Approximately two thirds of adults in the United

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1 Change in Body Mass Index Over 1 Year in a Family Medicine Clinic: A Retrospective Analysis of Medical Records James E. Rohrer, PhD, Gregory A. Bartel, MD, Steven C. Adamson, MD, Joseph Furst, MD, and Todd Wade, MD Abstract Objective: To determine if baseline body mass index (BMI) is a predictor of weight loss after 1 year in adult family medicine patients who are overweight or obese. Design: Retrospective chart review. Setting and participants: 598 overweight or obese (BMI, 25 kg/m 2 ) adult patients treated in family medicine practices in Rochester, MN, between January 2006 and June Results: Over 40% of patients lost weight after 1 year, and 13% lost at least 5% of BMI. The percentage of patients losing weight was highest in those with a BMI between 30 and 34.9 kg/m 2 at baseline. Multiple logistic regression analysis revealed that compared with patients with a BMI between 25 and 29.9 kg/m 2, those with BMI of 30 kg/m 2 or more had a higher adjusted odds ratio (OR) for losing any weight (OR, 2.1, 2.2, and 2.0 for BMI ranges , , and 45 kg/m 2, respectively). Adjusted ORs for losing at least 5% of BMI were significantly higher for patients with a BMI of kg/m 2 and kg/m 2 (OR, 1.9 and 2.5, respectively). Conclusion: Overweight and obese patients can be advised that avoiding weight gain and losing a small amount of weight are achievable goals. Approximately two thirds of adults in the United States are overweight or obese [1]. This epidemic may seem inexorable to primary care providers who treat the sequelae of obesity in their clinics. Many individuals attempt to lose weight each year using sensible self-help strategies [2 5]. Although the efficacy of various diet plans has been established for patients who adhere to them [6 8], the likelihood that free-living family medicine patients will be able to control their weight is not widely known. Of special interest is the degree to which baseline obesity affects the odds of being able to lose weight. Weight control is more urgent for heavier patients, and referral to a specialized program may be indicated if the chances of losing weight independently are unacceptably low. The objective of this study was to test the hypothesis that baseline body mass index (BMI) is a predictor of weight loss after 1 year in adult family medicine patients who are overweight or obese at baseline (BMI 25 kg/m 2 ). If higher BMI levels independently reduce the odds of losing weight, referral to weight management programs might be indicated. Methods We analyzed a convenience sample of adult patients who were treated in our family medicine clinics in Rochester, MN, and referred for any type of specialist consultation between January 2006 and June Our sampling frame included 1009 patients with BMI 25 and for whom age, gender, marital status, and comorbidity information were recorded in the medical record. We used a data set that was originally assembled originally for a study of referred patients. Medical records were the sole source of information used in this study. Two trained medical secretaries were used as abstractors. Data collection was approved by the institutional review board. Independent variables included BMI at the index date, age, gender, marital status (yes/no), and comorbidity (none, low, moderate). BMI was categorized as 25 to 29.9, 30 to 34.9, 35 to 44.9, and 45 or greater. Age was divided into 5 categories: 18 to 35, 36 to 45, 46 to 55, 56 to 65, and 66 to 100. The Charlson index was used to score comorbidity [9,10]. An index visit was defined as the visit in which a specialist consultation was ordered. The dependent variables in this study were any weight lost after 1 year (yes/no) and 5% or more of BMI lost after 1 year (yes/no). Percentage weight change was computed as BMI after 1 year BMI at baseline divided by BMI at baseline. A negative number indicated weight loss. A 3-month window was used around both the index date and the 1-year follow-up date. When BMI was recorded more than 1 time during the interval, the value closest to the desired date was chosen. From the Mayo Clinic, Rochester, MN. 66 JCOM February 2008 Vol. 15, No. 2

