during pregnancy has an effect on the risk of preterm birth.

Design. Systematic review and meta-analysis of randomized controlled trials.

Study selection. The authors followed the protocol for conducting meta-analyses recommended by the Cochrane Collaboration. MEDLINE, EMBASE, Web of Science, Scopus, ClinicalTrials.gov, OVID, and the Cochrane Library were searched from the inception of each database to April 2016. Selection criteria included randomized clinical trials that examined the effect of aerobic exercise on preterm birth. Keywords included exercise or physical activity and pregnancy and preterm birth or preterm delivery. Studies were included only if women were randomized to an aerobic exercise program prior to 23 weeks, participants had uncomplicated singleton pregnancies and no contraindication to exercise, and preterm birth was an outcome.

Nine studies met the inclusion criteria and were included in the meta-analysis. The quality of included studies was good overall, with most studies having low risk of selection or attrition bias and low or unclear risk of reporting bias. Most of the studies did not include blinding of participants and research personnel or of the outcome assessment. Sample sizes ranged from 14 to 697, with 2 studies with < 100 participants, 3 with 100 to 200 participants, and 3 with 290 to 687 participants. All of the women randomized to the experimental group began an exercise program by 22 weeks’ gestation. The types of physical activity used in the experimental group included strength and flexibility training, cycling, stretching, resistance, dance, joint mobilization, walking, and toning. Participants engaged in the activity for 35 to 90 minutes (mean, 57 minutes) 3 times a week in 8 studies and 4 times a week in 1 study. The intensity of the aerobic activities ranged from less than 60% to less than 80% of age-predicted maximum heart rate. Participants in 3 control groups were explicitly told not to engage in exercise while those in the others were neither encouraged or discouraged from doing so.

Main outcome measure. Incidence of preterm birth (birth prior to 37 weeks’ gestation).

Main results. A total of 2059 women were included in the meta-analysis, with 1022 in the exercise group and 1037 in the control group. The incidence of preterm birth was similar in the experimental and the control groups (4.5% vs 4.4% respectively, 95% confidence interval [CI], –0.07 to 0.17). The mean gestational age at delivery was also similar, with a mean difference of 0.05 (95% CI, –0.07 to 0.17). Women in the exercise group had a decreased risk of cesarean delivery (0.82%), with 17.9% having a cesarean delivery compared to 22% in the control group ( 95% CI, 0.69 to 0.97).

Conclusion. Exercise during pregnancy in women with singleton, uncomplicated pregnancy is not associated with increased risk of preterm delivery. Additionally, it is associated with a decreased risk of cesarean delivery.

Commentary

Preterm birth accounts for most perinatal deaths in the United States and places surviving infants at risk for serious short- and long-term health problems [1]. Though the rate of preterm births in the United States has been slowly declining in recent years, at 9.57% it continues to be one of the highest among high-income countries [2]. Determining factors that contribute to incidence of preterm birth is critical to reducing this unacceptably high rate. According to the authors of this meta-analysis, the role of exercise related to preterm birth remains controversial due to past beliefs that the increased release of catecholamines during exercise would stimulate myometrial activity and ongoing concerns about possible adverse effects. The health benefits of regular exercise are well-known, including in pregnancy where it has been shown to lower the risk of gestational diabetes and preeclampsia.

Researchers have investigated exercise during pregnancy in earlier reviews; however, this appears to be the first with both preterm birth as the primary outcome and an adequate number of clinical trials in the sample. Prior reviews that examined the effects of exercise on preterm birth, either specifically or as one of a number of pregnancy outcomes, included only 3 to 5 studies pertaining to preterm birth [3–5].

The strengths of this review were the low statistical heterogeneity and high quality of the included studies, lack of publication bias, and the large sample of 2059 participants. As noted by the authors, however, lack of stratification by body mass (underweight, overweight, obese), differences in the types and intensity of exercise among interventions, as well as possible differences in adherence may have affected outcomes. In addition, in 6 studies women in the control group were not specifically instructed to refrain from exercise and there is no information about their exercise habits. The risk of contamination bias exists because some of these women may have engaged in a regular program of exercise. However, considering that levels of regular exercise in pregnant women are low, it is unlikely that this would occur at a rate that would have a significant effect on the outcomes [6].

Applications for Clinical Practice

The results of this meta-analysis provide strong support for the American College of Obstetrics and Gynecology recommendation that women with uncomplicated pregnancies be encouraged to engage in moderate-intensity exercise 20 to 30 minutes per day during pregnancy [7]. Clinicians should advise all women with uncomplicated singleton pregnancies and no medical contraindications to engage in regular aerobic and strength-conditioning exercise throughout their pregnancy.

—Karen Roush, PhD, RN

Study Overview

Objective. To evaluate if exercise during pregnancy has an effect on the risk of preterm birth.

Design. Systematic review and meta-analysis of randomized controlled trials.

Study selection. The authors followed the protocol for conducting meta-analyses recommended by the Cochrane Collaboration. MEDLINE, EMBASE, Web of Science, Scopus, ClinicalTrials.gov, OVID, and the Cochrane Library were searched from the inception of each database to April 2016. Selection criteria included randomized clinical trials that examined the effect of aerobic exercise on preterm birth. Keywords included exercise or physical activity and pregnancy and preterm birth or preterm delivery. Studies were included only if women were randomized to an aerobic exercise program prior to 23 weeks, participants had uncomplicated singleton pregnancies and no contraindication to exercise, and preterm birth was an outcome.

Nine studies met the inclusion criteria and were included in the meta-analysis. The quality of included studies was good overall, with most studies having low risk of selection or attrition bias and low or unclear risk of reporting bias. Most of the studies did not include blinding of participants and research personnel or of the outcome assessment. Sample sizes ranged from 14 to 697, with 2 studies with < 100 participants, 3 with 100 to 200 participants, and 3 with 290 to 687 participants. All of the women randomized to the experimental group began an exercise program by 22 weeks’ gestation. The types of physical activity used in the experimental group included strength and flexibility training, cycling, stretching, resistance, dance, joint mobilization, walking, and toning. Participants engaged in the activity for 35 to 90 minutes (mean, 57 minutes) 3 times a week in 8 studies and 4 times a week in 1 study. The intensity of the aerobic activities ranged from less than 60% to less than 80% of age-predicted maximum heart rate. Participants in 3 control groups were explicitly told not to engage in exercise while those in the others were neither encouraged or discouraged from doing so.

Main outcome measure. Incidence of preterm birth (birth prior to 37 weeks’ gestation).

Main results. A total of 2059 women were included in the meta-analysis, with 1022 in the exercise group and 1037 in the control group. The incidence of preterm birth was similar in the experimental and the control groups (4.5% vs 4.4% respectively, 95% confidence interval [CI], –0.07 to 0.17). The mean gestational age at delivery was also similar, with a mean difference of 0.05 (95% CI, –0.07 to 0.17). Women in the exercise group had a decreased risk of cesarean delivery (0.82%), with 17.9% having a cesarean delivery compared to 22% in the control group ( 95% CI, 0.69 to 0.97).

Conclusion. Exercise during pregnancy in women with singleton, uncomplicated pregnancy is not associated with increased risk of preterm delivery. Additionally, it is associated with a decreased risk of cesarean delivery.

Commentary

Preterm birth accounts for most perinatal deaths in the United States and places surviving infants at risk for serious short- and long-term health problems [1]. Though the rate of preterm births in the United States has been slowly declining in recent years, at 9.57% it continues to be one of the highest among high-income countries [2]. Determining factors that contribute to incidence of preterm birth is critical to reducing this unacceptably high rate. According to the authors of this meta-analysis, the role of exercise related to preterm birth remains controversial due to past beliefs that the increased release of catecholamines during exercise would stimulate myometrial activity and ongoing concerns about possible adverse effects. The health benefits of regular exercise are well-known, including in pregnancy where it has been shown to lower the risk of gestational diabetes and preeclampsia.

Researchers have investigated exercise during pregnancy in earlier reviews; however, this appears to be the first with both preterm birth as the primary outcome and an adequate number of clinical trials in the sample. Prior reviews that examined the effects of exercise on preterm birth, either specifically or as one of a number of pregnancy outcomes, included only 3 to 5 studies pertaining to preterm birth [3–5].

The strengths of this review were the low statistical heterogeneity and high quality of the included studies, lack of publication bias, and the large sample of 2059 participants. As noted by the authors, however, lack of stratification by body mass (underweight, overweight, obese), differences in the types and intensity of exercise among interventions, as well as possible differences in adherence may have affected outcomes. In addition, in 6 studies women in the control group were not specifically instructed to refrain from exercise and there is no information about their exercise habits. The risk of contamination bias exists because some of these women may have engaged in a regular program of exercise. However, considering that levels of regular exercise in pregnant women are low, it is unlikely that this would occur at a rate that would have a significant effect on the outcomes [6].

Applications for Clinical Practice

The results of this meta-analysis provide strong support for the American College of Obstetrics and Gynecology recommendation that women with uncomplicated pregnancies be encouraged to engage in moderate-intensity exercise 20 to 30 minutes per day during pregnancy [7]. Clinicians should advise all women with uncomplicated singleton pregnancies and no medical contraindications to engage in regular aerobic and strength-conditioning exercise throughout their pregnancy.

—Karen Roush, PhD, RN

Study Overview

Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.

Design. Randomized clinical trial.

Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.

The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.

Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.

Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.

Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.

Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.

Commentary

The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.

The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.

Applications for Clinical Practice

PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.

—Ajay Dharod, MD

Study Overview

Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.

Design. Randomized clinical trial.

Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.

The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.

Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.

Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.

Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.

Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.

Commentary

The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.

The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.

Applications for Clinical Practice

PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.

—Ajay Dharod, MD

Study Overview

Objective. To evaluate patient navigation (PN) for breast, cervical, and colorectal cancer (CRC) screening using a population-based information technology (IT) system within a primary care network.

Design. Randomized clinical trial.

Setting and participants. Patients were from 18 primary care practices in the Massachusetts General Primary Care Practice-Based Research Network, which included 4 community health centers. The study used a population health IT application (TopCare [SRG Technology]) to identify patients overdue for breast, cervical and/or CRC screening. Women were deemed eligible and overdue for breast cancer [1] and cervical cancer [2] screening based on United States Preventive Services Task Force (USPSTF) recommendation statements. Patients aged 50 to 75 years without prior total colectomy were considered eligible for CRC screening and overdue if they did not have a colonoscopy in the past 10 years or sigmoidoscopy/barium enema/colonography in the past 5 years.

The study identified patients at high risk for non-adherence via a point system based on history of non-adherence to cancer screening tests, missed appointments, and primary language spoken (non-English speaking). A total of 1956 patients were identified, and after excluding those who were participating in an existing PN program, left the primary care network, died, or were lost to follow-up, the final study population consisted of 1612 patients overdue for at least 1 screening at the start of the study period.

Intervention: The intervention was a PN program comprising 4 part-time patient navigators with at least 2 years’ experience with cancer navigation and who worked 50% of their time in other PN programs. The navigators tracked intervention patients using the IT system, contacted them in their own language, and used extensive outreach efforts to assist them in completing their cancer screening. Most contact with patients took place via phone calls.

Main outcome measures. The primary outcome was the mean cancer screening test completion rate over the follow-up period for each eligible patient, with all eligible cancers combined in intention-to-treat analyses. Secondary outcomes included assessing the proportion of patients completing any and each cancer screening during follow-up among those who were eligible and overdue for at least 1 cancer screening at baseline in intention-to-treat analyses. Additionally, as-treated analyses were conducted, in which patients who left the network or died during follow-up were removed from the intervention and control groups and patients who could not be reached were removed from the intervention group.

Results. A total of 792 patients were randomized to theintervention group (PN) and 820 patients were randomized to usual care. The mean age in the intervention and control groups was 56.9 and 57.1 years, respectively. The intervention and control groups were well-matched in terms of sex, primary language, insurance, proportion of patients connected to a specific physician or seen in a community health center, number of clinic visits over the past 3 years, and risk for nonadherence. Among patients eligible and overdue for cancer screening, mean cancer screening completion rates were higher in the intervention group compared with the control group for all cancers combined (10.2% vs 6.8%; 95% CI [for the difference] 1.5% to 5.2%; P < 0.001) and for breast (14.7% vs 11.0%; 95% CI 0.2% to 7.3%; P = 0.04), cervical (11.1% vs 5.7%; 95% CI 0.8% to 5.2%; P = 0.002), and colon (7.6% vs 4.6%;95% CI 0.8% to 5.2%; P = 0.01) cancer. The secondary outcome, the proportion of overdue patients who completed any cancer screening during follow-up, was higher in the intervention group (25.5% vs 17.0%; 95% CI 4.7% to 12.7%; P < 0.001). More patients in the intervention group completed screening for breast (23.4% vs 16.6%; 95% CI 1.8% to 12.0%; P = 0.009), cervical (14.4% vs 8.6%; 95% CI 1.6% to 10.5%; P = 0.007), and colorectal (13.7% vs 7.0%; 95% CI 3.2% to 10.4%; P < 0.001) cancer. The effect size increased in the as-treated analyses.

Conclusion. PN, using a health IT application, improved cancer screening completion rates among patients at high risk for nonadherence over an 8-month period in an academic primary care network.

Commentary

The potential of PN to help individuals traverse the complexity of the current health care system continues to attract great interest as value-based care becomes a reality for physicians and health systems. Several studies have demonstrated PN to be an effective modality to improve adherence to recommended screenings [3–5]; however, issues surrounding cost, patient perception, and the “outsourcing” of care from the primary care physician to navigators require attention. At this time, the most robust aggregation of data demonstrating benefit outweighing harm for cancer screening is published by the USPSTF [6]. Breast cancer [7], cervical cancer [8], and CRC [9] have the greatest weight of evidence to support screening.

The study was conducted at a single academic medical center with established IT infrastructure and an established PN program, which limits application of the results to large networked organizations and/or private practice settings. One important limitation in the CRC screening component was the lack of alternatives to colonoscopy. Studies have demonstrated greater adherence to CRC screening with methods other than colonoscopy [10], especially among racial/ethnic minorities. Although the authors estimate the intervention cost approximately $100,000, the study does not include the cost of the population health IT solution. The costs associated with both the IT solution in addition to PN may ultimately outweigh the benefits. The short time frame of the study may also limit effect size and add to long-term cost considerations. Lastly, a high percentage of patients randomized to the intervention group were unable to be contacted, declined PN services, had competing comorbidities, or were screened elsewhere. On the other hand, the study has several strengths. Statistically, the study utilized intention-to-treat analyses, where estimate of treatment effect is generally conservative. As compared to the current literature, the authors evaluate 3 different types of cancer—a pragmatic approach from a clinician’s perspective. Additionally, the authors focused efforts on individuals at high risk for nonadherence, a strategy also practicable by clinicians. Another realistic element of the study is that patient navigators had other responsibilities, which implies applicability to resource-limited settings.

Applications for Clinical Practice

PN has been shown to be an effective means of improving population-based health outcomes, and this study demonstrates it improves cancer screening rates, assuming the appropriate IT infrastructure is in place. The costs and benefits of PN should be assessed when considering use of PN in nonadherent populations, and PN interventions should be tailored to available resources and the unique practice environment.

—Ajay Dharod, MD

Study Overview

Objective. To determine whether weight loss and cardiometabolic risk factors are improved when mindfulness training is added to a diet-exercise program.

Design. 2-arm randomized controlled trial.

Setting and participants. Study participants were recruited through fliers, newspaper advertisements, online postings, and referrals at University of California, San Francisco clinics, and were enrolled from July 2009 to February 2012. Inclusion criteria were body mass index (BMI) between 30 and 45.9, abdominal obesity (waist circumference > 102 cm for men and > 88 cm for women), and age 18 or older. Exclusion criteria were current involvement with diet program or diet mediation, diabetes mellitus, fasting glucose ≥ 126 mg/dL, or hemoglobin A1c (HbA1C) between 6.0% and 6.5% with abnormal oral glucose tolerance test. Participants were randomized in a 1:1 ratio to one of 2 weight loss program arms using a computer-generated randomization sequence.

Intervention. In both arms, participants received general diet and exercise guidelines prescribing healthy eating and frequent exercise delivered in 16 sessions lasting 2 to 2½ hours and one all-day session over 5.5 months. Participants in the mindfulness intervention additionally received mindfulness training for eating, physical activity, and stress management from mindfulness mediation instructors and a registered dietician. They also followed guidelines at home, which included practicing meditation for up to 30 minutes 6 days a week, mini-meditations, and eating mindfully. To control for the activities and attention inherent in the mindfulness arm (eg, social support, expectation of benefit, snacks provided during mindful eating exercises, at home practice), the control arm was an “active control” and  included additional nutritional and physical activity information, snacks, strength training, home activities, conversations about society and weight loss, and low-dose progressive muscle relaxation and cognitive-behavioral training. Active control materials were delivered by one of 3 registered dieticians.

Main outcomes measures. The primary outcome was 18-month weight change. Participants’ weight, height, blood pressure, and weight circumference were measured at baseline and 3, 6, 12, and 18 months between 8 am and 10 am. Measurements were taken under fasting conditions and by arm-blinded staff. Blood samples were taken to assess secondary outcome changes in glucose, lipid, HbA1C, insulin, and C-reactive protein. Researchers also collected anonymous qualitative feedback from participants and supervisors to do a secondary analysis assessing differences in effectiveness and helpfulness of mindfulness teachings among instructors.

Main results. Of the potential participants that contacted the study team in response to recruitment efforts (n = 1485), 216 were fully eligible based on criteria and a screening visit. Participants that consented to participate (n = 194) were randomized. Participants across both groups were predominantly female, of European ethnic origin, and similar in age: mindfulness group, 47.2 years (13.0) and active control group, 47.8 years (12.4). At baseline, the mindfulness and active control arms had average BMIs of 35.4 (3.5) and 35.6 (3.8), respectively. Baseline characteristics, session attendance, and 18-month retention were similar for both arms. Participants in the mindfulness arm reported completing 70% (2.1 hours per week, SD = 1.2) of the recommended meditation time and eating 57% (SD = 29) of meals mindfully.

Weight loss outcomes between groups favored the mindfulness arms, but results were not significant. The largest difference of –1.9 kg (95% CI –4.5 to 0.8; P = 0.17) was at 12 months. The difference persisted at 18 months with –1.7 kg (95% CI –4.7 to 1.2 kg; P = 0.24). The mindfulness arm lost 4.2 kg (95% CI –6.2 to 2.2 kg) while the active control arm lost 2.4 kg (95% CI –4.5 to –0.3 kg).

Cardiometabolic outcomes at 12 months showed group differences in fasting glucose that favored the mindfulness arm, –3.1 mg/dL (95% CI 26.3 to 0.1; P = 0.06), while there was a significant group difference at 18 months, –4.1 mg/dL (95% CI –7.3 to –0.9; P  = 0.01). Data at 18-months showed that normal glucose changed minimally in the mindfulness arm, –0.31 mg/dL (95% CI –2.5 to 1.9), but increased in the active control arm 3.8 mg/dL (95% CI 1.5 to 6.1). Other cardiometabolic outcomes (ie,  triglyceride/HDL ratio and triglycerides) showed significance at 12 months, favoring the mindfulness arm, but not at 18 months. Although not all were statistically significant, 9 of 11 outcomes favored the mindfulness arm at 18 months.

