Abstract
BACKGROUND
Evidence for the effect of early menopause on cognition among older women is not consistent and is scant among the Indian population.
METHODS
We aimed to examine the effect of early menopause (≤45 years) on cognitive performance and brain morphology among older dementia‐free females of the TLSA cohort using a multiple linear regression analysis.
RESULTS
In a sample of 528 women, 144 (27%) had early menopause. The linear regression analysis showed that women with early menopause performed poorly in cognition and had lesser total gray matter volume [β = −11973.94, p = 0.033], left middle frontal [β = −353.14, p = 0.033], and left superior frontal [β = −460.97, p < 0.026] volume.
CONCLUSION
Dementia‐free women with early menopause had poorer cognition, lower total gray matter, and frontal lobe. More research is needed to explore the link between earlier menopause and cognitive decline and develop ways to address it.
Highlights
Evidence on the effect of early menopause on brain morphology is inconsistent and scant in low and middle‐income countries, such as India.
In a cohort of dementia‐free individuals in urban Bangalore, we observed that participants with early menopause had significantly lower cognitive performance and lower total gray matter and frontal lobe volume.
We recommend increasing awareness of this fact among the medical community and the general public. There is an urgent need to explore the underlying biological mechanism and to discover effective interventions to mitigate the effect.
Keywords: cognition, dementia, Indian population, menopause, MRI
1. BACKGROUND
Dementia is a clinical syndrome, characterized by loss of cognitive abilities severe enough to interfere with daily life. 1 It is estimated in 2017 that around 50 million people suffer from dementia and that 60% of them lived in low‐ and middle‐income countries (LMIC). 2 The etiologic mechanisms have not yet been elucidated, and the available medical treatments are predominantly focused on slowing down the progress of the illness. The existing evidence indicates that reducing modifiable risk factors may help to prevent and control dementia. 3
Menopause is a routine, nonpathologic condition involving the permanent cessation of mense for at least 12 months. 4 It is characterized by a period of intense hormonal changes and symptomatic stress, which may be related to cognitive decline. Early menopause refers to menopause that occurs at or before age 45 years which can be spontaneous or surgically induced. 5 Several cohort studies from European countries and the United States have shown a possible association between early menopause and dementia. 6 , 7 , 8 A recent longitudinal study analyzed around 150,000 postmenopausal women from the UK Biobank data showed that women who have early menopause (<40 years) have a 71% increased likelihood of developing dementia when compared to women who attain menopause after 50 years. 9
A review article that included around 16 observational studies concluded that estrogen plays a neuroprotective role in women; however, the exact mechanism is unclear and needs further exploration. 10 Cognitive performance in postmenopausal women tended to be lower than that during pre‐ and perimenopausal women. The cognitive domains most likely to be affected are verbal delayed memory and executive function as it is assumed to be more sensitive to changing estrogen levels. A few studies have reported a gradient of Alzheimer's disease (AD) biomarkers such as including hypometabolism, increased amyloid‐beta (Aβ) deposition, and reduced gray and white matter volumes with the most remarkable abnormalities in menopausal women, an intermediate number of abnormalities in perimenopausal women, and the lowest number of abnormalities in premenopausal women. 11 , 12
On the contrary, the 10/66 population‐based study which included data from Latin America and China found no evidence of a relationship between early menopause and dementia. 13 A systematic review of 19,328 postmenopausal women from 13 observational studies (8 cross‐sectional and 5 longitudinal) concluded that definitive evidence linking early menopause and dementia is lacking because of methodological issues. One such issue is a lack of consensus on the cutoff age of menopause, some studies have used 50 years and others have used 45 years. 14 We addressed this issue in our paper by taking 45 years as the cutoff as defined by the North American Menopause Society. 5 Moreover, the available literature on the effect of early menopause and cognitive decline is not homogenous and is mainly restricted to the Western population; therefore, we have designed this study to fill this lacunae.
RESEARCH IN CONTEXT
Systematic review: We searched PubMed using the search terms (“dementia” or “Alzheimer” or “cognition”) AND (“early” or “earlier” or “premature”) AND (“menopause” or “menopausal”) in the title and abstract, up to October 10, 2023. The evidence for an association between early menopause and brain structure is inconsistent and scant among the Indian population.
Interpretation: In 528 dementia‐free women, we found that subjects with early menopause had significantly lower cognitive performance across all the cognitive domains assessed and had significantly lower total gray matter volume as well as frontal and cingulate volumes.
