Highlights
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Sex differences in intrinsic capacity are underexplored in the WHO Healthy Aging Framework.
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Women aged 60 and above had poorer intrinsic capacity than their male counterparts.
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Older women faced greater socioeconomic disadvantages, with less education, employment, and financial independence.
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The sex difference in intrinsic capacity diminished after adjusting for socioeconomic status.
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Sex differences in intrinsic capacity appeared only in financially dependent group.
Keywords: Intrinsic capacity, Sex difference, Socioeconomic factor, Older people, Cross-sectional study
Abstract
Objectives
The World Health Organization’s Integrated Care for Older People (ICOPE) framework launched in 2019 is used to assess the intrinsic capacity of older individuals. Older women may face greater socioeconomic disadvantages, which can impact their physical and mental well-being. Therefore, we examined sex differences in intrinsic capacity and the influence of socioeconomic status.
Methods
We conducted a cross-sectional study in Tainan, Taiwan, recruiting 1,268 adults aged 60 or older in 2022. The ICOPE screening assessed cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms. Intrinsic capacity scores ranged from 0 to 6 and were categorized as impairment (1 or higher) or no impairment (0). Binary logistic regression models were used to analyze sex differences in intrinsic capacity, adjusting sequentially for demographics, lifestyle, and socioeconomic factors.
Results
The prevalence of intrinsic capacity impairment was 34 %. Women had significantly higher odds of intrinsic capacity impairment (women vs. men, odds ratio [OR] = 1.39, 95 % CI = 1.10–1.75). After sequentially adjusting for demographic characteristics, lifestyle, and socioeconomic factors, the ORs were 1.46 (95 % CI = 1.12–1.90), 1.69 (95 % CI = 1.23–2.31), and 1.24 (95 % CI = 0.88–1.73), respectively. Stratified analyses showed that higher odds of impairment in women than in men was evident only in the financially dependent group (P for interaction = 0.059).
Conclusions
Older women in Taiwan have poorer intrinsic capacity than men, a disparity largely attributable to women’s lower socioeconomic status. Strategies to promote healthy aging among women from disadvantaged socioeconomic backgrounds may help mitigate this sex difference in intrinsic capacity.
1. Introduction
In the World Report on Ageing and Health, World Health Organization (WHO) introduced ‘intrinsic capacity' as a concept encompassing an individual's physical and mental abilities. Intrinsic capacity, along with the characteristics of the environment a person inhabits and the interactions between them, collectively determines functional ability, which is at the core of healthy aging (WHO, 2015). Studies have consistently confirmed the validity of the intrinsic capacity construct, which includes domains of locomotion, vitality (or nutrition), sensory, cognition, and psychology, and its strong relationship with performance in activities of daily living in older people, after accounting for multimorbidity and other personal characteristics (Aliberti et al., 2022, Beard et al., 2019, Beard et al., 2022). A higher intrinsic capacity composite score has also been linked to a reduced risk of adverse outcomes in older people, including mortality, falls, and cardiovascular disease in both institutional and community settings (Ramírez-Vélez et al., 2023, Zhou and Ma, 2022). These findings underscore the importance of maintaining intrinsic capacity throughout an individual’s life course, a crucial goal in WHO’s public health framework for Healthy Ageing (WHO, 2017).
Research evaluating intrinsic capacity has increased over the years, yet sex differences in intrinsic capacity have received limited attention. Generally, women outlive men but often endure poorer health conditions and greater functional limitations in later life (Hägg and Jylhävä, 2021, Oksuzyan et al., 2008). The most commonly cited biological hypothesis for the differential aging of men and women involves hormonal and genetic sex-related differences (Hägg and Jylhävä, 2021, Olivieri et al., 2023). However, it is increasingly acknowledged that both sex (biological constructs) and gender (social constructs) influence human health, encompassing the effects of behavior, lifestyle, and social factors molded by gender roles (Mauvais-Jarvis et al., 2020).
Previous studies suggest that men generally exhibit superior intrinsic capacity compared to women, and social determinants of health are linked to intrinsic capacity (Aliberti et al., 2022, Muneera et al., 2022, Zhao et al., 2023). However, the extent to which socioeconomic factors contribute to sex differences in intrinsic capacity is unclear. A deeper comprehension of these sex differences in the aging process could offer important information for health policy, especially regarding equity. Therefore, we explored the sex disparity in intrinsic capacity and the influence of socioeconomic factors in older individuals from both hospital and community settings.
