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Targeting the Home Environment May Help with Weight Control
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
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015;175:1412–3.
2. Koop EC. Health promotion and disease prevention in clinical practice. In: Lawrence RS, Woolf SH, Jonas S, editors. Health promotion and disease prevention in clinical practice. Baltimore: Williams & Wilkins; 1996: vii-ix.
3. Laniado-Laborin R. Smoking cessation intervention: an evidence-based approach. Postgrad Med 2010;122:74–82.
4. Winter SJ, Sheats JL, King AC. The use of behavior change techniques and theory in technologies for cardiovascular disease prevention and treatment in adults: a comprehensive review. Prog Cardiovasc Dis 2016. Epub ahead of print.
5. Foster GD, Wadden TA, Makris AP, et al. Primary care physicians’ attitudes about obesity and its treatment. Obesity Res 2007;11:1168–77.
6. Jay M, Chintapalli S, Squires A, et al. Barriers and facilitators to providing primary care-based weight management services in a patient centered medical home for veterans: a qualitative study. BMC Fam Pract 2015;16:167.
7. Jay M, Gillespie C, Ark T, et al. Do internists, pediatricians, and psychiatrists feel competent in obesity care? Using a needs assessment to drive curriculum design. J Gen Intern Med 2008;23:1066–70.
8. Ruelaz AR, Diefenbach P, Simon B, et al. Perceived barriers to weight management in primary care—perspectives of patients and providers. J Gen Intern Med 2007;22:518–22.
9. Gudzune KA, Bennett WL, Cooper LA, Bleich SN. Perceived judgment about weight can negatively influence weight loss: A cross-sectional study of overweight and obese patients. Prev Med 2014;62:103–7.
10. McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA 1993;27:2207–12.
11. Lin B-H, Guthrie J. Nutritional quality of food prepared at home and away from home, 1977-2008. Washington, DC: US Department of Agriculture, Economic Research Service; 2012.
12. Bureau of Labor Statistics, US Department of Labor. American time use survey – 2014 results. Accessed 1 Mar 2016 at www.bls.gov/nes.release/pdf/atus.pdf.
13. Hays RD, Kravitz RL, Mazel RM, et al. The impact of patient adherence on health outcomes for patients with chronic disease in the medical outcomes study. J Behav Med 1994;17:347–60.
14. Obesity prevention in black communities. The state of obesity. Accessed 2 Mar 2016 at http://stateofobesity.org/disparities/blacks/
15. Swift DL, Johannsen NM, Lavie CJ, et al. The role of exercise and physical activity in weight loss and maintenance. Prog Cardiovasc Dis 2014;56:441–7.
16. Dye CJ, Williams JE, Evatt JH. Improving hypertension self-management with community health coaches. Health Prom Pract 2015;16:271–81.
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
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015;175:1412–3.
2. Koop EC. Health promotion and disease prevention in clinical practice. In: Lawrence RS, Woolf SH, Jonas S, editors. Health promotion and disease prevention in clinical practice. Baltimore: Williams & Wilkins; 1996: vii-ix.
3. Laniado-Laborin R. Smoking cessation intervention: an evidence-based approach. Postgrad Med 2010;122:74–82.
4. Winter SJ, Sheats JL, King AC. The use of behavior change techniques and theory in technologies for cardiovascular disease prevention and treatment in adults: a comprehensive review. Prog Cardiovasc Dis 2016. Epub ahead of print.
5. Foster GD, Wadden TA, Makris AP, et al. Primary care physicians’ attitudes about obesity and its treatment. Obesity Res 2007;11:1168–77.
6. Jay M, Chintapalli S, Squires A, et al. Barriers and facilitators to providing primary care-based weight management services in a patient centered medical home for veterans: a qualitative study. BMC Fam Pract 2015;16:167.
7. Jay M, Gillespie C, Ark T, et al. Do internists, pediatricians, and psychiatrists feel competent in obesity care? Using a needs assessment to drive curriculum design. J Gen Intern Med 2008;23:1066–70.
8. Ruelaz AR, Diefenbach P, Simon B, et al. Perceived barriers to weight management in primary care—perspectives of patients and providers. J Gen Intern Med 2007;22:518–22.
9. Gudzune KA, Bennett WL, Cooper LA, Bleich SN. Perceived judgment about weight can negatively influence weight loss: A cross-sectional study of overweight and obese patients. Prev Med 2014;62:103–7.
10. McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA 1993;27:2207–12.
11. Lin B-H, Guthrie J. Nutritional quality of food prepared at home and away from home, 1977-2008. Washington, DC: US Department of Agriculture, Economic Research Service; 2012.
12. Bureau of Labor Statistics, US Department of Labor. American time use survey – 2014 results. Accessed 1 Mar 2016 at www.bls.gov/nes.release/pdf/atus.pdf.
13. Hays RD, Kravitz RL, Mazel RM, et al. The impact of patient adherence on health outcomes for patients with chronic disease in the medical outcomes study. J Behav Med 1994;17:347–60.
14. Obesity prevention in black communities. The state of obesity. Accessed 2 Mar 2016 at http://stateofobesity.org/disparities/blacks/
15. Swift DL, Johannsen NM, Lavie CJ, et al. The role of exercise and physical activity in weight loss and maintenance. Prog Cardiovasc Dis 2014;56:441–7.
16. Dye CJ, Williams JE, Evatt JH. Improving hypertension self-management with community health coaches. Health Prom Pract 2015;16:271–81.
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015;175:1412–3.
