Abstract
Background
Metabolic syndrome (MetSyn) is associated with frailty in older adults, with few data among midlife women. We examined MetSyn, including duration, for associations with the development of prefrailty and frailty.
Methods
The Study of Women’s Health Across the Nation is a multiethnic, longitudinal cohort study of women aged 42-52 years at the time of enrollment (1996-1997). MetSyn was measured longitudinally, using ATP III criteria, starting at baseline. Pre-frailty and frailty were measured at two later visits (2012/13 and 2015/16) using Fried criteria. Associations of pre-frailty and frailty with prevalent MetSyn, the cumulative number of prior visits with MetSyn, and individual MetSyn criteria were examined using multivariable models.
Results
A total of 1769 women were included (mean age 59.7 years, SD 3.3). The adjusted odds ratios (aOR) for having pre-frailty or frailty in women with MetSyn compared to those without were 2.77 (95% CI, 2.19-3.50) and 8.73 (95% CI, 5.89-12.95), respectively. Each additional visit a woman met criteria for MetSyn was associated with a higher odds of pre-frailty and frailty (aOR 1.20; 95% CI: 1.14-1.26, and aOR: 1.41; 95% CI: 1.33-1.50, respectively). Individual MetSyn criteria were also associated with the risk of frailty.
Conclusions
Among women in this multiethnic cohort, MetSyn was common during midlife and strongly associated with future development of pre-frailty and frailty while women were in their early 60s. Measurement of MetSyn during midlife can help identify women at high risk for developing frailty early in the aging process.
Keywords: Frailty, Metabolic syndrome, Women
Introduction
Approximately half of all women in the United States over the age of 60 meet the criteria for metabolic syndrome (MetSyn) as defined by the National Cholesterol Education Program’s Adult Treatment Panel III.1,2 MetSyn is a cluster of risk factors that are associated with an increased risk of cardiovascular disease.3 These include increased waist circumference, a marker of visceral adiposity, elevated blood pressure (BP), elevated blood glucose, and abnormal lipids. Prior studies, predominantly in adults over the age of 70, have observed associations between MetSyn and frailty.4–8 However, the association between MetSyn and the future risk of frailty among younger women is less well understood. In particular, the number of years a woman meets criteria for MetSyn may increase the risk for early development of frailty, given the associations of MetSyn with physical function.5 Furthermore, the data on the association between MetSyn and pre-frailty are limited. Living with frailty increases a woman’s risk for disability and increased healthcare costs, while lowering her quality of life.9–12 Thus, identifying women early in the aging process who are at higher risk for frailty can allow for interventions that address MetSyn and reduce or prevent the development of frailty.
The Study of Women’s Health Across the Nation (SWAN) is a unique cohort of multi-ethnic women followed for over two decades with repeated longitudinal assessments of MetSyn factors throughout midlife and frailty metrics assessed at more recent visits. Using these data, we sought to examine the association of ever meeting the criteria for MetSyn during midlife and the duration of MetSyn with subsequent pre-frailty and frailty. We hypothesized that a history of MetSyn during midlife and the number of prior visits with MetSyn (a measure of MetSyn duration) increase a woman’s risk of developing both pre-frailty and frailty in late midlife.
Methods
Study population
SWAN is a community-based, multiethnic longitudinal study that, in 1996-1997, enrolled 3302 women from seven study sites (Boston, Massachusetts, United States; Chicago, Illinois, United States; Detroit area, Michigan, United States; Los Angeles, California, United States; Newark, New Jersey, United States; Oakland, California, United States; and Pittsburgh, Pennsylvania, United States). Each site recruited White women and one site-specific minority group (non-Hispanic Black [Boston, Massachusetts, United States; Chicago, Illinois, United States; Detroit, Michigan, United States; Pittsburgh, Pennsylvania, United States], Chinese [Oakland, California, United States], Hispanic [Newark, New Jersey, United States], and Japanese [Los Angeles, California, United States]). The study design has been previously described.13 Briefly, eligible women were aged 42-52 at baseline, had an intact uterus and at least one ovary, and had not used exogenous hormones affecting ovarian function in the past 3 months. Additionally, they had experienced at least one menstrual period in the previous 3 months. Clinic visits were conducted at baseline and approximately annually through 2017. The present study includes women with available data on frailty criteria and at least one prior visit at which MetSyn criteria were assessed (n = 1769). Participants from the Newark site were excluded from the analysis, as this site did not measure skeletal muscle mass. The study was approved by the institutional review boards at each site, and all participants provided written informed consent.