2. Methods
2.1. Study design and participants
This cross-sectional study, conducted in 2022, included older adults from southern Taiwan. Participants were recruited using convenience sampling from Tainan city communities, as well as the outpatient clinics and inpatient wards of National Cheng Kung University Hospital. Individuals aged 60 years and older, without acute illness, who were capable of communicating in Mandarin Chinese or Taiwanese and able to provide consent were considered eligible. Trained interviewers collected data on demographic characteristics (age, sex, marital status, living alone, and religion), lifestyle, socioeconomic factors, and health circumstances through face-to-face questionnaires. All participants provided written informed consent. The study procedures, including data collection and analysis, adhered to the Declaration of Helsinki and the institution's guidelines for the protection of participants’ safety and privacy. Ethical approval was granted by the Institutional Review Board of National Cheng Kung University Hospital (A-ER-110-249).
2.2. Measurements
2.2.1. Intrinsic capacity
We assessed intrinsic capacity using the Taiwanese version of the Integrated Care for Older People (ICOPE) Screening Tool, derived from the WHO ICOPE guidelines, which includes six domains (WHO, 2019). The vitality (nutrition), psychology (depressive symptoms) and vision domains were assessed via self-reported measures. The remaining domains—cognition, locomotion and hearing—were evaluated using objective physical performance tests. Cognition was assessed using a 3-item test comprising two questions on orientation in time and space, and a three-word recall task administered by the interviewer. Cognitive decline was defined as the inability to correctly answer any of these three items. Locomotion was evaluated using a chair rise test. Limited mobility was defined as the inability to complete five chair rises within 12 s, according to the Asian Working Group for Sarcopenia consensus (Chen et al., 2020). Malnutrition (the vitality domain) was defined as self-reported weight loss exceeding 3 kg in the past three months or a loss of appetite. Vision was assessed through the question: 'Do you have any difficulty seeing things at a distance, up close, or while reading?' Participants reporting no visual difficulty, regardless of glasses use, were classified as having normal vision. Hearing capacity was assessed using the whisper test on both ears. Participants unable to correctly repeat three numbers in either ear were considered having hearing impairment. Hearing tests were conducted without removing hearing aids. Depressive symptoms were assessed using two questions regarding feelings of being down, depressed, or hopeless, or a reduction in engagement in activities over the preceding two weeks. The presence of depressive symptoms was defined by a positive response to either question. All domains were dichotomized into 1 (impaired) and 0 (not impaired), resulting in a total score ranging from 0 to 6. Participants were categorized into two groups based on their total intrinsic capacity scores: ‘no impairment’ for a score of 0 (indicating no problems in all domains) and ‘intrinsic capacity impairment’ for a score greater than 0 (indicating problems in one or more domains).
2.2.2. Sex and covariates
Data were collected through self-reported questionnaires. The main independent variable in this study was sex, categorized as ‘male’ or ‘female.’ Socio-demographic and economic factors included: age (60–69 years, 70–79 years, 80 years and above), current marital status (married or others, including widowed, divorced, or never married), living alone (yes or no), religion (none, Buddhist, Taoist, or others), educational attainment (uneducated, primary school, junior school, senior high school or higher), currently working (yes or no), and financial independence (yes or no). Currently working was defined as engaging in paid employment or self-employment, including part-time work. Financial independence was defined as being self-supporting, while participants receiving financial support from others, such as family, government, or friends, were classified as not financially independent.
Smoking, alcohol consumption, and physical activity are modifiable behavioral factors strongly associated with intrinsic capacity in older individuals (Ma et al., 2021, Muneera et al., 2022). Furthermore, betel quid chewing has been linked to health conditions in older adults in Taiwan (Hsu et al., 2017, Lin et al., 2014). Therefore, we collected data on these lifestyle factors for each participant. Cigarette smoking, alcohol consumption, and betel nut chewing were each classified into two categories: never, and current or former. Cigarette smoking was defined as smoking ≥1 pack per month for at least six months. Alcohol consumption and betel nut chewing were defined as consuming alcohol or chewing betel nuts ≥once per week for at least six months, respectively. Exercise habits were categorized as either no physical activity or engaging in physical activity at any intensity and frequency. Participants were also asked whether they engaged in vigorous exercise, which was defined as physical activity lasting at least 30 min and causing sweating, rapid breathing, and an increased heart rate. Vigorous exercise was classified as ≥1 day or <1 day per week.
