Secondary Logo

Journal Logo

Original Studies

Hand grip strength and health-related quality of life in postmenopausal women: a national population-based study

Hong, Yun Soo MD, MHS1; Kim, Hoon MD, PhD, NCMP2,3

Author Information
doi: 10.1097/GME.0000000000001863


After menopause, the risk for health problems, including cardiovascular disease (CVD) and osteoporosis, increases dramatically in women.1,2 In addition, postmenopausal women experience a gradual decline in muscle strength and physical function.3,4 Poor muscle strength is often related to worse prognosis among individuals with chronic conditions,5-7 and even among healthy individuals, it is associated with an increased risk of CVD and cardiovascular, cancer, and all-cause mortality.7-12 Moreover, loss of muscle strength leads to disability in daily living, higher dependency, and impaired physical performance and may eventually result in low health-related quality of life (HRQoL).13,14

HRQoL is an individual's perception of overall health status and function across physical, mental, and social aspects of life.15 It is commonly measured using questionnaires, such as the European Quality of Life Questionnaire - Five Dimensions (EQ-5D), which is a widely used self-administered questionnaire validated in many countries and languages.16 Various physical and psychological changes during menopause, including vasomotor symptoms and depression, have a negative effect on HRQoL in menopausal women regardless of age, menopausal symptoms, and other sociodemographic factors.17-20

Hand grip strength (HGS) is a noninvasive and useful measure to assess the overall strength of muscle. It has been widely accepted as a biomarker of aging and general health status21 as it is positively associated with physical function, bone mineral density, and cardiovascular health and inversely associated with mortality.7,9,21 In postmenopausal women, HGS is also positively associated with body composition, such as waist-to-hip ratio and waist circumference.22-24 Moreover, low HGS is negatively associated with HRQoL in various populations, including elderly individuals,13,25,26 cancer survivors,27 and hip fracture patients.28

Although both HGS and HRQoL, particularly the physical functioning aspects, decline after menopause, the associations between muscle strength and HRQoL in postmenopausal women have not been fully understood. Therefore, we aimed to investigate the associations between HGS and EQ-5D using nationally representative data.


Study population

The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationally representative cross-sectional survey that has aimed to evaluate the health and nutritional status of the general population of Korea since 1998. We used data from 21,362 women who were included in the survey between 2014 and 2018 when both HGS and EQ-5D were measured (Fig. 1). We excluded participants <40 years old (n = 8,598) or ≥80 years old (n = 875). We then excluded women who were premenopausal (n = 3,074), did not know their menstrual status (n = 1,273), or were breastfeeding (n = 5) or pregnant (n = 3) at the time of participation. As women who underwent surgical menopause might have subsequent morbidities different from women with natural menopause,29,30 we only included women who had natural menopause, further excluding women who had a history of hysterectomy or bilateral oophorectomy (artificial menopause; n = 968). In the KNHANES, menopausal status was classified only into natural menopause and artificial menopause. Artificial menopause might have meant previous hysterectomy or bilateral oophorectomy, but information about the causes of artificial menopause was not available. Therefore, only women with natural menopause were included in our study.

FIG. 1
FIG. 1:
Flow chart of study participants. EQ-5D, European Quality of Life Questionnaire-Five Dimensions; HGS, hand grip strength.

Among 6,566 participants, we further excluded 507 women who did not perform HGS measurements and/or did not respond to the EQ-5D questionnaire. A total of 6,059 women who were 40 to 79 years old and had experienced natural menopause were included in our study.

Ethics approval and informed consent

The institutional review board at the Korea Center for Disease Control and Prevention approved the sixth and seventh KNHANES (KNHANES VI-VII), 2014 to 2018 (Approval No. 2013-12EXP-03-5C and 2018-01-03-P-A). All study participants provided informed consent before participation, and the study was performed following the ethical principles of the Declaration of Helsinki. The institutional review board of the Seoul National University Hospital waived ethical approval due to the retrospective nature of our study and because all the data were publicly available.

HGS measurement

In the KNHANES, HGS has been measured since 2014. Participants missing an arm, hand, or thumb or wearing a cast on the wrist or hand were exempt from testing. HGS was evaluated with a digital hand dynamometer (Digital Grip Strength Dynamometer, T.K.K.5401, Takei Scientific Instruments Co., Tokyo, Japan) under a standardized protocol according to the manual by Korean Centers for Disease Control and Prevention.31 The participants were asked to squeeze the dynamometer with full force for 3 seconds while standing with their feet apart at hip-width and their toes pointing forward. The participants were also instructed so that the dynamometer and the hand did not touch the body. HGS was measured three times on each side, alternating between right and left hands. Between measurements, the participants were allowed to rest for at least 60 seconds. In the analysis, we used the maximum value of the six measurements, regardless of which hand it was measured with, and rounded up to the nearest 0.1 kilograms. The intraclass correlation coefficient (ICC) for HGS across the measurements were 0.98 (95% CI 0.92-0.99) and 0.95 (95% CI 0.83-0.99) for the right and left sides, respectively. HGS was further categorized into quintiles and deciles based on the complex survey design.

Assessment of HRQoL

The EQ-5D is a short, generic self-report questionnaire designed to evaluate the HRQoL.16 It has been validated in many countries and widely used with country-specific EQ-5D value sets. In the KNHANES, the EQ-5D was initially adopted in 2005 to assess the overall HRQoL of study participants. The EQ-5D measures five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. For each dimension, the participants selected one of the three possible responses that best described their current health status: having “no problems,” “moderate problems,” or “severe problems.” We categorized the responses as having either no problems or moderate/severe problems as the number of participants with severe problems was small (range: 21-261). The EQ-5D index, a single index continuous value reflecting the overall health status, can be calculated using the estimated weighted quality value developed for Koreans.32 The EQ-5D index can range from −0.171 to 1 in the Korean population.33 A value of 1 indicates the best health status while 0 and negative values correspond to death and health status worse than death, respectively.34 In our analysis, the EQ-5D index was multiplied by 100 to improve interpretability and the transformed index ranged from −17.1 to 100.

