Summary: Socioeconomic Inequality In Health

The next natural step after determining the socioeconomic inequalities in a health variable is to disentangle the sources of the socioeconomic inequalities. The method for decomposing the inequalities into their contributing factors proposed by Wagstaff et al (2003) has become a staple in empirical research on socioeconomic inequalities in health. Wagstaff et al (2003) have demonstrated that if the relevant health outcome, h, can be expressed as a linear function of a set of k covariates, as follows: h=α+∑_k▒〖β_k x_k+ε〗

Then substituting the linear regression of the health outcome in the formula for concentration index and performing some algebraic manipulation yields the following formula for the decomposition (which, following Heckley et

Erreygers and Kessels (2013) point to the fact that, being derived entirely from the health regression, the decomposition method by Wagstaff et al (2003) only focuses on one dimension, health, and ignores the income or socioeconomic status dimension. Therefore, in the context of bivariate rank dependent indices, which depend on joint distribution of health and socioeconomic status, WDW decomposition inadvertently explains the degree of variation only in the health variable rather than explaining the covariance between health and the socioeconomic rank (Heckley, 2016). Erreygers and Kessels (2013) and Erreygers and Kessels (2015) propose modified decomposition procedures to correct the unidimensional character of the WDW decomposition, but their procedures, as critiqued by Heckley et al (2016), are only suitable for absolute inequality measures and not relative inequality measures like the standard concentration

The poorer segments of the population are the worst affected by the obesity epidemic in richer societies. A number of studies conducted recently lend additional credence to this conclusion. These studies, for instance, find that in countries such as the United States of America, United Kingdom Spain, Sweden, and Canada, there is a clear inverse relationship between socioeconomic status and obesity (Zhang and Wang, 2004; El Sayed et al, 2012; Ventosa and Urbanos-Garrido, 2016; Rodriguez-Caro et al, 2016; Hajizadeh et al, 2013). The magnitude and direction of the socioeconomic gradient, however, varies within population sub-groups. Zhang and Wang (2004) assess socioeconomic disparities in overweight and obesity in the United States of America, stratifying the study population by gender, age and ethnicity, and discover substantial heterogeneity in the socioeconomic disparities in overweight and obesity across the strata. A systematic review and meta-regression analysis of the obesity epidemic in the United States by Wang and Meydoun (2007) also unearths substantial disparities in obesity among adults along various dimensions including ethnicity, education and socioeconomic status. Using nationally representative Canadian Community Health Surveys, Hajizadeh et al (2013) find that risk of obesity is higher among richer males and