Future directions: Further research is needed to examine the pathophysiological effects of early menopause on cognition.
Tata Longitudinal Study of Aging (TLSA) is an ongoing, large‐scale, prospective, population‐based cohort study conducted in the urban metropolitan city of Bangalore, India. 15 This cohort study is designed to identify risk and protective factors for dementia and related disorders by carrying out periodic, multimodal assessments (clinical, cognitive, biochemical, genetic, and neuroimaging) on subjects of both genders aged 45 years and older and following their trajectories of cognitive aging. In this paper, we aimed to examine the effect of early menopause on global cognition as well as in various cognitive domains and magnetic resonance imaging (MRI) brain volumes among aging elderly urban women of the TLSA cohort.
2. METHODS
2.1. Study setting and participants
The TLSA cohort comprises urban‐dwelling individuals aged 45 years and older recruited from urban Bangalore, the capital of Karnataka state in southern India. Participants are recruited into this cohort by convenient sampling (Figure 1). The current study is a cross‐sectional analysis of data from TLSA participants who completed their baseline study assessments from June 2015 to June 2023. The figure depicts that, at the time of analysis, 1403 participants had completed their baseline assessments, of which 528 postmenopausal women were included for the analysis, and the rest were excluded for reasons such as men (714) and premenopausal or menopause status was not available (161). These 528 postmenopausal women were grouped based on their age of attaining menopause as either early menopause (≤45 years) or normal menopause (>45 years).
FIGURE 1.
This figure depicts the selection of the sample used in this study.
2.2. Measurements
Study participants underwent detailed clinical proforma, anthropometric measurements, cognitive assessments, and laboratory investigations.
2.2.1. Age of attaining menopause
Participants were asked by trained clinicians (“How old were you when your periods stopped?” or “How old were you when you attained menopause?”) about the age at menopause at baseline. Based on the response, they were categorized into two groups: early menopause (≤45 years) or normal menopause (>45 years). Other related parameters such as the age of menarche, the age at which the first child was born, and the number of live births were obtained through a structured clinical proforma.
2.2.2. Cognitive performance
A thorough cognitive evaluation was performed by trained clinical psychologists using a completely digital neuropsychological battery, which includes global cognition, processing speed, working memory, auditory attention, verbal short‐term memory, and visuospatial skills. The Addenbrooke's Cognitive Evaluation (ACE) III total score was used as an indicator of global cognition, and its five domains‐attention, memory, verbal fluency, language, and visuospatial abilities were also examined. 16 ACE III has been validated in the Indian setting and has a sensitivity of 0.9 and 0.86 to identify dementia and mild cognitive impairment (MCI), respectively. 17 The ACE III covers most cognitive domains except for executive functioning, processing speed, and verbal memory, so we used the Digit Span Test (DST), Trail Making Test (TMT), and Modified Taylor's Complex Figure Drawing Test (MTCF) tests to cover these domains. 18 , 19 , 20 Apart from this battery, the Hindi Mental Status Examination (HMSE), 21 an Indian adaptation of the Mini‐Mental Status Examination (MMSE), and Digit Symbol Substitution Test (DSST) 22 were also used as a measure of global cognition. All the cognitive tests have been validated for the Indian population, 23 , 24 and further details of these tests are mentioned in the appendix.
2.2.3. Brain imaging
All brain imaging studies were conducted using a 3‐Tesla MRI system (Magnetom Prisma, Siemens) while participants lay supine. All the high‐resolution T1‐weighed images were analyzed to evaluate the brain volumes using FreeSurfer software (v 7.2.0) (http://surfer.nmr.mgh.harvard.edu/). This software employs a template‐driven methodology for volumetric and surface‐based segmentation, as described in prior publications. 25 , 26 We utilized the variable “Total Gray Matter Volume” to estimate gray matter volume. We calculated the frontal gyrus regions by combining the superior, middle, and inferior regions of interest (ROIs). Further details are described in the appendix section.
