https://orcid.org/0009-0004-8105-4592
Abstract
Background
Dementia is a major public health concern, with its incidence rising as the population ages. Recent studies suggest links between childhood health, socioeconomic status, and later-life cognitive impairment and dementia, though findings remain inconclusive. This systematic review evaluates the influence of childhood health and socioeconomic status on cognitive impairment and dementia.
Method and findings
A systematic search conducted in MEDLINE, CiNAHL, and PsycINFO in December 2024 identified 44 studies matching our inclusion criteria. Findings are presented under five key themes: (1) childhood health, (2) childhood educational attainment, (3) family socioeconomic and educational factors, (4) childhood experiences, and (5) childhood reading habits and social interactions.
Conclusion
Our results highlight the need for further longitudinal studies to establish causal relationships between early-life risk factors and later cognitive decline. Policymakers should prioritize early childhood development programs that integrate health, nutrition, education, and social support to help mitigate cognitive impairment and dementia in later life.
Figures
Citation: Le T, Maharani A, Hayter M, Gilleen J, Lee A (2025) Cognitive impairment and dementia—Are they linked to childhood health and socioeconomic status? A systematic review. PLoS ONE 20(3): e0311074. https://doi.org/10.1371/journal.pone.0311074
Editor: Jordi Gumà, Centre d’Estudis Demogràfics: Centre d'Estudis Demografics, SPAIN
Received: September 12, 2024; Accepted: February 11, 2025; Published: March 27, 2025
Copyright: © 2025 Le et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Our aging population will pass 2 billion by 2050 [1], meaning we face urgent challenges to mitigate age-related diseases, particularly Alzheimer’s disease and other dementias [2]. Dementia care has become a top public health priority due to its widespread prevalence and lack of curative treatments [3]. Consequently, understanding causation is crucial to underpin targeted early interventions and diagnoses. It can inform policy and healthcare strategies that may mitigate the significant burden of dementia and reinforce the disease as a public health priority.
The Lancet Commission on Dementia Prevention, Intervention, and Care identified 14 modifiable risk factors, including childhood-related factors such as low education, which account for 40% of global dementia cases [3]. Lifecourse preventative strategies are supported by the World Health Organization (WHO) 2019 report, “Reducing the Risk of Cognitive Decline and Dementia” [4]. Their guidelines highlight the impact of early-life interventions in mitigating cognitive decline and reinforce a need to evaluate childhood health and socioeconomic conditions as potential contributors to later-life cognitive decline. Thus, this systematic review seeks to reveal early-life risk factors linked to cognitive impairment and dementia.
Malnutrition affects over 149 million children under five and has significant long-term neurodevelopmental consequences [5]. Over 356 million children are living in extreme poverty and lacking access to basic healthcare, food, education, and resources [6]. There is evidence linking poor health or adverse socioeconomic conditions in childhood with later-stage cognitive decline, suggesting those from poorer backgrounds had a 1.5 to 2.0 times higher risk of cognitive decline and dementia [7]. The evidence is clear that childhood nutrition is critical to neurological development, and malnutrition leads to long-term deficits which increase the risk of dementia later in life [8]. Other contributing clinical factors, such as inflammatory defense mechanisms associated with repeated childhood chronic illnesses, and adverse childhood experiences (ACE) are also linked to neurodegeneration and cognitive decline [9,10]. Poor living conditions and limited access to healthcare in children from lower socioeconomic backgrounds mean they are more likely to suffer repeated illnesses [11]. As socioeconomic status (SES) increases, so does access to education and stimulation. Increasingly educated parents provide more learning resources, healthier environments, and greater cognitive stimulation at home, which are linked to improved cognitive function and a reduced risk of dementia in later life [12]. Thus, we can establish that childhood health and SES are factors that pose a long-lasting impact on cognitive health and neurodevelopment.
However, establishing causative links between childhood health, childhood SES, and cognitive function in later life remains contentious. Some studies suggest that the negative effects of poor health or low SES in childhood may be mitigated by positive experiences in adulthood [13,14]. Children may reach higher educational attainment or secure more stable and engaging employment, thus mitigating some of the causative relationships [13,14]. Others oppose this, stating childhood disadvantages have long-term effects on neurodevelopmental structure and function [15], which cannot be entirely mitigated by improvements in later life [16].