2. Koop EC. Health promotion and disease prevention in clinical practice. In: Lawrence RS, Woolf SH, Jonas S, editors. Health promotion and disease prevention in clinical practice. Baltimore: Williams & Wilkins; 1996: vii-ix.
3. Laniado-Laborin R. Smoking cessation intervention: an evidence-based approach. Postgrad Med 2010;122:74–82.
4. Winter SJ, Sheats JL, King AC. The use of behavior change techniques and theory in technologies for cardiovascular disease prevention and treatment in adults: a comprehensive review. Prog Cardiovasc Dis 2016. Epub ahead of print.
5. Foster GD, Wadden TA, Makris AP, et al. Primary care physicians’ attitudes about obesity and its treatment. Obesity Res 2007;11:1168–77.
6. Jay M, Chintapalli S, Squires A, et al. Barriers and facilitators to providing primary care-based weight management services in a patient centered medical home for veterans: a qualitative study. BMC Fam Pract 2015;16:167.
7. Jay M, Gillespie C, Ark T, et al. Do internists, pediatricians, and psychiatrists feel competent in obesity care? Using a needs assessment to drive curriculum design. J Gen Intern Med 2008;23:1066–70.
8. Ruelaz AR, Diefenbach P, Simon B, et al. Perceived barriers to weight management in primary care—perspectives of patients and providers. J Gen Intern Med 2007;22:518–22.
9. Gudzune KA, Bennett WL, Cooper LA, Bleich SN. Perceived judgment about weight can negatively influence weight loss: A cross-sectional study of overweight and obese patients. Prev Med 2014;62:103–7.
10. McGinnis JM, Foege WH. Actual causes of death in the United States. JAMA 1993;27:2207–12.
11. Lin B-H, Guthrie J. Nutritional quality of food prepared at home and away from home, 1977-2008. Washington, DC: US Department of Agriculture, Economic Research Service; 2012.
12. Bureau of Labor Statistics, US Department of Labor. American time use survey – 2014 results. Accessed 1 Mar 2016 at www.bls.gov/nes.release/pdf/atus.pdf.
13. Hays RD, Kravitz RL, Mazel RM, et al. The impact of patient adherence on health outcomes for patients with chronic disease in the medical outcomes study. J Behav Med 1994;17:347–60.
14. Obesity prevention in black communities. The state of obesity. Accessed 2 Mar 2016 at http://stateofobesity.org/disparities/blacks/
15. Swift DL, Johannsen NM, Lavie CJ, et al. The role of exercise and physical activity in weight loss and maintenance. Prog Cardiovasc Dis 2014;56:441–7.
16. Dye CJ, Williams JE, Evatt JH. Improving hypertension self-management with community health coaches. Health Prom Pract 2015;16:271–81.
Fast and Furious: Rapid Weight Loss Via a Very Low Calorie Diet May Lead to Better Long-Term Outcomes Than a Gradual Weight Loss Program
Study Overview
Objective. To determine if the rate at which a person loses weight impacts long-term weight management.
Design. Two-phase, non-masked, randomized controlled trial.
Setting and participants. Study participants were recruited through radio and newspaper advertisements and word of mouth in Melbourne, Australia. Eligible participants were randomized into 2 different weight loss programs—a 12-week rapid program or a 36-week gradual program—using a computer-generated randomization sequence with a block design to account for the potential confounding factors of age, sex, and body mass index (BMI). Investigators and laboratory staff were blind to the group assignments. Inclusion criteria were healthy men and women aged between 18–70 years who were weight stable for 3 months and had a BMI between 30.0–45.0kg/m2. Exclusion criteria included use of a very low energy diet or weight loss drugs in the previous 3 months, contraceptive use, pregnancy or lactation, smoking, current use of drugs known to affect body weight, previous weight loss surgery, and the presence of clinically significant disease (including diabetes).
Intervention. Participants were randomized to the rapid or gradual weight loss program, both with the stated goal of 15% weight loss. For phase 1, participants in the rapid weight loss group replaced 3 meals a day with a commercially available meal replacement (Optifast, Nestlé Nutrition) over a period of 12 weeks (450–800 kcal/day). Participants in the gradual group replaced 1 to 2 meals daily with the same supplements and followed a diet program based on recommendations from the Australian Guide to Healthy Eating for the other meals over a period of 36 weeks (400–500 kcal deficit per day). Both groups were given comparable dietary education materials and had appointments every 2 weeks with the same dietician. Participants who achieved 12.5% or greater weight loss were eligible for phase 2. In phase 2, participants met with their same dietician at weeks 4 and 12, and then every 12 weeks until week 144. During appointments, the dietician assessed adherence based on participants’ self-reported food intake, and participants were encouraged to partake in 30 minutes of physical activity of mild to moderate intensity. Participants who gained weight were given a 400–500 kcal deficit diet.
Main outcome measures. The main outcome was mean weight loss maintained at week 144 of phase 2. Secondary outcomes were mean difference in fasting ghrelin and leptin concentrations measured at baseline, end of phase 1 (week 12 for rapid and week 36 for gradual), and at weeks 48 and 144 of phase 2. The authors examined the following changes from baseline: weight, BMI, waist and hip circumferences, fat mass, fat free mass, ghrelin, leptin, and physical activity (steps per day). A standardized protocol was followed for all measurements.
