Social capital II: determinants of economic connectedness

Chetty, Raj; Jackson, Matthew O.; Kuchler, Theresa; Stroebel, Johannes; Hendren, Nathaniel; Fluegge, Robert B.; Gong, Sara; Gonzalez, Federico; Grondin, Armelle; Jacob, Matthew; Johnston, Drew; Koenen, Martin; Laguna-Muggenburg, Eduardo; Mudekereza, Florian; Rutter, Tom A.; Thor, Nicolaj; Townsend, Wilbur; Zhang, Ruby; Bailey, Mike; Barberá, Pablo; Bhole, Monica; Wernerfelt, Nils

doi:10.1038/s41586-022-04997-3

Cited by 99 publications

(43 citation statements)

References 39 publications

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“…Doing so requires an understanding of the determinants of EC and potential interventions to increase it. We address these questions in the companion paper 9 , in which we study why economic connectedness varies with SES and how we can increase connectedness among individuals with low SES.…”

Section: Discussionmentioning

confidence: 99%

“…There is less homophily by parental SES during childhood than by own SES in adulthood, with a slope of 0.31 instead of 0.44. Much of this difference in slopes arises from the fact that SES in adulthood among friends from high school is more similar than their parents' SES, perhaps because children who befriend each other tend to follow similar trajectories 9 .…”

Section: Childhood Economic Connectednessmentioning

confidence: 99%

“…This geographical variation in connectedness is partially driven by differences in the share of high-SES individuals in an area and partly by differences in the rates at which low-SES individuals befriend high-SES individuals in their area. We decompose the relative contributions of these two factors, which we refer to as exposure and friending bias, in the companion paper 9 .…”

Section: Economic Connectedness Across Areasmentioning

confidence: 99%

“…However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers 9 , we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering.…”

mentioning

confidence: 99%

“…Here, we use data on the social networks of 72.2 million users of Facebook aged between 25 and 44 years to construct and publicly release (https://www.socialcapital.org) new measures of social capital for each ZIP code in the United States. In a companion paper 9 , we also release data on social capital for each high school (secondary school) and college (university). As in previous research using Facebook data [22][23][24][25][26] (Supplementary Information C.1), we use social network data as a proxy for real-world friendships rather than online interactions per se.…”

mentioning

confidence: 99%

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Social capital I: measurement and associations with economic mobility

Chetty

Jackson

Kuchler

et al. 2022

Nature

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266

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Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health1–8. However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers9, we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date10,11. Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality12–14. To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org.

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Section: Discussionmentioning

confidence: 99%

Section: Childhood Economic Connectednessmentioning

confidence: 99%

Section: Economic Connectedness Across Areasmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Social capital I: measurement and associations with economic mobility

Chetty

Jackson

Kuchler

et al. 2022

Nature

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266

121

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Association of Population Well-Being With Cardiovascular Outcomes

et al. 2023

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ImportanceMortality from cardiovascular disease (CVD) varies across communities and is associated with known structural and population health factors. Still, a population’s well-being, including sense of purpose, social relationships, financial security, and relationship to community, may be an important target to improve cardiovascular health.ObjectiveTo examine the association of population level measures of well-being with rates of CVD mortality in the US.Design, Setting, and ParticipantsThis cross-sectional study linked data from the Gallup National Health and Well-Being Index (WBI) survey to county-level rates of CVD mortality from the Centers for Disease Control and Prevention Atlas of Heart Disease and Stroke. Participants were respondents of the WBI survey, which was conducted by Gallup with randomly selected adults aged 18 years or older from 2015 to 2017. Data were analyzed from August 2022 to May 2023.Main Outcomes and MeasuresThe primary outcome was the county-level rate of total CVD mortality; secondary outcomes were mortality rates for stroke, heart failure, coronary heart disease, acute myocardial infarction, and total heart disease. The association of population well-being (measured using a modified version of the WBI) with CVD mortality was assessed, and an analysis of whether the association was modified by county structural factors (Area Deprivation Index [ADI], income inequality, and urbanicity) and population health factors (percentages of the adult population who had hypertension, diabetes, or obesity; were currently smoking; and were physically inactive) was conducted. Population WBI and its ability to mediate the association of structural factors associated with CVD using structural equation models was also assessed.ResultsWell-being surveys were completed by 514 971 individuals (mean [SD] age 54.0 [19.2] years; 251 691 [48.9%] women; 379 521 [76.0%] White respondents) living in 3228 counties. Mortality rates for CVD decreased from a mean of 499.7 (range, 174.2-974.7) deaths per 100 000 persons in counties with the lowest quintile of population well-being to 438.6 (range, 110.1-850.4) deaths per 100 000 persons in counties with the highest quintile of population well-being. Secondary outcomes showed similar patterns. In the unadjusted model, the effect size (SE) of WBI on CVD mortality was −15.5 (1.5; P &lt; .001), or a decrease of 15 deaths per 100 000 persons for each 1-point increase of population well-being. After adjusting for structural factors and structural plus population health factors, the association was attenuated but still significant, with an effect size (SE) of −7.3 (1.6; P &lt; .001); for each 1-point increase in well-being, the total cardiovascular death rate decreased by 7.3 deaths per 100 000 persons. Secondary outcomes showed similar patterns, with mortality due to coronary heart disease and heart failure being significant in fully adjusted models. In mediation analyses, associations of income inequality and ADI with CVD mortality were all partly mediated by the modified population WBI.Conclusions and RelevanceIn this cross-sectional study assessing the association of well-being and cardiovascular outcomes, higher well-being, a measurable, modifiable, and meaningful outcome, was associated with lower CVD mortality, even after controlling for structural and cardiovascular-related population health factors, indicating that well-being may be a focus for advancing cardiovascular health.