2.3. Statistical analysis
Demographic characteristics, lifestyle, and socioeconomic factors for male and female participants were presented separately. Differences between men and women were examined using the chi-square test for categorical variables and the independent t-test for continuous variables. We also compared participant characteristics between the intrinsic capacity impairment and non-impairment groups. A binary logistic regression model was constructed to evaluate sex differences in intrinsic capacity impairment, yielding ORs and 95 % CIs. In the covariate-adjusted models, demographic characteristics, lifestyle factors, and socioeconomic factors were sequentially included to assess their impact on sex differences in intrinsic capacity. In addition, stratified analyses by the three socioeconomic factors – educational level, current employment status, and financial independence – were conducted to assess whether these variables modify the association between sex and intrinsic capacity impairment. Education level was grouped into two categories: uneducated or primary school, and junior school or above, because of the small number of participants in certain categories, such as uneducated men. Interaction effects were examined using the likelihood ratio test comparing models that excluded and included the interaction term between sex and the socioeconomic factors.
To explore whether there are sex differences in each individual domain of intrinsic capacity, we repeated the logistic regression analyses, treating each of the six components of intrinsic capacity as the dependent variable instead of overall intrinsic capacity impairment. All statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). A p-value of <0.05 was considered significant.
3. Results
Table 1 presents the background characteristics of male and female participants. Of the 1,268 participants, 48.7 % (n = 617) were men. The age distribution did not differ significantly between men and women (P = 0.1586), with 18.67 % of men and 16.13 % of women being 80 years or older. Compared to men, a smaller percentage of women were currently married (60.06 % vs. 83.79 %, P < 0.0001), while a higher percentage identified as Buddhist (40.09 % vs. 30.47 %, P = 0.0010). Men had a much higher prevalence of smoking, alcohol drinking, and betel quid chewing. Exercise levels, however, were similar between men and women. Women were more likely to experience unfavorable socioeconomic conditions; 12.65 % of women were uneducated, 18.13 % were currently working, and 53.30 % were financially independent, compared to 2.12 %, 26.74 %, and 68.88 % of men, respectively. A total of 436 participants (34.4 %) had intrinsic capacity impairment (intrinsic capacity score >0). The mean intrinsic capacity score was 0.60 (SD = 0.93) for women and 0.47 (SD = 0.85) for men, suggesting better intrinsic capacity in men (P = 0.0026). A higher proportion of women had intrinsic capacity impairment compared to men (37.94 % vs. 30.63 %, P = 0.0062).
Table 1.
Distribution of demographic, lifestyle, and socioeconomic characteristics among older men and women (n = 1,268), Tainan, Taiwan, 2022.
| Total | Men | Women | P valuea | |
|---|---|---|---|---|
| Characteristics | N (%) | N (%) | N (%) | |
| Total respondent | 1268 | 617 | 651 | |
| Demographic characteristics | ||||
| Age | ||||
| 60–69 years | 495 (39.07) | 249 (40.42) | 246 (37.79) | 0.19 |
| 70–79 years | 552 (43.57) | 252 (40.91) | 300 (46.08) | |
| ≥80 years | 220 (17.36) | 115 (18.67) | 105 (16.13) | |
| Current marital status | ||||
| Married | 908 (71.61) | 517 (83.79) | 391 (60.06) | <0.001 |
| Others (widowed/divorced/never married) | 360 (28.39) | 100 (16.21) | 260 (39.94) | |
| Live alone | ||||
| Yes | 147 (11.59) | 59 (9.56) | 88 (13.52) | 0.054 |
| No | 1120 (88.33) | 557 (90.28) | 563 (86.48) | |