Frailty assessment
The primary outcomes of interest were pre-frailty and frailty, as defined by the Fried criteria.14 These outcomes were measured at visits 13 (2012-2013) and 15 (2015-2016), when participants completed physical function assessments. Frailty was defined as having three or more of the five criteria: weakness, slow walking speed, low physical activity, self-reported exhaustion, and unintentional weight loss, while pre-frailty was defined as having one or two criteria. Grip strength was measured using a handgrip dynamometer with the participants seated, using a validated protocol.15 Testing was performed three times, with the mean and weight-adjusted max readings in the dominant hand, recorded in kilograms. For the present study, weakness was defined as the lowest 20% for weight-normalized grip strength. For gait speed, participants were asked to walk at their usual pace, which was timed over a 4-meter level course.15 This was completed twice, and the faster test was recorded. Slow walking speed was defined as the slowest 20% for gait speed.
Mean physical energy expenditure was collected through an adaptation of the questionnaire used in the Kaiser Permanente Health Plan Activity Survey.16 Self-reported exhaustion was collected using items from the 36-Item Short Form Health Survey17 including “are you full of pep”, “did you have a lot of energy”, “did you feel worn out”, and “did you feel tired”. Skeletal muscle mass, a measure of sarcopenia, was measured using a bioelectrical impedance analysis and quantified using the equation by Janssen et al.18 For each participant, we defined frailty based on the earliest assessment for which these measures were completed.
Metabolic syndrome
SWAN collected data on MetSyn criteria from baseline through follow-up visit 15. For the present analysis, MetSyn data were included from baseline up to the visit preceding the measurement of frailty criteria: for women with frailty measures completed at visit 13, MetSyn criteria through visit 12 were used; for women with frailty measures collected at visit 15, MetSyn criteria through visit 13 were used. MetSyn was defined using the National Cholesterol Education Program Adult Treatment Panel criteria19; the definition in use at the time participants were enrolled. Women met the definition of MetSyn if they had three or more of the following: waist circumference ≥88 cm (or ≥80 cm for Chinese or Japanese), BP ≥130/85 mm Hg, or use of antihypertensive medication, fasting triglyceride levels ≥150 mg/dL, fasting high-density lipoprotein (HDL) cholesterol <50 mg/dL and fasting blood glucose ≥110 mg/dL or use of antiglycemic medication. Standard protocols were used for measuring waist circumference and BP. Waist circumference was measured in centimeters at the narrowest part of the torso from the anterior aspect. BP was measured following a 5-minute rest, and the average of two measurements was recorded. All lipid, lipoprotein, and apolipoprotein fractions were analyzed on EDTA-treated plasma.20,21 Total cholesterol and triglycerides were analyzed by enzymatic methods on a Hitachi 747 analyzer (Boehringer Mannheim Diagnostics, Indianapolis, IN) for baseline-visit 7, and using the ADVIAcholesterol, direct HDL and triglyceride assays for later visits as previously described.20 HDL-C was isolated using heparin-2M manganese chloride.21 When triglycerides were less than 400 mg/dL, low-density lipoprotein (LDL) cholesterol was calculated by using the Friedewald formula (LDL = total cholesterol-HDL—triglycerides/five). Fasting glucose was measured in serum by automated enzymatic assay on a Hitachi 747-200 (Roche Diagnostics Corp., Indianapolis, Indiana) chemistry analyzer (Baseline-V7) and, for later visits, was measured in serum using the ADVIA Chemistry Glucose Hexokinase_3 Concentrated Reagents (GLUH_c) method. HDL, triglycerides, and glucose were not collected at follow-up visits 2, 8, or 10; at these visits, MetSyn was determined based on all available information.
Covariates
Covariates were selected based on the a priori knowledge of factors associated with both MetSyn and the development of frailty. Demographic factors included age, race/ethnicity, and education level. Financial strain was assessed based on responses to “how hard is it to pay for basics” with possible responses “very hard,” “somewhat hard,” and “not hard at all”. Smoking status was categorized as never, former, or current. Height and weight were measured by a trained interviewer using a stadiometer and a balance beam scale, respectively, and were used to calculate the body mass index (BMI). Co-morbid conditions, including osteoarthritis, were based on self-report of ever having been diagnosed. Depressive symptoms were assessed based on the Center for Epidemiologic Studies - Depression (CES-D),22 using a cut point of ≥16 as indicative of depressive symptoms. All covariates were assessed concurrently with MetSyn.
Statistical analysis
We calculated means and SD for continuous variables and frequencies for categorical variables, overall and by the ever presence of MetSyn between baseline and V12/13 (the visit prior to the frailty assessment). We tested for significant differences using t-tests for continuous variables and χ2-tests or Fisher’s exact test for categorical variables.
