# paper.pdf ## Metadata - PDFFormatVersion=1.4 - Language=en-US - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - CreationDate=D:20260511062133+02'00' - Creator=Adobe InDesign 18.3 (Windows) - Custom.CrossMarkDomains[1]=springer.com - Custom.CrossMarkDomains[2]=springerlink.com - Custom.CrossmarkDomainExclusive=true - Custom.CrossmarkMajorVersionDate=2010-04-23 - Custom.doi=10.1186/s13293-026-00908-7 - ModDate=D:20260518115103+02'00' - Producer=Adobe PDF Library 17.0; modified using iText® 5.5.13.4 ©2000-2024 iText Group NV (SPRINGER SBM; licensed version) - Trapped=False - crossmark:crossmarkdomains=springer.comspringerlink.com - pdfx:crossmarkdomains=springer.comspringerlink.com ## Contents ### Page 1 © The Author(s) 2026. 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) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit. TheCreative Commons Public Domain Dedication waiver () applies to the data made availablein this article, unless otherwise stated in a credit line to the data. *Correspondence: Judy Pa Full list of author information is available at the end of the article Abstract Background Women have a greater lifetime risk of developing dementia. Despite clear sex differences, studiesinvestigating modifiable dementia risk factors often overlook differences between sexes and age. This study examinedsex and age differences in the prevalence of modifiable dementia risk factors and their associations with cognition. Methods Participants were from the Health and Retirement Study, a nationally representative cohort study. Thirteenrisk factors were examined, including education, hearing loss, cholesterol, depression, physical inactivity, diabetes,smoking, hypertension, obesity, excessive alcohol use, social isolation, poor vision, and poor sleep. A global cognitivesummary score was also examined. Chi-square and t-tests examined sex and age differences in prevalence; linearregression examined interactions between sex, age, and risk factors on cognition. Results This study included 17,182 participants with a mean age of 69.2 ± 10.6 years, 59.2% of which were women.Ten out of 13 risk factors had sex differences in prevalence. Women had higher prevalence of elevated cholesterol,depression, physical inactivity, smoking, poor vision, and poor sleep. Women also had fewer years of education. Menhad a higher prevalence of hearing loss, diabetes, and excessive alcohol use. Hearing loss, diabetes, and hypertensionwere associated with greater effects on cognitive performance in woman than men. BMI was negatively associatedwith cognitive performance in women compared to men in their 50s and 60s, but not at older ages. Education andcholesterol had stronger, positive associations with cognitive performance in women compared to men. Conclusions These data suggest that women’s greater risk of dementia may be due to a higher prevalence ofmultiple risk factors and stronger cognitive effects of risk factors. Results may inform future personalized preventionstrategies for dementia risk reduction, particularly in women. Plain english summary Women are more likely than men to develop dementia over their lifetime, but many studies do not examine howdementia risk factors differ by sex or age. This study investigated whether modifiable dementia risk factors aremore common in women or men and whether these risk factors differentially impact cognition by sex. Thirteenrisk factors linked to dementia were examined: education, hearing loss, cholesterol, depression, physical inactivity,diabetes, smoking, high blood pressure, obesity, alcohol use, social isolation, poor vision, and poor sleep. Women Sex differences in modifiable risk factorsof dementia and their associationswith cognition Megan C. Fitzhugh1,2 and Judy Pa1,2* Fitzhugh and Pa Biology of Sex Differences (2026) 17:110 [ ![http://crossmark.crossref.org/dialog/?doi=10.1186/s13293-026-00908-7&domain=pdf&date_stamp=2026-5-11]() ](http://crossmark.crossref.org/dialog/?doi=10.1186/s13293-026-00908-7&domain=pdf&date_stamp=2026-5-11) ![BioMed Central Logo]() ### Page 2 Background Alzheimer’s disease is a major public health prior-ity, affecting one in nine adults aged 65 and older inthe United States []. Of the seven million adults livingwith Alzheimer’s disease, nearly two-thirds are women[]. Not only is Alzheimer’s disease more prevalent inwomen, the lifetime risk of developing dementia due toAlzheimer’s disease is 20% for women and only 10% formen in the US [], with similar findings across Europe[]. However, other studies report no sex differences inthe incidence of Alzheimer’s disease [,], suggestingthat sex differences may depend on age or the cohortexamined. While on average, women live longer thanmen, differences in longevity do not fully explain thehigher prevalence and increased risk of Alzheimer’s dis-ease experienced by women []. It has been suggested that sex differences in Alzheim-er’s disease and related dementias may be explained, inpart, by differences in the influence of modifiable riskfactors. The Lancet Commission on Dementia Preven-tion, Intervention, and Care and others have identified14 risk factors that over the life course accumulate andcontribute to dementia risk [,]. If these risk factorsare mitigated or eliminated, it could reduce an estimated45% of dementia cases. The Lancet Commission furtheridentifies the period in the lifespan at which each riskfactor has its greatest effect on dementia risk, includ-ing early life (education), midlife, between the ages of 45and 65 (hearing loss, LDL cholesterol, depression, trau-matic brain injury, physical