Living in poverty and accelerated biological aging: evidence from population-representative sample of U.S. adults
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
857487
European Union's Horizon 2020 research and innovation program
857487
European Union's Horizon 2020 research and innovation program
857487
European Union's Horizon 2020 research and innovation program
857487
European Union's Horizon 2020 research and innovation program
857487
European Union's Horizon 2020 research and innovation program
LX22NPO5101
European Union - Next Generation EU (Ministry of Education, Youth and Sports, NPO: EXCELES)
LX22NPO5101
European Union - Next Generation EU (Ministry of Education, Youth and Sports, NPO: EXCELES)
LX22NPO5101
European Union - Next Generation EU (Ministry of Education, Youth and Sports, NPO: EXCELES)
LX22NPO5101
European Union - Next Generation EU (Ministry of Education, Youth and Sports, NPO: EXCELES)
PubMed
38350911
PubMed Central
PMC10865704
DOI
10.1186/s12889-024-17960-w
PII: 10.1186/s12889-024-17960-w
Knihovny.cz E-zdroje
- Klíčová slova
- Aging, Biological age, Biomarkers, Health inequalities, Poverty, Socioeconomic position,
- MeSH
- biologické markery MeSH
- chudoba * MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- průřezové studie MeSH
- senioři MeSH
- stárnutí * MeSH
- výživa - přehledy MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- biologické markery MeSH
BACKGROUND: Biological aging reflects a decline in the functions and integrity of the human body that is closely related to chronological aging. A variety of biomarkers have been found to predict biological age. Biological age higher than chronological age (biological age acceleration) indicates an accelerated state of biological aging and a higher risk of premature morbidity and mortality. This study investigated how socioeconomic disadvantages influence biological aging. METHODS: The data from the National Health and Nutrition Examination Survey (NHANES) IV, including 10 nationally representative cross-sectional surveys between 1999-2018, were utilized. The analytic sample consisted of N = 48,348 individuals (20-84 years). We used a total of 11 biomarkers for estimating the biological age. Our main outcome was biological age acceleration, indexed by PhenoAge acceleration (PAA) and Klemera-Doubal biological age acceleration (KDM-A). Poverty was measured as a ratio of family income to the poverty thresholds defined by the U.S. Census Bureau, adjusted annually for inflation and family size (5 categories). The PAA and KDM-A were regressed on poverty levels, age, their interaction, education, sex, race, and a data collection wave. Sample weights were used to make the estimates representative of the U.S. adult population. RESULTS: The results showed that higher poverty was associated with accelerated biological aging (PAA: unstandardized coefficient B = 1.38 p <.001, KDM: B = 0.96, p = .026 when comparing the highest and the lowest poverty level categories), above and beyond other covariates. The association between PAA and KDM-A and age was U-shaped. Importantly, there was an interaction between poverty levels and age (p <.001), as the effect of poverty was most pronounced in middle-aged categories while it was modest in younger and elderly groups. CONCLUSION: In a nationally representative US adult population, we found that higher poverty was positively associated with the acceleration of biological age, particularly among middle-aged persons.
