Abstract
To investigate the knowledge, attitudes, and practices (KAP) of the elderly population regarding their intrinsic capacity, as defined by the World Health Organization as a marker of healthy aging. A cross-sectional study was conducted at the Shanghai Traditional Chinese Medicine Hospital from July to November 2023. Participants’ socio-demographic information and KAP scores were collected through a self-designed questionnaire. A total of 507 elderly individuals participated, with 53.25% being male and a mean age of 70.76 ± 7.63 years. The mean knowledge, attitude, and practice scores were 19.58 ± 8.85, 30.07 ± 4.81, and 34.71 ± 7.77, respectively. Pearson’s correlation analysis showed significant positive correlations among the KAP scores (all P < 0.001). Multivariate logistic regression indicated that knowledge scores (OR = 1.127, P < 0.001), attitude scores (OR = 1.189, P < 0.001), and current employment status (OR = 2.759, P = 0.009) were associated with proactive practices. Structural equation modeling demonstrated that knowledge had a direct influence on attitude (β = 0.572, P < 0.001) and practice (β = 0.776, P < 0.001), while attitude directly impacted practice (β = 0.412, P < 0.001). The study reveals that the elderly lack knowledge but have positive attitudes and proactive behaviors about intrinsic capacity. Enhancing education and attitudes is vital for healthy aging and well-being.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-97063-7.
Keywords: Knowledge, Attitude, Practice, Elderly population, Intrinsic capacity
Subject terms: Health care, Quality of life
Introduction
China, currently home to the world’s largest elderly population, has been experiencing a rapid acceleration in its aging process1. By the end of 2020, China’s population aged 60 and above reached 264 million, accounting for 18.7% of the total population, with the population aged 65 and above reaching 191 million, accounting for 13.5% of the total population2. The “China Development Report 2020: Trends and Policies on Population Aging in China” projects that by 2050, the aging population will comprise 30% of the total population3. The health challenges faced by the elderly represent the most prominent issue in an aging society, and the physical and mental well-being of the elderly population in China is a matter of concern. The World Health Organization introduced the concept of intrinsic capacity in 2015 to holistically capture the composite functions of older adults4. Defined as the aggregate of an individual’s physical and mental capacities, intrinsic capacity encompasses five key domains: cognition, mobility, vitality, mood, and sensory abilities5. Healthy aging is characterized by functional abilities, with intrinsic capacity being the culmination of the physical and mental abilities of older people, influenced by their physical and social environments and overall well-being6.
Studies have shown that impairment in intrinsic capacity affects self-care, increases dependency, hospitalization rates, and mortality among the elderly7,8. Emerging evidence also suggests that the domains of intrinsic capacity are interconnected. A decline in intrinsic capacity in older age is associated with heightened risks of adverse health outcomes, such as frailty, disability, nursing home stays, and even mortality9. Recent studies have further emphasized the role of early screening and targeted interventions in preserving intrinsic capacity and preventing age-related decline10,11. Consequently, strengthening and maintaining the intrinsic capacity of older adults is pivotal for delaying disability and promoting healthy aging12.
In the discipline of public health, the ‘knowledge, attitude, and practice’ (KAP) surveys serve as a crucial tool for examining behavioral practices alongside knowledge and risk perception13. According to the KAP model, individual behaviors are shaped by their knowledge and attitudes14. The global increase in aging populations underscores the urgent need to comprehend how the elderly perceive and manage their intrinsic capacity. Research has highlighted the significance of various components of intrinsic capacity, such as mobility, cognition, and nutritional status, with studies demonstrating their influence on aging-related outcomes15,16. However, these previous studies have primarily focused on specific components of intrinsic capacity rather than examining it as a comprehensive concept. In China, research on intrinsic capacity has largely centered on clinical interventions to preserve specific functional domains, with limited attention to public awareness and behavioral engagement in maintaining overall intrinsic capacity17. Additionally, no studies have applied structured models to examine the interrelationships among knowledge, attitudes, and practices in this context. Despite growing recognition of the importance of intrinsic capacity, there remains a significant gap in understanding how older adults perceive and actively manage it as a whole. Addressing these gaps is essential for developing culturally tailored strategies to enhance intrinsic capacity and promote healthy aging in diverse populations.
