Secular changes in mortality disparities in New York City: a reexamination.
Ontology highlight
ABSTRACT:
SUBMITTER: Althoff KN
PROVIDER: S-EPMC2729862 | biostudies-other | 2009 Sep
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Residing in a high-poverty area has consistently been associated with higher mortality rates, but the association between poverty and mortality can change over time. We examine the association between neighborhood poverty and mortality in New York City (NYC) during 1990-2010 to document mortality disparity changes over time and determine causes of death for which disparities are greatest. We used NYC and New York state mortality data for years 1990, 2000, and 2010 to calculate all-cause and cause-specific age-adjusted death rates (AADRs) by census tract poverty (CTP), which is the proportion of persons in a census tract living below the federal poverty threshold. We calculated mortality disparities, measured as the difference in AADR between the lowest and highest CTP groups, within and across race/ethnicity, nativity, and sex categories by year. We observed higher all-cause AADRs with higher CTP for each year for all race/ethnicities, both sexes, and US-born persons. Mortality disparities decreased progressively during 1990-2010 for the NYC population overall, for each race/ethnic group, and for the majority of causes of death. The overall mortality disparity between the highest and lowest CTP groups during 2010 was 2.55 deaths/1000 population. The largest contributors to mortality disparities were heart disease (51.52 deaths/100,000 population), human immunodeficiency virus (19.96/100,000 population), and diabetes (19.59/100,000 population). We show that progress was made in narrowing socioeconomic disparities in mortality during 1990-2010, but substantial disparities remain. Future efforts toward achieving health equity in NYC mortality should focus on areas contributing most to disparities.
| S-EPMC4899332 | biostudies-literature
Project description:INTRODUCTION:Existing socioeconomic and racial disparities in healthcare access in New York City have likely impacted the public health response to COVID-19. An ecological study was performed to determine the spatial distribution of COVID-19 testing by ZIP code Tabulation Area and investigate if testing was associated with race or SES. METHODS:Data were obtained from the New York City coronavirus data repository and 2018 American Community Survey 5-year estimates. A combined index of SES was created using principal component analysis and incorporated household income, gross rent, poverty, education, working class status, unemployment, and occupants per room. Multivariable Poisson regressions were performed to predict the number of total tests and the ratio of positive tests to total tests performed, using the SES index, racial composition, and Hispanic composition as predictors. RESULTS:The number of total tests significantly increased with the increasing proportion of white residents (?=0.004, SE=0.001, p=0.0032) but not with increasing Hispanic composition or SES index score. The ratio of positive tests to total tests significantly decreased with the increasing proportion of white residents in the ZIP code Tabulation Area (?= -0.003, SE=0.000 6, p<0.001) and with increasing SES index score (?= -0.001 6, SE=0.0007, p=0.0159). CONCLUSIONS:In New York City, COVID-19 testing has not been proportional to need; existing socioeconomic and racial disparities in healthcare access have likely impacted public health response. There is urgent need for widespread testing and public health outreach for the most vulnerable communities in New York City.
| S-EPMC7316038 | biostudies-literature
Project description:ImportanceBlack and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored.ObjectiveTo compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics.Design, setting, and participantsThis retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status.ExposuresRace and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients).Main outcomes and measuresThe likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death).ResultsAmong 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9).Conclusions and relevanceIn this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.
| S-EPMC7718605 | biostudies-literature
Project description:Black and Hispanic communities in the U.S. have endured a disproportionate burden of COVID-19-related morbidity and mortality. Racial and ethnic health disparities such as these are frequently aggravated by inequitable access to healthcare resources in disadvantaged communities. Yet, no known studies have investigated disadvantaged communities' access to COVID-19-related healthcare resources. The current study accordingly examined racial and ethnic differences in (1) April 2020 COVID-19 total and positive viral test rates across 177 New York City (NYC) ZIP Code Tabulation Areas (ZCTA); and (2) November 2019-April 2020 licensed and intensive care unit (ICU) hospital bed access across 194 NYC ZCTAs. Pairwise analyses indicated higher COVID-19 total and positive test rates per 1000 persons in majority Black and Hispanic vs. majority White ZCTAs (CI [0.117, 4.55]; CI [2.53, 5.14]). Multiple linear regression analyses indicated that higher percentage of Black and Hispanic residents predicted more total COVID-19 tests per 1000 persons (p < 0.05). In contrast, majority Black and Hispanic ZCTAs had fewer licensed and ICU beds (CI [6.50, 124.25]; CI [0.69, 7.16]), with social disadvantage predicting lower licensed and ICU bed access per 1000 persons (p < 0.01). While news reports of inequitable access to COVID-19-related healthcare resources in ethnocultural minority communities have emerged, this is the first study to reveal that social disadvantage may be a major driver of hospital resource inequities in Black and Hispanic communities. Thus, it will be imperative to enact policies that ensure equitable allocation of healthcare resources to socially disadvantaged communities to address current and future public health crises.
