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    • Socioeconomic characteristics in peoples neighborhoods such

    2018-10-30

    Socioeconomic characteristics in peoples\'neighborhoods – such as median level of income and material deprivation – affect individual health through a number of avenues (Riva et al., 2007; Yen et al., 2009; Meijer et al., 2012; Jonker et al., 2015; Schule and Bolte, 2015). Low-SES neighborhoods are less likely to have healthy built environments, including access to healthy food or safe spaces for physical recreation (Yen et al., 2009; Schule and Bolte, 2015). Low-SES individuals are also more likely to live in low-SES neighborhoods and their relatively high rates of smoking, physical inactivity, and obesity account for approximately a third of the increased cardiovascular mortality seen in these areas (Jonker et al., 2015). In addition to their higher rates of unhealthy behaviors (Jonker et al., 2015; Schule and Bolte, 2015), inhabitants of low-SES neighborhoods are less likely to self-manage appropriately (Coventry et al., 2014) or be adherent with medical therapy and recommendations (Gerber et al., 2011). Reduced mobility and increased vulnerability render older adults especially susceptible to the unhealthy effects of low-SES neighborhoods (Yen et al., 2009; Rosso et al., 2011).
    Methods
    Results A sample of 1,518,939 older adults was included in the analysis and is described in Table 1. Older adults living in lower income neighborhoods were significantly more likely to have high chronic condition burden: 18.2% of people in the lowest income neighborhoods had five or more chronic conditions, compared to 14.3% of those in highest income neighborhoods. The prevalence of the 16 chronic conditions by income quintile is presented in Supplementary Figure A. Despite the higher morbidity burden in older adults from low-income neighborhoods, the frequency of their visits to primary care and specialist physicians during follow-up did not differ significantly from people in high-income neighborhoods (Table 2). Of the 130,417 (8.6%) individuals who EHT 1864 cost died during follow-up, a higher proportion was from the lowest income neighborhoods (10.1%) than the highest income neighborhoods (7.6%), however this difference was not statistically significant (Table 3). In unadjusted models (Table 4), there was a significantly higher risk of death associated with increasing age, being male, lower neighborhood income quintile, higher chronic condition burden, living in a non-urban setting, and not having a UPC. The results of the un-stratified multivariable Cox regression model are presented in Supplementary Table B. Table 5 presents the results of neighborhood income stratified Cox proportional hazards models, adjusted for all of the other variables listed. These data show that there was a stepwise increase in hazard of death during the two-year follow-up period for each additional chronic condition present at baseline. Counter to our a priori hypothesis, the effect of increasing chronic condition burden on two-year survival was comparable for older adults in the poorest versus wealthiest neighborhoods in Ontario. This is indicated by the overlapping 95% confidence intervals for chronic condition burden hazard ratios across all five income quintiles. The minor exception to this finding occurs in the 95% confidence intervals for five-plus chronic conditions; the hazard of death with this high chronic condition burden appears to be slightly higher among those in the highest income quintile than the lowest.
    Discussion Our stratified multivariable models also showed that older age and male sex were associated with a higher hazard of death among people living in wealthy neighborhoods versus poorer ones. This unexpected gradient did not exist in the sensitivity analysis among the cohort aged 45 to 64years old, and may be attributable to a hearty survivor effect in the lower SES quintiles of our cohort (Glymour and Greenland, 2008). Having five or more chronic conditions was associated with a marginally higher hazard of death among people in the wealthiest neighborhoods than the poorest ones. This may be attributable to the higher hazard of death associated with specific chronic conditions such as dementia (Supplementary Table C) in high-SES individuals (Qiu et al., 2001).