2.2.4. Assessment of covariates
Covariates such as literacy (years of education), age, marital status, diet, smoking status, and alcohol use were obtained using a structured clinical proforma. Socioeconomic status was measured using a modified Kuppuswamy scale, 27 the Global Physical Activity Questionnaire (GPAQ) 28 was used to obtain the status of physical activity, and body mass index (BMI) was used to classify obesity. We used the Geriatric Depression Scale 30 29 and Clinical Dementia Rating Scale 30 to ascertain the status of depression and MCI, respectively. MCI was diagnosed in subjects whose Clinical Dementia Rating (CDR) score was 0.5, as per the NIA‐AA (National Institute on Aging‐Alzheimer's Association) criteria, 2011. 30 Diagnosis of hypertension (HTN) and diabetes mellitus (DM) was based on American Heart Association and American Diabetes Association diagnostic criteria, respectively. 31 , 32 Diagnosis of HTN and DM was based on clinical interviews to determine if they had already been diagnosed, whenever participants were not aware of their diagnosis or unsure, we used blood pressure recordings (systolic > / = 140 mmHg or diastolic > / = 90 mmHg) measured on right upper limb in the supine position and fasting blood sugar levels (FBS) of more than 126 mg/dL to arrive at a diagnosis. Similarly, the diagnosis of dyslipidemia was based on clinical interviews to know if they had already been diagnosed, whenever participants were not aware of their diagnosis or unsure, we used fasting lipid profile (total cholesterol > 200 mg/dL or triglycerides ≥ 150 mg/dL, or high density lipoprotein [HDL] < 40 mg/dL or low density lipoprotein [LDL] > 100 mg/dL) to arrive at a diagnosis. Other clinical co‐morbidities such as cardiac illness and hypothyroidism were self‐reported. The Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) scores are calculated by assigning scores to participants risk factors [age(<47 years = 0, 47‐53 years = 3, >53 years = 4); education (> / = 10 years = 0, 7‐9 years = 2, 0‐6 years = 3); sex (female = 0, male = 1); systolic blood pressure (< / = 140 mmHg = 0, >140 mmHg = 2); body mass index (< / = 30 kg/m2 = 0, >30 mg/m2 = 2); total cholesterol (< / = 6.5 mmol/L = 0, >6.5 mmol/L = 2); physical activity (active = 0, inactive = 1)] and then totaling it. Scores range from 0 to 15. Scores less than 9 are considered low risk and > / = 9 are considered high risk. 33
Fasting blood samples were collected from the participants individually by visiting their homes. Collection of a 15 mL total volume of peripheral venous blood sample was performed by trained phlebotomists using serum vacutainers from fasting (overnight) participants, for detailed biochemical investigations. The measurement of glucose was carried out through the hexokinase technique, while the lipid parameters under study were determined using an enzymatic approach. Serum vitamin B12 was measured with an electro‐chemiluminescence method, homocysteine was determined with enzymatic methods in an autoanalyzer, and C‐reactive protein (CRP) was assessed with immunonephelometry. Genomic DNA was isolated from whole blood according to the manufacturer's protocol using a genomic DNA isolation kit (NucleoSpin Blood, Mid Kit for DNA from blood, MACHEREY‐NAGEL, GmbH, Germany). 50 ng of genomic DNA was used for apolipoprotein E (APOE) genotyping analysis. The polymerase chain reaction (PCR) was performed using standard conditions and the amplified PCR products were sequenced by Sanger's sequencing method. After DNA sequencing, we categorized the alleles as ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4, and ε4/ε4. Individuals with at least one ε4 allele were grouped as the APOE ε4 group while those without the ε4 alleles were categorized as the non‐APOE ε4 group.
2.3. Ethics
The Institutional Ethics Committee of the Center for Brain Research (CBR), Indian Institute of Science, Bangalore, approved the TLSA study. All participants provided voluntary, written informed consent for the study procedures.
2.4. Statistical analysis
All data (outcome variables and covariates) were checked to see if they were normally distributed using the Kolmogorov–Smirnov test. To decide which factors to include in the main analysis, we compared characteristics between the two groups (normal menopause and early menopause). Categorical variables were compared using a Chi‐Square test and continuous variables were compared using the Mann–Whitney U test. Two models were used to examine the immediate effect of early menopause on brain function and structure. In Model 1, multiple linear regressions were run separately for each cognitive test and brain volume measurement, age of menopause (early vs. normal) was the independent variable. Brain volumes were adjusted for total head size in these analyses. Model 2 included statistically significant factors identified in the previous step, such as education, depression, and APOE ε4 status. We also ran additional analyses such as the correlation between the age of menopause (continuous variable) and all outcome variables and linear regression analysis examining any difference in outcome variables between early menopause and normal menopause groups after excluding MCI participants. Furthermore, we divided the sample based on age of attaining menopause into four groups; premature menopause (<40 years), early menopause (40‐45 years), (normal menopause (46‐55 years), and late menopause (>55 years) and examined differences in outcome variables using multiple linear regression analysis. We also examined any difference in outcome measures if a person had natural menopause. We then added additional covariates; difference in age of assessment and age of attaining menopause and age. Last, we used the average age of menopause as the cutoff to determine early menopause (≤46.2 years) and normal menopause (>46.2 years) Missing data were handled using the pairwise deletion method and a p‐value < 0.05 was considered statistically significant. All analyses were computed using the Statistical Package for Social Sciences (SPSS) software version 26, IBM Corp, NY.