| Religion | ||||
| No religion | 162 (12.78) | 90 (14.59) | 72 (11.06) | 0.001 |
| Buddhist | 449 (35.41) | 188 (30.47) | 261 (40.09) | |
| Taoism | 464 (36.59) | 249 (40.36) | 215 (33.03) | |
| Others | 193 (15.22) | 90 (14.59) | 103 (15.82) | |
| Lifestyle | ||||
| Cigarette smoking (≥1 pack per month)b | ||||
| Current or former | 259 (20.42) | 254 (41.17) | 5 (0.76) | <0.001 |
| Never | 1009 (79.57) | 363 (58.83) | 646 (99.23) | |
| Alcohol consumption (≥once per week)b | ||||
| Current or former | 134 (10.57) | 127 (20.59) | 7 (1.07) | <0.001 |
| Never | 1134 (89.43) | 490 (79.42) | 644 (98.92) | |
| Betel nut chewing (≥once per week)b | ||||
| Current or former | 83 (6.55) | 82 (13.29) | 1 (0.15) | <0.001 |
| Never | 1185 (93.45) | 535 (86.71) | 650 (99.85) | |
| Exercise (any intensity) | ||||
| Any frequency | 985 (77.68) | 476 (77.15) | 509 (78.19) | 0.66 |
| No exercise | 283 (22.32) | 141 (22.85) | 142 (21.81) | |
| Vigorous exercise per weekc | ||||
| ≥1 day | 246 (19.40) | 124 (20.10) | 122 (18.74) | 0.54 |
| <1 day | 1022 (80.60) | 493 (79.90) | 529 (81.26) | |
| Socioeconomic factors | ||||
| Educational attainment | ||||
| Uneducated | 95 (7.54) | 13 (2.12) | 82 (12.65) | <0.001 |
| Primary School | 417 (33.10) | 167 (27.29) | 250 (38.58) | |
| Junior School | 188 (14.92) | 92 (15.03) | 96 (14.81) | |
| Senior high school or above | 560 (44.44) | 340 (55.56) | 220 (33.95) | |
| Currently workingd | ||||
| Yes | 283 (22.32) | 165 (26.74) | 118 (18.13) | 0.001 |
| No | 985 (77.68) | 452 (73.26) | 533 (81.87) | |
| Financial independencee | ||||
| Yes | 772 (60.88) | 425 (68.88) | 347 (53.30) | <0.001 |
| No | 496 (39.12) | 192 (31.12) | 304 (46.70) | |
| Intrinsic capacity level | ||||
| 0 (no impairment) | 832 (65.62) | 428 (69.37) | 404 (62.06) | 0.006 |
| >0 (impairment) | 436 (34.38) | 189 (30.63) | 247 (37.94) | |
| Mean (SD) | 0.54 (0.89) | 0.47 (0.85) | 0.60 (0.93) | 0.003 |
| Median (Q1, Q3) | 0 (0,1) | 0 (0,1) | 0 (0,1) | |
Abbreviations: Q1, the first quartile; Q3, the third quartile; SD, standard deviation.
The chi-square test was used to compare differences between men and women, except for the mean levels of intrinsic capacity, which were analyzed using an independent t-test.
Considered only if sustained for at least six months, according to the provided definitions (e.g., ≥1 pack per month, ≥once per week).
Defined as physical activity that lasted at least 30 min and caused sweating, rapid breathing, and an increased heart rate.
Defined as engaging in paid employment or self-employment, including part-time jobs.
Yes indicates currently self-supporting; no indicates receiving financial support from others, such as family, government, or friends.
Participants without intrinsic capacity impairment were younger than those with impairment (Table 2). In the intrinsic capacity impairment group, 23.22 % were aged 60–69, compared to 47.36 % in the non-impairment group (P < 0.0001). Participants with intrinsic capacity impairment were less likely than those without impairment to be currently married (66.28 % vs.74.40 %, P = 0.0023), financially independent (50.46 % vs. 66.35 %, P < 0.0001), or currently working (13.53 % vs. 26.92 %, P < 0.0001). The intrinsic capacity impairment group also had a significantly higher proportion of uneducated individuals (14.62 % vs. 3.86 %, P < 0.0001). No significant differences were observed between the two groups in terms of living alone and religion. Regarding lifestyle factors, the intrinsic capacity impairment group had a lower prevalence of both mild and vigorous exercise than the non-impairment group. However, there were no significant differences in the prevalence of smoking, alcohol consumption, and betel quid chewing between the intrinsic capacity impairment and non-impairment groups.
Table 2.