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Community Social Capital and Population Health Outcomes

Linde,

Egede

2023

JAMA Netw Open

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ImportanceWhile the association between economic connectedness and social mobility has now been documented, the potential linkage between community-level economic connectedness and population health outcomes remains unknown.ObjectiveTo examine the association between community social capital measures (defined as economic connectedness, social cohesion, and civic engagement) and population health outcomes (defined across prevalence of diabetes, hypertension, high cholesterol, kidney disease, and obesity).Design, Setting, and ParticipantsThis cross-sectional study included communities defined at the zip code tabulation area (ZCTA) level in all 50 US states. Data were collected from January 2021 to December 2022.Main Outcomes and MeasuresMultivariable regression analyses were used to examine the association between population health outcomes and social capital. Adjusted analyses controlled for area demographic variables and county fixed effects. Heterogeneities within the associations based on the racial and ethnic makeup of communities were also examined.ResultsIn this cross-sectional study of 17 800 ZCTAs, across 50 US states, mean (SD) economic connectedness was 0.88 (0.32), indicating friendship sorting on income; the mean (SD) support ratio was 0.90 (0.10), indicating that 90% of ties were supported by a common friendship tie; and the mean (SD) volunteering rate was 0.08 (0.03), indicating that 8% of individuals within a given community were members of volunteering associations. Mean (SD) ZCTA diabetes prevalence was 10.8% (2.9); mean (SD) high blood pressure prevalence was 33.2% (6.2); mean (SD) high cholesterol prevalence was 32.7% (4.2), mean (SD) kidney disease prevalence was 3.0% (0.7), and mean (SD) obesity prevalence was 33.4% (5.6). Regression analyses found that a 1% increase in community economic connectedness was associated with significant decreases in prevalence of diabetes (−0.63%; 95% CI, −0.67% to −0.60%); hypertension (−0.31%; 95% CI, −0.33% to −0.29%); high cholesterol (−0.14%; 95% CI, −0.15% to −0.12%); kidney disease (−0.48%; 95% CI, −0.50% to −0.46%); and obesity (−0.28%; 95% CI, −0.29% to −0.27%). Second, a 1% increase in the community support ratio was associated with significant increases in prevalence of diabetes (0.21%; 95% CI, 0.16% to 0.26%); high blood pressure (0.16%; 95% CI, 0.13% to 0.19%); high cholesterol (0.16%; 95% CI, 0.13% to 0.19%); kidney disease (0.17%; 95% CI, 0.13% to 0.20%); and obesity (0.08%; 95% CI, 0.06% to 0.10%). Third, a 1% increase in the community volunteering rate was associated with significant increases in prevalence of high blood pressure (0.02%; 95% CI, 0.01% to 0.02%); high cholesterol (0.03%; 95% CI, 0.02% to 0.03%); and kidney disease (0.02%; 95% CI, 0.01% to 0.02%). Additional analyses found that the strength of these associations varied based on the majority racial and ethnic population composition of communities.Conclusions and RelevanceIn this study, higher economic connectedness was significantly associated with better population health outcomes; however, higher community support ratios and volunteering rates were both significantly associated with worse population health. Associations also differed by majority racial and ethnic composition of communities.

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Social capital II: determinants of economic connectedness

Cited by 99 publications

References 39 publications

Social capital I: measurement and associations with economic mobility

Social capital I: measurement and associations with economic mobility

Association of Population Well-Being With Cardiovascular Outcomes

Community Social Capital and Population Health Outcomes

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