Effect of a CommunityBased Weight Management Program on Weight ...

Social and Behavioral

Effect of a Community-Based Weight Management Program on Weight Loss and Cardiovascular Disease Risk Factors Cheryl L. Graffagnino, James M. Falko, Michelle La Londe, Joann Schaumburg, Michael F. Hyek, Lynn E.T. Shaffer, Richard Snow, and Teresa Caulin-Glaser

Abstract GRAFFAGNINO, CHERYL L., JAMES M. FALKO, MICHELLE LA LONDE, JOANN SCHAUMBURG, MICHAEL F. HYEK, LYNN E.T. SHAFFER, RICHARD SNOW, AND TERESA CAULIN-GLASER. Effect of a community-based weight management program on weight loss and cardiovascular disease risk factors. Obesity. 2006; 14:280 –288. Objective: The purpose of our retrospective database analysis was to describe and evaluate the outcomes of a weight loss intervention in a community medical wellness center. Research Methods and Procedures: Four hundred eighteen overweight and obese adults entered the program between 2001 and 2004. Forty-seven percent completed the 6-month program designed using standards and recommendations established by the NIH, the American Dietetic Association, and the American Academy of Sports Medicine. Data analysis was limited to 198 participants (142 women, 56 men) completing the program. Results: Individuals completing the 6-month program averaged a weight loss of 7.3% in men and 4.7% in women. Fasting lipids and blood glucose improved in both genders regardless of age. Outcomes including BMI and lipids improved in women regardless of menopausal status or hormone replacement therapy. There was a significant correlation between percentage weight loss and number of weekly counseling sessions attended and number of visits to the wellness center for exercise. Discussion: Participants who complete a structured community-based weight management program can achieve sig-

Received for review April 21, 2005. Accepted in final form November 22, 2005. Riverside Methodist Hospitals/McConnell Heart Health Center, Columbus, Ohio. Address correspondence to Cheryl L. Graffagnino, McConnell Heart Health Center, 3773 Olentangy River Road, Columbus, OH 43214. E-mail: [email protected] Copyright © 2006 NAASO

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nificant weight loss and improvement in cardiovascular risk factors regardless of age, gender, or menopausal status. Our analysis suggests that national treatment guidelines/recommendations for weight management can be effectively implemented in a community medical wellness center. The relatively high drop-out rate associated with this program suggests the need to identify strategies and techniques to enhance adherence and completion of programs. Key words: weight loss, cardiovascular disease, menopause, physical activity, therapeutic lifestyle change diet

Introduction Obesity has reached epidemic proportions in the United States, as have metabolic syndrome and type 2 diabetes (1,2). In the 1990s, the prevalence of obesity (BMI calculated as weight in kilograms divided by the square of height in meters ⱖ 30) (3) rose from 23.3% (1988 to 1994) to 30.9% (1999 to 2000) (1). Over a similar time period, the number of Americans categorized as severely obese (BMI ⬎ 40 or ⬎100 pounds overweight) quadrupled from 1 in 200 adult Americans to 1 in 50 (4). The growing prevalence of overweight, obesity, metabolic syndrome, and diabetes seems to occur irrespective of ethnicity, gender, or age (1,2,5). There is a general acceptance that the combination of increased physical activity and reduced caloric intake results in weight loss for overweight individuals (3,6,7). Clinical trials designed to promote increased physical activity and decreased caloric intake have reported varying outcomes with regard to percentage weight loss (3,8 –10). However, the vast majority of overweight and obese Americans are not participating in clinical trials but instead are seeking community weight loss programs and services. Due to the increased risk of cardiovascular disease, metabolic syndrome, and type 2 diabetes associated with overweight and obesity and the lack of published outcomes for community-based weight management programs, it is essential

Outcomes of a Community-Based Weight Management Program, Graffagnino et al.