In the last few decades, only one systematic review and meta-analysis on early-life factors associated with dementia and cognitive impairment in later life has been conducted [17]. However, epidemiological data in this study spanned from 1865 to 2017, perhaps lacking temporal relevance to today’s society. Search strings were slightly limited for systematic and relevant evidence retrieval, and researcher funding potentially led to intrinsic bias. Thus, our systematic review evaluates current empirical evidence, published within the last decade (2014-2024). Our search strategy also included childhood health and childhood SES to ensure a more comprehensive analysis of early-life factors.
Definition of childhood health and childhood SES
Childhood health refers to the physical, mental, and emotional well-being of children from birth through adolescence [18]. In the context of this study, childhood health is defined in various ways, ranging from general assessments to more specific measurements. Most studies use retrospective self-reports, asking participants to rate their childhood health from excellent to poor. Additionally, childhood health can be assessed through factors like hunger or food insecurity, as well as the occurrence of illnesses, such as infections or psychological issues, during childhood.
Childhood SES refers to the economic and social conditions experienced during early life, often assessed through a combination of self-reported and objective measures [19]. Common measurements include retrospective self-assessments of social status during childhood, typically using a Likert scale (e.g., high, middle, low), as well as parental education and occupation, which are key indicators of a household’s socioeconomic position. Additional variables include household income, financial stability, and community factors, such as the percentage of adults with higher education or in professional occupations. These measures are typically categorized into “high,” “middle,” or “low” SES and are consistent across studies, although specific variables may vary slightly.
Research question and objectives
This systematic literature review poses the following research question: “Are there any childhood health and childhood SES factors that may predispose or be linked to cognitive impairment and dementia in later life?”
There are two objectives:
- To systematically identify and synthesize evidence on the relationship between childhood health and SES with cognitive impairment and dementia in later life.
- To explore the possible association between these early-life factors and the risk of cognitive impairment and dementia, thereby informing future cohort analyses and intervention strategies.
Methods
Design
This study adheres to the reporting standards of the Equator Network for systematic reviews [20], including the implementation of appropriate search strategies and the formulation of research questions based on the structured PICOS framework [21–23]. The eligibility and exclusion criteria for this study are presented in Table 1.
Briefly, this review focused on studies examining the impact of childhood health and SES on cognitive decline and dementia in older adults, including peer-reviewed research published in the past decade (2014–2024) to ensure the information is up to date.
Search strategy
We applied the 2024 Medical Subject Headings (MeSH), Boolean operands, and truncations to source relevant studies for this systematic review. The search was conducted in three electronic databases, i.e., MEDLINE, CiNAHL, and PsycINFO, on 17th December 2024. The search strings were:
- MEDLINE: (“child* health*”[All Fields] OR “child* experience*”[All Fields] OR “child* illness”[All Fields] OR “child* disease*”[All Fields] OR “child* socioeconomic”[All Fields] OR “parental education”[All Fields] OR “parental occupation”[All Fields] OR “household income”[All Fields]) AND (“cogn* impairment”[All Fields] OR “cogn* decline”[All Fields] OR “cogn* disorder”[All Fields] OR “dementia”[All Fields] OR “Alzheimer*”[All Fields]) AND (“older adults”[All Fields] OR “older age”[All Fields] OR “older people”[All Fields] OR “elderly”[All Fields] OR “aged”[All Fields] OR “aging”[All Fields]), Filters: in the last 10 years, English.
- CiNAHL: childhood health OR childhood health issues OR childhood socioeconomic status OR (childhood adversity or childhood trauma or adverse childhood experiences) AND (cognitive impairment or cognitive dysfunction or cognitively impaired or dementia or Alzheimer) AND (older people or older adults or elderly or aged), Filter: Publication Year: 2014-2024, Peer-Reviewed, English Language, Human.
- PsycINFO: Any Field: child * health * OR Any Field: child * experience * OR Any Field: child * illness OR Any Field: child * disease * OR Any Field: child * socioeconomic OR Any Field: parental education OR Any Field: parental occupation OR Any Field: household income AND Any Field: cogn * impairment OR Any Field: cogn * decline OR Any Field: dementia OR Any Field: Alzheimer * AND Population Group: Human AND Age Group: Middle Age (40-64 yrs) OR Aged (65 yrs & older) AND Document Type: Journal Article AND Open Access AND Peer-Reviewed Journals only AND Year: 2014 To 2024.
