Abstract 16562: Association of County-Level Social Vulnerability Index and Cardiovascular Disease in the United States, 1999-2018

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Quentin R Youmans ◽  
Megan E McCabe ◽  
Clyde W Yancy ◽  
Lucia Petito ◽  
Kiarri N Kershaw ◽  
...  
Keyword(s):  
United States ◽  
Cardiovascular Disease ◽  
Social Vulnerability ◽  
Cardiovascular Health ◽  
Vulnerability Index ◽  
The United States ◽  
County Level ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
Cvd Mortality

Introduction: Social determinants of health are multi-dimensional and span various interrelated domains. In order to inform community-engaged clinical and policy efforts, we sought to examine the association between a national social vulnerability index (SVI) and age-adjusted mortality rate (AAMR) of CVD. Hypothesis: Higher county-level SVI or greater vulnerability will be associated with higher AAMR of CVD between 1999-2018 in the United States. Methods: In this serial, cross-sectional analysis, we queried CDC WONDER for age-adjusted mortality rates (AAMRs) per 100,000 population for cardiovascular disease (I00-78) at the county-level between 1999-2018. We quantified the association of county-level SVI and CVD AAMR using Spearman correlation coefficients and examined trends in CVD AAMR stratified by median SVI at the county-level. Finally, we performed geospatial county-level analysis stratified by combined median SVI and CVD AAMR (high/high, high/low, low/high, and low/low). Results: We included data from 2766 counties (representing 95% of counties in the US) with median SVI 0.53 (IQR 0.28, 0.76). Overall SVI and the household and socioeconomic subcomponents were strongly correlated with 2018 CVD AAMR (0.47, 0.50, and 0.56, respectively with p<0.001 for all). CVD mortality declined between 1999-2011 and was stagnant between 2011-2018 with similar patterns in high and low SVI counties (FIGURE). Counties with high SVI and CVD AAMR were clustered in the South and Midwest (n=977, 35%). Conclusion: County-level social vulnerability is associated with higher CVD mortality. High SVI and CVD AAMR coexist in more than 1 in 3 US counties and have persisted over the past 2 decades. Identifying counties that are disproportionately vulnerable may inform targeted and community-based strategies to equitably improve cardiovascular health across the country.

scholarly journals Greater Acculturation is Associated With Poorer Cardiovascular Health in the Multi‐Ethnic Study of Atherosclerosis

2021 ◽  
Author(s):  
Olatokunbo Osibogun ◽  
Oluseye Ogunmoroti ◽  
Lena Mathews ◽  
Victor Okunrintemi ◽  
Martin Tibuakuu ◽  
...  
Keyword(s):  
United States ◽  
Cardiovascular Disease ◽  
Cardiovascular Health ◽  
Hispanic Americans ◽  
The United States ◽  
Foreign Born ◽  
Cross Sectional ◽  
Lower Odds ◽  
Increased Risk ◽  
At Home

Background Greater acculturation is associated with increased risk of cardiovascular disease. However, little is known about the association between acculturation and ideal cardiovascular health (CVH) as measured by the American Heart Association's 7 CVH metrics. We investigated the association between acculturation and ideal CVH among a multi‐ethnic cohort of US adults free of clinical cardiovascular disease at baseline. Methods and Results This was a cross‐sectional analysis of 6506 men and women aged 45 to 84 years of 4 races/ethnicities. We examined measures of acculturation(birthplace, language spoken at home, and years lived in the United States [foreign‐born participants]) by CVH score. Scores of 0 to 8 indicate inadequate, 9 to 10 average and 11 to 14 optimal CVH. We used multivariable regression to examine associations between acculturation and CVH, adjusting for age, sex, race/ethnicity, education, income and health insurance. The mean (SD) age was 62 (10) years, 53% were women, 39% non‐Hispanic White‐, 26% non‐Hispanic Black‐, 12% Chinese‐ and 22% Hispanic‐Americans. US‐born participants had lower odds of optimal CVH (odds ratio [OR]: 0.63 [0.50–0.79], P <0.001) compared with foreign‐born participants. Participants who spoke Chinese and other foreign languages at home had greater odds of optimal CVH compared with those who spoke English (1.91 [1.08–3.36], P =0.03; and 1.65 [1.04–2.63], P =0.03, respectively). Foreign‐born participants who lived the longest in the United States had lower odds of optimal CVH (0.62 [0.43–0.91], P =0.02). Conclusions Greater US acculturation was associated with poorer CVH. This finding suggests that the promotion of ideal CVH should be encouraged among immigrant populations since more years lived in the United States was associated with poorer CVH.

