Dataset Information

Large health disparities in cardiovascular death in men and women, by ethnicity and socioeconomic status in an urban based population cohort.

ABSTRACT:

Background

Socioeconomic status and ethnicity are not incorporated as predictors in country-level cardiovascular risk charts on mainland Europe. The aim of this study was to quantify the sex-specific cardiovascular death rates stratified by ethnicity and socioeconomic factors in an urban population in a universal healthcare system.

Methods

Age-standardized death rates (ASDR) were estimated in a dynamic population, aged 45-75 in the city of The Hague, the Netherlands, over the period 2007-2018, using data of Statistics Netherlands. Results were stratified by sex, ethnicity (country of birth) and socioeconomic status (prosperity) and compared with a European cut-off for high-risk countries (ASDR men 225/100,000 and women 175/100,000).

Findings

In total, 3073 CVD deaths occurred during 1·76 million person years follow-up. Estimated ASDRs (selected countries of birth) ranged from 126 (95%CI 89-174) in Moroccan men to 379 (95%CI 272-518) in Antillean men, and from 86 (95%CI 50-138) in Moroccan women to 170 (95%CI 142-202) in Surinamese women. ASDRs in the highest and lowest prosperity quintiles were 94 (95%CI 90-98) and 343 (95%CI 334-351) for men, and 43 (95%CI 41-46) and 140 (95%CI 135-145), for women, respectively.

Interpretation

In a diverse urban population, large health disparities in cardiovascular ASDRs exists across ethnic and socioeconomic subgroups. Identifying these high-risk subgroups followed by targeted preventive efforts, might provide a basis for improving cardiovascular health equity within communities. Instead of classifying countries as high-risk or low-risk, a shift towards focusing on these subgroups within countries might be needed.

Funding

Leiden University Medical Center and Leiden University.

SUBMITTER: Kist JM

PROVIDER: S-EPMC8408518 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo characterize health disparities in common chronic diseases among adults by socioeconomic status (SES) and ethnicity in a mixed rural-urban community of the United States.Patients and methodsWe conducted a cross-sectional study to assess the association of the prevalence of the 5 most burdensome chronic diseases in adults with SES and ethnicity and their interaction. The Rochester Epidemiology Project medical records linkage system was used to identify the prevalence of coronary heart disease, asthma, diabetes, hypertension, and mood disorder using International Classification of Diseases, Ninth Revision codes recorded from January 1, 2005, through December 31, 2009, among all adult residents of Olmsted County, Minnesota, on April 1, 2009. For SES measurements, an individual HOUsing-based index of SocioEconomic Status (HOUSES) derived from real property data was used. Logistic regression models were used to examine the association of the prevalence of chronic diseases with ethnicity and HOUSES score and their interaction.ResultsWe identified 88,010 eligible adults with HOUSES scores available, of whom 48,086 (54.6%) were female and 80,699 (91.7%) were non-Hispanic white; the median (interquartile range) age was 45 years (30-58 years). Overall and in the subgroup of non-Hispanic whites, SES measured by HOUSES was inversely associated with the prevalence of all 5 chronic diseases independent of age, sex, and ethnicity (P<.001). While an association of ethnicity with disease prevalence was observed for all the chronic diseases, SES modified the effect of ethnicity for clinically less overt conditions (interaction P<.05 for each condition [diabetes, hypertension, and mood disorder]) but not for coronary heart disease, a clinically more overt condition.ConclusionIn a mixed rural-urban setting with a predominantly non-Hispanic white population, health disparities in chronic diseases still exist across SES. The extent to which SES modifies the effect of ethnicity on the risk of chronic diseases may depend on the nature of the disease.

Project description:ObjectivesThis study sought to describe the health status of outpatients with heart failure and reduced ejection fraction (HFrEF) by sex, race/ethnicity, and socioeconomic status (SES).BackgroundAlthough a primary goal in treating patients with HFrEF is to optimize health status, whether disparities by sex, race/ethnicity, and SES exist is unknown.MethodsIn the CHAMP-HF (Change the Management of Patients with Heart Failure) registry, the associations among sex, race, and SES and health status, as measured by the Kansas City Cardiomyopathy Questionnaire-overall summary (KCCQ-os) score (range 0 to 100; higher scores indicate better health status) was compared among 3,494 patients from 140 U.S. clinics. SES was categorized by total household income. Hierarchical multivariate linear regression estimated differences in KCCQ-os score after adjusting for 31 patient characteristics and 10 medications.ResultsOverall mean KCCQ-os scores were 64.2 ± 24.0 but lower for women (29% of sample; 60.3 ± 24.0 vs. 65.9 ± 24.0, respectively; p < 0.001), for blacks (60.5 ± 25.0 vs. 64.9 ± 23.0, respectively; p < 0.001), for Hispanics (59.1 ± 21.0 vs. 64.9 ± 23.0, respectively; p < 0.001), and for those with the lowest income (<$25,000; mean: 57.1 vs. 63.1 to 74.7 for other income categories; p < 0.001). Fully adjusted KCCQ-os scores were 2.2 points lower for women (95% confidence interval [CI]: -3.8 to -0.6; p = 0.007), no different for blacks (p = 0.74), 4.0 points lower for Hispanics (95% CI: -6.6 to -1.3; p = 0.003), and lowest in the poorest patients (4.7 points lower than those with the highest income (95% CI: 0.1 to 9.2; p = 0.045; p for trend = 0.003).ConclusionsAmong outpatients with HFrEF, women, blacks, Hispanics, and poorer patients had worse health status, which remained significant for women, Hispanics, and poorer patients in fully adjusted analyses. This suggests an opportunity to further optimize treatment to reduce these observed disparities.

Project description:IntroductionInfant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.MethodsNational Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.ResultsNonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.ConclusionsInfant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.

