Abstract
Objective
Hip fracture and falls are significant health concerns. Handgrip strength (HGS) is closely associated with overall muscle strength and physical health. However, the longitudinal relationship between HGS and the risk of hip fractures and falls remains unclear, particularly regarding gender differences. This longitudinal study aimed to investigate the association between HGS and the risk of hip fracture and falls in individuals aged 45 years and above, considering gender‐specific differences over a 4‐year period.
Methods
This study included 10,092 participants (4471 men and 5621 women) aged 45 years and above from the China Health and Retirement Longitudinal Study (CHARLS). Incidents of hip fractures and falls were recorded during a 4‐year follow‐up, along with various demographic and clinical factors. Participants were categorized into five groups based on their HGS quintiles. Logistic regression models were employed to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to assess the relationship between HGS and hip fracture/fall risk.
Results
During the 4‐year follow‐up period, 223 cases of hip fracture (2.2%) and 1831 cases of falls (18.1%) were documented. Notably, higher HGS demonstrated a strong inverse association with the risk of hip fracture in both males and females (p < 0.05). In comparison to the lowest HGS quintile, the adjusted odds ratios (ORs) for hip fracture were 0.46 (0.27–0.78) for the total population, 0.4 (0.19–0.81) for males and 0.48 (0.23–0.98) for females in the highest HGS quintile. Furthermore, a profound and statistically significant negative correlation between HGS and falls was detected (p < 0.05). The adjusted ORs for falls in the highest HGS quintile, compared to the lowest quintile, were 0.62 (0.51–0.76) in the overall population, 0.59 (0.44–0.78) in males, and 0.78 (0.62–0.99) in females.
Conclusion
Our findings highlight the significant inverse association between HGS and the risk of hip fracture and falls in both males and females aged 45 years and above. Assessing handgrip strength may serve as a valuable tool for predicting fracture and fall risk.
Keywords: Fall risk, Handgrip strength, Hip fracture, The China Health and Retirement Longitudinal Study
Hip fracture and falls are significant health concerns among middle‐aged and older adults. Our findings highlight the significant inverse association between handgrip strength (HGS) and the risk of hip fracture and falls in both males and females aged 45 years and above. Assessing handgrip strength may serve as a valuable tool for predicting fracture and fall risk.
Introduction
Hip fractures, the most severe form of osteoporotic fractures, result in elevated morbidity, mortality, and disability, along with significant healthcare expenses. 1 , 2 , 3 Each year, 4.5 million people globally face disability from hip fractures, expected to soar to 21 million in the next 40 years. 3 Studies indicate a high 1‐year mortality rate post‐hip fracture, reaching up to 30%, with 50% of survivors experiencing a loss of functional independence and one‐third becoming fully dependent. 4 , 5 , 6 Globally, hip fractures are among the top 10 causes of disability, with Asia projected to contribute significantly due to its three‐quarters share of the world population. 3 By 2050, more than 50% of hip fractures are anticipated to occur in Asia, 3 especially in China. A retrospective cohort study involving 480 million residents in China from 2012 to 2016 revealed that the overall hip fracture incidence varied from 130.11 to 164.17 per 100,000 person‐years. 6 The incidence demonstrated an age‐dependent increase in China, with rates ranging from 36.15 to 48.35 in the 55–64 age group, 131.50 to 115.16 in the 65–74 age group, 342.80 to 314.99 in the 75–84 age group, and 523.96 to 633.03 in the ≥ 85 age group. 6
Handgrip strength (HGS) is widely recognized as an indicator of overall muscle strength and functional status, providing a valuable tool for assessing musculoskeletal health and predicting adverse health outcomes. Our previous research indicated a significant correlation between low HGS and an increased risk of all‐cause mortality and cardiovascular mortality in the American population. 7 Furthermore, we have identified a causal relationship between HGS and all‐cause mortality based on a Genome‐wide association study analysis of a population of 1.1 million Europeans. 8 Additionally, HGS serves as a predictor of hip fracture recovery and is associated with falls and fractures in older adults. 9 , 10 Dowling et al. found that reduced muscle strength in elderly women with obesity in the UK significantly increases the risk of falls and fractures, particularly in the lower extremities. 9 Kunutsor et al. conducted a prospective study involving 853 elderly individuals with ischemic heart disease and a meta‐analysis, both of which indicated that higher HGS is associated with a decreased risk of accidental fractures. 10 While HGS is just one measure of muscle strength, its simplicity, rapidity, and non‐invasiveness make it advantageous for testing. However, the longitudinal relationship between HGS and the risk of hip fractures and falls remains unclear, especially regarding gender differences. There is ongoing debate regarding the relationship between HGS and fracture risk. In a study of 5958 Chinese community residents aged 60 years or above, Zhong et al. found no correlation between HGS and an increased risk of hip fractures. 11 This controversy may be attributed to a lack of consideration for gender differences in handgrip strength. Therefore, this study aimed to investigate the association between HGS and the risk of hip fractures over a 4‐year period in a large population‐based sample of Chinese adults. It specifically sought to: (i) assess HGS as a marker for hip fracture and fall risks in a large cohort of Chinese adults aged 45 and above; (ii) investigate gender‐specific differences in the relationship between HGS and the incidence of hip fractures and falls; and (iii) track the occurrence of these health events over a 4‐year period, thereby understanding the long‐term implications of varying HGS levels and emphasizing the potential of HGS assessment as a valuable predictive tool.
Methods
Population
The nationally longitudinal study China Health and Retirement Longitudinal Study (CHARLS) was established in 2011 to recruit community‐dwelling adults in China. 12 , 13 The study's detailed methodology and validity have been previously reported. 12 The Peking University Ethical Review Committee approved the CHARLS protocol (IRB00001052–11015) in accordance with the Declaration of Helsinki, and all participants provided informed consent before participating in secondary research related to CHARLS. 12 , 13 All research findings were reported in compliance with STROBE guidelines throughout. Data from publicly accessible Harmonized CHARLS 2011–2015 were included (n = 25,586). Participants with missing data on HGS (n = 12,133), age <45 years (n = 526), hip fracture (n = 1820), fall (n = 9), high blood pressure (n = 64), diabetes (n = 88), Cancer (n = 22), lung disease (n = 17), heart disease (n = 30), stroke (n = 10), liver disease (n = 23), digest disease (n = 12), asthma (n = 32), memory disease (n = 13), drinking (n = 554), smoking (n = 19), weight (n = 60), and height (n = 62) were excluded. Ultimately, 10,092 participants above the age of 45 were enrolled in this study (Figure 1).