3. RESULTS
The distribution of the baseline characteristics between both groups is displayed in Table 1. The median age, and distribution of study participants according to socioeconomic status, marital status, dietary habits, obesity, physical activity, smoking, and alcohol use did not differ between both groups. However, the median years of education obtained were slightly more for the normal menopause group when compared to early menopause [U = 23842, p = 0.013]. The proportion of clinical co‐morbidities did not statistically differ between both groups except for depression which was higher in the early menopause group [χ 2 (1, N = 488) = 3.9, p = 0.05]. The menstrual cycle‐related characteristics such as the age of menarche, number of live births, and age when the first child was born did not differ between both groups. The early menopause group has a slightly higher proportion of APOE ε4 carriers when compared to the normal menopause group [χ 2 (1, N = 422) = 4.9, p = 0.028].
TABLE 1.
Baseline characteristics of the study participants by age at menopause.
| Age at menopause | ||||
|---|---|---|---|---|
| Characteristics | >45 years (n = 384, 72.7%) | ≤45 years (n = 144, 27.3%) | p‐value | n (%) |
| Age, years | 61 (56, 68) | 63 (58, 69) | 0.085 | 528 (100%) |
| Education, years | 15 (12, 17) | 15 (10, 16) | 0.013 | 528 (100%) |
| Socio economic status | ||||
| Upper (MKS I) | 206 (54) | 68 (47) | 0.673 | 526 (99.6%) |
| Middle (MKS II & III) | 172 (45) | 75 (52) | ||
| Lower (MKS IV & V) | 4 (1) | 1 (1) | ||
| Marital status | ||||
| Living with a partner | 232 (81) | 79 (74) | 0.071 | 392 (74.2%) |
| Living without a partner | 53 (19) | 28 (26) | ||
| Diet | ||||
| Vegetarian | 224 (71) | 99 (80) | 0.130 | 437 (82.8%) |
| Non‐Vegetarian | 90 (29) | 24 (20) | ||
| Obesity | ||||
| Malnourished (BMI < 18.5) | 1 (0.3) | 3 (2.3) | 0.061 | 485 (91.9%) |
| Normal (BMI 18.5–22.9) | 50 (14.2) | 15 (11.3) | ||
| Overweight (23–24.9) | 47 (13.4) | 25 (18.8) | ||
| Obesity (BMI > = 25) | 254 (72.2) | 90 (67.7) | ||
| Physical activity | ||||
| Active (MET < 600) | 195 (60) | 68 (60) | 0.768 | 440 (83.3%) |
| Inactive (MET > = 600) | 129 (40) | 48 (40) | ||
| Smoking status (ever) | ||||
| No | 249 (65) | 97 (67) | 0.639 | 526 (99.6%) |
| Yes | 133 (35) | 47 (33) | ||
| Alcohol status (ever) | ||||
| No | 234 (91) | 88 (89) | 0.607 | 357 (67.6%) |
| Yes | 24 (9) | 11 (11) | ||
| Depression | ||||
| No (GDS < = 9) | 318 (90) | 113 (84) | 0.050 | 488 (92.4%) |
| Yes (GDS > 9) | 35 (10) | 22 (16) | ||
| Hypertension | ||||
| No | 158 (41) | 51 (35) | 0.206 | 525 (99.4%) |
| Yes | 223 (59) | 93 (65) | ||
| Cardiac illness | ||||
| No | 310 (95) | 114 (92) | 0.311 | 452 (85.6%) |
| Yes | 18 (5) | 10 (8) | ||
| Type 2 diabetes mellitus | ||||
| No | 263 (69) | 90 (63) | 0.133 | 523 (99.1%) |
| Yes | 116 (31) | 54 (37) | ||
| Dyslipidemia | ||||