Measurement of covariates

Residential area (rural or urban), education level (elementary school and below, middle school, high school, or college graduates), and income level were collected by trained staff using a standardized questionnaire. Income levels were classified into quintiles based on monthly average household income. Smoking status was categorized into current smoker, former smoker, or never-smoker. High-risk alcohol consumption was defined as ≥5 drinks/time and ≥2 times/wk. Physical activity was assessed based on self-report and categorized into minimal (< 3.0 metabolic equivalents (METs)), moderate (3.0-6.0 METs), and vigorous (> 6 METs) physical activity. Years since menopause were determined by subtracting the age at menopause from the age at screening. Body mass index (BMI) was defined as body weight (kg) divided by height in meters squared (m2).

Prevalent chronic disease was defined as the presence of any of the following chronic conditions: stroke, coronary heart disease, diabetes, chronic obstructive pulmonary disease (COPD), asthma, arthritis, chronic kidney disease (CKD) ≥ stage 3a, or history of any type of cancer. Diabetes was defined as a self-reported physician's diagnosis of diabetes, the use of an oral hypoglycemic agent or insulin, fasting plasma glucose levels ≥126 mg/dL, or hemoglobin A1c levels ≥ 6.5%. Coronary heart disease was defined by a self-report of a history of angina pectoris or prior myocardial infarction. Stroke, COPD, and asthma were also based on self-report. Arthritis included a self-report of any type of arthritis, including osteoarthritis and rheumatoid arthritis. CKD was determined as an estimated glomerular filtration rate (eGFR) ≤60 mL/min/1.73m2, ie, CKD stage 3a based on the CKD Epidemiology (CKD-EPI) Collaboration equation.35

Statistical analyses

The KNHANES is based on stratified multistage probability sampling to represent the general population of South Korea. To account for complex, stratified, multistage sampling procedures, we conducted all analyses using survey weights developed by the KNHANES.

Weighted means and standard errors (SEs) are reported for continuous variables. Absolute numbers and weighted proportions are reported for categorical variables. Baseline participant characteristics were compared across quintiles of HGS using analysis of variance (ANOVA), univariable linear regression models, or Rao-Scott chi-square tests, as appropriate.

The main outcomes of the study were the presence of moderate/severe problems in each dimension of the EQ-5D and the EQ-5D index. The primary exposure was scaled HGS (HGS divided by its standard deviation [SD]) to allow comparison of the magnitude of the association between HGS and EQ-5D across different dimensions. We used HGS categorized into quintiles as an additional exposure metric.

To estimate the prevalence ratios (PRs) and 95% confidence intervals (CIs) of having moderate/severe problems in each dimension of the EQ-5D by HGS, we used Poisson regression with the linearized variance estimator. Multivariable Poisson regression analysis was conducted with progressive degrees of adjustment. Model 1 was controlled for age and BMI; Model 2 was further adjusted for years since menopause; Model 3 was further adjusted for lifestyle factors, including education, income, alcohol consumption, smoking status, and physical activity; Model 4 was further adjusted for the presence of each of the chronic diseases. The covariates were selected based on previous studies that investigated the associations of menopausal status and HRQoL,36 or the associations of HGS and HRQoL.7,9,10,13,14,37,38 We identified potential confounders, defined as variables associated with both the exposure (HGS) and the outcome (HRQoL), and are not intermediate variables in the exposure–outcome relationship based on prior clinical and biological knowledge and descriptive statistics. After running the analysis of every model, we performed the Wald test to assess the significance of each predictor. In addition, to better understand the dose–response relationship, we used deciles of HGS and plotted them against the adjusted prevalence of moderate/severe problems in each dimension of the EQ-5D. As a sensitivity analysis, we repeated the same analyses after excluding participants with primary ovarian insufficiency (POI, age at menopause ≤40; n = 117) because POI might negatively impact HRQoL or psychosocial well-being.39-42 In addition, we performed subgroup analyses using predefined characteristics because the association of HGS with HRQoL may be different by levels of covariates. The subgroup analysis allows us to identify a more susceptible population based on participant characteristics, and the overall estimate without subgroup analysis may miss this significant association. Therefore, we performed stratified analyses by age (<65 and 65-79 y), BMI (< 25 and ≥ 25 kg/m2), physical activity (low and moderate-to-high), years since menopause (<10 y and ≥ 10 y), and presence of any chronic disease. The cut-off values were chosen based on clinical knowledge.

All statistical analyses were performed at the statistical significance level of 0.05 and using Stata 15 (StataCorp LLC, College Station, TX) and R 4.0.2 (R Foundation, Vienna, Austria).


In the KNHANES from 2014 to 2018, a total of 6,059 postmenopausal women aged 40 and 79 years performed the HGS test and responded to the EQ-5D questionnaire, representing an estimated population of 6,207,365 postmenopausal women accounting for the complex sampling and weighting methods used. The mean age (SE) of the participants was 62.4 (0.1) years, and the mean grip strength was 23.1 (0.1) kg (Table 1). The prevalence of having moderate/severe problems in any one of the five EQ-5D dimensions was 43.6%, with the highest and lowest prevalence for the pain/discomfort dimension (33.2%) and self-care dimension (5.3%), respectively. Compared with the participants in the lowest HGS quintile, the women in the higher HGS quintiles were younger, had fewer years since menopause, and had a lower prevalence of chronic diseases. The women with high HGS were also more likely to be involved in moderate-to-vigorous physical activity and to be high-risk drinkers. The prevalence of moderate/severe problems was lower in each dimension of the EQ-5D with increasing quintiles of HGS.