Significant interactions (P < 0.05) were found between arm and enrollment rounds categorized by mindfulness instructor on weight, BMI, fasting glucose, homeostatic homeostasis model assessment of insulin resistance (defined as [glucose x insulin/{40 × 33.25}]), and HbA1c, with a marginally significant effect for waist circumference (P = 0.08). Qualitative feedback on mindfulness instructors showed that in the group with a lowly rated instructor, participants lost less weight at 18 months (–2.0 kg [95% CI –4.7 to 0.7]), compared to participants in groups with highly rated instructors (–6.3 kg [95% CI –9.1 to –3.6]; P = 0.02). Similar trends followed for reductions in BMI and waist circumference.

Conclusions. With regard to weight loss outcomes, a mindfulness-enhanced diet-exercise program and an active control arm did not show substantial differences. Some evidence, however, suggests modest benefit of added mindfulness components, which may lead to long-term maintenance of fasting glucose levels and improved atherogenic lipid profiles.

Commentary

Mindfulness, or nonjudgmental focus on the present moment, has been utilized by many interventions targeted at self-regulated behavior [1]. Mindfulness interventions aim to promote healthy behavior changes by encouraging careful monitoring of behavior reactivity. Weight loss and weight loss maintenance have been of particular interest with this approach because mindfulness-based interventions may promote long-term maintenance of weight loss [2]. This maintenance is achieved through a focus on modifying health behaviors, rather than a focus on weight loss alone [3]. Mindfulness has been incorporated into weight loss interventions through yoga practices [4] and mindfulness meditation [5].

Several studies have explored the relationship between mindfulness and weight loss in various populations, highlighting mindfulness’s role in weight loss and behavior change. Most notably, mindfulness interventions have shown improvements in fasting glucose levels [6], psychological distress [7], self-efficacy, weight loss, eating behaviors, and physical activity [8–10]. Despite being well designed, this study by Daubenmier et al did not find significant changes in weight loss. However, secondary outcomes related to weight, metabolic, syndrome, and cardiovascular risk showed modest improvements with mindfulness. These results may correlate to previous findings showing that lifestyle changes many not result in weight loss but can reverse or reduce disorders related to obesity [11].

The study was strengthened by randomization, intention-to-treat analysis, objective measures by arm-blinded staff, standardized measuring conditions, balanced participant allocation to each arm, 1-year follow-up, and qualitative feedback on instructors to assess whether weight loss may be instructor-dependent. In addition, the authors made an effort to mask their intention to test the effects of a mindfulness-enhanced intervention. They designed a rigorous active control intervention arm by controlling for attention, social support, expectations of benefit, diet-exercise guidelines, and elements of a mindfulness approach to stress management. An additional strength included a cost-analysis of adding mindfulness components. The generalizability of the results may be limited as the study population were predominantly white females and most had a bachelor’s degree. The study sample was also disproportionately menopausal women, a group that especially struggles with weight loss. This demographic factor may be responsible for the lack of significant weight loss. Other limitations of this study include participant dropout and variability between instructor styles, although the latter was explored in a secondary analysis of weight loss differences between instructors.

The researchers discussed how the active control intervention arm may have contributed to the lack of significant weight loss difference between groups. The researchers also highlighted that participants randomized to the mindfulness arm that were not interested in mindfulness practices may have benefitted less than those who were interested.  This combined with the modest diet and exercise components of the intervention may also explain the lack of significance in results. It may also explain why some outcomes were significant at earlier months but attenuated by 18 months. Future studies should assess incorporating more intense exercise and diet approaches, as well as continuous contact throughout the 18-month time period.

Applications for Clinical Practice

This study demonstrated that mindfulness components added to a diet-exercise program can be helpful in promoting metabolic changes but not necessarily weight loss. Since metabolic changes can be protective against morbidities (eg, type 2 diabetes), mindfulness can be a powerful and cost-effective approach within clinical practice. Mindfulness practices can also be easily implemented in various settings and with diverse populations. Future studies should explore adding mindfulness components to more intensive weight loss interventions. Providers and health care settings should consider incorporating mindfulness practices into weight management counseling and programs.

—Michelle J. Williamson and Katrina F. Mateo, MPH

Study Overview

Objective. To determine whether weight loss and cardiometabolic risk factors are improved when mindfulness training is added to a diet-exercise program.

Design. 2-arm randomized controlled trial.

Setting and participants. Study participants were recruited through fliers, newspaper advertisements, online postings, and referrals at University of California, San Francisco clinics, and were enrolled from July 2009 to February 2012. Inclusion criteria were body mass index (BMI) between 30 and 45.9, abdominal obesity (waist circumference > 102 cm for men and > 88 cm for women), and age 18 or older. Exclusion criteria were current involvement with diet program or diet mediation, diabetes mellitus, fasting glucose ≥ 126 mg/dL, or hemoglobin A1c (HbA1C) between 6.0% and 6.5% with abnormal oral glucose tolerance test. Participants were randomized in a 1:1 ratio to one of 2 weight loss program arms using a computer-generated randomization sequence.

Intervention. In both arms, participants received general diet and exercise guidelines prescribing healthy eating and frequent exercise delivered in 16 sessions lasting 2 to 2½ hours and one all-day session over 5.5 months. Participants in the mindfulness intervention additionally received mindfulness training for eating, physical activity, and stress management from mindfulness mediation instructors and a registered dietician. They also followed guidelines at home, which included practicing meditation for up to 30 minutes 6 days a week, mini-meditations, and eating mindfully. To control for the activities and attention inherent in the mindfulness arm (eg, social support, expectation of benefit, snacks provided during mindful eating exercises, at home practice), the control arm was an “active control” and  included additional nutritional and physical activity information, snacks, strength training, home activities, conversations about society and weight loss, and low-dose progressive muscle relaxation and cognitive-behavioral training. Active control materials were delivered by one of 3 registered dieticians.

Main outcomes measures. The primary outcome was 18-month weight change. Participants’ weight, height, blood pressure, and weight circumference were measured at baseline and 3, 6, 12, and 18 months between 8 am and 10 am. Measurements were taken under fasting conditions and by arm-blinded staff. Blood samples were taken to assess secondary outcome changes in glucose, lipid, HbA1C, insulin, and C-reactive protein. Researchers also collected anonymous qualitative feedback from participants and supervisors to do a secondary analysis assessing differences in effectiveness and helpfulness of mindfulness teachings among instructors.

Main results. Of the potential participants that contacted the study team in response to recruitment efforts (n = 1485), 216 were fully eligible based on criteria and a screening visit. Participants that consented to participate (n = 194) were randomized. Participants across both groups were predominantly female, of European ethnic origin, and similar in age: mindfulness group, 47.2 years (13.0) and active control group, 47.8 years (12.4). At baseline, the mindfulness and active control arms had average BMIs of 35.4 (3.5) and 35.6 (3.8), respectively. Baseline characteristics, session attendance, and 18-month retention were similar for both arms. Participants in the mindfulness arm reported completing 70% (2.1 hours per week, SD = 1.2) of the recommended meditation time and eating 57% (SD = 29) of meals mindfully.

Weight loss outcomes between groups favored the mindfulness arms, but results were not significant. The largest difference of –1.9 kg (95% CI –4.5 to 0.8; P = 0.17) was at 12 months. The difference persisted at 18 months with –1.7 kg (95% CI –4.7 to 1.2 kg; P = 0.24). The mindfulness arm lost 4.2 kg (95% CI –6.2 to 2.2 kg) while the active control arm lost 2.4 kg (95% CI –4.5 to –0.3 kg).

Cardiometabolic outcomes at 12 months showed group differences in fasting glucose that favored the mindfulness arm, –3.1 mg/dL (95% CI 26.3 to 0.1; P = 0.06), while there was a significant group difference at 18 months, –4.1 mg/dL (95% CI –7.3 to –0.9; P  = 0.01). Data at 18-months showed that normal glucose changed minimally in the mindfulness arm, –0.31 mg/dL (95% CI –2.5 to 1.9), but increased in the active control arm 3.8 mg/dL (95% CI 1.5 to 6.1). Other cardiometabolic outcomes (ie,  triglyceride/HDL ratio and triglycerides) showed significance at 12 months, favoring the mindfulness arm, but not at 18 months. Although not all were statistically significant, 9 of 11 outcomes favored the mindfulness arm at 18 months.

Significant interactions (P < 0.05) were found between arm and enrollment rounds categorized by mindfulness instructor on weight, BMI, fasting glucose, homeostatic homeostasis model assessment of insulin resistance (defined as [glucose x insulin/{40 × 33.25}]), and HbA1c, with a marginally significant effect for waist circumference (P = 0.08). Qualitative feedback on mindfulness instructors showed that in the group with a lowly rated instructor, participants lost less weight at 18 months (–2.0 kg [95% CI –4.7 to 0.7]), compared to participants in groups with highly rated instructors (–6.3 kg [95% CI –9.1 to –3.6]; P = 0.02). Similar trends followed for reductions in BMI and waist circumference.

Conclusions. With regard to weight loss outcomes, a mindfulness-enhanced diet-exercise program and an active control arm did not show substantial differences. Some evidence, however, suggests modest benefit of added mindfulness components, which may lead to long-term maintenance of fasting glucose levels and improved atherogenic lipid profiles.

Commentary

Mindfulness, or nonjudgmental focus on the present moment, has been utilized by many interventions targeted at self-regulated behavior [1]. Mindfulness interventions aim to promote healthy behavior changes by encouraging careful monitoring of behavior reactivity. Weight loss and weight loss maintenance have been of particular interest with this approach because mindfulness-based interventions may promote long-term maintenance of weight loss [2]. This maintenance is achieved through a focus on modifying health behaviors, rather than a focus on weight loss alone [3]. Mindfulness has been incorporated into weight loss interventions through yoga practices [4] and mindfulness meditation [5].

Several studies have explored the relationship between mindfulness and weight loss in various populations, highlighting mindfulness’s role in weight loss and behavior change. Most notably, mindfulness interventions have shown improvements in fasting glucose levels [6], psychological distress [7], self-efficacy, weight loss, eating behaviors, and physical activity [8–10]. Despite being well designed, this study by Daubenmier et al did not find significant changes in weight loss. However, secondary outcomes related to weight, metabolic, syndrome, and cardiovascular risk showed modest improvements with mindfulness. These results may correlate to previous findings showing that lifestyle changes many not result in weight loss but can reverse or reduce disorders related to obesity [11].

The study was strengthened by randomization, intention-to-treat analysis, objective measures by arm-blinded staff, standardized measuring conditions, balanced participant allocation to each arm, 1-year follow-up, and qualitative feedback on instructors to assess whether weight loss may be instructor-dependent. In addition, the authors made an effort to mask their intention to test the effects of a mindfulness-enhanced intervention. They designed a rigorous active control intervention arm by controlling for attention, social support, expectations of benefit, diet-exercise guidelines, and elements of a mindfulness approach to stress management. An additional strength included a cost-analysis of adding mindfulness components. The generalizability of the results may be limited as the study population were predominantly white females and most had a bachelor’s degree. The study sample was also disproportionately menopausal women, a group that especially struggles with weight loss. This demographic factor may be responsible for the lack of significant weight loss. Other limitations of this study include participant dropout and variability between instructor styles, although the latter was explored in a secondary analysis of weight loss differences between instructors.

The researchers discussed how the active control intervention arm may have contributed to the lack of significant weight loss difference between groups. The researchers also highlighted that participants randomized to the mindfulness arm that were not interested in mindfulness practices may have benefitted less than those who were interested.  This combined with the modest diet and exercise components of the intervention may also explain the lack of significance in results. It may also explain why some outcomes were significant at earlier months but attenuated by 18 months. Future studies should assess incorporating more intense exercise and diet approaches, as well as continuous contact throughout the 18-month time period.

Applications for Clinical Practice

This study demonstrated that mindfulness components added to a diet-exercise program can be helpful in promoting metabolic changes but not necessarily weight loss. Since metabolic changes can be protective against morbidities (eg, type 2 diabetes), mindfulness can be a powerful and cost-effective approach within clinical practice. Mindfulness practices can also be easily implemented in various settings and with diverse populations. Future studies should explore adding mindfulness components to more intensive weight loss interventions. Providers and health care settings should consider incorporating mindfulness practices into weight management counseling and programs.

—Michelle J. Williamson and Katrina F. Mateo, MPH

Study Overview

Objective. To determine whether weight loss and cardiometabolic risk factors are improved when mindfulness training is added to a diet-exercise program.

Design. 2-arm randomized controlled trial.

Setting and participants. Study participants were recruited through fliers, newspaper advertisements, online postings, and referrals at University of California, San Francisco clinics, and were enrolled from July 2009 to February 2012. Inclusion criteria were body mass index (BMI) between 30 and 45.9, abdominal obesity (waist circumference > 102 cm for men and > 88 cm for women), and age 18 or older. Exclusion criteria were current involvement with diet program or diet mediation, diabetes mellitus, fasting glucose ≥ 126 mg/dL, or hemoglobin A1c (HbA1C) between 6.0% and 6.5% with abnormal oral glucose tolerance test. Participants were randomized in a 1:1 ratio to one of 2 weight loss program arms using a computer-generated randomization sequence.

Intervention. In both arms, participants received general diet and exercise guidelines prescribing healthy eating and frequent exercise delivered in 16 sessions lasting 2 to 2½ hours and one all-day session over 5.5 months. Participants in the mindfulness intervention additionally received mindfulness training for eating, physical activity, and stress management from mindfulness mediation instructors and a registered dietician. They also followed guidelines at home, which included practicing meditation for up to 30 minutes 6 days a week, mini-meditations, and eating mindfully. To control for the activities and attention inherent in the mindfulness arm (eg, social support, expectation of benefit, snacks provided during mindful eating exercises, at home practice), the control arm was an “active control” and  included additional nutritional and physical activity information, snacks, strength training, home activities, conversations about society and weight loss, and low-dose progressive muscle relaxation and cognitive-behavioral training. Active control materials were delivered by one of 3 registered dieticians.

Main outcomes measures. The primary outcome was 18-month weight change. Participants’ weight, height, blood pressure, and weight circumference were measured at baseline and 3, 6, 12, and 18 months between 8 am and 10 am. Measurements were taken under fasting conditions and by arm-blinded staff. Blood samples were taken to assess secondary outcome changes in glucose, lipid, HbA1C, insulin, and C-reactive protein. Researchers also collected anonymous qualitative feedback from participants and supervisors to do a secondary analysis assessing differences in effectiveness and helpfulness of mindfulness teachings among instructors.

Main results. Of the potential participants that contacted the study team in response to recruitment efforts (n = 1485), 216 were fully eligible based on criteria and a screening visit. Participants that consented to participate (n = 194) were randomized. Participants across both groups were predominantly female, of European ethnic origin, and similar in age: mindfulness group, 47.2 years (13.0) and active control group, 47.8 years (12.4). At baseline, the mindfulness and active control arms had average BMIs of 35.4 (3.5) and 35.6 (3.8), respectively. Baseline characteristics, session attendance, and 18-month retention were similar for both arms. Participants in the mindfulness arm reported completing 70% (2.1 hours per week, SD = 1.2) of the recommended meditation time and eating 57% (SD = 29) of meals mindfully.

Weight loss outcomes between groups favored the mindfulness arms, but results were not significant. The largest difference of –1.9 kg (95% CI –4.5 to 0.8; P = 0.17) was at 12 months. The difference persisted at 18 months with –1.7 kg (95% CI –4.7 to 1.2 kg; P = 0.24). The mindfulness arm lost 4.2 kg (95% CI –6.2 to 2.2 kg) while the active control arm lost 2.4 kg (95% CI –4.5 to –0.3 kg).

Cardiometabolic outcomes at 12 months showed group differences in fasting glucose that favored the mindfulness arm, –3.1 mg/dL (95% CI 26.3 to 0.1; P = 0.06), while there was a significant group difference at 18 months, –4.1 mg/dL (95% CI –7.3 to –0.9; P  = 0.01). Data at 18-months showed that normal glucose changed minimally in the mindfulness arm, –0.31 mg/dL (95% CI –2.5 to 1.9), but increased in the active control arm 3.8 mg/dL (95% CI 1.5 to 6.1). Other cardiometabolic outcomes (ie,  triglyceride/HDL ratio and triglycerides) showed significance at 12 months, favoring the mindfulness arm, but not at 18 months. Although not all were statistically significant, 9 of 11 outcomes favored the mindfulness arm at 18 months.

Significant interactions (P < 0.05) were found between arm and enrollment rounds categorized by mindfulness instructor on weight, BMI, fasting glucose, homeostatic homeostasis model assessment of insulin resistance (defined as [glucose x insulin/{40 × 33.25}]), and HbA1c, with a marginally significant effect for waist circumference (P = 0.08). Qualitative feedback on mindfulness instructors showed that in the group with a lowly rated instructor, participants lost less weight at 18 months (–2.0 kg [95% CI –4.7 to 0.7]), compared to participants in groups with highly rated instructors (–6.3 kg [95% CI –9.1 to –3.6]; P = 0.02). Similar trends followed for reductions in BMI and waist circumference.

Conclusions. With regard to weight loss outcomes, a mindfulness-enhanced diet-exercise program and an active control arm did not show substantial differences. Some evidence, however, suggests modest benefit of added mindfulness components, which may lead to long-term maintenance of fasting glucose levels and improved atherogenic lipid profiles.

Commentary

Mindfulness, or nonjudgmental focus on the present moment, has been utilized by many interventions targeted at self-regulated behavior [1]. Mindfulness interventions aim to promote healthy behavior changes by encouraging careful monitoring of behavior reactivity. Weight loss and weight loss maintenance have been of particular interest with this approach because mindfulness-based interventions may promote long-term maintenance of weight loss [2]. This maintenance is achieved through a focus on modifying health behaviors, rather than a focus on weight loss alone [3]. Mindfulness has been incorporated into weight loss interventions through yoga practices [4] and mindfulness meditation [5].

Several studies have explored the relationship between mindfulness and weight loss in various populations, highlighting mindfulness’s role in weight loss and behavior change. Most notably, mindfulness interventions have shown improvements in fasting glucose levels [6], psychological distress [7], self-efficacy, weight loss, eating behaviors, and physical activity [8–10]. Despite being well designed, this study by Daubenmier et al did not find significant changes in weight loss. However, secondary outcomes related to weight, metabolic, syndrome, and cardiovascular risk showed modest improvements with mindfulness. These results may correlate to previous findings showing that lifestyle changes many not result in weight loss but can reverse or reduce disorders related to obesity [11].