| No | 44 (12) | 16 (11) | 0.865 | 522 (98.9%) |
| Yes | 334 (88) | 128 (89) | ||
| Hypothyroidism | ||||
| No | 280 (83) | 96 (75) | 0.065 | 467 (88.4%) |
| Yes | 59 (17) | 32 (25) | ||
| Mild cognitive impairment | ||||
| No (CDR = 0) | 340 (93) | 130 (92) | 0.677 | 509 (96.4%) |
| Yes (CDR = 0.5) | 27 (7) | 12 (8) | ||
| Cardiovascular risk score | ||||
| Low risk (CAIDE < 9) | 194 (70) | 64 (65) | 0.345 | 377 (71.4%) |
| High risk (CAIDE > = 9) | 84 (30) | 35 (35) | ||
| Vitamin B12, pg/mL | 283 (204, 484) | 265 (190, 499) | 0.526 | 467 (88.4%) |
| Homocysteine, μmol/L | 14.9 (12, 19.3) | 15.9 (11.5, 20.2) | 0.507 | 476 (90.2%) |
| C‐reactive protein, mg/L | 2.5 (1.1, 5) | 2.6 (1, 6) | 0.592 | 410 (77.7%) |
| APOE ε4 status | ||||
| Non‐carrier | 252 (81) | 100 (90) | 0.028 | 422 (79.9%) |
| Carrier | 59 (19) | 11 (10) | ||
| Age at menarche, years | 13 (13, 14) | 14 (13, 15) | 0.399 | 525 (99.4%) |
| Number of live births | 2 (1, 2) | 2 (1, 2) | 0.630 | 501 (94.9%) |
| Age at first child's birth | 25 (22, 28) | 24 (21, 27) | 0.148 | 480 (90.9%) |
Notes: Continuous data is presented as mean (± SD) for normal distribution variables, or median (IQR) for non‐normal distribution variables. Categorical variables are presented as numbers (%).
Abbreviations: BMI, body mass index; CAIDE, Cardiovascular Risk Factors, Aging, and Incidence of Dementia score; CDR, Clinical Dementia Rating Scale; GDS, Geriatric Depression Score; IQR, interquartile range (25th percentile, 75th percentile).; MET, metabolic equivalents; MKS: Modified Kuppuswamy Scale 2022.
The bold value indicates a p‐value < 0.05, which is considered statistically significant.
Table 2 shows the results of multiple linear regression analysis to examine the effect of early menopause on global cognitive performance and various cognitive domains. The women in the early menopause group had statistically significant lower ACE Total scores when compared to the normal menopause group [β = −2.86, 95% confidence interval (CI) (−4.41, −1.310), p < 0.001]. Furthermore, when we examined the subdomains of ACE, we found that early menopause women performed poorer in attention [β = −0.39, 95% CI (−0.72, −0.05), p = 0.022], memory [β = −1.09, 95% CI (−1.69, −0.48), p < 0.001], fluency [β = −0.70, 95% CI (−1.08, −0.31), p < 0.001], and visuospatial [β = −0.44, 95% CI (−0.83, −0.05), p = 0.025] domains but not in language domain [β = −0.23, 95% CI (−0.58, 0.11), p = 0.183]. In the digit backward test [β = −0.47, 95% CI (−0.81, −0.13), p = 0.007] and MTCF DR tests [β = −1.37, 95% CI (−2.70, −0.04), p = 0.042] women in early menopause group showed significantly lower scores when compared to normal menopause group. However, no significant differences were observed in digit forward, MTCF IR, TMT A, TMT B, and DSST tests.
TABLE 2.
Associations between earlier menopause and cognitive parameters.