inactivity, smoking, diabetes,hypertension, obesity, and excessive alcohol use), or latelife, after age 65 (social isolation, air pollution, and visionloss). There is a growing recognition for the need to developrisk reduction approaches that target one or more modi-fiable risk factors of dementia, including interventionslike the US POINTER [], World-Wide FINGERS []and SMARRT [,] trials, and educational platformslike HALT-AD [] and Brain Health PRO [,]. How-ever, these efforts often do not consider sex as part of theindividualized intervention. Evidence of sex differencesacross numerous dementia risk factors and their impacton dementia risk is a small but growing body of research.Findings from observational studies show that womenand men express modifiable risk factors of dementia atdifferent rates. This work suggests that women experi-ence high cholesterol, physical inactivity, and depressionin greater numbers than men, more men experience dia-betes, hearing loss, and substance abuse (including smok-ing and alcohol), and sex differences in the prevalence ofhypertension varies by study [–]. It is a major chal-lenge to change behavior, particularly when asked tochange multiple behaviors. Therefore, it is critical thatwe identify which risk factors to target considering boththe individual’s sex and age in order to tailor our inter-ventions to the risk factors that not only have the high-est prevalence, but also the greatest potential impact oncognition. The purpose of this study was to conduct a comprehen-sive, secondary data analysis to identify sex and age dif-ferences in (1) the prevalence of modifiable risk factors ofdementia and (2) the association between each risk fac-tor and cognitive performance. This study included over17,000 participants who were 40 years or older at the2008 data collection wave of the Health and RetirementStudy. Thirteen modifiable risk factors were examined.We hypothesized that men would have a higher preva-lence in more risk factors compared to women. However,given women’s greater risk of developing dementia, wepredicted that the presence of a given risk factor wouldhave a greater effect on cognitive performance on womencompared to men. had a higher prevalence of more risk factors than men, including poor sleep, poor vision, physical inactivity,cholesterol, depression, smoking, and fewer years of education. Men were more likely to have hearing loss,diabetes, and high alcohol use. Several risk factors were linked to worse cognitive performance in women thanmen, including hearing loss, diabetes, hypertension, and obesity. However, more years of education was associatedwith better cognition in women compared to men. These findings suggest that women’s higher dementia risk mayreflect both greater exposure to risk factors and stronger negative effects of these risk factors on cognition. Highlights - • Women had higher prevalence in 7 of 13 examined modifiable risk factors. - • Men had higher prevalence in only 3 of the 13 risk factors. - • 3 risk factors (hearing loss, diabetes, and hypertension) had larger, negative effects on cognition in womencompared to men. - • 2 risk factors (cholesterol and education) had larger, positive effects on cognition in women compared to men. Keywords Sex differences, Modifiable risk factors, Cognition, Prevalence, Dementia ### Page 3 Methods Study population The Health and Retirement Study is a nationally rep-resentative, longitudinal study of adults in the UnitedStates aged 50 years and older, and their spouses (of anyage), at the time of recruitment. The study began in 1992and collects, in part, comprehensive self-report question-naires on demographics, health status, functional activi-ties, cognition, occupation and financial status every twoyears. This study used data from the 2008 collection wavefrom participants who were 40 years in age and older. Itshould be noted that beginning in 2006, participants didnot complete all questionnaires and assessments at everystudy wave. Instead, participants were split into twogroups and alternated in-depth, in-person data collectionby study wave, such that at any study wave only half ofthe sample completed all assessments []. Consent statement Participants and their informants provided writteninformed consent to participate. The study protocols forthe Health and Retirement Study and Harmonized Cog-nitive Assessment Protocol were approved by the Univer-sity of Michigan Institutional Review Board. Risk factors Information on 12 modifiable risk factors from the14 identified in the Lancet Commission 2024 reportwere available within the dataset []. These risk factorsincluded years of education, hearing loss, total choles-terol (as a proxy for LDL cholesterol), depression, physi-cal inactivity, diabetes, smoking, hypertension, obesity,excessive alcohol use, social isolation, and poor vision.The self-report questionnaires did not include queriesfor two of the risk factors identified by the Lancet Com-mission: traumatic brain injury and air pollution. Weincluded poor sleep as a risk factor because it has beenrepeatedly recognized as a potential risk factor in theLancet Commission Reports, but currently has insuf-ficient evidence to include in their models [,]. InAdditional File 1, we describe how these 13 total risk fac-tors were operationalized from self-report questionnairesor from health data for our study. Briefly, 10 of the 13 riskfactors were dichotomized into “Yes, presence of risk fac-tor” or “No, absence of risk factor” from questionnaires,while years of education, total cholesterol, and obesity(calculated