Distribution of demographic, lifestyle, and socioeconomic characteristics among 1,268 older people with and without intrinsic capacity impairment, Tainan, Taiwan, 2022.
| Characteristics | No impairment |
Intrinsic capacity impairment |
P valuea |
|---|---|---|---|
| N (%) | N (%) | ||
| Total respondent | 832 | 436 | |
| Demographic characteristics | |||
| Age | |||
| 60–69 years | 394 (47.36) | 101 (23.22) | <0.001 |
| 70–79 years | 364 (43.75) | 188 (43.22) | |
| ≥80 years | 74 (8.89) | 146 (33.56) | |
| Sex | |||
| Men | 428 (51.44) | 189 (43.35) | 0.006 |
| Women | 404 (48.56) | 247 (56.65) | |
| Current marital status | |||
| Married | 619 (74.40) | 289 (66.28) | 0.002 |
| Others (widowed/divorced/never married) | 213 (25.60) | 147 (33.72) | |
| Live alone | |||
| Yes | 95 (11.42) | 52 (11.93) | 0.37 |
| No | 737 (88.58) | 383 (87.84) | |
| Religion | |||
| No religion | 108 (12.98) | 54 (12.39) | 0.35 |
| Buddhist | 287 (34.50) | 162 (37.16) | |
| Taoism | 300 (36.06) | 164 (37.61)) | |
| Others | 137 (16.47) | 56 (12.84) | |
| Lifestyle | |||
| Cigarette smoking (≥1 pack per month)b | |||
| Current or former | 175 (21.03) | 84 (19.26) | 0.46 |
| Never | 657 (78.97) | 352 (80.73) | |
| Alcohol consumption (≥once per week)b | |||
| Current or former | 85 (10.25) | 49 (11.24) | 0.57 |
| Never | 747 (89.78) | 387 (88.76) | |
| Betel nut chewing (≥once per week)b | |||
| Current or former | 50 (6.01) | 33 (7.57) | 0.29 |
| Never | 782 (93.99) | 403 (92.43) | |
| Exercise (any intensity) | |||
| Any frequency | 694 (83.41) | 291 (66.74) | <0.001 |
| No exercise | 138 (16.59) | 145 (33.26) | |
| Vigorous exercise per weekc | |||
| ≥1 day | 206 (24.76) | 40 (9.17) | <0.001 |
| <1 day | 626 (75.24) | 396 (90.83) | |
| Socioeconomic factors | |||
| Educational attainment | |||
| Uneducated | 32 (3.86) | 63 (14.62) | <0.001 |
| Primary School | 236 (28.47) | 181 (42.00) | |
| Junior School | 132 (15.92) | 56 (12.99) | |
| Senior high school or above | 429 (51.75) | 131 (30.39) | |
| Currently workingd | |||
| Yes | 224 (26.92) | 59 (13.53) | <0.001 |
| No | 608 (73.08) | 377 (86.47) | |
| Financial independencee | |||
| Yes | 552 (66.35) | 220 (50.46) | <0.001 |
| No | 280 (33.65) | 216 (49.54) | |
The chi-square test was used to compare differences between participants with and without intrinsic capacity impairment.
Considered only if sustained for at least six months, according to the provided definitions (e.g., ≥1 pack per month, ≥once per week).
Defined as physical activity that lasted at least 30 min and caused sweating, rapid breathing, and an increased heart rate.
Defined as engaging in paid employment or self-employment, including part-time jobs.
Yes indicates currently self-supporting; no indicates receiving financial support from others, such as family, government, or friends.
Table 3 presents the ORs with 95 % CIs for the sex difference in intrinsic capacity impairment. Only 0.8 % of participants had missing values across all covariates, and these individuals were excluded from the multiple regression analysis. In the unadjusted model, the OR for intrinsic capacity impairment was 1.39 (95 % CI: 1.10–1.75) for women compared to men. After adjusting for demographic characteristics, the OR remained similar (OR: 1.46 [95 % CI: 1.13–1.90], Model 1). The sex difference in intrinsic capacity persisted after further adjustment for lifestyle factors (OR: 1.69 [95 % CI: 1.23–2.31], Model 2). However, the OR was markedly attenuated to 1.24 (95 % CI: 0.88–1.73) in Model 3, which included socioeconomic factors in addition to those in Model 2. The ORs with 95 % CIs for the covariates are detailed in Supplementary Table 1. To assess the robustness of the results, we conducted an additional regression analysis excluding variables not statistically significantly associated with intrinsic capacity impairment in the univariate analysis (Supplementary Table 2). The findings were consistent with the primary analysis.