that the effectiveness of these programs and services be evaluated. The Surgeon General and groups such as the American Dietetic Association have called on health care providers and researchers to help resolve the epidemic of obesity by documenting program outcomes to aid in the development of best practice guidelines for the treatment of obesity in our communities (6,11). A community-based medical wellness center provides a unique, semicontrolled setting to address the question of effectiveness of a voluntary, structured weight management program and characteristics and behaviors that may affect individual outcomes. The purpose of our study was to complete a retrospective analysis of the outcomes of a community-based weight management program established in 2001. The relationships between weight loss achieved and records of pre- and post-program demographic, anthropometric, and health history data and records of center visits and attendance at weekly counseling sessions were also evaluated. Exploring these relationships in a communitybased weight loss population is important because characteristics such as age, initial body weight, menopausal status, and gender have been frequently evaluated as predictors of weight loss in clinical trials (12). However, there are only limited data available regarding the effect of these predictors on weight loss in a community-based weight loss treatment program.

Research Methods and Procedures Study Design In a retrospective analysis, we studied the outcomes of a weight loss program offered in a community-based medical wellness facility. All participants received the same weight loss intervention as described in Program Components/ Treatment. Participants There were 418 overweight and obese men and women who entered the program between July 1, 2001 and March 31, 2004. All participants entering the weight management program gave informed consent for their outcomes and data to be used for research and publication. Our study cohort consisted of the 198 (47%) subjects who completed the program. Program completion was defined as a participant finishing the program with measurement, at least, of preprogram body weight and post-program body weight after 6 ⫾ 1 months of active program enrollment. Program Components/Treatment The weight management program was self-pay and based in a 105,000-square-foot medical wellness facility associated with a 1000-bed hospital. The center includes a 0.1mile indoor track, 0.5-mile outdoor walking path, a lap pool,

a warm water therapy pool, three group exercise studios, ⬃100 pieces of cardiovascular exercise equipment, and 40 pieces of strength training equipment. Participants paid an initial enrollment fee of $350.00 for testing and facility orientations followed by a monthly membership fee of $130.00 for which they received access to all amenities of the facility and the services of registered dietitians and exercise physiologists as outlined in the program components. The weight management program design was based on guidelines established by the NIH in the Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults (3) and position statements from the American Dietetic Association and the American College of Sports Medicine (6,7). The purpose of the program was to develop lifestyle behaviors that encourage an increase in caloric expenditure while decreasing caloric intake, with an emphasis on long-term behavior change. Upon enrollment in the program, all individuals underwent a comprehensive health and risk assessment including demographic and health history questionnaires and an exercise stress test using a standard Bruce protocol (13). Each individual completed an initial nutrition assessment with a registered dietitian. Thereafter, an exercise physiologist designed individualized cardiovascular and resistance training programs including exercise both at home and in the center. On completion of the nutrition assessment and exercise orientations, individuals were strongly encouraged to attend weekly, 10-minute counseling sessions with a dietitian and exercise physiologist, respectively. The counseling sessions were completed in the medical wellness facility, usually while the participants were exercising. The dietitian reviewed food records to ensure nutritional adequacy of the diet and offered recommendations for controlling caloric intake. The dietary component of the program was based on the Therapeutic Lifestyle Change Diet (14), with caloric restriction to ⬃1200 to 1800 calories daily as appropriate to the individual. A mixed diet with an emphasis on fruits, vegetables, and low-fat dairy products in appropriate portions was encouraged. Table 1 provides additional information regarding the dietary patterns recommended during the course of the weight management program. During the weekly counseling sessions, an exercise physiologist reviewed the exercise log to assist with goal setting and exercise progression. Participants were encouraged to increase daily activity, accumulating 30 to 60 minutes of cardiovascular activity 4 to 6 d/wk, and to include strength training 2 to 3 non-consecutive d/wk. A series of 12 educational classes with topics including healthy eating, physical activity, lifestyle change, and stress management were offered but were not mandatory. Participants could repeat these educational classes as often as they felt necessary. The program also offered optional behavioral health assistance from a clinical psychologist. At the conclusion of the OBESITY Vol. 14 No. 2 February 2006

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Table 1. Dietary patterns utilized in the weight management program 1200 calories

1400 calories

1500 calories

1600 calories

1700 calories

1800 calories

4 2 5 2 5 2 0

4 3 5 2 5 3 100

4 3 5 3 5 3 100

4 3 6 3 5 3 100

4 4 6 3 6 3 100

4 4 7 3 6 3 100

Vegetables (servings) Fruit (servings) Grains/starchy vegetables (servings) Dairy (servings) Lean meat and alternatives (ounces) Fats (servings) Extra (calories)*

* Denotes discretionary calories that individuals used for other foods including, but not limited to, alcohol, sweets, and nutrient-poor snack foods.

