ArticleInternational journal for equity in health2023
Longitudinal trends (2011-2020) of premature mortality and years of potential life loss (YPLL) and associated covariates of the 62 New York State counties.
Article in International journal for equity in health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Examining Racial Discrimination Index and Black-Years of Potential Life Lost (YPLL) in South Carolina: A Real-Time Social Media Research.Journal of racial and ethnic health disparities · 2026Article
- Parkinson's disease mortality and years of potential life lost in Iran: A 10-year national analysis (2013-2023).Journal of public health research · 2026Article
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Abstract
backgroundNew York State (NYS) is the 27
methodsThe goal of this study is to analyze the longitudinal trends in NYS counties of age-adjusted premature mortality rate and years of potential life loss rate (YPLL) from 2011-2020 using (CHR&R) data to identify similarities and trends among the counties of the state. This study used a weighted mixed regression model to analyze the longitudinal trend in health outcomes as a function of the time-varying covariates and clustered the 62 counties according to the trend over time in the covariates.
resultsFour clusters of counties were identified. Cluster 1, which represents 33 of the 62 counties in NYS, contains the most rural counties and the least racially and ethnically diverse counties. Clusters 2 and 3 mirror each other in most covariates and Cluster 4 is comprised of 3 counties (Bronx, Kings/Brooklyn, Queens) representing the most urban and racial and ethnic diverse counties in the state.
conclusionThe analysis clustered counties according to the longitudinal trends of the covariates, and by doing so identified clusters of counties that shared similar trends among the covariates, to later examine trends in the health outcomes through a regression model. The strength of this approach lies in the predictive feature of what is to come for the counties by understanding the covariates and setting prevention goals.
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