FIGURE 1.
The flowchart of participants from China Health and Retirement Longitudinal Study (CHARLS) 2011 to 2015 in this study.
Handgrip Strength
In this study, HGS was assessed twice for each hand using a handgrip dynamometer (YuejianTM WL‐1000, Nantong, China). in 2011. The participants stood upright and held the dynamometer at a right angle, squeezing it as tightly as possible for several seconds before releasing. Two measurements were taken for each hand, with a maximum of four recordings used in statistical analysis described in the previous study. 14 , 15 HGS was categorized according to quintiles for both males and females, ranging from Q1 to Q5, with Q1 representing the lowest and Q5 the highest. 16 , 17
Hip Fracture and Falls
The primary objective of this study was to examine hip fracture incidence. Self‐reported responses to the inquiry “Have you experienced a hip fracture since your last interview?” were used to assess hip fractures. Before the interview, the interviewer would explain the precise location of the hip bone to ensure that the respondent understood the definition of a hip fracture and could provide accurate answers. Responses were categorized as either “Yes” or “No.” Incidents of falls were documented through self‐reported responses to the question “Have you fallen within the past 2 years?” Participants who responded with a “yes” were classified as having a history of falls. The deadline for follow‐up was January 2016.
Covariates
Data on sociodemographic and medical covariates were collected from the 2011 China Health and Retirement Longitudinal Study (CHARLS). The sociodemographic variables included age, gender (male, female), marital status (single, married, divorced, widowed, or other), education (elementary school or lower, secondary school or higher), and dwelling location (urban or rural). Additionally, information on drinking, smoking, and multimorbidity was obtained. Self‐reported chronic diseases were documented through responses to the question “Have you received a physician's diagnosis of XX?” Hypertension, diabetes or high blood sugar, chronic lung diseases (such as chronic bronchitis and emphysema, excluding tumors or cancer), heart disease (including heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems), stroke, memory‐related diseases (such as Alzheimer's disease, brain atrophy, and Parkinson's disease), liver disease (excluding fatty liver, tumors, and cancer), digestive disease (such as stomach or other gastrointestinal disease, excluding tumors or cancer), cancer or malignant tumor (excluding minor skin cancers), and asthma were determined by self‐reported physician diagnoses in conjunction with health assessment and medication data. The smoking behaviors were categorized as never, past, and current use. The formula for calculating body mass index (BMI) as weight (kg)/(height [m2] × height [m2]).
Statistical Analysis
Continuous variables were reported with 95% confidence intervals (CI), while categorical variables were presented as percentage frequencies. T‐tests and χ 2‐tests were utilized to compare continuous and categorical data, respectively. No imputation approach was employed, as all variables displayed low missing data rates. Curve fitting was visually demonstrated. Logistic regression models were established to assess the relationship between grip strength and the risk of falls and hip fractures, with the quintiles of HGS analyzed separately for males and females. Model 1 was a crude model, while model 2 adjusted for age group and BMI. Model 3 included additional adjustments for marital status, education level, urban and rural residence, smoking, and alcohol consumption. Model 4 further adjusted for chronic diseases beyond those in model 3, encompassing hypertension, diabetes, lung diseases, heart disease, stroke, memory‐related diseases, liver disease, digestive disease, cancer or malignant tumor, and asthma. Odds ratios (OR) and 95% confidence intervals (CI) were reported for all regression models. Statistical analyses were performed utilizing the R software package (http://www.R-project.org) and Free Statistics software version 1.8. Statistical significance was assigned by a two‐sided p‐value <0.05.
Results
Characteristics of Participants in the Longitudinal Study
In total, 10,092 participants were enrolled in the study, consisting of 4621 males and 5471 females. Of these, 9869 individuals (4516 males and 5353 females) did not experience hip fractures during the 4‐year follow‐up period. During the 4‐year period, 233 individuals (105 males and 118 females) developed hip fractures, with an average age of 61.6 ± 10.2 years, including 101 individuals under 60 years old, 112 between 60 and 80 years old, and 10 over 80 years old (Table 1).
TABLE 1.
The baseline characteristics of the study population in the China Health and Retirement Longitudinal Study (CHARLS).
| Variables | Total (n = 10,092) | No hip‐fracture (n = 9869) | Hip fracture (n = 223) | t/F/χ 2 value | p‐value |
|---|---|---|---|---|---|
| Age (years), mean ± SD | 58.6 ± 9.1 | 58.5 ± 9.0 | 61.6 ± 10.2 | 25.309 | <0.001 |
| Age group, n (%) | Fisher | <0.001 | |||
| <60 years | 5835 (57.8) | 5734 (58.1) | 101 (45.3) | ||
| 60–80 years | 4073 (40.4) | 3961 (40.1) | 112 (50.2) | ||
| >80 years | 184 (1.8) | 174 (1.8) | 10 (4.5) | ||
| Gender, n (%) | 0.154 | 0.694 | |||
| Men | 4621 (45.8) | 4516 (45.8) | 105 (47.1) | ||
| Women | 5471 (54.2) | 5353 (54.2) | 118 (52.9) | ||
| Handgrip strength (kg), Mean ± SD | 31.9 ± 10.3 | 32.0 ± 10.3 | 29.3 ± 10.4 | 15.032 | <0.001 |
| Education, n (%) | Fisher | 0.054 | |||
