Social Determinants of Health and Risk of SARS-CoV-2 Infection in Community-Dwelling Older Adults Living in a Rural Latin American Setting

Abstract

High social risk, as measured by the social determinants of health (SDH), may increase the risk of SARS-CoV-2 infection. However, this association has not been studied in rural communities. Using the Atahualpa Project cohort, we aimed to assess the association between SDH and SARS-CoV-2 seropositivity in community-dwelling older adults living in rural Ecuador. SARS-CoV-2 antibodies were determined in 319 individuals aged ≥ 60 years that completed a validated field instrument to assess their social risk before the introduction of this novel pandemic. Multivariate models were fitted to assess the independent association between SDH—and each of their components—and SARS-CoV-2 seropositivity, after adjusting for relevant covariates. According to the Gijon scale, 102 (32%) individuals had a high social risk (≥ 10 points). A total of 141 (44%) individuals were seropositive to SARS-CoV-2. A fully-adjusted logistic regression model showed an independent) association between social risk and SARS-CoV-2 positivity (OR 1.15; 95% CI 1.04–1.27; p = 0.008). For every unit of the total SDH score, the odds of SARS-CoV-2 seropositivity increased 15% (95% CI 3.7–27%). In addition, multivariate models showed that the individual component of SDH more strongly associated with SARS-CoV-2 seropositivity was housing, which suggested that lack of basic home facilities may increase the risk of SARS-CoV-2 infection. Knowledge on the association between high social risk and SARS-CoV-2 infection is indispensable for the development of cost-effective preventive strategies for controlling modifiable factors that are in the path of SARS-CoV-2 infection among older adults living in underserved communities.

The Association of Social Determinants of Health With COVID‐19 Mortality in Rural and Urban Counties

“…found that poor quality of life in the cancer survivors was also noticed in residents living in the highly segregated black counties. Del Brutto et al 74 . found that in rural communities of Ecuador, for each unit increase in social risk measured by the Gijon scale, the infection rates of COVID‐19 increased by 15%.…”

Late incidence of SARS-CoV-2 infection in a highly-endemic remote rural village. A prospective population-based cohort study

“…This problem has also been anticipated in Brazilian aborigines living in closed communities, since they will be forced to travel to highly infected cities to receive a compensatory monetary bonus from the government [8]. To the immunological naivete of these populations, it must be added the adverse circumstances in which they live regarding inadequacy of control measures, poor social determinants of health and inadequate access to medical care [13]. Rural communities of Latin America do not seem to be prepared for this situation, and will likely be one of the hot spots of this pandemic.…”

“…The study was conducted in Atahualpa, a remote rural village in coastal Ecuador, where previous studies on SARS-CoV-2 infection have been conducted [9,[11][12][13]. Characteristics of Atahualpa residents have been described elsewhere [14].…”

“…The village has electricity and almost all houses have piped water. However, about 20% of houses do not have a flushing toilet and still use open latrines [13]. The population is homogeneous regarding race/ethnicity, living conditions, and dietary habits; most men belong to the blue collar class (artisan carpenters) and most women are homemakers.…”

Implementing an Urban Public Health Observatory for (Near) Real-Time Surveillance for the COVID-19 Pandemic

“…The Center for Disease Control and Prevention (CDC) provides a taxonomy for SDoH that is comprised of 6 domains: economic stability (e.g., income), education (e.g., educational attainment and graduation rates), health and healthcare access ( access to health and how well an individual or group understands the health information to make the appropriate decisions), social and community context (variables reflect the social setting that an individual resides and their community involvement), demographics (e.g., race/ethnicity, sex, age), and neighborhood and built environment (variables that relate to the physical surrounding environment and have the potential to overlap other domains) [8,9]. SDoH are associated with COVID-19 transmission and mortality [10][11][12][13][14][15][16][17]. SDoH overlap and interact in real-world setttings, requiring careful disentanglement of their individual downstream inpact on health outcomes such as COVID-19 spread.…”