Evidence map›Paper›PMID 42774187›Full record

ArticleFrontiers in public health2026

Childhood adversity and disadvantage in relation to incident disability and multimorbidity: prospective analyses of ELSA and two SHARE inception samples.

Tao Zhou, Guohua Jiang, Ruijinlin Hao, Yi Fang, Li Liu, Jun Wu, Xiaojin Zhang

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Tao ZhouDepartment of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Guohua JiangDepartment of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Ruijinlin HaoDepartment of Anesthesiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Yi FangDepartment of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Li LiuDepartment of Geriatric Cardiology, Jiangsu Provincial Key Laboratory of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Jun WuDepartment of Geriatric Cardiology, Jiangsu Provincial Key Laboratory of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Xiaojin ZhangDepartment of Geriatrics, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Enhancing the Comparability of SHARE with HRS and ELSAR01AG052527 · NIA · MAX PLANCK INST/SOCIAL LAW/SOCIAL POLICY · PI BOERSCH-SUPAN, AXEL H · 2016 to 2020
$2.1M
Mega Meta Data Set of the Health and Retirement Surveys Around the WorldRC2AG036619 · NIA · RAND CORPORATION · PI KAPTEYN, ARIE · 2009 to 2010
$2.0M
Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in IndiaR03AG043052 · NIA · RAND CORPORATION · PI LEE, JINKOOK · 2012 to 2012
$95k
NIA NIH HHS HHSN271201300071CNIA NIH HHS R01 AG017644NIA NIH HHS R01 AG030153NIA NIH HHS R01 AG052527NIA NIH HHS R03 AG043052NIA NIH HHS RC2 AG036619
6 · The paper itself

Abstract

Background: Childhood health adversity and socioeconomic disadvantage may shape late-life health, but evidence for incident disability and multimorbidity remains limited. Cross-cohort inference is complicated by non-equivalent measures of childhood experiences and differences in timing. We estimated cohort-specific prospective associations in the English Longitudinal Study of Ageing (ELSA) and the Survey of Health, Ageing and Retirement in Europe (SHARE). Methods: ELSA childhood-health/material-adversity indicators and health were assessed at wave 3. SHARE material/cultural disadvantage was assessed at wave 3 or wave 7, with health landmarks at waves 4 and 8; the two inception samples were analyzed separately. Outcomes were the first observed onset of difficulty in at least one of six activities of daily living (ADL-6) and the first observed onset of at least two of seven disease groups (MM-7). Complementary log-log person-period models incorporated interval duration, repeated observations, available survey-design information and baseline weights, and stabilized inverse-probability-of-censoring weights; death was a competing event. Highest exposure categories were compared with zero, without assuming measurement equivalence. Results: Combined survey/attrition-weighted models included 4,290/3,424 ELSA participants, 13,863/9,064 SHARE wave-3 participants, and 23,026/12,560 SHARE wave-7 participants for ADL-6/MM-7, respectively. In the mortality-ascertained ELSA wave 4-6 window, highest-versus-zero hazard ratios (HRs) were 1.43 (95% confidence interval [CI] 1.09-1.87) for ADL-6 and 1.35 (1.02-1.80) for MM-7. After excluding ADL-6 onset observed at wave 4, the lagged ELSA HR was 1.03 (0.70-1.52) through wave 6. Over waves 4-9, HRs were 1.47 (1.19-1.82) and 1.24 (0.98-1.57). SHARE wave-3 HRs were 1.36 (1.08-1.71) and 1.34 (1.09-1.64); wave-7 HRs were 1.60 (1.06-2.43) and 0.93 (0.68-1.27). Standardized competing-risk estimates showed a higher risk of ADL-6 in the primary ELSA analysis and both SHARE inception-sample analyses. MM-7 risk differences were positive in ELSA and SHARE wave 3, whereas the SHARE wave-7 contrast was imprecise and compatible with no association. Conclusion: The highest cohort-specific exposure category versus zero was associated with incident ADL disability in the primary ELSA and SHARE landmark analyses, but the ELSA association appeared strongest in the earliest interval and was not clearly sustained later. Associations with multimorbidity varied by observation window and SHARE inception sample. The findings neither establish measurement equivalence nor explain the observed cross-cohort heterogeneity.

Indexed as

Adverse Childhood ExperiencesMultimorbidityPersons with DisabilitiesActivities of Daily LivingEuropeFemaleHumansLongitudinal StudiesMaleProspective StudiesSocioeconomic Disparities in Healthactivities of daily livingchildhood adversitychildhood socioeconomic disadvantagedisabilityELSAlife-course epidemiologymultimorbiditySHARE

Identifiers

PMID42774187
PMCPMC13593477

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