The material and psychosocial/psychological pathways that help explain socioeconomic inequalities in allostatic load and health are not mutually exclusive and may be difficult to separate (Bartley, 2003).
Material factors, namely home tenure and income status, and smoking have important roles in explaining socioeconomic disparities in allostatic load, particularly when accumulated over time.
In contrast with Reid et al. (2009), who identified AC as a separate principal factor for their national HVI, AC/cooler loaded with socioeconomic variables in our analysis.
The results from many other studies of work-related factors such as occupational socioeconomic status, physical work loading, and psychosocial aspects [ 3, 7, 8] and how they predict DP due to MSD are in line with our results.
Moreover, social adversity in adolescence (in women) and young adulthood (in men) was related to allostatic load, independently of cumulative socioeconomic disadvantage and also of later adversity exposure during adulthood.
We have previously demonstrated that the life course accumulation of low socioeconomic status (SES) relates to allostatic load [ 30], and because cumulative SES also could be expected to influence adversity exposure it was considered a potential confounder.
Prior studies have suggested that the effects of depression may be more severe in Blacks and those with low socioeconomic status, possibly due to increased allostatic load from socioeconomic and cultural stressors., - The Dutch Famine studies and our own analysis of the effects of maternal cigarette smoking suggest that epigenetic dysregulation may be sex-specific.
Of the 50 cities with >70.0000 inhabitants, we selected municipalities according to socio-demographic parameters associated with high risk load (maternal age, parity, ethnicity, and socioeconomic status) and perinatal outcome data (overall 'Big4' and perinatal mortality prevalence).
At the start of the study low CD4 counts, high viral load, a lower level education, depression and socioeconomic dependence on other people were found to be predictors of poor HRQoL.
The patterns of association within the socioeconomic construct were fairly consistent, however, meaning the variables that loaded negatively in the urban counties also loaded negatively in the least urban counties.