Results. Researchers evaluated 525 participants, of which 321 were excluded for ineligibility, being unwilling to participate, or having type 2 diabetes. Of the 204, 4 dropped out after randomization leaving 97 in the rapid weight loss group and 103 in the gradual group during phase 1. The mean age of participants was 49.8 (SD = 10.9) years with 25.5% men. There were no significant demographic or weight differences between the 2 groups. The completion rate for phase 1 was 94% in the rapid program and 82% of the gradual program. The mean phase 1 weight changes in the rapid and gradual program groups were –13 kg and –8.9 kg, respectively. A higher proportion of participants in the rapid weight loss group lost 12.5% or more of their weight than in the gradual group (76/97 vs. 53/103). 127 participants entered phase 2 of the study (2 in the gradual group who lost 12.5% body weight before 12 weeks were excluded). 1 participant in the rapid group developed cholecystitis requiring cholecystectomy.
In Phase 2, seven participants in the rapid group withdrew due to logistical issues, psychological stress, and other health-related issues; 4 participants in the gradual group withdrew for the same reasons, as well as pregnancy. 2 participants from the rapid group developed cancer. All but 6 participants regained weight (5 in rapid group, 1 in gradual group) and were put on a 400-500 kcal deficit diet. There was no significant difference in mean weight regain of the rapid and gradual participants. By week 144 of phase 2, average weight regain in the gradual group was 10.4 kg (95% confidence interval [CI] 8.4–12.4; 71.2% of lost weight regained, CI 58.1–84.3) and 10.3 kg in rapid weight loss participants (95% CI 8.5–12.1; 70.5% of lost weight regained, CI 57.8–83.2). This result did not change significantly in the intention to treat analysis where dropouts were assumed to return to baseline.
During phase 2, leptin concentrations increased in both groups, and there was no difference in leptin concentrations between the 2 groups at weeks 48 and 144, nor were they significantly different from baseline at week 48. Ghrelin concentrations increased in both groups from baseline, but there was no significant difference between the groups at the end of 144 weeks.
Conclusion. In highly selected Australian participants, rapid weight loss (12 weeks) using a very low calorie meal replacement program led to greater weight loss than a gradual weight loss program (36 weeks) using a combination of meal replacements and diet recommendations. In participants who lost 12.5% or greater body weight, the speed at which participants regained weight was similar in both groups.
Commentary
Obesity rates have increased globally over the past 20 years. In the United States, Yang and Colditz found that approximately 35% of men and 37% of women are obese and approximately 40% of men and 30% of women are overweight, marking the first time that obese Americans outnumber overweight Americans [1]. Approximately 45 million Americans diet each year, and Americans spend $33 billion on weight-loss products annually. Thus, we need to determine the most effective and cost-effective weight management practices. The Purcell et al study suggests that a 12-week intervention may lead to greater weight loss and better adherence than a 36-week program, and that weight regain in participants achieving 12.5% or greater weight loss may be the same in both interventions. While they did not formally evaluate cost effectiveness, these findings suggest that a rapid weight loss program through a very low calorie diet (VLCD) may be more cost-effective since they achieved better results in a shorter period of time. However, caution must be taken before universally recommending VLCDs to promote rapid weight loss.
Many organizations advise patients to lose weight slowly to increase their chances of reaching weight loss goals and long-term success. The American Heart Association, American College of Cardiology, and The Obesity Society (AHA/ACC/TOS) guidelines for the management of overweight and obesity in adults recommend 3 types of diets for weight loss: a 1200–1800 calorie diet, depending on weight and gender; a 500 kcal/day or 750kcal/day energy deficit, or an evidence-based diet that restricts specific food types (such as high-carbohydrate foods) [2]. These guidelines also state that individuals likely need to follow lifestyle changes for more than 6 months to increase their chances of achieving weight loss goals [2]. They acknowledge maximum weight loss is typically achieved at 6 months, and is commonly followed by plateau and gradual regain [2]. The US Preventive Services Task Force (USPSTF) also advises gradual weight loss [3].
The results of the Purcell et al study and others provide evidence that contradicts these recommendations. For example, Nackers et al found that people who lost weight quickly achieved and maintained greater weight loss than participants who lost weight gradually [4]. Further, those who lost weight rapidly were no more susceptible to regaining weight than people who lost weight gradually [4]. Toburo and Astrup also found the rate of initial weight loss had no impact on the long-term outcomes of weight maintenance [5]. Astrup and Rössner found initial weight loss was positively associated with long-term weight maintenance, and rapid weight loss resulted in improved sustained weight maintenance [6]. Finally, Wing and Phelan found the best predictor of weight regain was the length of time weight loss was maintained, not how the weight was lost [7].
VCLDs replace regular meals with prepared formulas to promote rapid weight loss, and are not recommended for the mildly obese or overweight. VLCDs have been shown to greatly reduce cardiovascular risk factors and relieve obesity-related symptoms; however, they result in more side effects compared to a low calorie diet [8]. Individuals who follow VLCDs must be monitored regularly to ensure they do not experience serious side effects, such as gallstones, electrolyte imbalance that can cause muscle and nerve malfunction, and an irregular heartbeat [9]. Indeed, 1 patient in the rapid group required a cholecystectomy. The providers in this study were obesity specialists, which may account for the strong outcomes and relatively few adverse events.
This study has many strengths. First, researchers achieved low rates of attrition (22% compared to about 40% in other studies) [9,10]. This study also followed participants for 2 years post-intervention and achieved high rates of weight loss in both groups. In addition to low dropout rates and long-term follow-up, the population was highly adherent to each intervention. Limitations of the study include that the authors were highly selective in choosing participants—none of the participants had obesity-related comorbidities such as diabetes or significant medical conditions. Individuals with these conditions may not be able to follow the dietary recommendations used in this study, restricting generalizability from a population that is largely overweight and obese. Further, all participants were from Melbourne, Australia. Since the authors did not provide data on race/ethnicity, we can assume a relatively homogeneous population, further limiting generalizability.