We also conducted a manual search of the reference lists of relevant articles to identify additional studies. Following Equator guidelines, all authors meticulously reviewed the references of all included studies to eliminate duplicates and exclude articles that did not align with the scope of the study. The search was restricted to articles published in English. Duplicates were manually removed after identifying high-risk duplicate articles using the Rayyan platform. TL and AM independently assessed eligibility, and any disagreements were resolved by the final decision from AL.
Study selection
The search strategy identified 7,616 records from electronic databases (1049 articles from MEDLINE, 6475 articles from CINAHL, and 92 articles from PsycINFO) and 24 from hand searching, resulting in 7,640 publications for initial evaluation. After removing 166 duplicates, 7,474 records were screened by title and abstract, resulting in the exclusion of 7,410 records for reasons including: not in English, was not published from 2014 to 2024, wrong study design, and irrelevant topic. Of the remaining 64 reports sought for retrieval, 2 were not retrieved, leaving 62 full-text papers to be assessed for eligibility. A further 18 reports were excluded because the outcome was not focused on exploring the impact of childhood health or childhood SES on dementia or cognitive impairment in later life. Ultimately, 44 publications were selected as the most relevant for the systematic review, comprising 18 cross-sectional studies and 26 cohort studies (Fig 1).
Quality appraisal
To assess article quality for this literature review, we utilized the Joanna Briggs Institute (JBI) tool, known for its superior reliability compared to the Critical Appraisal Checklists Programme (CASP) [24]. The JBI checklist comprises eight questions for cross-sectional studies and 11 questions for cohort studies (See Tables 2 and 3 for results of quality appraisal) [25]. Responses were categorized as “yes” (1 point) and others as 0 points (“no,” “unclear,” or “not applicable”). Tertile classifications of high- (score > 70%), mid- (score 50–70%), and low-quality (score < 50%) were assigned using the appropriate JBI checklist. Only “high-quality” papers were included in the review. Quality assessments of each study were conducted independently by TL and AM, with cross-checking by AL to minimize bias and ensure that no data were missing in this systematic review.
Data extraction
We extracted data from 44 articles using an Excel spreadsheet. Table 4 presents the detailed empirical research matrix: (1) Authors; (2) Title; (3) Country/Region; (4) Study design; (5) Data source; (6) Age of participants; (7) Sample size; (8) Data analysis methods; (9) Early-life factors; (10) Cognitive/dementia measures; and (11) Main outcomes.
Results
Study characteristics
Research on the relationship between childhood health, SES, and later-life dementia spans globally. This review identified a notable focus on resource-rich countries. The US published 15 studies [26–29,32,33,40,43,63–69], plus a multicentre study with the UK [62]. China published eight studies [44–51], and Japan published four studies [30,31,55,56]. Two studies were conducted across Europe [52,53], while two others were conducted in the UK [61], including one in Scotland [59]. The remaining countries–Australia [41], Finland [54], France [42], India [35], Indonesia [37], Ireland [36], Malaysia [39], Mexico [57], Nigeria [58], South Africa [34], Sweden [60], and Vietnam [38]–each have only one study. This highlights a diverse but uneven distribution of research.
Age ranges varied across participants, but the baseline was at least 40 years old because all studies aimed to evaluate any links between childhood health and childhood SES and cognitive function later in life. Sample sizes across studies varied significantly, ranging from 121 [29] to 515,013 [61], with the risk that the smaller population studies may lack sufficient power to detect meaningful differences or associations.
A number of population databases were noted across the 44 studies. Sixteen studies analyzed data from the Health and Retirement Studies International Family of Studies, including the Health and Retirement Study (HRS) [62,67], the China Health and Retirement Longitudinal Study (CHARLS) [45–51], the Indonesia Family Life Survey (IFLS) [37], the English Longitudinal Study of Aging (ELSA) [61], the Survey of Health, Aging, and Retirement in Europe (SHARE) [52,53], the Mexican Health and Aging Study (MHAS) [57], the Irish Longitudinal Study on Ageing (TILDA) [36], and the Longitudinal Ageing Study in India (LASI) [35]. Using these validated population datasets offers several strengths, such as harmonized data collection, diverse cross-cultural samples, and longitudinal assessments of cognitive function. Longitudinal data tracking cognitive changes over time allows for in-depth analyses of the long-term impact of childhood experiences. However, a notable limitation of this methodology is reliance on retrospective self-reports of childhood health and SES and associated recall bias.