The study was strengthened by randomization, intention-to-treat analysis, objective measures by arm-blinded staff, standardized measuring conditions, balanced participant allocation to each arm, 1-year follow-up, and qualitative feedback on instructors to assess whether weight loss may be instructor-dependent. In addition, the authors made an effort to mask their intention to test the effects of a mindfulness-enhanced intervention. They designed a rigorous active control intervention arm by controlling for attention, social support, expectations of benefit, diet-exercise guidelines, and elements of a mindfulness approach to stress management. An additional strength included a cost-analysis of adding mindfulness components. The generalizability of the results may be limited as the study population were predominantly white females and most had a bachelor’s degree. The study sample was also disproportionately menopausal women, a group that especially struggles with weight loss. This demographic factor may be responsible for the lack of significant weight loss. Other limitations of this study include participant dropout and variability between instructor styles, although the latter was explored in a secondary analysis of weight loss differences between instructors.

The researchers discussed how the active control intervention arm may have contributed to the lack of significant weight loss difference between groups. The researchers also highlighted that participants randomized to the mindfulness arm that were not interested in mindfulness practices may have benefitted less than those who were interested.  This combined with the modest diet and exercise components of the intervention may also explain the lack of significance in results. It may also explain why some outcomes were significant at earlier months but attenuated by 18 months. Future studies should assess incorporating more intense exercise and diet approaches, as well as continuous contact throughout the 18-month time period.

Applications for Clinical Practice

This study demonstrated that mindfulness components added to a diet-exercise program can be helpful in promoting metabolic changes but not necessarily weight loss. Since metabolic changes can be protective against morbidities (eg, type 2 diabetes), mindfulness can be a powerful and cost-effective approach within clinical practice. Mindfulness practices can also be easily implemented in various settings and with diverse populations. Future studies should explore adding mindfulness components to more intensive weight loss interventions. Providers and health care settings should consider incorporating mindfulness practices into weight management counseling and programs.

—Michelle J. Williamson and Katrina F. Mateo, MPH

Study Overview

Objective. To examine the feasibility, acceptability and benefits of mindfulness meditation training in men with low-grade prostate cancer on active surveillance.

Design. Randomized controlled pilot trial.

Setting and participants. Participants were men with low-risk localized prostate cancer who were on an IRB-approved active surveillance protocol within a medium-sized community hospital system in suburban Chicago. Enrolled patients were randomized to the active intervention or a control condition where participants received a book on mindfulness but no specific instructions to read it.

Intervention. Patients in the intervention arm attended an 8-week mindfulness-based stress reduction intervention, consisting of weekly sessions lasting 2½ hours held at their local primary hospital. Sessions were conducted by a trained and experienced mindfulness instructor. The intervention also included a half day retreat near the end of the intervention period to practice the skills that were taught.

Main outcome measures. Main outcome measures were prostate cancer anxiety (measured using the 18-item Memorial Anxiety Scale for Prostate Cancer), uncertainty tolerance (measured using the 12-item Intolerance of Uncertainty Short Form), mindfulness (measured via the 15-item Mindful Attention Awareness Scale), and health-related quality of life (measured using 10-item PROMIS Global Health-10). Researchers also measured “posttraumatic growth” using the Posttraumatic Growth Inventory, a 21-item self-report scale used to assess growth or benefits after a specific traumatic life event, such as a diagnosis of cancer. Participants completed instruments at baseline, 8 weeks, 6 months, and 12 months. At 12 months they also complete a brief feasibility and acceptance survey.

Main results. Over a 3-year period, 115 men were approached to participate and 54 enrolled. 11 withdrew prior to randomization citing lack of time as the primary reason. Ultimately, 24 men were randomized to the mindfulness arm and 19 to control. Average age was 70 years and 95% were white. Over 90% had never previously meditated or had never meditated on a regular basis. There were no significant differences between enrollees and decliners on baseline clinical or sociodemographic variables, and there were no significant differences between mindfulness and control patients on sociodemographic or clinical variables or outcome measures.

Participants in the intervention group reported decreased prostate cancer anxiety at 6 months (P = 0.02, effect size ([ES] 0.30) and uncertainty intolerance at 12 months (P = 0.02, ES 0.32) and increased quality of life at 8 weeks (P = 0.05, ES 0.17), mindfulness at 8 weeks (P < 0.04, ES 0.35) and 12 months (P < 0.01, ES 0.17), and posttraumatic growth (P < 0.05 for all follow-up measurements). When measuring changes between the groups, the only outcome that was significant was posttraumatic growth (P = 0.01, ES 0.73). Written responses to the open-ended survey questions regarding participants’ experience with the course cited increased emotional regulation and self-awareness and positive health behavior change.

Conclusion. An 8-week mindfulness training is feasible and acceptable to men with prostate cancer on active surveillance and may help men cope more effectively with stress and anxiety related to their cancer experience.

Commentary

Prostate cancer is the most common nonskin malignancy in men. More than 180,000 men are diagnosed per year, with over 26,000 prostate cancer deaths annually [1]. The optimal approach to treating newly diagnosed prostate cancer can be variable, but for most patients with low-risk (Gleason score ≤ 6) localized prostate cancer, active surveillance is the recommended disease management strategy [2]. Despite the favorable prognosis of low-risk prostate cancer, men who choose active surveillance may experience anxiety and uncertainty, which can cause many to request definitive therapy even when there is no tumor progression [3].

Mindfulness-based meditation is a practice that is increasingly being investigated for a wide array of health conditions. Mindfulness has been defined as being intentionally aware of internal and external experiences that occur at the present moment, without judgment. Behavioral interventions such as mindfulness training may lessen anxiety related to uncertainty intolerance and help maintain patient engagement in active surveillance [4].

This small pilot study by Victorson et al evaluated an 8-week mindfulness meditation intervention intended to help men in active surveillance manage cancer-related uncertainty intolerance. They found the meditation training to be generally feasible and acceptable among participants. Men in the active intervention demonstrated statistically significant within-group changes that included decreased prostate cancer anxiety and increased mental well-being and posttraumatic growth, but there were no differences between groups except for posttraumatic growth. Interestingly, the control group also reported a moderate increase in mindfulness at 12 months, which was found (in an exploratory follow-up analysis) to be unrelated to reading the mindfulness book they were given (eg, those who did not open the book had higher average mindfulness scores than those who read the book from cover to cover).

Limitations of the study include the small sample size and lack of diversity among the participants, who were 95% white and well educated. In addition, the response rate prior to randomization was low: out of 115 men approached, 43 were ultimately randomized. Retention rates at 12 months were similar: 71% for intervention and 74% for control.

Applications for Clinical Practice

A growing body of research demonstrates that mindfulness practice may aid in improving psychological well-being. Further research is necessary before a clinical recommendation can be offered regarding use of mindfulness instruction to alleviate anxiety in men with low-grade prostate cancer being managed with active surveillance.

Study Overview

Objective. To examine the feasibility, acceptability and benefits of mindfulness meditation training in men with low-grade prostate cancer on active surveillance.

Design. Randomized controlled pilot trial.

Setting and participants. Participants were men with low-risk localized prostate cancer who were on an IRB-approved active surveillance protocol within a medium-sized community hospital system in suburban Chicago. Enrolled patients were randomized to the active intervention or a control condition where participants received a book on mindfulness but no specific instructions to read it.

Intervention. Patients in the intervention arm attended an 8-week mindfulness-based stress reduction intervention, consisting of weekly sessions lasting 2½ hours held at their local primary hospital. Sessions were conducted by a trained and experienced mindfulness instructor. The intervention also included a half day retreat near the end of the intervention period to practice the skills that were taught.

Main outcome measures. Main outcome measures were prostate cancer anxiety (measured using the 18-item Memorial Anxiety Scale for Prostate Cancer), uncertainty tolerance (measured using the 12-item Intolerance of Uncertainty Short Form), mindfulness (measured via the 15-item Mindful Attention Awareness Scale), and health-related quality of life (measured using 10-item PROMIS Global Health-10). Researchers also measured “posttraumatic growth” using the Posttraumatic Growth Inventory, a 21-item self-report scale used to assess growth or benefits after a specific traumatic life event, such as a diagnosis of cancer. Participants completed instruments at baseline, 8 weeks, 6 months, and 12 months. At 12 months they also complete a brief feasibility and acceptance survey.

Main results. Over a 3-year period, 115 men were approached to participate and 54 enrolled. 11 withdrew prior to randomization citing lack of time as the primary reason. Ultimately, 24 men were randomized to the mindfulness arm and 19 to control. Average age was 70 years and 95% were white. Over 90% had never previously meditated or had never meditated on a regular basis. There were no significant differences between enrollees and decliners on baseline clinical or sociodemographic variables, and there were no significant differences between mindfulness and control patients on sociodemographic or clinical variables or outcome measures.

Participants in the intervention group reported decreased prostate cancer anxiety at 6 months (P = 0.02, effect size ([ES] 0.30) and uncertainty intolerance at 12 months (P = 0.02, ES 0.32) and increased quality of life at 8 weeks (P = 0.05, ES 0.17), mindfulness at 8 weeks (P < 0.04, ES 0.35) and 12 months (P < 0.01, ES 0.17), and posttraumatic growth (P < 0.05 for all follow-up measurements). When measuring changes between the groups, the only outcome that was significant was posttraumatic growth (P = 0.01, ES 0.73). Written responses to the open-ended survey questions regarding participants’ experience with the course cited increased emotional regulation and self-awareness and positive health behavior change.

Conclusion. An 8-week mindfulness training is feasible and acceptable to men with prostate cancer on active surveillance and may help men cope more effectively with stress and anxiety related to their cancer experience.

Commentary

Prostate cancer is the most common nonskin malignancy in men. More than 180,000 men are diagnosed per year, with over 26,000 prostate cancer deaths annually [1]. The optimal approach to treating newly diagnosed prostate cancer can be variable, but for most patients with low-risk (Gleason score ≤ 6) localized prostate cancer, active surveillance is the recommended disease management strategy [2]. Despite the favorable prognosis of low-risk prostate cancer, men who choose active surveillance may experience anxiety and uncertainty, which can cause many to request definitive therapy even when there is no tumor progression [3].

Mindfulness-based meditation is a practice that is increasingly being investigated for a wide array of health conditions. Mindfulness has been defined as being intentionally aware of internal and external experiences that occur at the present moment, without judgment. Behavioral interventions such as mindfulness training may lessen anxiety related to uncertainty intolerance and help maintain patient engagement in active surveillance [4].

This small pilot study by Victorson et al evaluated an 8-week mindfulness meditation intervention intended to help men in active surveillance manage cancer-related uncertainty intolerance. They found the meditation training to be generally feasible and acceptable among participants. Men in the active intervention demonstrated statistically significant within-group changes that included decreased prostate cancer anxiety and increased mental well-being and posttraumatic growth, but there were no differences between groups except for posttraumatic growth. Interestingly, the control group also reported a moderate increase in mindfulness at 12 months, which was found (in an exploratory follow-up analysis) to be unrelated to reading the mindfulness book they were given (eg, those who did not open the book had higher average mindfulness scores than those who read the book from cover to cover).

Limitations of the study include the small sample size and lack of diversity among the participants, who were 95% white and well educated. In addition, the response rate prior to randomization was low: out of 115 men approached, 43 were ultimately randomized. Retention rates at 12 months were similar: 71% for intervention and 74% for control.

Applications for Clinical Practice

A growing body of research demonstrates that mindfulness practice may aid in improving psychological well-being. Further research is necessary before a clinical recommendation can be offered regarding use of mindfulness instruction to alleviate anxiety in men with low-grade prostate cancer being managed with active surveillance.

Study Overview

Objective. To examine the feasibility, acceptability and benefits of mindfulness meditation training in men with low-grade prostate cancer on active surveillance.

Design. Randomized controlled pilot trial.

Setting and participants. Participants were men with low-risk localized prostate cancer who were on an IRB-approved active surveillance protocol within a medium-sized community hospital system in suburban Chicago. Enrolled patients were randomized to the active intervention or a control condition where participants received a book on mindfulness but no specific instructions to read it.

Intervention. Patients in the intervention arm attended an 8-week mindfulness-based stress reduction intervention, consisting of weekly sessions lasting 2½ hours held at their local primary hospital. Sessions were conducted by a trained and experienced mindfulness instructor. The intervention also included a half day retreat near the end of the intervention period to practice the skills that were taught.

Main outcome measures. Main outcome measures were prostate cancer anxiety (measured using the 18-item Memorial Anxiety Scale for Prostate Cancer), uncertainty tolerance (measured using the 12-item Intolerance of Uncertainty Short Form), mindfulness (measured via the 15-item Mindful Attention Awareness Scale), and health-related quality of life (measured using 10-item PROMIS Global Health-10). Researchers also measured “posttraumatic growth” using the Posttraumatic Growth Inventory, a 21-item self-report scale used to assess growth or benefits after a specific traumatic life event, such as a diagnosis of cancer. Participants completed instruments at baseline, 8 weeks, 6 months, and 12 months. At 12 months they also complete a brief feasibility and acceptance survey.

Main results. Over a 3-year period, 115 men were approached to participate and 54 enrolled. 11 withdrew prior to randomization citing lack of time as the primary reason. Ultimately, 24 men were randomized to the mindfulness arm and 19 to control. Average age was 70 years and 95% were white. Over 90% had never previously meditated or had never meditated on a regular basis. There were no significant differences between enrollees and decliners on baseline clinical or sociodemographic variables, and there were no significant differences between mindfulness and control patients on sociodemographic or clinical variables or outcome measures.

Participants in the intervention group reported decreased prostate cancer anxiety at 6 months (P = 0.02, effect size ([ES] 0.30) and uncertainty intolerance at 12 months (P = 0.02, ES 0.32) and increased quality of life at 8 weeks (P = 0.05, ES 0.17), mindfulness at 8 weeks (P < 0.04, ES 0.35) and 12 months (P < 0.01, ES 0.17), and posttraumatic growth (P < 0.05 for all follow-up measurements). When measuring changes between the groups, the only outcome that was significant was posttraumatic growth (P = 0.01, ES 0.73). Written responses to the open-ended survey questions regarding participants’ experience with the course cited increased emotional regulation and self-awareness and positive health behavior change.

Conclusion. An 8-week mindfulness training is feasible and acceptable to men with prostate cancer on active surveillance and may help men cope more effectively with stress and anxiety related to their cancer experience.

Commentary

Prostate cancer is the most common nonskin malignancy in men. More than 180,000 men are diagnosed per year, with over 26,000 prostate cancer deaths annually [1]. The optimal approach to treating newly diagnosed prostate cancer can be variable, but for most patients with low-risk (Gleason score ≤ 6) localized prostate cancer, active surveillance is the recommended disease management strategy [2]. Despite the favorable prognosis of low-risk prostate cancer, men who choose active surveillance may experience anxiety and uncertainty, which can cause many to request definitive therapy even when there is no tumor progression [3].

Mindfulness-based meditation is a practice that is increasingly being investigated for a wide array of health conditions. Mindfulness has been defined as being intentionally aware of internal and external experiences that occur at the present moment, without judgment. Behavioral interventions such as mindfulness training may lessen anxiety related to uncertainty intolerance and help maintain patient engagement in active surveillance [4].

This small pilot study by Victorson et al evaluated an 8-week mindfulness meditation intervention intended to help men in active surveillance manage cancer-related uncertainty intolerance. They found the meditation training to be generally feasible and acceptable among participants. Men in the active intervention demonstrated statistically significant within-group changes that included decreased prostate cancer anxiety and increased mental well-being and posttraumatic growth, but there were no differences between groups except for posttraumatic growth. Interestingly, the control group also reported a moderate increase in mindfulness at 12 months, which was found (in an exploratory follow-up analysis) to be unrelated to reading the mindfulness book they were given (eg, those who did not open the book had higher average mindfulness scores than those who read the book from cover to cover).

Limitations of the study include the small sample size and lack of diversity among the participants, who were 95% white and well educated. In addition, the response rate prior to randomization was low: out of 115 men approached, 43 were ultimately randomized. Retention rates at 12 months were similar: 71% for intervention and 74% for control.

Applications for Clinical Practice

A growing body of research demonstrates that mindfulness practice may aid in improving psychological well-being. Further research is necessary before a clinical recommendation can be offered regarding use of mindfulness instruction to alleviate anxiety in men with low-grade prostate cancer being managed with active surveillance.

Study Overview

Objective. To compare several behavioral strategies for weight gain prevention in young adults.

Study design. Randomized clinical trial.

Setting and participants. The study took place at 2 U.S. academic centers between 2010 and 2016. Participants were recruited using email and postal mailings if they were 18–35 years old, had a body mass index (BMI) between 21 and 30.9 (ie, they ranged from normal body weight to class I obesity), spoke English, had internet access, and did not have contraindications to participating in a behavioral weight management intervention (eg, eating disorders). Once recruited, participants were block randomized, stratified by site, sex, and ethnic group, in to 1 of 3 study arms. The control arm of the study consisted of a single in-person meeting where behavioral strategies to prevent weight gain were discussed, as well as quarterly newsletters and personalized reports on interim weight data during follow-up.

Intervention. There were 2 intervention arms in the study. Both intervention groups had 10 in-person group-based visits over the initial 4 months of the intervention, at which strategies to prevent weight gain were discussed. Additionally they received annual invitations to participate in online refresher courses and the same newsletter frequency and content as the control group. Advice to the 2 intervention groups differed, however. Those in the “small changes” group were advised to decrease caloric intake by about 100 kcal per day in order to prevent weight gain. Additionally they were given pedometers, with a goal of increasing their daily step counts by about 2000. In the “large changes” group, participants were given lower calorie targets and more aggressive physical activity goals, with a goal of producing weight loss over the first 4 months of follow-up (2.3 kg for those with normal baseline BMI, and 4.5 kg if overweight or obese at baseline). Participants in all groups were encouraged to engage in self-monitoring behaviors such as daily weighing, and to report these weights to study staff by email, text, or on the web. Aside from pre-specified study follow-up assessments, most follow-up beyond the initial 4 month “small” or “large” changes phase was done using email or web-based intervention.

Main outcome measures. All participants were scheduled for follow-up assessments at 4 months, 1 year, and 2 years, with some early participants having additional follow-ups at 3 and 4 years. The primary outcome of interest was change in weight from baseline through follow-up, with additional outcome measures including the proportion in each group who gained at least 0.45 kg, or developed obesity. Additionally, the investigators did a thorough evaluation of intervention implementation and delivery. Weight change was modeled using mixed effects linear models, adjusting for clinic site. They corrected for multiple measures using Bonferroni adjustment to minimize the risk of type I error and used multiple imputation to examine the impact of missing data on their results. Pre-specified subgroup comparisons between several groups of patients were conducted—those in the normal weight vs. overweight category at baseline, those younger vs. older than age 25 at baseline, and men vs. women.