Table 3.
Odds ratio for the association between sex and intrinsic capacity impairment among older people, Tainan, Taiwan, 2022.
| Odds ratio for women vs. men | 95 % confidence interval | |
|---|---|---|
| Crude model | 1.39 | 1.10–1.75 |
| Adjusted model 1 | 1.46 | 1.13–1.90 |
| Adjusted model 2 | 1.69 | 1.23–2.31 |
| Adjusted model 3 | 1.24 | 0.88–1.73 |
Model 1 was adjusted for demographic characteristics (age, current marital status, living alone, and religion; n = 1,266); model 2 was adjusted for demographic characteristics and lifestyle factors (cigarette smoking, alcohol consumption, betel nut chewing, exercise at any intensity, and vigorous exercise; n = 1,266); model 3 was adjusted for demographic characteristics, lifestyle factors and socioeconomic factors (educational attainment, currently working and financial independence; n = 1,258).
The results of the stratified analyses by socioeconomic factors are presented in Table 4. In all models, no significant interaction effects were observed with educational level or current employment status. However, the OR for the association between sex and intrinsic capacity impairment was higher in individuals who were not financially independent than in those who were, approaching borderline statistical significance in Model 3 (OR [95 % CI]: 1.68 [0.96–2.96] and 0.97 [0.62–1.50]; P for interaction = 0.059).
Table 4.
Odds ratios for the association between sex and intrinsic capacity impairment, stratified by socioeconomic factors, among older people, Tainan, Taiwan, 2022.
| Prevalence of intrinsic capacity impairment, N (%)a |
Odds ratio (95 % confidence interval) for women vs. men |
|||||
|---|---|---|---|---|---|---|
| Women | Men | Unadjusted | Adjusted model 1 | Adjusted model 2 | Adjusted model 3 | |
| Educational attainment | ||||||
| Uneducated or primary school | 164 (49.40) | 80 (44.44) | 1.22 (0.85–1.76) | 1.32 (0.88–1.98) | 1.38 (0.81–2.34) | 1.19 (0.69–2.06) |
| Junior school or above | 80 (25.32) | 107 (24.77) | 1.03 (0.74–1.44) | 1.21 (0.83–1.75) | 1.47 (0.96–2.27) | 1.42 (0.92–2.20) |
| P for interactionb | 0.50 | 0.74 | 0.42 | 0.49 | ||
| Currently workingc | ||||||
| Yes | 27 (22.88) | 32 (19.39) | 1.23 (0.69–2.20) | 1.35 (0.73–2.51) | 1.40 (0.68–2.90) | 1.07 (0.49–2.36) |
| No | 220 (41.28) | 157 (34.73) | 1.32 (1.02––1.71) | 1.42 (1.06––1.90) | 1.63 (1.14–2.35) | 1.28 (0.88–1.88) |
| P for interactionb | 0.83 | 0.78 | 0.79 | 0.68 | ||
| Financial independenced | ||||||
| Yes | 102 (29.39) | 118 (27.76) | 1.08 (0.79–1.48) | 1.13 (0.79–1.61) | 1.19 (0.79–1.80) | 0.97 (0.62–1.50) |
| No | 145 (47.70) | 71 (36.98) | 1.55 (1.07–2.25) | 1.72 (1.14–2.60) | 2.25 (1.33–3.80) | 1.68 (0.96–2.96) |
| P for interactionb | 0.14 | 0.084 | 0.10 | 0.059 | ||
Model 1 was adjusted for demographic characteristics (age, current marital status, living alone, and religion; n = 1,266); model 2 was adjusted for demographic characteristics and lifestyle factors (cigarette smoking, alcohol consumption, betel nut chewing, exercise at any intensity, and vigorous exercise; n = 1,266); model 3 was adjusted for demographic characteristics, lifestyle factors and socioeconomic factors (educational attainment, currently working and financial independence; n = 1,258). The socioeconomic factor being stratified was not included as a covariate in that analysis.
A total score of intrinsic capacity >0 indicates intrinsic capacity impairment.
Interaction effects were examined using the likelihood ratio test comparing models with and without the interaction term between sex and the socioeconomic factors.
Defined as engaging in paid employment or self-employment, including part-time jobs.
Yes indicates currently self-supporting; no indicates receiving financial support from others, such as family, government, or friends.
