The relationship between Social Determinants of Health (SDoH) and death from cardiovascular disease or opioid use in counties across the United States (2009–2018)

Abstract

Background Death from cardiovascular disease (CVD) has been a longstanding public health challenge in the US, whereas death from opioid use is a recent, growing public health crisis. While population-level approaches to reducing CVD risk are known to be effective in preventing CVD deaths, more targeted approaches in high-risk communities are known to work better for reducing risk of opioid overdose. For communities to plan effectively in addressing both public health challenges, they need information on significant community-level (vs individual-level) predictors of death from CVD or opioid use. This study addresses this need by examining the relationship between 1) county-level social determinants of health (SDoH) and CVD deaths and 2) county-level SDoH and opioid-use deaths in the US, over a ten-year period (2009–2018). Methods A single national county-level ten-year ‘SDoH Database’ is analyzed, to address study objectives. Fixed-effects panel-data regression analysis, including county, year, and state-by-year fixed effects, is used to examine the relationship between 1) SDoH and CVD death-rate and 2) SDoH and opioid-use death-rate. Eighteen independent (SDoH) variables are included, spanning three contexts: socio-economic (e.g., race/ethnicity, income); healthcare (e.g., system-characteristics); and physical-infrastructure (e.g., housing). Results After adjusting for county, year, and state-by-year fixed effects, the significant county-level positive SDoH predictors for CVD death rate were, median age and percentage of civilian population in armed forces. The only significant negative predictor was percentage of population reporting White race. On the other hand, the four significant negative predictors of opioid use death rate were median age, median household income, percent of population reporting Hispanic ethnicity and percentage of civilian population consisting of veterans. Notably, a dollar increase in median household income, was estimated to decrease sample mean opioid death rate by 0.0015% based on coefficient value, and by 20.05% based on effect size. Conclusions The study provides several practice and policy implications for addressing SDoH barriers at the county level, including population-based approaches to reduce CVD mortality risk among people in military service, and policy-based interventions to increase household income (e.g., by raising county minimum wage), to reduce mortality risk from opioid overdoses.

The Future of the United States Overdose Crisis: Challenges and Opportunities

“…Three priorities should be pursued. First, the expansion of social and economic policies that aim to raise income and provide buffers against job loss in poor and working-class communities, and policies that aim to protect workers, could prove to be a promising primary prevention strategy [45][46][47] to reduce initiation of misuse of both opioids and stimulants, thus reducing the risk for polydrug use and overdose. Prior evidence suggests that the adoption of more generous unemployment in-surance benefits reduces the harmful effects of job loss on overdose.…”

The effects of minimum wages on (almost) everything? A review of recent evidence on health and related behaviors

“…The only reference to drugs in the literature I review is the Agan and Makowsky (forthcoming) finding that minimum wages reduce recidivism for drug crimes, which they interpret as the minimum wage reducing revenue-generating crime. Rangachari et al (2022) hypothesize that a higher minimum wage might reduce opioid overdoses but present no evidence. 8 Freeman (1996), for example, notes that "[I]f the elasticity of demand for minimum wage workers exceeds one [in absolute value], the minimum wage will reduce rather than increase the share of earnings going to the low-paid" (p. 641, italicized text added).…”

Life expectancy at birth for the rf population: prediction based on modeling influence exerted by a set of socio-hygienic determinants on age-specific mortality rates exemplified by diseases of the circulatory system

“…The whole set of determinants (without primary incidence rates) N o t e : * is the model showing LEB dependence on socio-hygienic determinants (SHD), which we described in our previous study [11]; ** is the set of models showing dependence of age-specific mortality rates on sociohygienic determinants, which is analyzed in the present work with the following LEB calculation.…”

“…We also established another significant factor with comparable priority. It characterized diets, namely, consumption of vegetables and melons growing by 34.0 % against the current levels up to the recommended standards 11 . This target achieved, effects produced on LEB would be positive in both larger age groups, resulting in its growth by 6 and 25 days accordingly.…”

“…Available at: http://www.consultant.ru/document/cons_doc_LAW_317388/4e8c28415c3cabb0f45fa6ed843c85bd7dbee4b9/ (August 15, 2022) (in Russian). 11 Ob utverzhdenii Rekomendatsii po ratsional'nym normam potrebleniya pishchevykh produktov, otvechayushchikh sovremennym trebovaniyam zdorovogo pitaniya: Prikaz Ministerstva zdravookhraneniya RF ot 19 avgusta 2016 g. № 614 [On approval of the Recommendations on rational consumption of foods that correspond to up-to-date standards of a healthy diet: The Order by the RF Public Healthcare Ministry dated August 19, 2016 Discussion. As we were modeling relations between the analyzed socio-hygienic determinants and age-specific mortality rates due to CVD, we established low explained variance of the analyzed factors in age groups younger than 30 years and, in addition, declining values of the determination coefficient in age groups 70 years and older although it still remained higher than 0.55.…”