Results. 599 participants were randomized to the control (n = 202), small changes (n = 200), or large changes groups (n = 197), with no significant differences between groups in terms of measured baseline characteristics. The majority of participants were women (78%) and non-Hispanic white (73%). Mean (SD) baseline age was 28.2 (4.4) years and BMI was 25.4 (2.6) kg/m². The group as a whole was highly educated—between 77% and 82% had college degrees. The series of 10 intervention sessions in the first 4 months was very well-attended (87% attendance on average for large changes group, 86% for small changes group), and by 4 months of follow-up, a majority of participants in both intervention groups endorsed the behavior of daily self-weighing (75% in large changes, 72% in small changes).

Both intervention groups had statistically significant weight losses compared to control (average weight change in control +0.3 kg, in small change –0.6 kg, and in large change –2.4 kg, over an average of 3 years), with large change participants also having significantly greater average weight loss in follow-up than small change participants. Significantly fewer participants in the intervention groups went on to develop obesity than in the control group (16.9% incidence in control, vs. 7.9% incidence in small changes [P = 0.002] and 8.6% in large changes [P = 0.02]). Importantly, the trajectories of weight gain (or regain) after the initial 4-month intervention differed between the small and large change groups, with small change participants experiencing a more gradual rate of gain throughout follow-up, versus a steeper rate of gain in the large changes group, such that the groups were at very similar weights by the final time point. The investigators did not observe any differences in effect between subgroups according to participant baseline BMI, sex, age, or race.

Conclusion. The authors conclude that these scalable small- and large-change interventions reduced longer-term weight gain and even promoted weight loss in a group of young adults, with the large-change intervention having a greater impact on weight than the small-change intervention.

Commentary

Treatment of obesity is difficult, leading to frustration for many patients and clinicians. Although it is often possible to help patients lose weight with tools such as low-calorie diets and increased physical activity, the long-term maintenance of weight loss is quite challenging. There is a growing awareness that the difficulty in maintaining weight loss has strong physiologic underpinnings. The human body has complex energy regulatory systems that may oppose weight loss by lowering metabolic rate, increasing hunger cues, and limiting satiety cues, when faced with energy restriction or weight loss [1,2].

In order to decrease the number of patients who ultimately require treatment for obesity, an alternative approach may be to try to prevent weight gain in the first place. Young adults in the U.S. tend to gain weight steadily over time, yet this insidious pattern is unlikely to be addressed by physicians [3]. Given that gradual weight gain seems to be the norm for most young adults, it may be beneficial for primary care providers to advise all young adult patients to make small behavioral changes in order to prevent the onset of overweight or obesity. Preventing weight gain is an attractive approach for broad application because it may require lower intensity programs, and less behavioral commitment from patients, compared to what is required for weight loss [4].

In this randomized trial, Wing et al investigated several relatively low-intensity approaches for weight gain prevention. Strengths of the study include aspects of the design and analysis, including its randomized nature, the relatively long follow-up period, the use of multiple imputation to address missing data, and the use of statistical methods to account for the large number of comparisons made between groups over time (Bonferroni correction). More importantly, however, this study represents an important innovation in how physicians might think about obesity, with a shift toward prevention rather than treatment. Historically, many obesity prevention efforts have fallen in the domain of public health or population-level interventions, and it may be the case that physicians have felt they did not really have a role in prevention. On the other hand, doctors who have engaged in obesity treatment—trying to help patients lose weight—may have felt that they lacked the resources or training needed to implement successful programs to promote long-term weight loss. By testing several lower-intensity strategies for weight gain prevention, this study sheds light on what could possibly be a new role for primary care providers or health care systems who care for otherwise healthy young adults. As the authors point out, the methods they employed could also be easily scaled or disseminated using public health approaches and community organizations.

In addition to addressing an important topic, this study relied on intervention methods that would be relatively easy to replicate in clinical practice or in community settings. Aside from the initial 4-month intervention, which involved 10 face-to-face group sessions (which were very well attended by participants), the remainder of the ~3 year follow-up consisted mostly of contact that took place electronically using email and/or text messaging. These modes of communication align well with the move toward electronic health records (eg, e-visits) and are probably ideally suited for young adults, who as a group rely heavily on these methods of communication.

The study has several limitations, most of which are addressed by the authors in the discussion section of the paper. As with most studies of behavioral weight interventions, the majority of participants in this study were women, with relatively few racial and ethnic minorities. Furthermore this was a highly educated group of participants and it is unclear whether these results would generalize to a more diverse clinical population with fewer resources or lower health literacy. Given that the control arm of the study experienced less weight gain over time than would be expected based on population averages, it could be that the participants in this study were a select group of individuals who were more motivated around preventing long-term health problems than a general clinical population. One additional point of possible concern is that, while participants in the “large changes” group did, as per the design, lose weight at the beginning of the trial, they also went on to regain much of that weight and experienced a steeper trajectory of overall gain during follow-up compared to the “small changes” group, so that the 2 intervention groups were not statistically different from each other in terms of overall weight change from baseline by 2 years. Therefore, whether the “large changes” approach is truly more beneficial for long-term obesity prevention than the more modest “small changes” approach is not entirely clear from this study.

Applications for Clinical Practice

The identification of young adults who are gaining weight, but who are not yet obese, represents an opportunity for providers and health care systems. Efforts to promote modest dietary and physical activity changes in this population may prevent obesity, and may be achievable even in busy clinical practice settings. Whether weight-gain prevention programs should include an attempt to first foster a small amount of weight loss as a “buffer” against later gains is still not entirely clear.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To compare several behavioral strategies for weight gain prevention in young adults.

Study design. Randomized clinical trial.

Setting and participants. The study took place at 2 U.S. academic centers between 2010 and 2016. Participants were recruited using email and postal mailings if they were 18–35 years old, had a body mass index (BMI) between 21 and 30.9 (ie, they ranged from normal body weight to class I obesity), spoke English, had internet access, and did not have contraindications to participating in a behavioral weight management intervention (eg, eating disorders). Once recruited, participants were block randomized, stratified by site, sex, and ethnic group, in to 1 of 3 study arms. The control arm of the study consisted of a single in-person meeting where behavioral strategies to prevent weight gain were discussed, as well as quarterly newsletters and personalized reports on interim weight data during follow-up.

Intervention. There were 2 intervention arms in the study. Both intervention groups had 10 in-person group-based visits over the initial 4 months of the intervention, at which strategies to prevent weight gain were discussed. Additionally they received annual invitations to participate in online refresher courses and the same newsletter frequency and content as the control group. Advice to the 2 intervention groups differed, however. Those in the “small changes” group were advised to decrease caloric intake by about 100 kcal per day in order to prevent weight gain. Additionally they were given pedometers, with a goal of increasing their daily step counts by about 2000. In the “large changes” group, participants were given lower calorie targets and more aggressive physical activity goals, with a goal of producing weight loss over the first 4 months of follow-up (2.3 kg for those with normal baseline BMI, and 4.5 kg if overweight or obese at baseline). Participants in all groups were encouraged to engage in self-monitoring behaviors such as daily weighing, and to report these weights to study staff by email, text, or on the web. Aside from pre-specified study follow-up assessments, most follow-up beyond the initial 4 month “small” or “large” changes phase was done using email or web-based intervention.

Main outcome measures. All participants were scheduled for follow-up assessments at 4 months, 1 year, and 2 years, with some early participants having additional follow-ups at 3 and 4 years. The primary outcome of interest was change in weight from baseline through follow-up, with additional outcome measures including the proportion in each group who gained at least 0.45 kg, or developed obesity. Additionally, the investigators did a thorough evaluation of intervention implementation and delivery. Weight change was modeled using mixed effects linear models, adjusting for clinic site. They corrected for multiple measures using Bonferroni adjustment to minimize the risk of type I error and used multiple imputation to examine the impact of missing data on their results. Pre-specified subgroup comparisons between several groups of patients were conducted—those in the normal weight vs. overweight category at baseline, those younger vs. older than age 25 at baseline, and men vs. women.

Results. 599 participants were randomized to the control (n = 202), small changes (n = 200), or large changes groups (n = 197), with no significant differences between groups in terms of measured baseline characteristics. The majority of participants were women (78%) and non-Hispanic white (73%). Mean (SD) baseline age was 28.2 (4.4) years and BMI was 25.4 (2.6) kg/m². The group as a whole was highly educated—between 77% and 82% had college degrees. The series of 10 intervention sessions in the first 4 months was very well-attended (87% attendance on average for large changes group, 86% for small changes group), and by 4 months of follow-up, a majority of participants in both intervention groups endorsed the behavior of daily self-weighing (75% in large changes, 72% in small changes).

Both intervention groups had statistically significant weight losses compared to control (average weight change in control +0.3 kg, in small change –0.6 kg, and in large change –2.4 kg, over an average of 3 years), with large change participants also having significantly greater average weight loss in follow-up than small change participants. Significantly fewer participants in the intervention groups went on to develop obesity than in the control group (16.9% incidence in control, vs. 7.9% incidence in small changes [P = 0.002] and 8.6% in large changes [P = 0.02]). Importantly, the trajectories of weight gain (or regain) after the initial 4-month intervention differed between the small and large change groups, with small change participants experiencing a more gradual rate of gain throughout follow-up, versus a steeper rate of gain in the large changes group, such that the groups were at very similar weights by the final time point. The investigators did not observe any differences in effect between subgroups according to participant baseline BMI, sex, age, or race.

Conclusion. The authors conclude that these scalable small- and large-change interventions reduced longer-term weight gain and even promoted weight loss in a group of young adults, with the large-change intervention having a greater impact on weight than the small-change intervention.

Commentary

Treatment of obesity is difficult, leading to frustration for many patients and clinicians. Although it is often possible to help patients lose weight with tools such as low-calorie diets and increased physical activity, the long-term maintenance of weight loss is quite challenging. There is a growing awareness that the difficulty in maintaining weight loss has strong physiologic underpinnings. The human body has complex energy regulatory systems that may oppose weight loss by lowering metabolic rate, increasing hunger cues, and limiting satiety cues, when faced with energy restriction or weight loss [1,2].

In order to decrease the number of patients who ultimately require treatment for obesity, an alternative approach may be to try to prevent weight gain in the first place. Young adults in the U.S. tend to gain weight steadily over time, yet this insidious pattern is unlikely to be addressed by physicians [3]. Given that gradual weight gain seems to be the norm for most young adults, it may be beneficial for primary care providers to advise all young adult patients to make small behavioral changes in order to prevent the onset of overweight or obesity. Preventing weight gain is an attractive approach for broad application because it may require lower intensity programs, and less behavioral commitment from patients, compared to what is required for weight loss [4].

In this randomized trial, Wing et al investigated several relatively low-intensity approaches for weight gain prevention. Strengths of the study include aspects of the design and analysis, including its randomized nature, the relatively long follow-up period, the use of multiple imputation to address missing data, and the use of statistical methods to account for the large number of comparisons made between groups over time (Bonferroni correction). More importantly, however, this study represents an important innovation in how physicians might think about obesity, with a shift toward prevention rather than treatment. Historically, many obesity prevention efforts have fallen in the domain of public health or population-level interventions, and it may be the case that physicians have felt they did not really have a role in prevention. On the other hand, doctors who have engaged in obesity treatment—trying to help patients lose weight—may have felt that they lacked the resources or training needed to implement successful programs to promote long-term weight loss. By testing several lower-intensity strategies for weight gain prevention, this study sheds light on what could possibly be a new role for primary care providers or health care systems who care for otherwise healthy young adults. As the authors point out, the methods they employed could also be easily scaled or disseminated using public health approaches and community organizations.

In addition to addressing an important topic, this study relied on intervention methods that would be relatively easy to replicate in clinical practice or in community settings. Aside from the initial 4-month intervention, which involved 10 face-to-face group sessions (which were very well attended by participants), the remainder of the ~3 year follow-up consisted mostly of contact that took place electronically using email and/or text messaging. These modes of communication align well with the move toward electronic health records (eg, e-visits) and are probably ideally suited for young adults, who as a group rely heavily on these methods of communication.

The study has several limitations, most of which are addressed by the authors in the discussion section of the paper. As with most studies of behavioral weight interventions, the majority of participants in this study were women, with relatively few racial and ethnic minorities. Furthermore this was a highly educated group of participants and it is unclear whether these results would generalize to a more diverse clinical population with fewer resources or lower health literacy. Given that the control arm of the study experienced less weight gain over time than would be expected based on population averages, it could be that the participants in this study were a select group of individuals who were more motivated around preventing long-term health problems than a general clinical population. One additional point of possible concern is that, while participants in the “large changes” group did, as per the design, lose weight at the beginning of the trial, they also went on to regain much of that weight and experienced a steeper trajectory of overall gain during follow-up compared to the “small changes” group, so that the 2 intervention groups were not statistically different from each other in terms of overall weight change from baseline by 2 years. Therefore, whether the “large changes” approach is truly more beneficial for long-term obesity prevention than the more modest “small changes” approach is not entirely clear from this study.

Applications for Clinical Practice

The identification of young adults who are gaining weight, but who are not yet obese, represents an opportunity for providers and health care systems. Efforts to promote modest dietary and physical activity changes in this population may prevent obesity, and may be achievable even in busy clinical practice settings. Whether weight-gain prevention programs should include an attempt to first foster a small amount of weight loss as a “buffer” against later gains is still not entirely clear.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To compare several behavioral strategies for weight gain prevention in young adults.

Study design. Randomized clinical trial.

Setting and participants. The study took place at 2 U.S. academic centers between 2010 and 2016. Participants were recruited using email and postal mailings if they were 18–35 years old, had a body mass index (BMI) between 21 and 30.9 (ie, they ranged from normal body weight to class I obesity), spoke English, had internet access, and did not have contraindications to participating in a behavioral weight management intervention (eg, eating disorders). Once recruited, participants were block randomized, stratified by site, sex, and ethnic group, in to 1 of 3 study arms. The control arm of the study consisted of a single in-person meeting where behavioral strategies to prevent weight gain were discussed, as well as quarterly newsletters and personalized reports on interim weight data during follow-up.

Intervention. There were 2 intervention arms in the study. Both intervention groups had 10 in-person group-based visits over the initial 4 months of the intervention, at which strategies to prevent weight gain were discussed. Additionally they received annual invitations to participate in online refresher courses and the same newsletter frequency and content as the control group. Advice to the 2 intervention groups differed, however. Those in the “small changes” group were advised to decrease caloric intake by about 100 kcal per day in order to prevent weight gain. Additionally they were given pedometers, with a goal of increasing their daily step counts by about 2000. In the “large changes” group, participants were given lower calorie targets and more aggressive physical activity goals, with a goal of producing weight loss over the first 4 months of follow-up (2.3 kg for those with normal baseline BMI, and 4.5 kg if overweight or obese at baseline). Participants in all groups were encouraged to engage in self-monitoring behaviors such as daily weighing, and to report these weights to study staff by email, text, or on the web. Aside from pre-specified study follow-up assessments, most follow-up beyond the initial 4 month “small” or “large” changes phase was done using email or web-based intervention.

Main outcome measures. All participants were scheduled for follow-up assessments at 4 months, 1 year, and 2 years, with some early participants having additional follow-ups at 3 and 4 years. The primary outcome of interest was change in weight from baseline through follow-up, with additional outcome measures including the proportion in each group who gained at least 0.45 kg, or developed obesity. Additionally, the investigators did a thorough evaluation of intervention implementation and delivery. Weight change was modeled using mixed effects linear models, adjusting for clinic site. They corrected for multiple measures using Bonferroni adjustment to minimize the risk of type I error and used multiple imputation to examine the impact of missing data on their results. Pre-specified subgroup comparisons between several groups of patients were conducted—those in the normal weight vs. overweight category at baseline, those younger vs. older than age 25 at baseline, and men vs. women.

Results. 599 participants were randomized to the control (n = 202), small changes (n = 200), or large changes groups (n = 197), with no significant differences between groups in terms of measured baseline characteristics. The majority of participants were women (78%) and non-Hispanic white (73%). Mean (SD) baseline age was 28.2 (4.4) years and BMI was 25.4 (2.6) kg/m². The group as a whole was highly educated—between 77% and 82% had college degrees. The series of 10 intervention sessions in the first 4 months was very well-attended (87% attendance on average for large changes group, 86% for small changes group), and by 4 months of follow-up, a majority of participants in both intervention groups endorsed the behavior of daily self-weighing (75% in large changes, 72% in small changes).

Both intervention groups had statistically significant weight losses compared to control (average weight change in control +0.3 kg, in small change –0.6 kg, and in large change –2.4 kg, over an average of 3 years), with large change participants also having significantly greater average weight loss in follow-up than small change participants. Significantly fewer participants in the intervention groups went on to develop obesity than in the control group (16.9% incidence in control, vs. 7.9% incidence in small changes [P = 0.002] and 8.6% in large changes [P = 0.02]). Importantly, the trajectories of weight gain (or regain) after the initial 4-month intervention differed between the small and large change groups, with small change participants experiencing a more gradual rate of gain throughout follow-up, versus a steeper rate of gain in the large changes group, such that the groups were at very similar weights by the final time point. The investigators did not observe any differences in effect between subgroups according to participant baseline BMI, sex, age, or race.

Conclusion. The authors conclude that these scalable small- and large-change interventions reduced longer-term weight gain and even promoted weight loss in a group of young adults, with the large-change intervention having a greater impact on weight than the small-change intervention.

Commentary

Treatment of obesity is difficult, leading to frustration for many patients and clinicians. Although it is often possible to help patients lose weight with tools such as low-calorie diets and increased physical activity, the long-term maintenance of weight loss is quite challenging. There is a growing awareness that the difficulty in maintaining weight loss has strong physiologic underpinnings. The human body has complex energy regulatory systems that may oppose weight loss by lowering metabolic rate, increasing hunger cues, and limiting satiety cues, when faced with energy restriction or weight loss [1,2].

In order to decrease the number of patients who ultimately require treatment for obesity, an alternative approach may be to try to prevent weight gain in the first place. Young adults in the U.S. tend to gain weight steadily over time, yet this insidious pattern is unlikely to be addressed by physicians [3]. Given that gradual weight gain seems to be the norm for most young adults, it may be beneficial for primary care providers to advise all young adult patients to make small behavioral changes in order to prevent the onset of overweight or obesity. Preventing weight gain is an attractive approach for broad application because it may require lower intensity programs, and less behavioral commitment from patients, compared to what is required for weight loss [4].

In this randomized trial, Wing et al investigated several relatively low-intensity approaches for weight gain prevention. Strengths of the study include aspects of the design and analysis, including its randomized nature, the relatively long follow-up period, the use of multiple imputation to address missing data, and the use of statistical methods to account for the large number of comparisons made between groups over time (Bonferroni correction). More importantly, however, this study represents an important innovation in how physicians might think about obesity, with a shift toward prevention rather than treatment. Historically, many obesity prevention efforts have fallen in the domain of public health or population-level interventions, and it may be the case that physicians have felt they did not really have a role in prevention. On the other hand, doctors who have engaged in obesity treatment—trying to help patients lose weight—may have felt that they lacked the resources or training needed to implement successful programs to promote long-term weight loss. By testing several lower-intensity strategies for weight gain prevention, this study sheds light on what could possibly be a new role for primary care providers or health care systems who care for otherwise healthy young adults. As the authors point out, the methods they employed could also be easily scaled or disseminated using public health approaches and community organizations.