To bridge this research gap, the present study aims to conduct a comprehensive KAP assessment of intrinsic capacity among the elderly.
Methods
Study design and participants
This cross-sectional study included the elderly population at the Shanghai Traditional Chinese Medicine Hospital from July to November 2023. The inclusion criteria were the following: (1) age ≥ 60 years; (2) those who with clear consciousness, and capable of independently responding to the questionnaire. No specific exclusion criteria were applied in this study. The research protocol was approved by the Medical Ethics Committee of the Shanghai Traditional Chinese Medicine Hospital, with the approval number 2023SHL-KY- 86 - 02, and informed consent was obtained from all participants.
Questionnaire introduction
The questionnaire’s design drew upon previous literature18–20and the 2022 Expert Consensus on Prevention and Intervention for Physical Function Impairment in the Elderly in China21. A pilot study was conducted among 31 participants, yielding a Cronbach’s α value of 0.927, which indicated good internal consistency. During the pilot study, participants were encouraged to provide feedback on any items they found confusing or unclear. As no such concerns were reported, this supports the questionnaire’s face validity.
The finalized questionnaire encompassed four dimensions: Demographic Characteristics, Knowledge, Attitude, and Practice. The demographic characteristics section contained 11 questions, including age, sex, residence, education level, and average monthly income. The knowledge dimension, comprising 17 questions, evaluated understanding on a scale where complete, partial, and no understanding were awarded 2, 1, and 0 points, respectively. Question 17 was not assigned any points, resulting in a total possible score ranging from 0 to 32. The attitude dimension consisted of 8 items, scored using a five-point Likert scale from strongly agree to strongly disagree (5 − 1 points). The attitude dimension’s total score ranged from 8 to 40 points. The practice dimension included 9 questions, also utilizing a five-point Likert scale, with responses varying from always to never (5 − 1 points) and a total score range of 9–45 points. A score exceeding 70% in any dimension was considered indicative of sufficient knowledge, positive attitude and proactive practice22.
Questionnaire distribution and quality control
The questionnaire was distributed using both online and offline methods. In the offline approach, the study employed an electronic questionnaire distributed to participants via an online platform facilitated by the Soiump website (https://www.wjx.cn/app/survey.aspx). A unique QR code, linked to the questionnaire, was generated and shared with participants through WeChat. By scanning this QR code, participants could easily access and complete the questionnaire. For those older adults who were willing or unable to answer online, proficient research team members conducted alternative face-to-face interviews using paper questionnaires. To maintain the integrity and completeness of the responses, the system was configured to allow only one submission per IP address, and all questions were mandatory. All questionnaires were collected anonymously. If participants encountered any problem in answering, members of the research group were responsible for interpreting and solving the problem. The research team diligently reviewed each submission for completeness, internal consistency, and logical coherence. Throughout the data collection phase, three research team members collaboratively managed the questionnaire collection process, ensuring efficient and accurate data gathering.
Samples size
The minimal sample size was estimated based on 10 times the number of demographic information and KAP items based on the sample size estimation methods for surveys23. Hence, the minimal sample size was 450. When accounting for a 10% invalid questionnaire rate, the minimal sample size was 495.