| Model 1 | Model 2 | |||||
|---|---|---|---|---|---|---|
| Cognitive test | β (95% CI) | SE | p‐value | β (95% CI) | SE | p‐value |
| Global | ||||||
| HMSE | −0.16 (−0.45, 0.12) | 0.15 | 0.265 | −0.06 (−0.38, 0.25) | 0.16 | 0.691 |
| ACE total | −2.86 (−4.41, −1.31) | 0.79 | <0.001# | −2.17 (−4.03, −0.31) | 0.95 | 0.022 |
| DSST time | 24.21 (−3.28, 51.71) | 14.03 | 0.084 | 34.20 (0.64, 67.75) | 17.12 | 0.046 |
| Attention | ||||||
| ACE attention | −0.39 (−0.72, −0.05) | 0.17 | 0.022 | −0.32 (−0.72, 0.08) | 0.21 | 0.119 |
| Digit forward | −0.31 (−0.69, 0.07) | 0.20 | 0.110 | −0.28 (−0.75, 0.18) | 0.24 | 0.239 |
| TMT A time | 5.49 (−0.87, 11.87) | 3.25 | 0.091 | 3.58 (−4.09, 11.27) | 3.92 | 0.360 |
| Memory | ||||||
| ACE memory | −1.09 (−1.69, −0.48) | 0.31 | <0.001# | −1.02 (−1.76, −0.27) | 0.38 | 0.007 |
| Executive functioning | ||||||
| ACE fluency | −0.70 (−1.08, −0.31) | 0.20 | <0.001# | −0.50 (−0.96, −0.04) | 0.24 | 0.033 |
| Digit backward | −0.47 (−0.81, −0.13) | 0.17 | 0.007 | −0.44 (−0.84, −0.04) | 0.20 | 0.028 |
| TMT B time | 10.83 (−2.92, 24.59) | 7.02 | 0.123 | 9.23 (−8.36, 26.83) | 8.98 | 0.304 |
| Language | ||||||
| ACE language | −0.23 (−0.58, 0.11) | 0.18 | 0.183 | 0.00 (−0.39, 0.40) | 0.20 | 0.979 |
| Visuospatial ability | ||||||
| ACE visuospatial | −0.44 (−0.83, −0.05) | 0.20 | 0.025 | −0.33 (−0.80, 0.14) | 0.24 | 0.171 |
| Visual memory | ||||||
| MTCF IR | −0.81 (−2.14, 0.51) | 0.68 | 0.231 | 0.09 (−1.53, 1.71) | 0.83 | 0.913 |
| MTCF DR | −1.37 (−2.70, −0.04) | 0.68 | 0.042 | −0.62 (−2.24, 0.99) | 0.83 | 0.450 |
Note: Standardized beta, standard error, and 95% CIs were calculated from earlier menopause (≤45 years) versus normal menopause (>45 years) using a linear regression model. Model 1 is unadjusted, and Model 2 is adjusted for depression, APOE ε4 status, and years of education. Emboldened values represent significant differences (p < 0.05), and symbol # represents significant differences after Bonferroni correction (p < 0.003; i.e., p‐value/number of outcome variables).
Abbreviations: ACE, Addenbrooke's Cognitive Examination III; CI, confidence Interval; DR, Delayed Recall; DSST, Digit Symbol Substitution Test; HMSE, Hindi Mental Status Examination; IR, Immediate Recall; MTCF, Modified Taylor Complex Figure; SE, standard error; TMT, Trail Making Test; β, standardized beta.
The bold value indicates a p‐value < 0.05, which is considered statistically significant.
We have summarized the result of the relationship between early menopause on brain MRI volumes in Table 3, which shows that earlier menopause was associated with a reduction of the global gray matter volume GMV [β = −11973.94, 95% CI (−22987.71, −960.18), p = 0.033]. Furthermore, the left middle frontal [β = −353.14, 95% CI (−697.43, −8.86), p = 0.044] and left superior frontal [β = −460.97, 95% CI (−866.56, −55.37), p = 0.026] showed significantly lower volumes in early menopause group when compared to normal menopause group. Other regional volumes did not show any significant differences.
TABLE 3.
Associations between earlier menopause and brain MRI volumes.
| Model 1 | Model 2 | |||||
|---|---|---|---|---|---|---|
| MRI parameter | β (95% CI) | SE | p‐value | β (95% CI) | SE | p‐value |
| Total gray matter | −11973.94 (−22987.71, −960.18) | 5619.37 | 0.033 | −13126.71 (−25582.62, −670.81) | 6355 | 0.039 |
| Left inferior frontal | −145.03 (−381.81, 91.73) | 120.81 | 0.230 | −258.09 (−505.87, −10.30) | 126.4 | 0.041 |
| Left middle frontal | −353.14 (−697.43, −8.86) | 175.66 | 0.044 | −450.81 (−852.63, −49.00) | 205 | 0.028 |
| Left superior frontal | −460.97 (−866.56, −55.37) | 206.94 | 0.026 | −446.22 (−928.35, 35.90) | 246 | 0.070 |
| Right inferior frontal | −101.29 (−301.21, 98.62) | 102.00 | 0.321 | −146.93 (−382.91, 89.05) | 120.4 | 0.222 |
| Right middle frontal | −12.90 (−345.00, 319.19) | 169.44 | 0.939 | −117.73 (−490.40, 254.93) | 190.1 | 0.536 |
| Right superior frontal | −324.13 (−710.89, 62.63) | 197.33 | 0.100 | −492.47 (−965.36, −19.58) | 241.3 | 0.041 |
Note: Standardized beta, standard error, and 95% CIs were calculated from earlier menopause (≤45 years) versus normal menopause (>45 years) using a linear regression model. Model 1 is adjusted for total intracranial volume, Model 2 is adjusted for total intracranial volume, depression, APOE ε4 status, and years of education. Emboldened values represent significant differences (p < 0.05), and symbol # represents significant differences after Bonferroni correction (p < 0.007; that is, p‐value/number of outcome variables).