| Elementary school or below | 6994 (69.3) | 6825 (69.2) | 169 (75.8) | ||
| Secondary school | 2991 (29.6) | 2940 (29.8) | 51 (22.9) | ||
| College or above | 107 (1.1) | 104 (1.1) | 3 (1.3) | ||
| Marriage, n (%) | Fisher | 0.018 | |||
| Single | 70 (0.7) | 67 (0.7) | 3 (1.3) | ||
| Married | 8877 (88.0) | 8694 (88.1) | 183 (82.1) | ||
| Divorced or widowed or others | 1145 (11.3) | 1108 (11.2) | 37 (16.6) | ||
| Rural area, n (%) | 0.005 | 0.945 | |||
| Urban community | 3508 (34.8) | 3430 (34.8) | 78 (35) | ||
| Rural village | 6584 (65.2) | 6439 (65.2) | 145 (65) | ||
| Drinking, n (%) | 4.723 | 0.193 | |||
| Never | 7137 (70.7) | 6984 (70.8) | 153 (68.6) | ||
| Less than once a month | 830 (8.2) | 807 (8.2) | 23 (10.3) | ||
| Less than daily | 958 (9.5) | 943 (9.6) | 15 (6.7) | ||
| Daily or more drink | 1167 (11.6) | 1135 (11.5) | 32 (14.3) | ||
| Smoking, n (%) | 0.929 | 0.628 | |||
| Never | 6234 (61.8) | 6100 (61.8) | 134 (60.1) | ||
| Previous smoker | 825 (8.2) | 809 (8.2) | 16 (7.2) | ||
| Current smoker | 3033 (30.1) | 2960 (30) | 73 (32.7) | ||
| Weight, mean ± SD | 59.0 ± 11.7 | 59.0 ± 11.7 | 58.1 ± 11.1 | 1.24 | 0.265 |
| Height, mean ± SD | 1.6 ± 0.1 | 1.6 ± 0.1 | 1.6 ± 0.1 | 1.57 | 0.21 |
| Body mass index, mean ± SD | 23.5 ± 3.9 | 23.5 ± 3.9 | 23.4 ± 3.8 | 0.206 | 0.65 |
| Hypertension, n (%) | 2.744 | 0.098 | |||
| No | 7541 (74.7) | 7385 (74.8) | 156 (70) | ||
| Yes | 2551 (25.3) | 2484 (25.2) | 67 (30) | ||
| Diabetes, n (%) | 6.965 | 0.008 | |||
| No | 9474 (93.9) | 9274 (94) | 200 (89.7) | ||
| Yes | 618 (6.1) | 595 (6) | 23 (10.3) | ||
| Cancer, n (%) | Fisher | 0.7 | |||
| No | 10,011 (99.2) | 9790 (99.2) | 221 (99.1) | ||
| Yes | 81 (0.8) | 79 (0.8) | 2 (0.9) | ||
| Lung disease, n (%) | 14.906 | <0.001 | |||
| No | 9130 (90.5) | 8945 (90.6) | 185 (83) | ||
| Yes | 962 (9.5) | 924 (9.4) | 38 (17) | ||
| Heart disease, n (%) | 4.606 | 0.032 | |||
| No | 8922 (88.4) | 8735 (88.5) | 187 (83.9) | ||
| Yes | 1170 (11.6) | 1134 (11.5) | 36 (16.1) | ||
| Stroke, n (%) | Fisher | 0.155 | |||
| No | 9873 (97.8) | 9658 (97.9) | 215 (96.4) | ||
| Yes | 219 (2.2) | 211 (2.1) | 8 (3.6) | ||
| Liver disease, n (%) | 0.083 | 0.774 | |||
| No | 9764 (96.7) | 9549 (96.8) | 215 (96.4) | ||
| Yes | 328 (3.3) | 320 (3.2) | 8 (3.6) | ||
| Digest disease, n (%) | 2.178 | 0.14 | |||
| No | 7833 (77.6) | 7669 (77.7) | 164 (73.5) | ||
| Yes | 2259 (22.4) | 2200 (22.3) | 59 (26.5) | ||
| Asthma, n (%) | 2.606 | 0.106 | |||
| No | 9637 (95.5) | 9429 (95.5) | 208 (93.3) | ||
| Yes | 455 (4.5) | 440 (4.5) | 15 (6.7) | ||
| Memory disease, n (%) | Fisher | 0.227 | |||
| No | 9957 (98.7) | 9739 (98.7) | 218 (97.8) | ||
| Yes | 135 (1.3) | 130 (1.3) | 5 (2.2) | ||
| Fall, n (%) | 120.771 | <0.001 | |||
| No | 8261 (81.9) | 8141 (82.5) | 120 (53.8) | ||
| Yes | 1831 (18.1) | 1728 (17.5) | 103 (46.2) | ||
| Falltime, median (IQR) | 0.0 (0.0, 1.0) | 0.0 (0.0, 1.0) | 1.0 (0.0, 1.5) | 31.43 | <0.001 |
The age of individuals who experienced hip fractures was significantly higher compared to those who did not (p < 0.05), while there were no significant differences in gender, education level, urban/rural residence, smoking, alcohol consumption, height, weight, or BMI (p > 0.05) (Table 1).
The HGS decreased progressively with age: <60 years (34.1 ± 10.2 kg), 60–80 years (29.3 ± 9.7 kg), and >80 years (22.6 ± 10.0 kg). HGS was significantly lower in individuals who experienced hip fractures (29.3 ± 10.4 kg) than in those who did not (32.0 ± 10.3 kg) (p < 0.05). The incidence of hip fractures was significantly higher in single individuals (4.28%) than in married (2.06%) or widowed/divorced (3.23%) individuals (p < 0.05). The incidence of hip fractures was significantly higher in participants with diabetes mellitus (3.72%) compared to those without (2.11%) (p < 0.05). Similarly, participants with pulmonary diseases (3.95%) and heart disease (3.08%) had significantly higher rates of hip fractures compared to those without these conditions (2.03% and 2.10%) (p < 0.05) (Table 1).
However, no significant differences in hip fracture incidence were observed among individuals with hypertension, cancer, stroke, liver disease, digestive disease, asthma, or memory‐related diseases (p > 0.05) (Table 1).
Notably, individuals who had experienced falls had a significantly higher incidence of hip fractures (5.63%) compared to those who had not fallen (1.45%) (p < 0.05), and the frequency of falls was significantly higher in individuals who experienced hip fractures than in those who did not (p < 0.05) (Table 1).
The Relationship between HGS and 4‐Year Hip Fracture
According to curve fitting, men and women with higher HGS had a lower risk of 4‐year hip fracture (Figures 2 and 3). Overall, multivariate logistic regression results showed that the hip fracture risk decreased as the quintiles of HGS increased in the crude model and all adjusted models (models 1–4). The trend test also indicated a significant dose–response relationship between HGS and hip fracture risk (p < 0.05 for all models) (Table 2).
FIGURE 2.
The relationship between handgrip strength with 4‐year hip fracture in men and women by curve fitting. (A): The relationship between handgrip strength (HGS) and 4‐year hip fracture by curve fitting in total participants. (B): The relationship between HGS and 4‐year hip fracture by curve fitting in men. (C): The relationship between HGS and 4‐year hip fracture by curve fitting in women. All the curve fitting figures were adjusted for age, body mass index (BMI), urban/rural residence, education level, marriage status, drinking, and smoking.
FIGURE 3.
