Restricted accessResearch articleFirst published online 2025-10
Exposures and conditions prior to age 16 are associated with incidence of dementia status among adults in the United States Health and Retirement Study
Dementia and cognitive impairment are prevalent conditions, and susceptibility likely begins years before symptoms. Early life has not been comprehensively tested for potential risk factors for dementia.
Objective
To explore the associations between childhood conditions and exposures and cognitive impairment in adulthood.
Methods
In the US Health and Retirement Study (normal baseline cognition; n = 16,509; 2008–2018 waves), 31 exposures before age 16 were retrospectively assessed with ten-year incident cognitive status (dementia, impaired, normal). Using parallel modified Poisson models, each exposure was tested with incident cognition, adjusting for sex, baseline age, follow-up, race/ethnicity, personal/parental education.
Results
Among the analytic sample, participants were mean 61 years of age at baseline and all had normal cognition. During up to 10 years of follow-up, 14.5% developed cognitive impairment and 5.3% developed dementia. Participants with depression during childhood had 1.49 (95%CI:1.2,1.84) times higher risk of incident impairment, relative to normal cognition. Participants with headaches/migraines during childhood had 1.43 (95%CI:1.14,1.79) times higher risk of incidence of dementia. Participants with learning problems during childhood had 1.71 (95%CI:1.44,2.03) times higher risk of incident impairment. Childhood self-rated health of fair (1.59, 95%CI:1.2,2.1) and poor (2.42, 95%CI:1.62,3.61) had higher risk of incidence of dementia, relative to excellent self-rated health. Associations between additional exposures and either incident impairment or dementia did not reach the multiple testing threshold (false discovery rate < 0.01).
Conclusions
Conditions and exposures during the early life period may be important for later life cognitive impairment or dementia. These findings support extending the relevant dementia risk window to evaluate childhood.
GillisCMontenigroPNejatiM, et al.Estimating prevalence of early Alzheimer’s disease in the United States, accounting for racial and ethnic diversity. Alzheimers Dement2023; 19: 1841–1848.
3.
MatthewsKAXuWGagliotiAH, et al.Racial and ethnic estimates of Alzheimer’s disease and related dementias in the United States (2015–2060) in adults aged ≥65 years. Alzheimers Dement2019; 15: 17–24.
LivingstonGHuntleyJSommerladA, et al.Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet2020; 396: 413–446.
6.
JackCRTherneauTMWeigandSD, et al.Prevalence of biologically vs clinically defined Alzheimer spectrum entities using the National Institute on Aging–Alzheimer’s Association Research Framework. JAMA Neurol2019; 76: 1174.
7.
LivingstonGHuntleyJLiuKY, et al.Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. Lancet2024; 404: 572–628.
8.
CurrieJAlmondD. Human capital development before age five. In: CardDAshenfelterO (eds) Handbook of labor economics. Amsterdam: Elsevier B.V., 2022, pp.1315–1486.
9.
SperlingRAAisenPSBeckettLA, et al.Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement2011; 7: 280–292.
10.
FischerMLövdénMNilssonT, et al.Very early-life risk factors for developing dementia: evidence from full population registers. The Journals of Gerontology: Series B2023; 78: 2131–2140.
11.
WangX-JXuWLiJ-Q, et al.Early-life risk factors for dementia and cognitive impairment in later life: a systematic review and meta-analysis. J Alzheimers Dis2019; 67: 221–229.
12.
OveisgharanSWilsonRSYuL, et al.Association of early-life cognitive enrichment with Alzheimer disease pathological changes and cognitive decline. JAMA Neurol2020; 77: 1217.
13.
SternY. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc2002; 8: 448–460.
14.
XuWTanLWangH-F, et al.Meta-analysis of modifiable risk factors for Alzheimer’s disease. J Neurol Neurosurg Psychiatry2015; 86: 1299–1306.
15.
HymanBTPhelpsCHBeachTG, et al.National Institute on Aging–Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease. Alzheimers Dement2012; 8: 1–13.
16.
MontineTJPhelpsCHBeachTG, et al.National Institute on Aging–Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease: a practical approach. Acta Neuropathol2012; 123: 1–11.
17.
ZhengYChenZPearsonT, et al.Design and methodology challenges of environment-wide association studies: a systematic review. Environ Res2020; 183: 109275.
18.
ChungMKHouseJSAkhtariFS, et al.Decoding the exposome: data science methodologies and implications in exposome-wide association studies (ExWASs). Exposome2024; 4: osae001.
19.
JusterFTSuzmanR. An overview of the Health and Retirement Study. J Hum Resources1995; 30: S7.
20.
SonnegaAFaulJDOfstedalMB, et al.Cohort Profile: the Health and Retirement Study (HRS). Int J Epidemiol2014; 43: 576–585.
LangaKMLarsonEBCrimminsEM, et al.A comparison of the prevalence of dementia in the United States in 2000 and 2012. JAMA Intern Med2017; 177: 51.
23.
DavydowDSLevineDAZivinK, et al.The association of depression, cognitive impairment without dementia, and dementia with risk of ischemic stroke: a cohort study. Psychosom Med2015; 77: 200–208.
24.
WeiMYKabetoMULangaKM, et al.Multimorbidity and physical and cognitive function: performance of a new multimorbidity-weighted index. J Gerontol A Biol Sci Med Sci2018; 73: 225–232.
25.