2 original Research Table 1. Descriptive Statistics: Continuous Variables Mean Standard Deviation Minimum Median Maximum BMI at index visit, kg/m BMI at 1 year post index visit, kg/m Change in BMI after 1 year, kg/m Percentage change in BMI BMI = body mass index. Each predictor variable was compared with the 2 weight loss variables using chi-square tests. A difference was considered statistically significant if P was less than Multiple logistic regression analyses were performed to identify associations between the independent variables and whether BMI declined. All of the independent variables were included in the multiple logistic regression models. Statistical analysis was performed using Epi Info version (Centers for Disease Control and Prevention, Atlanta, GA). Results Six patients were removed from our sampling frame because they received bariatric surgery. Of the remaining 1003, BMI after 1 year was recorded for 598. Incomplete cases (ie, cases missing BMI measurements at 1 year; n = 405) were not different from complete cases in regard to marital status or gender. However, patients with incomplete data were more likely to be younger (mean age, 50.9 years vs years for patients with complete data; P < 0.01) and tended to weigh less at baseline (mean BMI, 31.7 kg/m 2 vs kg/m 2 for patients with complete data; P = 0.02). Median BMI was 30.1 kg/m 2 and 31.0 kg/m 2 for incomplete and complete cases, respectively. Table 1 reports descriptive statistics for continuous variables. Mean BMI at baseline and after 1 year was 32.2 kg/m 2 (median, 30.9 kg/m 2 ) and 32.3 kg/m 2 (median, 31.0 kg/m 2 ). The mean change in BMI after 1 year was 0.15 kg/m 2 (median, 0.2 kg/m 2 ). The mean percentage change in BMI was 0.7 (median, 0.8). However, this apparent stability is misleading; over 40% of patients in our sample achieved some weight loss. Table 2 demonstrates that patients with higher baseline BMI lost slightly more weight on average after 1 year. Mean changes were small, with patients in the BMI category 40 kg/m 2 or greater losing an average of 0.71 kg/m 2 (median, 0.11 kg/m 2 ). The trend was significant at P < The mean percentage change was 1.5 (median, 0.3) for baseline BMI of 40 kg/m 2 and over. Over 40% of patients lost at least some weight after 1 year (Table 3), and over 13% lost at least 5% of baseline BMI. The typical patient was female, married, and older than 45 years. Over 40% of patients had a BMI between 25 and Table 2. Body Mass Index Change at 1 Year BMI at Baseline, kg/m 2 Mean BMI Change (Median) P Value* Mean Percentage Change (Median) P Value* (0.42) 2.0 (1.5) (0.09) 0.1 (0.3) ( 0.01) (0.04) ( 0.11) 1.5 ( 0.3) *Kruskal-Wallis test kg/m 2 at the index date. Almost 50% of patients were scored in the lowest comorbidity category. Univariate tests of the association also are shown in Table 3. Gender, being married, and comorbidity were unrelated to either measure of weight loss. Older patients (P = 0.04) and patients with a BMI between 30 and 35 kg/m 2 (P < 0.01) were more likely to have lost some weight than younger patients and patients with the highest and lowest baseline BMI. BMI at baseline was not related to losing 5% of body weight in the univariate analyses. Multiple logistic regression analysis was performed to determine the independent effects of BMI category on weight loss (Table 4). Being married, gender, and comorbidity were not associated with either measure of weight loss. Patients aged 34 to 56 years were less likely to lose some weight as compared with adults younger than 35 years. Patients aged between 35 and 66 years were less likely to lose at least 5% of BMI as compared with patients younger than 35 years. The odds of some losing weight were greater for patients whose baseline BMI was 30 kg/m 2 or greater compared with those whose BMIs were less than 30 kg/m 2. Adjusted ORs were 2.08, 2.16, and 2.03 for BMI 30 to 35 kg/m 2 (P < 0.01), 35 to 45 kg/m 2 (P < 0.01), and 45 kg/m 2 or greater (P = 0.03), respectively. The odds of losing 5% or more of BMI were greater for patients with a BMI 30 to 35 kg/m 2 and 35 to 45 kg/m 2 at baseline (OR, 1.89 [P =0.03] and 2.45 [P = 0.02], respectively). Vol. 15, No. 2 February 2008 JCOM 67

3 Table 3. Descriptive Statistics: Categorical Variables % of Sample Lost Weight Did Not Lose Any Weight P Value Lost 5% Total sample (n = 598) Age, yr P = Gender Female P = 0.56 Male Married No P = 0.99 Yes Comorbidity None Low P = Moderate BMI at index visit, kg/m P = BMI = body mass index. Did Not Lose 5% of Weight P Value P = 0.08 P = 0.20 P = 0.22 P = 0.54 P = 0.06 Discussion Over 40% of the patients in our sample lost weight after 1 year, and more than 13% lost 5% of BMI or more. This result is similar to findings reported by Crawford et al [4], in which 11.2% of patients lost 5% of BMI after 1 year. Patients in the Crawford et al study had lower BMI at baseline and were younger (aged years), and fewer men were included. In addition, it was a population sample drawn from an urban setting, targeting a university community. In both our study and the study by Crawford et al, weights were measured rather than self-reported. We found that family medicine patients with a BMI between 30 and 45 kg/m 2 at baseline were more likely to experience a decline in BMI than those with a BMI between 25 and 30 kg/m 2 at baseline. Because this relationship was independent of comorbidity, obese patients with a BMI of 30 to 45 kg/m 2 may have reason to be optimistic about their chances of losing small amounts of weight compared with patients who are merely overweight. This is useful information for a group of patients who may have given up hope because of previous failures or because the magnitude of the challenge they face. It is not surprising that those with higher BMI were more likely to lose weight, since concerned friends, family, and health care providers are likely to mobilize support for heavier patients. Obese patients are also more likely to have comorbidities (eg, hypertension, dyslipidemia, hyperglycemia or diabetes, degenerative joint disease) or symptoms such as shortness of breath, fatigue, and joint pains, all of which can at least temporarily motivate the patient. Although it may not lower BMI to the normal range, losing 5% of body weight is still clinically beneficial. The clinical implications of small amounts of weight loss have been well documented. As early as 1992, evidence has shown that for every kilogram of body weight lost, a mmol/l increase in high-density lipoprotein cholesterol is expected [11]. Clinical experience suggests direct correlations in other risk factor parameters, such as glucose and blood pressure. The findings of this study may aid in clarifying recommendations for weight management in primary care. Many primary care practices have no standard decision rules about referral of obese patients to weight loss programs [12 15]. Because many primary care patients are at an advanced stage of readiness to adopt weight control behaviors [16], timely advice and appropriate referrals could precipitate change. The consensus among researchers is that intentional 68 JCOM February 2008 Vol. 15, No. 2

4 original Research Table 4. Multiple Logistic Regression Analysis of Any Weight Loss and Weight Loss of at Least 5% of BMI (n = 598) Any Weight Loss At Least 5% BMI Adjusted OR (95% CI) P Value Adjusted OR (95% CI) P Value BMI at baseline, kg/m Reference Reference ( ) ( ) ( ) ( ) ( ) ( ) 0.06 Age, yr Reference Reference ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 0.07 Male vs. female 0.85 ( ) ( ) 0.27 Married vs. not married 0.20 ( ) ( ) 0.84 Comorbidity None Reference Reference Low 0.99 ( ) ( ) 0.69 Moderate 1.26 ( ) ( ) log likelihood BMI = body mass index; CI = confidence interval; OR = odds ratio. dieting is modestly successful over the short term, and employing more strategies persistently can lead to positive results over longer periods [2,5]. A variety of approaches can be effective, including commercial programs [6]. Additional research is needed to test the various low-cost interventions available to free-living primary care patients. More information is also needed about repeated weight loss attempts, since re-starts are well-accepted in smoking cessation and problem drinking. Certainly, 1 failed diet is not proof-positive that nonsurgical approaches will never work. Our study has several limitations. First, patients were not randomly selected and thus may not constitute a representative sample. However, since most randomized studies rely on volunteers, some selection bias may influence the findings reported. Another limitation is that methods of weight control (if any) used by the study patients are unknown. Our sample may suffer from selection bias as well, since it was not random, included pregnant women, and was limited to patients who were referred to specialists for any reason. Nevertheless, referral to specialists is common in our system and this is unlikely to substantially bias our findings, especially because we adjusted for comorbidity in the analysis. Conclusion After finding that only about one third of their sample avoided weight gain and approximately 11% lost more than 5% of BMI, Crawford et al [4] concluded that relatively few people successfully control their weight. We prefer to see the glass as half full. Over 40% of our patients lost some weight, and more than 13% lost at least 5% of BMI. The degree of weight control we observed is