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

Abstract

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.

Is a ‘culture of plus-size women’ the independent effect of neighborhood disadvantage on female BMI? A cross-sectional study in two Chilean Municipalities

“…This study found that neighborhood disadvantage has an effect on female BMI that is independent of individual disadvantage, as previous research reported (Feng and Wilson, 2015;Rachele et al, 2019;King et al, 2006). Unlike preceding studies, in this sample of Chilean women, the independent effect of neighborhood disadvantage on BMI is explained by body size dissatisfaction.…”

“…Studies about neighborhoods and overweight/obesity show that the association between the socioeconomic conditions of residential areas and BMI is much more pronounced in women than in men (Harrington and Elliott, 2009;Matheson et al, 2008;Rundle et al, 2008). Research has shown as well that neighborhood disadvantage has an effect on BMI that is independent of individual disadvantage, which could be at least as important as individual SES in explaining individual differences in excess weight; however, this effect is observed mainly in women (Feng and Wilson, 2015;Rachele et al, 2019;King et al, 2006).…”

Associations between obesity and neighborhood socioeconomic status: Variations by gender and family income status

“…Neighborhood deprivation was found to be associated with higher BMI for women but lower BMI for men in Canada (Matheson, Moineddin, & Glazier, 2008). Such relationship was also found to be stronger for women than for men in Australia (Feng & Wilson, 2015; Rachele et al, 2019). Neighborhood education level was associated with weight outcomes for women but not men in a Brazilian study (Boing & Subramanian, 2015).…”

“…On the one hand, compared with higher-income individuals, lower-income individuals may be more affected by neighborhood SES because they may benefit more from public goods offered by higher-SES neighborhoods to compensate for limited individual resources while experiencing intensified unhealthy consequences of living in lower-SES neighborhoods due to limited public goods (Wen & Christakis, 2005). This “deprivation amplification,” a process whereby neighborhood conditions amplify individual disadvantages resulting in detrimental health consequences, has rarely been tested on obesity outcomes with the exception of a recent Australian study (Rachele et al, 2019). The more affluent residents may also provide role models for mainstream social norms, maintain social cohesion (Child et al, 2019), and uphold neighborhood institutions, and therefore increase the wellbeing of the poor (Wilson, 1987, 1996).…”

Diabetes and physical activity: A prospective cohort study

“…( 5. Annual gross household income (AUD) at each wave: The 13 response options were recategorized as: (1) < $25,999, (2) $26,000-51,999 (3) $52,000-72,799, (4) $72,800-129,999, (5) � $130,000, (6) Don't Know/ Don't want to answer this, as for previous analyses of HABI-TAT data [25].…”