Other sources of data across the studies were retrieved from surveys, such as the Behavioral Risk Factor Surveillance System Survey (BRFSS) [27,32,40], the Japan Gerontological Evaluation Study (JAGES) [31,55,56], and the Wisconsin Longitudinal Study (WLS) [66,69]. Each survey drew from prevalidated cognitive assessment tools, such as dementia diagnosis, medical records, and MMSE. These tools are highly reliable in identifying dementia-related outcomes. Papers drawn from survey data had smaller study populations when compared with larger longitudinal datasets. This may reduce the generalizability and cross-cultural applicability of the findings, but they offer contextual, country-specific foci.
In summary, compared to other studies, those in the HRS family excel at capturing long-term, cross-cultural trends, though they still encounter challenges related to recall bias.
A number of pre-validated measurement instruments were applied across the evidence. For cognitive function and dementia diagnosis, most studies utilized the Mini-Mental State Examination (MMSE) [35,36,38,42,44,51,55,56,59]. MMSE is a validated tool for assessing cognitive function in community settings due to its quick administration, ease of use, and robust validation across diverse populations [70]. The MMSE’s 11 items evaluate five domains of cognitive function: orientation, registration, attention, recall, and language, providing a comprehensive overview of an individual’s cognitive status. This makes it particularly suitable for large-scale surveys and effective screening of cognitive impairment in older populations [70]. Other tools included the Cognitive Abilities Screening Instrument (CASI) [68], Community Screening Interview for Dementia (CSI ‘D’) [58], Cross-Cultural Cognitive Examination (CCCE) [57], Delayed Word Recall Test (DWRT) [44,63,65,66], Geriatric Mental State (GMS) [39], ICD-8, 9, & 10 [54], medical records [41,60], Quick Mild Cognitive Impairment (QMCI) [30], Telephone Interview for Cognitive Status (TICS) [37,45,62], Montreal Cognitive Assessment (MoCA-SA) [26], and Wechsler Adult Intelligence Scale (WAIS) [69].
Variables related to childhood health, childhood SES, ACEs, parental engagement, education, nutritional status, living conditions, and books read were included, ensuring a comprehensive evaluation of the link between childhood health, childhood SES, and cognitive impairment or dementia in later life.
Only 11 papers reported response rates [26,30,31,34,36,40,48,51,55–57]. The highest response rate (91.8%) was observed in the MHAS from the HRS family of surveys [57], whereas the lowest response rate (35.3%) was in a Japanese cross-sectional study [30]. This is notable from a methodological perspective, as higher response rates may be subject to response and selection bias. Individuals with better cognitive function, higher SES, or greater engagement with healthcare systems are more likely to participate, therefore overrepresenting the healthier populations. Recognizing these biases is essential when interpreting results, particularly in studies evaluating datasets that measure early-life factors against later-stage cognitive outcomes. Moreover, most studies relied on retrospective information about childhood health and childhood SES, which may be subject to recall bias and/or missing data. To mitigate these biases, a range of advanced statistical techniques such as structural equation modeling (SEM) [63,66], latent growth curve modeling [49], sensitivity analysis [36], and path analysis [61] were used. To determine linear relationships, binary, multinomial, and multivariate regression models were applied [26,28,31,34–37,42,43,55,56,58]. Mixed-effects models evaluated temporal trends [28,50,65]. More advanced regression techniques were employed to assess relative effects. These included Cox proportional hazards models [42,55,56,58], multi-state survival models [53], and group trajectory models [46]. More specific data distributions and between-group comparisons across variables were statistically evaluated using appropriate tests such as chi-square [26,44], ANOVA [44], and Fisher’s exact test [58]. Additionally, quantile regression [38] and marginal structural models [45] were applied to address specific data distributions and explore causal relationships.