The relationship between handgrip strength with 4‐year fall in men and women by curve fitting. (A): The relationship between handgrip strength (HGS) and 4‐year fall by curve fitting in total participants. (B): The relationship between HGS and 4‐year fall by curve fitting in men. (C): The relationship between HGS and 4‐year fall in women. All the curve fitting figures were adjusted for age, body mass index (BMI), urban/rural residence, education level, marriage status, drinking, and smoking.
TABLE 2.
The relationship between handgrip strength (HGS) and 4‐year hip fracture in men and women.
| Handgrip strength (kg) | n | Hip fracture, % | Model 1 | p‐value | Model 2 | p‐value | Model 3 | p‐value | Model 4 | p‐value |
|---|---|---|---|---|---|---|---|---|---|---|
| Total | ||||||||||
| Q1 (≤23) | 2014 | 64 (3.2) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (23.1–28.8) | 2023 | 47 (2.3) | 0.72 (0.49 ~ 1.06) | 0.098 | 0.78 (0.53 ~ 1.15) | 0.207 | 0.76 (0.52 ~ 1.12) | 0.168 | 0.78 (0.53 ~ 1.15) | 0.203 |
| Q3 (28.9–33.9) | 1963 | 35 (1.8) | 0.55 (0.36 ~ 0.84) | 0.005 | 0.62 (0.41 ~ 0.94) | 0.026 | 0.58 (0.38 ~ 0.89) | 0.014 | 0.59 (0.38 ~ 0.91) | 0.018 |
| Q4 (34–40.4) | 2031 | 48 (2.4) | 0.74 (0.5 ~ 1.08) | 0.116 | 0.83 (0.56 ~ 1.22) | 0.345 | 0.73 (0.48 ~ 1.12) | 0.147 | 0.75 (0.49 ~ 1.15) | 0.19 |
| Q5 (≥ 40.5) | 2061 | 29 (1.4) | 0.43 (0.28 ~ 0.68) | <0.001 | 0.52 (0.33 ~ 0.82) | 0.005 | 0.43 (0.26 ~ 0.72) | 0.001 | 0.46 (0.27 ~ 0.78) | 0.004 |
| Trend.test | 10,092 | 223 (2.2) | 0.85 (0.77 ~ 0.93) | 0.001 | 0.89 (0.8 ~ 0.98) | 0.016 | 0.85 (0.75 ~ 0.95) | 0.004 | 0.86 (0.76 ~ 0.96) | 0.009 |
| Men | ||||||||||
| Q1 (≤ 30.9) | 887 | 32 (3.6) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (31–36.4) | 951 | 18 (1.9) | 0.52 (0.29 ~ 0.93) | 0.026 | 0.52 (0.29 ~ 0.95) | 0.033 | 0.52 (0.29 ~ 0.94) | 0.031 | 0.52 (0.29 ~ 0.95) | 0.033 |
| Q3 (36.5–40.9) | 914 | 29 (3.2) | 0.88 (0.53 ~ 1.46) | 0.61 | 0.9 (0.53 ~ 1.54) | 0.706 | 0.92 (0.54 ~ 1.57) | 0.759 | 0.93 (0.54 ~ 1.6) | 0.801 |
| Q4 (41–45.9) | 854 | 13 (1.5) | 0.41 (0.22 ~ 0.79) | 0.008 | 0.43 (0.22 ~ 0.85) | 0.015 | 0.44 (0.22 ~ 0.87) | 0.018 | 0.46 (0.23 ~ 0.91) | 0.026 |
| Q5 (≥ 46) | 1015 | 13 (1.3) | 0.35 (0.18 ~ 0.66) | 0.001 | 0.37 (0.18 ~ 0.74) | 0.005 | 0.37 (0.18 ~ 0.76) | 0.007 | 0.4 (0.19 ~ 0.81) | 0.011 |
| Trend.test | 4621 | 105 (2.3) | 0.8 (0.69 ~ 0.92) | 0.001 | 0.81 (0.69 ~ 0.94) | 0.007 | 0.81 (0.69 ~ 0.95) | 0.01 | 0.82 (0.7 ~ 0.97) | 0.017 |
| Women | ||||||||||
| Q1 (≤ 19.9) | 901 | 29 (3.2) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (20–24.8) | 1284 | 31 (2.4) | 0.74 (0.45 ~ 1.24) | 0.259 | 0.85 (0.51 ~ 1.44) | 0.553 | 0.87 (0.52 ~ 1.48) | 0.614 | 0.91 (0.54 ~ 1.55) | 0.741 |
| Q3 (24.9–27.9) | 984 | 21 (2.1) | 0.66 (0.37 ~ 1.16) | 0.146 | 0.78 (0.44 ~ 1.41) | 0.414 | 0.82 (0.45 ~ 1.47) | 0.495 | 0.84 (0.47 ~ 1.51) | 0.562 |
| Q4 (28–31.9) | 1183 | 25 (2.1) | 0.65 (0.38 ~ 1.12) | 0.118 | 0.83 (0.47 ~ 1.47) | 0.516 | 0.87 (0.49 ~ 1.54) | 0.624 | 0.92 (0.51 ~ 1.64) | 0.77 |
| Q5 (≥ 32) | 1119 | 12 (1.1) | 0.33 (0.17 ~ 0.64) | 0.001 | 0.43 (0.21 ~ 0.88) | 0.02 | 0.45 (0.22 ~ 0.93) | 0.031 | 0.48 (0.23 ~ 0.98) | 0.043 |
| Trend.test | 5471 | 118 (2.2) | 0.81 (0.7 ~ 0.92) | 0.002 | 0.86 (0.75 ~ 0.99) | 0.042 | 0.87 (0.75 ~ 1.01) | 0.067 | 0.88 (0.76 ~ 1.02) | 0.092 |
Note: Model 1: Crude model. Model 2: Adjusted for age group and body mass index (BMI). Model 3: Adjusted for age group, BMI, urban/rural residence, education level, marriage status, drinking, and smoking. Model 4: Adjusted for age group, BMI, urban/rural residence, education level, marriage status, drinking, smoking, hypertension, diabetes, cancer, lung disease, heart disease, stroke, liver disease, digestive disease, asthma, memory‐related diseases.
