Social Capital and COVID-19 Deaths: An Ecological Analysis in Japan

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Social contextual factors could determine mortality by the coronavirus disease 2019 (COVID-19), with social capital as a potential determinant. This study aimed to examine the association between prefecture-level social capital and COVID-19 deaths in Japan. Data on the cumulative number of COVID-19 deaths per 100,000 individuals between 1 October 2020 and 30 June 2021 in 47 prefectures were obtained from the government open-access database. Prefecture-level social capital was collected from a large-scale web-based nationwide survey conducted between August and September 2020. We included trust in neighbors, norm of reciprocity in the neighborhood, and trust in the national government as cognitive social capital, and neighborhood ties and social participation as structural social capital. The cumulative COVID-19 deaths per 100,000 individuals (1 October 2020 to 30 June 2021) ranged from 0.15 to 27.98 in 47 prefectures. A multiple regression analysis after adjusting for covariates showed that a greater norm of reciprocity and government trust were associated with fewer COVID-19 deaths during the first and second 3-month periods of observation. In the third 3-month period, the association between COVID-19 deaths and government trust became nonsignificant. Trust in neighbors, neighborhood ties, and social participation were not related to COVID-19 deaths during any time period. The disparity of COVID-19 deaths by prefecture in Japan can be explained by cognitive social capital. This study suggests that the association between social capital and COVID-19 deaths may vary according to the dimension of social capital and time period.

Related collections

Most cited references 27

Record: found
Abstract: found
Article: found

Is Open Access

OpenSAFELY: factors associated with COVID-19 death in 17 million patients

Elizabeth J Williamson, Alex J Walker, Krishnan Bhaskaran … (2020)

COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.