6-month program, anthropometric and laboratory measures were repeated. Participants also met with a registered dietitian at program completion to create a plan for continued healthy lifestyle practices. Measures Anthropometric Measures. Anthropometric measures including height, pre- and post-program weight, and BMI were evaluated. Body weight was also measured at program midpoint. The frequency of other body weight measurements during the course of the program was at the discretion of the individual. Laboratory Measures. Pre- and post-program lipid profile and blood glucose were analyzed from fasting plasma samples. Laboratory samples were collected in the medical wellness facility, or the information was provided to the center by the participant’s personal physician. Samples collected in the medical wellness facility were analyzed in our accredited hospital-based laboratory. Laboratory data supplied to the center by individual physicians were analyzed by the physician’s accredited laboratory of choice. Complete laboratory data were available for 90% of the participants. Some individuals declined repeat laboratory measures at the time of program completion; however, they were included in the data set if they completed 6 ⫾ 1 months of program participation and had pre- and postprogram weight measurements. Program Participation. In addition to the above anthropometric data, participation in weekly counseling sessions and the number of center visits were also monitored. Statistical Analysis All statistical analysis of data was performed using SAS software. Comparisons of within- and between-group means were performed using Student’s t tests. All tests for normality were satisfied. Pre- and post-comparisons of lab282


oratory values included only those individuals with both pre- and post-measures. Pearson product moment coefficients were calculated to determine the strength and direction of the relationship between variables. ␹2 and Fisher exact test were used to compare frequencies between groups. To investigate the independent associations among entry weight, diabetes, gender, and weight loss, a linear regression model using weight loss as the dependent variable was developed.

Results The clinical and demographic characteristics of the study cohort and of those individuals who dropped out of the program are shown in Table 2. Based on known pre-program characteristics, a comparison of individuals who did and did not complete the program found that individuals who did not complete the program were younger, less likely to be taking lipid-lowering medications, and less likely to be white than those completing the program (p ⬍ 0.05). No other significant differences between drop-outs and completers were found. A comparison of available pre-program anthropometric and laboratory data also identified no significant differences between individuals who completed the program and those who dropped out. All drop-outs were included in this analysis with the exception of 11 individuals who failed to complete the data collection process at the start of their program. Among those completing the program, ⬎2.5 times as many women met the criteria for program completion as compared with men (p ⬍ 0.0001). The majority of the participants were obese, with men having a significantly higher BMI than women (p ⫽ 0.002). Approximately 15% of participants reported a history of diabetes, with a significantly greater percentage of men reporting diabetes as compared with women (p ⫽ 0.02). Similarly, 27.3% of all


Table 2. Clinical and demographic characteristics at program enrollment Population characteristics

Drop-outs (n ⴝ 220)

Completers (n ⴝ 198)

Completers: women (n ⴝ 142)

Completers: men (n ⴝ 56)

Age (years ⫾ SD) BMI (kg/m2 ⫾ SD) Known diabetes (%) Lipid-lowering medications (%) White (%) African-American (%) ⱖ16 years of education (%) Income ⬎ $60K (%)

47.6 ⫾ 11.3* 38.5 ⫾ 8.6 14.1 18.2 85.9* 6.4 59.5 52.3

51.8 ⫾ 11.1 37.5 ⫾ 8.8 15.2 27.3 93.8 4.1 68.2 51.5

50.7 ⫾ 10.0 36.0 ⫾ 7.5 11.3 23.2 94.2 4.3 70.4 49.3

54.6 ⫾ 13.2 41.1 ⫾ 10.8 25.0 37.5 92.7 3.6 62.5 57.1

* Denotes that difference between completers and drop-outs is significant at p ⬍ 0.05.

