Abstract
Purpose
The World Health Organization (WHO) defines Intrinsic Capacity (IC) as the integration of an individual’s physiological and psychological capacities. Encompassing five dimensions— locomotion, cognitive, vitality, psychological, and sensory function—it plays a central role in the assessment of healthy ageing. This study aimed to evaluate the association between IC and hip fractures among community-dwelling older adults in China.
Patients and methods
This population-based longitudinal study analyzed data from 3102 community-dwelling residents aged ≥ 60 years in the China Health and Retirement Longitudinal Study (CHARLS), with baseline assessments conducted in 2011 and a 4-year follow-up through 2015. IC was assessed across five domains: cognitive, psychology, vitality, locomotion, and sensory function. The outcome measure was self-reported hip fracture, while demographic characteristics and other covariates were analyzed as potential confounders. Multivariable logistic regression models were employed to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CI). The relationship between IC and hip fracture was further evaluated using restricted cubic splines and subgroup analyses.
Results
A total of 3,102 older adults (57.16% male) with a median age of 65.00 years were included. Over the 4-year follow-up, 96 participants (3.09%) experienced hip fractures. Regarding IC, the total IC score for the entire cohort was 1.56 ± 1.07(range 0–5, a total score of ≥ 2 is defined as IC impairment). The hip fracture group exhibited significantly higher IC scores compared to the non-fracture group (2.14 ± 1.06 vs.1.14 ± 1.06, p < 0.001). Baseline IC impairment (observed in 48.42% of participants) was associated with a 2.34-fold higher incidence of hip fracture compared to those without impairment (4.39% vs.1.88%). Analysis revealed that each 1-point increase in IC score among individuals aged ≥ 60 years was associated with a 55% elevated risk of hip fracture (adjusted OR = 1.55, 95% CI 1.25–1.94, p < 0.001). When stratified by IC status, the effect was more pronounced with IC-impaired. Compared to without impaired group, individuals with IC impairment had 87% higher risk of fracture (adjusted OR = 1.87, 95% CI 1.72–2.98, p = 0.009). Additionally, a linear relationship was demonstrated between IC and hip fracture risk.
Conclusion
Among community-dwelling older adults, the composite IC score demonstrated a significant independent association with an elevated risk of hip fracture. Regular monitoring of individual IC scores may serve as an early warning indicator to initiate preventive interventions.
Keywords: Hip fracture, Intrinsic capacity, CHARLS
Introduction
With the deepening global trend of population aging, the number of older adults with hip fractures continues to rise. It is projected that by 2050, the annual global incidence of hip fractures will exceed 6 million cases. Due to severe aging trends in many Asian countries, approximately 50% of these fractures are expected to occur in Asia, with China facing a particularly significant burden [1, 2]. Demographic data reveal that China’s population aged 60 and above reached 249 million in 2018, accounting for 17.9% of the total population. This proportion is anticipated to surpass 30% by 2050, corresponding to an elderly population exceeding 450 million [3]. Hip fractures in the elderly are highly devastating acute events characterized by high morbidity, disability, and mortality rates, posing significant challenges to both individual health and healthcare systems. Globally, approximately 20% of hip fracture patients die within one year post-fracture, and over 50% experience permanent functional impairment. This public health crisis is exacerbated in the context of rapidly aging societies [4]. Current research identifies age, gender, bone mineral density, smoking, alcohol consumption, and falls as key risk factors for hip fractures [5–7]. It is noteworthy that although hip fracture is often viewed as a purely mechanical injury caused by external force, recent reviews increasingly recognize it as a systemic event that both reflects and accelerates biological vulnerability and frailty progression. Its occurrence and prognosis are closely linked to the decline in overall physiological reserve in older adults [8]. Given the high complexity of health status in the elderly population, a multidimensional approach is urgently needed to assess their underlying risk [9].
The concept of “healthy ageing,” proposed by the World Health Organization (WHO) in the Global Report on Ageing and Health (2015) [10], transcends the static notion of “absence of disease as health.” It defines healthy ageing as “a holistic state based on functional ability”. This framework emphasizes the need to continuously develop and maintain the functional ability of older adults from a life-course perspective to enhance their well-being and quality of life [10, 11]. To this end, WHO proposes “Intrinsic Capacity” (IC) as a core integrative indicator for assessing the overall health status of older adults and formulating personalized intervention plans. IC is defined as “the integration of an individual’s physiological and psychological capacities”, encompassing five core domains: locomotion, cognition, vitality, sensory function, and psychological health [10, 11]. Together, these constitute the foundation of an individual’s ability to adapt to stressors (including disease, injury, or hospitalization) [12].IC moves beyond a narrow focus on isolated diseases or deficits, emphasizing the holistic, dynamic, and individual-differentiated nature of older adults’ health status. It also highlights resilience (i.e., the ability to recover from stressors) as a key determinant of long-term health outcomes [13]. Longitudinal studies provide robust evidence for the aggregation model of IC, demonstrating its ability to accurately reflect current health status and predict adverse health outcomes in the older adults [14–16]. Recent systematic reviews show that 76.1% [17] of older adults globally exhibit signs of declining IC, with this proportion reaching 67.8% among community-dwelling older adults [18]. This decline is prevalent and strongly associated with frailty, falls, long-term nursing home admission, mortality, and other adverse health conditions [19–21]. It also provides a scientific basis for shifting the healthcare model from “disease-centered” to “function-sustaining management” [10]. As a comprehensive measure of aging, IC reflects an individual’s functional ability and physiological reserve, which determine their capacity to cope with stressors and withstand acute health events. Within this framework, hip fracture constitutes a significant challenge to IC, simultaneously impacting multiple domains such as locomotion, cognitive, psychological, vitality, and sensory function [9]. This exposes underlying, potentially previously compensated, vulnerabilities. Understanding hip fracture from an IC perspective enables clinicians and researchers to move beyond focusing solely on survival or symptom control. It allows them to focus on strategies for fostering recovery capacity amidst adversity, supporting adaptation, and maintaining autonomy [22]. However, the relationship between IC and hip fracture risk remains insufficiently studied. This study leverages nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS) to investigate the association between IC and hip fractures among adults aged ≥ 60 years.