Applications for Clinical Practice
This study suggests that rapid weight loss through VLCDs may achieve better weight loss outcomes and adherence when compared to more gradual programs without resulting in higher weight regain over time in highly selected patients treated by obesity specialists. Caution must be advised since primary care practitioners may not have sufficient training to deliver these diets. VLCDs have higher risk of gallstones and other adverse outcomes such as gout or cardiac events [11,12]. A more gradual weight loss program, similar to the 36-week program in the Purcell et al study, used meal replacements and achieved outcomes that were relatively high, with 72% achieving at least 5% weight loss, and 19% achieving 15% weight loss or greater (P < 0.001) [13]. Indeed, meal replacements of 1 to 2 meals per day have been shown to be safe and effective in primary care [14]. Current AHA/ACC/TOS guidelines on VLCDs are inconclusive, stating there is insufficient evidence to comment on the value of VLCDs, or on strategies to provide more supervision of adherence to these diets [2]. Thus, practitioners without training in the use of VLCDs should still follow USPSTF and other recommendations to promote gradual weight loss [2]. However, if patients want to lose weight faster with a VLCD, then providers can refer them to an obesity specialist since this may promote greater adherence and long-term weight maintenance in select patients.
—Natalie L. Ricci, Mailman School of Public Health, New York, NY, and Melanie Jay, MD, MS
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015 Jun 22.
2. Jensen MD, Ryan DH, Apovian CM, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. Circulation 2014;129(25 Suppl 2):S102–38.
3. Final recommendation statement: Obesity in adults: screening and management, June 2012. U.S. Preventive Services Task Force. Available at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/obesity-in-adults-screening-and-management.
4. Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med 2010;17:161–7.
5. Toubro S, Astrup A. Randomised comparison of diets for maintaining obese subjects’ weight after major weight loss: ad lib, low fat, high carbohydrate diet v fixed energy intake. BMJ 1997;314:29–34.
6. Astrup A, Rössner S. Lessons from obesity management programmes: greater initial weight loss improves long-term maintenance. Obes Rev 2000;1:17–9.
7. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr 2005;82(1 Suppl):222S–225S.
8. Christensen P, Bliddal H, Riecke BF, et al. Comparison of a low-energy diet and a very low-energy diet in sedentary obese individuals: a pragmatic randomized controlled trial. Clin Obes 2011;1:31–40.
9. Anderson JW, Hamilton CC, Brinkman-Kaplan V. Benefits and risks of an intensive very-low-calorie diet program for severe obesity. Am J Gastroenterol 1992;87:6–15.
10. Ditschuneit HH, Flechtner-Mors M, Johnson TD, Adler G. Metabolic and weight-loss effects of a long-term dietary intervention in obese patients. Am J Clin Nutr 1999;69:198–204.
11. Rössner S, Flaten H. VLCD versus LCD in long-term treatment of obesity. Int J Obes Relat Metab Disord 1997;21:22–6.
12. Weinsier RL, Ullmann DO. Gallstone formation and weight loss. Obes Res 1993;1:51–6.
13. Kruschitz R, Wallner-Liebmann SJ, Lothaller H, et al. Evaluation of a meal replacement-based weight management program in primary care settings according to the actual European clinical practice guidelines for the management of obesity in adults. Wien Klin Wochenschr 2014;126:598–603.
14. Haas WC, Moore JB, Kaplan M, Lazorick S. Outcomes from a medical weight loss program: primary care clinics versus weight loss clinics. Am J Med 2012;125:603.e7–11.
Study Overview
Objective. To determine if the rate at which a person loses weight impacts long-term weight management.
Design. Two-phase, non-masked, randomized controlled trial.
Setting and participants. Study participants were recruited through radio and newspaper advertisements and word of mouth in Melbourne, Australia. Eligible participants were randomized into 2 different weight loss programs—a 12-week rapid program or a 36-week gradual program—using a computer-generated randomization sequence with a block design to account for the potential confounding factors of age, sex, and body mass index (BMI). Investigators and laboratory staff were blind to the group assignments. Inclusion criteria were healthy men and women aged between 18–70 years who were weight stable for 3 months and had a BMI between 30.0–45.0kg/m2. Exclusion criteria included use of a very low energy diet or weight loss drugs in the previous 3 months, contraceptive use, pregnancy or lactation, smoking, current use of drugs known to affect body weight, previous weight loss surgery, and the presence of clinically significant disease (including diabetes).
Intervention. Participants were randomized to the rapid or gradual weight loss program, both with the stated goal of 15% weight loss. For phase 1, participants in the rapid weight loss group replaced 3 meals a day with a commercially available meal replacement (Optifast, Nestlé Nutrition) over a period of 12 weeks (450–800 kcal/day). Participants in the gradual group replaced 1 to 2 meals daily with the same supplements and followed a diet program based on recommendations from the Australian Guide to Healthy Eating for the other meals over a period of 36 weeks (400–500 kcal deficit per day). Both groups were given comparable dietary education materials and had appointments every 2 weeks with the same dietician. Participants who achieved 12.5% or greater weight loss were eligible for phase 2. In phase 2, participants met with their same dietician at weeks 4 and 12, and then every 12 weeks until week 144. During appointments, the dietician assessed adherence based on participants’ self-reported food intake, and participants were encouraged to partake in 30 minutes of physical activity of mild to moderate intensity. Participants who gained weight were given a 400–500 kcal deficit diet.
