Social factors, health policy, and environment: implications for cardiovascular disease across the globe

Abstract

Cardiovascular disease (CVD) is the leading cause of deaths worldwide, with 80% occurring in low- and middle-income countries. These countries are characterized by rapid urbanization, poorly funded health systems, poor access to prevention and treatment strategies, and increasing age and a higher prevalence of chronic disease. Rapid urbanization has contributed to the significant environmental and societal changes affecting daily life habits and cardiovascular health. There is growing awareness that environmental and social exposures and policies can influence CVD directly or through behavioural risk factors. However, much of this knowledge comes from studies in high-income countries and is applied to low- and middle-income countries without evidence to indicate this is appropriate. This state-of-the-art review will present and synthesize key findings from the Prospective Urban Rural Epidemiology study and related studies that have aimed to understand the environmental, social, and policy determinants of cardiovascular health in countries across varying levels of economic development through an urban/rural lens. Emerging from these findings are future policy and research recommendations to accelerate the reduction of the global burden of CVD.

Keywords: Access to care; Cardiovascular disease; Diet; Environment; Physical activity; Pollution; Social determinants.

Graphical Abstract

Figure 1

Environmental factors that have been linked to human behaviours and established risk factors that cause cardiovascular diseases. Reprinted with permission from Chow et al.

Figure 2

Graphical summary of the Prospective Urban Rural Epidemiology study

Figure 3

Physical activity patterns by country income level stratified by type of activity and urban/rural area residency. PA, physical activity; Rec, recreational; Non-rec, non-recreational; HIC, high-income country; UMIC, upper middle-income country; LMIC, lower middle-income country; LIC, low-income country

Figure 4

Fruit and vegetable servings per day (bars) and affordability (line) by country income level. *Affordability is the percentage of household income spent to purchase two servings of fruit and three servings of vegetables per day. HIC, high-income country; UMIC, upper middle-income country; LMIC, lower middle-income country; LIC, low-income country. Modified from Miller et al.

Figure 5

Tobacco-selling outlets in urban or rural study community, 16 countries, 2009–12. HIC, high-income country; UMIC, upper middle-income country; LMIC, lower middle-income country; LIC, low-income country. Reprinted with permission from Savell et al.

Figure 6

Age-standardized and sex-standardized proportion of PURE participants with INTERHEART risk score > 10 in high-income, middle-income, and low-income countries by education (A) and 28-day case fatality rate after a first cardiovascular event and odds ratio by country income and level of education among participants without previous cardiovascular disease (B). Data are adjusted for age and gender. CFR, case fatality rate; OR, odds ratio. Reprinted with permission from Rosengren et al.

Figure 7

Age-sex adjusted prevalence of social isolation (%) by country income levels (A) and by residence areas (B). The prevalence of social isolation is the lowest in the low-income countries (A). The prevalence of social isolation is higher in the urban areas (B). LIC, low-income country; MIC, middle-income countries; HIC, high-income countries. Reprinted with permission from Naito et al.

Figure 8

Percentage availability of aspirin, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and statins. P for trend < .0001 across country income levels (excluding India due to large generic pharmaceutical industry) for both urban and rural areas. n, total number of communities in each location of each country income group. Reprinted with permission from Khatib et al.

Figure 9

Effects of outdoor air pollution (left) and household air pollution (right). In the left panel, red lines show linear hazard ratios and blue lines show non-linear hazard ratios for cardiovascular disease mortality (A), all cardiovascular disease events (B), stroke (C), and myocardial infarction (D). Shaded areas represent 95% confidence intervals for the non-linear models. In the right panel, hazard ratio and 95% confidence interval for living in a household using solid fuels for cooking. Graphs on the left reprinted with permission from Hystad et al. (2020) with additional modification from Hystad et al. (2019)

Figure 10

Locations of PURE communities (A) and the mean annual temperature anomalies predicted under the RCP 8.5 scenario for the 2020–99 time period (B)