participants reported taking a lipid-lowering medication at the time of enrollment, with a significantly greater percentage of the men in the cohort taking these medications as compared with women (p ⫽ 0.04). The majority of the participants were white (94%), and 68% were college graduates, with ⬃52% earning a mean annual income of greater than $60,000. Table 3 shows the mean clinical outcomes for all individuals completing the program. Significant improvements were noted in body weight (p ⬍ 0.0001), total cholesterol (TC)1 (p ⬍ 0.0001), low-density lipoprotein-cholesterol (LDL-C) (p ⬍ 0.0001), high-density lipoprotein-cholesterol (HDL-C) (p ⫽ 0.005), triglycerides (TGs) (p ⬍ 0.0001), and fasting glucose (p ⫽ 0.02). Fifty percent of the cohort lost at least 5% of their initial body weight.

1 Nonstandard abbreviations: TC, total cholesterol; LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; TG, triglyceride; HRT, hormone replacement therapy.

Figure 1 shows the effect of gender on clinical outcomes. Significant improvements in body weight, TC, LDL-C, and TG occurred in both men and women (p ⬍ 0.05). Table 4 shows the clinical outcome of both men and women completing the program. There were significant changes in glucose in men but not in women (⫺7.2 ⫾ 19.8, p ⫽ 0.01 vs. ⫺2.1 ⫾ 20.3, p ⫽ 0.26). Although both groups achieved significant improvements in body weight (p ⬍ 0.0001), men achieved significantly greater weight loss than did women (⫺9.6 ⫾ 10.6 kg vs. ⫺4.5 ⫾ 6.3 kg; p ⬍ 0.0001). Men achieved significant improvements in TC (⫺20.4 ⫾ 25.4 mg/dL; p ⬍ 0.0001), LDL-C (⫺17.4 ⫾ 21.7 mg/dL; p ⬍ 0.0001), and TG (⫺29.6 ⫾ 75.0 mg/dL; p ⫽ 0.006). Women also achieved significant improvements in TC (⫺8.6 ⫾ 31.4 mg/dL; p ⫽ 0.003), LDL-C (⫺6.4 ⫾ 28.0 mg/dL; p ⫽ 0.01), HDL-C (1.6 ⫾ 8.3; p ⫽ 0.03), and TG (⫺18.5 ⫾ 62.4 mg/dL; p ⫽ 0.001). However, men achieved significantly greater improvements in TC and LDL-C (p ⬍ 0.05) than did women.

Table 3. Clinical outcomes Outcome

n

Pre-program [mean(SD)]

Body weight (kg) TC (mg/dL) LDL-C (mg/dL) HDL-C (mg/dL) TG (mg/dL) Glucose (mg/dL)

198 178 178 178 178 176

106.0 (28.8) 205.3 (39.2) 120.2 (36.3) 52.1 (14.7) 166.8 (75.4) 101.8 (27.1)

Post-program [mean(SD)]

Mean change [mean(SD)]

Change (%)

p

100.1 (27.0) 192.9 (40.0) 110.3 (35.8) 53.7 (15.1) 145.2 (72.1) 97.9 (23.7)

⫺6.0 (8.0) ⫺12.1 (30.2) ⫺9.6 (26.7) 1.7 (7.9) ⫺21.7 (66.3) ⫺3.6 (20.3)

5.7 5.9 8.0 3.2 13.0 3.5

⬍0.0001 ⬍0.0001 ⬍0.0001 0.005 ⬍0.0001 0.02

SD, standard deviation; TC, total cholesterol; LDL-C, low density lipoprotein-cholesterol; HDL-C, high density lipoprotein-cholesterol; TG, triglycerides. Comparisons of laboratory values include only those individuals for which pre- and post-values were available.


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Figure 1: Change in risk factors by gender.