In addition to addressing an important topic, this study relied on intervention methods that would be relatively easy to replicate in clinical practice or in community settings. Aside from the initial 4-month intervention, which involved 10 face-to-face group sessions (which were very well attended by participants), the remainder of the ~3 year follow-up consisted mostly of contact that took place electronically using email and/or text messaging. These modes of communication align well with the move toward electronic health records (eg, e-visits) and are probably ideally suited for young adults, who as a group rely heavily on these methods of communication.

The study has several limitations, most of which are addressed by the authors in the discussion section of the paper. As with most studies of behavioral weight interventions, the majority of participants in this study were women, with relatively few racial and ethnic minorities. Furthermore this was a highly educated group of participants and it is unclear whether these results would generalize to a more diverse clinical population with fewer resources or lower health literacy. Given that the control arm of the study experienced less weight gain over time than would be expected based on population averages, it could be that the participants in this study were a select group of individuals who were more motivated around preventing long-term health problems than a general clinical population. One additional point of possible concern is that, while participants in the “large changes” group did, as per the design, lose weight at the beginning of the trial, they also went on to regain much of that weight and experienced a steeper trajectory of overall gain during follow-up compared to the “small changes” group, so that the 2 intervention groups were not statistically different from each other in terms of overall weight change from baseline by 2 years. Therefore, whether the “large changes” approach is truly more beneficial for long-term obesity prevention than the more modest “small changes” approach is not entirely clear from this study.

Applications for Clinical Practice

The identification of young adults who are gaining weight, but who are not yet obese, represents an opportunity for providers and health care systems. Efforts to promote modest dietary and physical activity changes in this population may prevent obesity, and may be achievable even in busy clinical practice settings. Whether weight-gain prevention programs should include an attempt to first foster a small amount of weight loss as a “buffer” against later gains is still not entirely clear.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To describe the feasibility of a primary care–based group visit model focused on advance care planning.

Design. Qualitative study.

Setting and participants. Participants were patients attending the Senior Clinic, a patient-centered medical home at the University of Colorado Hospital in Aurora, CO. Patients had to be aged 65, English speakers, and receiving primary care at the Clinic. Participants could be referred by their primary care clinician, a partner or friend, or self-refer in response to flyers. Clinicians were not asked to prioritize patients with poor health status or known end-of-life needs.

Intervention. Groups of patients met for 2 sessions (1 month apart), each 2 hours in length, facilitated by a geriatrician and a social worker. About 1 hour was spent on discussion of advance care planning concepts, including sharing experiences and considering values. Other time in the session was for introductions/rapport building, individual goal setting, and optional completion or directives and/or individual clinical visits. Facilitators were supported by a Facilitator’s Communication Guide and used educational materials and handouts with the group.

Main outcome measures. Researchers used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the project.

Main results. Patients were referred by 10 out of 11 clinicians. Of 80 patients approached, 32 participated in 5 group visit cohorts (40% participation rate) and 27 participated in both sessions (84% retention rate). Mean age was 79 years; 59% of participants were female and 72% white. Most evaluated the group visit as better than usual clinic visits for discussing advance care planning. Patients reported increases in detailed advance care planning conversations after participating (19% to 41%, P = 0.02). Patients were willing to share personal values and challenges related to advance care planning and they initiated discussions about a broad range of relevant topics.

Conclusion. A group visit to facilitate discussions about advance care planning and increase patient engagement is feasible. This model warrants further evaluation for effectiveness in improving advance care planning outcomes for patients, clinicians, and the system.

Commentary

An understanding of patients’ care goals is an essential element of high-quality care, allowing clinicians to align the care provided with what is most important to the patient [1]. Existing evidence does not support the commonly held belief that communication about end-of-life issues increases patient distress [1]. Early discussions about goals of care are associated with better quality of life, reduced use of nonbeneficial medical care near death, enhanced goal-consistent care, positive family outcomes, and reduced costs; however, significant barriers to having advance care planning discussions exist [2], including communication issues and lack of appropriate counseling by clinicians in primary care. Clinicians cite limited time and lack of clinic-based support as factors that impede discussions with patients about advance care planning.

New models are being developed in order to facilitate the process. Group medical visits have been recognized as a useful and effective strategy for approaching patients [1]. The current study describes what the authorssay is the first advance care planning group visit, which they named the “Conversation Group Medical Visit” (CGMV). Its aim is to engage patients in a discussion of key advance care planning concepts and support patient-initiated advance care planning actions, such as choosing surrogate decision makers, deciding on preferences during serious illness, discussing preferences with decision makers and health care providers, and documenting advance directives in the electronic health record [3].

As part of the group medical visits, participants receive an agenda, a personal copy of their EHR highlighting current advance care planning documentation, if any, and a blank medical durable power of attorney form. Facilitators use educational materials including videos from the PREPARE website (prepareforyourcare.org) that demonstrate a family’s conversation, advance directives, and various degrees of flexibility in the decision-making role. A Conversation Starter Kit is also used, which prompts individuals to think about their values and guides conversations about preferences.

Researcher used the RE-AIM framework [4] to evaluate the implementation of this group medical visit model. This framework looks at Reach (if older adults would participate in the medical group visits), Effectiveness (related to participant’s engagement in the conversations), the Adoption of the model by health providers (clinician referral patterns), Implementation (related to the attendance of patients at both clinical and group visits and aspects of planning discussed), and Maintenance (not assessed in this study).

There was a 40% participation rate. Reasons given for declining to participate were having participated in past advance care planning conversation or having an existing advance directive (30%), lack of interest (13%), illness (3.3%), lack of transportation (3.3%), and other/unknown (50%). Regarding effectiveness, the majority of patients rated the group visit as better than usual clinic visits for talking about advance care planning. Participants reported that they received useful information and felt comfortable talking about advance care planning in the group. In addition, participants reported finding it helpful to talk with others about advance care planning (92%). Participants also reported an overall increase (19% to 41%) in advance care planning conversations with family members after participating in the group visit (P =0.02). Participants said these conversations included enough details that they felt confident that their family members knew their wishes. Thus, enrollment in a CGMV led to improvements in conversation not only between patient and health care provider but also between family members.

Several themes were identified during discussions. Patients shared personal values and challenges related to advance care planning. Also, the facilitated discussions introduced key advance care planning concepts and encouraged patients to share related experiences, questions, successes, and challenges in regards to these topics. An interesting finding was that patients in groups of 4 or 5 seemed less engaged in the discussion than those in groups of 7 to 9 patients.

Applications for Clinical Practice

This novel strategy to faciliate discussions about advance care planning showed promising results and appears feasible, but further study is needed to evaluate the model. It may prove useful as a new model of advance care planning in primary care. Further longitudinal research is encouraged.

 —Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To describe the feasibility of a primary care–based group visit model focused on advance care planning.

Design. Qualitative study.

Setting and participants. Participants were patients attending the Senior Clinic, a patient-centered medical home at the University of Colorado Hospital in Aurora, CO. Patients had to be aged 65, English speakers, and receiving primary care at the Clinic. Participants could be referred by their primary care clinician, a partner or friend, or self-refer in response to flyers. Clinicians were not asked to prioritize patients with poor health status or known end-of-life needs.

Intervention. Groups of patients met for 2 sessions (1 month apart), each 2 hours in length, facilitated by a geriatrician and a social worker. About 1 hour was spent on discussion of advance care planning concepts, including sharing experiences and considering values. Other time in the session was for introductions/rapport building, individual goal setting, and optional completion or directives and/or individual clinical visits. Facilitators were supported by a Facilitator’s Communication Guide and used educational materials and handouts with the group.

Main outcome measures. Researchers used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the project.

Main results. Patients were referred by 10 out of 11 clinicians. Of 80 patients approached, 32 participated in 5 group visit cohorts (40% participation rate) and 27 participated in both sessions (84% retention rate). Mean age was 79 years; 59% of participants were female and 72% white. Most evaluated the group visit as better than usual clinic visits for discussing advance care planning. Patients reported increases in detailed advance care planning conversations after participating (19% to 41%, P = 0.02). Patients were willing to share personal values and challenges related to advance care planning and they initiated discussions about a broad range of relevant topics.

Conclusion. A group visit to facilitate discussions about advance care planning and increase patient engagement is feasible. This model warrants further evaluation for effectiveness in improving advance care planning outcomes for patients, clinicians, and the system.

Commentary

An understanding of patients’ care goals is an essential element of high-quality care, allowing clinicians to align the care provided with what is most important to the patient [1]. Existing evidence does not support the commonly held belief that communication about end-of-life issues increases patient distress [1]. Early discussions about goals of care are associated with better quality of life, reduced use of nonbeneficial medical care near death, enhanced goal-consistent care, positive family outcomes, and reduced costs; however, significant barriers to having advance care planning discussions exist [2], including communication issues and lack of appropriate counseling by clinicians in primary care. Clinicians cite limited time and lack of clinic-based support as factors that impede discussions with patients about advance care planning.

New models are being developed in order to facilitate the process. Group medical visits have been recognized as a useful and effective strategy for approaching patients [1]. The current study describes what the authorssay is the first advance care planning group visit, which they named the “Conversation Group Medical Visit” (CGMV). Its aim is to engage patients in a discussion of key advance care planning concepts and support patient-initiated advance care planning actions, such as choosing surrogate decision makers, deciding on preferences during serious illness, discussing preferences with decision makers and health care providers, and documenting advance directives in the electronic health record [3].

As part of the group medical visits, participants receive an agenda, a personal copy of their EHR highlighting current advance care planning documentation, if any, and a blank medical durable power of attorney form. Facilitators use educational materials including videos from the PREPARE website (prepareforyourcare.org) that demonstrate a family’s conversation, advance directives, and various degrees of flexibility in the decision-making role. A Conversation Starter Kit is also used, which prompts individuals to think about their values and guides conversations about preferences.

Researcher used the RE-AIM framework [4] to evaluate the implementation of this group medical visit model. This framework looks at Reach (if older adults would participate in the medical group visits), Effectiveness (related to participant’s engagement in the conversations), the Adoption of the model by health providers (clinician referral patterns), Implementation (related to the attendance of patients at both clinical and group visits and aspects of planning discussed), and Maintenance (not assessed in this study).

There was a 40% participation rate. Reasons given for declining to participate were having participated in past advance care planning conversation or having an existing advance directive (30%), lack of interest (13%), illness (3.3%), lack of transportation (3.3%), and other/unknown (50%). Regarding effectiveness, the majority of patients rated the group visit as better than usual clinic visits for talking about advance care planning. Participants reported that they received useful information and felt comfortable talking about advance care planning in the group. In addition, participants reported finding it helpful to talk with others about advance care planning (92%). Participants also reported an overall increase (19% to 41%) in advance care planning conversations with family members after participating in the group visit (P =0.02). Participants said these conversations included enough details that they felt confident that their family members knew their wishes. Thus, enrollment in a CGMV led to improvements in conversation not only between patient and health care provider but also between family members.

Several themes were identified during discussions. Patients shared personal values and challenges related to advance care planning. Also, the facilitated discussions introduced key advance care planning concepts and encouraged patients to share related experiences, questions, successes, and challenges in regards to these topics. An interesting finding was that patients in groups of 4 or 5 seemed less engaged in the discussion than those in groups of 7 to 9 patients.

Applications for Clinical Practice

This novel strategy to faciliate discussions about advance care planning showed promising results and appears feasible, but further study is needed to evaluate the model. It may prove useful as a new model of advance care planning in primary care. Further longitudinal research is encouraged.

 —Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To describe the feasibility of a primary care–based group visit model focused on advance care planning.

Design. Qualitative study.

Setting and participants. Participants were patients attending the Senior Clinic, a patient-centered medical home at the University of Colorado Hospital in Aurora, CO. Patients had to be aged 65, English speakers, and receiving primary care at the Clinic. Participants could be referred by their primary care clinician, a partner or friend, or self-refer in response to flyers. Clinicians were not asked to prioritize patients with poor health status or known end-of-life needs.

Intervention. Groups of patients met for 2 sessions (1 month apart), each 2 hours in length, facilitated by a geriatrician and a social worker. About 1 hour was spent on discussion of advance care planning concepts, including sharing experiences and considering values. Other time in the session was for introductions/rapport building, individual goal setting, and optional completion or directives and/or individual clinical visits. Facilitators were supported by a Facilitator’s Communication Guide and used educational materials and handouts with the group.

Main outcome measures. Researchers used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the project.

Main results. Patients were referred by 10 out of 11 clinicians. Of 80 patients approached, 32 participated in 5 group visit cohorts (40% participation rate) and 27 participated in both sessions (84% retention rate). Mean age was 79 years; 59% of participants were female and 72% white. Most evaluated the group visit as better than usual clinic visits for discussing advance care planning. Patients reported increases in detailed advance care planning conversations after participating (19% to 41%, P = 0.02). Patients were willing to share personal values and challenges related to advance care planning and they initiated discussions about a broad range of relevant topics.

Conclusion. A group visit to facilitate discussions about advance care planning and increase patient engagement is feasible. This model warrants further evaluation for effectiveness in improving advance care planning outcomes for patients, clinicians, and the system.

Commentary

An understanding of patients’ care goals is an essential element of high-quality care, allowing clinicians to align the care provided with what is most important to the patient [1]. Existing evidence does not support the commonly held belief that communication about end-of-life issues increases patient distress [1]. Early discussions about goals of care are associated with better quality of life, reduced use of nonbeneficial medical care near death, enhanced goal-consistent care, positive family outcomes, and reduced costs; however, significant barriers to having advance care planning discussions exist [2], including communication issues and lack of appropriate counseling by clinicians in primary care. Clinicians cite limited time and lack of clinic-based support as factors that impede discussions with patients about advance care planning.

New models are being developed in order to facilitate the process. Group medical visits have been recognized as a useful and effective strategy for approaching patients [1]. The current study describes what the authorssay is the first advance care planning group visit, which they named the “Conversation Group Medical Visit” (CGMV). Its aim is to engage patients in a discussion of key advance care planning concepts and support patient-initiated advance care planning actions, such as choosing surrogate decision makers, deciding on preferences during serious illness, discussing preferences with decision makers and health care providers, and documenting advance directives in the electronic health record [3].

As part of the group medical visits, participants receive an agenda, a personal copy of their EHR highlighting current advance care planning documentation, if any, and a blank medical durable power of attorney form. Facilitators use educational materials including videos from the PREPARE website (prepareforyourcare.org) that demonstrate a family’s conversation, advance directives, and various degrees of flexibility in the decision-making role. A Conversation Starter Kit is also used, which prompts individuals to think about their values and guides conversations about preferences.

Researcher used the RE-AIM framework [4] to evaluate the implementation of this group medical visit model. This framework looks at Reach (if older adults would participate in the medical group visits), Effectiveness (related to participant’s engagement in the conversations), the Adoption of the model by health providers (clinician referral patterns), Implementation (related to the attendance of patients at both clinical and group visits and aspects of planning discussed), and Maintenance (not assessed in this study).

There was a 40% participation rate. Reasons given for declining to participate were having participated in past advance care planning conversation or having an existing advance directive (30%), lack of interest (13%), illness (3.3%), lack of transportation (3.3%), and other/unknown (50%). Regarding effectiveness, the majority of patients rated the group visit as better than usual clinic visits for talking about advance care planning. Participants reported that they received useful information and felt comfortable talking about advance care planning in the group. In addition, participants reported finding it helpful to talk with others about advance care planning (92%). Participants also reported an overall increase (19% to 41%) in advance care planning conversations with family members after participating in the group visit (P =0.02). Participants said these conversations included enough details that they felt confident that their family members knew their wishes. Thus, enrollment in a CGMV led to improvements in conversation not only between patient and health care provider but also between family members.

Several themes were identified during discussions. Patients shared personal values and challenges related to advance care planning. Also, the facilitated discussions introduced key advance care planning concepts and encouraged patients to share related experiences, questions, successes, and challenges in regards to these topics. An interesting finding was that patients in groups of 4 or 5 seemed less engaged in the discussion than those in groups of 7 to 9 patients.

Applications for Clinical Practice

This novel strategy to faciliate discussions about advance care planning showed promising results and appears feasible, but further study is needed to evaluate the model. It may prove useful as a new model of advance care planning in primary care. Further longitudinal research is encouraged.

 —Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To examine the effects of acupuncture on vasomotor symptoms (VMS) and quality of life in perimenopausal and postmenopausal women.

Design. Pragmatic randomized controlled trial.

Setting and participants. Participants were perimenopausal and postmenopausal women aged 45 to 60 years who had 4 or more VMS episodes a day. Women were excluded if they had initiated or changed a dose of any VMS treatment in the 4 weeks prior to the study, initiated or changed the dose of an antidepressant in the prior 3 months, had received acupuncture in the prior 4 weeks, self-reported their health as poor or fair, or had a diagnosis of hemophilia. The study was conducted at the Wake Forest School of Medicine and the Chapel Hill Doctors Healthcare Center in North Carolina with women recruited from the community. Potential participants completed a 2-week hot flash diary to establish that they met the eligibility criteria of 4 or more hot flashes a day.

Intervention. Eligible participants were randomized to either the experimental group, who received up to 20 acupuncture treatments over a 6-month period, or a waitlist control group who received usual care for 6 months followed by the same 6 months of acupuncture treatment received by the experimental group. The researchers decided not to use sham acupuncture in the control group because outside of the experiment women would not receive sham acupuncture and because it has been shown to have an effect on menopausal symptoms in other studies.

Participants could receive up to 20 acupuncture treatments from 1 of the 4 study licensed acupuncturists over a period of 6 months. The acupuncturist assessed the participant and made a traditional Chinese medicine diagnosis to guide treatment at the initial and each subsequent visit. During treatment, acupuncture needles were inserted 0.5 to 3 cm through the skin to achieve a “de Qi” sensation, which is a sensation of heaviness, numbness, soreness, or distention at the insertion site. Acupuncturists were permitted to administer additional acupuncture-related treatments with the exception of the use of Chinese herbal remedies. Additionally, participants were permitted to start other treatments, and 11 women in the acupuncture group and 2 women in the control group started other behavioral treatments during the study.

Main outcome measures. The primary outcome measure was the frequency and severity of hot flashes and night sweats, measured using the Daily Diary of Hot Flashes (DDHF). Secondary measures were the following quality of life indicators: hot flash interference (the degree to which hot flashes interfered with specific daily activities), measured using the Hot Flash-related Daily Interference Scale; sleep quality, measured using the Pittsburgh Sleep Quality Index (PSQI) and the PROMIS Sleep Disturbance short form; menopause related symptoms other than VMS, measured using the Women’s Health Questionaire (WHQ); depression, measured using the short form of the Center for Epidemiologic Studies Depression scale (CESD-10); anxiety, measured using the General Anxiety Disorder (GAD-7) and the PROMIS Anxiety short form; perceived stress, measured using the Perceived Stress Scale (PSS); and health-related quality of life (HRQOL), measured using a global visual analog scale (VAS) and the Physical and Mental Health Component scores of the Medical Outcomes Study short form health survey (SF-36).