The long arm of childhood circumstances on cognitive function and dementia
A review of all data and information across studies revealed five common themes, presenting factors describing the associations between childhood health and childhood SES, and potential links with dementia and cognitive function. These include: (1) childhood health; (2) childhood educational attainment; (3) family socioeconomic and educational factors; (4) childhood experiences; and (5) childhood reading habits and social interactions.
Childhood health.
Several studies identified links between childhood health and cognitive impairment or dementia later in life. Sha et al.’s longitudinal study of 10,533 participants linked better childhood health with 1.1 times higher cognitive performance in middle and older age when compared with those reporting poorer childhood health [49]. Cross-sectional studies report even higher likelihood estimates of 1.4–1.74 across India [35] and the US [26]. Similarly, Kobayashi et al.’s population-based analysis of older people linked poor childhood health history to a 28% reduction in cognitive scores later in life [34]. Donley et al.’s Finnish longitudinal study of 2,682 participants revealed that childhood stress approximately doubled the risk of dementia [54]. Findings related to childhood nutrition were also noteworthy. Momtaz’s (2015) Malaysian cross-sectional study of 2,745 participants revealed that childhood food scarcity nearly doubled the likelihood of cognitive impairment in old age [39]. This finding was slightly higher than those reported in studies conducted in Vietnam [38] and China [48], which linked severe childhood hunger to a 1.5 times increased risk of poor cognitive outcomes. Conversely, analysis of data from the Irish longitudinal study on aging linked improved cognitive functions with childhood infectious diseases. They found the more infectious diseases experienced by children, the better their cognitive function later in life. This study of 2,994 participants posits that each additional infectious disease may be associated with a 0.18-point improvement in cognitive functioning [36].
Childhood educational attainment.
Childhood education has also been significantly linked to later-life cognitive function. Koyabishi et al.’s study found that each additional year of education may increase cognitive function scores in later life by 0.09 points [34]. Similarly, Hendrie et al.’s (2018) Nigerian study of 3,276 participants found that each additional year of education reduced the risk of dementia by 7% [58]. These figures are reflected in studies across the US (1.23 times higher risk of dementia with lower education attainment) [68]. In Sweeden, Dekhtyar et al.’s (2015) retrospective analysis of 7,574 students, aggregated to subject-specific performance, found links between lowest grade point average students and a 1.21 times higher risk of dementia in later life [60].
Family socioeconomic and educational factors.
This systematic review also indicates a significant body of evidence linking family socioeconomic and education factors with dementia. Studies across India, the US, the UK, and China revealed individuals in midlife or older who had reported experiencing financial hardship during childhood tend to exhibit greater cognitive decline, ranging from 9% to 22% when compared to those with more favorable financial conditions [35,48,49,68]. A slightly higher figure was reported by a cross-study in Indonesia, which found that lack of basic amenities such as electricity, running water, and indoor toilets during childhood was associated with lower cognitive function scores later in life, with a difference of up to 26% [37]. Another cross-sectional study in South Africa found that individuals whose fathers held professional jobs had cognitive scores 0.25 points higher than those whose fathers worked in unskilled manual labor [34]. Additionally, a study conducted in Japan reported that compared to individuals with high SES during childhood, those with low SES and middle SES were 1.29 times and 1.1 times more likely to report subjective memory complaints in later life, respectively [31]. A retrospective study using data from the WLS found that an increase of one standard deviation in childhood SES was associated with memory scores higher by 8% and language/executive function scores higher by 34% at age 72 [66]. Aartsen et al.’s (2019) European longitudinal study of 24,066 participants [52], compared lower childhood SES (disadvantaged) populations with higher SES (advantaged) populations and identified significant reductions in verbal fluency and recall by age 73 in the most disadvantaged groups. A US cross-sectional study [33] of 9,331 participants aged 45-74 linked parental higher educational status with a 0.26 higher average score for their children on cognitive tests in later life. Children of parents who are literate and educated were found to have 0.5 times higher memory scores when compared to lower-educated parents [44].
However, Racine et al.’s Scottish cohort analysis [59] found that a lower education status mother may predict an increased risk of cognitive decline, yet the study indicated additional confounding factors. They found father’s employment as manual labor, or reduced educational attainment, had no impact on cognitive outcome measures.
Childhood experiences.