Method
Study population
This study utilized three waves of longitudinal data (2011–2015) from the China Health and Retirement Longitudinal Study (CHARLS). This nationally representative survey employed a four-stage stratified sampling protocol: (1) selecting 150 county-level units across 28 provincial-level administrative regions; (2) identifying 450 villages/communities; (3) sampling households; and (4) enrolling individuals aged ≥ 45 years. The baseline survey (June 2011–March 2012) included 17,705 adults (80.5% response rate), with biennial follow-up waves conducted in 2013 (Wave 2) and 2015 (Wave 3). CHARLS collects multidimensional health metrics, encompassing demographics, physical examinations (height, weight, grip strength), functional tests (balance assessment, walking speed, repeated chair stand performance), and health status/functionality (including falls and hip fractures). Exclusion criteria: (1) age < 60 years or missing age data; (2) baseline history of hip fracture (2011); (3) missing baseline IC data; (4) absence of follow-up hip fracture data. The study commenced in 2011 and followed participants until 2016. At baseline, we screened individuals aged ≥ 60 years (excluding 10,016 individuals). Subsequently, 708 participants were excluded due to pre-existing hip fractures or unknown fracture status at baseline, 3,109 due to incomplete IC data, 736 due to missing follow-up data, and 34 due to missing covariates (Fig. 1). The final analytic sample comprised 3,102 participants. Ethical approval for CHARLS was granted by the Biomedical Ethics Committee of Peking University (IRB00001052-11015) [23]. All CHARLS participants provided informed consent. Further details on CHARLS methodology are publicly accessible. Secondary use of data for this study complied with ethical requirements, including prior ethical approval and participant consent protocols [24].
Fig. 1.
Flowchart showing the selection of the elder participants enrolled in the study of hip fracture in China
Intrinsic capacity domains
The five-domain structure of IC established by Cesari et al. [25] has been validated in multiple studies, demonstrating that IC effectively assesses the overall functional status of older adults. Therefore, this study adopts a comprehensive IC score based on these five domains. Each domain is evaluated dichotomously (impaired = 1, unimpaired = 0), and a total score of ≥ 2 is defined as IC dysfunction [26]. The assessment tools adopted in each dimension are based on the framework [27] formulated by the WHO and previous studies [28–30], as follows:
(1) Cognitive [31]: Cognitive function was assessed across four domains: orientation (year, month, date, day of the week, and season), memory (immediate and delayed recall of 10 words after 4 min), calculation (serial subtraction of 7 from 100 repeated five times), and visuospatial ability (figure drawing). Memory score (range: 0–20) was calculated by summing the number of correctly recalled words in both immediate and delayed recall tasks. Orientation, calculation, and drawing tasks awarded 1 point for each correct response. Total cognitive score (maximum: 31 points) was derived from the sum of scores in orientation (5 points), memory (20 points), calculation (5 points), and drawing (1 point).Cognitive impairment was defined as age-related decline in cognitive ability, specifically identified as a score falling ≥ 1 standard deviation (SD) below the age-specific normative mean [32]. All participants were stratified into 5-year age intervals for comparative analysis [33].
(2) Psychological [34, 35]: The psychological dimension was assessed using the 10-item Center for Epidemiologic Studies Depression (CES-D) scale, which evaluates the frequency of emotional and behavioral symptoms experienced in the past week. Response options range from 0 (“rarely or never”) to 3 (“most of the time”), with Items 5 and 8 reverse-scored. Higher CES-D scores indicate greater severity of depressive symptoms, with total scores ranging from 0 to 30. A total score of ≥ 10 was classified as indicative of psychological impairment [36].
(3) Sensory [37, 38]: Sensory function was assessed via self-report using three questions: “How well can you see distant objects?“, “How well can you see nearby objects?“, “How well can you hear?“. Responses were categorized as “excellent,” “very good,” “good,” “fair,” or “poor.” Sensory impairment was defined as reporting “poor” in at least one of the three items [15].