Abbreviations: β, standardized beta, CI, confidence interval; SE, standard error.
The bold value indicates a p‐value < 0.05, which is considered statistically significant.
In Model 2, we added those covariates which were statistically significant between both groups. The results of multiple linear regression analysis to examine the effect of early menopause on cognitive performance after adjusting for education, depression and APOE ε4 status show that women who had early menopause performed poorly in ACE Total [β = 2.17, 95% CI (−4.03, −0.31), p = 0.022], DSST time [β = 34.20, 95% CI (0.64, 67.75), p = 0.046], ACE Memory [β = −1.02, 95% CI (−1.76, −0.27), p = 0.007], ACE Fluency [β = −0.50, 95% CI (−0.96, −0.04), p = 0.033], and digit backward test [β = −0.44, 95% CI (−0.84, −0.04), p = 0.028]. Furthermore, we included these covariates in the multiple linear regression models examining the effect of early menopause on brain morphology which shows that earlier menopause was associated with lower total gray matter volume [β = −13126.71, 95% CI −25582.62, −670.81), p = 0.039]. We also found that regional volumes such as left inferior frontal, left middle frontal, and right superior frontal were less in the early menopause group when compared to the normal menopause group as shown in Table 3.
We did a series of sensitivity analyses. First, we divided the study sample into four groups [premature menopause (<40 years), early menopause (40‐45 years), normal menopause (46‐55 years), and late menopause (>55 years)] and examined group differences in all outcome variables as shown in Table S1. The results did not differ much. We then divided the early menopause group (<45 years) based on the history of hysterectomy. There are no differences in cognition and brain morphology between women who attained surgical menopause and nonsurgical menopause as shown in Table S2. Furthermore, we examined if the cognitive parameters are correlating with the MRI variables which are presented in Table S3. Last, we added covariate to the linear regression model, the difference in age of menopause and age when cognitive or MRI assessment was done. The results did not change as shown in Table S4. Table S5 shows the results of multiple linear regression when the cutoff for early menopause was set as 46.3 years (the average age of menopause in Indian women), and Table S6 shows the results of multiple linear regression after using age as covariate.
4. DISCUSSION
In a dementia‐free community‐based cohort of aging from an urban Indian setting, we observed that participants with early menopause had significantly lower cognitive performance across all the cognitive domains assessed – attention, executive functioning, visuospatial ability, language, and memory – and had significantly lower total gray matter volume as well as frontal and cingulate volumes. To the best of our knowledge, this is the first study from India examining the association of early menopause with cognitive performance along with MRI brain volumes in a healthy, dementia‐free cohort.
Our findings are in line with other studies published across the globe such as in the United Kingdom, 34 France, 7 and in some Asian countries such as South Korea 35 and China. 36 A large (around 1000 sample size) population‐based British birth cohort examining the effect of early menopause on cognition found that women with earlier menopause performed poorly in verbal memory compared with women with later menopause. Another European study done in three cities in France concluded that premature menopause (<40 years) was associated with global cognitive decline after 7 years. They went on to say that hormone replacement did not prevent cognitive decline in women who attained menopause prematurely. A nationwide cohort study in Korea examined around 4.5 million postmenopausal women and found that women who attain menopause after 55 years have a 21% reduced risk of developing dementia when compared to women who attain menopause before 40 years. Given that the previous study shows that early menopause increases the risk of dementia, our study shows even among postmenopausal women who are free from dementia early menopause affects cognition and brain volumes. The significance of demonstrating the detrimental effects of early menopause on cognitive performance even before the onset of dementia is that it allows us to implement preventive measures. Interestingly, we see a pattern of cognitive domains being affected, with global cognition, memory, and executive functioning predominantly being affected but the language domain is spared as it is usually not the earliest domain to be affected in early stages of dementia. However, more studies are necessary to see if this pattern is consistent among the Indian population.