McGrathRVincentBMHackneyKJ, et al.The longitudinal associations of handgrip strength and cognitive function in aging Americans. J Am Med Dir Assoc2020; 21: 634–639.e1.
26.
StephanYSutinARLuchettiM, et al.Physical, cognitive, and social activities as mediators between personality and cognition: evidence from four prospective samples. Aging Ment Health2024; 28: 1294–1303.
27.
GutierrezSMezaEGlymourMM, et al.My parent, myself, or my child: whose education matters most for trajectories of cognitive aging in middle age?Am J Epidemiol2024; 193: 695–706.
28.
MiddletonLYMNguyenVKDouJ, et al.Environmental chemical-wide associations with immune biomarkers in US adults: a cross-sectional analysis. Environ Res2024; 252: 118956.
29.
Anguita-RuizAAmineIStratakisN, et al.Beyond the single-outcome approach: a comparison of outcome-wide analysis methods for exposome research. Environ Int2023; 182: 108344.
30.
YorletsRRLeeYGantenbergJR. Calculating risk and prevalence ratios and differences in R: developing intuition with a hands-on tutorial and code. Ann Epidemiol2023; 86: 104–109.
31.
BenjaminiYDraiDElmerG, et al.Controlling the false discovery rate in behavior genetic research. Behav Brain Res2001; 125: 279–284.
32.
BenjaminiYYekutieliD. The control of the false discovery rate in multiple testing under dependency. Ann Stat2001; 29: 1165–1188.
33.
ViechtbauerW. Conducting meta-analyses in R with the metafor Package. J Stat Softw2010; 36: 1–48.
34.
Van De MheenHStronksKLoomanCwn, et al.Recall bias in self-reported childhood health: differences by age and educational level. Sociol Health Illn1998; 20: 241–254.
35.
SeifanAAssurasSHueyED, et al.Childhood learning disabilities and atypical dementia: a retrospective chart review. PLoS One2015; 10: e0129919.
36.
SeifanASchelkeMObeng-AduasareY, et al.Early life epidemiology of Alzheimer’s disease - a critical review. Neuroepidemiology2015; 45: 237–254.
37.
CooperS-A. High prevalence of dementia among people with learning disabilities not attributable to Down’s syndrome. Psychol Med1997; 27: 609–616.
38.
WhalleyLJStarrJMAthawesR, et al.Childhood mental ability and dementia. Neurology2000; 55: 1455–1459.
39.
BartelsCBelzMVogelgsangJ, et al.To be continued? Long-term treatment effects of antidepressant drug classes and individual antidepressants on the risk of developing dementia: a German case-control study. J Clin Psychiatry2020; 81: 19m13205.
40.
HakimA. Perspectives on the complex links between depression and dementia. Front Aging Neurosci2022; 14: 821866.
41.
ChuangCSLinCLLinMC, et al.Migraine and risk of dementia: a nationwide retrospective cohort study. Neuroepidemiology2013; 41: 139–145.
42.
WangJXuWSunS, et al.Headache disorder and the risk of dementia: a systematic review and meta-analysis of cohort studies. J Headache Pain2018; 19: 95.
43.
IraniFBarboneJMBeausoleilJ, et al.Is asthma associated with cognitive impairments? A meta-analytic review. J Clin Exp Neuropsychol2017; 39: 965–978.
44.
WatsonRSBeersSRAsaroLA, et al.Association of Acute respiratory failure in early childhood with long-term neurocognitive outcomes. JAMA2022; 327: 836.
WangRReddyPH. Role of glutamate and NMDA receptors in Alzheimer’s disease. J Alzheimers Dis2017; 57: 1041–1048.
47.
PatelCJBhattacharyaJButteAJ. An environment-wide association study (EWAS) on type 2 diabetes mellitus. PLoS One2010; 5: e10746.
48.
RotsteinALevineSZ. Childhood infectious diseases and old age cognitive functioning: a nationally representative sample of community-dwelling older adults. Int Psychogeriatr2021; 33: 75–82.
49.
KodeshA. Childhood viral infections may be beneficial to cognition in old age. Int Psychogeriatr2021; 33: 19–20.
50.
WuXYangHHeS, et al.Adult vaccination as a protective factor for dementia: a meta-analysis and systematic review of population-based observational studies. Front Immunol2022; 13: 872542.
51.
EcarnotFBoccardiVCalcagnoA, et al.Dementia, infections and vaccines: 30 years of controversy. Aging Clin Exp Res2023; 35: 1145–1160.
52.
WeuveJProust-LimaCPowerMC, et al.Guidelines for reporting methodological challenges and evaluating potential bias in dementia research. Alzheimers Dement2015; 11: 1098–1109.
53.
CollishawS. Annual research review: secular trends in child and adolescent mental health. J Child Psychol Psychiatry2015; 56: 370–393.
54.
YuLLiuWWangX, et al.A review of practical statistical methods used in epidemiological studies to estimate the health effects of multi-pollutant mixture. Environ Pollut2022; 306: 119356.
55.
TibshiraniR. Regression shrinkage and selection via the Lasso. J R Stat Soc B Methodol1996; 58: 267–288.
56.
CadiouSBasagañaXGonzalezJR, et al.Performance of approaches relying on multidimensional intermediary data to decipher causal relationships between the exposome and health: a simulation study under various causal structures. Environ Int2021; 153: 106509.
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