Department of Epidemiology and Public Health University College London London United Kingdom
RECETOX Faculty of Science Masaryk University Kotlarska 2 Brno Czech Republic
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López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell. 2013;153:1194–217. doi: 10.1016/j.cell.2013.05.039. PubMed DOI PMC
Hsu HC, Jones BL. Multiple trajectories of successful aging of older and younger cohorts. Gerontologist. 2012;52:843–56. doi: 10.1093/geront/gns005. PubMed DOI
Kwon D, Belsky DW. A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge. Geroscience. 2021;43:2795–808. doi: 10.1007/s11357-021-00480-5. PubMed DOI PMC
Johnson AA, English BW, Shokhirev MN, Sinclair DA, Cuellar TL. Human age reversal: fact or fiction? Aging Cell. 2022;21. 10.1111/acel.13664. PubMed PMC
Ferrucci L, Gonzalez-Freire M, Fabbri E, Simonsick E, Tanaka T, Moore Z, et al. Measuring biological aging in humans: a quest. Aging Cell. 2020;19. 10.1111/acel.13080. PubMed PMC
Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49:359–67. doi: 10.1016/j.molcel.2012.10.016. PubMed DOI PMC
Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging. 2018;10:573–91. 10.18632/aging.101414. PubMed PMC
Roetker NS, Pankow JS, Bressler J, Morrison AC, Boerwinkle E. Prospective Study of Epigenetic Age Acceleration and Incidence of Cardiovascular Disease Outcomes in the ARIC Study (Atherosclerosis Risk in Communities). Circ Genom Precis Med. 2018;11. 10.1161/CIRCGEN.117.001937. PubMed PMC
Levine ME, Lu AT, Chen BH, Hernandez DG, Singleton AB, Ferrucci L, et al. Menopause accelerates biological aging. Proc Natl Acad Sci. 2016;113:9327–32. doi: 10.1073/pnas.1604558113. PubMed DOI PMC
Bae C-Y, Im Y, Lee J, Park C-S, Kim M, Kwon H, et al. Comparison of biological age prediction models using clinical biomarkers commonly measured in clinical practice Settings: ai techniques Vs. traditional statistical methods. Front Anal Sci. 2021;1. 10.3389/frans.2021.709589.
Jia L, Zhang W, Chen X. Common methods of biological age estimation. Clin Interv Aging. 2017;12:759–72. doi: 10.2147/CIA.S134921. PubMed DOI PMC
Hamczyk MR, Nevado RM, Barettino A, Fuster V, Andrés V. Biological versus chronological aging: JACC focus seminar. J Am Coll Cardiol. 2020;75:919–30. doi: 10.1016/j.jacc.2019.11.062. PubMed DOI
Noren Hooten N, Pacheco NL, Smith JT, Evans MK. The accelerated aging phenotype: the role of race and social determinants of health on aging. Ageing Res Rev. 2022;73. 10.1016/j.arr.2021.101536. PubMed PMC
Marmot M, Allen JJ. Social determinants of health equity. Am J Public Health. 2014;104:S517–9. doi: 10.2105/AJPH.2014.302200. PubMed DOI PMC
Braveman P, Egerter S, Williams DR. The social determinants of health: coming of age. Annu Rev Public Health. 2011;32:381–98. doi: 10.1146/annurev-publhealth-031210-101218. PubMed DOI
Cohen S, Doyle WJ, Baum A. Socioeconomic status is associated with stress hormones. Psychosom Med. 2006;68:414–20. doi: 10.1097/01.psy.0000221236.37158.b9. PubMed DOI
Pampel FC, Krueger PM, Denney JT. Socioeconomic disparities in health behaviors. Annu Rev Sociol. 2010;36:349–70. doi: 10.1146/annurev.soc.012809.102529. PubMed DOI PMC
Kuh D. Life course epidemiology. J Epidemiol Community Health. 1978;2003(57):778–83. doi: 10.1136/jech.57.10.778. PubMed DOI PMC
Wagg E, Blyth FM, Cumming RG, Khalatbari-Soltani S. Socioeconomic position and healthy ageing: a systematic review of cross-sectional and longitudinal studies. Ageing Res Rev. 2021;69:101365. doi: 10.1016/j.arr.2021.101365. PubMed DOI
Klemera P, Doubal S. A new approach to the concept and computation of biological age. Mech Ageing Dev. 2006;127:240–8. doi: 10.1016/j.mad.2005.10.004. PubMed DOI
Jee H, Park J. Selection of an optimal set of biomarkers and comparative analyses of biological age estimation models in Korean females. Arch Gerontol Geriatr. 2017;70:84–91. doi: 10.1016/j.archger.2017.01.005. PubMed DOI
Levine ME. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci. 2013;68:667–74. doi: 10.1093/gerona/gls233. PubMed DOI PMC
Poverty Thresholds. n.d. Available at: https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.