Main outcome measures. The main outcome was mean weight loss maintained at week 144 of phase 2. Secondary outcomes were mean difference in fasting ghrelin and leptin concentrations measured at baseline, end of phase 1 (week 12 for rapid and week 36 for gradual), and at weeks 48 and 144 of phase 2. The authors examined the following changes from baseline: weight, BMI, waist and hip circumferences, fat mass, fat free mass, ghrelin, leptin, and physical activity (steps per day). A standardized protocol was followed for all measurements.
Results. Researchers evaluated 525 participants, of which 321 were excluded for ineligibility, being unwilling to participate, or having type 2 diabetes. Of the 204, 4 dropped out after randomization leaving 97 in the rapid weight loss group and 103 in the gradual group during phase 1. The mean age of participants was 49.8 (SD = 10.9) years with 25.5% men. There were no significant demographic or weight differences between the 2 groups. The completion rate for phase 1 was 94% in the rapid program and 82% of the gradual program. The mean phase 1 weight changes in the rapid and gradual program groups were –13 kg and –8.9 kg, respectively. A higher proportion of participants in the rapid weight loss group lost 12.5% or more of their weight than in the gradual group (76/97 vs. 53/103). 127 participants entered phase 2 of the study (2 in the gradual group who lost 12.5% body weight before 12 weeks were excluded). 1 participant in the rapid group developed cholecystitis requiring cholecystectomy.
In Phase 2, seven participants in the rapid group withdrew due to logistical issues, psychological stress, and other health-related issues; 4 participants in the gradual group withdrew for the same reasons, as well as pregnancy. 2 participants from the rapid group developed cancer. All but 6 participants regained weight (5 in rapid group, 1 in gradual group) and were put on a 400-500 kcal deficit diet. There was no significant difference in mean weight regain of the rapid and gradual participants. By week 144 of phase 2, average weight regain in the gradual group was 10.4 kg (95% confidence interval [CI] 8.4–12.4; 71.2% of lost weight regained, CI 58.1–84.3) and 10.3 kg in rapid weight loss participants (95% CI 8.5–12.1; 70.5% of lost weight regained, CI 57.8–83.2). This result did not change significantly in the intention to treat analysis where dropouts were assumed to return to baseline.
During phase 2, leptin concentrations increased in both groups, and there was no difference in leptin concentrations between the 2 groups at weeks 48 and 144, nor were they significantly different from baseline at week 48. Ghrelin concentrations increased in both groups from baseline, but there was no significant difference between the groups at the end of 144 weeks.
Conclusion. In highly selected Australian participants, rapid weight loss (12 weeks) using a very low calorie meal replacement program led to greater weight loss than a gradual weight loss program (36 weeks) using a combination of meal replacements and diet recommendations. In participants who lost 12.5% or greater body weight, the speed at which participants regained weight was similar in both groups.
Commentary
Obesity rates have increased globally over the past 20 years. In the United States, Yang and Colditz found that approximately 35% of men and 37% of women are obese and approximately 40% of men and 30% of women are overweight, marking the first time that obese Americans outnumber overweight Americans [1]. Approximately 45 million Americans diet each year, and Americans spend $33 billion on weight-loss products annually. Thus, we need to determine the most effective and cost-effective weight management practices. The Purcell et al study suggests that a 12-week intervention may lead to greater weight loss and better adherence than a 36-week program, and that weight regain in participants achieving 12.5% or greater weight loss may be the same in both interventions. While they did not formally evaluate cost effectiveness, these findings suggest that a rapid weight loss program through a very low calorie diet (VLCD) may be more cost-effective since they achieved better results in a shorter period of time. However, caution must be taken before universally recommending VLCDs to promote rapid weight loss.
Many organizations advise patients to lose weight slowly to increase their chances of reaching weight loss goals and long-term success. The American Heart Association, American College of Cardiology, and The Obesity Society (AHA/ACC/TOS) guidelines for the management of overweight and obesity in adults recommend 3 types of diets for weight loss: a 1200–1800 calorie diet, depending on weight and gender; a 500 kcal/day or 750kcal/day energy deficit, or an evidence-based diet that restricts specific food types (such as high-carbohydrate foods) [2]. These guidelines also state that individuals likely need to follow lifestyle changes for more than 6 months to increase their chances of achieving weight loss goals [2]. They acknowledge maximum weight loss is typically achieved at 6 months, and is commonly followed by plateau and gradual regain [2]. The US Preventive Services Task Force (USPSTF) also advises gradual weight loss [3].
The results of the Purcell et al study and others provide evidence that contradicts these recommendations. For example, Nackers et al found that people who lost weight quickly achieved and maintained greater weight loss than participants who lost weight gradually [4]. Further, those who lost weight rapidly were no more susceptible to regaining weight than people who lost weight gradually [4]. Toburo and Astrup also found the rate of initial weight loss had no impact on the long-term outcomes of weight maintenance [5]. Astrup and Rössner found initial weight loss was positively associated with long-term weight maintenance, and rapid weight loss resulted in improved sustained weight maintenance [6]. Finally, Wing and Phelan found the best predictor of weight regain was the length of time weight loss was maintained, not how the weight was lost [7].
