Background: Epidemiologic studies point to multiple health inequities among sexual minority people, but few studies have examined mortality. Some causes of death are more preventable than others, and access to prevention is theorized to follow patterns of access to social and material resources. The objective of this study is to compare estimates of preventable mortality between sexual minority (SM)-i.e., bisexual, lesbian, gay-and heterosexual adults in Canada.
Methods: A population-based retrospective cohort with 442,260 (unweighted N) Canadian adults, ages 18-59 years, was drawn from the Canadian Community Health Survey/Canadian Mortality Database linked database (2003-2017). The Rutstein preventability rating index was used to classify cause-specific mortality (low/high). Longitudinal analyses were conducted using Cox proportional hazards models.
Results: SM respondents had higher hazard of all-cause mortality (unadjusted hazard ratio [uHR] 1.28, 95% CI 1.06, 1.55). The uHR increased when the outcome was limited to highly-preventable causes of mortality (uHR 1.43, 95% CI 1.14, 1.80). The uHR further increased in sensitivity analyses using higher thresholds of the Rutstein index. SM respondents had higher hazard of cause-specific mortality for heart disease (uHR 1.53, 95% CI 1.03, 2.29), accidents (uHR 1.97, 95% CI 1.01, 3.86), HIV (uHR 75.69, 95% CI 18.77, 305.20), and suicide (uHR 2.22, 95% CI 0.93, 5.30) but not for cancer (uHR 0.86, 95% CI 0.60, 1.25). The adjusted HR (aHR) for highly-preventable mortality was not attenuated by adjustment for confounders (aHR 1.57, 95% CI 1.20, 2.05) but was reduced by adjustment for hypothesized mediators relating to access to social and material resources (marital status, children, income, education; aHR 1.11, 95% CI 0.78, 1.58).
Conclusions: Preventable mortality was elevated for SM Canadians compared to heterosexuals. Early and broad access to sexual minority-affirming primary and preventive healthcare should be expanded.
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http://dx.doi.org/10.1016/j.ssmph.2022.101276 | DOI Listing |
Acta Pharm
December 2024
Department of Clinical Pharmacy, University Hospital Dubrava, 10000 Zagreb Croatia.
Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity globally. It is estimated that 17.9 million people died from CVDs in 2019, which represents 32 % of all deaths worldwide.
View Article and Find Full Text PDFPLoS Negl Trop Dis
January 2025
Disease control and immunization unit, Bauchi State Primary Health Care Development Agency, Dass Emirate, Nigeria.
Objective: Schistosomiasis has been recognized by WHO as a major contributor to mortality and morbidity, particularly in Sub-Sahara Africa, where it is most prevalent. There is a lack of reliable data on the effectiveness of health education interventions in reducing the prevalence of schistosomiasis in Bauchi State. Hence, the study assessed the prevalence of schistosomiasis and the knowledge, attitude and practices of community members of Dass Emirate towards the prevention and control of schistosomiasis before and after health education intervention.
View Article and Find Full Text PDFPLoS One
January 2025
Employee Health Department, General Directorate of Public Health, Ministry of Health, Ankara, Türkiye.
Introduction: Chronic diseases have become a significant public health problem with the prolongation of human life. There are four main behavioral risk factors for mortality. This study evaluated the significant risk factors for chronic diseases in university hospital employees.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Diagnostic and Health Sciences, College of Health Professions, University of Tennessee Health Science Center, Memphis, TN, United States of America.
For patients hospitalized with COVID-19, delirium is a serious and under-recognized complication, and people experiencing homelessness (PEH) may be at greater risk. This retrospective cohort study compared delirium-associated risk factors and clinical outcomes between PEH and non-PEH. This study used patient records from 154 hospitals discharged from 2020-2021 from the Texas Inpatient Public Use Data file.
View Article and Find Full Text PDFPLoS One
January 2025
Institute for Physical Activity and Nutrition, Deakin University, Melbourne, VIC, Australia.
Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the development of accurate and reliable predictive models to facilitate early detection and intervention. While state of the art work has focused on various machine learning approaches for predicting heart disease, but they could not able to achieve remarkable accuracy. In response to this need, we applied nine machine learning algorithms XGBoost, logistic regression, decision tree, random forest, k-nearest neighbors (KNN), support vector machine (SVM), gaussian naïve bayes (NB gaussian), adaptive boosting, and linear regression to predict heart disease based on a range of physiological indicators.
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