The childhood experiences summarized in this review encompass various factors influencing children’s development. These experiences are categorized into key groups: abuse and neglect, including physical, emotional, and sexual abuse, lack of parental care and attention or absence of peer relationships; family-related issues, such as parental loss, divorce, remarriage, domestic violence, or parental mental health problems and substance abuse; and adverse living environments including unsafe neighborhoods.
There is a wealth of evidence supporting links between high levels of ACEs and increased risk of dementia. Longitudinal studies in Japan [55,56] and the US [32], indicate individuals with three or more ACEs had a 1.78 to 3.25 times higher risk of developing dementia compared to those without such experiences. A French study estimated that individuals with three to four ACEs had a 1.39 times higher risk of reduced psychomotor speed, and risks increased with each additional ACE [42]. Those with five or more ACEs had a 1.52 times higher risk compared to individuals with two or fewer ACEs [42]. Lor et al.’s study of healthy aging in Africa, with 764 participants linked to two ACEs posed an 11.7% higher risk of cognitive decline, those with three ACEs had a 7.5% higher risk, and those with four or more ACEs had an 8.9% higher risk, perhaps indicating ACES is not cumulative [64].
Moving on from comparative studies determining how many ACES cumulatively affect cognitive functioning in later life, we can assert that there is a link. This is supported by a large cross-sectional US study (N = 1,488), which identified a 10.3% higher prevalence of dementia in older adults with four or more ACEs [43].
Childhood sexual abuse is also associated with a 1.37 increased risk of cognitive decline in later life [51]. Another US-based study found this even higher, citing that individuals who experienced sexual abuse as a child had a 2.83 times greater likelihood of subjective cognitive decline when compared to those without [27].
Parent-child relationships are also highly important, with one linking medium to high levels of positive parental involvement during childhood with increased cognitive score outcomes [30]. A large UK longitudinal evaluation of 515,013 participants revealed the significant impact of parental abuse on future cognitive development, memory, verbal fluency, and recall [61]. Other negative family events, (such as parental remarriage, and parent death) have been linked to lower cognitive outcomes in later life. Specifically, parental remarriage was associated with a 0.11-point decrease in cognitive test scores, maternal death with a 0.18-point decrease, and paternal death with a 0.11-point decrease [28]. Conversely, an Australian study of 1568 participants revealed no links between ACEs and diagnoses of dementia [41].
Childhood reading habits and social interactions.
There is also evidence supporting childhood reading habits and social interactions and potential links with cognitive function. A Japanese study found regular reading resulted in 3.11 higher test scores in later life when compared to non-readers [30]. Individuals with more books in the household had higher cognitive outcome scores and a 21% risk reduction of dementia [37,53]. Furthermore, longitudinal studies in China found that individuals who faced difficulties in establishing peer relationships during childhood scored 0.208 points lower on cognitive tests and had a 21% higher risk of developing dementia compared to those with positive peer relationships [45,47].
Discussion
This study highlights poor childhood health, low educational attainment, adverse socioeconomic conditions, ACEs, limited reading habits, and inadequate social interactions increase the risk of dementia later in life. It could be explained that chronic illnesses and malnutrition during childhood disrupt neurodevelopment [71], negatively affecting brain structure and function. Such disruptions result in reduced grey matter volume and alterations in white matter integrity, which are known contributors to long-term cognitive decline [72–74]. However, one study reported that children who experienced multiple infectious diseases during childhood scored higher on cognitive assessments [36]. This counterintuitive finding suggests a need for further research to understand potential mechanisms linking childhood immune challenges and cognitive outcomes.
Several studies showed that higher education levels are consistently associated with better cognitive function. This aligns with prior evidence suggesting that higher education levels were linked to slower brain function decline, lower prevalence of cognitive disorders [75,76], and better short- and long-term memory performance throughout life [77]. Childhood SES also plays a pivotal role in later cognitive outcomes. Children from low-income families face barriers to adequate nutrition, healthcare, educational opportunities, and limited access to intellectually stimulating activities [78–82]. Moreover, substandard living conditions—such as homes lacking electricity or running water—exacerbate childhood stress and impair development [37,83,84]. These factors hinder optimal brain development and predispose children to poorer cognitive function [85]. Furthermore, a stable family structure and higher parental education levels significantly contribute to cognitive function later in life [86]. This can be explained by the fact that parents with higher education levels, leading to stable and well-paying jobs, are better positioned to provide resources, opportunities, academic support, and an environment conducive to cognitive development [87–89].