To examine the association between frailty and MetSyn, we ran separate multinomial logistic regressions of frailty status (pre-frail, frail, vs not frail) on ever having MetSyn (yes/no) and of frailty status on the number of prior visits at which MetSyn was present.
Secondary analyses were conducted to examine how associations between individual components of MetSyn and frailty may differ. We ran separate models relating frailty to the individual components at the most recent prior visit. We regressed frailty on each MetSyn variable in unadjusted models. Next, we ran adjusted models in the following stages: (1) adjusting for age, race/ethnicity, education, and financial strain; and (2) additionally adjusting for smoking, osteoarthritis, and depressive symptoms. Covariate values were taken from the last visit, during which information was available on MetSyn. Models that included the number of visits with MetSyn were additionally adjusted for the total number of visits to account for women who were missing MetSyn at one or more timepoints. We also included an interaction term to examine potential differences in the association of MetSyn with frailty, between women with cardiovascular disease (CVD) at baseline and those without CVD.
Finally, we conducted stratified analyses to explore differences in the associations between frailty and MetSyn by obesity status (≥30 kg/m2 vs <30 kg/m2). We ran models for having MetSyn at any time during follow-up and the number of visits with MetSyn stratified by obesity at V13/15. Additionally, a sensitivity analysis was completed comparing a study sample limited to women with frailty measured at visit 13 to women with frailty measured at either visit 13 or 15. Statistical significance was defined at α < 0.05. All analyses were conducted in RStudio Version 3.0.38.6 (Boston, MA).23
Results
Of the 1769 women included in the present analysis, 1627 completed frailty measures at visit 13, and 142 completed them at visit 15. Compared to women excluded from this analysis, included participants were less likely to report difficulty paying for basics, had a modestly lower BMI, were never smokers, and were more likely to report hypertension or diabetes (Table S1). Demographic characteristics of the participants included in the present analysis at visit 12/13 are reported in Table 1. A total of 732 (41.3%) women met the criteria for MetSyn at one or more study visits. The average number of visits at which a woman met MetSyn criteria was 4.4 (SD 3.2; range 1-13). Women who met MetSyn criteria were more likely to be Black, report difficulty paying for basic necessities, and report current or former smoking compared to women without MetSyn.
Table 1.
Study participant characteristics by presence or absence of metabolic syndrome during follow-up.
| Characteristics |
Metabolic syndrome
a
|
|||
|---|---|---|---|---|
| Overall N = 1769 | Present N = 732 | Absence N = 1037 | p-Value | |
| Age (years), mean (SD) | 59.7 (3.3) | 59.9 (3.1) | 59.6 (3.4) | .021 |
| Race, n (%) | <.001 | |||
| White | 877 (49.6) | 341 (46.6) | 536 (51.7) | |
| Black | 512 (28.9) | 274 (37.4) | 238 (23.0) | |
| Japanese | 186 (10.5) | 59 (8.1) | 127 (12.2) | |
| Chinese | 194 (11.0) | 58 (7.9) | 136 (13.1) | |
| Difficulty paying for basic necessities, n (%) | <.001 | |||
| Very | 86 (5.0) | 51 (7.2) | 35 (3.4) | |
| Somewhat | 378 (22.0) | 184 (26.1) | 194 (19.1) | |
| Not at all | 1257 (73.0) | 471 (66.7) | 786 (77.4) | |
| Height (cm), mean (SD) | 161.7 (6.5) | 162.0 (6.5) | 161.5 (6.6) | .064 |
| Weight (kg), mean (SD) | 76.5 (20.3) | 88.4 (19.6) | 68.2 (16.2) | <.001 |
| BMI (kg/m2), mean (SD) | 29.2 (7.2) | 33.5 (6.9) | 26.1 (5.6) | <.001 |
| BMI >30 kg/m2, n (%) | 674 (38.1) | 478 (65.3) | 196 (18.9) | <.001 |
| Waist circumference (cm), mean (SD) | 90.4 (15.8) | 101.4 (13.9) | 82.6 (11.9) | <.001 |
| Smoking status, n (%) | .018 | |||