Project description:Although South Asians experience cardiovascular disease (CVD) and risk factors at an early age, the distribution of CVD risks across the socioeconomic spectrum remains unclear.We analysed the 2011 Centre for Cardiometabolic Risk Reduction in South Asia survey data including 16,288 non-pregnant adults (≥20 years) that are representative of Chennai and Delhi, India, and Karachi, Pakistan. Socioeconomic status (SES) was defined by highest education (primary schooling, high/secondary schooling, college graduate or greater); wealth tertiles (low, middle, high household assets) and occupation (not working outside home, semi/unskilled, skilled, white-collar work). We estimated age and sex-standardized prevalence of behavioural (daily fruit/vegetables; tobacco use), weight (body mass index; waist-to-height ratio) and metabolic risk factors (diabetes, hypertension, hypercholesterolaemia; hypo-HDL; and hypertriglyceridaemia) by each SES category.Across cities, 61.2% and 16.1% completed secondary and college educations, respectively; 52.8% reported not working, 22.9% were unskilled; 21.3% were skilled and 3.1% were white-collar workers. For behavioural risk factors, low fruit/vegetable intake, smoked and smokeless tobacco use were more prevalent in lowest education, wealthy and occupation (for men only) groups compared to higher SES counterparts, while weight-related risks (body mass index 25.0-29.9 and ≥30 kg/m(2); waist-to-height ratio ≥0.5) were more common in higher educated and wealthy groups, and technical/professional men. For metabolic risks, a higher prevalence of diabetes, hypertension and dyslipidaemias was observed in more educated and affluent groups, with unclear patterns across occupation groups.SES-CVD patterns are heterogeneous, suggesting customized interventions for different SES groups may be warranted. Different behavioural, weight, and metabolic risk factor prevalence patterns across SES indicators may signal on-going epidemiological transition in South Asia.

Project description:BackgroundThe association of several comorbidities, including diabetes mellitus, hypertension, cardiovascular disease, heart failure and chronic kidney or liver disease, with acute kidney injury (AKI) is well established. Evidence on the effect of sex and socioeconomic factors are scarce. This study was designed to examine the association of sex and socioeconomic factors with AKI and AKI-related mortality and further to evaluate the additional relationship with other possible risk factors for AKI occurrence.MethodsWe included 3534 patients (1878 males with mean age 61.1 ± 17.7 and 1656 females 1656 with mean age 60.3 ± 20.0 years) admitted to Queen Elizabeth or Heartlands Hospitals, Birmingham, between October 2013 and January 2016. Patients were prospectively followed-up for a median 47.70 [IQR, 18.20] months. Study-endpoints were incidence of AKI, based on KDIGO-AKI Guidelines, and all-cause mortality. Data acquisition was automated, and information on mortality was collected from the Hospital Episode Statistics and Office of National Statistics. Socioeconomic status was evaluated with the Index of Multiple Deprivation (IMD).ResultsIncidence of AKI was higher in men compared to women (11.3% vs 7.1%; P < 0.001). Model regression analysis revealed significant association of male sex with higher AKI risk (OR, 1.659; 95% CI, 1.311-2.099; P < 0.001); this association remained significant after adjustment for age, eGFR, IMD, smoking, alcohol consumption, ethnicity, existing comorbidities and treatment (OR, 1.599; 95% CI, 1.215-2.103; P = 0.001). All-cause mortality was higher in patients with compared to those without AKI. Males with AKI had higher mortality rates in the first 6-month and 1-year periods after the index AKI event. The association of male sex with mortality was independent of socioeconomic factors but was not statistically significant after adjustment for existing comorbidities.ConclusionsMen are at higher risk of AKI and this association is independent from existing risk factors for AKI. The association between male sex and AKI-related mortality was not independent from existing comorbidities. A better understanding of factors associated with AKI may help accurately identify high-risk patients.

Project description:ImportanceCOVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.ObjectiveTo evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.Data sourcesA systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.Study selectionStudies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.Data extraction and synthesisPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.Main outcomes and measuresThe main measures were RRs, ORs, and combined prevalence values.ResultsA total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).Conclusions and relevanceIn this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Project description:BACKGROUND:Very few studies with nationally representative samples have investigated the combined effects of race/ethnicity and socioeconomic position (SEP) on polypharmacy (PP) among older Americans. For instance, we do not know if prevalence of PP differs between African Americans (AA) and white older adults, whether this difference is due to a racial gap in SEP, or whether racial and ethnic differences exist in the effects of SEP indicators on PP. Aims: We investigated joint effects of race/ethnicity and SEP on PP in a national household sample of American older adults. Methods: The first wave of the University of Michigan National Poll on Healthy Aging included a total of 906 older adults who were 65 years or older (80 AA and 826 white). Race/ethnicity, SEP (income, education attainment, marital status, and employment), age, gender, and PP (using 5+ medications) were measured. Logistic regression was applied for data analysis. Results: Race/ethnicity, age, marital status, and employment did not correlate with PP; however, female gender, low education attainment, and low income were associated with higher odds of PP among participants. Race/ethnicity interacted with low income on odds of PP, suggesting that low income might be more strongly associated with PP in AA than white older adults. Conclusions: While SEP indicators influence the risk of PP, such effects may not be identical across diverse racial and ethnic groups. That is, race/ethnicity and SEP have combined/interdependent rather than separate/independent effects on PP. Low-income AA older adults particularly need to be evaluated for PP. Given that race and SEP have intertwined effects on PP, racially and ethnically tailored interventions that address PP among low-income AA older adults may be superior to universal interventions and programs that ignore the specific needs of diverse populations. The results are preliminary and require replication in larger sample sizes, with PP measured directly without relying on individuals' self-reports, and with joint data collected on chronic disease.