as body mass index (BMI)) were left as con-tinuous variables. To assess sex differences in the influence of mul-tiple risk factors on cognitive performance, two differ-ent composite scores were computed. The first summedthe presence (Yes = 1, No = 0) of each risk factor, for atotal possible composite score of 13. The three continu-ous risk factors were binarized such that less than a highschool education, total cholesterol levels greater than orequal to 200 mg/dL, and BMI greater than or equal to 30were coded as 1 (Yes, presence of risk factor), with othervalues coded 0 (No, absence of risk factor). The secondcomposite adjusted for the proportion of variance sharedbetween risk factors using the adjusted population attrib-utable fraction (PAF) for each risk factor []. Adjustedrisk was calculated by multiplying the PAF of a given riskfactor by the risk factor presence (1 = Yes, 0 = No), divid-ing by the total PAF across all risk factors, and summingacross risk factors for a total possible score of 1. Whilethe Lancet Commission on Dementia Prevention iden-tifies an overall PAF across all risk factors of 45%, sincewe could not operationalize TBI and air pollution in thisstudy, our total PAF was 39%. Sleep was not included asrisk factor in these analyses because it does not yet havea PAF score. Cognitive performance Cognitive performance was assessed using a shortenedversion of the Telephone Interview for Cognitive Status(TICS []). This assessment is a brief test of global men-tal status and includes a 10-word immediate and delayedrecall, serial 7 subtractions, and backwards counting from20. A summary score reflecting performance on each testwas previously created by the Health and RetirementStudy team. The score was calculated as follows: 10 totalpoints for immediate word recall, 10 points for delayedword recall, five total points for serial 7 s, and up to twototal points for backwards counting (two points for cor-rect counting on the first attempt, one point for correctcounting on the second attempt, or no points for incor-rectly counting on the first and second attempts), for atotal score of 27 points []. This summary score is theonly cognitive performance score assessed in the entireHealth and Retirement Study sample, which allowed alarge sample size for our scoping assessment of severalrisk factors. The TICS has been compared against com-prehensive neuropsychological batteries and is effectiveat categorizing cognitive impairment and dementia fromthose who are cognitively unimpaired [–]. Statistical analysis To determine if the prevalence or mean value of the riskfactors differed by sex, Chi-square tests (for dichotomousrisk factors) and Student’s t-tests (for continuous risk fac-tors) were used. Sex differences were examined withinthe whole sample and within age groups. An age groupvariable was created to separate participants into a lessthan 65 years in age group, or a 65 years in age or oldergroup, for comparison to the simple effects performedfollowing significant interactions in linear regressionmodels (see below). The threshold of 65 years was chosento reflect the inflection point between midlife and late life ### Page 4 described in the Lancet Commission on Dementia Pre-vention. Significance was set at p <.05 with Bonferronicorrections for multiple comparisons across all tests. Parallel linear regression models were used to examinethe three-way interaction of risk factor, sex, and age onthe TICS cognitive summary score. Significant three-wayinteractions were followed by simple effects (or simpleslopes for continuous variables) between risk factor (yesvs. no, the reference) and sex, at three representativeages, 55, 65, and 75 years. These representative ages wereselected to reflect the Lancet Commission on DementiaPrevention’s inflection point between midlife and latelife, 65 years, and 10 years before and after this point. Forrisk factors with no significant three-way interactions,models were reduced to include only two-way interac-tions between risk factor and sex, and were followed upby simple effects or slopes of the risk factor within menand women separately. Parallel models were also runusing the unadjusted and adjusted risk factor compositescores as predictors. Significance for the three- and two-way model interactions was set at p <.05. Significance forthe simple effects was set at p <.05 with Bonferroni cor-rections for multiple comparisons within each risk factor. Since many of the predictors in our analyses are com-monly used as covariates in investigations of cognition inolder adults (e.g., age, sex, education, hypertension, etc.),the primary analyses were performed without covariates.Secondary analyses were then performed that includedyears of education (except for the model where educationis the risk factor of interest, which was excluded from thesecondary analyses). Significance for tests in the second-ary analyses was set at p <.05, uncorrected for multiplecomparisons. Chi-square tests and t-tests for prevalence compari-sons were performed using SPSS (IBM Corp., release2020, IBM SPSS Statistics for Macintosh, version 28.0.1).Linear regressions were conducted using R (v4.4.1) andRStudio (v2026.01.0) via the {lm} package. Significantinteractions were decomposed using {emmeans} and{emtrends} packages. Results Cohort demographics This study included 17,182 participants who were 40years of age or older at the 2008 Health and RetirementStudy data collection wave (see Fig. for missing dataand total sample size for each risk factor). This included7,009 men (40.8%) and 10,173 women (59.2%). The mean(SD) age was 69.2 (10.7) years, and the mean (SD) totalyears of education was 12.4 (3.3). Table includes theprevalence (or mean) of each risk factor for the entirestudy sample and stratified by sex. Sex differences in risk factor prevalence Complete statistics for comparisons in the prevalence (ormean) of each risk factor between women and men inthe entire sample and within each age group are reportedin Additional File 2. To summarize these findings (seeFig.), women exhibited greater prevalence of seven riskfactors compared to men. In general, women had slightlyfewer years of education, elevated total cholesterol, anda higher prevalence of depression, physical inactivity,smoking, poor vision, and poor sleep compared to men.Conversely, men had higher prevalence of three risk fac-tors compared to women, including hearing loss, diabe-tes, and excessive alcohol use. One risk factor showedmixed sex differences, depending on the age group. Theprevalence of hypertension was slightly higher in menbetween the ages of 40 to 64 (though not statisticallysignificant after correction for multiple comparisons),but after age 65, the prevalence was significantly greaterin women. Lastly, there were no sex differences in meanBMI nor in the prevalence of social isolation. Sex differences in associations between risk factors andcognitive performance Sex and age differences in the associations between eachof the 13 risk factors and the cognitive summary scorewere examined. Complete model statistics of all three-way interactions of risk factor, sex, and age on cognition,and their simple effects, are reported in Additional File2 Table 1). There was a significant three-way interac-tion between BMI, sex, and age (β = −0.005, SE = 0.002,p =.011). Regression coefficients represent the changein the cognitive summary score (range 0–27) associ-ated with a one-unit increase in BMI. In women, therewere negative associations between BMI and cognitionat ages 55 and 65 (β = −0.05, SE = 0.02, p <.001 and β =−0.03, SE = 0.01, p =.002, respectively). Conversely, menshowed positive associations between BMI and cogni-tion (β = 0.07, SE = 0.03, p =.015 and β = 0.04, SE = 0.02, p=.012, respectively). Pairwise comparisons showed thatthese associations were significantly different betweenwomen and men (β = −0.12, SE = 0.03, p <.001 at age55 and β = −0.08, SE = 0.02, p <.001 at age 65) (Fig.).However, the associations between BMI and cognitiondid not differ by sex at age 75 (β = −0.03, SE = 0.02, p=.256). No other risk factor showed significant three-wayinteractions. In reduced models, several risk factors exhibited signif-icant two-way interactions between risk factor and sex,with greater effects on cognition in women compared tomen (Fig., complete model statistics of two-way inter-actions and simple effects in Additional File 2, Table 2).Regression coefficients in these models represent thechange in the cognitive summary score (range 0–27) inthe group with the risk factor compared to the group ### Page 5 without the risk factor, or per one-unit increase in con-tinuous risk factors. The presence of hearing loss had agreater, negative effect on cognition in women (β = −1.23,SE = 0.09, p <.001) compared to men (β = −0.65, SE = 0.11,p <.001; women vs. men β = 0.57, SE = 0.14, p <.001). Dia-betes also had a greater, negative effect on cognition inwomen (β = −1.71, SE = 0.11, p <.001) compared to men(β = − 0.59, SE = 0.13, p <.001; women vs. men β = 1.12,SE = 0.16, p <.001). Similarly, hypertension had a greater,negative effect on cognition in women (β = −1.06,SE = 0.09, p <.001) than men (β = −0.76, SE = 0.11, p <.001;women vs. men β = 0.29, SE = 0.14, p =.038). Conversely,there was a positive association between level of educa-tion and cognitive scores in both sexes (women: β = 0.63,SE = 0.01, p <.001; men: β = 0.55, SE = 0.01, p <.001),yet the association was stronger in women (women vs.men (the reference group) β = −0.08, SE = 0.02, p <.001).The association between total cholesterol and cogni-tion also differed by sex (β = −0.01, SE < 0.01, p =.049),with women showing a significant, positive association ### Page 6 (β = 0.01, SE < 0.01, p =.005) and men showing no signifi-cant association (β = < −0.01, SE < 0.01, p =.735). While there was not a significant three-way interactionbetween the composite risk score, sex, and age on cogni-tion, there was a significant two-way interaction betweenthe composite risk score and sex on cognition (β = 0.11,SE = 0.04, p =.005; see Tables and 2 in Additional File2). Both women (β = −0.70, SE = 0.02, p <.001) and men(β = −0.59, SE = 0.03, p <.001) showed negative associa-tions between number of risk factors and cognition, butthe decrease in cognition with increasing number of riskfactors was steeper in women (Fig., last panel). Therewere no significant interactions between composite riskscore adjusted for shared variance and sex on cognition(see Tables 1 and 2 in Additional File 2). Secondary analyses were performed such that thethree-way interactions of risk factor, age, and sex on thecognitive summary score, and the reduced models withtwo-way interactions of risk factor and sex, includededucation as a covariate. The results in these analysesfollowed the same trends as the primary analysis. Com-plete results are reported in Additional File 2 (Tables 3and 4). Discussion In a representative cohort of older adults in the UnitedStates, we examined 13 modifiable risk factors of demen-tia and identified sex differences in risk factor preva-lence and in their associations with cognition. Contraryto our