ACEs, including abuse, neglect, and family dysfunction, have consistently been associated with poorer cognitive outcomes. These findings corroborate previous evidence suggesting that stress and trauma during critical periods of brain development lead to structural and functional changes in the brain [90–92]. Such alterations often affect regions involved in stress regulation and cognitive functioning, resulting in long-term impairments. Additionally, the presence of both parents in a family, compared to single-parent families or those without parental presence, has been linked to better emotional regulation and social skills, which are crucial for cognitive health [93]. However, one cross-sectional study conducted in Australia did not find an association between ACEs and cognitive impairment [41]. This finding may be explained by the fact that the study only included participants from Canberra (the capital) and Queanbeyan, which are both relatively affluent areas [94]. These cities have a higher concentration of wealth, and individuals residing in such environments may have experienced lower levels of childhood adversity compared to populations from less advantaged regions. As a result, this could have influenced the study’s findings.
A notable finding in this study is that access to books during childhood is associated with a reduced risk of dementia. While evidence on this topic is limited in previous research, this finding can be explained by the cognitive stimulation provided by reading, which enhances language skills and promotes lifelong learning—factors crucial for maintaining cognitive resilience [95]. Children engaged in reading activities are more likely to develop critical thinking and comprehension skills, contributing to improved educational and cognitive outcomes [95]. However, as previously noted, limited research has explored the influence of childhood reading on cognitive function in later life, emphasizing the need for further studies to provide a clearer understanding of its role in cognitive development.
Finally, the importance of social interactions during childhood was also recorded. This finding can be explained by the role of social interactions in developing key skills such as communication, emotional regulation, and problem-solving [96]. Children who experience social isolation are deprived of opportunities to cultivate these skills, which can adversely impact cognitive health [97].
This study synthesizes global evidence, emphasizing the importance of early-life interventions in preventing cognitive decline. Public health initiatives should prioritize enhancing children’s physical and mental health while addressing socioeconomic inequalities. These strategies not only benefit individuals but also alleviate the societal and economic burden of cognitive decline and dementia, aligning with WHO guidelines [4]. Beyond the scope of these guidelines, this study shows that promoting reading habits from an early age may serve as a potential protective factor for cognitive health, supporting existing theories on cognitive reserve. Future research is needed to clarify the causal relationship between reading habits and cognitive development. Additionally, a deeper exploration of the impact of childhood infectious diseases on later-life cognition is warranted to inform future preventive strategies.
This study may have some limitations. Firstly, it was restricted to English-language papers published between 2014 and 2024, potentially excluding relevant research published in other languages or from earlier periods. Secondly, a substantial proportion of the studies were cross-sectional, which limits the ability to establish causality between risk factors and dementia. Thirdly, the variation in sample sizes among the included studies could affect the reliability of the results. There were also inconsistencies in the criteria used to define exposure factors in some studies may impact the comparability and validity of the findings and, as many studies drew from the same datasets, (such as CHARLS, WLS, and JAGES), and thus, results may be skewed through duplicate counting.
Conclusions and implications
Childhood health, childhood educational attainment, family socioeconomic and educational factors, childhood experiences, and childhood reading habits and social interactions were all linked to the risk of cognitive impairment and dementia in later life. To establish causal links between early-life risk factors and later cognitive impairment, further superior longitudinal studies are essential. Policymakers should prioritize early childhood development programs that combine health, nutrition, education, and social support to mitigate the incidence of dementia and cognitive impairment in later life. Over 60% of studies included in this review concentrated in a few wealthy nations (the US, China, and Japan), likely reflecting disparities in research capacity and funding priorities at the global level. It also raises concerns about whether the findings, which specific socioeconomic and cultural contexts may influence, can be generalized to other parts of the world, particularly those with fewer resources and different social structures. Future research should prioritize broader geographic inclusion to ensure a more comprehensive and equitable understanding of how childhood experiences influence dementia risk.
Supporting information
S2 Appendix. Systematic review screening process.
https://doi.org/10.1371/journal.pone.0311074.s002
(XLSX)
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