Main results. The final sample size was 209 women, with 170 randomized to the acupuncture group and 39 to the control group. There were no significant differences between the groups at baseline. The retention rate was 89% at 6 months and 84% at 12 months. At 6 months there was a 36.7% decrease VMS frequency in the acupuncture group compared to a 6.0% increase in the control group (P < 0.001). At 12 months the decrease in VMS frequency was 29.5% in the acupuncture group. The control group began acupuncture at 6 months and by 12 months the frequency of VMS in this group was 31.0% less than at baseline (P < 0.001). Overall, the maximal effect was achieved at week 7 with a median of 8 acupuncture treatments. Sensitivity analysis indicated that there were no differences in effect in those who started other behavioral treatments during this period. There were also significant improvements in scores on the hot flash interference scale (P < 0.001), fewer sleep problems on the sleep measures, and fewer symptoms on the WHQ for women in the acupuncture group and these effects were maintained at 12 months. In addition, similar results were found in the control group after they initiated acupuncture at 6 months.

Conclusion. Overall, acupuncture resulted in significant and sustained improvements in VMS and quality of life measures.

Commentary

More than half of women will experience frequent VMS beginning with the menopause transition [1] and lasting an average of 7.4 years [2]. The effect of VMS on women’s quality of life is considerable, including anxiety, stress, decreased energy, sleep disruption and interference with leisure, social, and work activities [3,4]. Estrogen therapy remains the most effective therapy for VMS; however, its use is contraindicated in many women and duration of use is limited [5]. Therefore, safe and effective alternate therapies are needed.

Acupuncture is a traditional Chinese medicine therapy that has gained popularity in recent years for therapeutic management of many conditions, including pain, nausea related to pregnancy or chemotherapy, anxiety, headache, and addiction. Evidence regarding effectiveness has been equivocal, with studies of its effectiveness in some conditions, such as nausea and dental pain, showing strong positive results while evidence for its use in other conditions is lacking or inconsistent [6]. There have been consistent positive findings in prior research of the use of acupuncture to reduce the severity and frequency of VMS, however, according to the authors of this study, little is known about the long-term effects or the effect on quality of life. Additionally, most studies use sham acupuncture in the control group, which would not be offered to women outside a study protocol and has been shown to have a physiological effect of its own. Therefore, the authors conducted a pragmatic randomized control trial; designing the intervention so that it more closely reflected what happens in a real world clinical setting, to examine the overall effects and effect on quality of life measures.

The results of this study were a significant positive effect of acupuncture on the frequency and severity of VMS in the acupuncture group that was sustained over 12 months and improvements on all quality of life measures. There was also a significant effect in the control group when they received the intervention after the initial 6-month period. As the authors note, it is unclear if improvements in the quality of life indicators were a direct effect of the acupuncture or secondary to the relief of the vasomotor symptoms. Its use in women who experience other menopause-related symptoms, such as mood disorders or sleep disruption, in the absence of VMS needs further study.

The authors compare their results with that of research on the use of selective serotonin reuptake inhibitors (SSRIs) for VMS, one of the more efficacious alternatives to hormone therapy. As they note, though the reduction was somewhat less than that found with SSRIs (for example 35% for acupuncture vs. 47% with escitalopram), the risk of adverse effects is much lower with acupuncture. The only reported adverse effects in this study were 2 women who reported pain during treatment and 1 who reported numbness while SSRIs are known to have significant adverse effects. In addition, the results in this study were sustained longer, until the final follow-up at 6 months, while women who used escitalopram relapsed three weeks after discontinuing the medication.

The use of a pragmatic design allows for more confidence that the findings will translate to the real world setting. The number and timing of acupuncture treatments were determined by each woman with the acupuncturist as would happen in the clinical setting. In addition, the initiation of other therapies during the treatment stage was allowed, with 11 women in the acupuncture group and 2 women in the treatment group starting other behavioral interventions during that time. Though this approach has a small chance of introducing confounding variables, sensitivity analysis indicated it did not. As such, this design results in a study that is an accurate reflection of the experience of women receiving acupuncture in the clinical setting and thus good external validity.

There were 2 limitations of note. Though retention was excellent, 89% and 84% for the acupuncture and control group respectively, it is unknown if the women who dropped out did so due to lack of improvement, in which case the actual reduction in VMS would have been less than reported. Additionally, the use of self-report (diaries) of VMS can be unreliable and biased.

Applications for Clinical Practice

The results of this study indicate that acupuncture offers women a safe and effective therapy for VMS. The optimal dose appears to be 8 treatments. Clinicians should consider it as a first-line treatment for women with moderate to severe VMS who have contraindications to hormone therapy and before prescribing SSRI therapy, which carries the potential for significant adverse effects.

 —Karen Roush, PhD, RN

Study Overview

Objective. To examine the effects of acupuncture on vasomotor symptoms (VMS) and quality of life in perimenopausal and postmenopausal women.

Design. Pragmatic randomized controlled trial.

Setting and participants. Participants were perimenopausal and postmenopausal women aged 45 to 60 years who had 4 or more VMS episodes a day. Women were excluded if they had initiated or changed a dose of any VMS treatment in the 4 weeks prior to the study, initiated or changed the dose of an antidepressant in the prior 3 months, had received acupuncture in the prior 4 weeks, self-reported their health as poor or fair, or had a diagnosis of hemophilia. The study was conducted at the Wake Forest School of Medicine and the Chapel Hill Doctors Healthcare Center in North Carolina with women recruited from the community. Potential participants completed a 2-week hot flash diary to establish that they met the eligibility criteria of 4 or more hot flashes a day.

Intervention. Eligible participants were randomized to either the experimental group, who received up to 20 acupuncture treatments over a 6-month period, or a waitlist control group who received usual care for 6 months followed by the same 6 months of acupuncture treatment received by the experimental group. The researchers decided not to use sham acupuncture in the control group because outside of the experiment women would not receive sham acupuncture and because it has been shown to have an effect on menopausal symptoms in other studies.

Participants could receive up to 20 acupuncture treatments from 1 of the 4 study licensed acupuncturists over a period of 6 months. The acupuncturist assessed the participant and made a traditional Chinese medicine diagnosis to guide treatment at the initial and each subsequent visit. During treatment, acupuncture needles were inserted 0.5 to 3 cm through the skin to achieve a “de Qi” sensation, which is a sensation of heaviness, numbness, soreness, or distention at the insertion site. Acupuncturists were permitted to administer additional acupuncture-related treatments with the exception of the use of Chinese herbal remedies. Additionally, participants were permitted to start other treatments, and 11 women in the acupuncture group and 2 women in the control group started other behavioral treatments during the study.

Main outcome measures. The primary outcome measure was the frequency and severity of hot flashes and night sweats, measured using the Daily Diary of Hot Flashes (DDHF). Secondary measures were the following quality of life indicators: hot flash interference (the degree to which hot flashes interfered with specific daily activities), measured using the Hot Flash-related Daily Interference Scale; sleep quality, measured using the Pittsburgh Sleep Quality Index (PSQI) and the PROMIS Sleep Disturbance short form; menopause related symptoms other than VMS, measured using the Women’s Health Questionaire (WHQ); depression, measured using the short form of the Center for Epidemiologic Studies Depression scale (CESD-10); anxiety, measured using the General Anxiety Disorder (GAD-7) and the PROMIS Anxiety short form; perceived stress, measured using the Perceived Stress Scale (PSS); and health-related quality of life (HRQOL), measured using a global visual analog scale (VAS) and the Physical and Mental Health Component scores of the Medical Outcomes Study short form health survey (SF-36).

Main results. The final sample size was 209 women, with 170 randomized to the acupuncture group and 39 to the control group. There were no significant differences between the groups at baseline. The retention rate was 89% at 6 months and 84% at 12 months. At 6 months there was a 36.7% decrease VMS frequency in the acupuncture group compared to a 6.0% increase in the control group (P < 0.001). At 12 months the decrease in VMS frequency was 29.5% in the acupuncture group. The control group began acupuncture at 6 months and by 12 months the frequency of VMS in this group was 31.0% less than at baseline (P < 0.001). Overall, the maximal effect was achieved at week 7 with a median of 8 acupuncture treatments. Sensitivity analysis indicated that there were no differences in effect in those who started other behavioral treatments during this period. There were also significant improvements in scores on the hot flash interference scale (P < 0.001), fewer sleep problems on the sleep measures, and fewer symptoms on the WHQ for women in the acupuncture group and these effects were maintained at 12 months. In addition, similar results were found in the control group after they initiated acupuncture at 6 months.

Conclusion. Overall, acupuncture resulted in significant and sustained improvements in VMS and quality of life measures.

Commentary

More than half of women will experience frequent VMS beginning with the menopause transition [1] and lasting an average of 7.4 years [2]. The effect of VMS on women’s quality of life is considerable, including anxiety, stress, decreased energy, sleep disruption and interference with leisure, social, and work activities [3,4]. Estrogen therapy remains the most effective therapy for VMS; however, its use is contraindicated in many women and duration of use is limited [5]. Therefore, safe and effective alternate therapies are needed.

Acupuncture is a traditional Chinese medicine therapy that has gained popularity in recent years for therapeutic management of many conditions, including pain, nausea related to pregnancy or chemotherapy, anxiety, headache, and addiction. Evidence regarding effectiveness has been equivocal, with studies of its effectiveness in some conditions, such as nausea and dental pain, showing strong positive results while evidence for its use in other conditions is lacking or inconsistent [6]. There have been consistent positive findings in prior research of the use of acupuncture to reduce the severity and frequency of VMS, however, according to the authors of this study, little is known about the long-term effects or the effect on quality of life. Additionally, most studies use sham acupuncture in the control group, which would not be offered to women outside a study protocol and has been shown to have a physiological effect of its own. Therefore, the authors conducted a pragmatic randomized control trial; designing the intervention so that it more closely reflected what happens in a real world clinical setting, to examine the overall effects and effect on quality of life measures.

The results of this study were a significant positive effect of acupuncture on the frequency and severity of VMS in the acupuncture group that was sustained over 12 months and improvements on all quality of life measures. There was also a significant effect in the control group when they received the intervention after the initial 6-month period. As the authors note, it is unclear if improvements in the quality of life indicators were a direct effect of the acupuncture or secondary to the relief of the vasomotor symptoms. Its use in women who experience other menopause-related symptoms, such as mood disorders or sleep disruption, in the absence of VMS needs further study.

The authors compare their results with that of research on the use of selective serotonin reuptake inhibitors (SSRIs) for VMS, one of the more efficacious alternatives to hormone therapy. As they note, though the reduction was somewhat less than that found with SSRIs (for example 35% for acupuncture vs. 47% with escitalopram), the risk of adverse effects is much lower with acupuncture. The only reported adverse effects in this study were 2 women who reported pain during treatment and 1 who reported numbness while SSRIs are known to have significant adverse effects. In addition, the results in this study were sustained longer, until the final follow-up at 6 months, while women who used escitalopram relapsed three weeks after discontinuing the medication.

The use of a pragmatic design allows for more confidence that the findings will translate to the real world setting. The number and timing of acupuncture treatments were determined by each woman with the acupuncturist as would happen in the clinical setting. In addition, the initiation of other therapies during the treatment stage was allowed, with 11 women in the acupuncture group and 2 women in the treatment group starting other behavioral interventions during that time. Though this approach has a small chance of introducing confounding variables, sensitivity analysis indicated it did not. As such, this design results in a study that is an accurate reflection of the experience of women receiving acupuncture in the clinical setting and thus good external validity.

There were 2 limitations of note. Though retention was excellent, 89% and 84% for the acupuncture and control group respectively, it is unknown if the women who dropped out did so due to lack of improvement, in which case the actual reduction in VMS would have been less than reported. Additionally, the use of self-report (diaries) of VMS can be unreliable and biased.

Applications for Clinical Practice

The results of this study indicate that acupuncture offers women a safe and effective therapy for VMS. The optimal dose appears to be 8 treatments. Clinicians should consider it as a first-line treatment for women with moderate to severe VMS who have contraindications to hormone therapy and before prescribing SSRI therapy, which carries the potential for significant adverse effects.

 —Karen Roush, PhD, RN

Study Overview

Objective. To examine the effects of acupuncture on vasomotor symptoms (VMS) and quality of life in perimenopausal and postmenopausal women.

Design. Pragmatic randomized controlled trial.

Setting and participants. Participants were perimenopausal and postmenopausal women aged 45 to 60 years who had 4 or more VMS episodes a day. Women were excluded if they had initiated or changed a dose of any VMS treatment in the 4 weeks prior to the study, initiated or changed the dose of an antidepressant in the prior 3 months, had received acupuncture in the prior 4 weeks, self-reported their health as poor or fair, or had a diagnosis of hemophilia. The study was conducted at the Wake Forest School of Medicine and the Chapel Hill Doctors Healthcare Center in North Carolina with women recruited from the community. Potential participants completed a 2-week hot flash diary to establish that they met the eligibility criteria of 4 or more hot flashes a day.

Intervention. Eligible participants were randomized to either the experimental group, who received up to 20 acupuncture treatments over a 6-month period, or a waitlist control group who received usual care for 6 months followed by the same 6 months of acupuncture treatment received by the experimental group. The researchers decided not to use sham acupuncture in the control group because outside of the experiment women would not receive sham acupuncture and because it has been shown to have an effect on menopausal symptoms in other studies.

Participants could receive up to 20 acupuncture treatments from 1 of the 4 study licensed acupuncturists over a period of 6 months. The acupuncturist assessed the participant and made a traditional Chinese medicine diagnosis to guide treatment at the initial and each subsequent visit. During treatment, acupuncture needles were inserted 0.5 to 3 cm through the skin to achieve a “de Qi” sensation, which is a sensation of heaviness, numbness, soreness, or distention at the insertion site. Acupuncturists were permitted to administer additional acupuncture-related treatments with the exception of the use of Chinese herbal remedies. Additionally, participants were permitted to start other treatments, and 11 women in the acupuncture group and 2 women in the control group started other behavioral treatments during the study.

Main outcome measures. The primary outcome measure was the frequency and severity of hot flashes and night sweats, measured using the Daily Diary of Hot Flashes (DDHF). Secondary measures were the following quality of life indicators: hot flash interference (the degree to which hot flashes interfered with specific daily activities), measured using the Hot Flash-related Daily Interference Scale; sleep quality, measured using the Pittsburgh Sleep Quality Index (PSQI) and the PROMIS Sleep Disturbance short form; menopause related symptoms other than VMS, measured using the Women’s Health Questionaire (WHQ); depression, measured using the short form of the Center for Epidemiologic Studies Depression scale (CESD-10); anxiety, measured using the General Anxiety Disorder (GAD-7) and the PROMIS Anxiety short form; perceived stress, measured using the Perceived Stress Scale (PSS); and health-related quality of life (HRQOL), measured using a global visual analog scale (VAS) and the Physical and Mental Health Component scores of the Medical Outcomes Study short form health survey (SF-36).

Main results. The final sample size was 209 women, with 170 randomized to the acupuncture group and 39 to the control group. There were no significant differences between the groups at baseline. The retention rate was 89% at 6 months and 84% at 12 months. At 6 months there was a 36.7% decrease VMS frequency in the acupuncture group compared to a 6.0% increase in the control group (P < 0.001). At 12 months the decrease in VMS frequency was 29.5% in the acupuncture group. The control group began acupuncture at 6 months and by 12 months the frequency of VMS in this group was 31.0% less than at baseline (P < 0.001). Overall, the maximal effect was achieved at week 7 with a median of 8 acupuncture treatments. Sensitivity analysis indicated that there were no differences in effect in those who started other behavioral treatments during this period. There were also significant improvements in scores on the hot flash interference scale (P < 0.001), fewer sleep problems on the sleep measures, and fewer symptoms on the WHQ for women in the acupuncture group and these effects were maintained at 12 months. In addition, similar results were found in the control group after they initiated acupuncture at 6 months.

Conclusion. Overall, acupuncture resulted in significant and sustained improvements in VMS and quality of life measures.

Commentary

More than half of women will experience frequent VMS beginning with the menopause transition [1] and lasting an average of 7.4 years [2]. The effect of VMS on women’s quality of life is considerable, including anxiety, stress, decreased energy, sleep disruption and interference with leisure, social, and work activities [3,4]. Estrogen therapy remains the most effective therapy for VMS; however, its use is contraindicated in many women and duration of use is limited [5]. Therefore, safe and effective alternate therapies are needed.

Acupuncture is a traditional Chinese medicine therapy that has gained popularity in recent years for therapeutic management of many conditions, including pain, nausea related to pregnancy or chemotherapy, anxiety, headache, and addiction. Evidence regarding effectiveness has been equivocal, with studies of its effectiveness in some conditions, such as nausea and dental pain, showing strong positive results while evidence for its use in other conditions is lacking or inconsistent [6]. There have been consistent positive findings in prior research of the use of acupuncture to reduce the severity and frequency of VMS, however, according to the authors of this study, little is known about the long-term effects or the effect on quality of life. Additionally, most studies use sham acupuncture in the control group, which would not be offered to women outside a study protocol and has been shown to have a physiological effect of its own. Therefore, the authors conducted a pragmatic randomized control trial; designing the intervention so that it more closely reflected what happens in a real world clinical setting, to examine the overall effects and effect on quality of life measures.

The results of this study were a significant positive effect of acupuncture on the frequency and severity of VMS in the acupuncture group that was sustained over 12 months and improvements on all quality of life measures. There was also a significant effect in the control group when they received the intervention after the initial 6-month period. As the authors note, it is unclear if improvements in the quality of life indicators were a direct effect of the acupuncture or secondary to the relief of the vasomotor symptoms. Its use in women who experience other menopause-related symptoms, such as mood disorders or sleep disruption, in the absence of VMS needs further study.

The authors compare their results with that of research on the use of selective serotonin reuptake inhibitors (SSRIs) for VMS, one of the more efficacious alternatives to hormone therapy. As they note, though the reduction was somewhat less than that found with SSRIs (for example 35% for acupuncture vs. 47% with escitalopram), the risk of adverse effects is much lower with acupuncture. The only reported adverse effects in this study were 2 women who reported pain during treatment and 1 who reported numbness while SSRIs are known to have significant adverse effects. In addition, the results in this study were sustained longer, until the final follow-up at 6 months, while women who used escitalopram relapsed three weeks after discontinuing the medication.

The use of a pragmatic design allows for more confidence that the findings will translate to the real world setting. The number and timing of acupuncture treatments were determined by each woman with the acupuncturist as would happen in the clinical setting. In addition, the initiation of other therapies during the treatment stage was allowed, with 11 women in the acupuncture group and 2 women in the treatment group starting other behavioral interventions during that time. Though this approach has a small chance of introducing confounding variables, sensitivity analysis indicated it did not. As such, this design results in a study that is an accurate reflection of the experience of women receiving acupuncture in the clinical setting and thus good external validity.