TABLE 1 - Baseline characteristics of study participants in the Korea National Health and Nutrition Examination Survey (2014-2018)
All Grip strength
Characteristic 1st quintile (lowest) 2nd 3rd 4th 5th quintile (highest)
No. of participants 6,059 1,311 1,264 1,206 1,150 1,128
Age, y 62.4 ± 0.1 67.8 ± 0.3 64.2 ± 0.3 61.4 ± 0.3 60.7 ± 0.2 58.0 ± 0.2
BMI, kg/m2 24.1 ± 0.1 24.1 ± 0.1 24.0 ± 0.1 24.0 ± 0.1 24.1 ± 0.1 24.3 ± 0.1
Years since menopause, years 12.4 ± 0.2 18.4 ± 0.4 14.3 ± 0.3 11.4 ± 0.3 10.2 ± 0.3 7.9 ± 0.2
Residence (urban area), % 4,725 (81.3%) 934 (75.0%) 995 (81.7%) 957 (82.4%) 935 (84.1%) 904 (83.3%)
Education, %
 ≤Elementary school 2,767 (41.4%) 862 (62.0%) 642 (48.2%) 505 (35.7%) 425 (34.3%) 333 (26.5%)
 Middle school 1,068 (18.1%) 183 (14.8%) 213 (17.4%) 213 (18.7%) 247 (21.0%) 212 (18.8%)
 High school 1,472 (27.2%) 172 (15.1%) 263 (22.3%) 320 (31.2%) 319 (29.5%) 398 (37.8%)
 ≥ College 745 (13.2%) 92 (7.8%) 146 (12.0%) 166 (14.2%) 158 (15.2%) 183 (16.7%)
 No response 7 (0.1%) 2 (0.2%) 0 2 (0.1%) 1 (0.05%) 2 (0.2%)
 Lower 1,150 (19.0%) 299 (23.1%) 251 (20.6%) 217 (18.4%) 213 (18.2%) 170 (14.9%)
 Lower-middle 1,176 (19.0%) 285 (21.7%) 253 (18.8%) 217 (18.0%) 201 (17.1%) 220 (19.5%)
 Middle 1,236 (20.2%) 251 (18.5%) 241 (18.6%) 253 (20.5%) 258 (22.3%) 233 (21.0%)
 Upper-middle 1,216 (20.0%) 237 (18.1%) 247 (19.9%) 257 (21.2%) 221 (19.3%) 254 (21.6%)
 Upper 1,258 (21.1%) 234 (17.8%) 268 (21.5%) 258 (21.6%) 253 (22.2%) 245 (22.4%)
 No response 23 (0.7%) 5 (0.9%) 4 (0.6%) 4 (0.4%) 4 (0.9%) 6 (0.6%)
Smoking status, %
 Never 5,651 (92.9%) 1,212 (92.0%) 1,170 (93.3%) 1,137 (93.2%) 1,068 (92.3%) 1,064 (93.8%)
 Former 153 (2.4%) 38 (3.0%) 40 (2.9%) 19 (1.5%) 32 (2.4%) 24 (2.2%)
 Current 197 (3.7%) 42 (3.6%) 36 (2.4%) 42 (4.5%) 41 (4.2%) 36 (3.7%)
 No response 58 (1.0%) 19 (1.4%) 18 (1.5%) 8 (0.8%) 9 (1.0%) 4 (0.3%)
High-risk alcohol drinking 148 (2.9%) 15 (1.5%) 30 (3.0%) 31 (2.6%) 20 (1.9%) 52 (5.6%)
Moderate-to-vigorous exercise, % 1,908 (33.4%) 289 (23.1%) 375 (31.1%) 387 (34.3%) 397 (36.7%) 460 (42.1%)
Hypertension 2,796 (42.8%) 735 (53.4%) 610 (45.2%) 543 (41.3%) 482 (39.1%) 426 (34.6%)
Diabetes mellitus 1,059 (16.6%) 312 (23.0%) 242 (18.2%) 179 (14.3%) 171 (14.2%) 155 (13.0%)
Stroke 189 (2.8%) 75 (4.7%) 49 (4.1%) 24 (1.6%) 21 (1.7%) 20 (2.0%)
Coronary heart disease 233 (3.4%) 78 (5.2%) 53 (3.8%) 44 (3.2%) 36 (2.9%) 22 (1.8%)
Asthma 247 (3.9%) 71 (5.2%) 60 (4.8%) 40 (3.1%) 41 (3.6%) 35 (2.8%)
Chronic obstructive pulmonary disease 33 (0.5%) 7 (0.5%) 9 (0.7%) 5 (0.5%) 6 (0.5%) 6 (0.3%)
Arthritis 1,927 (29.7%) 565 (40.5%) 438 (34.3%) 368 (27.7%) 311 (26.2%) 245 (19.7%)
Chronic kidney disease ≥ stage 3a 252 (3.6%) 91 (6.8%) 60 (4.3%) 55 (3.2%) 24 (2.3%) 22 (1.4%)
History of cancer 453 (7.4%) 100 (7.9%) 113 (9.1%) 82 (7.1%) 85 (7.0%) 73 (6.0%)
EQ-5D (moderate/severe problem)
 Any 2,729 (43.6%) 785 (57.4%) 621 (47.9%) 500 (41.1%) 456 (39.1%) 367 (32.1%)
 Mobility 1,563 (23.6%) 549 (38.9%) 370 (27.2%) 268 (21.1%) 218 (18.1%) 158 (12.6%)
 Self-care 374 (5.3%) 158 (11.0%) 94 (6.1%) 60 (4.4%) 34 (2.9%) 28 (2.1%)
 Usual activities 807 (11.9%) 303 (21.4%) 191 (13.3%) 135 (10.0%) 112 (9.5%) 66 (5.0%)
 Pain/ discomfort 2,066 (33.2%) 584 (42.5%) 468 (36.7%) 400 (33.4%) 340 (29.6%) 274 (23.8%)
 Anxiety/ depression 895 (14.1%) 256 (18.2%) 206 (15.2%) 169 (13.2%) 137 (11.6%) 127 (12.1%)
EQ-5D index 0.916 ± 0.002 0.863 ± 0.005 0.905 ± 0.004 0.925 ± 0.004 0.934 ± 0.004 0.952 ± 0.003
EQ-5D index × 100 91.6 ± 0.2 86.3 ± 0.5 90.5 ± 0.4 92.5 ± 0.4 93.4 ± 0.4 95.2 ± 0.3
Mean grip strength, kg 23.1 ± 0.1 16.3 ± 0.1 20.8 ± 0.0 23.2 ± 0.0 23.7 ± 0.0 29.6 ± 0.1
Range of grip strength 7.1-39.7 7.1-19.2 19.3-22.0 22.1-24.3 24.4-27.0 27.1-39.7
Values are presented as mean ± standard error (SE) or number (weighted %) except the range of grip strength.BMI, body mass index; EQ-5D, EuroQoL-5 dimensions.