promising, given that the alternative would have been weight gain. Optimism about the chances of weight control is important in clinical settings. Obesity may be ignored by patients and their doctors in the false belief that weight loss attempts are guaranteed to fail. In our sample, patients lost small amounts of weight and were more likely to lose weight if their starting BMI was between 30 and 45 kg/m 2. Patients can reasonably be offered encouragement and practical information about weight loss. If they fail, restarting is reasonable and should entail no stigma. Additional research is needed to test the relative effectiveness of different low-cost, patient-driven approaches to weight management that might be used by patients with a BMI between 30 and 45 kg/m 2. Unknown are the number and length of visits required to help patients lose weight, the types of providers who can most cost-effectively provide the service (nurses, health educators, or counselors), and the best modalities for losing weight (internet, group classes, or personal health services). Regardless of the availability of systematic and objective evidence, patients should be encouraged to use common sense and employ an experimental attitude, buoyed Vol. 15, No. 2 February 2008 JCOM 69

5 by the knowledge that some degree of weight control is not only possible, it is achieved by many people every year. Acknowledgments: Julie Maxson and Kelly Amunrud abstracted medical records for the project. Corresponding author: James Rohrer, PhD, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, Funding/support: This study was funded by the Department of Family Medicine, Mayo Clinic, Rochester, MN. Financial disclosures: None. Author contributions: conception and design, JER, JF; analysis and interpretation of data, JER, GAB, SCA, TW; drafting of the article, JER, GAB, SCA, JF, TW; critical revision of the article, JER. References 1. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, JAMA 2006;295: Linde JA, Erickson DJ, Jeffery RW, et al. The relationship between prevalence and duration of weight loss strategies and weight loss among overweight managed care organization members enrolled in a weight loss trial. Int J Behav Nutr Phys Act 2006;3:3. 3. Bish CL, Blanck HM, Serdula MK, et al. Diet and physical activity behaviors among Americans trying to lose weight: 2000 Behavioral Risk Factor Surveillance System. Obes Res 2005;13: Crawford D, Jeffery RW, French SA. Can anyone successfully control their weight? Findings of a three year communitybased study of men and women. Int J Obes Relat Metab Disord 2000;24: French SA, Jeffery RW, Murray D. Is dieting good for you?: Prevalence, duration and associated weight and behaviour changes for specific weight loss strategies over four years in US adults. Int J Obes Relat Metab Disord 1999;23: Truby H, Baic S, delooy A, et al. Randomised controlled trial of four commercial weight loss programmes in the UK: initial findings from the BBC diet trials [published erratum appears in BMJ 2006;332:1418]. BMJ 2006;332: Gardner CD, Kiazand A, Alhassan S, et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial [published erratum appears in JAMA 2007;298: 178]. JAMA 2007;297: Dansinger MK, Gleason JA, Griffith JL, et al. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA 2005;293: Chaudhry S, Jin L, Meltzer D. Use of a self-report-generated Charlson Comorbidity Index for predicting mortality. Med Care 2005;43: Rohrer JE, Rasmussen N, Adamson S. Illness severity and total visits in family medicine. J Eval Clin Prac. In press Dattilo AM, Kris-Etherton PM. Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis. Am J Clin Nutr 1992;56: Rohrer JE, Merry SP, Lopez-Jimenez F, et al. A patientcentered decision rule for referral of patients to weight-loss programs. Qual Manag Health Care 2007;16: Lavin JH, Avery A, Whitehead SM, et al. Feasibility and benefits of implementing a Slimming on Referral service in primary care using a commercial weight management partner. Public Health 2006;120: Fontaine KR, Barofsky I, Bartlett SJ, et al. Weight loss and health-related quality of life: results at 1-year follow-up. Eat Behav 2004;5: Fontaine KR, Haaz S, Bartlett SJ. Are overweight and obese adults with arthritis being advised to lose weight? J Clin Rheumatol 2007;13: Wee CC, Davis RB, Phillips RS. Stage of readiness to control weight and adopt weight control behaviors in primary care. J Gen Intern Med 2005;20: Copyright 2008 by Turner White Communications Inc., Wayne, PA. All rights reserved. 70 JCOM February 2008 Vol. 15, No. 2