VCLDs replace regular meals with prepared formulas to promote rapid weight loss, and are not recommended for the mildly obese or overweight. VLCDs have been shown to greatly reduce cardiovascular risk factors and relieve obesity-related symptoms; however, they result in more side effects compared to a low calorie diet [8]. Individuals who follow VLCDs must be monitored regularly to ensure they do not experience serious side effects, such as gallstones, electrolyte imbalance that can cause muscle and nerve malfunction, and an irregular heartbeat [9]. Indeed, 1 patient in the rapid group required a cholecystectomy. The providers in this study were obesity specialists, which may account for the strong outcomes and relatively few adverse events.
This study has many strengths. First, researchers achieved low rates of attrition (22% compared to about 40% in other studies) [9,10]. This study also followed participants for 2 years post-intervention and achieved high rates of weight loss in both groups. In addition to low dropout rates and long-term follow-up, the population was highly adherent to each intervention. Limitations of the study include that the authors were highly selective in choosing participants—none of the participants had obesity-related comorbidities such as diabetes or significant medical conditions. Individuals with these conditions may not be able to follow the dietary recommendations used in this study, restricting generalizability from a population that is largely overweight and obese. Further, all participants were from Melbourne, Australia. Since the authors did not provide data on race/ethnicity, we can assume a relatively homogeneous population, further limiting generalizability.
Applications for Clinical Practice
This study suggests that rapid weight loss through VLCDs may achieve better weight loss outcomes and adherence when compared to more gradual programs without resulting in higher weight regain over time in highly selected patients treated by obesity specialists. Caution must be advised since primary care practitioners may not have sufficient training to deliver these diets. VLCDs have higher risk of gallstones and other adverse outcomes such as gout or cardiac events [11,12]. A more gradual weight loss program, similar to the 36-week program in the Purcell et al study, used meal replacements and achieved outcomes that were relatively high, with 72% achieving at least 5% weight loss, and 19% achieving 15% weight loss or greater (P < 0.001) [13]. Indeed, meal replacements of 1 to 2 meals per day have been shown to be safe and effective in primary care [14]. Current AHA/ACC/TOS guidelines on VLCDs are inconclusive, stating there is insufficient evidence to comment on the value of VLCDs, or on strategies to provide more supervision of adherence to these diets [2]. Thus, practitioners without training in the use of VLCDs should still follow USPSTF and other recommendations to promote gradual weight loss [2]. However, if patients want to lose weight faster with a VLCD, then providers can refer them to an obesity specialist since this may promote greater adherence and long-term weight maintenance in select patients.
—Natalie L. Ricci, Mailman School of Public Health, New York, NY, and Melanie Jay, MD, MS
Study Overview
Objective. To determine if the rate at which a person loses weight impacts long-term weight management.
Design. Two-phase, non-masked, randomized controlled trial.
Setting and participants. Study participants were recruited through radio and newspaper advertisements and word of mouth in Melbourne, Australia. Eligible participants were randomized into 2 different weight loss programs—a 12-week rapid program or a 36-week gradual program—using a computer-generated randomization sequence with a block design to account for the potential confounding factors of age, sex, and body mass index (BMI). Investigators and laboratory staff were blind to the group assignments. Inclusion criteria were healthy men and women aged between 18–70 years who were weight stable for 3 months and had a BMI between 30.0–45.0kg/m2. Exclusion criteria included use of a very low energy diet or weight loss drugs in the previous 3 months, contraceptive use, pregnancy or lactation, smoking, current use of drugs known to affect body weight, previous weight loss surgery, and the presence of clinically significant disease (including diabetes).
Intervention. Participants were randomized to the rapid or gradual weight loss program, both with the stated goal of 15% weight loss. For phase 1, participants in the rapid weight loss group replaced 3 meals a day with a commercially available meal replacement (Optifast, Nestlé Nutrition) over a period of 12 weeks (450–800 kcal/day). Participants in the gradual group replaced 1 to 2 meals daily with the same supplements and followed a diet program based on recommendations from the Australian Guide to Healthy Eating for the other meals over a period of 36 weeks (400–500 kcal deficit per day). Both groups were given comparable dietary education materials and had appointments every 2 weeks with the same dietician. Participants who achieved 12.5% or greater weight loss were eligible for phase 2. In phase 2, participants met with their same dietician at weeks 4 and 12, and then every 12 weeks until week 144. During appointments, the dietician assessed adherence based on participants’ self-reported food intake, and participants were encouraged to partake in 30 minutes of physical activity of mild to moderate intensity. Participants who gained weight were given a 400–500 kcal deficit diet.
Main outcome measures. The main outcome was mean weight loss maintained at week 144 of phase 2. Secondary outcomes were mean difference in fasting ghrelin and leptin concentrations measured at baseline, end of phase 1 (week 12 for rapid and week 36 for gradual), and at weeks 48 and 144 of phase 2. The authors examined the following changes from baseline: weight, BMI, waist and hip circumferences, fat mass, fat free mass, ghrelin, leptin, and physical activity (steps per day). A standardized protocol was followed for all measurements.
Results. Researchers evaluated 525 participants, of which 321 were excluded for ineligibility, being unwilling to participate, or having type 2 diabetes. Of the 204, 4 dropped out after randomization leaving 97 in the rapid weight loss group and 103 in the gradual group during phase 1. The mean age of participants was 49.8 (SD = 10.9) years with 25.5% men. There were no significant demographic or weight differences between the 2 groups. The completion rate for phase 1 was 94% in the rapid program and 82% of the gradual program. The mean phase 1 weight changes in the rapid and gradual program groups were –13 kg and –8.9 kg, respectively. A higher proportion of participants in the rapid weight loss group lost 12.5% or more of their weight than in the gradual group (76/97 vs. 53/103). 127 participants entered phase 2 of the study (2 in the gradual group who lost 12.5% body weight before 12 weeks were excluded). 1 participant in the rapid group developed cholecystitis requiring cholecystectomy.