| Current | 148 (8.4) | 69 (9.5) | 79 (7.6) | |
| Former | 540 (30.6) | 243 (33.4) | 297 (28.6) | |
| Never | 1076 (61.0) | 415 (57.1) | 661 (63.7) | |
| Menopausal status, n (%) | .035 | |||
| Pre-menopausal | 7 (0.4) | 2 (0.3) | 5 (0.5) | |
| Early Peri | 47 (2.7) | 18 (2.5) | 29 (2.8) | |
| Late Peri | 34 (1.9) | 15 (2.0) | 19 (1.8) | |
| Natural post-menopausal | 1522 (86.0) | 613 (83.7) | 909 (87.7) | |
| Surgical post-menopausal | 145 (8.2) | 79 (10.8) | 66 (6.4) | |
| Unknown due to HT use | 14 (0.8) | 5 (0.7) | 9 (0.9) | |
| Blood pressure, mean (SD) | ||||
| Systolic BP (mm Hg) | 120.6 (16.5) | 125.7 (16.0) | 117.0 (16.0) | <.001 |
| Diastolic BP (mm Hg) | 74.1 (10.0) | 75.9 (9.9) | 72.8 (9.9) | <.001 |
| Hypertension, n (%)b | 976 (55.4) | 594 (81.5) | 382 (37.0) | <.001 |
| Lipids, mean (SD) | ||||
| Total cholesterol (mg/dL) | 206.7 (35.9) | 198.2 (37.7) | 212.7 (33.3) | <.001 |
| LDL cholesterol (mg/dL) | 120.0 (25.2) | 116.7 (26.0) | 122.3 (24.4) | <.001 |
| HDL cholesterol (mg/dL) | 63.5 (16.2) | 53.5 (11.2) | 70.4 (15.4) | <.001 |
| Triglycerides (mg/dL) | 113.7 (54.3) | 141.6 (63.2) | 94.4 (36.2) | <.001 |
| Fasting glucose (mg/dL), mean (SD) | 97.4 (26.0) | 108.3 (35.7) | 89.9 (11.3) | <.001 |
| Diabetes, n (%)c | 258 (14.6) | 240 (32.8) | 18 (1.7) | <.001 |
| Osteoarthritis | 511 (28.9) | 277 (37.9) | 234 (22.6) | <.001 |
| Depressive symptoms (CES-D ≥ 16) | 234 (13.3) | 117 (16.0) | 117 (11.3) | .005 |
Abbreviations: BMI, body mass index; BP, blood pressure; CES-D, Center for Epidemiologic Studies-Depression; HT, hormonal therapy; MetSyn, metabolic syndrome; SD, standard deviation; LDL, low-density lipoprotein; HDL, high-density lipoprotein. Missingness: difficulty paying for basics, n = 48; height, n = 12; weight, n = 12; BMI, n = 13; waist circumference, n = 12; smoking status, n = 5; total cholesterol, n = 12; LDL, n = 22; HDL, n = 12; triglycerides, n = 21; glucose, n = 18; SBP, n = 11; DBP, n = 11; hypertension, n = 8; osteoarthritis, n = 3; depressive symptoms, n = 6.
MetSyn defined as meeting criteria of MetSyn up through the latest visit prior to frailty assessment (visit 12 or 13). Participant characteristics assessed at the last visit included in defining MetSyn.
Hypertension was defined as a mean systolic ≥130 mm Hg or mean diastolic ≥85 mm Hg or use of antihypertensive medications.
Diabetes was defined as fasting glucose ≥126 mg/dL of use of antiglycemic medications.
As expected, the individual factors used to define MetSyn were more common among women diagnosed with MetSyn. BMI, waist circumference, and resting BP were higher among women who met the MetSyn criteria than among those who did not (Table 1). The majority of women with MetSyn carried a diagnosis of hypertension, compared to less than half of women without MetSyn (81.5% vs 37.0%, p < .001). Women with MetSyn had lower levels of total cholesterol, LDL cholesterol, and HDL cholesterol and higher levels of triglycerides and fasting blood glucose, compared to women without MetSyn. The prevalence of diabetes, osteoarthritis, and depressive symptoms were also higher among women with MetSyn.
Metrics related to frailty are shown in Table 2. The mean Short Physical Performance Battery (SPPB) summary scores were lower among women with MetSyn, as was weight-normalized grip strength. Women with MetSyn were more likely to fail the balance assessment compared to women without MetSyn (16.7% vs 7.1%, respectively, p < .001). Women with MetSyn also took significantly longer to complete the 4-meter gait speed test, completed fewer chair stands and stair climbs, and were slower when completing the timed 40-foot walk compared to women without MetSyn. Women with MetSyn were more likely to report feeling exhausted and have a lower average physical energy expenditure. Weight-normalized skeletal muscle mass was also lower among women with MetSyn compared to women without MetSyn.
Table 2.