Kresovich JK, Garval EL, Martinez Lopez AM, Xu Z, Niehoff NM, White AJ, et al. Associations of body composition and physical activity level with multiple measures of epigenetic age acceleration. Am J Epidemiol. 2021;190:984–93. doi: 10.1093/aje/kwaa251. PubMed DOI PMC
Hu Y, Wang X, Huan J, Zhang L, Lin L, Li Y, et al. Effect of dietary inflammatory potential on the aging acceleration for cardiometabolic disease: a population-based study. Front Nutr. 2022;9. 10.3389/fnut.2022.1048448. PubMed PMC
Crimmins EM, Kim JK, Seeman TE. Poverty and biological risk: the earlier “aging” of the poor. J Gerontol A Biol Sci Med Sci. 2009;64A:286–92. doi: 10.1093/gerona/gln010. PubMed DOI PMC
Shen B, Mode NA, Noren Hooten N, Pacheco NL, Ezike N, Zonderman AB, et al. Association of race and poverty status with DNA methylation-based age. JAMA Netw Open. 2023;6:e236340. doi: 10.1001/jamanetworkopen.2023.6340. PubMed DOI PMC
Avila-Rieger J, Turney IC, Vonk JMJ, Esie P, Seblova D, Weir VR, et al. Socioeconomic status, biological aging, and memory in a diverse national sample of older US men and women. Neurology. 2022. 10.1212/WNL.0000000000201032. 10.1212/WNL.0000000000201032. PubMed PMC
Braveman P, Gottlieb L. The social determinants of health: it’s time to consider the causes of the causes. 2014;129:19-31. 10.1177/00333549141291S206. PubMed PMC
Khaw K-T, Wareham N, Bingham S, Welch A, Luben R, Day N. Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study. PLoS Med. 2008;5:e12. doi: 10.1371/journal.pmed.0050012. PubMed DOI PMC
Pase MP, Rowsthorn E, Cavuoto MG, Lavale A, Yassi N, Maruff P, et al. Association of neighborhood-level socioeconomic measures with cognition and dementia risk in Australian adults. JAMA Netw Open. 2022;5:e224071. doi: 10.1001/jamanetworkopen.2022.4071. PubMed DOI PMC
Ailshire J, Karraker A, Clarke P. Neighborhood social stressors, fine particulate matter air pollution, and cognitive function among older U.S. adults. Soc Sci Med 2017;172:56–63. 10.1016/j.socscimed.2016.11.019. PubMed PMC
Li Y, Chen T, Li Q, Jiang L. The impact of subjective poverty on the mental health of the elderly in China: the mediating role of social capital. Int J Environ Res Public Health. 2023;20:6672. doi: 10.3390/ijerph20176672. PubMed DOI PMC
Hastings WJ, Shalev I, Belsky DW. Comparability of biological aging measures in the National Health and Nutrition Examination Study, 1999–2002. Psychoneuroendocrinology. 2019;106:171–8. doi: 10.1016/j.psyneuen.2019.03.012. PubMed DOI PMC
Belsky DW, Moffitt TE, Cohen AA, Corcoran DL, Levine ME, Prinz JA, et al. Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing? Am J Epidemiol. 2017. 10.1093/aje/kwx346. PubMed PMC
Darin-Mattsson A, Fors S, Kåreholt I. Different indicators of socioeconomic status and their relative importance as determinants of health in old age. Int J Equity Health. 2017;16:173. doi: 10.1186/s12939-017-0670-3. PubMed DOI PMC
Rowe JW, Kahn RL. Successful Aging. Gerontologist. 1997;37. 10.1093/geront/37.4.433. PubMed
Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:R115. doi: 10.1186/gb-2013-14-10-r115. PubMed DOI PMC
Husted KLS, Fogelstrøm M, Hulst P, Brink-Kjær A, Henneberg K-Å, Sorensen HBD, et al. A Biological Age Model Designed for Health Promotion Interventions: Protocol for an Interdisciplinary Study for Model Development. JMIR Res Protoc. 2020;9:e19209. doi: 10.2196/19209. PubMed DOI PMC