Results of the regression model demonstrated significant weight loss in women, although men lost an average of 2.8 kg more than did women (p ⫽ 0.04) after adjustment for diabetes (p ⫽ 0.03) and entry weight (p ⬍ 0.0001). Of the 142 women completing the program, 138 provided complete information regarding menopausal status and use of hormone replacement therapy (HRT). Both pre- and post-menopausal women achieved significant improvements in body weight, BMI, and TC (Table 5). Pre-menopausal women also achieved significant improvements in TG (Table 5). Of the 64 post-menopausal women, 29 were receiving HRT at the time of their participation in the weight management program. Regardless of HRT, postmenopausal women achieved significant improvements in body weight and BMI (Table 5). Post-menopausal women who were not receiving HRT also achieved significant

improvements in HDL-C (Table 5). No other significant differences in risk factors were noted in between-group comparisons. Neither menopausal status nor HRT had an impact on the degree of weight loss achieved by the women completing the program. The effect of age on clinical outcomes of our participants is shown in Table 6. The data were analyzed in three age categories (18 to 45, 46 to 65, and ⱖ66 years of age) based on age at the time of enrollment in the program. Significant improvements in body weight, TC, LDL-C, and TG were noted across all age groups. The 46- to 65-year-old group also achieved a significant improvement in HDL-C, whereas the ⱖ66 year old group had a significant improvement in glucose. Age had no effect on the degree of weight loss achieved. A positive relationship (p ⬍ 0.0001) between weight loss and TGs (r ⫽ 0.33) was identified. No other significant relationships between weight loss and our clinical outcomes were found. In addition, we noted that there was a correlation between percentage weight loss and the number of weekly counseling sessions attended (r ⫽ 0.28) and the number of center visits for exercise (r ⫽ 0.40) (p ⬍ 0.001 for both). Participation in weekly counseling sessions ranged from one to 28 sessions, with a mean participation of 18.1 ⫾ 6.3 sessions in 6 months. The frequency of center visits for exercise ranged from four to 157 visits, with a mean of 67.3 ⫾ 30.4 visits during the 6-month program. To further evaluate the effect of participation in these program components on the outcome of weight loss, quartile rankings were used to establish four groups based on frequency of participation in each component. The four groups were established at ⱕ25th percentile, ⬎25th and ⬍50th percentile, ⱖ50th and ⬍75th percentile, and those whose participation was ⱖ75th percentile. The mean percentage weight loss associated with each level of participation in weekly

Table 4. Change in risk factors by gender

Gender

Change LDL-C HDL-C Glucose BMI 2 weight (%) TC (mg/dL) (mg/dL) (mg/dL) TG (mg/dL) (mg/dL) (kg/m ) [mean (SD)] [mean (SD)] [mean (SD)] [mean (SD)] [mean (SD)] [mean (SD)] [mean (SD)]

Male ⫺3.1 (3.3)* ⫺9.6 (10.5)* ⫺20.4 (25.4)* [Pre-mean (SD)] 41.0 (10.8) 127.9 (33.1)kg 197.5 (40.7) [Post-mean (SD)] 38.0 (9.8) 118.5 (30.5)kg 177.2 (34.7) Female ⫺1.7 (2.3)* ⫺4.6 (13.8)* ⫺8.6 (31.4)* [Pre-mean (SD)] 35.7 (7.4) 96.3 (20.8)kg 208.1 (38.5) [Post-mean (SD)] 33.8 (7.5) 91.3 (20.7)kg 200.0 (40.2)

⫺17.4 (21.7)* 118.4 (37.4) 101.0 (32.7) ⫺6.4 (28.0)* 120.4 (36.2) 114.6 (36.5)

1.9 (6.9) 43.9 (13.4) 45.8 (13.6) 1.6 (8.3)* 55.2 (13.8) 56.8 (14.2)

⫺29.6 (75.0)* 179.6 (72.7) 150.0 (70.1) ⫺18.5 (62.4)* 163.0 (76.0) 144.4 (73.5)

⫺7.2 (19.8)* 105.2 (24.3) 98.0 (20.5) ⫺2.1 (20.3) 100.3 (28.3) 98.2 (25.0)

SD, standard deviation; TC, total cholesterol; LDL-C, low density lipoprotein-cholesterol; HDL-C, high density lipoprotein-cholesterol; TG, triglycerides. Comparisons of laboratory values include only those individuals for whom pre- and post-values were available. * p ⬍ 0.05 for mean change from baseline.