In Phase 2, seven participants in the rapid group withdrew due to logistical issues, psychological stress, and other health-related issues; 4 participants in the gradual group withdrew for the same reasons, as well as pregnancy. 2 participants from the rapid group developed cancer. All but 6 participants regained weight (5 in rapid group, 1 in gradual group) and were put on a 400-500 kcal deficit diet. There was no significant difference in mean weight regain of the rapid and gradual participants. By week 144 of phase 2, average weight regain in the gradual group was 10.4 kg (95% confidence interval [CI] 8.4–12.4; 71.2% of lost weight regained, CI 58.1–84.3) and 10.3 kg in rapid weight loss participants (95% CI 8.5–12.1; 70.5% of lost weight regained, CI 57.8–83.2). This result did not change significantly in the intention to treat analysis where dropouts were assumed to return to baseline.
During phase 2, leptin concentrations increased in both groups, and there was no difference in leptin concentrations between the 2 groups at weeks 48 and 144, nor were they significantly different from baseline at week 48. Ghrelin concentrations increased in both groups from baseline, but there was no significant difference between the groups at the end of 144 weeks.
Conclusion. In highly selected Australian participants, rapid weight loss (12 weeks) using a very low calorie meal replacement program led to greater weight loss than a gradual weight loss program (36 weeks) using a combination of meal replacements and diet recommendations. In participants who lost 12.5% or greater body weight, the speed at which participants regained weight was similar in both groups.
Commentary
Obesity rates have increased globally over the past 20 years. In the United States, Yang and Colditz found that approximately 35% of men and 37% of women are obese and approximately 40% of men and 30% of women are overweight, marking the first time that obese Americans outnumber overweight Americans [1]. Approximately 45 million Americans diet each year, and Americans spend $33 billion on weight-loss products annually. Thus, we need to determine the most effective and cost-effective weight management practices. The Purcell et al study suggests that a 12-week intervention may lead to greater weight loss and better adherence than a 36-week program, and that weight regain in participants achieving 12.5% or greater weight loss may be the same in both interventions. While they did not formally evaluate cost effectiveness, these findings suggest that a rapid weight loss program through a very low calorie diet (VLCD) may be more cost-effective since they achieved better results in a shorter period of time. However, caution must be taken before universally recommending VLCDs to promote rapid weight loss.
Many organizations advise patients to lose weight slowly to increase their chances of reaching weight loss goals and long-term success. The American Heart Association, American College of Cardiology, and The Obesity Society (AHA/ACC/TOS) guidelines for the management of overweight and obesity in adults recommend 3 types of diets for weight loss: a 1200–1800 calorie diet, depending on weight and gender; a 500 kcal/day or 750kcal/day energy deficit, or an evidence-based diet that restricts specific food types (such as high-carbohydrate foods) [2]. These guidelines also state that individuals likely need to follow lifestyle changes for more than 6 months to increase their chances of achieving weight loss goals [2]. They acknowledge maximum weight loss is typically achieved at 6 months, and is commonly followed by plateau and gradual regain [2]. The US Preventive Services Task Force (USPSTF) also advises gradual weight loss [3].
The results of the Purcell et al study and others provide evidence that contradicts these recommendations. For example, Nackers et al found that people who lost weight quickly achieved and maintained greater weight loss than participants who lost weight gradually [4]. Further, those who lost weight rapidly were no more susceptible to regaining weight than people who lost weight gradually [4]. Toburo and Astrup also found the rate of initial weight loss had no impact on the long-term outcomes of weight maintenance [5]. Astrup and Rössner found initial weight loss was positively associated with long-term weight maintenance, and rapid weight loss resulted in improved sustained weight maintenance [6]. Finally, Wing and Phelan found the best predictor of weight regain was the length of time weight loss was maintained, not how the weight was lost [7].
VCLDs replace regular meals with prepared formulas to promote rapid weight loss, and are not recommended for the mildly obese or overweight. VLCDs have been shown to greatly reduce cardiovascular risk factors and relieve obesity-related symptoms; however, they result in more side effects compared to a low calorie diet [8]. Individuals who follow VLCDs must be monitored regularly to ensure they do not experience serious side effects, such as gallstones, electrolyte imbalance that can cause muscle and nerve malfunction, and an irregular heartbeat [9]. Indeed, 1 patient in the rapid group required a cholecystectomy. The providers in this study were obesity specialists, which may account for the strong outcomes and relatively few adverse events.
This study has many strengths. First, researchers achieved low rates of attrition (22% compared to about 40% in other studies) [9,10]. This study also followed participants for 2 years post-intervention and achieved high rates of weight loss in both groups. In addition to low dropout rates and long-term follow-up, the population was highly adherent to each intervention. Limitations of the study include that the authors were highly selective in choosing participants—none of the participants had obesity-related comorbidities such as diabetes or significant medical conditions. Individuals with these conditions may not be able to follow the dietary recommendations used in this study, restricting generalizability from a population that is largely overweight and obese. Further, all participants were from Melbourne, Australia. Since the authors did not provide data on race/ethnicity, we can assume a relatively homogeneous population, further limiting generalizability.
