Dataset Information

Ecological Analysis of the Temporal Trends in the Association of Social Vulnerability and Race/Ethnicity with County-Level COVID-19 Incidence and Outcomes in the United States.

ABSTRACT:

Background

The COVID-19 pandemic adversely affected the socially vulnerable and minority communities in the U.S. initially, but the temporal trends during the year-long pandemic remain unknown.

Objective

We examined the temporal association between the county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in the U.S. in the year starting in March 2020.

Methods

Counties (n=3091) with ≥ 50 COVID-19 cases by March 6 ^th , 2021 were included in the study. Associations between SVI (and its subcomponents) and county level racial composition with the incidence and death per capita were assessed by fitting a negative-binomial mixed-effects model. This model was also used to examine potential time varying associations between weekly number of cases/deaths and SVI or racial composition. Data was adjusted for percentage of population aged ≥65 years, state level testing rate, comorbidities using the average Hierarchical Condition Category (HCC) score, and environmental factors including average fine particulate matter (PM _2.5 ), temperature and precipitation.

Results

Higher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio [IRR] per-10 percentile increase:1.02, (95% CI 1.02, 1.03, p<0.001), and death per capita (1.04, (95% CI 1.04, 1.05, p<0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by the winter, a period that coincided with a sharp increase in infection rates and mortality, and when counties with higher proportion of White residents were disproportionately represented ("third wave"). By Spring of 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of Black residents also observed similar temporal trends COVID-19-related adverse outcomes. Counties with greater proportion of Hispanic residents had worse outcomes throughout the duration of the analysis.

Conclusion

Except for the winter "third wave" when majority White communities had the highest incidence of cases, counties with greater social vulnerability and proportionately higher minority populations, experienced worse COVID-19 outcomes.

Article summary/strengths & limitations

Examined full 12 months of county-level data in the US delineating the temporal trends in the association between social vulnerability index and COVID-19 outcomesInvestigated COVID-19 outcomes in predominantly Black and Hispanic communities in comparison to White communities in the USAnalysis is ecological, descriptive, and on the county-level rather than on an individual levelAnalysis adjusted for confounders including county level age ≥ 65, comorbidities, and environmental factorsAnalysis limited to the US.

SUBMITTER: Islam SJ

PROVIDER: S-EPMC8202439 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe COVID-19 pandemic adversely affected the socially vulnerable and minority communities in the USA initially, but the temporal trends during the year-long pandemic remain unknown.ObjectiveWe examined the temporal association of county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in the USA in the year starting in March 2020.MethodsCounties (n=3091) with ≥50 COVID-19 cases by 6 March 2021 were included in the study. Associations between SVI (and its subcomponents) and county-level racial composition with incidence and death per capita were assessed by fitting a negative-binomial mixed-effects model. This model was also used to examine potential time-varying associations between weekly number of cases/deaths and SVI or racial composition. Data were adjusted for percentage of population aged ≥65 years, state-level testing rate, comorbidities using the average Hierarchical Condition Category score, and environmental factors including average fine particulate matter of diameter ≥2.5 μm, temperature and precipitation.ResultsHigher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio per 10 percentile increase: 1.02, 95% CI 1.02 to 1.03, p<0.001) and death per capita (1.04, 95% CI 1.04 to 1.05, p<0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by the winter, a period that coincided with a sharp increase in infection rates and mortality, and when counties with higher proportion of white residents were disproportionately represented ('third wave'). By spring of 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of black residents also observed similar temporal trends in COVID-19-related adverse outcomes. Counties with greater proportion of Hispanic residents had worse outcomes throughout the duration of the analysis.ConclusionExcept for the winter 'third wave', when majority of the white communities had the highest incidence of cases, counties with greater social vulnerability and proportionately higher minority populations experienced worse COVID-19 outcomes.