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Change weight† (%) [mean (SD)] ⫺4.4 (6.4)* (n ⫽ 74) ⫺5.1 (6.2)* (n ⫽ 64) ⫺5.2 (4.6)* (n ⫽ 29) ⫺5.1 (7.4)* (n ⫽ 35)

BMI† (kg/m2) [mean (SD)]

⫺1.5 (2.3)* (n ⫽ 74) ⫺1.9 (2.3)* (n ⫽ 64) ⫺1.9 (1.8)* (n ⫽ 29) ⫺1.8 (2.6)* (n ⫽ 35)

⫺8.9 (34.9)* (n ⫽ 67) ⫺8.9 (27.8)* (n ⫽ 55) ⫺8.4 (23.4) (n ⫽ 25) ⫺9.2 (31.4) (n ⫽ 30)

TC (mg/dL) [mean (SD)] ⫺7.3 (30.5) (n ⫽ 67) ⫺5.3 (25.8) (n ⫽ 55) ⫺2.7 (24.4) (n ⫽ 25) ⫺7.4 (27.2) (n ⫽ 30)

LDL-C (mg/dL) [mean (SD)] 2.0 (8.9) (n ⫽ 67) 0.7 (7.8) (n ⫽ 55) ⫺1.5 (8.9) (n ⫽ 25) 2.5 (5.8)* (n ⫽ 30)

HDL-C (mg/dL) [mean (SD)] ⫺18.9 (54.1)* (n ⫽ 67) ⫺18.8 (73.0) (n ⫽ 55) ⫺14.9 (81.3) (n ⫽ 25) ⫺22.0 (66.6) (n ⫽ 30)

TG (mg/dL) [mean (SD)]

0.9 (16.0) (n ⫽ 66) ⫺5.5 (24.7) (n ⫽ 54) ⫺4.2 (26.6) (n ⫽ 25) ⫺6.6 (23.3) (n ⫽ 29)

Glucose (mg/dL) [mean (SD)]

⫺6.3 (7.3)* (n ⫽ 62) ⫺4.7 (6.6)* (n ⫽ 118) ⫺7.3 (5.2)* (n ⫽ 18)

⫺2.5 (3.2)* (n ⫽ 62) ⫺1.7 (2.4)* (n ⫽ 118) ⫺2.8 (2.1)* (n ⫽ 18)

⫺15.8 (30.8)* (n ⫽ 58) ⫺8.1 (30.8)* (n ⫽ 103) ⫺23.0 (19.7)* (n ⫽ 17)

TC (mg/dL) [mean (SD)]

⫺13.1 (25.9)* (n ⫽ 58) ⫺6.3 (28.0)* (n ⫽ 103) ⫺17.7 (17.8)* (n ⫽ 17)

LDL-C (mg/dL) [mean (SD)]

2.1 (8.7) (n ⫽ 58) 1.6 (7.8)* (n ⫽ 103) 0.9 (6.3) (n ⫽ 17)

HDL-C (mg/dL) [mean (SD)]

⫺26.6 (54.8)* (n ⫽ 58) ⫺16.4 (71.9)* (n ⫽ 103) ⫺37.0 (66.8)* (n ⫽ 17)

TG (mg/dL) [mean (SD)]

SD, standard deviation; TC, total cholesterol; LDL-C, low density lipoprotein-cholesterol; HDL-C, high density lipoprotein-cholesterol; TG, triglycerides. * p ⬍ 0.05 for mean change from baseline. † There were no significant differences in BMI or percentage change in weight between any age category.

ⱖ66

46 to 65

18 to 45

Age (years)

Change weight† (%) [mean (SD)]

BMI† (kg/m2) [mean (SD)]

Table 6. Change in risk factors

⫺1.4 (14.7) (n ⫽ 57) ⫺3.9 (23.2) (n ⫽ 102) ⫺8.9 (17.5)* (n ⫽ 17)

Glucose (mg/dL) [mean (SD)]

HRT, hormone replacement therapy; SD, standard deviation; TC, total cholesterol; LDL-C, low density lipoprotein-cholesterol; HDL-C, high density lipoprotein-cholesterol; TG, triglycerides. Comparisons of laboratory values include only those individuals for whom pre- and post-values were available. * p ⬍ 0.05 for mean change from baseline. † There were no significant differences in BMI or percentage change in weight between any menopausal group.