Frailty components at V13/15 among women with and without metabolic syndrome.
| Frailty characteristics |
Metabolic syndrome
a
|
|||
|---|---|---|---|---|
| Overall N = 1769 | Present N = 732 | Absence N = 1037 | p-Value | |
| Grip strength (kg), mean (SD) | 25.5 (5.6) | 25.6 (5.9) | 25.4 (5.5) | .577 |
| Weight-normalized grip strength, mean (SD) | 0.35 (0.10) | 0.30 (0.09) | 0.39 (0.10) | <.001 |
| Gait Speed (4 m walk) (m/s), mean (SD) | 1.06 (0.25) | 0.97 (0.22) | 1.12 (0.25) | <.001 |
| Timed 40 foot walk (s), mean (SD) | 9.01 (2.40) | 9.72 (2.48) | 8.45 (2.17) | <.001 |
| Self-reported exhaustion, n (%) | 237 (13.4) | 130 (17.8) | 107 (10.3) | <.001 |
| Physical energy expenditure scale,b mean (SD) | 7.62 (1.81) | 7.13 (1.74) | 7.97 (1.78) | <.001 |
| Skeletal muscle mass (kg), mean (SD) | 19.6 (3.3) | 21.0 (3.5) | 18.7 (2.9) | <.001 |
| Weight-normalized skeletal muscle mass, mean (SD) | 0.27 (0.05) | 0.25 (0.04) | 0.28 (0.05) | <.001 |
MetSyn defined as meeting criteria of MetSyn up to visit 12 or 13 which ever preceded measurement of frailty.
Physical Energy Expenditure scale with range form 3-15, Missingness: timed walk, n = 318.
Women who ever met the criteria for MetSyn had threefold higher unadjusted odds for pre-frailty (OR 3.18; 95% CI: 2.57-3.95) and tenfold higher odds for frailty (OR 10.74; 95% CI: 7.49-15.39) compared to women without MetSyn (Figure 1 and Table S2). The results were minimally attenuated in adjusted models. The odds of pre-frailty or frailty were 2.77 (95% CI: 2.19-3.50) and 8.73 (95% CI: 5.89-12.95), respectively, for women with MetSyn compared to those without MetSyn in the fully adjusted model. No interaction was observed for baseline CVD, although the number of women with CVD at baseline was small (n = 36).
Figure 1.
Unadjusted and adjusted multinomial logistic models of prefrailty and frailty with metabolic syndrome. Models with number of visits with metabolic syndrome additionally adjusted for total number of visits; all covariates measured concurrently with MetSyn; MetSyn defined as meeting criteria of MetSyn up to visit 12 or 13 whichever preceded measurement of frailty. Metabolic syndrome criteria definitions: elevated blood pressure ≥130/85 mm Hg; fasting triglyceride levels >150 mg/dL; fasting HDL cholesterol <50 mg/dL; fasting glucose ≥110 mg/dL; elevated waist circumference ≥88 cm or ≥80 cm for Chinese or Japanese. Model 1: unadjusted. Model 2: adjusted for age, race/ethnicity, education, difficulty paying for basic necessities. Model 3: Model 2 + smoking, osteoarthritis, and depression. Abbreviations: CI, confidence interval; OR, odds ratio.
The number of prior visits at which women met the criteria for MetSyn was significantly associated with pre-frailty and frailty (Figure 1 and Table S2). In fully adjusted models, for each additional visit where women met the criteria for MetSyn, the OR for pre-frailty was 1.20 (95% CI: 1.14-1.26), and for frailty, the OR was 1.41 (95% CI: 1.33-1.50). For models of individuals who have ever had MetSyn and the number of visits with MetSyn, we conducted a sensitivity analysis that included only visits where all five MetSyn components were collected. The results from the sensitivity analysis were consistent with those from the primary analysis. No interaction by baseline CVD status was observed.
Secondary analyses were conducted to examine the associations of frailty and pre-frailty with individual MetSyn components measured at study visits (V12/13) (Table 3). In the fully adjusted models, MetSyn criteria for elevated BP was associated with pre-frailty (OR 1.52; 95% CI: 1.20-1.92) and frailty (OR 3.50; 95% CI: 2.26-5.42) compared to women with normal range BP. Elevated fasting glucose, elevated waist circumference, and low fasting HDL cholesterol were also associated with a higher risk for pre-frailty or frailty. Sensitivity analyses stratifying women by BMI <30 kg/m2 or ≥30 kg/m2 demonstrated similar results. Significant associations were also observed for MetSyn and the number of visits with MetSyn for both pre-frailty and frailty for both obese and non-obese women (Table S3). In addition, we compared the association between pre-frailty and frailty with MetSyn, including only women from visit 13, with the sample including women from both visit 13 and 15. No significant difference was observed (Table S4).
Table 3.
