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Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?

BACKGROUND: Racial and ethnic inequalities in all-cause mortality exist, and individual-level lifestyle factors have been proposed to contribute to these inequalities. In this study, we evaluate the extent to which the association between race and ethnicity and all-cause mortality can be explained b...

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Autores principales: Puka, Klajdi, Kilian, Carolin, Zhu, Yachen, Mulia, Nina, Buckley, Charlotte, Lasserre, Aurélie M., Rehm, Jürgen, Probst, Charlotte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464312/
https://www.ncbi.nlm.nih.gov/pubmed/37605166
http://dx.doi.org/10.1186/s12889-023-16178-6
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author Puka, Klajdi
Kilian, Carolin
Zhu, Yachen
Mulia, Nina
Buckley, Charlotte
Lasserre, Aurélie M.
Rehm, Jürgen
Probst, Charlotte
author_facet Puka, Klajdi
Kilian, Carolin
Zhu, Yachen
Mulia, Nina
Buckley, Charlotte
Lasserre, Aurélie M.
Rehm, Jürgen
Probst, Charlotte
author_sort Puka, Klajdi
collection PubMed
description BACKGROUND: Racial and ethnic inequalities in all-cause mortality exist, and individual-level lifestyle factors have been proposed to contribute to these inequalities. In this study, we evaluate the extent to which the association between race and ethnicity and all-cause mortality can be explained by differences in the exposure and vulnerability to harmful effects of different lifestyle factors. METHODS: The 1997–2014 cross-sectional, annual US National Health Interview Survey (NHIS) linked to the 2015 National Death Index was used. NHIS reported on race and ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx), lifestyle factors (alcohol use, smoking, body mass index, physical activity), and covariates (sex, age, education, marital status, survey year). Causal mediation using an additive hazard and marginal structural approach was used. RESULTS: 465,073 adults (18–85 years) were followed 8.9 years (SD: 5.3); 49,804 deaths were observed. Relative to White adults, Black adults experienced 21.7 (men; 95%CI: 19.9, 23.5) and 11.5 (women; 95%CI: 10.1, 12.9) additional deaths per 10,000 person-years whereas Hispanic/Latinx women experienced 9.3 (95%CI: 8.1, 10.5) fewer deaths per 10,000 person-years; no statistically significant differences were identified between White and Hispanic/Latinx men. Notably, these differences in mortality were partially explained by both differential exposure and differential vulnerability to the lifestyle factors among Black women, while different effects of individual lifestyle factors canceled each other out among Black men and Hispanic/Latinx women. CONCLUSIONS: Lifestyle factors provide some explanation for racial and ethnic inequalities in all-cause mortality. Greater attention to structural, life course, healthcare, and other factors is needed to understand determinants of inequalities in mortality and to advance health equity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16178-6.
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spelling pubmed-104643122023-08-30 Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults? Puka, Klajdi Kilian, Carolin Zhu, Yachen Mulia, Nina Buckley, Charlotte Lasserre, Aurélie M. Rehm, Jürgen Probst, Charlotte BMC Public Health Research BACKGROUND: Racial and ethnic inequalities in all-cause mortality exist, and individual-level lifestyle factors have been proposed to contribute to these inequalities. In this study, we evaluate the extent to which the association between race and ethnicity and all-cause mortality can be explained by differences in the exposure and vulnerability to harmful effects of different lifestyle factors. METHODS: The 1997–2014 cross-sectional, annual US National Health Interview Survey (NHIS) linked to the 2015 National Death Index was used. NHIS reported on race and ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx), lifestyle factors (alcohol use, smoking, body mass index, physical activity), and covariates (sex, age, education, marital status, survey year). Causal mediation using an additive hazard and marginal structural approach was used. RESULTS: 465,073 adults (18–85 years) were followed 8.9 years (SD: 5.3); 49,804 deaths were observed. Relative to White adults, Black adults experienced 21.7 (men; 95%CI: 19.9, 23.5) and 11.5 (women; 95%CI: 10.1, 12.9) additional deaths per 10,000 person-years whereas Hispanic/Latinx women experienced 9.3 (95%CI: 8.1, 10.5) fewer deaths per 10,000 person-years; no statistically significant differences were identified between White and Hispanic/Latinx men. Notably, these differences in mortality were partially explained by both differential exposure and differential vulnerability to the lifestyle factors among Black women, while different effects of individual lifestyle factors canceled each other out among Black men and Hispanic/Latinx women. CONCLUSIONS: Lifestyle factors provide some explanation for racial and ethnic inequalities in all-cause mortality. Greater attention to structural, life course, healthcare, and other factors is needed to understand determinants of inequalities in mortality and to advance health equity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-16178-6. BioMed Central 2023-08-22 /pmc/articles/PMC10464312/ /pubmed/37605166 http://dx.doi.org/10.1186/s12889-023-16178-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Puka, Klajdi
Kilian, Carolin
Zhu, Yachen
Mulia, Nina
Buckley, Charlotte
Lasserre, Aurélie M.
Rehm, Jürgen
Probst, Charlotte
Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title_full Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title_fullStr Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title_full_unstemmed Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title_short Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?
title_sort can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among us adults?
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464312/
https://www.ncbi.nlm.nih.gov/pubmed/37605166
http://dx.doi.org/10.1186/s12889-023-16178-6
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