Post without HRT

Post with HRT

Post

Pre

Menopause status

Table 5. Change in risk factors by menopause and HRT



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Figure 2: Effect of participation in weekly counseling sessions on percentage weight loss.

counseling sessions and center visits for exercise is shown in Figures 2 and 3, respectively. With respect to weekly counseling sessions, individuals who attended 20 to 22 and ⱖ23 counseling sessions had significantly greater weight loss (p ⬍ 0.04) than the individuals in the other two groups. With respect to center visits for exercise, those individuals with ⱖ84 visits had significantly greater weight loss than the other three groups (p ⫽ 0.01), whereas those with 64 to 83 visits had significantly greater weight loss (p ⫽ 0.01) than those with fewer than 64 visits. There were no differences in the rate of participation in these program components between the different age groups or menopausal groups analyzed. However, men visited the center for exercise significantly more often than did women during the 6-month program, 81.1 ⫾ 26.2 vs. 61.9 ⫾ 66.6 times (p ⬍ 0.0001), respectively.

Discussion Results from randomized, controlled trials and largescale interventions have clearly identified obesity as an independent risk factor for coronary heart disease (15). Additionally, these trials have shown that weight loss in obese individuals can improve comorbid conditions and reduce blood lipids and lipoproteins, thereby reducing the risk for coronary heart disease (3,15,16). However, many of the aforementioned studies showing these effects have been performed in highly controlled experimental environments. Because of this, the American Dietetic Association and other organizations have issued a call to action to identify the effectiveness of research-driven obesity treatments in community settings. We analyzed the results of our weight loss program retrospectively to determine the impact of a community286


Figure 3: Effect of participation in center visits for exercise on percentage weight loss.

based program on weight loss and improvements in cardiovascular risk factors and other clinical parameters. In addition, we analyzed whether gender, age, or menopausal status might influence our results. Many trials open to both men and women report a significantly greater number of women participants (3,17). The results of our voluntary, self-pay program were similar. Although both men and women achieved significant weight loss, our study showed that men achieved significantly greater weight loss and improvement in TC, LDL-C, and TG. The greater weight loss in men persisted after adjustments for entry weight and may be a result of their greater number of visits to the center for exercise. Previous research suggests that the greater improvements in TC, LDL-C, and TG are likely secondary to the greater weight loss achieved (16). The greater weight loss in men is consistent with findings in previous studies (12). It has been suggested that weight gain is a common occurrence at menopause (18). However, recent findings from the Study of Women’s Health Across the Nation found no significant association between menopause and weight gain. In fact, this study suggests that women with higher levels of physical activity during menopause are less likely to gain weight. These findings suggest that weight gain is not a function of menopause but is more likely related to physical inactivity (19). It has also been suggested that HRT may affect weight gain or loss in post-menopausal women. However, a controlled trial indicated that post-menopausal women receiving HRT had a lower BMI compared with those who did not (18). Despite these available data, women often report an expectation that weight loss will be more difficult to achieve in post-menopausal years, especially with HRT. Our results support the previously mentioned study (18) because neither menopausal status nor HRT had an effect on weight loss in women participating in a community-based program. In