An increase of 1 SD in HGS (4.78 kg) was associated with a 7% to 28% lower prevalence of moderate/severe problems in each dimension of the EQ-5D (Table 2) after controlling for demographic factors, lifestyle and reproductive factors, and medical history. More specifically, the fully adjusted prevalence of having moderate/severe problems was significantly lower in four of the five dimensions of the EQ-5D: mobility (PR 0.90, 95% CI 0.85-0.95), self-care (PR 0.72, 95% CI 0.64-0.81), usual activities (PR 0.83, 95% CI 0.77-0.90), and pain/discomfort (PR 0.91, 95% CI 0.87-0.95). The association was marginally significant for the anxiety/depression dimension (PR 0.93, 95% CI 0.85-1.00). Higher scaled HGS was also associated with a higher overall EQ-5D index (PR 1.39, 95% CI 0.97-1.81).

TABLE 2 - The association of hand grip strength (scaled) with adjusted prevalence of moderate/severe problem in each dimension of EQ-5D and adjusted EQ-5D index
Domain Model 1 Model 2 Model 3 Model 4
Mobility problem 0.85 (0.80-0.90) 0.85 (0.80-0.90) 0.88 (0.84-0.94) 0.90 (0.85-0.95)
Self-care problem 0.67 (0.59-0.75) 0.67 (0.59-0.75) 0.70 (0.62-0.79) 0.72 (0.64-0.81)
Usual activities problem 0.78 (0.71-0.85) 0.78 (0.71-0.85) 0.81 (0.74-0.89) 0.83 (0.77-0.91)
Pain/ discomfort 0.88 (0.84-0.92) 0.88 (0.84-0.92) 0.89 (0.85-0.94) 0.91 (0.87-0.95)
Anxiety/ depression 0.87 (0.81-0.95) 0.88 (0.81-0.96) 0.91 (0.84-0.99) 0.93 (0.85-1.00)
EQ-5D index 0.020 (0.015-0.024) 0.019 (0.014-0.023) 0.016 (0.012-0.020) 0.014 (0.010-0.018)
EQ-5D index × 100 1.96 (1.52-2.40) 1.87 (1.43-2.32) 1.60 (1.18-2.03) 1.39 (0.97-1.81)
Model 1: adjusted for age and body mass index; Model 2: further adjusted for years since menopause; Model 3: further adjusted for living in urbanicity, education level, income level, smoking, alcohol drinking, and physical activity; Model 4: further adjusted for chronic diseases including diabetes, stroke, coronary heart disease, asthma, chronic obstructive pulmonary disease, arthritis, chronic kidney disease, and history of cancer. EQ-5D, EuroQoL-5 dimensions.

When we categorized HGS into quintiles, the fully adjusted PRs of having moderate/severe problems were significantly lower in postmenopausal women with the highest quintile of HGS than in those with the lowest quintile across all dimensions except anxiety/depression (Table 3): mobility (PR 0.73, 95% CI 0.60-0.89), self-care (PR 0.45, 95% CI 0.28-0.72), usual activity (PR 0.52, 95% CI 0.38-0.71), and pain/discomfort (PR 0.74, 95% CI 0.64-0.87). In addition, there was a significant trend of a lower prevalence of moderate/severe problems on the EQ-5D with increasing HGS (P for trend <0.001), except for the anxiety/depression dimension (Table 3). Similarly, the adjusted probability of having moderate/severe problems was inversely associated with HGS in a dose–response relationship (Fig. 2).