Statistical analysis
SPSS 22.0 (IBM, Armonk, New York, USA) and Amos 22.0 (IBM, Armonk, New York, USA) were utilized for statistical analysis. The normal distribution of continuous data was checked using the Kolmogorov-Smirnov test. The continuous variables conforming to the normal distribution were presented as means ± standard deviations (SD) and analyzed using Student’s t-test (two groups) or ANOVA (more than two groups). Those with a skewed distribution were presented as medians (ranges) and analyzed using the Wilcoxon-Mann-Whitney U-test (two groups) or the Kruskal-Wallis analysis of variance (more than two groups). Count variables were presented as n (%) and analyzed using the chi-square test. Pearson correlation analysis was used to assess the correlation in the three KAP dimensions. Univariable and multivariable logistic regression were performed to determine the independent factors relevant to the sufficient knowledge, positive attitude and proactive practice. Variables with P-values less than 0.05 in the univariate analysis were included in the multivariate logistic analysis. Structural equation modeling (SEM) analysis was further conducted to explore the direct and indirect associations among the KAP scores. Two-sided P-values < 0.05 were considered statistically significant.
Results
Demographic characteristics
In this study, a total of 507 participants were included for analysis, of which 70.76 ± 7.63 were male, with mean age of 70.76 ± 7.63 years, 175 (34.52%) had high school/technical school education, 275 (54.24) had an average monthly income of 5,000–10,000 Yuan, 373 (73.57%) had a history of high hypertension, 335 (66.07%) living with their children or other relatives, 439 (86.59%) were able to perform daily activities independently (Table 1).
Table 1.
Baseline characteristics of the participants.
| N (%) | Knowledge score | Attitude score | Practice score | ||||
|---|---|---|---|---|---|---|---|
| mean ± SD | P | mean ± SD | P | mean ± SD | P | ||
| Age (years) | 70.76 ± 7.63 | 19.58 ± 8.85 | 30.07 ± 4.81 | 34.71 ± 7.77 | |||
| Gender | 0.232 | 0.845 | 0.641 | ||||
| Male | 270 (53.25) | 20.02 ± 8.43 | 30.03 ± 4.68 | 34.86 ± 7.53 | |||
| Female | 237 (46.75) | 19.08 ± 9.29 | 30.11 ± 4.96 | 34.54 ± 8.05 | |||
| Residence | < 0.001 | 0.002 | 0.001 | ||||
| Urban | 445 (87.77) | 20.14 ± 8.66 | 30.31 ± 4.64 | 35.12 ± 7.62 | |||
| Rural | 62 (12.23) | 15.55 ± 9.22 | 28.27 ± 5.62 | 31.74 ± 8.27 | |||
| Education | < 0.001 | 0.429 | 0.004 | ||||
| Primary school and below | 63 (12.43) | 15.57 ± 9.71 | 29.24 ± 4.99 | 32.57 ± 9.26 | |||
| Junior high school | 168 (33.14) | 17.68 ± 7.95 | 30.12 ± 4.40 | 33.74 ± 7.02 | |||
| High school/technical school | 175 (34.52) | 20.59 ± 8.63 | 30.05 ± 4.87 | 35.50 ± 7.55 | |||
| College/undergraduate and above | 101 (19.92) | 23.49 ± 8.31 | 30.51 ± 5.23 | 36.28 ± 7.92 | |||
| Current employment status | 0.169 | 0.003 | 0.226 | ||||
| Retired | 459 (90.53) | 19.40 ± 8.72 | 30.27 ± 4.53 | 34.57 ± 7.53 | |||
| Currently employed | 48 (9.47) | 21.25 ± 9.93 | 28.10 ± 6.68 | 36.00 ± 9.75 | |||