hypothesis, our findings showed that risk factorprevalence was greater among women compared to men.Women had higher rates of depression, physical inac-tivity, smoking, poor vision, and poor sleep comparedto men, as well as lower levels of education and highertotal cholesterol levels. Comparatively, men had higherrates of only three risk factors: hearing loss, diabetes, andexcessive alcohol use. The associations between risk fac-tors and cognitive performance differed by sex. Womengenerally had higher cognitive scores than men in theabsence of a given risk factor, but the presence of risk fac-tors was associated with greater reductions in cognitive | Table 1 Prevalence (or mean) of 13 modifiable lifestyle risk factors of dementia | | - | | All(N = 17,182) | Women(n = 10,173) | Men(n = 7,009) | Sex Difference | | Age (Mean (SD), years)(n = 17,182) | 69.2 (10.7) | 69.1 (11.1) | 69.4 (9.9) | p <.001* | | Education (Mean (SD), years)(n = 17,017; w = 10,092; m = 6,925) | 12.4 (3.3) | 12.3 (3.1) | 12.6 (3.5) | p <.001* | | Poor Hearing No. (% Yes)(n = 17,171) | 9,605 (56%) | 5,105 (50%) | 4,500 (64%) | p <.001* | | Total Cholesterol (Mean (SD))(n = 6,018; w = 3,625; m = 2,393) | 201.0 (42.0) | 207.1 (42.5) | 191.7 (39.3) | p <.001* | | Depression No. (% Yes)(n = 15,970) | 2,222 (14) | 1,623 (17%) | 599 (9%) | p <.001* | | Physical Inactivity No. (% Yes)(n = 17,182) | 7,821 (46) | 4,908 (48%) | 2,913 (42%) | p <.001* | | Diabetes No. (% Yes)(n = 17,060) | 3,767 (22) | 2,087 (21%) | 1,680 (24%) | p <.001* | | Current Smoker No. (% Yes)(n = 9,688) | 2,221 (23) | 1,278 (26%) | 943 (20%) | p <.001* | | Hypertension No. (% Yes)(n = 16,943) | 10,383 (61) | 6,164 (62%) | 4,219 (61%) | p =.511 | | BMI (Mean (SD))(n = 6,432; w = 3,838; m = 2,594) | 29.3 (6.1) | 29.4 (6.7) | 29.2 (5.1) | p =.226 | | Alcohol Use No. (% Yes)(n = 5,581) | 968 (17) | 313 (12%) | 655 (22%) | p <.001* | | Social Isolation No. (% Yes)(n = 4,708) | 644 (14) | 407 (15%) | 237 (12%) | p =.025 | | Poor Vision No. (% Yes)(n = 14,007) | 4,034 (29) | 2,495 (30%) | 1,539 (28%) | p =.009 | | Poor Sleep No. (% Yes)(n = 17,113) | 7,379 (43) | 4,579 (45%) | 2,800 (40%) | p <.001* | | The prevalence reported as percent of the available sample (or mean) for each risk factor is shown for the entire study sample and within men and women. Thesample size available for each risk factor is also provided, as not all participants were asked to partake in each study wave, per the Health and Retirement Studydesign, and not all participants chose to respond to each question. The p-values are shown unadjusted, but we indicate with a * which results survive correctionfor multiple comparisons using the Bonferroni method (13 risk factors * 3 tests = 39 separate tests, adjusted alpha 0.05/39=0.001; see Additional File 2 for completestatistics) | | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | ### Page 7 scores in women than in men. Specifically, hearing loss,diabetes, hypertension, and BMI, had larger, negativeeffects on cognition in women compared to men. Whiletwo risk factors, years of education and total cholesterol,showed positive associations with cognition, such thathigher levels were correlated with greater cognition. Theaccumulation of multiple risk factors was also associatedwith worse cognition in women compared to men. Theabsence of significant 3-way interactions for most riskfactors suggests that sex differences in the association ### Page 8 between these risk factors and cognition were relativelyconsistent across the age groups examined. Together, ourstudy suggests that risk factors of dementia may influencecognition to a greater degree in women than in men. As described earlier, the previous literature shows theprevalence of modifiable risk factors of dementia dif-fer between women and men. The literature consistentlyreports that women are more likely to experience lowerlevels of education, high cholesterol, physical inactivity,and depression, while more men experience diabetes,hearing loss, and substance abuse [–]. Our studyextends our understanding of sex differences to includea greater prevalence of poor visual health and poor self-reported sleep quality in women compared to men. Pre-vious work further shows that many of these risk factors,like hypertension, increase dementia risk to a greaterdegree in women compared to men [,], supporting ### Page 9 our findings that the presence of risk factors reduce cog-nitive performance more in women than men. Across the literature and within our study, hyperten-sion is consistently associated with poorer cognitiveoutcomes in women compared to men. We found thathypertension had a stronger, negative association withcognitive performance in women. Several empirical stud-ies and systematic reviews report that midlife hyperten-sion is associated with greater cognitive decline and riskof dementia in women than men [–]. Recent com-prehensive reviews suggests that women may be moreprone to hypertension and other cardiovascular condi-tions due to experiencing pregnancy complications (i.e.,gestational hypertension), hormonal shifts associatedwith menopause, and having a higher prevalence of cere-bral small vessel disease, though the mechanisms link-ing these events with increased hypertension risk are notwell-understood [,]. Other co-morbidities of hypertension similarly affectedwomen to a greater degree than men. Despite being moreprevalent in men, diabetes was associated with a greaterreduction in cognitive performance in women comparedto men. Other recent longitudinal studies also reportsteeper declines in cognition over