Analyses of the individual components of intrinsic capacity revealed that women had higher odds of limited mobility and the presence of depressive symptoms than men in both crude and adjusted models (Supplementary Table 3). In model 3, the ORs for limited mobility and having depressive symptoms were 1.51 (95 % CI: 1.05–2.16) and 2.36 (95 % CI: 1.16–4.79), respectively. In contrast, there was an indication that women had lower odds of visual impairment than men. The inverse relationship between sex and visual impairment became more evident, reaching borderline significance after adjusting for socioeconomic factors (OR: 0.52 [95 % CI: 0.25–1.06]; Model 3, Supplementary Table 3).
4. Discussion
In this study, which included older individuals recruited from community and hospital settings, we found that women demonstrated poorer intrinsic capacity compared to men. This sex difference in intrinsic capacity remained after adjusting for demographic and lifestyle variables; however, it was diminished upon further adjustment for socioeconomic factors. These results highlight the necessity of considering socioeconomic factors to fully comprehend the sex disparities in intrinsic capacity among the older people over age 60.
The literature has consistently reported poorer health conditions in women compared to men in later life (Oksuzyan et al., 2008, Olivieri et al., 2023). However, studies focusing on sex differences in intrinsic capacity are scarce. Among older individuals, women exhibit a higher prevalence of frailty (Kane and Howlett, 2021, Zeidan et al., 2023), a condition that heightens susceptibility to stressors and raises the risk of adverse health outcomes, including disability (Bautmans et al., 2022, Fried et al., 2004). Moreover, research on both Western and non-Western populations has shown a higher prevalence of functional limitations and a more rapid increase in disability among older women than men (Bloomberg et al., 2021, Liang et al., 2010). Low intrinsic capacity is associated with increased incidence and progression of frailty and functional decline (Tay et al., 2023, Yu et al., 2022, Zhou and Ma, 2022). Our findings of poorer intrinsic capacity in older women are consistent with the existing literature, which indicates women’s generally worse health compared to men in later life.
Sex differences in aging and health involve a complex interplay among biological, psychological, and social factors (Mauvais-Jarvis et al., 2020, Zeidan et al., 2023). Our observations indicate that sex differences in intrinsic capacity were largely explained by educational level, current working status, and financial standing, suggesting that the poorer intrinsic capacity in women could be largely attributed to women’s lower socioeconomic status. Disadvantaged socioeconomic status influences individuals' access to essential resources within the community and has been linked to adverse affective reactivity to daily stressors, all of which could result in negative health outcomes and health disparities (Jiang et al., 2023). Studies from China and India have shown a high intrinsic capacity associated with better socioeconomic status in older people, independent of demographic, comorbidity, and lifestyle factors (Muneera et al., 2022, Zhao et al., 2023). Notably, these studies did not specifically address sex differences in intrinsic capacity. The significance of the social aspect in sex differences in healthy aging is evidenced by an analysis of multiple cohorts in Europe and the USA, which revealed a higher prevalence of functional limitations (basic activities of daily living and instrumental activities of daily living) in women and that the sex difference was substantially attenuated after adjusting for socioeconomic factors (Bloomberg et al., 2021). Similarly, a multi-country decomposition analysis revealed that among those 50 years and older, 45 % of the sex inequality in disability was attributed to differences in the distribution of social determinants between men and women (Hosseinpoor et al., 2012). Among these determinants, employment status contributed most to the sex differences in disability, followed by education level (Hosseinpoor et al., 2012).
In our study, although the adjustment for socioeconomic variables significantly reduced the overall differences in intrinsic capacity between men and women, the sex differences in mobility limitations and depressive symptoms persisted (Supplementary Table 3). This suggests that additional strategies may be necessary to address these specific domains. Nonetheless, intrinsic capacity is proposed as a composite measure of multiple domains reflecting an individual's overall health status (WHO, 2019, Yu et al., 2022). Growing evidence indicates that the intrinsic capacity summary score is associated with important health outcomes, such as frailty, functional decline, and mortality in older adults (Sánchez-Sánchez et al., 2024, Yu et al., 2022). Beyond the substantial impact of adjusting socioeconomic factors on sex differences in intrinsic capacity, we also observed that financial independence modified the association. In our stratified analyses, the higher odds of intrinsic capacity impairment in women than in men were evident only in the financially dependent group. These observations suggest that addressing socioeconomic disparities could be an important step toward reducing sex differences in intrinsic capacity and promoting healthier aging.
