Social vulnerability and aging of elderly people in the United States.
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ABSTRACT:
SUBMITTER: Abeliansky AL
PROVIDER: S-EPMC8463908 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSocial vulnerability is related to the health of elderly people, but its measurement and relationship to frailty are controversial. The aims of the present study were to operationalize social vulnerability according to a deficit accumulation approach, to compare social vulnerability and frailty, and to study social vulnerability in relation to mortality.Methods and findingsThis is a secondary analysis of community-dwelling elderly people in two cohort studies, the Canadian Study of Health and Aging (CSHA, 1996/7-2001/2; N = 3707) and the National Population Health Survey (NPHS, 1994-2002; N = 2648). Social vulnerability index measures that used self-reported items (23 in NPHS, 40 in CSHA) were constructed. Each measure ranges from 0 (no vulnerability) to 1 (maximum vulnerability). The primary outcome measure was mortality over five (CHSA) or eight (NPHS) years. Associations with age, sex, and frailty (as measured by an analogously constructed frailty index) were also studied. All individuals had some degree of social vulnerability. Women had higher social vulnerability than men, and vulnerability increased with age. Frailty and social vulnerability were moderately correlated. Adjusting for age, sex, and frailty, each additional social 'deficit' was associated with an increased odds of mortality (5 years in CSHA, odds ratio = 1.05, 95% confidence interval: 1.02-1.07; 8 years in the NPHS, odds ratio = 1.08, 95% confidence interval: 1.03-1.14). We identified a meaningful survival gradient across quartiles of social vulnerability, and although women had better survival than men, survival for women with high social vulnerability was equivalent to that of men with low vulnerability.ConclusionsSocial vulnerability is reproducibly related to individual frailty/fitness, but distinct from it. Greater social vulnerability is associated with mortality in older adults. Further study on the measurement and operationalization of social vulnerability, and of its relationships to other important health outcomes, is warranted.
| S-EPMC2375054 | biostudies-literature
Project description:Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm "clocks" and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.
| S-EPMC9123172 | biostudies-literature
Project description:Background Although cardiovascular mortality (CVM) rates in the United States have been declining overall, our study evaluated whether this holds true for areas with increased social deprivation. Methods and Results We used county-level cross-sectional age-adjusted CVM rates (aa-CVM) (2000-2019) linked to the Centers for Disease Control and Prevention Social Vulnerability Index (SVI-2010). We grouped counties as per SVI (Groups I 0-0.2, II 0.21-0.4, III 0.41-0.6, IV 0.61-0.8, and V 0.81-1) and calculated the relative change in the aa-CVM between 2000 to 2003 and 2016 to 2019. We used adjusted linear regression analyses to explore the association between a higher SVI and temporal aa-CVM improvement; we studied this temporal change in aa-CVM across subgroups of race, sex, and location. The median aa-CVM rate (per 100 000) was 272.6 (interquartile range [IQR]: 237.5-311.7). The aa-CVM was higher in men (315.6 [IQR: 273.4-363.9]) than women (221.3 [IQR: 189.6-256.7]), and in Black residents (347.2 [IQR: 301.1-391.1]; P<0.001) than White residents (258.9 [IQR: 226-299.1]; P<0.001). The aa-CVM for SVI I (233.6 [IQR: 214.8-257.0]) was significantly lower than that of group V (323.6 [IQR: 277.2-359.2]; P<0.001). The relative reduction in CVM was significantly higher for SVI group I (32.2% [IQR: 24.2-38.4]) than group V (27.2% [IQR: 19-34.1]) counties. After multivariable adjustment, a higher SVI index was associated with lower relative improvement in the age-adjusted CVM (model coefficient -3.11 [95% CI, -5.66 to -1.22]; P<0.001). Conclusions Socially deprived counties in the United States had higher aa-CVM rates, and the improvement in aa-CVM over the past 20 years was lower in these counties.
| S-EPMC10757513 | biostudies-literature
Project description:This study summarizes the results from fitting a Bayesian hierarchical spatiotemporal model to coronavirus disease 2019 (COVID-19) cases and deaths at the county level in the United States for the year 2020. Two models were created, one for cases and one for deaths, utilizing a scaled Besag, York, Mollié model with Type I spatial-temporal interaction. Each model accounts for 16 social vulnerability and 7 environmental variables as fixed effects. The spatial pattern between COVID-19 cases and deaths is significantly different in many ways. The spatiotemporal trend of the pandemic in the United States illustrates a shift out of many of the major metropolitan areas into the United States Southeast and Southwest during the summer months and into the upper Midwest beginning in autumn. Analysis of the major social vulnerability predictors of COVID-19 infection and death found that counties with higher percentages of those not having a high school diploma, having non-White status and being Age 65 and over to be significant. Among the environmental variables, above ground level temperature had the strongest effect on relative risk to both cases and deaths. Hot and cold spots, areas of statistically significant high and low COVID-19 cases and deaths respectively, derived from the convolutional spatial effect show that areas with a high probability of above average relative risk have significantly higher Social Vulnerability Index composite scores. The same analysis utilizing the spatiotemporal interaction term exemplifies a more complex relationship between social vulnerability, environmental measurements, COVID-19 cases, and COVID-19 deaths.