TABLE 3 - The association of hand grip strength (in quintiles) with adjusted prevalence of moderate/severe problem in each dimension of EQ-5D and adjusted EQ-5D index
Variable Model 1 P for trend Model 2 P for trend Model 3 P for trend Model 4 P for trend
Mobility problem
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref 0.001
 2nd quintile 0.90 (0.79-1.02) 0.89 (0.79-1.01) 0.93 (0.82-1.05) 0.92 (0.82-1.04)
 3rd quintile 0.83 (0.72-0.96) 0.84 (0.72-0.97) 0.90 (0.78-1.04) 0.92 (0.80-1.06)
 4th quintile 0.76 (0.64-0.89) 0.76 (0.64-0.90) 0.81 (0.69-0.95) 0.84 (0.71-0.98)
 5th quintile (highest) 0.63 (0.51-0.77) 0.63 (0.51-0.77) 0.70 (0.57-0.86) 0.73 (0.60-0.89)
Self-care problem
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref <0.001
 2nd quintile 0.72 (0.55-0.95) 0.72 (0.54-0.95) 0.76 (0.57-1.00) 0.76 (0.57-1.01)
 3rd quintile 0.63 (0.45-0.90) 0.64 (0.45-0.90) 0.69 (0.49-0.98) 0.73 (0.52-1.04)
 4th quintile 0.44 (0.29-0.65) 0.44 (0.29-0.66) 0.48 (0.32-0.72) 0.50 (0.33-0.75)
 5th quintile (highest) 0.38 (0.24-0.62) 0.39 (0.24-0.63) 0.44 (0.27-0.70) 0.45 (0.28-0.72)
Usual activities problem
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref <0.001
 2nd quintile 0.78 (0.65-0.95) 0.77 (0.64-0.94) 0.80 (0.66-0.97) 0.80 (0.66-0.97)
 3rd quintile 0.70 (0.56-0.89) 0.71 (0.56-0.90) 0.77 (0.61-0.96) 0.80 (0.64-1.01)
 4th quintile 0.71 (0.55-0.92) 0.71 (0.55-0.93) 0.77 (0.60-0.99) 0.81 (0.63-1.04)
 5th quintile (highest) 0.44 (0.32-0.60) 0.44 (0.32-0.61) 0.49 (0.36-0.68) 0.52 (0.38-0.71)
Pain/ discomfort
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref <0.001
 2nd quintile 0.93 (0.84-1.04) 0.93 (0.84-1.04) 0.96 (0.86-1.07) 0.95 (0.86-1.06)
 3rd quintile 0.90 (0.79-1.02) 0.90 (0.79-1.02) 0.93 (0.82-1.06) 0.95 (0.84-1.08)
 4th quintile 0.80 (0.70-0.93) 0.81 (0.70-0.93) 0.84 (0.73-0.96) 0.86 (0.75-0.98)
 5th quintile (highest) 0.68 (0.58-0.79) 0.68 (0.58-0.79) 0.71 (0.61-0.84) 0.74 (0.64-0.87)
Anxiety/ depression
 1st quintile (lowest) Ref 0.01 Ref 0.02 Ref 0.11 Ref 0.22
 2nd quintile 0.88 (0.73-1.07) 0.90 (0.74-1.09) 0.93 (0.77-1.13) 0.92 (0.76-1.12)
 3rd quintile 0.81 (0.65-0.99) 0.82 (0.66-1.02) 0.88 (0.70-1.09) 0.90 (0.72-1.11)
 4th quintile 0.71 (0.57-0.90) 0.73 (0.58-0.93) 0.78 (0.62-0.98) 0.79 (0.63-0.99)
 5th quintile (highest) 0.78 (0.60-1.00) 0.80 (0.62-1.03) 0.88 (0.68-1.13) 0.91 (0.70-1.18)
EQ-5D index
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref <0.001
 2nd quintile 0.026 (0.014-0.039) 0.025 (0.012-0.038) 0.021 (0.009-0.034) 0.021 (0.009-0.033)
 3rd quintile 0.036 (0.023-0.048) 0.033 (0.020-0.046) 0.028 (0.015-0.040) 0.024 (0.012-0.037)
 4th quintile 0.042 (0.029-0.055) 0.039 (0.025-0.052) 0.033 (0.021-0.046) 0.030 (0.017-0.042)
 5th quintile (highest) 0.051 (0.038-0.063) 0.048 (0.036-0.061) 0.040 (0.028-0.052) 0.035 (0.023-0.047)
EQ-5D index × 100
 1st quintile (lowest) Ref <0.001 Ref <0.001 Ref <0.001 Ref <0.001
 2nd quintile 2.65 (1.39-3.90) 2.49 (1.22-3.77) 2.12 (0.89-3.36) 2.10 (0.89-3.31)
 3rd quintile 3.55 (2.26-4.84) 3.31 (2.01-4.62) 2.77 (1.51-4.03) 2.44 (1.22-3.67)
 4th quintile 4.18 (2.87-5.50) 3.87 (2.53-5.21) 3.33 (2.06-4.60) 2.98 (1.74-4.22)
 5th quintile (highest) 5.07 (3.82-6.31) 4.81 (3.56-6.06) 4.04 (2.84-5.25) 3.53 (2.34-4.72)
Model 1: adjusted for age and body mass index; Model 2: further adjusted for years since menopause; Model 3: further adjusted for living in urbanicity, education level, income level, smoking, alcohol drinking, and physical activity; Model 4: further adjusted for chronic diseases including diabetes, stroke, coronary heart disease, asthma, chronic obstructive pulmonary disease, arthritis, chronic kidney disease, and history of cancer.

FIG. 2
FIG. 2:
Probability of moderate/severe problem on each domain of EQ-5D according to the deciles of grip strength. (A) Mobility problem. (B) Self-care problem. (C) Usual activities problem. (D) Pain/discomfort. (E) Anxiety/depression. Footnotes: Adjusted for age and BMI, years since menopause, living in urbanicity, education level, income level, smoking, alcohol drinking, physical activity, and chronic diseases including diabetes, stroke, coronary heart disease, asthma, chronic obstructive pulmonary disease, arthritis, chronic kidney disease, and history of cancer.

In the subgroup analysis, the association between HGS and the EQ-5D index was more substantial among participants who were older (65-79 y), had a higher BMI (≥ 25.0 kg/m2), had low physical activity, had a longer duration since menopause (≥ 10 y), and had a chronic disease (Fig. 3). The results were similar after excluding participants who experienced POI (Supplementary Tables 1-2, and Supplementary Figure 1,

FIG. 3
FIG. 3:
The association between hand grip strength (scaled) and adjusted EQ-5D index by predefined subgroups. Footnotes: Adjusted for age and BMI, years since menopause, living in urbanicity, education level, income level, smoking, alcohol drinking, and physical activity. Chronic diseases are defined as having any of diabetes, stroke, coronary heart disease, asthma, chronic obstructive pulmonary disease, arthritis, chronic kidney disease, and history of cancer.


In this nationally representative population study, higher HGS was associated with a lower prevalence of moderate/severe problems on HRQoL, measured using the EQ-5D, in postmenopausal women. In particular, the prevalence of moderate/severe problems on HRQoL was 9% to 55% lower in participants with the highest quintile of HGS compared to those with the lowest quintile after adjusting for all covariates. To the best of our knowledge, this is the largest study to date investigating the association between HGS and HRQoL in postmenopausal women.

HRQoL is a multidimensional concept of self-assessed quality of life encompassing physical and psychological aspects that can affect health. Several useful tools have been developed to evaluate multiple components of HRQoL, primarily based on physical health and psychological aspects.16,43,44 Among them, the EQ-5D is simple and straightforward.45 The EQ-5D was developed as a self-administered questionnaire to measure general health status, including physical functioning in daily living and mental health. Various physical and psychological changes during menopause have a negative effect on HRQoL in menopausal women. For instance, compared to premenopausal women, those in the late perimenopausal or postmenopausal stage had reduced physical functioning,46 and those who had menopause for 2 to 5 years were more likely to experience problems of mobility and had lower overall HRQoL.47 In a longitudinal study of middle-aged women, menopause was negatively associated with quality of life in both physical and mental aspects, regardless of the presence of menopausal symptoms.18

Muscle strength declines with age, and in women, the decline in muscle strength is accelerated around menopause.48 HGS is a surrogate measure of overall muscle strength and physical function. Lower HGS has been associated with increased CVD incidence and all-cause, cardiovascular, and cancer mortality.7,9,10,12 Lower HGS has also been associated with more inferior quality of life, particularly in older adults.13,14,37,38 Although menopause itself is related to worsening quality of life,17,49 whether muscle strength is associated with HRQoL has not been studied very well in postmenopausal women. We, therefore, examined the association between HGS and HRQoL among middle-aged women who had natural menopause.