Our observations indicated that in the multiple regression analysis, exercise was strongly associated with improved intrinsic capacity. In contrast, smoking, alcohol consumption, and betel quid chewing showed no association with intrinsic capacity impairment (Supplementary Table 1). The positive impact of exercise on intrinsic capacity was also demonstrated in a secondary analysis of a randomized clinical trial involving older adults with pre-frailty, frailty, mild cognitive impairment, or mild dementia (Sánchez-Sánchez et al., 2022). This analysis revealed a significant improvement in the intrinsic capacity composite score among participants who engaged in a 12-week individualized, multicomponent exercise program compared to those receiving usual care (Sánchez-Sánchez et al., 2022). To confirm the influence of exercise on intrinsic capacity in the general older population, further longitudinal and intervention studies are warranted.
Our study is unique in its focus on sex differences in intrinsic capacity and in considering the role of socioeconomic factors in these differences. We are unaware of any studies that have specifically explored this issue. Another strength of the present study is the recruitment of participants from both clinical and community settings, allowing for the inclusion of relatively healthy and unhealthy older individuals.
This study has several limitations. First, reporting and recall biases may have occurred since the six domains of intrinsic capacity were measured using self-reported indicators. Second, 54.5 % of participants were recruited from outpatient clinics, 8.9 % from inpatient wards, and 36.6 % from communities in Tainan city (Supplementary Table 4). Participants from hospital settings, particularly inpatient wards, tended to have lower intrinsic capacity, while the majority from the community had higher intrinsic capacity. Consequently, the background characteristics of the study participants and the levels of intrinsic capacity may not be representative of the general older population. Third, due to the cross-sectional nature of the study, we cannot establish a causal relationship between covariates such as socioeconomic status and lifestyle, and intrinsic capacity. Nonetheless, our observations regarding sex differences in intrinsic capacity and the impact of socioeconomic disadvantages on this disparity should be considered valid. Fourth, the study participants were older adults in Taiwan, predominantly of ethnic Chinese descent. Therefore, the results may not generalize to other ethnic groups.
5. Conclusions
Among individuals aged 60 years and older in Taiwan, we found that women had poorer intrinsic capacity than men. The sex difference in intrinsic capacity was largely explained by socioeconomic factors, rather than by demographics or lifestyle factors. Our findings suggest that addressing socioeconomic disparities among women could be key to narrowing the gap in intrinsic capacity impairment between older men and women.
CRediT authorship contribution statement
Mei-Tzu Huang: Writing – original draft, Investigation, Formal analysis, Conceptualization. Ya-Hui Chang: Writing – review & editing, Software, Formal analysis, Data curation. Chung-Yi Li: Writing – review & editing, Resources, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Li-Jung Elizabeth Ku: Writing – review & editing, Methodology, Investigation, Funding acquisition. Yu-Tsung Chou: Writing – review & editing, Resources, Methodology, Investigation, Funding acquisition. Wen-Hsuan Hou: Writing – review & editing, Resources, Methodology, Investigation. Hung-Yu Chen: Writing – review & editing, Resources, Methodology, Investigation. Hui-Chen Su: Writing – review & editing, Resources, Methodology, Investigation. Yi-Lin Wu: Writing – review & editing, Resources, Methodology, Investigation. Chieh-Hsiu Liu: Writing – review & editing, Resources, Methodology. Yi-Ching Yang: Writing – review & editing, Supervision, Resources, Methodology, Investigation, Funding acquisition, Data curation. Pei-Chun Chen: Writing – original draft, Validation, Methodology, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors are grateful for grants from the National Health Research Institutes (NHRI-11A1-CG-CO-04-2225-1). We thank the interviewers, the participants, and the caregivers of the participants in the study participation.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.pmedr.2024.102897.
Contributor Information
Yi-Ching Yang, Email: yiching@mail.ncku.edu.tw.
Pei-Chun Chen, Email: peichun.chen@nhri.edu.tw.
Appendix A. Supplementary material
The following are the Supplementary data to this article:
Data availability
Data will be made available on request.
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Associated Data
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Supplementary Materials
Data Availability Statement
Data will be made available on request.