scholarly journals Assessment of Social Vulnerability to Wildfire in Missouri, United States of America

2019 ◽  
Vol 12 (4) ◽  
pp. 76
Author(s):  
Omolola Victoria Akinola ◽  
Jimmy Adegoke ◽  
Temi Emmanuel Ologunorisa
Keyword(s):  
United States ◽  
Low Income ◽  
Social Vulnerability ◽  
Rating Scale ◽  
Biodiversity Loss ◽  
Vulnerability Index ◽  
The United States ◽  
Social Vulnerability Index ◽  
Wildfire Risk ◽  
Property Loss

Wildfire is a major environmental hazard causing property damage and destruction including biodiversity loss in the United States. In order to reduce property loss and destruction arising from wildfire, this study assessed and identified social vulnerability to wildfire in Missouri using the American Community Survey data on social and demographic variables for the state of Missouri and social vulnerability index (S0VI). The study divided Missouri into five geopolitical zones from which ten counties were randomly selected for this study. The selected counties formed the basis on which fourteen social and demographic indicators were identified and assessed using Bogardi, Birkmann and Cadona conceptual framework. The result of the analysis shows that S0VI estimated for the five geopolitical zones of Missouri is moderate with a rating scale of 1.42 &ndash; 1.71. Education, income and marital status have a rating scale of 2.0 - 3.0 attributed for the high value of Social Vulnerability to wildfire. Race / ethnicity, language spoken, employment and percentage of house units that are mobile homes had a low S0VI value of 1.0 thereby contributing positively to resilience to wildfire risk. The study observes that government involvement in wildfire risk reduction is quite impressive and should still be intensified. The policy implication of this study is that education and income are key variables that contribute to high wildfire risk in Missouri. The need for government to formulate a policy on environmental education of the populace especially for people of low income and education become imperative. This will go a long way in reducing damage and property loss arising from wildfire.

scholarly journals Revising Ncei’s Climate Extremes Index And The Cdc’s Social Vulnerability Index To Analyze Climate Extremes Vulnerability Across The United States

2020 ◽  
pp. 1-42
Author(s):  
Emily L. Pauline ◽  
John A. Knox ◽  
Lynne Seymour ◽  
Andrew J. Grundstein
Keyword(s):  
United States ◽  
Social Vulnerability ◽  
Demographic Data ◽  
Climate Extremes ◽  
Vulnerability Index ◽  
The United States ◽  
Social Vulnerability Index ◽  
Social Demographic

CapsuleWhere are climate extremes happening? This information is urgently needed. We combine this information with social demographic data to create an index identifying U.S. locations vulnerable to climate extremes.

scholarly journals Social Vulnerability in Patients with Multimorbidity: A Cross-Sectional Analysis

2019 ◽  
Vol 16 (7) ◽  
pp. 1244 ◽  
Author(s):  
Tu Nguyen ◽  
Patrice Ngangue ◽  
Tarek Bouhali ◽  
Bridget Ryan ◽  
Moira Stewart ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Social Vulnerability ◽  
Chronic Conditions ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
Term Care ◽  
Cross Sectional Analysis ◽  
The Social ◽  
Sectional Analysis