In all the participants, compared with the reference group Q1, the odds ratios (ORs) and 95% CI of hip fracture adjusted for age group and BMI in Q2–Q5 were 0.78 (0.53–1.15), 0.62 (0.41–0.94), 0.83 (0.56–1.22), and 0.52 (0.33–0.82), respectively (model 2). In men, compared to Q1 of HGS (≤ 30.9 kg), the adjusted ORs were 0.52 (0.29–0.95), 0.9 (0.53–1.54), 0.43 (0.22–0.85), and 0.37 (0.18–0.74) for Q2–Q5, respectively (model 2). Similarly, in women, compared to the lowest Q1 of HGS (≤ 19.9 kg), the adjusted ORs for hip fracture were 0.85 (0.51–1.44), 0.78 (0.44–1.41), 0.83 (0.47–1.47), and 0.43 (0.21–0.88) for Q2–Q5, respectively (model 2) (Table 2).
In the fully adjusted model, potential confounding factors were adjusted, including age group, BMI, urban/rural residence, education level, marriage status, drinking, smoking, and comorbidities (model 4). Compared to Q1, the adjusted ORs (95% CIs) for hip fractures in the Q2–Q5 groups were as follows: Q2: 0.78 (0.53–1.15), Q3: 0.59 (0.38–0.91), Q4: 0.75 (0.49–1.15), and Q5: 0.46 (0.27–0.78) (model 4). Among males, the adjusted ORs for hip fractures were as follows: Q2: 0.52 (0.29–0.95), Q3: 0.93 (0.54–1.6), Q4: 0.46 (0.23–0.91), and Q5: 0.4 (0.19–0.81) (model 4). Among females, the adjusted ORs were: Q2:0.91 (0.54–1.55), Q3: 0.84 (0.47–1.51), Q4: 0.92 (0.51–1.64), and Q5: 0.48 (0.23–0.98) (model 4) (Table 2).
The subgroup analysis have similar results for both men and women. In men, each kilogram increase in grip strength was associated with a 4% lower risk of hip fracture (OR: 0.96, 95% CI: 0.94–0.99, p < 0.05). Similarly, women experienced a 3% decrease in hip fracture risk for every kilogram increase in grip strength (OR: 0.97, 95% CI: 0.94–0.99, p < 0.05). In the age group of 60–80 years, each kilogram increase in grip strength showed a 4% lower risk of hip fracture (OR: 0.96, 95% CI: 0.94–0.98, p < 0.05). However, similar trends without significant association were observed in individuals younger than 60 years or older than 80 years. For individuals with comorbidities such as hypertension, diabetes, cancer, lung disease, heart disease, stroke, liver disease, or digestive system disorders, higher HGS (HGS) was associated with a reduced risk of hip fractures (p < 0.001). However, no statistically significant interaction was found between HGS and these chronic conditions in relation to the risk of hip fractures, except for individuals with asthma (Table 3).
TABLE 3.
Subgroup analyses for the association between HGS and 4‐year hip fracture risk.
| Subgroup | Total | Event (%) | Crude OR (95% CI) | Crude p‐value | Adjusted OR (95% CI) | Adjusted p‐value | P for interaction |
|---|---|---|---|---|---|---|---|
| Age group | 0.37 | ||||||
| <60 years | 5835 | 101 (1.7) | 0.99 (0.97 ~ 1.01) | 0.283 | 0.97 (0.95 ~ 1) | 0.023 | |
| 60–80 years | 4073 | 112 (2.7) | 0.97 (0.95 ~ 0.99) | 0.007 | 0.96 (0.94 ~ 0.98) | 0.001 | |
| >80 years | 184 | 10 (5.4) | 0.95 (0.87 ~ 1.03) | 0.193 | 0.96 (0.88 ~ 1.05) | 0.402 | |
| Gender | 0.711 | ||||||
| Men | 4621 | 105 (2.3) | 0.96 (0.94 ~ 0.98) | <0.001 | 0.96 (0.94 ~ 0.99) | 0.001 | |
| Women | 5471 | 118 (2.2) | 0.95 (0.93 ~ 0.98) | <0.001 | 0.97 (0.94 ~ 0.99) | 0.016 | |
| Hypertension | 0.765 | ||||||
| No | 7541 | 156 (2.1) | 0.97 (0.96 ~ 0.99) | 0.001 | 0.96 (0.94 ~ 0.98) | <0.001 | |
| Yes | 2551 | 67 (2.6) | 0.98 (0.95 ~ 1) | 0.067 | 0.98 (0.95 ~ 1.01) | 0.114 | |
| Diabetes | 0.551 | ||||||
| No | 9474 | 200 (2.1) | 0.98 (0.96 ~ 0.99) | 0.001 | 0.97 (0.95 ~ 0.99) | <0.001 | |
| Yes | 618 | 23 (3.7) | 0.96 (0.92 ~ 1) | 0.075 | 0.96 (0.91 ~ 1.01) | 0.097 | |
| Cancer | 0.873 | ||||||
| No | 10,011 | 221 (2.2) | 0.97 (0.96 ~ 0.99) | <0.001 | 0.97 (0.95 ~ 0.98) | <0.001 | |
| Yes | 81 | 2 (2.5) | 0.99 (0.86 ~ 1.13) | 0.878 | 1.01 (0.83 ~ 1.22) | 0.931 | |
| Lung disease | 0.1 | ||||||
| No | 9130 | 185 (2) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.96 (0.94 ~ 0.98) | <0.001 | |
| Yes | 962 | 38 (4) | 1 (0.97 ~ 1.03) | 0.965 | 1 (0.96 ~ 1.05) | 0.897 | |
| Heart disease | 0.062 | ||||||
| No | 8922 | 187 (2.1) | 0.98 (0.97 ~ 0.99) | 0.006 | 0.97 (0.95 ~ 0.99) | 0.003 | |
| Yes | 1170 | 36 (3.1) | 0.95 (0.91 ~ 0.98) | 0.002 | 0.94 (0.9 ~ 0.98) | 0.006 | |
| Stroke | 0.691 | ||||||
| No | 9873 | 215 (2.2) | 0.97 (0.96 ~ 0.99) | <0.001 | 0.97 (0.95 ~ 0.98) | <0.001 | |
| Yes | 219 | 8 (3.7) | 0.99 (0.92 ~ 1.06) | 0.699 | 0.95 (0.87 ~ 1.04) | 0.269 | |
| Liver disease | 0.372 | ||||||
| No | 9764 | 215 (2.2) | 0.97 (0.96 ~ 0.99) | <0.001 | 0.96 (0.95 ~ 0.98) | <0.001 | |
| Yes | 328 | 8 (2.4) | 1.01 (0.94 ~ 1.07) | 0.87 | 1.01 (0.92 ~ 1.11) | 0.821 | |
| Digest disease | 0.726 | ||||||
| No | 7833 | 164 (2.1) | 0.97 (0.96 ~ 0.99) | <0.001 | 0.97 (0.95 ~ 0.99) | 0.001 | |
| Yes | 2259 | 59 (2.6) | 0.98 (0.95 ~ 1.01) | 0.114 | 0.97 (0.94 ~ 1) | 0.055 | |
| Asthma | 0.038 | ||||||
| No | 9637 | 208 (2.2) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.96 (0.95 ~ 0.98) | <0.001 | |
| Yes | 455 | 15 (3.3) | 1.03 (0.98 ~ 1.08) | 0.311 | 1.02 (0.95 ~ 1.09) | 0.585 | |
| Memory disease | 0.414 | ||||||
| No | 9957 | 218 (2.2) | 0.97 (0.96 ~ 0.99) | <0.001 | 0.97 (0.95 ~ 0.98) | <0.001 | |
| Yes | 135 | 5 (3.7) | 0.94 (0.86 ~ 1.03) | 0.195 | 0.96 (0.86 ~ 1.07) | 0.41 |
Note: Adjusted for age group and body mass index (BMI).