(4) Vitality: Vitality was assessed using body mass index (BMI), which is similar to previous studies in IC [37, 38]. Body weight and height were measured with an Omron™ HN-286 digital scale and a Seca™ 213 stadiometer, respectively. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m²). Underweight (BMI < 18.5) and severe obesity (BMI >40.0) were classified as vitality impairment [39].
(5) Locomotion: The locomotion domain was assessed using the Short Physical Performance Battery (SPPB). Five-Times Sit-to-Stand Test: Participants were seated with arms crossed over the chest and instructed to complete five consecutive sit-to-stand movements. Scoring criteria: ≥16.7 s: 1 point; 13.7–16.6 s: 2 points; 11.2–13.6 s: 3 points; ≤11.1 s: 4 points; Inability to complete: 0 points. 2.5-Meter Gait Speed Test: Participants walked a 2.5-meter straight path twice, with the fastest time recorded. Gait speed (m/s) was calculated as: Gait speed (m/s) = 2.5/completion time (s). 2.5Scoring criteria: ≤0.43 m/s: 1 point; 0.44–0.60 m/s: 2 points; 0.61–0.77 m/s: 3 points; ≥0.78 m/s: 4 points; Inability to complete: 0 points. Balance Test: Semi-tandem stand: Participants attempted to stand with the heel of one foot touching the toe of the other for 10 s. Full tandem stand: Participants who passed the semi-tandem stand were further assessed based on age: ≥70 years: 30-second full tandem stand; <70 years: 60-second full tandem stand. Side-by-side stand: Participants unable to perform the semi-tandem stand were tested for 10 s. Scoring criteria: 1 point: Held side-by-side stand for 10 s but failed semi-tandem stand.2 points: Held semi-tandem stand for 10 s but full tandem stand for 0–2 s.3 points: Held full tandem stand for 3–9 s.4 points: Held full tandem stand for ≥ 10 s.0 points: Inability to perform any balance task. A total SPPB score < 9 was defined as locomotion impairment [40, 41].
Hip fracture
The occurrence of hip fractures was assessed using a standardized interview protocol [42, 43]. The primary outcome measure was collected through a hierarchical question structure:
Initial participants were asked, “Have you ever experienced a hip fracture?“. Follow-up participants were asked, “Have you experienced a hip fracture since your last interview?“. During the inquiry, investigators provided detailed explanations of the definition and anatomical location of hip fractures (e.g., femoral neck, intertrochanteric, or subtrochanteric regions) to ensure participants fully understood the condition. Responses were recorded as binary outcomes (“Yes” or “No”).
Covariates
The following variables, potentially associated with hip fracture risk, were adjusted for in the analysis: Demographics: Age, sex (male/female), education level (secondary school or low/secondary school or higher), marital status(married/single or divorced or widowed).Lifestyle factors: Smoking status (smoker/ex-smoker/non-smoker), alcohol consumption (yes/no), grip strength. Fall history: Participants were asked, “Have you experienced any falls in the past two years?” with explicit clarification that “past two years” referred to the 24-month period preceding the interview date. A “yes” response was classified as a fall history. Chronic diseases: Self-reported physician-diagnosed conditions, including hypertension, dyslipidemia, diabetes, chronic lung disease, heart disease, kidney disease, and arthritis or rheumatism. These conditions were confirmed based on self-reported physician diagnoses combined with health assessments and medication records.
Statistical analysis
In this study, baseline characteristics were summarized using descriptive statistics. Normally distributed variables are presented as mean ± standard deviation (SD), while non-normally distributed variables are reported as median with interquartile range (IQR). Continuous variables were compared using the non-parametric Mann-Whitney U test, and categorical variables were analyzed with the chi-square test. Participants with missing data in any variable were excluded via complete-case analysis. Logistic regression models were employed to examine the independent and joint associations between hip fractures and IC scores or domain-specific impairments. Three models were constructed: Model 1: Crude model (unadjusted for covariates). Model 2: Adjusted for age, sex, education level, marital status, residence, smoking status, alcohol consumption, fall history, and grip strength. Model 3: Further adjusted for comorbidities (hypertension, dyslipidemia, diabetes, chronic lung disease, heart disease, kidney disease, and arthritis or rheumatism) based on Model 2. The dose-response relationship between IC scores and hip fracture risk was evaluated using restricted cubic spline (RCS) regression. Subgroup analyses were conducted, including sex-stratified analyses (male vs. female). All regression results are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Statistical analyses were performed using R software (version 4.3.1) and SPSS (version 26.0). A two-sided p-value < 0.05 was considered statistically significant.