Unadjusted and adjusted multinomial logistic models of pre-frailty and frailty with metabolic syndrome individual criteria at V12/13.
| Metabolic syndrome and individual criteriaa | Frailty category | Model 1 | Model 2 | Model 3 |
|---|---|---|---|---|
| OR | OR | OR | ||
| (95% CI) | (95% CI) | (95% CI) | ||
| p-Value | p-Value | p-Value | ||
| Elevated blood pressure | Pre-frail |
|
|
|
| Frail |
|
|
|
|
| Not frail | Ref | Ref | Ref | |
| Elevated fasting triglycerides | Pre-frail |
|
|
|
| Frail |
|
|
|
|
| Not frail | Ref | Ref | Ref | |
| Low fasting HDL | Pre-frail |
|
|
|
| Frail |
|
|
|
|
| Not frail | Ref | Ref | Ref | |
| Elevated fasting glucose | Pre-frail |
|
|
|
| Frail |
|
|
|
|
| Not frail | Ref | Ref | Ref | |
| Ethnic-specific waist circumference | Pre-frail |
|
|
|
| Frail |
|
|
|
|
| Not frail | Ref | Ref | Ref |
Metabolic syndrome criteria definitions: elevated blood pressure ≥130/85 mm Hg; fasting triglyceride levels >150 mg/dL; fasting HDL cholesterol <50 mg/dL; fasting glucose ≥ 110 mg/dL; elevated waist circumference ≥88 cm or ≥80 cm for Chinese or Japanese. Model 1: unadjusted. Model 2: adjusted for age, race/ethnicity, education, difficulty paying for basic necessities. Model 3: Model 2 + smoking, osteoarthritis and depression. Bolded values reflect statistically significant results (p<0.005).
Abbreviations: CI, confidence interval; OR, odds ratio.
All covariates measured concurrently with MetSyn; MetSyn criteria measured at visit preceding frailty measures.
Discussion
In this cohort of midlife women, MetSyn was common, and women with MetSyn were significantly more likely to meet criteria for pre-frailty or frailty. Furthermore, with each additional study visit, a woman met criteria for MetSyn, her risk for developing pre-frailty and frailty significantly increased. Lastly, individual MetSyn criteria, particularly elevated BP, fasting glucose, and waist circumference, were significantly associated with both pre-frailty and frailty.
Among midlife women in SWAN, MetSyn was common. Over 40% of women met the criteria for MetSyn during midlife, with 39% of White participants and 54% of Black participants meeting the criteria during an average follow-up period of 13.9 years. In contrast, Japanese and Chinese women were less likely to have MetSyn. Our findings are consistent with prior epidemiologic data.1 A recent analysis using the National Health and Nutrition Examination Survey (NHANES) data suggests that the general prevalence of MetSyn among women in the United States is 34.3%, with a higher prevalence of 48.6% among women aged 60 years or older.2 Other studies have observed higher proportions of MetSyn among minority populations. Data from NHANES suggest that non-Hispanic Black women are 20% more likely to meet the criteria for MetSyn compared to non-Hispanic White women.24 In addition, lower educational attainment and increased age were independently associated with MetSyn in NHANES. Household income has also been linked to MetSyn risk among women.25 Thus, our findings are consistent with other studies that have observed a higher prevalence of MetSyn among minority women and associated with worse socioeconomic levels.
The presence of MetSyn at any prior visit was significantly associated with meeting the criteria for pre-frailty and frailty at relatively young ages. After adjustment for multiple confounders, women with MetSyn had three times the odds of pre-frailty and nearly nine times the odds of frailty as women who never met the criteria. In a meta-analysis of 11 studies, including 19 270 participants, a 73% increased risk of frailty was observed among participants with MetSyn compared to those without MetSyn.8 It should be noted, the majority of prior studies included study populations, with the average age in their 70s.6,8,26 Finding a strong association between MetSyn and frailty among women in their early 60s suggests further research to understand if prevention or treatment of MetSyn criteria may lower a woman’s risk for frailty as she ages.
Unlike prior studies, we also evaluated for pre-frailty. Adults who are pre-frail are at high risk for becoming frail and for mortality. We found a 2-fold increase in the odds of women with MetSyn becoming pre-frail at a relatively young age. This suggests MetSyn may assist in identifying women at high risk for developing pre-frailty, followed by frailty.27–29 Given the increased risk of mortality related to frailty, identifying women earlier in the aging process may allow for interventions to prevent frailty.28,30
Additionally, our study is unique in that we examined the number of visits at which women met MetSyn criteria in relation to frailty measures. For each additional visit that a woman met MetSyn criteria, she had 20% higher adjusted odds of having pre-frailty and 41% higher odds of having frailty at a subsequent visit. This suggests that the duration of MetSyn may impact the development of frailty.