Background: Social aspects play an important role in individual health and should be taken into consideration in the long-term care for people with multimorbidity. Purposes: To describe social vulnerability, to examine its correlation with the number of chronic conditions, and to investigate which chronic conditions were significantly associated with the most socially vulnerable state in patients with multimorbidity. Methods: Cross-sectional analysis from the baseline data of the Patient-Centred Innovations for Persons with Multimorbidity (PACEinMM) Study. Participants were patients attending primary healthcare settings in Quebec, Canada. A social vulnerability index was applied to identify social vulnerability level. The index value ranges from 0 to 1 (1 as the most vulnerable). Spearman’s rank correlation coefficient was calculated for the correlation between the social vulnerability index and the number of chronic conditions. Logistic regression was applied to investigate which chronic conditions were independently associated with the most socially vulnerable state. Results: There were 301 participants, mean age 61.0 ± 10.5, 53.2% female. The mean number of chronic health conditions was 5.01 ± 1.82, with the most common being hyperlipidemia (78.1%), hypertension (69.4%), and obesity (54.2%). The social vulnerability index had a median value of 0.13 (range 0.00–0.78). There was a positive correlation between the social vulnerability index and the number of chronic conditions (r = 0.24, p < 0.001). Obesity, depression/anxiety, and cardiovascular diseases were significantly associated with the most socially vulnerable patients with multimorbidity. Conclusions: There was a significant correlation between social vulnerability and the total number of chronic conditions, with depression/anxiety, obesity, and cardiovascular diseases being the most related to social vulnerability.

scholarly journals Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

2021 ◽  
Vol 18 (18) ◽  
pp. 9488
Author(s):  
Abolfazl Mollalo ◽  
Moosa Tatar
Keyword(s):  
United States ◽  
Healthcare Providers ◽  
Vulnerability Index ◽  
The United States ◽  
Vaccine Hesitancy ◽  
Social Vulnerability Index ◽  
Vaccination Programs ◽  
Public Health Decision ◽  
Vaccination Rates ◽  
The Impact

Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.

scholarly journals Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study

2020 ◽  
Author(s):  
Xiao Wu ◽  
Rachel C Nethery ◽  
M Benjamin Sabath ◽  
Danielle Braun ◽  
Francesca Dominici
Keyword(s):  
United States ◽  
Air Pollution ◽  
Death Rate ◽  
The United States ◽  
Sensitivity Analyses ◽  
List Type ◽  
County Level ◽  
Cross Sectional ◽  
Increased Risk

AbstractObjectivesUnited States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affected by long-term exposure to air pollution. We investigated whether long-term average exposure to fine particulate matter (PM2.5) is associated with an increased risk of COVID-19 death in the United States.DesignA nationwide, cross-sectional study using county-level data.Data sourcesCOVID-19 death counts were collected for more than 3,000 counties in the United States (representing 98% of the population) up to April 22, 2020 from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center.Main outcome measuresWe fit negative binomial mixed models using county-level COVID-19 deaths as the outcome and county-level long-term average of PM2.5 as the exposure. In the main analysis, we adjusted by 20 potential confounding factors including population size, age distribution, population density, time since the beginning of the outbreak, time since state’s issuance of stay-at-home order, hospital beds, number of individuals tested, weather, and socioeconomic and behavioral variables such as obesity and smoking. We included a random intercept by state to account for potential correlation in counties within the same state. We conducted more than 68 additional sensitivity analyses.ResultsWe found that an increase of only 1 μg/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%). The results were statistically significant and robust to secondary and sensitivity analyses.ConclusionsA small increase in long-term exposure to PM2.5 leads to a large increase in the COVID-19 death rate. Despite the inherent limitations of the ecological study design, our results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis. The data and code are publicly available so our analyses can be updated routinely.Summary BoxWhat is already known on this topicLong-term exposure to PM2.5 is linked to many of the comorbidities that have been associated with poor prognosis and death in COVID-19 patients, including cardiovascular and lung disease.PM2.5 exposure is associated with increased risk of severe outcomes in patients with certain infectious respiratory diseases, including influenza, pneumonia, and SARS.Air pollution exposure is known to cause inflammation and cellular damage, and evidence suggests that it may suppress early immune response to infection.What this study addsThis is the first nationwide study of the relationship between historical exposure to air pollution exposure and COVID-19 death rate, relying on data from more than 3,000 counties in the United States. The results suggest that long-term exposure to PM2.5 is associated with higher COVID-19 mortality rates, after adjustment for a wide range of socioeconomic, demographic, weather, behavioral, epidemic stage, and healthcare-related confounders.This study relies entirely on publicly available data and fully reproducible, public code to facilitate continued investigation of these relationships by the broader scientific community as the COVID-19 outbreak evolves and more data become available.A small increase in long-term PM2.5 exposure was associated with a substantial increase in the county’s COVID-19 mortality rate up to April 22, 2020.