Results
Table 1 summarizes the characteristics of the baseline study population. The final analysis included 3,102 participants with a median age of 65.00 years (IQR: 62.00–70.00) and a mean age of 66.77 (SD = 5.71), of whom 1,773 (57.16%) were male. During the 4-year follow-up, 96 participants (3.09%) experienced hip fractures, including 42 females and 54 males. Univariate analysis revealed that the hip fracture group exhibited the following characteristics: Higher median age (68.00 vs. 65.00 years, p = 0.002), Lower education attainment (86.46% vs. 77.78% with secondary education or below, p = 0.043), Higher prevalence of falls in the past two years (28.12% vs. 17.56%, p = 0.008), Reduced grip strength (median: 26.25 [IQR: 20.00–35.50] vs. 28.77 [23.50–35.60] kg, p = 0.006). For IC metrics, the total IC score in the overall population was 1.56 ± 1.07. The fracture group had significantly higher IC scores than the non-fracture group (2.14 ±1 .14 vs. 1.54 ± 1.06, p < 0.001). Participants with baseline IC impairment (48.42%) exhibited a 2.34-fold higher incidence of hip fractures compared to those without impairment (4.39% vs. 1.88%) (Fig. 2). Across specific IC domains: Cognitive impairment (31.25% vs. 16.63%, p < 0.001), Psychological impairment (52.08% vs. 35.99%, p = 0.001), Locomotor impairment (44.75% vs. 24.92%, p < 0.001) were significantly associated with fracture risk. Notably, sensory impairment (p = 0.117) and vitality impairment (p ≥ 0.562) showed no significant associations.
Table 1.
Characteristics of surveyed participants at baseline (2011)
| Total (n = 3102) |
Non-fracture (n = 3006) |
Hip fracture (n = 96) |
χ²/F/Z | P | |
|---|---|---|---|---|---|
| Age (Q₁, Q₃) | 65.00 (62.00, 70.00) | 65.00 (62.00, 70.00) | 68.00 (64.00, 73.00) | -2.74 | 0.002 |
| Gender, n (%) | |||||
| Female | 1329 (42.84) | 1287 (42.81) | 42 (43.75) | 0.03 | 0.855 |
| Male | 1773 (57.16) | 1719 (57.19) | 54 (56.25) | ||
| Education, n (%) | 4.09 | 0.043 | |||
| Secondary school or low | 2421 (78.05) | 2338 (77.78) | 83 (86.46) | ||
| Secondary school or higher | 681 (21.95) | 668 (22.22) | 13 (13.54) | ||
| Marriage, n(%) | 2.04 | 0.153 | |||
| Married | 2589 (83.46) | 2514 (83.63) | 75 (78.12) | ||
| Single or divorce or widowed | 513 (16.54) | 492 (16.37) | 21 (21.88) | ||
| Smoking, n (%) | 0.48 | 0.786 | |||
| Non-smoker | 1637 (52.77) | 1583 (52.66) | 54 (56.25) | ||
| Ex-smoker | 379 (12.22) | 368 (12.24) | 11 (11.46) | ||
| Smoker | 1086 (35.01) | 1055 (35.10) | 31 (32.29) | ||
| Drinking, n (%) | 0.49 | 0.485 | |||
| No | 2029 (65.41) | 1963 (65.30) | 66 (68.75) | ||
| Yes | 1073 (34.59) | 1043 (34.70) | 30 (31.25) | ||
| Grip strength(Q₁, Q₃) | 29.77 (23.50, 36.00) | 29.77 (23.50, 36.00) | 26.25 (20.00, 35.50) | -2.74 | 0.006 |
| Hypertension, n(%) | 0.58 | 0.445 | |||
| No | 2177 (70.18) | 2113 (70.29) | 64 (66.67) | ||
| Yes | 321 (10.35) | 313 (10.41) | 8 (8.33) | ||
| Dyslipidemia | 0.43 | 0.51 | |||
| No | 2781 (89.65) | 2693 (89.59) | 88 (91.67) | ||
| Yes | 321 (10.35) | 313 (10.41) | 8 (8.33) | ||
| Diabetes, n(%) | 3.33 | 0.068 | |||
| No | 2890 (93.17) | 2805 (93.31) | 85 (88.54) | ||
| Yes | 212 (6.83) | 201 (6.69) | 11 (11.46) | ||
| Chronic lung disease, n(%) | Fisher | 0.574 | |||
| No | 3075 (99.13) | 2980 (99.14) | 95 (98.96) | ||
| Yes | 27 (0.87) | 26 (0.86) | 1 (1.04) | ||
| Heart disease, n(%) | 2.05 | 0.152 | |||
| No | 2646 (85.30) | 2569 (85.46) | 77 (80.21) | ||
| Yes | 456 (14.70) | 437 (14.54) | 19 (19.79) | ||
| Kidney disease | 1.23 | 0.268 | |||
| No | 2897 (93.39) | 2810 (93.48) | 87 (90.62) | ||
| Yes | 205 (6.61) | 196 (6.52) | 9 (9.38) | ||
| Arthritis or rheumatism, n(%) | 3.33 | 0.068 | |||
| No | 1955 (63.02) | 1903 (63.31) | 52 (54.17) | ||
| Yes | 1147 (36.98) | 1103 (36.69) | 44 (45.83) | ||
| Fall in past two years | 7.06 | 0.008 | |||
| No | 2547 (82.11) | 2478 (82.44) | 69 (71.88) | ||
| Yes | 555 (17.89) | 528 (17.56) | 27 (28.12) | ||
| IC score | 1.56 ± 1.07 | 1.54 ± 1.06 | 2.14 ± 1.14 | − 5.42 | < 0.001 |
| IC impairment, n(%) | 1502 (48.42) | 1436 (47.77) | 66 (68.75) | 16.39 | < 0.001 |
| Cognitive impairment, n(%) | 530 (17.09) | 500 (16.63) | 30 (31.25) | 14.03 | < 0.001 |
| Vitality impairment, n(%) | 272 (8.77) | 262 (8.72) | 10 (10.42) | 0.34 | 0.562 |
| Sensory impairment, n(%) | 2098 (67.63) | 2026(67.40) | 72 (75.00) | 2.46 | 0.117 |
| Psychological impairment, n(%) | 1132 (36.49) | 1082 (35.99) | 50 (52.08) | 10.39 | 0.001 |
| Locomotion impairment, n(%) | 793 (25.56) | 750 (24.95) | 43 (44.79) | 19.25 | < 0.001 |
Abbreviations: IC: Intrinsic capacity; Q1: 25th percentile; Q3: 75th percentile
Fig. 2.