Abbreviations: 95% CI, 95% confidence interval; HGS, handgrip strength; OR, odds ratio.
The Relationship between HGS and 4‐Year Fall
The multivariate logistic regression results showed that the risk of fall decreased with increasing HGS quintiles in all the models (models 1–4, Table 4). For both men and women, the trend test shows each quintile of HGS has a decreasing risk of falls compared to the lowest quintile (Table 4). Compared to the lowest quintile (Q1), the adjusted odds ratios (ORs) for falls in the highest quintile (Q5) were 0.49 (95% CI, 0.42–0.59) in total population, 0.51 (95% CI, 0.39–0.67) in men and 0.69 (95% CI, 0.55–0.87) in women (model 2). In the fully adjusted model, the ORs for falls consistently decreased as HGS increased: Q2–0.96 (0.82–1.11), Q3–0.8 (0.68–0.94), Q4–0.69 (0.58–0.82), and Q5–0.62 (0.51–0.76) (model 4). In the male group, higher HGS quartiles also demonstrated a lower risk of falls: Q2–0.67 (0.52–0.85), Q3–0.69 (0.53–0.89), Q4–0.66 (0.51–0.87), and Q5–0.59 (0.44–0.78) (model 4). Among females, the adjusted ORs were: Q2–0.94 (0.77–1.16), Q3–0.91 (0.73–1.14), Q4–0.92 (0.73–1.14), and Q5–0.78 (0.62–0.99) (model 4).
TABLE 4.
The relationship between handgrip strength (HGS) and 4‐year fall in men and women.
| Handgrip strength | n | Fall, % | Model 1 | p‐value | Model 2 | p‐value | Model 3 | p‐value | Model 4 | p‐value |
|---|---|---|---|---|---|---|---|---|---|---|
| Total | ||||||||||
| Q1 (≤23) | 2014 | 485 (24.1) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (23.1–28.8) | 2023 | 440 (21.7) | 0.88 (0.76 ~ 1.01) | 0.078 | 0.92 (0.79 ~ 1.06) | 0.242 | 0.94 (0.81 ~ 1.09) | 0.395 | 0.96 (0.82 ~ 1.11) | 0.558 |
| Q3 (28.9–33.9) | 1963 | 346 (17.6) | 0.67 (0.58 ~ 0.79) | <0.001 | 0.72 (0.62 ~ 0.85) | <0.001 | 0.77 (0.66 ~ 0.9) | 0.001 | 0.8 (0.68 ~ 0.94) | 0.006 |
| Q4 (34–40.4) | 2031 | 307 (15.1) | 0.56 (0.48 ~ 0.66) | <0.001 | 0.6 (0.51 ~ 0.71) | <0.001 | 0.67 (0.56 ~ 0.8) | <0.001 | 0.69 (0.58 ~ 0.82) | <0.001 |
| Q5 (≥ 40.5) | 2061 | 253 (12.3) | 0.44 (0.37 ~ 0.52) | <0.001 | 0.49 (0.42 ~ 0.59) | <0.001 | 0.59 (0.48 ~ 0.71) | <0.001 | 0.62 (0.51 ~ 0.76) | <0.001 |
| Trend.test | 10,092 | 1831 (18.1) | 0.81 (0.78 ~ 0.84) | <0.001 | 0.83 (0.8 ~ 0.87) | <0.001 | 0.87 (0.83 ~ 0.91) | <0.001 | 0.88 (0.84 ~ 0.92) | <0.001 |
| Men | ||||||||||
| Q1 (≤ 30.9) | 887 | 198 (22.3) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (31–36.4) | 951 | 142 (14.9) | 0.61 (0.48 ~ 0.78) | <0.001 | 0.64 (0.5 ~ 0.81) | <0.001 | 0.65 (0.51 ~ 0.83) | <0.001 | 0.67 (0.52 ~ 0.85) | 0.001 |
| Q3 (36.5–40.9) | 914 | 134 (14.7) | 0.6 (0.47 ~ 0.76) | <0.001 | 0.65 (0.5 ~ 0.83) | 0.001 | 0.67 (0.52 ~ 0.86) | 0.002 | 0.69 (0.53 ~ 0.89) | 0.004 |
| Q4 (41–45.9) | 854 | 113 (13.2) | 0.53 (0.41 ~ 0.68) | <0.001 | 0.59 (0.45 ~ 0.77) | <0.001 | 0.63 (0.48 ~ 0.82) | 0.001 | 0.66 (0.51 ~ 0.87) | 0.003 |
| Q5 (≥ 46) | 1015 | 112 (11) | 0.43 (0.34 ~ 0.56) | <0.001 | 0.51 (0.39 ~ 0.67) | <0.001 | 0.56 (0.42 ~ 0.74) | <0.001 | 0.59 (0.44 ~ 0.78) | <0.001 |
| 4621 | 699 (15.1) | 0.83 (0.78 ~ 0.88) | <0.001 | 0.86 (0.81 ~ 0.92) | <0.001 | 0.88 (0.83 ~ 0.94) | <0.001 | 0.89 (0.84 ~ 0.95) | 0.001 | |
| Women | ||||||||||
| Q1 (≤ 19.9) | 901 | 230 (25.5) | 1 (Ref) | 1 (Ref) | 1 (Ref) | 1 (Ref) | ||||
| Q2 (20–24.8) | 1284 | 282 (22) | 0.82 (0.67 ~ 1) | 0.053 | 0.89 (0.72 ~ 1.08) | 0.239 | 0.89 (0.73 ~ 1.09) | 0.276 | 0.94 (0.77 ~ 1.16) | 0.58 |
| Q3 (24.9–27.9) | 984 | 204 (20.7) | 0.76 (0.62 ~ 0.95) | 0.014 | 0.86 (0.69 ~ 1.07) | 0.164 | 0.87 (0.7 ~ 1.09) | 0.218 | 0.91 (0.73 ~ 1.14) | 0.419 |
| Q4 (28–31.9) | 1183 | 232 (19.6) | 0.71 (0.58 ~ 0.88) | 0.001 | 0.84 (0.67 ~ 1.04) | 0.11 | 0.86 (0.69 ~ 1.07) | 0.166 | 0.92 (0.73 ~ 1.14) | 0.437 |
| Q5 (≥ 32) | 1119 | 184 (16.4) | 0.57 (0.46 ~ 0.71) | <0.001 | 0.69 (0.55 ~ 0.87) | 0.002 | 0.72 (0.57 ~ 0.91) | 0.007 | 0.78 (0.62 ~ 0.99) | 0.041 |
| Trend.test | 5471 | 1132 (20.7) | 0.88 (0.84 ~ 0.93) | <0.001 | 0.93 (0.88 ~ 0.97) | 0.003 | 0.94 (0.89 ~ 0.99) | 0.011 | 0.95 (0.9 ~ 1) | 0.055 |
