|
Obesity-related medical problems are among the most serious health problems facing U.S. adults.Approximately 65% of U.S. adults are overweight (body mass index[BMI] _25 kg/m2), and approximately half of overweight adults are obese (BMI _30 kg/m2) (1). Coronary heart disease is twice as common in obese people as in normal-weight people, and obesity substantially exacerbates all metabolic cardiac risk factors (2, 3). Obesity is associated with decreased longevity (4 -7) and quality of life (8).Dietary and lifestyle modification efforts are the primary methods for treating and preventing obesity.Severalimportantsystematic reviews show that dietary-based lifestyle modification efforts can statistically significantly improve body weight and decrease related medical problems (9 -17). The average weight change due to dietary counseling compared with usual care is unclear, particularly over the long term.We systematically reviewed and quantitatively synthesized published data on the net effect of dietary-based counseling compared with usual care over time. We also evaluated various sources of heterogeneity on the effectiveness of weight loss strategies. METHODS Data Sources and Searches The starting point for the literature search was an extensive systematic review published in 1998, on which current clinical guidelines regarding identification, evaluation,and treatment of overweight and obesity in adults are based (9). For that report, a 24-member panel of experts methodically intervention, such as general verbal or written advice given at baseline, which was designed to approximate usual care).We excluded studies in which patients were younger than 18 years, the goal of the intervention was not weight loss,exercise was the only intervention, mean baseline BMI wasless than 25 kg/m2, or SEs could not be determined. In keeping with the eligibility criteria of the 1998 evidence report (9), we also excluded studies with interventions that lasted fewer than 12 weeks and those that did not report effects at a minimum of 16 weeks. Data Extraction and Quality Assessment One of 3 reviewers used standardized forms to extract all studies that met the eligibility criteria.A second reviewer reviewed all extracted data. When necessary, disagreements were resolved by consensus of 2 or more authors.For all included studies, we extracted or estimated the net change in BMI and the SE of the net change from the reported data. Net change was defined as the change from baseline in the treatment group minus the change from baseline in the control group. We did not analyze change from baseline in the treatment groups alone (without subtracting changes in the control groups). When necessary, we calculated the change in BMI by using the ratio of baseline BMI to kilograms as the conversion factor.For the 9 studies that did not report such data, we assumed a ratio of 2.7 (equal to a height of 1.64 m), which corresponded well to ratios from other studies. Within studies, we preferentially chose data from intention-to-treat analyses; however,we retained data from all studies regardless of whether their analyses omitted missing data, used last observations carried forward, or replaced missing data with baseline data. For each study that reported change in BMI at multiple time points, we calculated the slopes of the net change in BMI across the different time points.When necessary, the SE of the net change was estimated from the SEs of the changes in BMI in the inter a random-effects model. The calculated SEs of the slopes were used only for weighting the studies in the metaanalysis,not for estimating the statistical significance of the slopes. These SEs capture the relative variances of the net weight changes from baseline at the multiple time points but do not accurately estimate the SEs of the slopes themselves.For each period, we compared the effect of diabetes (inclusion vs. exclusion of patients with diabetes) andint ervention (diet and exercise vs. diet alone) by using 2-sample t tests.In addition, all data were analyzed in a random-effects model meta-regression--ameta-analytic technique of multivariable linear regression across studies--according to the method of Morris (21) as described by Berkey and colleagues (22). This model is similar to the DerSimonian and Laird (20) random-effects model meta-analysis. We regressed net change BMI against time in months. We also conducted analyses with study-level variables that were potentially associated with the magnitude of the treatment effect, based on known associations within individual studies or on what we considered to be clinically or methodologically relevant from previous studies.These variables included intervention type (diet vs. diet and exercise) (23),frequency of support meetings (prorated for the first year)(24), recommended calorie intake per day (9), whether patients with diabetes were included (25-27), whether intention-to-treat analyses were performed, withdrawal rates, and methodological quality of the studies. Author: promotive solution Michael L. Dansinger provides articles about health medicine. Dietary and lifestyle modification efforts are the primary treatments for people who are obese or overweight. View Count: 387
|
|||||||||||||||||||||||||||||||
 |
 |
 |
 |