Bar graph of hip fracture accident rates within participants without/with IC impairment. Note: chi-squared test: P < 0.001
Association between intrinsic capacity (IC) and 4-Year hip fracture risk
This study analyzed the relationship between IC and hip fracture risk using multivariable logistic regression models (Table 2). Results demonstrated a significant positive correlation between IC scores and hip fracture risk, which remained robust across adjustment models. In the unadjusted model (Model 1), each 1-unit increase in IC score was associated with a 74% higher fracture risk (OR = 1.74, 95% CI: 1.42–2.12, p < 0.001). After adjusting for age, education level, marital status, residence, smoking, alcohol consumption, grip strength, and fall history (Model 2), the risk increase attenuated to 58% (OR = 1.58, 95% CI: 1.27–1.96, p < 0.001). Further adjustment for chronic diseases (including hypertension, dyslipidemia, diabetes, chronic lung disease, heart disease, kidney disease, and arthritis or rheumatism) in Model 3 maintained a significant 55% elevated risk (OR = 1.55, 95% CI: 1.25–1.94, p < 0.001). When stratifying IC into impaired vs. unimpaired groups, the association was more pronounced. Compared to unimpaired individuals, those with IC impairment exhibited a 141% higher fracture risk in the unadjusted model (OR = 2.41, 95% CI: 1.55–3.73, p < 0.001). This risk remained significant, though reduced, after full adjustment (Model 3: OR = 1.87, 95% CI: 1.17–2.39, p = 0.009), indicating IC impairment as an independent risk factor for hip fractures. Sex-stratified analyses revealed notable disparities. Women had consistently higher fracture risks than men (Model 3: OR = 1.71 for women vs. 1.45 for men), with significance retained in adjusted models (Model 2 and 3: p ≤ 0.002). Restricted cubic spline (RCS) models further explored the nonlinear relationship between IC scores and fracture risk (Fig. 3). A linear positive association was observed in the overall population (linear trend p < 0.001; nonlinear p = 0.896). Stratified by sex, women exhibited a significant linear trend (p = 0.009), whereas men showed borderline significance (p = 0.051). No nonlinear trends were detected in either sex (women: p-nonlinear = 0.739; men: p-nonlinear = 0.938), aligning with logistic regression findings and underscoring heightened sensitivity to IC-related fracture risk in women. Furthermore, analyses of individual IC domains identified independent associations between psychological, locomotor, and cognitive impairments and hip fractures. Cognitive impairment demonstrated the strongest association with fracture risk.
Table 2.
The relationship between intrinsic capacity(IC) and 4-year hip fracture
| Variables | Model1 | Model2 | Model3 | |||
|---|---|---|---|---|---|---|
| OR (95%CI) | P | OR (95%CI) | P | OR (95%CI) | P | |
| IC score | 1.74 (1.42–2.12) | < 0.001 | 1.58 (1.27–1.96) | < 0.001 | 1.55 (1.25–1.94) | < 0.001 |
| Female IC score | 1.88 (1.39–2.55) | < 0.001 | 1.71 (1.23–2.37) | 0.001 | 1.71 (1.22–2.39) | 0.002 |
| Male IC score | 1.68 (1.27–2.21) | < 0.001 | 1.50 (1.11–2.01) | 0.007 | 1.45 (1.08–1.96) | 0.014 |
|
Without IC impairment |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|||
| IC impairment | 2.41 (1.55–3.73) | < 0.001 | 2.00 (1.26–3.16) | 0.003 | 1.87 (1.17–2.98) | 0.009 |
| Psychological | ||||||
| Without impairment |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|||
| impairment | 1.93 (1.29–2.90) | 0.002 | 1.68 (1.10–2.56) | 0.017 | 1.55 (1.01–2.39) | 0.048 |
| Cognitive | ||||||
| Without impairment |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|||
| impairment | 2.28 (1.46–3.54) | < 0.001 | 2.06 (1.29–3.27) | 0.002 | 2.03 (1.27–3.25) | 0.003 |
| Locomotion | ||||||
| Without impairment |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|||
| impairment | 2.44 (1.62–3.68) | < 0.001 | 1.97 (1.27–3.06) | 0.003 | 1.93 (1.24-3.00) | 0.004 |
Note: IC: intrinsic capacity; OR: Odds Ratio, CI: Confidence Interval; Model 1: Unadjusted (crude); Model 2: Adjusted for age, education, marriage, residence, smoking, drinking, grip strength, and fall; Model 3: Additionally adjusted for hypertension, dyslipidemia, diabetes, chronic lung disease, heart disease, kidney disease, and arthritis or rheumatism
Fig. 3.