Note: Model 1: Crude model. Model 2: Adjusted for age group and body mass index (BMI). Model 3: Adjusted for age group, BMI, urban/rural residence, education level, marriage status, drinking, and smoking. Model 4: Adjusted for age group, BMI, urban/rural residence, education level, marriage status, drinking, smoking, hypertension, diabetes, cancer, lung disease, heart disease, stroke, liver disease, digestive disease, asthma, memory‐related diseases.
The subgroup results show that participants below 60 years old had a lower fall risk with greater HGS (OR: 0.97, 95% CI: 0.96–0.98, p < 0.05), and similar trends were observed in other age groups. Both males and females with higher HGS had a reduced fall risk compared to those with lower HGS, but with no significant differences. Regarding comorbidities, individuals with hypertension, diabetes, cancer, lung disease, heart disease, stroke, liver disease, digestive disease, or asthma experienced decreased fall risks when exhibiting higher HGS p < 0.05). There was no statistically significant interaction between HGS and these chronic conditions in relation to fall risk.(Table 5).
TABLE 5.
Subgroup analyses for the association between HGS and 4‐year fall risk.
| Subgroup | Total | Event (%) | Crude OR (95% CI) | Crude p‐value | Adjusted OR (95% CI) | Adjusted p‐value | P for interaction |
|---|---|---|---|---|---|---|---|
| Age group | 0.672 | ||||||
| <60 years | 5835 | 898 (15.4) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.97 (0.96 ~ 0.98) | <0.001 | |
| 60–80 years | 4073 | 886 (21.8) | 0.98 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | 0.001 | |
| >80 years | 184 | 47 (25.5) | 0.96 (0.93 ~ 1) | 0.074 | 0.98 (0.95 ~ 1.03) | 0.447 | |
| Gender | 0.229 | ||||||
| Men | 4621 | 699 (15.1) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.97 (0.96 ~ 0.98) | <0.001 | |
| Women | 5471 | 1132 (20.7) | 0.98 (0.97 ~ 0.98) | <0.001 | 0.98 (0.98 ~ 0.99) | 0.002 | |
| Hypertension | 0.203 | ||||||
| No | 7541 | 1291 (17.1) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 2551 | 540 (21.2) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.97 (0.96 ~ 0.99) | <0.001 | |
| Diabetes | 0.625 | ||||||
| No | 9474 | 1685 (17.8) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 618 | 146 (23.6) | 0.97 (0.95 ~ 0.99) | 0.001 | 0.97 (0.94 ~ 0.99) | 0.006 | |
| Cancer | 0.387 | ||||||
| No | 10,011 | 1816 (18.1) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 81 | 15 (18.5) | 1 (0.95 ~ 1.05) | 0.939 | 0.96 (0.9 ~ 1.04) | 0.336 | |
| Lung disease | 0.213 | ||||||
| No | 9130 | 1605 (17.6) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 962 | 226 (23.5) | 0.98 (0.97 ~ 1) | 0.011 | 0.98 (0.96 ~ 1) | 0.045 | |
| Heart disease | 0.654 | ||||||
| No | 8922 | 1561 (17.5) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 1170 | 270 (23.1) | 0.98 (0.96 ~ 0.99) | 0.001 | 0.98 (0.97 ~ 1) | 0.08 | |
| Stroke | 0.679 | ||||||
| No | 9873 | 1762 (17.8) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 219 | 69 (31.5) | 0.98 (0.95 ~ 1.01) | 0.111 | 0.98 (0.94 ~ 1.02) | 0.28 | |
| Liver disease | 0.781 | ||||||
| No | 9764 | 1749 (17.9) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 328 | 82 (25) | 0.98 (0.95 ~ 1) | 0.044 | 0.97 (0.94 ~ 1) | 0.064 | |
| Digest disease | 0.541 | ||||||
| No | 7833 | 1328 (17) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | |
| Yes | 2259 | 503 (22.3) | 0.97 (0.96 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | 0.001 | |
| Asthma | 0.174 | ||||||
| No | 9637 | 1709 (17.7) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | 0.174 |
| Yes | 455 | 122 (26.8) | 0.99 (0.97 ~ 1.01) | 0.178 | 1 (0.97 ~ 1.03) | 0.882 | |
| Memory disease | |||||||
| No | 9957 | 1780 (17.9) | 0.97 (0.97 ~ 0.98) | <0.001 | 0.98 (0.97 ~ 0.99) | <0.001 | 0.35 |
| Yes | 135 | 51 (37.8) | 0.96 (0.93 ~ 0.99) | 0.018 | 0.96 (0.92 ~ 1) | 0.047 | |
Note: Adjusted for age group and body mass index (BMI).
Abbreviations: 95% CI, 95% confidence interval; HGS, handgrip strength; OR, odds ratio.
Discussion
Main Findings
Our study, involving a population of 10,092 middle‐aged and older individuals, investigated the association between HGS and hip fracture and falls. In this large population‐based study, we found compelling evidence that higher HGS was significantly associated with lower hip fracture and fall risk in both men and women, even after adjusting for various factors.