time in women com-pared to men with diabetes [,]. Hearing loss wasalso associated with a greater reduction in cognition inwomen compared to men, despite being more preva-lent in men. Conversely, mean BMI values were roughlyequal between men and women, but exerted sex- andage-specific effects on cognition. Higher BMI values wereassociated with poorer cognitive performance in womenat ages 55 and 65, yet had potentially positive effects oncognition in men. The literature on BMI and cognition is mixed, whichcomplicates interpretation of the sex differences observedin our results. Some studies suggest that higher BMI mayhave stronger adverse cognitive consequences for womenthan for men earlier in adulthood. For example, one studyreported that higher BMI in midlife was associated withpoorer cognitive performance in women but not men[], and another found that elevated BMI earlier in lifewas associated with increased Alzheimer’s disease risk inwomen only []. One potential explanation is that obe-sity and related metabolic conditions may exert greaterdetrimental cognitive effects in women, particularly dur-ing midlife and early older adulthood when hormonaland metabolic changes associated with the menopausaltransition occur. At the same time, the age-related pat-tern observed in our study is consistent with prior workdescribing the “obesity paradox,” whereby obesity inmidlife is associated with increased dementia risk, whilehigher BMI in later life is associated with lower dementiarisk [,]. In this context, higher body weight in laterolder age may confer similar protective associations forboth women and men. These findings highlight the needfor further research on sex differences in vascular andmetabolic risk factors, and their relationships with hor-monal changes through the lifespan, in order to bettermitigate the influence these risk factors have on cogni-tion and dementia risk, particularly in women. Limitations While the Health and Retirement Study collected a widearray of variables, many risk factors of interest couldonly be obtained from a single or small number of avail-able variables. For example, there were only self-reportedassessments of some health conditions and behaviors,like hearing loss and physical activity. Due to the scopeof data collected by the Health and Retirement Study, theuse of more extensive and validated questionnaires orclinical measures was likely not feasible. Future studieson risk factors should aim to use variables derived fromvalidated questionnaires or health records, to supplementself-reported information from single items. The way inwhich some variables were operationalized, such as bina-rizing an ordinal response, loses more nuanced informa-tion available in the range of the response. However, thegoal of this study was to examine prevalence and impactof the presence of several risk factors, therefore, binariz-ing risk factors into “yes, present” and “no, not present”was necessary. While the goal of this study was to assess awide range of risk factors, future studies should also seekto examine these relationships controlling for additional,explanatory covariates, such as socioeconomic status.Lastly, it is possible that the sex differences observed inthis study are at least partially explained by a survival biasin women, wherein men in poor health and with poorercognitive performance withdraw from the study ingreater numbers than women. However, the proportionof men to women in the sample remained consistent untilages 90 and older, suggesting that survival bias was lesslikely to play a major role in our findings. Perspectives and Significance It is important to distinguish between sex differences inthe prevalence of risk factors and their impact on cogni-tion, because prevalence and impact may not correspond.Targeting only the most prevalent risk factors withineach sex may overlook certain risk factors that moremarkedly influence cognitive decline. For instance, hear-ing loss is more prevalent in men but impacted cogni-tion to a greater degree in women. Similarly, other workhas shown that hearing loss in women is associated witha greater risk of dementia compared to men []. Riskreduction strategies of dementia should be sure to priori-tize risk factors with the strongest association with cog-nitive outcomes in each sex, and not merely those thatare most prevalent. ### Page 10 Conclusions In summary, our study suggests that women may beat greater risk of dementia because they experience agreater number of risk factors, and because these riskfactors reduce cognition to a greater degree than men.These findings help to provide personalized, sex-basedguidance for interventions on risk reduction. Our studysuggests that women have a greater number of risk fac-tors that can be targeted to mitigate their risk of demen-tia. Women particularly may want to seek treatments ormanagement for hearing loss, bouts of insomnia, hyper-tension, diabetes, and excess weight, particularly inmidlife and early older adulthood. Continued researchis needed to fully understand sex differences in demen-tia so that we can develop better lifestyle interventiondesigns and reduce both the prevalence and impact of thedisease. Supplementary Information The online version contains supplementary material available at. Supplementary Material 1 Supplementary Material 2 Acknowledgements The Health and Retirement Study (U01AG009740) and the HarmonizedCognitive Assessment Protocol (U01AG058499) are sponsored by the NationalInstitute on Aging and conducted by the University of Michigan. Part ofthis work was previously