Association Between Intrinsic Capacity index and Hip Fracture Risk
Subgroup analyses
In subgroup analyses, the positive association between IC and 4-year hip fracture risk was consistently observed across diverse populations (Table 3). Significant associations were found in both age groups: Age ≥ 65 years (adjusted OR = 1.65, 95% CI: 1.29–2.13, p < 0.001), Age < 65 years (adjusted OR = 1.56, 95% CI: 1.04–2.32, p = 0.03), though no significant interaction effect was detected between age groups (p for interaction = 0.604). Sex-stratified analyses revealed elevated risks in both: Women (adjusted OR = 1.73, 95% CI: 1.26–2.36, p < 0.001), Men (adjusted OR = 1.57, 95% CI: 1.17–2.10, p = 0.002), with no significant sex interaction (p for interaction = 0.526). The divorced/widowed group exhibited significantly higher fracture risk (adjusted OR = 2.24, 95% CI: 1.42–3.53) compared to the married group (adjusted OR = 1.49, 95% CI: 1.17–1.90). Notably, non-smokers (adjusted OR = 1.82, 95% CI: 1.38–2.41, p < 0.001) and current alcohol consumers (adjusted OR = 1.95, 95% CI: 1.31–2.90, p = 0.001) showed stronger associations than other subgroups. Among chronic diseases, higher IC scores were significantly associated with increased fracture risk in participants with hypertension, dyslipidemia, hyperglycemia, heart disease, and kidney disease (p < 0.001 for all). However, no statistically significant interaction effects were observed between IC and comorbid chronic diseases (p for interaction > 0.05), indicating that the combined influence of IC and chronic diseases on fracture risk did not differ significantly.
Table 3.
Subgroup analyses for the association between intrinsic capacity and 4-year hip fracture risk
| Subgroup | n (%) | Crude OR (95%CI) |
Crude P |
Adjusted OR (95% CI) |
Adjusted p-value | p for interaction |
|---|---|---|---|---|---|---|
| Age Group | 0.604 | |||||
| ≥65 | 1743 (56.19) | 1.77 (1.39–2.24) | < 0.001 | 1.65 (1.29–2.13) | < 0.001 | |
| <65 | 1359 (43.81) | 1.53 (1.04–2.24) | 0.029 | 1.56 (1.04–2.32) | 0.03 | |
| Gender | 0.526 | |||||
| Female | 1329 (42.84) | 1.88 (1.39–2.55) | < 0.001 | 1.73 (1.26–2.36) | < 0.001 | |
| Male | 1773 (57.16) | 1.68 (1.27–2.21) | < 0.001 | 1.57 (1.17–2.10) | 0.002 | |
| Marriage | 0.35 | |||||
| Single/divorced/widowed | 513 (16.54) | 2.10 (1.36–3.22) | < 0.001 | 2.24 (1.42–3.53) | < 0.001 | |
| Married | 2589 (83.46) | 1.63 (1.30–2.05) | < 0.001 | 1.49 (1.17–1.90) | 0.001 | |
| Education | 0.968 | |||||
| Secondary school or low | 2421 (78.05) | 1.70 (1.37–2.10) | < 0.001 | 1.61 (1.29–2.02) | < 0.001 | |
| Secondary school or higher | 681 (21.95) | 1.69 (0.86–3.34) | 0.129 | 1.58 (0.77–3.23) | 0.214 | |
| Residence | 0.88 | |||||
| Rural | 386 (12.44) | 1.70 (1.04–2.78) | 0.035 | 1.48 (0.88–2.50) | 0.142 | |
| Urban | 2716 (87.56) | 1.77 (1.42–2.20) | < 0.001 | 1.68 (1.34–2.12) | < 0.001 | |
| Smoking | 0.348 | |||||
| Ex-smoker | 379 (12.22) | 1.52 (0.80–2.89) | 0.202 | 1.52 (0.77–3.02) | 0.23 | |
| Non-smoker | 1637 (52.77) | 1.97 (1.52–2.57) | < 0.001 | 1.82 (1.38–2.41) | < 0.001 | |
| Smoker | 1086 (35.01) | 1.43 (0.99–2.06) | 0.057 | 1.37 (0.93–2.02) | 0.113 | |
| Drinking | 0.293 | |||||
| No | 2029 (65.41) | 1.61 (1.27–2.05) | < 0.001 | 1.53 (1.19–1.96) | < 0.001 | |
| Yes | 1073 (34.59) | 2.07 (1.43-3.00) | < 0.001 | 1.95 (1.31–2.90) | 0.001 | |
| Hypertension | 0.688 | |||||
| No | 2177 (70.18) | 1.78 (1.40–2.27) | < 0.001 | 1.65 (1.28–2.14) | < 0.001 | |
| Yes | 925 (29.82) | 1.64 (1.15–2.34) | 0.006 | 1.58 (1.09–2.29) | 0.015 | |
| Dyslipidemia | 0.666 | |||||
| No | 2781 (89.65) | 1.76 (1.43–2.17) | < 0.001 | 1.65 (1.32–2.05) | < 0.001 | |
| Yes | 321 (10.35) | 1.46 (0.70–3.04) | 0.312 | 1.39 (0.64-3.00) | 0.404 | |
| Diabetes | 0.325 | |||||
| No | 2890 (93.17) | 1.69 (1.37–2.09) | < 0.001 | 1.60 (1.28-2.00) | < 0.001 | |
| Yes | 212 (6.83) | 2.34 (1.20–4.56) | 0.012 | 2.12 (1.05–4.30) | 0.037 | |
| Chronic lung disease | 0.367 | |||||
| No | 3075 (99.13) | 1.73 (1.41–2.11) | < 0.001 | 1.62 (1.31-2.00) | < 0.001 | |
| Yes | 27 (0.87) | 4.73 (0.36–62.30) | 0.237 | 4.83 (0.13-174.83) | 0.39 | |