There were 2 limitations of note. Though retention was excellent, 89% and 84% for the acupuncture and control group respectively, it is unknown if the women who dropped out did so due to lack of improvement, in which case the actual reduction in VMS would have been less than reported. Additionally, the use of self-report (diaries) of VMS can be unreliable and biased.

Applications for Clinical Practice

The results of this study indicate that acupuncture offers women a safe and effective therapy for VMS. The optimal dose appears to be 8 treatments. Clinicians should consider it as a first-line treatment for women with moderate to severe VMS who have contraindications to hormone therapy and before prescribing SSRI therapy, which carries the potential for significant adverse effects.

 —Karen Roush, PhD, RN

Study Overview

Objective. To determine whether the administration of betamethasone to women who are likely to deliver in the late preterm period would decrease respiratory and other neonatal complications.

Design. Randomized controlled trial.

Setting and participants. Participants were women with a singleton pregnancy at 34 weeks 0 days to 36 weeks 5 days of gestation and a high probability of delivery in the late preterm period (which extends to 36 weeks 6 days) within the 17 university-based clinical centers participating in the Maternal Fetal Medicine Units Network of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). Eligible women were randomly assigned in a 1:1 ratio to a course of 2 intramuscular injections of either 12 mg betamethasone or matching placebo administered 24 hours apart. After administration of the study medications, the women were treated clinically according to local practice, including discharge to home if delivery did not occur.

Main outcome measures. The primary outcome was a composite endpoint consisting of need for respiratory support, stillbirth, or neonatal death within 72 hours after delivery. Need for respiratory support was defined as one or more of the following: the use of continuous positive airway pressure (CPAP) or high-flow nasal cannula for at least 2 consecutive hours, supplemental oxygen with a fraction of inspired oxygen of at least 0.30 for at least 4 continuous hours, extracorporeal membrane oxygenation (ECMO), or mechanical ventilation. Secondary outcomes included 2 composite outcomes: (1) respiratory distress syndrome, transient tachypnea of the newborn, or apnea; and (2) respiratory distress syndrome, intraventricular hemorrhage, or necrotizing enterocolitis.

Main results. Among 24,133 women assessed for eligibility, 2831 women underwent randomization with 1429 assigned to the betamethasone group and 1402 to the placebo group. A total of 860 (60.2%) in the betamethasone group and 826 (58.9%) in the placebo group received the prespecified 2 doses of study medication. 1083 of the 1145 women (94.6%) who did not receive a second dose delivered before 24 hours. Two women in each study group were lost to follow-up, with outcome information available for 2827 neonates.

The rate of the primary outcome was lower in the betamethasone group (11.6%) than in the placebo group (14.4%), with a relative risk of 0.80% (95% CI 0.66 to 0.97; P = 0.02); the number needed to treat was 35 women to prevent 1 case of the primary outcome. In regard to secondary outcomes, the rate of the composite outcome of severe respiratory complications was also lower in the betamethasone group than in the placebo group (8.1% vs. 12.1%; relative risk 0.67; CI 0.53 to 0.84; P < 0.001). Of note, the betamethasone group had a higher incidence of neonatal hypoglycemia when compared to the placebo group (24.0% vs. 15.0%; relative risk 1.60; 95% CI 1.37 to 1.87; P < 0.001).

Conclusion. Administration of antenatal betamethasone in women at risk for late preterm delivery significantly decreased the rate of respiratory complications in newborns.

Commentary

Use of antenatal glucocorticoids for early preterm delivery has been a widely accepted practice, with strong evidence that glucocorticoids reduce adverse neonatal outcomes when administered to women who are likely to deliver before 34 weeks of gestation [1,2]. In addition, use of glucocorticoids at the time of elective cesarean delivery at term from the results of the Antenatal Steroids for Term Elective Caesarean Section (ASTECS) trial demonstrated reduction in the rate of admission to neonatal intensive care units for respiratory complications in the betamethasone group when comparing to placebo [3]. However, the use of glucocorticoids in the late preterm period to prevent adverse neonatal respiratory outcomes remained inconclusive after 2 smaller randomized trials [4,5].

In the current study, Gyamfi-Bannerman and colleagues addressed the issue of whether the use of glucocorticoids, specifically betamethasone, in the late preterm period may prevent adverse neonatal respiratory outcomes. While only 60.2% of the betamethasone group and 58.9% of the placebo group received the proposed 2 doses of study medication, administration of betamethasone decreased the need for substantial respiratory support during the first 72 hours after birth and other respiratory complications.

There were no clinically significant adverse neonatal effects except that the betamethasone cohort babies had a 60% increased relative risk of neonatal hypoglycemia. There were no reported adverse events related to the hypoglycemia, and infants with hypoglycemia were discharged on average 2 days earlier than those without, which suggests that the condition was self-limiting. The authors suggested monitoring neonatal blood glucose after betamethasone exposure in the late preterm period.  It will be important to answer questions about the long-term outcomes of this therapy, both benefits and risks, such as the potential reduction of chronic lung diseases or risk of developmental delay due to hypoglycemia [6].

Applications for Clinical Practice

This multicenter randomized controlled study provides strong evidence for administering antenatal glucocorticoids, such as betamethasone, in women at risk for late preterm delivery. Betamethasone administration significantly decreased the rate of respiratory complications in newborns, with the precaution to monitor for neonatal hypoglycemia.

 —Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To determine whether the administration of betamethasone to women who are likely to deliver in the late preterm period would decrease respiratory and other neonatal complications.

Design. Randomized controlled trial.

Setting and participants. Participants were women with a singleton pregnancy at 34 weeks 0 days to 36 weeks 5 days of gestation and a high probability of delivery in the late preterm period (which extends to 36 weeks 6 days) within the 17 university-based clinical centers participating in the Maternal Fetal Medicine Units Network of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). Eligible women were randomly assigned in a 1:1 ratio to a course of 2 intramuscular injections of either 12 mg betamethasone or matching placebo administered 24 hours apart. After administration of the study medications, the women were treated clinically according to local practice, including discharge to home if delivery did not occur.

Main outcome measures. The primary outcome was a composite endpoint consisting of need for respiratory support, stillbirth, or neonatal death within 72 hours after delivery. Need for respiratory support was defined as one or more of the following: the use of continuous positive airway pressure (CPAP) or high-flow nasal cannula for at least 2 consecutive hours, supplemental oxygen with a fraction of inspired oxygen of at least 0.30 for at least 4 continuous hours, extracorporeal membrane oxygenation (ECMO), or mechanical ventilation. Secondary outcomes included 2 composite outcomes: (1) respiratory distress syndrome, transient tachypnea of the newborn, or apnea; and (2) respiratory distress syndrome, intraventricular hemorrhage, or necrotizing enterocolitis.

Main results. Among 24,133 women assessed for eligibility, 2831 women underwent randomization with 1429 assigned to the betamethasone group and 1402 to the placebo group. A total of 860 (60.2%) in the betamethasone group and 826 (58.9%) in the placebo group received the prespecified 2 doses of study medication. 1083 of the 1145 women (94.6%) who did not receive a second dose delivered before 24 hours. Two women in each study group were lost to follow-up, with outcome information available for 2827 neonates.

The rate of the primary outcome was lower in the betamethasone group (11.6%) than in the placebo group (14.4%), with a relative risk of 0.80% (95% CI 0.66 to 0.97; P = 0.02); the number needed to treat was 35 women to prevent 1 case of the primary outcome. In regard to secondary outcomes, the rate of the composite outcome of severe respiratory complications was also lower in the betamethasone group than in the placebo group (8.1% vs. 12.1%; relative risk 0.67; CI 0.53 to 0.84; P < 0.001). Of note, the betamethasone group had a higher incidence of neonatal hypoglycemia when compared to the placebo group (24.0% vs. 15.0%; relative risk 1.60; 95% CI 1.37 to 1.87; P < 0.001).

Conclusion. Administration of antenatal betamethasone in women at risk for late preterm delivery significantly decreased the rate of respiratory complications in newborns.

Commentary

Use of antenatal glucocorticoids for early preterm delivery has been a widely accepted practice, with strong evidence that glucocorticoids reduce adverse neonatal outcomes when administered to women who are likely to deliver before 34 weeks of gestation [1,2]. In addition, use of glucocorticoids at the time of elective cesarean delivery at term from the results of the Antenatal Steroids for Term Elective Caesarean Section (ASTECS) trial demonstrated reduction in the rate of admission to neonatal intensive care units for respiratory complications in the betamethasone group when comparing to placebo [3]. However, the use of glucocorticoids in the late preterm period to prevent adverse neonatal respiratory outcomes remained inconclusive after 2 smaller randomized trials [4,5].

In the current study, Gyamfi-Bannerman and colleagues addressed the issue of whether the use of glucocorticoids, specifically betamethasone, in the late preterm period may prevent adverse neonatal respiratory outcomes. While only 60.2% of the betamethasone group and 58.9% of the placebo group received the proposed 2 doses of study medication, administration of betamethasone decreased the need for substantial respiratory support during the first 72 hours after birth and other respiratory complications.

There were no clinically significant adverse neonatal effects except that the betamethasone cohort babies had a 60% increased relative risk of neonatal hypoglycemia. There were no reported adverse events related to the hypoglycemia, and infants with hypoglycemia were discharged on average 2 days earlier than those without, which suggests that the condition was self-limiting. The authors suggested monitoring neonatal blood glucose after betamethasone exposure in the late preterm period.  It will be important to answer questions about the long-term outcomes of this therapy, both benefits and risks, such as the potential reduction of chronic lung diseases or risk of developmental delay due to hypoglycemia [6].

Applications for Clinical Practice

This multicenter randomized controlled study provides strong evidence for administering antenatal glucocorticoids, such as betamethasone, in women at risk for late preterm delivery. Betamethasone administration significantly decreased the rate of respiratory complications in newborns, with the precaution to monitor for neonatal hypoglycemia.

 —Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To determine whether the administration of betamethasone to women who are likely to deliver in the late preterm period would decrease respiratory and other neonatal complications.

Design. Randomized controlled trial.

Setting and participants. Participants were women with a singleton pregnancy at 34 weeks 0 days to 36 weeks 5 days of gestation and a high probability of delivery in the late preterm period (which extends to 36 weeks 6 days) within the 17 university-based clinical centers participating in the Maternal Fetal Medicine Units Network of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). Eligible women were randomly assigned in a 1:1 ratio to a course of 2 intramuscular injections of either 12 mg betamethasone or matching placebo administered 24 hours apart. After administration of the study medications, the women were treated clinically according to local practice, including discharge to home if delivery did not occur.

Main outcome measures. The primary outcome was a composite endpoint consisting of need for respiratory support, stillbirth, or neonatal death within 72 hours after delivery. Need for respiratory support was defined as one or more of the following: the use of continuous positive airway pressure (CPAP) or high-flow nasal cannula for at least 2 consecutive hours, supplemental oxygen with a fraction of inspired oxygen of at least 0.30 for at least 4 continuous hours, extracorporeal membrane oxygenation (ECMO), or mechanical ventilation. Secondary outcomes included 2 composite outcomes: (1) respiratory distress syndrome, transient tachypnea of the newborn, or apnea; and (2) respiratory distress syndrome, intraventricular hemorrhage, or necrotizing enterocolitis.

Main results. Among 24,133 women assessed for eligibility, 2831 women underwent randomization with 1429 assigned to the betamethasone group and 1402 to the placebo group. A total of 860 (60.2%) in the betamethasone group and 826 (58.9%) in the placebo group received the prespecified 2 doses of study medication. 1083 of the 1145 women (94.6%) who did not receive a second dose delivered before 24 hours. Two women in each study group were lost to follow-up, with outcome information available for 2827 neonates.

The rate of the primary outcome was lower in the betamethasone group (11.6%) than in the placebo group (14.4%), with a relative risk of 0.80% (95% CI 0.66 to 0.97; P = 0.02); the number needed to treat was 35 women to prevent 1 case of the primary outcome. In regard to secondary outcomes, the rate of the composite outcome of severe respiratory complications was also lower in the betamethasone group than in the placebo group (8.1% vs. 12.1%; relative risk 0.67; CI 0.53 to 0.84; P < 0.001). Of note, the betamethasone group had a higher incidence of neonatal hypoglycemia when compared to the placebo group (24.0% vs. 15.0%; relative risk 1.60; 95% CI 1.37 to 1.87; P < 0.001).

Conclusion. Administration of antenatal betamethasone in women at risk for late preterm delivery significantly decreased the rate of respiratory complications in newborns.

Commentary

Use of antenatal glucocorticoids for early preterm delivery has been a widely accepted practice, with strong evidence that glucocorticoids reduce adverse neonatal outcomes when administered to women who are likely to deliver before 34 weeks of gestation [1,2]. In addition, use of glucocorticoids at the time of elective cesarean delivery at term from the results of the Antenatal Steroids for Term Elective Caesarean Section (ASTECS) trial demonstrated reduction in the rate of admission to neonatal intensive care units for respiratory complications in the betamethasone group when comparing to placebo [3]. However, the use of glucocorticoids in the late preterm period to prevent adverse neonatal respiratory outcomes remained inconclusive after 2 smaller randomized trials [4,5].

In the current study, Gyamfi-Bannerman and colleagues addressed the issue of whether the use of glucocorticoids, specifically betamethasone, in the late preterm period may prevent adverse neonatal respiratory outcomes. While only 60.2% of the betamethasone group and 58.9% of the placebo group received the proposed 2 doses of study medication, administration of betamethasone decreased the need for substantial respiratory support during the first 72 hours after birth and other respiratory complications.

There were no clinically significant adverse neonatal effects except that the betamethasone cohort babies had a 60% increased relative risk of neonatal hypoglycemia. There were no reported adverse events related to the hypoglycemia, and infants with hypoglycemia were discharged on average 2 days earlier than those without, which suggests that the condition was self-limiting. The authors suggested monitoring neonatal blood glucose after betamethasone exposure in the late preterm period.  It will be important to answer questions about the long-term outcomes of this therapy, both benefits and risks, such as the potential reduction of chronic lung diseases or risk of developmental delay due to hypoglycemia [6].

Applications for Clinical Practice

This multicenter randomized controlled study provides strong evidence for administering antenatal glucocorticoids, such as betamethasone, in women at risk for late preterm delivery. Betamethasone administration significantly decreased the rate of respiratory complications in newborns, with the precaution to monitor for neonatal hypoglycemia.

 —Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To assess the effectiveness of an intervention that focused on the home environment to reduce energy intake and increase physical activity among overweight and obese women.

Design. Randomized controlled trial.

Setting and participants. Study participants were overweight and obese females recruited via their providers from 3 community health centers (9 clinical sites) in southwest Georgia. Only women were recruited because of their potential role as gatekeepers of the home environment. Inclusion criteria included being aged 35 to 65 years at baseline, living with at least one other person, and living no further than 30 miles from the referring clinic. Exclusion criteria included patients with conditions that could impact their ability to be physically active and pregnant women.

Intervention. Participants in the intervention arm received 3 home visits and 4 coaching calls over 16 weeks. Core elements of the intervention were informed by social-cognitive theory and included a tailored home environment profile, goal setting, behavioral contracting for 6 healthy actions, and supportive materials delivered via mail. Home visits and coaching calls were completed by health coaches with at least high-school education and experience in social or customer service who had completed 2 days of formal training by university staff. Control condition patients received 3 mailings of educational booklets at 6-week intervals that included government documents encouraging adoption of US dietary and physical activity guidelines. All participants completed baseline, 6- and 12-month follow-up telephone interviews and wore an accelerometer at baseline and 6-month follow-up. Intervention patients also received follow-up surveys assessing satisfaction with the coach, home visits, telephone calls, and support materials.

Main outcome measures. The main outcomes were energy intake (average daily kilocalories from two 24-hour dietary recalls) and physical activity (hours per week spent in moderate or vigorous physical activity using the 7-day physical activity recall). Self-reported height and weight was used to calculate body mass index (BMI). Secondary outcome measures included self-reported weight loss and aspects of the home environment. Home food environment was assessed by asking participants about the presence of 3 unhealthy drinks and 8 unhealthy foods and snacks in the home in the past week, if fruits and vegetables and high-calorie snack foods were kept in easy to see and reach places in the home, how often the family ate meals and snacks in front of the TV, how often participants served healthier food or prepared foods using healthy cooking methods, and asking the number of days family meals were purchased from outside the home. Home activity environment was assessed by asking about rules regarding limits on time spent watching TV, using a computer, playing video games, and using other hand-held devices. The authors adapted a 14-item inventory to assess personal exercise equipment accessibility and availability in the home. Community facility use was assessed with 9 survey items that assessed frequency of use and spaces for exercise in the participants’ neighborhoods.

Main results. A total of 948 patients were referred, of which 751 were reached by phone and assessed for eligibility. 81 did not meet inclusion criteria, 203 declined to participate, and 118 did not complete baseline data collection, leaving 349 participants. Of these, 177 were randomized to the control group, 172 to the intervention, and 21 dropped out. The majority of participants were African-American women (84.8%) with an average age of 50.2 years (SD = 8.1) and average BMI of 38.3kg/m² (SD = 8.4). Most were low income, with 68.7% reporting an annual household income under $25,000, and nearly 50% reported fair or poor general health. Roughly 45% were employed and 49% lived in a rural area. At 6 months, 82.5% of participants completed data collection (n = 288); at 12 months, 76.8% completed data collection (n = 268). Participants who did not complete follow-up through 12 months were either non-responders (6 months: n = 36, 12 months: n = 44), refused (6 months: n = 3, 12 months: n = 7), or died (6 months: n = 0, 12 months: n = 1).

Daily energy consumption significantly decreased in the intervention group compared to the control group at 6 months (–274 vs. –69 kcal/day, P = 0.003), however there was no meaningful change in self-reported moderate to vigorous physical activity nor was there significant change in physical activity measured by accelerometers at 6 months compared to baseline. For secondary outcomes, self-reported weight loss at 6 months was significantly higher among intervention patients (mean, –9.1 lb) compared to control patients (mean, –5.0 pounds) (SD = 13.7 pounds; P = 0.03). In addition, at 12 months, 82.6% of intervention patients had not gained weight compared with 71.4% of control patients (P = 0.03). Intervention patients made several changes to their home food environments compared to control patients. Intervention patients had reduced the number of unhealthy drink and snacks, increased purchasing of fruits and vegetables, and reduced the frequency of watching TV while eating. In addition, they also improved meal preparation and service and reduced the number of non-home meals eaten. For home activity environment, having exercise equipment in a visible location changed significantly more in the intervention group compared to the control group. Intervention patients also incorporated more physical activity into their daily lives compared to control patients, and created more exercise space in their homes and yards. There were no significant differences in screen time rules, use of community facilities and spaces, and family social support for physical activity.

Conclusion. A moderate-intensity, coach-delivered weight gain prevention intervention targeting the home environment led to reduced energy intake and improved home environments to better facilitate healthy living and weight loss.