| S-EPMC7536513 | biostudies-literature
Project description:OBJECTIVES:Investigate whether or not race is associated with differences in hospitalization and survival to discharge among patients with coronavirus disease-2019 (COVID-19) at the height of the pandemic in New York City (NYC). METHODS:Single-center retrospective cohort study of COVID-19 patients hospitalized at our university-affiliated NYC hospital from 3/10/20 through 4/13/20 with follow-up to 5/1/20. Our primary endpoint was hospitalization rate among patients with confirmed COVID-19 compared with the regional population based on race. Our secondary endpoint survival to discharge among hospitalized COVID-19 patients. NYC Department of Health data were used to calculate hospitalization odds ratios. Chi-square and t tests were used to compare categorial and continuous variables, respectively. Cox proportional hazards regression and predictive analysis were used to investigate our endpoints further. RESULTS:Our cohort of 734 patients included 355 women (48.4%), 372 Blacks (50.7%), 214 Whites (29.2%), and 92 Hispanics (12.5%) in our analysis. Blacks were nearly twice as likely as Whites to require hospitalization for COVID-19 (OR 1.89, 95% CI, 1.59-2.24, p?<?0.001). Hispanics were also more likely to suffer in-hospital mortality from COVID-19 compared with Whites (HR 1.84; 95% CI 1.21-2.80; p?= 0.005). There was a non-significant increased hazard of in-hospital mortality among Blacks when compared with Whites (HR, 1.30; 95% CI, 0.95-1.78; p?= 0.09). CONCLUSIONS AND RELEVANCE:Blacks were more likely than Whites to require hospitalization for COVID-19 while Hispanics were more likely to experience in-hospital mortality. Further investigation into the socioeconomic factors underlying racial disparities in COVID-19 survival and severity requiring hospitalization is needed on a national scale.
| S-EPMC7500250 | biostudies-literature
Project description:Using data from New York City from January 2020 to April 2020, we found an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of severe acute respiratory syndrome coronavirus 2 within New York City boroughs. We also conducted a cross-sectional analysis of the associations between human mobility (i.e., subway ridership) on the week of April 11, 2020, sociodemographic factors, and coronavirus disease 2019 (COVID-19) incidence as of April 26, 2020. Areas with lower median income, a greater percentage of individuals who identify as non-White and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of health-care essential workers had more mobility during the pandemic. When adjusted for the percentage of essential workers, these associations did not remain, suggesting essential work drives human movement in these areas. Increased mobility and all sociodemographic variables (except percentage of people older than 75 years old and percentage of health-care essential workers) were associated with a higher rate of COVID-19 cases per 100,000 people, when adjusted for testing effort. Our study demonstrates that the most socially disadvantaged not only are at an increased risk for COVID-19 infection, they lack the privilege to fully engage in social distancing interventions.
| S-EPMC7799254 | biostudies-literature
Project description:Demographic and income disparities may impact food accessibility. Research has not yet well documented the precise location of healthy and unhealthy food resources around children's homes and schools. The objective of this study was to examine the food environment around homes and schools for all public school children, stratified by race/ethnicity and poverty status. This cross-sectional study linked data on the exact home and school addresses of a population-based sample of public school children in New York City from 2013 to all corner stores, supermarkets, fast-food restaurants, and wait-service restaurants. Two measures were created around these addresses for all children: 1) distance to the nearest outlet, and 2) count of outlets within 0.25 miles. The total analytic sample included 789,520 K-12 graders. The average age was 11.78 years (SD ± 4.0 years). Black, Hispanic, and Asian students live and attend schools closer to nearly all food outlet types than White students, regardless of poverty status. Among not low-income students, Black, Hispanic, and Asian students were closer from home and school to corner stores and supermarkets, and had more supermarkets around school than White students. The context in which children live matters, and more nuanced data is important for development of appropriate solutions for childhood obesity. Future research should examine disparities in the food environment in other geographies and by other demographic characteristics, and then link these differences to health outcomes like body mass index. These findings can be used to better understand disparities in food access and to help design policies intended to promote healthy eating among children.
