Neighborhood context and metabolic syndrome among youth: A multilevel analysis using the NHANES

The purpose of this study was to estimate the relationship between neighborhood context and metabolic syndrome in youth. This paper investigates neighborhood characteristics as explanatory factors for the variation of metabolic syndrome in children and adolescents across the United States. This study applied a geocoded national health survey in a multilevel modeling framework. We constructed a multilevel logistic regression model to evaluate the influence of individual demographic characteristics, zip code, county, and state on the metabolic syndrome measures from the National Health and Nutrition Examination Survey, restricting aged 12-19 years with complete information. Multilevel models in this study explained state-level, county-level and zip code-level variances significantly associated with metabolic syndromes across U.S. neighborhoods. In addition, neighborhood characteristics partially explained ethnic disparities in metabolic syndromes, net of individual-level adjustment for parents’ sociodemographic factors, household income, unhealthy and risky behaviors, social support and network. Living in socially and economically disadvantaged areas was associated with higher prevalence of metabolic syndrome among youth in the Unites States. Like many other multilevel modeling studies of metabolic syndrome among adults, the result of our research demonstrates that locale can be as significant as individual characteristics such as parents' socioeconomic postion and ethnicity in the development of the youth metabolic syndrome epidemic.