Both frailty and MetSyn are more common among older adults.1,31 With the aging of the US population, the number of adults with frailty is projected to increase. For MetSyn, an estimated one-third of the US population meets criteria for MetSyn, with almost half of adults over the age of 60 meeting criteria.1 Guidelines recommend management of MetSyn include lifestyle modifications, such as regular physical activity, reducing sedentary behaviors, and a healthy dietary pattern.32 These behaviors are also associated with a reduced risk for frailty. Fried criteria, such as weakness, gait speed, and low physical activity, can all be improved or prevented through regular physical activity as a woman ages. Diet is also associated with improvements in the maintenance of muscle strength and the ability to be active. The Multidomain Alzheimer’s Preventive Trial (MAPT) observed a slower increase in frailty metrics among participants randomized to a lifestyle intervention compared to usual care.33 In an ancillary study of Action for Health in Diabetes (Look AHEAD), an intensive lifestyle intervention was associated with a lower frailty index compared to the control group; 39.8% of the intervention group met criteria for frailty compared to 54.5% of the control group.34 Our findings, including the duration of MetSyn associated with the development of pre-frailty and frailty, suggest lifestyle interventions among younger or midlife women may lower risk for pre-frailty and frailty at relatively young ages.
Biological mechanisms linking MetSyn to frailty are likely related, in part, to chronic low-grade inflammation. Ample evidence links MetSyn to chronic inflammation, characterized by increases in oxidative stress and a pro-inflammatory environment.10,35 Higher waist circumference, a criterion for MetSyn, serves as a marker of visceral adiposity and is positively associated with inflammatory cytokines, including IL-6 and TNF-alpha. Higher levels of high-sensitivity CRP and fibrinogen are also observed among adults with MetSyn, both of which are associated with increased risk for CVD.36 Similarly, inflammatory markers suggest frailty is associated with a pro-inflammatory environment.37 Evidence suggests that inflammatory markers, such as IL-6, CRP, and TNF-alpha, are predictive of the development of frailty.35,38,39 Although we did not examine inflammatory biomarkers, future research to understand biological factors, such as inflammation, in understanding the association between MetSyn and frailty is warranted.
Our study has several strengths, including the ability to examine pre-frailty, the longitudinal follow-up with repeated measures of MetSyn, and the inclusion of sarcopenia in our assessment of frailty. However, limitations exist. Frailty was not assessed at every visit; therefore, we cannot examine possible bidirectional associations between frailty and MetSyn. We do not know if women taking metformin may have done so due to polycystic ovary syndrome (PCOS); however, the number of women in the SWAN cohort with PCOS is very small (<4% at study baseline). Our findings may not be generalizable to men and Hispanic women, who were excluded from this analysis. Finally, we examined the number of visits a woman met MetSyn criteria rather than consider year of first MetSyn diagnosis, since women may have met MetSyn criteria prior to the baseline visit or later visits. Thus, examining the number of visits provides a conservative indication of MetSyn across midlife into early older ages.
With the aging of the US population, the number of adults with frailty is projected to increase,31 highlighting the need to better understand frailty and its predictors. It is concerning that we observed women with MetSyn had a strong association with pre-frailty, not just frailty, and that women developed pre-frailty and frailty at relatively young ages. Interventions to prevent or manage pre-frailty can reduce the development of frailty.
Guidelines recommend management of MetSyn include lifestyle modifications, such as regular physical activity, reducing sedentary behaviors, and a healthy dietary pattern.32 These behaviors are also associated with a reduced risk for frailty. Fried criteria, such as weakness, gait speed, and low physical activity, can all be improved or prevented through regular physical activity as a woman ages. Diet is also associated with improvements in the maintenance of muscle strength and the ability to be active. The MAPT observed a slower increase in frailty metrics among participants randomized to a lifestyle intervention compared to usual care.33 In an ancillary study of Look AHEAD, an intensive lifestyle intervention was associated with a lower frailty indices compared to the control group; 39.8% of the intervention group met criteria for frailty compared to 54.5% of the control group.34
In summary, among this multiethnic cohort, women with MetSyn and those with a longer duration of MetSyn during midlife were significantly more likely to meet the criteria for pre-frailty or frailty in their 60s, suggesting an earlier onset of frailty among women with MetSyn. The association of MetSyn duration with pre-frailty and frailty suggests MetSyn can alert clinicians to younger women who are at higher risk for frailty as they age. Furthermore, the association of individual MetSyn criteria with pre-frailty and frailty will inform targeted interventions to improve these criteria and potentially prevent or reduce a woman’s risk of frailty.
