Metabolic health, menopause, and physical activity—a 4-year follow-up study

The study addresses how metabolic health changes during the menopausal transition and whether physical activity modulates these changes. Metabolic health encompasses measures such as body adiposity, anthropometrics, blood pressure, and blood-based biomarkers. Menopause, characterized by declining estradiol levels, has been linked to adverse changes including increased abdominal adiposity, higher blood glucose, unfavorable lipid profiles, increased inflammation, and decreased muscle mass, contributing to higher metabolic syndrome and cardiovascular disease risk after menopause. Physical activity is known to improve metabolic risk factors, yet longitudinal device-measured evidence on whether PA modifies menopause-related changes is limited, and prior studies often lacked comparable aging controls. The purpose of this study was to quantify changes in serum lipids, glucose, blood pressure, and adiposity around menopause and test if PA modulates these changes.

Prior research indicates menopause associates with increases in abdominal fat, blood glucose, and adverse lipid changes, along with increased inflammation and reduced muscle mass, elevating MetS and cardiovascular risk. PA generally reduces adiposity, improves insulin sensitivity, prevents dyslipidemia, and lowers blood pressure, and is used in MetS prevention and treatment. However, few longitudinal studies have used device-measured PA around menopause; existing studies predominantly examined women transitioning from pre/perimenopause to postmenopause without accounting for contemporaneous age-related changes. Findings on HDL-C and glucose changes during menopausal transition have been mixed, with reports of HDL-C increasing, peaking pre-menopause, or declining, and glucose showing decreases in some longitudinal studies yet higher levels postmenopause in cross-sectional data.

Design: Longitudinal observational study utilizing baseline data from ERMA (recruited 2014; measured 2015–2016) and approximately 4-year follow-up from EsmiRs (recruited 2018; measured 2019 until COVID-19 lockdown in March 2020). Participants: 298 white women aged 48–55 years at baseline, after exclusions for factors affecting ovarian/hormonal/inflammatory status (e.g., bilateral oophorectomy, estrogen-containing medications, severe obesity BMI ≥35 kg/m²), diabetes requiring insulin, severe cardiovascular dysfunction, cancer during follow-up, or >7 years since menopause. Mean follow-up time: 3.8 years (SD 0.1). Menopausal status: Determined at both timepoints using fasting serum estradiol (E2) and follicle-stimulating hormone (FSH) (IMMULITE 2000 XPI), and menstrual bleeding diaries per adapted STRAW+10 guidelines. Participants grouped by transition status: PRE-POST (pre/perimenopausal at baseline to postmenopausal at follow-up, n=149), PRE-PRE (pre/perimenopausal at both timepoints, n=56), POST-POST (postmenopausal at both timepoints, n=93). Outcomes: Indicators of metabolic health included body composition by DXA (LUNAR, GE Healthcare): total fat mass, android fat mass, total fat percentage, fat-free mass; anthropometrics: waist and hip circumferences (to derive WHR), body mass, height, BMI; blood pressure: SBP and DBP measured twice seated after 10 min rest (Omron M6 Comfort; mean used); fasting serum biomarkers: glucose, HDL-C, LDL-C, total cholesterol, triglycerides (KONELAB 20 XTi). Metabolic syndrome risk factors were defined by updated ATP III cut-points: waist circumference ≥88 cm; blood pressure ≥130/≥85 mmHg; triglycerides ≥1.69 mmol/L; glucose ≥5.6 mmol/L; HDL-C <1.29 mmol/L. Physical activity: Device-measured PA with ActiGraph GT3X/wGT3X worn on right hip for 7 consecutive days during waking hours (not during water activities), sampled at 60 Hz. Euclidean norm resultant acceleration used to compute mean amplitude deviation (MAD) for 5 s epochs, aggregated to 1 min; ACC-MAD reflects PA volume across intensities and is validated against oxygen consumption. Non-wear: ≥60 min with continuous 1-min MAD <0.001 g. Valid wear: ≥3 days with ≥10 h/day. ACC-MAD determined over wear time; MVPA defined as ≥0.091 g. PA also assessed via self-reported questionnaire (SR-PA) estimating leisure-time MET-hours/day and commuting activity. Covariates: Baseline age (mean-centered), use of exogenous sex hormone preparations (non-user, progestogen, estrogen, combined estrogen+progestogen). Lifestyle (alcohol portions/week, smoking) and medications (antihypertensives, lipid-modifying agents, thyroid therapy) collected but not included as primary confounders due to potential post-exposure status; sensitivity analyses included them. Diet Quality Score (11-point index aligned with Nordic Nutrition Recommendations) calculated from FFQ. Missing data and imputation: Overall missing values 5% (741/13,708). Assumed missing at random. Multiple imputation by chained equations (R mice package), 50 datasets, 50 iterations, passive imputation for WHR; models fit in each imputed dataset and pooled via Rubin's rules. Complete case analyses yielded similar conclusions. Statistical analysis: Linear mixed-effects models (random intercept) for continuous outcomes; Poisson mixed-effects models for count of MetS risk factors. Fixed effects: time (0 baseline, 1 follow-up), menopausal group, ACC-MAD, time×group, time×ACC-MAD; covariates: baseline age and hormone use. Model assumptions checked via residuals, Q-Q plots, correlations. Sensitivity analyses excluded users of lipid-modifying agents for lipid outcomes and antihypertensives for blood pressure; analyses repeated using SR-PA.

