Examining the association between socioeconomic position and body mass index in 1978 and 2005 among Canadian working-age women and men

Abstract

The SEP-BMI association in Canada is complex, showing variation by gender, by aspect of SEP, across the BMI distribution, and at different time points. The association departs from the more consistent social gradient in health, thereby challenging our view of BMI as a typical health issue.

The Relationship Between Diet Quality and Adult Obesity: Evidence from Canada

“…In women, higher income adequacy levels were weakly associated with lower BMI. These findings agree with those established in the literature: higher income is associated with increased obesity risk in men but decreased risk in women [30,32,33,35].…”

“…Respondents' education status was not statistically significant, which is contrary to many studies showing an inverse association between education and BMI [32,35,26].…”

A quantile regression approach to re-investigate the relationship between sleep duration and body mass index in Taiwan

“…However, we discover the significant relationships between sleep duration and BMI in certain BMI percentiles by using quantile regression to account for the potential heterogeneous effect of sleep duration. Similarly, previous studies that utilize quantile regression are also able to reveal significant relationships between various covariates and BMI in certain quantiles when OLS models show insignificant results (McLaren et al 2010;Shankar 2010). Our results highlight the importance of examining the effects of covariates across the entire distribution of BMI.…”

“…Thus, the different impact of the same covariate on the higher or lower tails of BMI distribution may be revealed. Several studies have shown that quantile regression can provide more information than OLS in exploring the effects of various socio-economic factors on BMI (McLaren et al 2010;Shankar 2010;Stifel and Averett 2009).…”

“…This flexibility gives quantile regression the advantage of modeling data with heterogeneous conditional distributions such as BMI. Recently, quantile regression has been applied to identify the effects of various socio-economic and health factors on BMI (McLaren et al 2010;Shankar 2010;Stifel and Averett 2009). However, sleep duration is not included in these studies.…”