| S-EPMC8335698 | biostudies-literature
Project description:Although human mobility is considered critical for the spread of the new coronavirus disease (COVID-19) both locally and globally, the extent to which such an association is impacted by social vulnerability remains unclear. Here, using multisource epidemiological and socioeconomic data of US counties, we develop a COVID-19 pandemic vulnerability index (CPVI) to quantify their levels of social vulnerability and examine how social vulnerability moderated the influence of mobility on disease transmissibility (represented by the effective reproduction number, Rt) during the US summer epidemic wave of 2020. We find that counties in the top CPVI quintile suffered almost double in regard to COVID-19 transmission (45.02% days with an Rt higher than 1) from mobility, particularly intracounty mobility, compared to counties in the lowest quintile (21.90%). In contrast, counties in the bottom CPVI quintile were only slightly affected by the level of mobility. As such, a 25% intracounty mobility change was associated with a 15.28% Rt change for counties in the top CPVI quintile, which is eight times the 1.81% Rt change for those in the lowest quintile. These findings suggest the need to account for the vulnerability of communities when making social distancing measures against mobility in the future.
| S-EPMC9702777 | biostudies-literature
Project description:The COVID-19 pandemic has disproportionately impacted Americans in socially vulnerable areas. Unfortunately, these groups are also experiencing lower vaccination rates. To understand how strategic vaccine site placement may benefit high vulnerability populations, we extracted vaccine site locations for 26 U.S. states and linked these data to county-level adult vaccination rates and the CDC 2018 Social Vulnerability Index rankings. We fit quasi-Poisson regression models to compare vaccine site density between the highest and lowest SVI domain quartiles, and assessed whether greater vaccine site density mediated or modified the relationship between social vulnerability and vaccination rates. We found that high vulnerability counties by socioeconomic status had more vaccine sites per 10,000 residents, yet this higher vaccine site density did not reduce socioeconomic disparities in vaccination rates. Persistent vaccination inequities may reflect other structural barriers to access. Our results suggest that targeted vaccine site placement in high vulnerability counties may be necessary but insufficient for the goal of widespread, equitable vaccination.
| S-EPMC8450273 | biostudies-literature
Project description:A recent paradigm shift from purely biophysical towards social-ecological assessment of watersheds has been proposed to understand, monitor, and manipulate the myriad interactions between human well-being and the ecosystem services that watersheds provide. However, large-scale, quantitative studies in this endeavour remain limited. We utilised two newly developed 'big-data' sets-the Index of Watershed Integrity (IWI) and the Human Well-Being Index (HWBI)-to explore the social-ecological condition of watersheds throughout the conterminous U.S., and identified environmental and socio-economic influences on watershed integrity and human well-being. Mean county IWI was highly associated with ecoregion, industry-dependence, and state, in a spatially-explicit regression model (R2 = 0.77, P < 0.001), whereas HWBI was not (R2 = 0.31, P < 0.001). HWBI is likely influenced by factors not explored here, such as governance structure and formal and informal organisations and institutions. 'Win-win' situations in which both IWI and HWBI were above the 75th percentile were observed in much of Utah, Colorado, and New Hampshire, and lessons from governance that has resulted in desirable outcomes might be learnt from here. Eastern Kentucky and West Virginia, along with large parts of the desert southwest, had intact watersheds but low HWBI, representing areas worthy of further investigation of how ecosystem services might be utilised to improve well-being. The Temperate Prairies and Central USA Plains had widespread areas of low IWI but high HWBI, likely a result of historic exploitation of watershed resources to improve well-being, particularly in farming-dependent counties. The lower Mississippi Valley had low IWI and HWBI, which is likely related to historical (temporal) and upstream (spatial) impacts on both watershed integrity and well-being. The results emphasise the importance of considering spatial and temporal trade-offs when utilising the ecosystem services provided by watersheds to improve human well-being.