| Average monthly income | 0.014 | 0.121 | 0.865 | ||||
| < 5,000 | 103 (20.32) | 17.58 ± 10.24 | 30.70 ± 5.05 | 34.34 ± 8.74 | |||
| 5,000–10,000 | 275 (54.24) | 20.51 ± 7.98 | 29.67 ± 4.26 | 34.79 ± 6.85 | |||
| > 10,000 | 129 (25.44) | 19.19 ± 9.19 | 30.40 ± 5.62 | 34.82 ± 8.79 | |||
| Smoking | 0.080 | 0.505 | 0.153 | ||||
| Yes | 126 (24.85) | 18.38 ± 8.22 | 29.82 ± 5.54 | 33.85 ± 8.50 | |||
| No | 381 (75.15) | 19.97 ± 9.02 | 30.15 ± 4.55 | 34.99 ± 7.50 | |||
| Drinking | 0.545 | 0.867 | 0.597 | ||||
| Yes | 93 (18.34) | 19.08 ± 8.76 | 29.99 ± 5.37 | 34.32 ± 8.81 | |||
| No | 414 (81.66) | 19.69 ± 8.88 | 30.08 ± 4.68 | 34.79 ± 7.53 | |||
| Comorbidities or Medical History | |||||||
| Hypertension | 373 (73.57) | 20.27 ± 9.07 | 30.26 ± 4.88 | 35.05 ± 7.98 | |||
| Diabetes | 192 (37.87) | 18.73 ± 8.61 | 29.98 ± 4.99 | 34.18 ± 7.74 | |||
| Hyperlipidemia | 115 (22.68) | 20.23 ± 9.10 | 29.57 ± 5.68 | 33.91 ± 8.57 | |||
| Coronary heart disease | 92 (18.15) | 19.03 ± 9.08 | 31.02 ± 5.37 | 34.02 ± 8.78 | |||
| Benign or malignant tumors | 54 (10.65) | 16.33 ± 11.50 | 30.57 ± 5.84 | 34.13 ± 8.39 | |||
| Living Arrangements with Children or Other Relatives | 0.001 | 0.767 | 0.069 | ||||
| Yes | 335 (66.07) | 20.48 ± 8.36 | 30.11 ± 4.68 | 35.16 ± 7.69 | |||
| No | 172 (33.93) | 17.83 ± 9.51 | 29.98 ± 5.07 | 33.83 ± 7.88 | |||
| Ability to Perform Daily Activities Independently | 0.011 | 0.426 | 0.373 | ||||
| Yes | 439 (86.59) | 19.97 ± 8.77 | 30.13 ± 4.77 | 34.83 ± 7.80 | |||
| No | 68 (13.41) | 17.03 ± 9.00 | 29.63 ± 5.08 | 33.93 ± 7.60 | |||
Knowledge
The mean knowledge score was 19.58 ± 8.85 (total score of 0–32). Specifically, participants with different residence (P < 0.001), education (P < 0.001), average monthly income (P = 0.014), living arrangement with children or other relatives (P = 0.001), and ability to perform daily activities (P = 0.011) were more likely to have different knowledge scores. The distribution of knowledge dimensions showed that the questions with the highest proportion choosing the “Aware” option were “Are you aware that cognitive decline may increase the risk of dementia?” (K5) with 44.18% and “Are you aware that enhancing motor abilities can effectively prevent falls in the elderly?” (K9) with 44.58%. On the other hand, the questions with the highest proportion choosing the “Not aware” option were “Have you heard of intrinsic capacity?"(K1) with 25.64%, “Are you aware that the decline in intrinsic capacity primarily includes cognitive decline, impaired motor skills, symptoms of depression, impaired vision and hearing, and malnutrition?” (K2) with 24.65%, and “Are you aware that the assessment of elderly motor abilities mainly focuses on grip strength, walking speed tests, timed up-and-go tests, and balance tests?” (K8) with 24.65% (Table 2). Notably, only 37.87% of participants were familiar with the definition of intrinsic capacity, while 25.64% were not aware of it (K1). Strikingly, the majority of the participants reported that they gained knowledge related to intrinsic capacity from new media (59.76%) and multimedia (58.58%) (K17) (Figure S1).
Table 2.