In this study, there was a strong inverse association between HGS and the probability of having problems on the EQ-5D on the physical health or pain dimensions. The presence of physical dysfunction or pain may be directly associated with limited muscle strength, precluding individuals from performing well on the HGS test. On the other hand, the association was weaker on the anxiety/depression dimension. Other studies evaluating the association between HGS and psychological problems using the EQ-5D or the Short Form (SF-36) Health Survey in older men and women also did not find any significant associations.13,38 HGS and psychological problems may have a more complex relationship. First, although the prevalence of moderate/severe anxiety/depression was significantly higher in individuals with low HGS, the association was attenuated after adjusting for chronic disease. Second, it is possible that anxiety or depressive symptoms are only perceived at a much lower level of muscle strength compared to other dimensions. Further studies with a wider range of HGS in diverse populations are needed to better understand the relationships between HGS and psychological problems.

HGS is a noninvasive and straightforward measure of muscle strength, but there is no single best cutoff that reflects overall muscle strength or predicts health outcomes.50-52 In this study, we used several different metrics, including scaled HGS (HGS divided by SD) and HGS categorized in quintiles and deciles (every 10th percentile). In all analyses, the probability of having problems in each dimension of the EQ-5D tended to decrease with increasing HGS. Moreover, even a small improvement in HGS (from the 1st decile [7.1-16.9 kg] to the 2nd decile [17.0-19.2 kg]) was related to lower prevalence of having problems on HRQoL. In addition, less physically active women had a stronger association between HGS and the EQ-5D than women who were physically active, suggesting implications of physical exercise on the EQ-5D.

In ongoing representative surveys, such as the KNHANES, multicycle data analysis is recommended because data accumulated over several cycles could provide adequate estimates.53 Our study includes all available data from 5 years, and it is the largest study on the association between HGS and HRQoL. In addition, the collection of numerous critical variables enabled us to adjust for multiple potential confounders, including various chronic diseases, and to perform subgroup analyses. Most previous studies, on the other hand, either did not account for comorbidities38,54 or excluded individuals with pre-existing conditions from the research, restricting the investigation only to healthy individuals.37 However, in this study, chronic diseases were associated with both HGS and HRQoL, and the adjustment for chronic disease is necessary in studies evaluating the association between HGS and HRQoL. Additionally, when we performed a stratified analysis according to the presence of chronic disease, HGS was significantly more strongly associated with the EQ-5D index in women with chronic disease compared to those without chronic disease.

It seems to be worthy of considering nation-specific patterns in a HRQoL study. Since the Korean War (1950-1953), the national economy of South Korea has grown rapidly. The gross national income per capita has increased from 67 US dollars (USD) in the early 1950s to 30,000 USD in 2018.55 During those years, South Korea has also rapidly adopted a westernized lifestyle and experienced dramatic urbanization and an increase in life expectancy. For example, in our study, the proportion of urban residents is over 80%, and the life expectancy of a female baby born in 2030 will be over 86.7 years with a 90% probability.56 Despite the rapid economic expansion and health promotion, Korean people are, on average, less satisfied with their life, compared to the other countries in the Organization for Economic Co-operation and Development (OECD) (5.9 vs. 6.5).57 In addition, only one-third of Koreans reported that they were in good health, which was the lowest among the OECD countries (on average, 69% of the population in the OECD countries reported being in good health).57 On the other hand, in a study comparing population norms of HRQoL using EQ-5D across national representative surveys, Korea reported the lowest prevalence of having problems, particularly in mobility, self-care, and usual activities domains.58 Collectively, there may be some differences in the perception of HRQoL across different cultures, countries, and HRQoL metrics.

There are several shortcomings to our study. First, the KNHANES is a cross-sectional study, and we cannot assume a temporal and causal association between HGS and HRQoL. Participants having problems in the EQ-5D dimensions may have debilitating conditions that may be associated with poorer muscle strength, and it may be reflected as lower HGS (reverse causation). Although the association between HGS and HRQoL persisted even after accounting for the presence of comorbid conditions, the findings in the present study do not indicate causality, and therefore, should be interpreted with caution. Second, HRQoL is a broad concept, and the EQ-5D may not capture all aspects of an individual's HRQoL. Several tools have been developed to assess HRQoL,59 but there is no single tool that performs better than others in reflecting HRQoL, and their performance may be population-specific.43 The EQ-5D, however, has been validated and widely used to measure HRQoL in the general population in many countries.60-63 Also, it is a relatively simple, short method and more feasible to apply in a national survey such as the KNHANES. Finally, information about the use of hormone therapy was not available in this study because questions on hormone therapy had no longer been included in the KNHANES since 2013. However, previous studies reported that hormone therapy did not protect against grip strength decline in postmenopausal women64-66 nor was associated with improvements in HRQoL.36,67-69 Therefore, hormone therapy might not have had an effect on HRQoL in the present study.

There are several strengths to our study. First, our study comprised over 6,000 postmenopausal women, which can be generalized to over 6 million Korean postmenopausal women. Second, the large scale of the study and standardized collection of demographic, lifestyle, and comorbidity information enabled us to perform multivariable analysis to control for multiple potential confounders and to perform subgroup analyses.


In summary, higher HGS was associated with a lower prevalence of having moderate/severe problems in each dimension of the EQ-5D in postmenopausal women. The association was more apparent in individuals who were older, had higher BMI, or had a chronic disease. Whether interventions to increase HGS may improve HRQoL in postmenopausal women needs to be further investigated in large prospective trials.