| S-EPMC5906808 | biostudies-literature
Project description:Emerging evidence suggests that socially vulnerable communities are at higher risk for coronavirus disease 2019 (COVID-19) outbreaks in the United States. However, no prior studies have examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. The purpose of this study was to examine temporal trends among counties with high and low social vulnerability and to quantify disparities in these trends over time. We hypothesized that highly vulnerable counties would have higher incidence and death rates compared to less vulnerable counties and that this disparity would widen as the pandemic progressed. We conducted a retrospective longitudinal analysis examining COVID-19 incidence and death rates from March 1 to August 31, 2020 for each county in the US. We obtained daily COVID-19 incident case and death data from USAFacts and the Johns Hopkins Center for Systems Science and Engineering. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention in which higher scores represent more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles. We adjusted for percentage of the county designated as rural, percentage in poor or fair health, percentage of adult smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, and the proportion tested for COVID-19 in the state. In unadjusted analyses, we found that for most of March 2020, counties in the upper SVI quartile had significantly fewer cases per 100,000 than lower SVI quartile counties. However, on March 30, we observed a crossover effect in which the RR became significantly greater than 1.00 (RR = 1.10, 95% PI: 1.03, 1.18), indicating that the most vulnerable counties had, on average, higher COVID-19 incidence rates compared to least vulnerable counties. Upper SVI quartile counties had higher death rates on average starting on March 30 (RR = 1.17, 95% PI: 1.01,1.36). The death rate RR achieved a maximum value on July 29 (RR = 3.22, 95% PI: 2.91, 3.58), indicating that most vulnerable counties had, on average, 3.22 times more deaths per million than the least vulnerable counties. However, by late August, the lower quartile started to catch up to the upper quartile. In adjusted models, the RRs were attenuated for both incidence cases and deaths, indicating that the adjustment variables partially explained the associations. We also found positive associations between COVID-19 cases and deaths and percentage of the county designated as rural, percentage of resident in fair or poor health, and average daily PM2.5. Results indicate that the impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties over time. This highlights the importance of protecting vulnerable populations as the pandemic unfolds.
| S-EPMC7491526 | biostudies-literature
Project description:BackgroundSocially vulnerable communities may be at higher risk for COVID-19 outbreaks in the US. However, no prior studies examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. Therefore, we examined temporal trends among counties with high and low social vulnerability to quantify disparities in trends over time.MethodsWe conducted a longitudinal analysis examining COVID-19 incidence and death rates from March 15 to December 31, 2020, for each US county using data from USAFacts. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention, with higher values indicating more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles, adjusting for rurality, percentage in poor or fair health, percentage female, percentage of smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, daily temperature and precipitation, and proportion tested for COVID-19.ResultsAt the outset of the pandemic, the most vulnerable counties had, on average, fewer cases per 100,000 than least vulnerable SVI quartile. However, on March 28, we observed a crossover effect in which the most vulnerable counties experienced higher COVID-19 incidence rates compared to the least vulnerable counties (RR = 1.05, 95% PI: 0.98, 1.12). Vulnerable counties had higher death rates starting on May 21 (RR = 1.08, 95% PI: 1.00,1.16). However, by October, this trend reversed and the most vulnerable counties had lower death rates compared to least vulnerable counties.ConclusionsThe impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties and back again over time.
| S-EPMC7990180 | biostudies-literature
Project description:IntroductionIn 2021, HHS Office of Minority Health and CDC developed a composite measure of social vulnerability called the Minority Health Social Vulnerability Index (MHSVI) to assess the needs of communities most vulnerable to COVID-19. The MHSVI extends the CDC Social Vulnerability Index with two new themes on healthcare access and medical vulnerability. This analysis examines COVID-19 vaccination coverage by social vulnerability using the MHSVI.MethodsCounty-level COVID-19 vaccine administration data among persons aged ≥18 years reported to CDC from 12/14/20 to 01/31/22 were analyzed. U.S. counties from 50 states and DC were categorized into tertiles of vulnerability (low, moderate, and high) for the composite MHSVI measure and each of the 34 indicators. Vaccination coverage (≥1 dose, primary series completion, and receipt of a booster dose) was calculated by tertiles for the composite MHSVI measure and each indicator.ResultsCounties with lower per capita income, higher proportion of individuals with no high school diploma, living below poverty, ≥65 years of age, with a disability, and in mobile homes had lower vaccination uptake. However, counties with larger proportions of racial/ethnic minorities and individuals speaking English less than "very well" had higher coverage. Counties with fewer primary care physicians and greater medical vulnerabilities had lower ≥ 1 dose vaccination coverage. Furthermore, counties of high vulnerability had lower primary series completion and receipt of a booster dose. There were no clear patterns in COVID-19 vaccination coverage by tertiles for the composite measure.ConclusionResults from the new components in the MHSVI identify needs to prioritize persons in counties with greater medical vulnerabilities and limited access to health care, who are at greater risk for adverse COVID-19 outcomes. Findings suggest that using a composite measure to characterize social vulnerability might mask disparities in COVID-19 vaccination uptake that would have otherwise been observed using specific indicators.
| S-EPMC9922574 | biostudies-literature