Project description:The effect of risk factors on ovarian cancer differs by histotype, and the prevalence of such risk factors varies by race/ethnicity. It is not clear how ovarian cancer incidence has changed over time by histotype and race/ethnicity. We used the Surveillance, Epidemiology, and End Results Program (SEER-12) 1992-2019 data to examine the trend of ovarian cancer incidence for three histotypes (high-grade serous N = 19,691, endometrioid N = 3,212, and clear cell N = 3,275) and four racial/ethnic groups (Asian/Pacific Islander, Hispanic, non-Hispanic Black, and non-Hispanic White). Joinpoint and age-period-cohort analyses were conducted to analyze ovarian cancer incidence trends. High-grade serous cancer was the most common histotype, but its incidence has significantly decreased over time for all racial/ethnic groups; the decrease was largest for non-Hispanic White women (average annual percent change AAPC during 2010-2019 = -6.1; 95% confidence interval (CI), -8.0 to -4.2). Conversely, clear cell cancer was most common in the Asian/Pacific Islanders, and its incidence has increased over time, particularly among Hispanic and Asian/Pacific Islander women (AAPC during 2010-2019 = 2.8; 95% CI, 0.8 to 4.7, and AAPC = 1.5; 95% CI, 0.7 to 2.2, respectively). Endometrioid cancer incidence has decreased in non-Hispanic White but increased in Hispanic women (AAPC during 2010-2019 = -1.3; 95% CI, -1.9 to -0.8, and AAPC = 3.6; 95% CI, 1.0 to 6.3, respectively). The differential incidence trends by histotype and race/ethnicity underscore the need to monitor incidence and risk factor trends across different groups and develop targeted preventive interventions to reduce the burden of ovarian cancer and disparity by race/ethnicity.SignificanceDuring 1992-2019, high-grade serous ovarian cancer incidence has decreased while clear cell cancer incidence has increased regardless of race/ethnicity. Endometrioid cancer incidence has decreased in non-Hispanic White but increased in Hispanic women. Differential ovarian cancer incidence trends highlight the need for targeted preventive interventions by histotype and race/ethnicity.

Project description:IntroductionAlthough there are racial/ethnic differences in cigarette use, little is known about how non-cigarette tobacco use differs among racial/ethnic groups. This study investigated trends in cigar use from 2002 to 2016, by racial/ethnic group, in nationally representative US data.MethodsData were drawn from the 2002-2016 National Survey on Drug Use and Health public use data files (total analytic sample n = 630 547 including 54 060 past-month cigar users). Linear time trends of past-month cigar use were examined by racial/ethnic group (Non-Hispanic [NH] White, NH Black, Hispanic, NH Other/Mixed Race/Ethnicity) using logistic regression models.ResultsIn 2016, the prevalence of past-month cigar use was significantly higher among NH Black respondents than among other racial/ethnic groups (ps < .001). Cigar use was also higher among NH White respondents than among Hispanic and NH Other/Mixed Race/Ethnicity respondents. The year by racial/ethnic group interaction was significant (p < .001). Past-month cigar use decreased significantly from 2002 to 2016 among NH White and Hispanic respondents (ps = .001), whereas no change in prevalence was observed among NH Black (p = .779) and NH Other/Mixed Race/Ethnicity respondents (p = .152). Cigar use decreased for NH White men (p < .001) and did not change for NH White women (p = .884). Conversely, cigar use increased for NH Black women (p < .001) and did not change for NH Black men (p = .546).ConclusionsCigar use remains significantly more common among NH Black individuals in the United States and is not declining among NH Black and NH Other/Mixed Race/Ethnicity individuals over time, in contrast to declines among NH White and Hispanic individuals.ImplicationsThis study identified racial/ethnic differences in trends in past-month cigar use over 15 years among annual cross-sectional samples of US individuals. The highest prevalence of cigar use in 2016 was found among NH Black individuals. In addition, cigar use prevalence did not decline from 2002 to 2016 among NH Black and NH Other/Mixed Race/Ethnicity groups over time, in contrast to NH White and Hispanic groups. Further, cigar use increased over time for NH Black women. Targeted public health and clinical efforts may be needed to decrease the prevalence of cigar use, especially for NH Black individuals.

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.