Applications for Clinical Practice
This study suggests that rapid weight loss through VLCDs may achieve better weight loss outcomes and adherence when compared to more gradual programs without resulting in higher weight regain over time in highly selected patients treated by obesity specialists. Caution must be advised since primary care practitioners may not have sufficient training to deliver these diets. VLCDs have higher risk of gallstones and other adverse outcomes such as gout or cardiac events [11,12]. A more gradual weight loss program, similar to the 36-week program in the Purcell et al study, used meal replacements and achieved outcomes that were relatively high, with 72% achieving at least 5% weight loss, and 19% achieving 15% weight loss or greater (P < 0.001) [13]. Indeed, meal replacements of 1 to 2 meals per day have been shown to be safe and effective in primary care [14]. Current AHA/ACC/TOS guidelines on VLCDs are inconclusive, stating there is insufficient evidence to comment on the value of VLCDs, or on strategies to provide more supervision of adherence to these diets [2]. Thus, practitioners without training in the use of VLCDs should still follow USPSTF and other recommendations to promote gradual weight loss [2]. However, if patients want to lose weight faster with a VLCD, then providers can refer them to an obesity specialist since this may promote greater adherence and long-term weight maintenance in select patients.
—Natalie L. Ricci, Mailman School of Public Health, New York, NY, and Melanie Jay, MD, MS
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015 Jun 22.
2. Jensen MD, Ryan DH, Apovian CM, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. Circulation 2014;129(25 Suppl 2):S102–38.
3. Final recommendation statement: Obesity in adults: screening and management, June 2012. U.S. Preventive Services Task Force. Available at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/obesity-in-adults-screening-and-management.
4. Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med 2010;17:161–7.
5. Toubro S, Astrup A. Randomised comparison of diets for maintaining obese subjects’ weight after major weight loss: ad lib, low fat, high carbohydrate diet v fixed energy intake. BMJ 1997;314:29–34.
6. Astrup A, Rössner S. Lessons from obesity management programmes: greater initial weight loss improves long-term maintenance. Obes Rev 2000;1:17–9.
7. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr 2005;82(1 Suppl):222S–225S.
8. Christensen P, Bliddal H, Riecke BF, et al. Comparison of a low-energy diet and a very low-energy diet in sedentary obese individuals: a pragmatic randomized controlled trial. Clin Obes 2011;1:31–40.
9. Anderson JW, Hamilton CC, Brinkman-Kaplan V. Benefits and risks of an intensive very-low-calorie diet program for severe obesity. Am J Gastroenterol 1992;87:6–15.
10. Ditschuneit HH, Flechtner-Mors M, Johnson TD, Adler G. Metabolic and weight-loss effects of a long-term dietary intervention in obese patients. Am J Clin Nutr 1999;69:198–204.
11. Rössner S, Flaten H. VLCD versus LCD in long-term treatment of obesity. Int J Obes Relat Metab Disord 1997;21:22–6.
12. Weinsier RL, Ullmann DO. Gallstone formation and weight loss. Obes Res 1993;1:51–6.
13. Kruschitz R, Wallner-Liebmann SJ, Lothaller H, et al. Evaluation of a meal replacement-based weight management program in primary care settings according to the actual European clinical practice guidelines for the management of obesity in adults. Wien Klin Wochenschr 2014;126:598–603.
14. Haas WC, Moore JB, Kaplan M, Lazorick S. Outcomes from a medical weight loss program: primary care clinics versus weight loss clinics. Am J Med 2012;125:603.e7–11.
1. Yang L, Colditz GA. Prevalence of overweight and obesity in the United States, 2007-2012. JAMA Intern Med 2015 Jun 22.
2. Jensen MD, Ryan DH, Apovian CM, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. Circulation 2014;129(25 Suppl 2):S102–38.
3. Final recommendation statement: Obesity in adults: screening and management, June 2012. U.S. Preventive Services Task Force. Available at www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/obesity-in-adults-screening-and-management.
4. Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med 2010;17:161–7.
5. Toubro S, Astrup A. Randomised comparison of diets for maintaining obese subjects’ weight after major weight loss: ad lib, low fat, high carbohydrate diet v fixed energy intake. BMJ 1997;314:29–34.
6. Astrup A, Rössner S. Lessons from obesity management programmes: greater initial weight loss improves long-term maintenance. Obes Rev 2000;1:17–9.
7. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr 2005;82(1 Suppl):222S–225S.
8. Christensen P, Bliddal H, Riecke BF, et al. Comparison of a low-energy diet and a very low-energy diet in sedentary obese individuals: a pragmatic randomized controlled trial. Clin Obes 2011;1:31–40.
9. Anderson JW, Hamilton CC, Brinkman-Kaplan V. Benefits and risks of an intensive very-low-calorie diet program for severe obesity. Am J Gastroenterol 1992;87:6–15.
10. Ditschuneit HH, Flechtner-Mors M, Johnson TD, Adler G. Metabolic and weight-loss effects of a long-term dietary intervention in obese patients. Am J Clin Nutr 1999;69:198–204.
11. Rössner S, Flaten H. VLCD versus LCD in long-term treatment of obesity. Int J Obes Relat Metab Disord 1997;21:22–6.
12. Weinsier RL, Ullmann DO. Gallstone formation and weight loss. Obes Res 1993;1:51–6.
13. Kruschitz R, Wallner-Liebmann SJ, Lothaller H, et al. Evaluation of a meal replacement-based weight management program in primary care settings according to the actual European clinical practice guidelines for the management of obesity in adults. Wien Klin Wochenschr 2014;126:598–603.
14. Haas WC, Moore JB, Kaplan M, Lazorick S. Outcomes from a medical weight loss program: primary care clinics versus weight loss clinics. Am J Med 2012;125:603.e7–11.