title: Using Decomposition Analysis to Identify Modifiable Racial Disparities in the Distribution of Blood Pressure in the United States.
abstract: To lower the prevalence of hypertension and racial disparities in hypertension, public health agencies have attempted to reduce modifiable risk factors for high blood pressure, such as excess sodium intake or high body mass index. In the present study, we used decomposition methods to identify how population-level reductions in key risk factors for hypertension could reshape entire population distributions of blood pressure and associated disparities among racial/ethnic groups. We compared blood pressure distributions among non-Hispanic white, non-Hispanic black, and Mexican-American persons using data from the US National Health and Nutrition Examination Survey (2003-2010). When using standard adjusted logistic regression analysis, we found that differences in body mass index were the only significant explanatory correlate to racial disparities in blood pressure. By contrast, our decomposition approach provided more nuanced revelations; we found that disparities in hypertension related to tobacco use might be masked by differences in body mass index that significantly increase the disparities between black and white participants. Analysis of disparities between white and Mexican-American participants also reveal hidden relationships between tobacco use, body mass index, and blood pressure. Decomposition offers an approach to understand how modifying risk factors might alter population-level health disparities in overall outcome distributions that can be obscured by standard regression analyses.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Basu
authors.forename: Anthony
authors.initials: A
authors.lastname: Hong
authors.forename: Arjumand
authors.initials: A
authors.lastname: Siddiqi
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000428:Alcohol Drinking / Q000009:adverse effects / Q000208:ethnology*; D015992:Body Mass Index; D015897:Comorbidity; D005260:Female; D040261:Harm Reduction; D054624:Health Status Disparities; D006801:Humans; D006973:Hypertension / Q000208:ethnology* / Q000209:etiology / Q000517:prevention & control; D016015:Logistic Models; D008297:Male; D017058:Mexican Americans / Q000706:statistics & numerical data; D054525:Minority Health / Q000706:statistics & numerical data*; D009749:Nutrition Surveys; D015995:Prevalence; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000208:ethnology*; D012982:Sodium, Dietary / Q000009:adverse effects*; D018709:Statistics, Nonparametric; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data
chemical_list: D012982:Sodium, Dietary
keywords: health disparities; hypertension; population studies; statistical methods