Supplementary Material
Acknowledgments
Clinical Centers: University of Michigan, Ann Arbor, MI—Carrie Karvonen-Gutierrez, PI 2021—present, Siobán Harlow, PI 2011—2021, MaryFran Sowers, PI 1994-2011; Massachusetts General Hospital, Boston, MA—Sherri‐Ann Burnett‐Bowie, PI 2020—Present; Joel Finkelstein, PI 1999—2020; Robert Neer, PI 1994—1999; Rush University, Rush University Medical Center, Chicago, IL—Imke Janssen, PI 2020—Present; Howard Kravitz, PI 2009—2020; Lynda Powell, PI 1994—2009; University of California, Davis, Davis, CA/Kaiser—Elaine Waetjen and Monique Hedderson, PIs 2020—Present; Ellen Gold, PI 1994—2020; University of California, Los Angeles, Los Angeles, CA—Arun Karlamangla, PI 2020—Present; Gail Greendale, PI 1994—2020; Albert Einstein College of Medicine, Bronx, NY—Carol Derby, PI 2011—present, Rachel Wildman, PI 2010—2011; Nanette Santoro, PI 2004—2010; University of Medicine and Dentistry—New Jersey Medical School, Newark, NJ—Gerson Weiss, PI 1994—2004; and the University of Pittsburgh, Pittsburgh, PA—Rebecca Thurston, PI 2020—Present; Karen Matthews, PI 1994—2020.
NIH Program Office: National Institute on Aging, Bethesda, MD—Rosaly Correa-de-Araujo 2020 - present; Chhanda Dutta 2016- present; Winifred Rossi 2012–2016; Sherry Sherman 1994—2012; Marcia Ory 1994—2001; National Institute of Nursing Research, Bethesda, MD—Program Officers.
Central Laboratory: University of Michigan, Ann Arbor, MI—Daniel McConnell (Central Ligand Assay Satellite Services).
Coordinating Center: University of Pittsburgh, Pittsburgh, PA—Maria Mori Brooks, PI 2012 - present; Kim Sutton-Tyrrell, PI 2001—2012; New England Research Institutes, Watertown, MA—Sonja McKinlay, PI 1995—2001.
Steering Committee: Susan Johnson, Current Chair, Chris Gallagher, Former Chair
We thank the study staff at each site and all the women who participated in SWAN.
Contributor Information
Elizabeth A Jackson, Division of Cardiovascular Disease, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.
Carrie A Karvonen-Gutierrez, Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States.
Maria M Brooks, School of Public Health, Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Elsa Strotmeyer, School of Public Health, Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Brittney S Lange-Maia, Department of Family and Preventive Medicine and Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States.
Daniel H Solomon, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Michelle M Hood, Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States.
Carol A Derby, Department of Neurology and Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, United States.
Lewis A Lipsitz, (Medical Sciences Section).
Supplementary material
Supplementary material is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online.
Funding
The Study of Women’s Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the NIH Office of Research on Women’s Health (ORWH) (Grants U01NR004061, U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495, and U19AG063720). The contents of this manuscript are solely the responsibility of the authors and does not necessarily represent the official views of the NIA, NINR, ORWH, or the NIH.
Conflicts of interest
E.S. serves on the editorial board of the The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. The other authors declare no conflict of interest.
Data availability
SWAN provides access to public use datasets that include data from SWAN screening, the baseline visit and follow-up visits (https://agingresearchbiobank.nia.nih.gov/). To preserve participant confidentiality, some, but not all, of the data used for this manuscript are contained in the public use datasets. A link to the public use datasets is also located on the SWAN web site: http://www.swanstudy.org/swan-research/data-access/. Investigators who require assistance accessing the public use dataset may contact the SWAN Coordinating Center at the following email address: swanaccess@edc.pitt.edu.
Author contributions
Elizabeth A. Jackson, Carrie A. Karvonen-Gutierrez, Maria M. Brooks, and Carol A. Derby were responsible for the study concept and design. Carrie A. Karvonen-Gutierrez, Maria M. Brooks, and Carol A. Derby were responsible for the acquisition of subjects’ data. Elizabeth A. Jackson, Carrie A. Karvonen-Gutierrez, Maria M. Brooks, Elsa Strotmeyer, Brittney S. Lange-Maia, Daniel H. Solomon, Michelle M. Hood, and Carol A. Derby were responsible for data analysis, interpretation of the data, and preparation of the manuscript.
Sponsor’s role
The sponsor had no role in the design, methods, subject recruitment, data collection, analysis, and preparation of the paper.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
SWAN provides access to public use datasets that include data from SWAN screening, the baseline visit and follow-up visits (https://agingresearchbiobank.nia.nih.gov/). To preserve participant confidentiality, some, but not all, of the data used for this manuscript are contained in the public use datasets. A link to the public use datasets is also located on the SWAN web site: http://www.swanstudy.org/swan-research/data-access/. Investigators who require assistance accessing the public use dataset may contact the SWAN Coordinating Center at the following email address: swanaccess@edc.pitt.edu.