Association between HGS and Hip Fracture Risk
Our study revealed a dose–response relationship between HGS and hip fracture risk, with higher quintiles of HGS associated with decreased odds ratios for hip fracture in both men and women. Individuals who suffered hip fractures exhibited lower HGS than those who remained fracture‐free, indicating the importance of musculoskeletal strength in maintaining bone health. This finding further supports the notion that interventions to improve muscle strength, such as resistance training, could potentially reduce the risk of hip fractures in older individuals. Our findings suggest that low HGS may be a potential risk factor for falls in middle age and older adults, and improving HGS may be beneficial in reducing fall risk. 18
Previous studies have shown inconsistent results regarding the association between HGS and bone health, possibly due to differences in age, gender, and population. 11 Wang and colleagues conducted a cross‐sectional study which analyzed that grip strength, hip muscle area and density, and bone parameters were lower in patients with hip fractures compared to corresponding healthy controls. 19 Han et al. found that pre‐ and post‐operative HGS was associated with walking ability and quality of life after hip fracture. 20 Selakovic et al. discovered that weak HGS was an independent predictor of poorer functional prognosis at 3 and 6 months after hip fracture for both genders and all age groups. 21 In addition, older obese women have increased risk of leg and ankle fractures if their HGS is insufficient. 9 A meta‐analysis conducted by Kunutsor et al. showed that improving HGS is associated with reducing the risk of future fractures. 10 These findings emphasize the importance of HGS as a prognostic factor for functional outcomes in patients with hip fractures. Some previous studies have also shown that grip strength is not associated with an increased risk of hip fracture. 11
Our study included a relatively large sample size of middle‐aged and older individuals, which may better reflect the relationship in this age group. Our findings are consistent with previous studies that have suggested the importance of HGS as a predictor of falls and fractures in middle age and older adults. The results showed a significant inverse association between HGS and hip fracture risk, suggesting that high HGS may be a protective factor against hip fracture in middle‐aged and older individuals.
Relationship between HGS and Falls
The results also suggest that the inverse dose–response relationship between HGS and falls, aligning with previous studies. 22 , 23 , 24 , 25 Falls are a common cause of injury among older individuals, and improving HGS may be an effective strategy to reduce fall risk. 9 , 22 Interestingly, the association between HGS and falls was stronger in men than in women, indicating that sex‐specific differences may exist in this relationship.
Mechanisms Supporting and Implications of HGS Assessment
The observed dose–response relationship between HGS and reduced hip fracture risk underscores its potential protective effect. HGS serves as a marker of overall muscle strength crucial for maintaining balance and preventing falls. 25 , 26 Stronger muscles can absorb more force during a fall, reducing the risk of injury. Additionally, HGS may signify overall health status, as diminished physical function often correlates with heightened risk of falls and fractures. 27 , 28 , 29 Low HGS has been suggested as an indicator of sarcopenia, potentially exacerbating fall and fracture risks. 30 Increased HGS may thus reflect enhanced overall physical function and mobility, mitigating fall and hip fracture risks.
Our findings advocate for assessing HGS to identify individuals at risk of hip fractures and falls. Regular monitoring could facilitate early intervention targeting muscle strength and fall risk reduction. Furthermore, our study could inform the development of future interventions aimed at reducing hip fracture risk and fall incidence, addressing modifiable risk factors such as impaired balance, gait abnormalities, and environmental hazards. Enhancing HGS may contribute to fall prevention by improving muscle strength, coordination, and postural control.
Limitations and Strengths
Although this study has several strengths, including a large sample size and comprehensive adjustments for potential confounding factors, there are also some limitations. First, the study is observational and cannot establish causality. Second, HGS was only measured once at baseline, and changes in HGS over time were not considered. Additionally, bone density and the time of the hip fracture data were not available. Furthermore, our study did not assess the prognosis for hip fractures and falls, which represents an important limitation. Future research should explore novel prognostic factors and therapeutic interventions to enhance the management and recovery of hip fractures and falls.
Conclusion
In conclusion, our study indicated that grip strength has significant predictive value in assessing hip fractures and falls risk among middle‐aged and elderly individuals. These findings carry critical implications for public health strategies, emphasizing the need for tailored interventions and the integration of HGS improvement initiatives into preventive programs. Further research is warranted to explore the mechanisms underlying these associations and determine optimal HGS levels for preventing hip fractures and falls.
Conflict of Interest Statement
The authors declare no conflicts of interest regarding the publication of this article.
Ethics Statement
The CHARLS is approved by the Biomedical Ethics Review Committee of Peking University, and all participants provide informed consent. The data of the CHARLS is available for free on the Peking University Open Research Data Platform (https://charls.charlsdata.com/). Because the study used publicly available deidentified data and informed consent was waived. Based on a publicly accessible database, this study did not require ethical approval or informed consent.
Author Contributions
Tianting Guo, Fei Zhang, and Lijiao Xiong: Conceiving the protocol, data analysis and interpretation, acquisition of data, statistical analysis and interpretation of data; manuscript preparation. Zhihua Huang: Revision of the manuscript. Xiaoan Zhang, Junming Wan and Jianwen Mo: Final drafting of the manuscript; study supervision. All authors agree to be fully accountable for ensuring the integrity and accuracy of the work, and read and approved the final manuscript.
Funding Information
This work was supported by Administration of Traditional Chinese Medicine of Jiangxi Province, China (grant Nos. 2021A374 and 2020A0042), Ganzhou Municipal Science and Technology Planning Project (grant No. 2023LNS26841) and the Science and technology plan of Jiangxi Provincial Health Committee (grant No. 202312146), China.
Consent for Publication
All participants agreed to publish.
Acknowledgments
Thanks to the CHARLS research team and every respondent for their time and efforts. We thank the Free Statistics team for providing technical assistance and valuable data analysis and visualization tools.
Tianting Guo and Fei Zhang contributed equally to this study.
Disclosure: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Contributor Information
Xiaoan Zhang, Email: zhangxa1972@126.com.
Junming Wan, Email: doctorwan@i.smu.edu.cn.
Jianwen Mo, Email: mjw1997@126.com.
Data Availability Statement
The datasets generated and analyzed during the current study are available in the CHARLS website, available in https://charls.charlsdata.com/.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analyzed during the current study are available in the CHARLS website, available in https://charls.charlsdata.com/.