Distribution percentage of correct knowledge responses.
| N (%) | Aware | Heard of | Not aware |
|---|---|---|---|
| 1. Have you heard of intrinsic capacity? Intrinsic capacity are defined as the combination of an individual’s overall physical and mental (including psychological) capabilities, encompassing five dimensions: motor ability, vitality/nutritional status, cognitive status, psychological status, and perception. | 192 (37.87) | 185 (36.49) | 130 (25.64) |
| 2. Are you aware that the decline in intrinsic capacity primarily includes cognitive decline, impaired motor skills, symptoms of depression, impaired vision and hearing, and malnutrition? | 179 (35.31) | 203 (40.04) | 125 (24.65) |
| 3. Are you aware that the risk factors for the decline in intrinsic capacity include age, gender, comorbidity with chronic diseases, daily behaviors, psychological factors, socioeconomic status, marital status, educational level, and family situation? | 191 (37.67) | 204 (40.24) | 112 (22.09) |
| 4. Are you aware that cognitive decline may manifest as a decline in memory, attention, and the ability to think independently? | 209 (41.22) | 204 (40.24) | 94 (18.54) |
| 5. Are you aware that cognitive decline may increase the risk of dementia? | 224 (44.18) | 194 (38.26) | 89 (17.55) |
| 6. Are you aware that cognitive decline in the elderly can also affect their physical and psychological well-being? | 215 (42.41) | 203 (40.04) | 89 (17.55) |
| 7. Are you aware that the motor abilities of the elderly are primarily influenced by muscle mass, flexibility, balance, and coordination? | 199 (39.25) | 196 (38.66) | 112 (22.09) |
| 8. Are you aware that the assessment of elderly motor abilities mainly focuses on grip strength, walking speed tests, timed up-and-go tests, and balance tests? | 180 (35.50) | 202 (39.84) | 125 (24.65) |
| 9. Are you aware that enhancing motor abilities can effectively prevent falls in the elderly? | 226 (44.58) | 209 (41.22) | 72 (14.20) |
| 10. Are you aware that exercise rehabilitation training is an ideal way to delay or reverse functional impairment, improve patient prognosis, and enhance quality of life? This includes resistance training, balance training, aerobic exercise training, and structured training. | 209 (41.22) | 202 (39.84) | 96 (18.93) |
| 11. Are you aware that to maintain normal function, the body needs a balance between energy intake and expenditure? When energy intake and expenditure are no longer balanced, malnutrition can occur. | 223 (43.98) | 204 (40.24) | 80 (15.78) |
| 12. Are you aware that in energy balance, not only malnutrition but also overweight, obesity, and decreased skeletal muscle mass are intervention indicators for preventing disability in older individuals? | 209 (41.22) | 213 (42.01) | 85 (16.77) |
| 13. Are you aware that malnutrition can lead to weakness and decreased physical resilience? | 237 (46.75) | 194 (38.26) | 76 (14.99) |
| 14. Are you aware that visual and hearing impairments directly impact the daily social interactions of the elderly, and in severe cases, can lead to social isolation, depression, accidents, and disability? | 234 (46.75) | 194 (38.26) | 79 (15.58) |
| 15. Are you aware that depressive emotions and depression are the most common adverse emotional and psychological issues in the elderly? Depressive symptoms may be an independent risk factor for disability in the elderly. | 209 (41.22) | 216 (42.60) | 82 (16.17) |
| 16. Are you aware that depression in the elderly can lead to a decline in motor and cognitive abilities? | 219 (43.20) | 193 (38.07) | 95 (18.74) |
Attitude
The mean attitude score was 30.07 ± 4.81 (total score of 8–40). Participants with different residence (P = 0.002) and current employment status (P = 0.003) showed different attitude scores. The responses to the attitude dimension showed that 33.14% and 35.11% of the participants strongly agreed that it is necessary to maintain a proper diet and adequate nutrition in daily life (A7) and to maintain an optimistic mood (A8), respectively. Meanwhile, 44.58% agreed that exercise not only improves motor ability but also improves cognitive ability, thus alleviating depression (A4). Also, 43.98% agreed that controlling their underlying diseases is important to prevent the decline of intrinsic capacity (A6). Strikingly, only 27.07% agreed that inevitable aging causes anxiety, while 32.94% were neutral and 19.53% disagreed with this view (as shown in Table S1).