1. Becker RC. Cardiology patient page. Heart attack and stroke prevention in women. Circulation 2005; 112:e273–e275.
2. Crandall CJ, Aragaki A, Cauley JA, et al. Associations of menopausal vasomotor symptoms with fracture incidence. J Clin Endocrinol Metab 2015; 100:524–534.
3. Bondarev D, Laakkonen EK, Finni T, et al. Physical performance in relation to menopause status and physical activity. Menopause 2018; 25:1432–1441.
4. Sowers M, Pope S, Welch G, Sternfeld B, Albrecht G. The association of menopause and physical functioning in women at midlife. J Am Geriatr Soc 2001; 49:1485–1492.
5. Hamasaki H, Kawashima Y, Katsuyama H, Sako A, Goto A, Yanai H. Association of handgrip strength with hospitalization, cardiovascular events, and mortality in Japanese patients with type 2 diabetes. Sci Rep 2017; 7:7041.
6. Lai S, Muscaritoli M, Andreozzi P, et al. Sarcopenia and cardiovascular risk indices in patients with chronic kidney disease on conservative and replacement therapy. Nutrition 2019; 62:108–114.
7. Rantanen T, Guralnik JM, Foley D, et al. Midlife hand grip strength as a predictor of old age disability. JAMA 1999; 281:558–560.
8. Leong DP, Teo KK, Rangarajan S, et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet 2015; 386:266–273.
9. Sasaki H, Kasagi F, Yamada M, Fujita S. Grip strength predicts cause-specific mortality in middle-aged and elderly persons. Am J Med 2007; 120:337–342.
10. Stessman J, Rottenberg Y, Fischer M, Hammerman-Rozenberg A, Jacobs JM. Handgrip strength in old and very old adults: mood, cognition, function, and mortality. J Am Geriatr Soc 2017; 65:526–532.
11. Volaklis KA, Halle M, Meisinger C. Muscular strength as a strong predictor of mortality: a narrative review. Eur J Intern Med 2015; 26:303–310.
12. Wu Y, Wang W, Liu T, Zhang D. Association of grip strength with risk of all-cause mortality, cardiovascular diseases, and cancer in community-dwelling populations: a meta-analysis of prospective cohort studies. J Am Med Dir Assoc 2017; 18:551 e517–551 e535.
13. Sayer AA, Syddall HE, Martin HJ, Dennison EM, Roberts HC, Cooper C. Is grip strength associated with health-related quality of life? Findings from the Hertfordshire Cohort Study. Age Ageing 2006; 35:409–415.
14. Syddall HE, Martin HJ, Harwood RH, Cooper C, Aihie Sayer A. The SF-36: a simple, effective measure of mobility-disability for epidemiological studies. J Nutr Health Aging 2009; 13:57–62.
15. Woods NF, Utian W. Quality of life, menopause, and hormone therapy: an update and recommendations for future research. Menopause 2018; 25:713–720.
16. Devlin NJ, Brooks R. EQ-5D and the EuroQol Group: past, present and future. Appl Health Econ Health Policy 2017; 15:127–137.
17. Blumel JE, Castelo-Branco C, Binfa L, et al. Quality of life after the menopause: a population study. Maturitas 2000; 34:17–23.
18. Hess R, Thurston RC, Hays RD, et al. The impact of menopause on health-related quality of life: results from the STRIDE longitudinal study. Qual Life Res 2012; 21:535–544.
19. Park H, Kim K. Depression and its association with health-related quality of life in postmenopausal women in Korea. Int J Environ Res Public Health 2018; 15:2327.
20. Williams RE, Levine KB, Kalilani L, Lewis J, Clark RV. Menopause-specific questionnaire assessment in US population-based study shows negative impact on health-related quality of life. Maturitas 2009; 62:153–159.
21. Bohannon RW. Grip strength: an indispensable biomarker for older adults. Clin Interv Aging 2019; 14:1681–1691.
22. Ilich JZ, Inglis JE, Kelly OJ, McGee DL. Osteosarcopenic obesity is associated with reduced handgrip strength, walking abilities, and balance in postmenopausal women. Osteoporos Int 2015; 26:2587–2595.
23. Shin H, Liu PY, Panton LB, Ilich JZ. Physical performance in relation to body composition and bone mineral density in healthy, overweight, and obese postmenopausal women. J Geriatr Phys Ther 2014; 37:7–16.
24. Ward-Ritacco CL, Adrian AL, Johnson MA, Rogers LQ, Evans EM. Adiposity, physical activity, and muscle quality are independently related to physical function performance in middle-aged postmenopausal women. Menopause 2014; 21:1114–1121.
25. Balogun S, Winzenberg T, Wills K, et al. Prospective associations of low muscle mass and strength with health-related quality of life over 10-year in community-dwelling older adults. Exp Gerontol 2019; 118:65–71.
26. Marques LP, Confortin SC, Ono LM, Barbosa AR, d’Orsi E. Quality of life associated with handgrip strength and sarcopenia: EpiFloripa Aging Study. Arch Gerontol Geriatr 2019; 81:234–239.
27. Paek J, Choi YJ. Association between hand grip strength and impaired health-related quality of life in Korean cancer survivors: a cross-sectional study. BMJ Open 2019; 9:e030938.
28. Selakovic I, Dubljanin-Raspopovic E, Markovic-Denic L, et al. Can early assessment of hand grip strength in older hip fracture patients predict functional outcome? PLoS One 2019; 14:e0213223.
29. Rocca WA, Gazzuola Rocca L, Smith CY, et al. Cohort profile: the Mayo Clinic Cohort Study of Oophorectomy and Aging-2 (MOA-2) in Olmsted County, Minnesota (USA). BMJ Open 2017; 7:e018861.
30. Rocca WA, Gazzuola-Rocca L, Smith CY, et al. Accelerated accumulation of multimorbidity after bilateral oophorectomy: a population-based cohort study. Mayo Clin Proc 2016; 91:1577–1589.
31. Korean Centers for Disease Control and Prevention. Procedures manual of the Korea National Health and Nutrition Examination Survey. Available at: Published 2016. Accessed Apr 07, 2021.
32. Lee YK, Nam HS, Chuang LH, et al. South Korean time trade-off values for EQ-5D health states: modeling with observed values for 101 health states. Value Health 2009; 12:1187–1193.
33. Kim SH, Jo MW, Lee JW, Lee HJ, Kim JK. Validity and reliability of EQ-5D-3L for breast cancer patients in Korea. Health Qual Life Outcomes 2015; 13:203.