• Sample: 298 women; mean follow-up 3.8 years; groups: PRE-POST n=149, PRE-PRE n=56, POST-POST n=93.
• Baseline: Participants were slightly overweight (BMI 25.3 ± 3.7 kg/m²), with slightly elevated SBP (132.0 ± 16.3 mmHg), DBP (84.1 ± 9.2 mmHg), total cholesterol (5.23 ± 0.91 mmol/L), and LDL-C (3.05 ± 0.80 mmol/L).
• Cross-sectional PA associations (per +10 mg ACC-MAD): higher PA associated with higher HDL-C (B=0.06, 95% CI [0.01, 0.11]) and lower LDL-C (B=−0.11, 95% CI [−0.21, −0.01]); lower total fat mass (B=−0.77 kg, 95% CI [−1.27, −0.26]), android fat mass (B=−0.11 kg, 95% CI [−0.18, −0.03]), waist circumference (B=−0.92 cm, 95% CI [−1.60, −0.24]), and WHR (B=−0.89×100, 95% CI [−1.51, −0.27]). No significant association with SBP/DBP at baseline.
• Longitudinal changes in PRE-POST group: significant increases in total fat mass (B=1.72 kg, 95% CI [0.16, 3.28]), android fat mass (B=0.26 kg, 95% CI [0.06, 0.46]), SBP (B=9.37 mmHg, 95% CI [3.34, 15.39]), and all blood biomarkers: total cholesterol (B=0.45 mmol/L, 95% CI [0.07, 0.84]), HDL-C (B=0.35 mmol/L, 95% CI [0.18, 0.52]), LDL-C (B=0.40 mmol/L, 95% CI [0.06, 0.74]), glucose (B=0.32 mmol/L, 95% CI [0.08, 0.55]), triglycerides (B=0.28 mmol/L, 95% CI [0.03, 0.52]).
• Group differences in change: increases tended to be smaller in PRE-PRE and especially POST-POST versus PRE-POST for lipids and adiposity; e.g., Time×POST-POST effects were negative for total cholesterol (−0.42, 95% CI [−0.65, −0.20]), HDL-C (−0.15, 95% CI [−0.24, −0.05]), LDL-C (−0.34, 95% CI [−0.53, −0.14]), and for total fat mass (−1.20 kg, 95% CI [−2.12, −0.28]). SBP change did not differ significantly between groups.
• PA change associations: time×ACC-MAD showed an inverse association with SBP change (B=−2.40 mmHg per +10 mg ACC-MAD, 95% CI [−4.34, −0.46]) and a direct association with WHR change (B=0.72×100 per +10 mg ACC-MAD, 95% CI [0.05, 1.38]); no significant time×ACC-MAD effects for blood biomarkers or waist circumference.
• Metabolic syndrome risk factors: number at baseline and change over time did not differ by group; per +10 mg ACC-MAD not associated with baseline count (exp(B)=0.91, 95% CI [0.79, 1.04]) nor with change (time×ACC-MAD exp(B)=0.88, 95% CI [0.73, 1.06]). Baseline age associated with higher number of risk factors (exp(B)=1.07, 95% CI [1.00, 1.14]).
• Hormone therapy: combined estrogen+progestogen use associated with lower glucose (B=−0.19 mmol/L, 95% CI [−0.33, −0.04]) and lower SBP (B=−5.55 mmHg, 95% CI [−9.61, −1.49]) and DBP (B=−4.33 mmHg, 95% CI [−6.36, −2.30]); progestogen-only use associated with lower HDL-C (B=−0.11 mmol/L, 95% CI [−0.20, −0.03]).
• Sensitivity and alternative PA measure: Results were similar using self-reported PA; excluding lipid-modifying agent or antihypertensive users did not materially change findings.

The study demonstrates that the menopausal transition is associated with accelerated adverse changes across multiple metabolic health indicators, particularly blood lipids, body fat, and systolic blood pressure. By comparing women of similar age in different menopausal stages over the same follow-up period, the analysis disentangles menopause-related changes from aging-related changes, showing the largest increases among those transitioning to postmenopause. While higher habitual PA is linked with more favorable lipid profiles and lower adiposity levels, changes in PA during follow-up did not substantially alter the trajectory of most biomarkers across the menopausal transition. Notable exceptions were an attenuation of SBP increase with higher PA and an unexpected greater increase in WHR with higher PA, possibly reflecting disproportionate changes at the hip (e.g., lean mass loss) rather than central adiposity. The lack of association between PA and the number of MetS risk factors may reflect insensitivity of dichotomous clinical thresholds to detect sub-threshold improvements. Overall, the findings support the importance of PA for maintaining healthier metabolic profiles, particularly blood pressure, but suggest that larger increases in PA may be necessary to counteract menopause-accelerated changes in lipids and adiposity.

Undesirable changes in blood lipids, body adiposity, and systolic blood pressure occur in middle-aged women and are accelerated during the menopausal transition. Habitual physical activity is associated with a healthier lipid profile and lower adiposity but generally does not modify menopause-related changes in most metabolic indicators. Higher PA may help attenuate increases in SBP and is linked to a greater rise in WHR over time. These results underscore the need to promote physical activity for early prevention of hypertension and cardiovascular disease in midlife women, and suggest that substantial increases in PA may be required to mitigate menopause-related lipid and adiposity changes. Future research should include more frequent longitudinal measurements, diverse populations, detailed characterization of tissue-specific changes (e.g., regional fat vs. lean mass), and evaluation of PA dose-response and timing relative to menopausal transition.

Only two measurement timepoints limited precision in temporal dynamics; the sample was homogeneous (white, middle-aged Finnish women) with exclusions (e.g., severe obesity, significant comorbidities), restricting generalizability. Healthy selection bias may be present due to dropouts, with included participants showing slightly better glucose control and higher PA. COVID-19 lockdown prevented measurements for 99 participants. Exogenous hormone analyses did not account for dosage, duration, or delivery route. Regional tissue composition changes at the hip could not be distinguished (fat vs. lean). Although multiple imputation addressed missing data under a missing at random assumption, residual bias cannot be excluded.