A handful number of studies investigated the biological mechanisms to understand the effect of early menopause on cognitive performance among elderly women, and the results to date remain unclear. Researchers in the Religious Order Study and Rush Memory and Aging study demonstrated that earlier age at menopause was associated with increased AD neuropathology, in particular neurotic plaques. 37 Furthermore, a study on UK Biobank data showed that earlier menopause was negatively associated with global and regional gray matter indices, and positively associated with white matter hyperintensities (WMHs). 9 In our study, individuals with earlier menopause had greater global and cortical GMV loss, especially in the frontal regions which may underlie cognitive performance related to early menopause. We can postulate from the estrogen deprivation theory from natural perimenopause influence on dementia that lack of estrogen could play a potential role in brain morphology and consequently cognitive performance among women. 38
Poorer cognitive performance among early menopause women can have many negative consequences such as a decrease in the number of women in the workforce, difficulties in activities of daily living, and poor sleep all of which can put more demand on elder care services. It can also hurt the economy where women contribute toward it significantly. Several actions can be taken to address the implications of menopause on cognition such as increasing awareness of the issue as women, their families, and healthcare providers need to be aware of the potential cognitive effects of menopause. We can also develop and implement interventions to prevent and treat cognitive decline which predominantly focus on lifestyle changes, such as eating a healthy diet, exercising regularly, and sleep hygiene, as well as cognitive training programs and hormone therapy. The use of hormone replacement treatment (HRT) in women after surgical menopause before 40 years of age is inconsistent, and further research is crucial to determine its use. A pan‐Indian survey conducted across 21 cities shows that the average of menopause in India is 46.2 years, 39 which is less than Western women where the average age of attaining menopause ranges between 49 to 50.5 years. 40 We are unsure of the potential reasons for this observation. Moreover, more research is needed in India to examine the effect of early menopause on cognition, including the development of new and more effective interventions as this will help improve the quality of life for women experiencing cognitive decline due to early menopause.
One of the main strengths of this study is that we included only participants without dementia to demonstrate that early menopause may start to affect cognitive performance even before the onset of dementia or predementia syndromes among Indian women. Moreover, we included only postmenopausal women and not perimenopausal women in whom estrogen deprivation could influence the outcome variables. Unlike most of the previous studies that used brief global cognitive measures or a few selected cognitive domains, we used a comprehensive, neuropsychological battery that covered most cognitive domains. Last, along with cognitive outcomes we have also used MRI brain volumes which substantiates the findings. Our study does have a few limitations, and the major one is the cross‐sectional study design, which prevents us from making causal connections. We intend to follow these participants for over a decade and explore the relationship between early menopause and cognitive decline, also we would like to explore how early menopause could affect other AD pathologies such as amyloid plaques and tau protein. The information on the use of HRT was not available which could be a potential confounding factor. Furthermore, our results may not be generalizable to all of India, and we recommend such studies be replicated in other parts of India. Last, we did not use the hormonal assay to define menopause and relied on the history of the last period which could lead to recall bias.
In conclusion, our findings suggest that early menopause could be a potential risk for cognitive impairment among aging women. We recommend increasing awareness of this fact among the medical community and the general public. There is an urgent need to explore the underlying biological mechanism and to discover effective interventions to mitigate the effect. These interventions implemented in the early stages of dementia can potentially mitigate the significant burden it imposes.
AUTHOR CONTRIBUTION
Abhishek Mensegere: Conceptualization; methodology; validation; formal analysis; data curation; writing—original draft preparation; visualization. Sadhana Singh: Methodology; validation; writing—review and editing. Albert Stezin Sunny: Conceptualization; methodology; validation; writing—review and editing. Jonas S Sundarakumar: Conceptualization; methodology; validation; writing—review and editing. Thomas Gregor Issac: Conceptualization; methodology; validation; writing—review and editing; project administration. All authors approved the final version of the manuscript for publication. All authors had full access to the data in the study and took responsibility for data integrity and accuracy of data analysis.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest. Author disclosures are available in the supporting information.
CONSENT STATEMENT
All study participants provided written informed consent.
Supporting information
Supporting information
Supporting information
Supporting information
ACKNOWLEDGMENTS
We are grateful to the volunteers who participated in the TLSA study. The study is funded by the Tata Education Trust (vide ID: TET/MUM/INN/CoBR/2021‐2022/0001/DV/sa). The funding source did not have any role in the study design; in the collection, analysis, and interpretation of data; in the writing of the manuscript; and in the decision to submit the article for publication.
Mensegere A, Singh S, Stezin A, Sundarakumar JS, Issac TG. Effect of early menopause on cognition and brain morphology in an Urban Indian Cohort. Alzheimer's Dement. 2024;20:5607–5616. 10.1002/alz.14069
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