| S-EPMC6561543 | biostudies-literature
Project description:ObjectiveTo investigate differences in severe maternal morbidity between Hispanic mothers and three major Hispanic subgroups compared with non-Hispanic white mothers and the extent to which differences in delivery hospitals may contribute to excess morbidity among Hispanic mothers.MethodsWe conducted a population-based cross-sectional study using linked 2011-2013 New York City discharge and birth certificate data sets (n=353,773). Rates of severe maternal morbidity were calculated using a published algorithm based on diagnosis and procedure codes. Mixed-effects logistic regression with a random hospital-specific intercept was used to generate risk-standardized severe maternal morbidity rates for each hospital taking into consideration patient sociodemographic characteristics and comorbidities. Differences in the distribution of Hispanic and non-Hispanic white deliveries were assessed among these hospitals in relation to their risk-adjusted morbidity. Sensitivity analyses were conducted after excluding isolated blood transfusion from the morbidity composite.ResultsSevere maternal morbidity occurred in 4,541 deliveries and was higher among Hispanic than non-Hispanic white women (2.7% compared with 1.5%, P<.001); this rate was 2.9% among those who were Puerto Rican, 2.7% among those who were foreign-born Dominican, and 3.3% among those who were foreign-born Mexican. After adjustment for patient characteristics, the risk remained elevated for Hispanic women (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.22-1.66) and for all three subgroups compared with non-Hispanic white women (P<.001). Risk for Hispanic women was attenuated in sensitivity analyses (OR 1.17, 95% CI 1.02-1.33). Risk-standardized morbidity across hospitals varied sixfold. We estimate that Hispanic-non-Hispanic white differences in delivery location may contribute up to 37% of the ethnic disparity in severe maternal morbidity rates in New York City hospitals.ConclusionHispanic compared with non-Hispanic white mothers are more likely to deliver at hospitals with higher risk-adjusted severe maternal morbidity rates and these differences in site of delivery may contribute to excess morbidity among Hispanic mothers. Our results suggest improving quality at the lowest performing hospitals could benefit both non-Hispanic white and Hispanic women and reduce ethnic disparities in severe maternal morbidity rates.
| S-EPMC5380443 | biostudies-literature
Project description:Disparities in availability of food retailers in the residential environment may help explain racial/ethnic and socio-economic differences in obesity risk. Research is needed that describes whether food environment dynamics may contribute to equalizing conditions across neighborhoods or to amplifying existing inequalities over time. This study improves the understanding of how the BMI-unhealthy food environment has evolved over time in New York City. We use longitudinal census tract-level data from the National Establishment Time-Series (NETS) for New York City in the period 1990-2010 and implement latent class growth analysis (LCGA) to (1) examine trajectories of change in the number of unhealthy food outlets (characterized as selling calorie-dense foods such as pizza and pastries) at the census tract-level, and (2) examine how trajectories are related to socio-demographic characteristics of the census tract. Overall, the number of BMI-unhealthy food outlets increased between 1990 and 2010. We summarized trajectories of evolutions with a 5-class model that indicates a pattern of fanning out, such that census tracts with a higher initial number of BMI-unhealthy food outlets in 1990 experienced a more rapid increase over time. Finally, fully adjusted logistic regression models reveal a greater increase in BMI-unhealthy food outlets in census tracts with: higher baseline population size, lower baseline income, and lower proportion of Black residents. Greater BMI-unhealthy food outlet increases were also noted in the context of census tracts change suggestive of urbanization (increasing population density) or increasing purchasing power (increasing income).
| S-EPMC6689383 | biostudies-literature
Project description:Shotgun metagenomic sequencing of NYC raw sewage samples
| PRJEB28033 | ENA