34. Luo N, Cheung YB, Ng R, Lee CF. Mapping and direct valuation: do they give equivalent EQ-5D-5L index scores? Health Qual Life Outcomes 2015; 13:166.
35. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150:604–612.
36. Hess R, Colvin A, Avis NE, et al. The impact of hormone therapy on health-related quality of life: longitudinal results from the Study of Women's Health Across the Nation. Menopause 2008; 15:422–428.
37. Kang SY, Lim J, Park HS. Relationship between low handgrip strength and quality of life in Korean men and women. Qual Life Res 2018; 27:2571–2580.
38. Kwak Y, Kim Y. Quality of life and subjective health status according to handgrip strength in the elderly: a cross-sectional study. Aging Ment Health 2019; 23:107–112.
39. European Society for Human Reproduction and Embryology Guideline Group on POI, Webber L, et al. ESHRE Guideline: management of women with premature ovarian insufficiency. Hum Reprod 2016; 31:926–937.
40. Liao KL, Wood N, Conway GS. Premature menopause and psychological well-being. J Psychosom Obstet Gynaecol 2000; 21:167–174.
41. Mann E, Singer D, Pitkin J, Panay N, Hunter MS. Psychosocial adjustment in women with premature menopause: a cross-sectional survey. Climacteric 2012; 15:481–489.
42. Schmidt PJ, Luff JA, Haq NA, et al. Depression in women with spontaneous 46, XX primary ovarian insufficiency. J Clin Endocrinol Metab 2011; 96:E278–E287.
43. Coons SJ, Rao S, Keininger DL, Hays RD. A comparative review of generic quality-of-life instruments. Pharmacoeconomics 2000; 17:13–35.
44. Lewis JE, Hilditch JR, Wong CJ. Further psychometric property development of the Menopause-Specific Quality of Life questionnaire and development of a modified version, MENQOL-Intervention questionnaire. Maturitas 2005; 50:209–221.
45. McCaffrey N, Kaambwa B, Currow DC, Ratcliffe J. Health-related quality of life measured using the EQ-5D-5L: South Australian population norms. Health Qual Life Outcomes 2016; 14:133.
46. Avis NE, Colvin A, Bromberger JT, et al. Change in health-related quality of life over the menopausal transition in a multiethnic cohort of middle-aged women: study of Women's Health Across the Nation. Menopause 2009; 16:860–869.
47. Liu K, He L, Tang X, et al. Relationship between menopause and health-related quality of life in middle-aged Chinese women: a cross-sectional study. BMC Womens Health 2014; 14:7.
48. Lowe DA, Baltgalvis KA, Greising SM. Mechanisms behind estrogen's beneficial effect on muscle strength in females. Exerc Sport Sci Rev 2010; 38:61–67.
49. Moilanen JM, Aalto AM, Raitanen J, Hemminki E, Aro AR, Luoto R. Physical activity and change in quality of life during menopause—an 8-year follow-up study. Health Qual Life Outcomes 2012; 10:8.
50. Chen LK, Liu LK, Woo J, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc 2014; 15:95–101.
51. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010; 39:412–423.
52. Yoo JI, Choi H, Ha YC. Mean hand grip strength and cut-off value for Sarcopenia in Korean Adults using KNHANES VI. J Korean Med Sci 2017; 32:868–872.
53. About the National Health and Nutrition Examination Survey. Available at: Accessed March 31, 2021.
54. Esain I, Rodriguez-Larrad A, Bidaurrazaga-Letona I, Gil SM. Health-related quality of life, handgrip strength and falls during detraining in elderly habitual exercisers. Health Qual Life Outcomes 2017; 15:226.
55. The World Bank In Republic of Korea. Available at: Accessed June 29, 2021.
56. Kontis V, Bennett JE, Mathers CD, Li G, Foreman K, Ezzati M. Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. Lancet 2017; 389:1323–1335.
57. OCED Better Life Index. Available at: Accessed June 30, 2021.
58. Janssen MF, Szende A, Cabases J, Ramos-Goni JM, Vilagut G, Konig HH. Population norms for the EQ-5D-3L: a cross-country analysis of population surveys for 20 countries. Eur J Health Econ 2019; 20:205–216.
59. Chen TH, Li L, Kochen MM. A systematic review: how to choose appropriate health-related quality of life (HRQOL) measures in routine general practice? J Zhejiang Univ Sci B 2005; 6:936–940.
60. Badia X, Schiaffino A, Alonso J, Herdman M. Using the EuroQoI 5-D in the Catalan general population: feasibility and construct validity. Qual Life Res 1998; 7:311–322.
61. Johnson JA, Coons SJ. Comparison of the EQ-5D and SF-12 in an adult US sample. Qual Life Res 1998; 7:155–166.
62. Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada. Med Care 2000; 38:115–121.
63. Kind P, Dolan P, Gudex C, Williams A. Variations in population health status: results from a United Kingdom national questionnaire survey. BMJ 1998; 316:736–741.
64. Michael YL, Gold R, Manson JE, et al. Hormone therapy and physical function change among older women in the Women's Health Initiative: a randomized controlled trial. Menopause 2010; 17:295–302.
65. Preisinger E, Alacamlioglu Y, Saradeth T, Resch KL, Holzer G, Metka M. Forearm bone density and grip strength in women after menopause, with and without estrogen replacement therapy. Maturitas 1995; 21:57–63.
66. Velez MP, Alvarado BE, Rosendaal N, et al. Age at natural menopause and physical functioning in postmenopausal women: the Canadian Longitudinal Study on Aging. Menopause 2019; 26:958–965.
67. Brunner RL, Gass M, Aragaki A, et al. Effects of conjugated equine estrogen on health-related quality of life in postmenopausal women with hysterectomy: results from the Women's Health Initiative Randomized Clinical Trial. Arch Intern Med 2005; 165:1976–1986.
68. Hays J, Ockene JK, Brunner RL, et al. Effects of estrogen plus progestin on health-related quality of life. N Engl J Med 2003; 348:1839–1854.
69. Utian WH, Woods NF. Impact of hormone therapy on quality of life after menopause. Menopause 2013; 20:1098–1105.

Hand strength; Health care surveys; Menopause; Quality of life

Supplemental Digital Content

© 2021 by The North American Menopause Society