presented at the 2025 Alzheimer’s AssociationInternational Conference () . Author contributions MCF made significant contributions to the conception and design of thework, the acquisition, analysis, and interpretation of the data, and drafted andrevised the manuscript. JP made significant contributions to the conceptionand design of the work, contributed to the interpretation of the data, andrevised the manuscript. All authors read and approved the final manuscript. Funding This work was supported by the National Institute on Aging (RF1AG088811,PI: J.P.) and the Alzheimer’s Association (SAGA23-1141238, PI: J.P.). The fundingsources were not involved in the study design, analyses, or interpretations. Data availability The dataset supporting the conclusions of this article are available from theHeath and Retirement Study ( [/ ] ( h t t p s : / h r s. i s r. u m i c h .e d u ) ) . Declarations Ethics approval and consent to participate Participants and their informants provided written informed consent toparticipate. The study protocols for the Health and Retirement Study andHarmonized Cognitive Assessment Protocol were approved by the Universityof Michigan Institutional Review Board. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details 1Department of Neurosciences, University of California, 9500 GilmanDrive, MC 0949, La Jolla, San Diego, CA 92093-0949, USA 2Alzheimer’s Disease Cooperative Study (ADCS), University of California,La Jolla, San Diego, CA 92093, USA Received: 15 January 2026 / Accepted: 14 April 2026 References 1. Alzheimer’s A. 2024 Alzheimer’s disease facts and figures. AlzheimersDement. 2024;20(5):3708–821..13809 PubMedPMID: 38689398; PubMed Central PMCID: PMC11095490. 2. Rajan KB, Weuve J, Barnes LL, McAninch EA, Wilson RS, Evans DA. Populationestimate of people with clinical Alzheimer’s disease and mild cogni-tive impairment in the United States (2020–2060). Alzheimers Dement.2021;17(12):1966–75.. 3. Chêne G, Beiser A, Au R, Preis SR, Wolf PA, Dufouil C, et al. Gender andincidence of dementia in the Framingham Heart Study from mid-adult life.Alzheimer’s Dement. 2015;11(3):310–20.. 4. Niu H, Álvarez-Álvarez I, Guillén-Grima F, Aguinaga-Ontoso I. Prevalence andincidence of Alzheimer’s disease in Europe: a meta-analysis. Neurología (Eng-lish Edition). 2017;32(8):523–32.. 5. Hebert LE, Scherr PA, McCann JJ, Beckett LA, Evans DA. Is the risk of develop-ing Alzheimer’s disease greater for women than for men? Am J Epidemiol.2001;153(2):132–6. 6. Kawas C, Gray S, Brookmeyer R, Fozard J, Zonderman A. Age-specificincidence rates of Alzheimer’s disease: the Baltimore Longitudinal Study ofAging. Neurology. 2000;54(11):2072–7. 7. Snyder HM, Asthana S, Bain L, Brinton R, Craft S, Dubal DB, et al. Sex biologycontributions to vulnerability to Alzheimer’s disease: A think tank convenedby the Women’s Alzheimer’s Research Initiative. Alzheimers Dement.2016;12(11):1186–96.. .004 PubMedPMID: 27692800. 8. Livingston G, Huntley J, Liu KY, Costafreda SG, Selbæk G, Alladi S, et al.Dementia prevention, intervention, and care: 2024 report of the Lancetstanding Commission. Lancet. 2024;404(10452):572–628.. 24)01296-0 PubMed PMID: 39096926. 9. Nianogo RA, Rosenwohl-Mack A, Yaffe K, Carrasco A, Hoffmann CM, BarnesDE. Risk factors associated with Alzheimer disease and related dementias bysex and race and ethnicity in the US. JAMA Neurol. 2022;79(6):584–91.. 10. Baker LD, Espeland MA, Whitmer RA, Snyder HM, Leng X, Lovato L, et al. Struc-tured vs self-guided multidomain lifestyle interventions for global cognitivefunction: the US POINTER randomized clinical trial. JAMA. 2025;334(8):681–91.. 11. Rosenberg A, Mangialasche F, Ngandu T, Solomon A, Kivipelto M. Multido-main interventions to prevent cognitive impairment, Alzheimer’s disease, anddementia: from FINGER to world-wide FINGERS. J Prev Alzheimer’s Disease.2020;7(1):29–36.. 12. Barnes DE, Balderson BH, Shulman L, Rosenberg DE, Matson TE, Mettert KD,et al. The systematic multi-domain Alzheimer’s risk reduction trial (SMARRT)intervention: a personalized approach to dementia risk reduction. J Alzheim-ers Dis. 2024;102(4):1121–32.. 13. Yaffe K, Vittinghoff E, Dublin S, Peltz CB, Fleckenstein LE, Rosenberg DE, et al.Effect of personalized risk-reduction strategies on cognition and demen-tia risk profile among older adults: the SMARRT randomized clinical trial.JAMA Intern Med. 2024;184(1):54–62.. (PubMed PMID: 38010725; PubMed Central PMCID:PMC10682943). 14. Moukarzel S, Zlatar ZZ, Hartman SJ, Lomas D, Feldman HH, Banks SJ. Develop-ing the healthy actions and lifestyles to avoid dementia or Hispanos y el ALToa la Demencia program. Alzheimer’s & Dementia: Translational Research &Clinical Interventions. 2024;10(1):e12457.. 15. Belleville S, Chertkow H, Feldman HH, Nygaard HB, Montero-Odasso M,Anderson ND, et al. Brain health PRO: an interactive, online, educationalprogram for dementia. Alzheimers Dement. 2023;19(S23):e075156.. ### Page 11 16. Belleville S, Anderson ND, Bherer L, Camicioli R, Carrier J, Chan S, et al. Brainhealth PRO/santé cerveau PRO: the development of a web-based programfor dementia literacy and risk factor reduction. J Prev Alzheimers Dis.2025;100134.. 17. Anstey KJ, Peters R, Mortby ME, Kiely KM, Eramudugolla R, Cherbuin N, et al.Association of sex differences in dementia risk factors with sex differencesin memory decline in a population-based cohort spanning 20–76 years. SciRep. 2021;11(1):7710.. 18. Gong J, Harris K, Peters SAE, Woodward M. Sex differences in the associationbetween major cardiovascular risk factors in midlife and dementia: a cohortstudy using data from the UK Biobank. BMC Med. 2021;19(1):110.. 