Literature DB >> 29253411

Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990-2014: a census tract-level analysis for the Global Burden of Disease Study 2015.

Laura Dwyer-Lindgren1, Rebecca W Stubbs1, Amelia Bertozzi-Villa1, Chloe Morozoff1, Charlton Callender1, Samuel B Finegold1, Shreya Shirude1, Abraham D Flaxman1, Amy Laurent2, Eli Kern2, Jeffrey S Duchin3, David Fleming4, Ali H Mokdad1, Christopher J L Murray5.   

Abstract

BACKGROUND: Health outcomes are known to vary at both the country and local levels, but trends in mortality across a detailed and comprehensive set of causes have not been previously described at a very local level. Life expectancy in King County, WA, USA, is in the 95th percentile among all counties in the USA. However, little is known about how life expectancy and mortality from different causes of death vary at a local, neighbourhood level within this county. In this analysis, we estimated life expectancy and cause-specific mortality within King County to describe spatial trends, quantify disparities in mortality, and assess the contribution of each cause of death to overall disparities in all-cause mortality.
METHODS: We applied established so-called garbage code redistribution algorithms and small area estimation methods to death registration data for King County to estimate life expectancy, cause-specific mortality rates, and years of life lost (YLL) rates from 152 causes of death for 397 census tracts from Jan 1, 1990, to Dec 31, 2014. We used the cause list developed for the Global Burden of Disease 2015 study for this analysis. Deaths were tabulated by age group, sex, census tract, and cause of death. We used Bayesian mixed-effects regression models to estimate mortality overall and from each cause.
FINDINGS: Between 1990 and 2014, life expectancy in King County increased by 5·4 years (95% uncertainty interval [UI] 5·0-5·7) among men (from 74·0 years [73·7-74·3] to 79·3 years [79·1-79·6]) and by 3·4 years (3·0-3·7) among women (from 80·0 years [79·7-80·2] to 83·3 years [83·1-83·5]). In 2014, life expectancy ranged from 68·4 years (95% UI 66·9-70·1) to 86·7 years (85·0-88·2) for men and from 73·6 years (71·6-75·5) to 88·4 years (86·9-89·9) for women among census tracts within King County. Rates of YLL by cause also varied substantially among census tracts for each cause of death. Geographical areas with relatively high and relatively low YLL rates differed by cause. In general, causes of death responsible for more YLLs overall also contributed more significantly to geographical inequality within King County. However, certain causes contributed more to inequality than to overall YLLs.
INTERPRETATION: This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. FUNDING: John W Stanton and Theresa E Gillespie.
Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Mesh:

Year:  2017        PMID: 29253411     DOI: 10.1016/S2468-2667(17)30165-2

Source DB:  PubMed          Journal:  Lancet Public Health


  22 in total

1.  Quantifying and explaining variation in life expectancy at census tract, county, and state levels in the United States.

Authors:  Antonio Fernando Boing; Alexandra Crispim Boing; Jack Cordes; Rockli Kim; S V Subramanian
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-13       Impact factor: 11.205

2.  The Complicity of the Population Health Scientist.

Authors:  Sandro Galea
Journal:  Milbank Q       Date:  2018-06       Impact factor: 4.911

3.  At-a-glance - Impact of drug overdose-related deaths on life expectancy at birth in British Columbia.

Authors:  Xibiao Ye; Jenny Sutherland; Bonnie Henry; Mark Tyndall; Perry Robert William Kendall
Journal:  Health Promot Chronic Dis Prev Can       Date:  2018-06       Impact factor: 3.240

4.  Life expectancy by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities.

Authors: 
Journal:  Lancet       Date:  2022-06-16       Impact factor: 202.731

5.  Historic Residential Redlining and Present-day Diabetes Mortality and Years of Life Lost: The Persistence of Structural Racism.

Authors:  Sebastian Linde; Rebekah J Walker; Jennifer A Campbell; Leonard E Egede
Journal:  Diabetes Care       Date:  2022-08-01       Impact factor: 17.152

6.  Developing a surveillance system of sub-county data: Finding suitable population thresholds for geographic aggregations.

Authors:  Angela K Werner; Heather M Strosnider
Journal:  Spat Spatiotemporal Epidemiol       Date:  2020-03-06

7.  Geographic disparities in mortality from Alzheimer's disease and related dementias.

Authors:  Igor Akushevich; Arseniy P Yashkin; Anatoliy I Yashin; Julia Kravchenko
Journal:  J Am Geriatr Soc       Date:  2021-05-19       Impact factor: 7.538

8.  Comparison of three small-area mortality metrics according to urbanity in Korea: the standardized mortality ratio, comparative mortality figure, and life expectancy.

Authors:  Ikhan Kim; Hwa-Kyung Lim; Hee-Yeon Kang; Young-Ho Khang
Journal:  Popul Health Metr       Date:  2020-07-03

9.  Smoking, alcohol consumption, and illicit substances use among adolescents in Poland.

Authors:  Maria Nowak; Malgorzata Papiernik; Alicja Mikulska; Bozena Czarkowska-Paczek
Journal:  Subst Abuse Treat Prev Policy       Date:  2018-11-29

10.  Disability Adjusted Life Years (DALYs) in Terms of Years of Life Lost (YLL) Due to Premature Adult Mortalities and Postneonatal Infant Mortalities Attributed to PM2.5 and PM10 Exposures in Kuwait.

Authors:  Ali Al-Hemoud; Janvier Gasana; Abdullah N Al-Dabbous; Ahmad Al-Shatti; Ahmad Al-Khayat
Journal:  Int J Environ Res Public Health       Date:  2018-11-21       Impact factor: 3.390

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.