A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects

This study examined associations between neighborhood disadvantage and body mass index (BMI), and tested whether this differed by level of individual socioeconomic position (SEP). Data were from 9953 residents living in 200 neighborhoods in Brisbane, Australia in 2007. Multilevel linear regression analyses were undertaken by gender to determine associations between neighborhood disadvantage, individual SEP (education, occupation and household income) and BMI (from self-reported height and weight); with cross-level interactions testing whether the relationship between neighborhood disadvantage and BMI differed by level of individual SEP. Both men (Quintile 4, where Quintile 5 is the most disadvantaged β = 0.66 95%CI 0.20, 1.12) and women (Quintile 5 β = 1.32 95%CI 0.76, 1.87) from more disadvantaged neighborhoods had a higher BMI. BMI was significantly higher for those with lower educational attainment (men β = 0.71 95%CI 0.36, 1.07 and women β = 1.66 95%CI 0.78, 1.54), and significantly lower for those in blue collar occupations (men β = −0.67 95%CI −1.09, −0.25 and women β = −0.71 95%CI −1.40, −0.01). Among men, those with a lower income had a significantly lower BMI, while the opposite was found among women. None of the interaction models had a significantly better fit than the random intercept models. The relationship between neighborhood disadvantage and BMI did not differ by level of education, occupation, or household income. This suggests that individual SEP is unlikely to be an effector modifier of the relationship between neighborhood disadvantage and BMI. Further research is required to assist policy-makers to make more informed decisions about where to intervene to counteract BMI-inequalities. This study examined associations between neighborhood disadvantage and body mass index (BMI), and tested whether this differed by level of individual socioeconomic position (SEP). Data were from 9953 residents living in 200 neighborhoods in Brisbane, Australia in 2007. Multilevel linear regression analyses were undertaken by gender to determine associations between neighborhood disadvantage, individual SEP (education, occupation and household income) and BMI (from self-reported height and weight); with cross-level interactions testing whether the relationship between neighborhood disadvantage and BMI differed by level of individual SEP. Both men (Quintile 4, where Quintile 5 is the most disadvantaged β = 0.66 95%CI 0.20, 1.12) and women (Quintile 5 β = 1.32 95%CI 0.76, 1.87) from more disadvantaged neighborhoods had a higher BMI. BMI was significantly higher for those with lower educational attainment (men β = 0.71 95%CI 0.36, 1.07 and women β = 1.66 95%CI 0.78, 1.54), and significantly lower for those in blue collar occupations (men β = −0.67 95%CI −1.09, −0.25 and women β = −0.71 95%CI −1.40, −0.01). Among men, those with a lower income had a significantly lower BMI, while the opposite was found among women. None of the interaction models had a significantly better fit than the random intercept models. The relationship between neighborhood disadvantage and BMI did not differ by level of education, occupation, or household income. This suggests that individual SEP is unlikely to be an effector modifier of the relationship between neighborhood disadvantage and BMI. Further research is required to assist policy-makers to make more informed decisions about where to intervene to counteract BMI-inequalities.