fact, pre-and post-menopausal women with and without HRT lost the same amount of weight. In the past 30 years, the prevalence of obesity in older adults in the U.S. has more than doubled (1). This is important because the Vitamins and Lifestyle study identified a significant relationship between obesity and the prevalence of numerous adverse health conditions in older adults. For example, even non-cardiac events such as bladder infections, frequent headaches, insomnia, and fatigue, along with other disorders that affect overall health and quality of life, are associated with obesity in older adults (20). Furthermore, older obese adults may be more likely to experience physical frailty and impaired quality of life than their non-obese counterparts (21). Thus, it is important to promote healthy lifestyle practices for older obese Americans by encouraging participation in a weight management program. Although age itself has been shown to be a weak but inconsistent predictor of weight loss in a clinical trial (12), we found that those over 65 years old had similar weight loss when compared with those ⬍65 years of age. Others have reported that frequency of participation in a structured program is a good predictor of weight loss (22). Consistent with these findings, we identified a significant relationship between weight loss and participation in two key program components, weekly counseling sessions and center visits for exercise. This suggests that program participation may affect the amount of weight loss achieved. An evaluation of commercial weight loss programs identified attrition rates varying from 0% to 65% in programs spanning 12 weeks to 2 years in duration. However, of the 20 programs reviewed, eight programs did not report their attrition rates. The attrition rate for our community-based program, at 53%, is comparable with programs of similar duration (23). The attrition rate in our program may be a reflection of the time and resource commitment required, because participants were asked to participate in a weekly progress check, to keep daily food and activity logs, and to participate in physical activity several days per week. However, the frequent contact with healthcare providers, selfmonitoring, and physical activity most days of the week are consistent with the recommendations of the NIH, the American Dietetic Association, and the American Academy of Sports Medicine for effective weight management programs (3,6,7). We continuously seek ways to enhance program adherence because our results and those of other programs indicate that individuals must participate in a weight loss program to achieve the desired outcome of weight loss (23). Current program development is focused on identifying effective incentives to promote health responsibility, an optimal frequency for contact with staff, and increased home-based exercise opportunities. However, because our program design was based on guidelines and recommendations for weight loss interventions established by national organizations, we must ask ourselves whether the steps that

science has identified as being necessary for effective weight loss are realistic for overweight and obese individuals in our current environment. Even with the resources available in this program, including weekly support and follow-up calls and letters to non-participators, a significant number of individuals enrolling in this program did not adhere to the recommended practices to achieve weight loss and failed to complete this program. Future research may be better directed at finding ways to create an environment in which healthy lifestyles are inherent and easy to adopt and to develop societal and healthcare incentives rather than solely motivating individuals to adhere to current recommendations. Our data on the frequency of exercise in the center did not include data from exercise undertaken at home or elsewhere. Although exercise time and intensity and strength training progression were routinely discussed during weekly counseling sessions, we did not formally assess compliance with these activities. We also did not have data from food frequency questionnaires or food record assessments to objectively assess dietary and behavioral compliance. These issues are clearly of great importance and represent a limitation of our study. Identifying valid methods that are both fiscally and resource efficient to quantitatively assess changes in physical activity and eating habits is essential to the success of commercial and community-based programs in effectively evaluating and documenting the outcomes of their programs. Based on this need, we have recently implemented a dietitian-obtained 24-hour dietary recall preand post-program to better evaluate dietary change. We are also investigating the feasibility of physical activity assessments such as 6-minute walk testing. Another limitation of our study is that the cost of our program likely limited the diversity of our population. However, the basic constructs of our program can be applied in other settings, including community recreation centers, worksite programs, and school environments. More than 65% of the cost of our program is associated with our wellness center fees. This cost contributes to the operations, maintenance, and staffing of the 105,000-square-foot wellness facility. In this regard, the basic cost of the components of our program could be significantly less if applied in a different setting. Evaluating the feasibility of implementing the basic components of this program in other settings represents an additional opportunity for future research. As with any weight loss program, we must also focus attention on weight loss maintenance after completion of this program. At this time, we have limited data regarding weight loss maintenance after completion of our program. As a result, we have recently instituted a follow-up program to attempt to capture body weight, BMI, and fasting lipid and glucose levels annually for participants who have completed the program. OBESITY Vol. 14 No. 2 February 2006

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As obesity rates rise in the U.S., it is essential that we develop effective programs and strategies for weight management in the communities in which we live. Based on extensive clinical research, the NIH, the American Dietetic Association, and the American College of Sports Medicine (3,6,7) have put forth guidelines for the development of such weight control programs. Based on our study’s design as a retrospective outcomes analysis, our results must be treated with caution because there are multiple variables that may have affected the results. However, these outcomes do confirm that many of these clinical recommendations can be implemented in a community-based weight management program. Regardless of gender, age, or menopausal status, participants can achieve clinically and statistically significant improvements in body weight and in several cardiovascular disease risk factors.

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