19. Gong J, Harris K, Lipnicki DM, Castro-Costa E, Lima‐Costa MF, Diniz BS, et al.Sex differences in dementia risk and risk factors: individual‐participant dataanalysis using 21 cohorts across six continents from the COSMIC consortium.Alzheimers Dement. 2023;alz.12962.. 20. LaPlume AA, McKetton L, Anderson ND, Troyer AK. Sex differences andmodifiable dementia risk factors synergistically influence memory over theadult lifespan. Alzheimer’s & Dementia: Diagnosis, Assessment & DiseaseMonitoring. 2022;14(1):e12301.. 21. Geraets AFJ, Leist AK. Sex/gender and socioeconomic differences in modifi-able risk factors for dementia. Sci Rep. 2023;13(1):80.. 22. Son S, Speechley M, Zou GY, Kivipelto M, Mangialasche F, Feldman HH, etal. Potentially modifiable dementia risk factors in Canada: an analysis ofCanadian Longitudinal Study on Aging with a multi-country comparison. TheJournal of Prevention of Alzheimer’s Disease. 2024;11(5):1490–9.. 23. Sonnega A, Institute for Social Research. Using Health and Retirement StudyData: A Guide for New USers. In. University of Michigan, ; 2025. Available from: 24. Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al.Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673–734.. 25. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al.Dementia prevention, intervention, and care: 2020 report of the Lancet Com-mission. Lancet. 2020.. 26. Brandt J, Spencer M, Folstein M, others. The telephone interview for cognitivestatus. Neuropsychiatry Neuropsychol Behav Neurol. 1988;1(2):111–7. 27. Crimmins EM, Kim JK, Langa KM, Weir DR. Assessment of cognition usingsurveys and neuropsychological assessment: the health and retirement studyand the aging, demographics, and memory study. Journals Gerontology: SerB. 2011;66B(suppl1):i162-71.. 28. Manly JJ, Schupf N, Stern Y, Brickman AM, Tang MX, Mayeux R. Telephone-based identification of mild cognitive impairment and dementia in a multi-cultural cohort. Arch Neurol. 2011;68(5):607–14.. 29. Chappelle SD, Gigliotti C, Léger GC, Peavy GM, Jacobs DM, Banks SJ, et al.Comparison of the telephone-Montreal Cognitive Assessment (T-MoCA) andTelephone Interview for Cognitive Status (TICS) as screening tests for earlyAlzheimer’s disease. Alzheimers Dement. 2023;19(10):4599–608.. 30. Cook SE, Marsiske M, McCoy KJM. The use of the modified telephone inter-view for cognitive status (TICS-M) in the detection of amnestic mild cognitiveimpairment. J Geriatr Psychiatry Neurol. 2009;22(2):103–9.. 31. Rotstein A, Kodesh A, Schnaider Beeri M, Levine SZ. Sex differences indementia risk: considering underlying medical conditions. Alz Res Ther.2025;7(1):219.. 32. Blanken AE, Nation DA. Does gender influence the relationship between highblood pressure and dementia? Highlighting areas for further investigation. JAlzheimer’s Disease. 2020;78(1):23–48.. 33. Gilsanz P, Mayeda ER, Glymour MM, Quesenberry CP, Mungas DM, DeCarli C,et al. Female sex, early-onset hypertension, and risk of dementia. Neurology.2017;31(18):1886–93.. 34. Laughlin GA, McEvoy LK, Von Mühlen D, Daniels LB, Kritz-Silverstein D, Berg-strom J, et al. Sex differences in the association of Framingham cardiac riskscore with cognitive decline in community-dwelling elders without clinicalheart disease. Psychosom Med. 2011;73(8):683–9.. 35. Huo N, Vemuri P, Graff-Radford J, Syrjanen J, Machulda M, Knopman DS, et al.Sex Differences in the Association Between Midlife Cardiovascular Conditionsor Risk Factors With Midlife Cognitive Decline. Neurology. 2022;98(6).. 36. Volgman AS, Bairey Merz CN, Aggarwal NT, Bittner V, Bunch TJ, Gorelick PB,et al. Sex differences in cardiovascular disease and cognitive impairment:another health disparity for women? J Am Heart Assoc. 2019;8(19):e013154.. 37. Kaur A, Ricciardelli S, Rajah N, Pilote L. Sex differences in the associationbetween hypertension, cerebral small vessel disease and cognitive decline: anarrative review. J Hypertens. 2025.. 38. Wood Alexander M, Paterson J, Arvanitakis Z, Black SE, Casaletto KB, ChristakisMK, et al. Cardiovascular contributions to dementia: examining sex differ-ences and female-specific factors. Alzheimers Dement. 2025;21(8):e70610.. 39. Palarino JV, Boardman JD, Rogers RG. Cognition and diabetes: examin-ing sex differences using a longitudinal sample of older adults. Res Aging.2023;45(2):161–72. 40. Verhagen C, Janssen J, Biessels GJ, Johansen OE, Exalto LG. Females with type2 diabetes are at higher risk for accelerated cognitive decline than males:CAROLINA-COGNITION study. Nutr Metab Cardiovasc Dis. 2022;32(2):355–64.. 41. Gwizdala KL, Bazzano LA, Carmichael OT, Newton RL. Greater BMI across thelifespan is associated with better midlife cognition: The Bogalusa Heart Study.Sci Rep. 2025;15(1):5336.. 42. Chen YC, Chen TF, Yip PK, Hu CY, Chu YM, Chen JH. Body mass index (BMI) atan early age and the risk of dementia. Arch Gerontol Geriatr. 2010;50:S48-52.. 43. Li J, Joshi P, Ang TFA, Liu C, Auerbach S, Devine S, et al. Mid- to late-life bodymass index and dementia risk: 38 years of follow-up of the FraminghamStudy. Am J Epidemiol. 2021;190(12):2503–10.. 44. Fitzpatrick AL, Kuller LH, Lopez OL, Diehr P, O’Meara ES, Longstreth WT Jr, et al.Midlife and late-life obesity and the risk of dementia: Cardiovascular HealthStudy. Arch Neurol. 2009;66(3):336–42.. 45. Fitzhugh MC, Pa J. Women with hearing loss show increased dementia riskand brain atrophy. Alzheimer’s & Dementia: Diagnosis, Assessment & DiseaseMonitoring. 2023;15(4):e12499.. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.