| Heart disease | 0.831 | |||||
| No | 2646 (85.30) | 1.72 (1.38–2.15) | < 0.001 | 1.65 (1.30–2.08) | < 0.001 | |
| Yes | 456 (14.70) | 1.78 (1.11–2.85) | 0.016 | 1.53 (0.93–2.53) | 0.094 | |
| Kidney disease | 0.56 | |||||
| No | 2897 (93.39) | 1.76 (1.43–2.18) | < 0.001 | 1.64 (1.31–2.05) | < 0.001 | |
| Yes | 205 (6.61) | 1.44 (0.75–2.76) | 0.268 | 1.45 (0.74–2.87) | 0.282 | |
| Arthritis or rheumatism | 0.653 | |||||
| No | 1955 (63.02) | 1.65 (1.25–2.19) | < 0.001 | 1.44 (1.07–1.95) | 0.015 | |
| Yes | 1147 (36.98) | 1.78 (1.32–2.39) | < 0.001 | 1.81 (1.33–2.47) | < 0.001 | 0.604 |
Adjusted for age group and grip strength; Abbreviations: Odds Ratio, CI: Confidence Interval
Discussion
Our study enrolled 3,102 community-dwelling elderly participants and conducted a 4-year follow-up to preliminarily explore the relationship between IC and hip fractures. To our knowledge, this is the first study utilizing nationally representative data to examine the longitudinal association between IC and hip fractures among individuals aged 60 and above in Chinese communities. We identified an independent association between IC scores and hip fracture risk, with further investigation highlighting the significance of gender differences. Results demonstrated that each 1-point increase in the total IC score was associated with a 55% elevated risk of hip fractures (adjusted OR = 1.55), while individuals with IC impairment exhibited an 87% higher risk (adjusted OR = 1.87). Notably, women demonstrated a stronger sensitivity to risk (OR = 1.71 vs. men OR = 1.45), and a significant linear association between IC and fracture risk was observed in this population.
The findings of this study are consistent with existing literature, further elucidating the predictive value of IC as a multidimensional health indicator for adverse outcomes in older adults. Previous studies have demonstrated that IC effectively predicts falls, frailty, disability, and mortality [44, 45]. By focusing specifically on hip fractures, this research extends the clinical applicability of IC assessments. Our results reveal an independent association between IC and hip fracture risk, corroborating findings from a cross-sectional study by Ma et al. [46], which identified a significant correlation between IC impairment and fracture susceptibility. However, few studies have explored the longitudinal relationship between IC and fractures. Our findings advance this knowledge by demonstrating that baseline IC impairment significantly increases subsequent hip fracture risk, supporting its potential as a prospective predictor of fractures. The exact mechanism linking IC to hip fractures is unclear, but several factors might explain this connection. Physical mobility impairment can lead to gait disorders and poor balance in the elderly, further increasing their risk of falls and subsequent hip fractures [47]. Cognitive impairment compromises decision-making and environmental risk assessment, leading to unsafe behaviors that elevate fracture risk [48]. Psychological factors, particularly depressive symptoms, are associated with fatigue-induced physical inactivity and accelerated functional decline, further exacerbating vulnerability to fractures [49]. Post-fracture IC deterioration, driven by prolonged hospitalization, reduced mobility, and complications, may create a bidirectional cycle of decline. Prior studies indicate that pre-fracture functional status independently predicts post-fracture recovery trajectories [50], aligning with our findings and suggesting that IC assessments hold dual value for risk stratification and prognostic evaluation. To deepen understanding in this field, future research should dynamically examine domain-specific IC trajectories preceding fractures and assess how pre-fracture IC status influences post-fracture functional outcomes. Such investigations could provide a comprehensive framework for understanding IC’s role in fracture risk and recovery, offering robust evidence to inform clinical practice and public health policies.