scholarly journals On the Relationship between Development and Fertility: The Case of the United States

2015 ◽  
Vol 40 (4) ◽  
Author(s):  
Igor Ryabov
Keyword(s):  
United States ◽  
Human Development ◽  
Negative Relationship ◽  
The United States ◽  
Median Income ◽  
County Level ◽  
Cross Sectional ◽  
Development Indicators ◽  
Rural Counties ◽  
The Relationship

The present article addresses the question of whether there is a link between the spatial patterns of human development and period fertility in the United States at the county level. Using cross-sectional analyses of the relationship between Total Fertility Rate (TFR) and an array of human development indicators (pertaining to three components of the Human Development Index (HDI) – wealth, health, and education), this study sheds light on the relationship between fertility and human development. The analyses were conducted separately for urban, suburban and rural counties. According to the multivariate results, a negative association between selected human development indicators and TFR exists in suburban and rural counties, as well as in the United States as a whole. However, this is not the case for urban counties, where the results were inconclusive. Some indicators (e.g., median income per capita) were found to be positively, and some (e.g., the share of adults with at least bachelor’s degree) negatively, associated with TFR in urban counties. All in all, our results provide evidence of a negative relationship between human development indicators and period fertility in the United States at the county level, a finding which is consistent with the basic tenets of classic demographic transition theory.

scholarly journals COVID-19 and excess mortality in the United States: A county-level analysis

PLoS Medicine ◽  
2021 ◽  
Vol 18 (5) ◽  
pp. e1003571
Author(s):  
Andrew C. Stokes ◽  
Dielle J. Lundberg ◽  
Irma T. Elo ◽  
Katherine Hempstead ◽  
Jacob Bor ◽  
...  
Keyword(s):  
United States ◽  
Formal Education ◽  
Excess Mortality ◽  
Time Lag ◽  
The United States ◽  
County Level ◽  
Level Variation ◽  
Cross Sectional ◽  
All Cause Mortality ◽  
Excess Deaths

Background Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics. Methods and findings In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics. Conclusions In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

scholarly journals Multilevel analysis concerning the relationship between social vulnerability and the healthy use of leisure time in children and adolescents in Argentina: A national population-based study

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1619
Author(s):  
Daniela Moyano ◽  
Zarina Forclaz ◽  
Raúl M. Chaparro ◽  
Akram Hernández-Vásquez ◽  
Nilda R. Perovic
Keyword(s):  
Health Promotion ◽  
Children And Adolescents ◽  
Social Vulnerability ◽  
Leisure Time ◽  
Multilevel Models ◽  
Household Survey ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
The Relationship

Background: Leisure time is a human right and has to be considered part of any health promotion initiative aimed at children and adolescents. The objective of this study was to analyze the relationship between social vulnerability and the healthy use of leisure time in children and adolescents in urban contexts of Argentina, in 2012. Methods: A cross-sectional and analytical study using data from the Module on Activities of Girls, Boys and Adolescents of the Annual Urban Household Survey was carried out. In this survey, a self-administered instrument was applied to 25,915 individuals aged from 5 to 17. A Social Vulnerability Index (SVI) was developed. Association was estimated by multilevel logistic regression. Results: Children and adolescents use most of their leisure time to carry out school activities (90.1%) with art activities having the lowest percentage (21.8%). In the multilevel models on the relationship between a high SVI and non-performance of socialization activities, the OR was 1.99 (p = 0.002, 95% CI: 1.28-3.12). The association between high SVI and non-use of ICT gave an OR of 14.17 (p ≤ 0.001, 95% CI: 5.13-39.17), and between high SVI and non-use of internet, an OR of 21.89 (p ≤ 0.001, 95% CI: 7.50-63.88). Conclusions: A high SVI negatively impacts on some healthy activities of leisure time for children and adolescents in Argentina. The SVI could be a useful tool to guide health promotion initiatives in this population.

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