Abstract
BACKGROUND: Results from clinical trials have shown that sugar-sweetened beverages (SSBs) lead to increased body mass index (BMI) and obesity. This relationship has yet to be explored in observational data for nonclinical populations of adults. OBJECTIVE: To compare adults who drank 4+ SSBs daily to those who drank 0 in the population of adults in New York City, and to better understand adult risk factors associated with higher daily SSB consumption and BMI. DESIGN: Secondary analysis of cross-sectional data using propensity score matching. PARTICIPANTS/SETTING: The 2009 New York City Community Health Survey (N=9,934) was used. MAIN OUTCOME MEASURE: BMI. STATISTICAL ANALYSES: For each participant who consumed 4+ SSBs daily, propensity score matching identified matched comparisons who did not drink any SSBs. BMI in unadjusted and matched pairs was tested using t tests. A post hoc analysis compared features of those likely to drink SSBs and those not likely to drink SSBs. RESULTS: In unmatched analyses, participants who consumed 4+ SSBs daily (n=475) had higher BMI than those who consumed 0 SSBs (n=3,818; BMI difference=1.4±0.29; t value=4.81; P<0.001); however, when compared with similar participants using nearest neighbor with replacement matching (n=1,062), the difference between those who consumed 4+ SSBs daily and those who consumed none decreased (BMI difference=0.37±0.36; t value=1.01; P=0.32). Analyses also indicated that those likely to drink SSBs and those unlikely to drink SSBs differed in several important characteristics, including sex, age, race, ethnicity, socioeconomic status, education, diet, and exercise. CONCLUSIONS: The data preclude strong causal conclusions about the role of SSB in obesity. However, our results suggest that there is a subset of participants demographically and behaviorally similar with higher BMI regardless of their self-reported SSB intake. In addition to targeting SSBs, public health policies and programs should identify and address other modifiable aspects of this profile and tailor approaches to the groups identified to be most affected by high BMI.