Commentary

More than half of all US adults are considered overweight or obese [1].Changing health behaviors has the best potential for decreasing morbidity and mortality and for improving quality of life and this has been supported by the literature in a wide variety of behaviors including smoking cessation and weight loss [2–4]. Currently, most overweight and obese patients are treated through primary care provider–based (PCP) counseling or referral to clinic-based weight management interventions. However, barriers to PCP weight management counseling include physicians’ negative attitudes towards the personal attributes of individuals with weight management issues, lack of time, and poor nutrition counseling competency [5–7]. In addition, there are notable differences between providers’ and patients’ beliefs about weight and weight loss; providers tend to believe patients lack self-control, while patients largely feel they should manage their weight problems on their own and that counseling from a provider is unhelpful [8]. Many patients report feeling judged by their doctor because of their weight, and very few of those who feel judged and discuss weight loss options actually lose a clinically significant amount of weight [9]. Considering the many barriers to providing/receiving weight management counseling in the clinic setting, weight management techniques provided outside the doctor’s office may be a more effective and feasible alternative.

The most common causes of death are related to lifestyle behaviors such as poor dietary habits and inactivity [10]. Since most calories are consumed within the home [11] and the average person spends the majority of their time in the home [12], interventions that target home-life behaviors are needed to combat weight gain. The Kegler et al study suggests that a moderate-intensity intervention targeted at changing home eating and exercise behaviors will be effective in changing home environments and reducing energy intake. While the authors had a fairly specific population, these findings suggest that interventions that specifically target health behaviors at home may have more potential for success than merely educating patients on the benefits of a healthy lifestyle.

This study has several strengths including the randomized controlled trial design, the intention-to-treat analysis, and low attrition rates. In addition, the intervention achieved reduced energy intake and improved health behaviors in the home, supporting significant weight loss among intervention participants, especially compared to control patients. Both of these suggest high adherence to the intervention, which is a complex but crucial component of successful weight loss and weight management [13]. Finally, the inclusion of a wide variety of secondary outcomes helped to distinguish between specific home environment changes to discern which aspects of the intervention were most successful. A limitation of the study was that the population was nearly entirely African American and from clinics in rural Georgia, which limits generalizability. However, the success of the intervention in this population is critical, as African American adults are nearly 1.5 times more likely to be obese compared to white adults, and greater than 75% of African Americans are overweight or obese [14]. Additionally, while the study did have significant success with energy intake and eating habits, the intervention was less successful with changing physical activity habits, and physical activity and exercise training can significantly impact weight loss and maintenance [15]. A final limitation is the use of self-reported weight and behaviors, which can reduce reliability of these results.

Applications for Clinical Practice

This study suggests that interventions that target health behaviors in the home may achieve better energy intake and physical activity outcomes and improve weight loss compared to traditional educational counseling. Providers may want to consider brief counseling around improving the home environment as opposed to or in addition to counseling around improving nutrition or physical activity. More research is necessary to understand whether this type of intervention is feasible and acceptable in other populations (eg, urban, other races). In addition, further research is necessary to improve the physical activity component of the intervention. The use of non-clinical providers has been shown to be effective in improving health outcomes [16] and this study provides further evidence on the impactful role that trained community residents can have on changing behaviors. These initiatives are vital to supplement weight loss and management efforts occurring in the clinical setting.

—Natalie L. Ricci, Columbia University Mailman School of Public Health, and Katrina F. Mateo, MPH

Study Overview

Objective. To assess the effectiveness of an intervention that focused on the home environment to reduce energy intake and increase physical activity among overweight and obese women.

Design. Randomized controlled trial.

Setting and participants. Study participants were overweight and obese females recruited via their providers from 3 community health centers (9 clinical sites) in southwest Georgia. Only women were recruited because of their potential role as gatekeepers of the home environment. Inclusion criteria included being aged 35 to 65 years at baseline, living with at least one other person, and living no further than 30 miles from the referring clinic. Exclusion criteria included patients with conditions that could impact their ability to be physically active and pregnant women.

Intervention. Participants in the intervention arm received 3 home visits and 4 coaching calls over 16 weeks. Core elements of the intervention were informed by social-cognitive theory and included a tailored home environment profile, goal setting, behavioral contracting for 6 healthy actions, and supportive materials delivered via mail. Home visits and coaching calls were completed by health coaches with at least high-school education and experience in social or customer service who had completed 2 days of formal training by university staff. Control condition patients received 3 mailings of educational booklets at 6-week intervals that included government documents encouraging adoption of US dietary and physical activity guidelines. All participants completed baseline, 6- and 12-month follow-up telephone interviews and wore an accelerometer at baseline and 6-month follow-up. Intervention patients also received follow-up surveys assessing satisfaction with the coach, home visits, telephone calls, and support materials.

Main outcome measures. The main outcomes were energy intake (average daily kilocalories from two 24-hour dietary recalls) and physical activity (hours per week spent in moderate or vigorous physical activity using the 7-day physical activity recall). Self-reported height and weight was used to calculate body mass index (BMI). Secondary outcome measures included self-reported weight loss and aspects of the home environment. Home food environment was assessed by asking participants about the presence of 3 unhealthy drinks and 8 unhealthy foods and snacks in the home in the past week, if fruits and vegetables and high-calorie snack foods were kept in easy to see and reach places in the home, how often the family ate meals and snacks in front of the TV, how often participants served healthier food or prepared foods using healthy cooking methods, and asking the number of days family meals were purchased from outside the home. Home activity environment was assessed by asking about rules regarding limits on time spent watching TV, using a computer, playing video games, and using other hand-held devices. The authors adapted a 14-item inventory to assess personal exercise equipment accessibility and availability in the home. Community facility use was assessed with 9 survey items that assessed frequency of use and spaces for exercise in the participants’ neighborhoods.

Main results. A total of 948 patients were referred, of which 751 were reached by phone and assessed for eligibility. 81 did not meet inclusion criteria, 203 declined to participate, and 118 did not complete baseline data collection, leaving 349 participants. Of these, 177 were randomized to the control group, 172 to the intervention, and 21 dropped out. The majority of participants were African-American women (84.8%) with an average age of 50.2 years (SD = 8.1) and average BMI of 38.3kg/m² (SD = 8.4). Most were low income, with 68.7% reporting an annual household income under $25,000, and nearly 50% reported fair or poor general health. Roughly 45% were employed and 49% lived in a rural area. At 6 months, 82.5% of participants completed data collection (n = 288); at 12 months, 76.8% completed data collection (n = 268). Participants who did not complete follow-up through 12 months were either non-responders (6 months: n = 36, 12 months: n = 44), refused (6 months: n = 3, 12 months: n = 7), or died (6 months: n = 0, 12 months: n = 1).

Daily energy consumption significantly decreased in the intervention group compared to the control group at 6 months (–274 vs. –69 kcal/day, P = 0.003), however there was no meaningful change in self-reported moderate to vigorous physical activity nor was there significant change in physical activity measured by accelerometers at 6 months compared to baseline. For secondary outcomes, self-reported weight loss at 6 months was significantly higher among intervention patients (mean, –9.1 lb) compared to control patients (mean, –5.0 pounds) (SD = 13.7 pounds; P = 0.03). In addition, at 12 months, 82.6% of intervention patients had not gained weight compared with 71.4% of control patients (P = 0.03). Intervention patients made several changes to their home food environments compared to control patients. Intervention patients had reduced the number of unhealthy drink and snacks, increased purchasing of fruits and vegetables, and reduced the frequency of watching TV while eating. In addition, they also improved meal preparation and service and reduced the number of non-home meals eaten. For home activity environment, having exercise equipment in a visible location changed significantly more in the intervention group compared to the control group. Intervention patients also incorporated more physical activity into their daily lives compared to control patients, and created more exercise space in their homes and yards. There were no significant differences in screen time rules, use of community facilities and spaces, and family social support for physical activity.

Conclusion. A moderate-intensity, coach-delivered weight gain prevention intervention targeting the home environment led to reduced energy intake and improved home environments to better facilitate healthy living and weight loss.

Commentary

More than half of all US adults are considered overweight or obese [1].Changing health behaviors has the best potential for decreasing morbidity and mortality and for improving quality of life and this has been supported by the literature in a wide variety of behaviors including smoking cessation and weight loss [2–4]. Currently, most overweight and obese patients are treated through primary care provider–based (PCP) counseling or referral to clinic-based weight management interventions. However, barriers to PCP weight management counseling include physicians’ negative attitudes towards the personal attributes of individuals with weight management issues, lack of time, and poor nutrition counseling competency [5–7]. In addition, there are notable differences between providers’ and patients’ beliefs about weight and weight loss; providers tend to believe patients lack self-control, while patients largely feel they should manage their weight problems on their own and that counseling from a provider is unhelpful [8]. Many patients report feeling judged by their doctor because of their weight, and very few of those who feel judged and discuss weight loss options actually lose a clinically significant amount of weight [9]. Considering the many barriers to providing/receiving weight management counseling in the clinic setting, weight management techniques provided outside the doctor’s office may be a more effective and feasible alternative.

The most common causes of death are related to lifestyle behaviors such as poor dietary habits and inactivity [10]. Since most calories are consumed within the home [11] and the average person spends the majority of their time in the home [12], interventions that target home-life behaviors are needed to combat weight gain. The Kegler et al study suggests that a moderate-intensity intervention targeted at changing home eating and exercise behaviors will be effective in changing home environments and reducing energy intake. While the authors had a fairly specific population, these findings suggest that interventions that specifically target health behaviors at home may have more potential for success than merely educating patients on the benefits of a healthy lifestyle.

This study has several strengths including the randomized controlled trial design, the intention-to-treat analysis, and low attrition rates. In addition, the intervention achieved reduced energy intake and improved health behaviors in the home, supporting significant weight loss among intervention participants, especially compared to control patients. Both of these suggest high adherence to the intervention, which is a complex but crucial component of successful weight loss and weight management [13]. Finally, the inclusion of a wide variety of secondary outcomes helped to distinguish between specific home environment changes to discern which aspects of the intervention were most successful. A limitation of the study was that the population was nearly entirely African American and from clinics in rural Georgia, which limits generalizability. However, the success of the intervention in this population is critical, as African American adults are nearly 1.5 times more likely to be obese compared to white adults, and greater than 75% of African Americans are overweight or obese [14]. Additionally, while the study did have significant success with energy intake and eating habits, the intervention was less successful with changing physical activity habits, and physical activity and exercise training can significantly impact weight loss and maintenance [15]. A final limitation is the use of self-reported weight and behaviors, which can reduce reliability of these results.

Applications for Clinical Practice

This study suggests that interventions that target health behaviors in the home may achieve better energy intake and physical activity outcomes and improve weight loss compared to traditional educational counseling. Providers may want to consider brief counseling around improving the home environment as opposed to or in addition to counseling around improving nutrition or physical activity. More research is necessary to understand whether this type of intervention is feasible and acceptable in other populations (eg, urban, other races). In addition, further research is necessary to improve the physical activity component of the intervention. The use of non-clinical providers has been shown to be effective in improving health outcomes [16] and this study provides further evidence on the impactful role that trained community residents can have on changing behaviors. These initiatives are vital to supplement weight loss and management efforts occurring in the clinical setting.

—Natalie L. Ricci, Columbia University Mailman School of Public Health, and Katrina F. Mateo, MPH

Study Overview

Objective. To assess the effectiveness of an intervention that focused on the home environment to reduce energy intake and increase physical activity among overweight and obese women.

Design. Randomized controlled trial.

Setting and participants. Study participants were overweight and obese females recruited via their providers from 3 community health centers (9 clinical sites) in southwest Georgia. Only women were recruited because of their potential role as gatekeepers of the home environment. Inclusion criteria included being aged 35 to 65 years at baseline, living with at least one other person, and living no further than 30 miles from the referring clinic. Exclusion criteria included patients with conditions that could impact their ability to be physically active and pregnant women.

Intervention. Participants in the intervention arm received 3 home visits and 4 coaching calls over 16 weeks. Core elements of the intervention were informed by social-cognitive theory and included a tailored home environment profile, goal setting, behavioral contracting for 6 healthy actions, and supportive materials delivered via mail. Home visits and coaching calls were completed by health coaches with at least high-school education and experience in social or customer service who had completed 2 days of formal training by university staff. Control condition patients received 3 mailings of educational booklets at 6-week intervals that included government documents encouraging adoption of US dietary and physical activity guidelines. All participants completed baseline, 6- and 12-month follow-up telephone interviews and wore an accelerometer at baseline and 6-month follow-up. Intervention patients also received follow-up surveys assessing satisfaction with the coach, home visits, telephone calls, and support materials.

Main outcome measures. The main outcomes were energy intake (average daily kilocalories from two 24-hour dietary recalls) and physical activity (hours per week spent in moderate or vigorous physical activity using the 7-day physical activity recall). Self-reported height and weight was used to calculate body mass index (BMI). Secondary outcome measures included self-reported weight loss and aspects of the home environment. Home food environment was assessed by asking participants about the presence of 3 unhealthy drinks and 8 unhealthy foods and snacks in the home in the past week, if fruits and vegetables and high-calorie snack foods were kept in easy to see and reach places in the home, how often the family ate meals and snacks in front of the TV, how often participants served healthier food or prepared foods using healthy cooking methods, and asking the number of days family meals were purchased from outside the home. Home activity environment was assessed by asking about rules regarding limits on time spent watching TV, using a computer, playing video games, and using other hand-held devices. The authors adapted a 14-item inventory to assess personal exercise equipment accessibility and availability in the home. Community facility use was assessed with 9 survey items that assessed frequency of use and spaces for exercise in the participants’ neighborhoods.

Main results. A total of 948 patients were referred, of which 751 were reached by phone and assessed for eligibility. 81 did not meet inclusion criteria, 203 declined to participate, and 118 did not complete baseline data collection, leaving 349 participants. Of these, 177 were randomized to the control group, 172 to the intervention, and 21 dropped out. The majority of participants were African-American women (84.8%) with an average age of 50.2 years (SD = 8.1) and average BMI of 38.3kg/m² (SD = 8.4). Most were low income, with 68.7% reporting an annual household income under $25,000, and nearly 50% reported fair or poor general health. Roughly 45% were employed and 49% lived in a rural area. At 6 months, 82.5% of participants completed data collection (n = 288); at 12 months, 76.8% completed data collection (n = 268). Participants who did not complete follow-up through 12 months were either non-responders (6 months: n = 36, 12 months: n = 44), refused (6 months: n = 3, 12 months: n = 7), or died (6 months: n = 0, 12 months: n = 1).

Daily energy consumption significantly decreased in the intervention group compared to the control group at 6 months (–274 vs. –69 kcal/day, P = 0.003), however there was no meaningful change in self-reported moderate to vigorous physical activity nor was there significant change in physical activity measured by accelerometers at 6 months compared to baseline. For secondary outcomes, self-reported weight loss at 6 months was significantly higher among intervention patients (mean, –9.1 lb) compared to control patients (mean, –5.0 pounds) (SD = 13.7 pounds; P = 0.03). In addition, at 12 months, 82.6% of intervention patients had not gained weight compared with 71.4% of control patients (P = 0.03). Intervention patients made several changes to their home food environments compared to control patients. Intervention patients had reduced the number of unhealthy drink and snacks, increased purchasing of fruits and vegetables, and reduced the frequency of watching TV while eating. In addition, they also improved meal preparation and service and reduced the number of non-home meals eaten. For home activity environment, having exercise equipment in a visible location changed significantly more in the intervention group compared to the control group. Intervention patients also incorporated more physical activity into their daily lives compared to control patients, and created more exercise space in their homes and yards. There were no significant differences in screen time rules, use of community facilities and spaces, and family social support for physical activity.

Conclusion. A moderate-intensity, coach-delivered weight gain prevention intervention targeting the home environment led to reduced energy intake and improved home environments to better facilitate healthy living and weight loss.

Commentary

More than half of all US adults are considered overweight or obese [1].Changing health behaviors has the best potential for decreasing morbidity and mortality and for improving quality of life and this has been supported by the literature in a wide variety of behaviors including smoking cessation and weight loss [2–4]. Currently, most overweight and obese patients are treated through primary care provider–based (PCP) counseling or referral to clinic-based weight management interventions. However, barriers to PCP weight management counseling include physicians’ negative attitudes towards the personal attributes of individuals with weight management issues, lack of time, and poor nutrition counseling competency [5–7]. In addition, there are notable differences between providers’ and patients’ beliefs about weight and weight loss; providers tend to believe patients lack self-control, while patients largely feel they should manage their weight problems on their own and that counseling from a provider is unhelpful [8]. Many patients report feeling judged by their doctor because of their weight, and very few of those who feel judged and discuss weight loss options actually lose a clinically significant amount of weight [9]. Considering the many barriers to providing/receiving weight management counseling in the clinic setting, weight management techniques provided outside the doctor’s office may be a more effective and feasible alternative.

The most common causes of death are related to lifestyle behaviors such as poor dietary habits and inactivity [10]. Since most calories are consumed within the home [11] and the average person spends the majority of their time in the home [12], interventions that target home-life behaviors are needed to combat weight gain. The Kegler et al study suggests that a moderate-intensity intervention targeted at changing home eating and exercise behaviors will be effective in changing home environments and reducing energy intake. While the authors had a fairly specific population, these findings suggest that interventions that specifically target health behaviors at home may have more potential for success than merely educating patients on the benefits of a healthy lifestyle.

This study has several strengths including the randomized controlled trial design, the intention-to-treat analysis, and low attrition rates. In addition, the intervention achieved reduced energy intake and improved health behaviors in the home, supporting significant weight loss among intervention participants, especially compared to control patients. Both of these suggest high adherence to the intervention, which is a complex but crucial component of successful weight loss and weight management [13]. Finally, the inclusion of a wide variety of secondary outcomes helped to distinguish between specific home environment changes to discern which aspects of the intervention were most successful. A limitation of the study was that the population was nearly entirely African American and from clinics in rural Georgia, which limits generalizability. However, the success of the intervention in this population is critical, as African American adults are nearly 1.5 times more likely to be obese compared to white adults, and greater than 75% of African Americans are overweight or obese [14]. Additionally, while the study did have significant success with energy intake and eating habits, the intervention was less successful with changing physical activity habits, and physical activity and exercise training can significantly impact weight loss and maintenance [15]. A final limitation is the use of self-reported weight and behaviors, which can reduce reliability of these results.

Applications for Clinical Practice

This study suggests that interventions that target health behaviors in the home may achieve better energy intake and physical activity outcomes and improve weight loss compared to traditional educational counseling. Providers may want to consider brief counseling around improving the home environment as opposed to or in addition to counseling around improving nutrition or physical activity. More research is necessary to understand whether this type of intervention is feasible and acceptable in other populations (eg, urban, other races). In addition, further research is necessary to improve the physical activity component of the intervention. The use of non-clinical providers has been shown to be effective in improving health outcomes [16] and this study provides further evidence on the impactful role that trained community residents can have on changing behaviors. These initiatives are vital to supplement weight loss and management efforts occurring in the clinical setting.

—Natalie L. Ricci, Columbia University Mailman School of Public Health, and Katrina F. Mateo, MPH