Sex-stratified analyses revealed heightened sensitivity to IC-related fracture risk in women (OR = 1.71 for women vs. OR = 1.45 for men), consistent with prior research. Potential mechanisms may include postmenopausal estrogen decline accelerating bone mineral density loss [51] and reduced muscle mass contributing to impaired balance [52]. Additionally, the significant associations between lower education levels, fall history (p < 0.05), and fracture risk underscore the critical role of socio-behavioral factors in fracture prevention, possibly linked to limited health literacy or environmental adaptability in less educated populations [53]. Notably, the linear relationship between IC scores and fracture risk remained robust even after adjusting for sociodemographic, behavioral, and chronic disease confounders, reinforcing IC’s clinical value as an independent risk marker. This supports the need for holistic IC optimization rather than single-domain interventions. The stronger linear association in women highlights the necessity for sex-specific prevention strategies. It is worth noting that this study classified the participants strictly within a binary (male/female) framework, based on biological gender variables. This approach did not take into account the diversity of gender identities (including non-binary, transgender, and gender diverse individuals), nor did it comprehensively cover the complex interactions between biological and social-cultural factors that affect health outcomes. Future research should, where feasible, strive to adopt more inclusive measures of gender identity. Nevertheless, these findings are consistent with the WHO’s emphasis on comprehensive intervention measures, advocating for a multi-dimensional approach rather than the traditional single model.
Study limitations
This study has several limitations: Limited statistical power: The small number of hip fracture events (n = 96) may reduce the robustness of subgroup analyses. IC measurement heterogeneity: The lack of consensus on IC assessment—including indicator selection, scoring, weighting, and validation—constrains the generalizability of our findings. Static IC assessment: IC was evaluated only at baseline, precluding analysis of dynamic changes in capacity during follow-up. Self-reported outcomes: Hip fracture diagnoses relied on participant self-reports, risking recall bias. To mitigate this, interviewers provided detailed anatomical explanations of hip fractures and employed trained personnel to standardize data collection. Chronic disease data were also self-reported, potentially introducing inaccuracies. While we implemented rigorous protocols (e.g., structured questions, trained staff), residual bias may persist. Gender distribution: our cohort had a higher proportion of males (57.16% vs. 42.84% female) than typically seen in hip fracture studies, largely due to exclusion criteria: requiring complete IC data likely excluded more females with functional impairments, and excluding baseline fractures removed more females who bear a higher fracture burden. This limits generalizability to high-risk frail women, but we mitigated bias by adjusting for sex in analyses and conducting sex-stratified tests (which confirmed stronger IC effects in women). Despite these limitations, our findings contribute novel insights into IC’s role in fracture risk, advocating for longitudinal and multidimensional approaches in future research.
Conclusion
This study preliminarily explored the correlation between IC and hip fractures. The results revealed a significant linear relationship between IC scores and hip fractures among community-dwelling older adults aged 60 and above in China. Compared to the non-IC impairment group, the IC impairment group was associated with a higher risk of hip fractures. The study confirmed that greater impairment in IC is linked to an increased risk of hip fractures in the elderly and suggests that IC may serve as a potential predictive tool for hip fracture risk.
Relevance for clinical practice
This study supports the use of IC as a potential tool for hip fracture screening. Through regular assessments, especially in the cognitive, psychological, and locomotion domains, community healthcare workers can identify high - risk individuals early and initiate multidimensional interventions, such as balance training, cognitive -behavioral interventions, or resistance exercises, to reduce fall and fracture risks.
Acknowledgements
Gratitude is extended to the CHARLS research team and every respondent for devoting their time and effort.
Author contributions
Youting Wang, Qingqing Su and Hongyi Wu: Conceiving the protocol, data analysis and interpretation, acquisition of data. Xueyang Gan, Mengqi Shao, Jingru Chen : statistical analysis and interpretation of data; Youting Wang, Dan Kong: manuscript preparation. Nan Tan: Revision of the manuscript. Yuan Gao, Jie Song and Xiaojie Fu: 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.
Data availability
The datasets generated and analyzed during the current study are available in the CHARLS website, available in https://charls.charlsdata.com/.
Declarations
Competing interests
The authors declare no competing interests.
Ethics statement
The CHARLS survey received ethical approval from the Institutional Review Board of Peking University (Approval No. IRB00001052-11015), and all participants provided written informed consent.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Youting Wang, Qingqing Su and Hongyi Wu contributed equally to this work.
Contributor Information
Xiaojie Fu, Email: fxj_sugus@163.com.
Jie Song, Email: 285619923@qq.com.
Yuan Gao, Email: gaoyuanzd@163.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/.