Practice
The participants achieved an average knowledge score of 34.71 ± 7.77 (total score of 9–45). Participants with different residences (P = 0.001) and education (P = 0.004) showed different practice scores (Table 1). When it comes to related practices, 34.71% always maintained a positive and optimistic mindset (P10). Intriguingly, 35.70% often maintained a varied and regular diet to avoid overeating (P7), and 31.36% often managed their underlying diseases (P6). Additionally, 32.74% sometimes sought the help of a health professional for a detailed assessment of their intrinsic capacity (P1), and 32.94% sometimes participated in social activities and communicated with others (P8). However, it is impressive that 13.21% never have regular screening and intervention for visual and hearing impairment (Table S2).
Correlations
Correlation analyses indicated significant positive correlations between knowledge and attitude (r = 0.387, P < 0.001), as well as practice (r = 0.583, P < 0.001). Meanwhile, there was also a correlation between attitude and practice (r = 0.515, P < 0.001) (Table 3).
Table 3.
Correlation analysis.
| Knowledge | Attitude | Practice | |
|---|---|---|---|
| Knowledge | 1 | ||
| Attitude | 0.387 (P < 0.001) | 1 | |
| Practice | 0.583 (P < 0.001) | 0.515 (P < 0.001) | 1 |
Multiple logistic regression analysis
The results of multivariate logistic regression showed that with education of college or undergraduate and above (OR = 3.416, 95% CI: [1.666 3.002], P = 0.001), smoking (OR = 0.511, 95% CI: [0.322 0.811], P = 0.004), living arrangement with children or other relatives (OR = 1.623, 95% CI: [1.081 2.435], P = 0.019) were independently associated with knowledge (Table 4). Further, knowledge score (OR = 1.062, 95% CI: [1.038 1.087], P < 0.001) and currently employed (OR = 0.291, 95% CI: [0.150 0.562], P < 0.001) were independently associated with attitude (Table 5). Moreover, knowledge score (OR = 1.127, 95% CI: [1.094 1.161], P < 0.001), attitude score (OR = 1.189, 95% CI: [1.124 1.259], P < 0.001), and currently employed (OR = 2.759, 95% CI: [1.284 5.933], P = 0.009) were independently associated with practice (as shown in Table 6).
Table 4.
Multivariate analysis for knowledge dimension.
| Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|
| OR (95%CI) | P | OR (95%CI) | P | |
| Age (years) | 0.982 (0.958 1.005) | 0.129 | ||
| Gender | ||||
| Male | ref. | |||
| Female | 1.013 (0.708 1.449) | 0.945 | ||
| Residence | ||||
| Urban | ref. | ref. | ||
| Rural | 0.465 (0.253 0.858) | 0.014 | 0.647 (0.335 1.248) | 0.194 |
| Education | ||||
| Primary school and below | ref. | ref. | ||
| Junior high school | 1.051 (0.549 2.014) | 0.881 | 0.988 (0.501 1.949) | 0.973 |
| High school/technical school | 1.891 (1.005 3.561) | 0.048 | 1.777 (0.910 3.469) | 0.092 |
| College/undergraduate and above | 3.960 (1.999 7.844) | < 0.001 | 3.416 (1.666 3.002) | 0.001 |
| Current employment status | ||||
| Retired | ref. | |||
| Currently employed | 1.521 (0.837 2.763) | 0.169 | ||
| Average monthly income | ||||
| < 5,000 | ref. | |||
| 5,000–10,000 | 1.358 (0.848 2.173) | 0.203 | ||
| > 10,000 | 0.963 (0.559 1.661) | 0.893 | ||
| Smoking | ||||
| Yes | 0.500 (0.321 0.778) | 0.002 | 0.511 (0.322 0.811) | 0.004 |
| No | ref. | ref. | ||
| Drinking | ||||
| Yes | 0.711 (0.441 1.146) | 0.162 | ||
| No | ref. | |||
| Living Arrangements with Children or Other Relatives | ||||
| Yes | 1.546 (1.050 2.277) | 0.027 | 1.623 (1.081 2.435) | 0.019 |
| No | ref. | ref. | ||
| Ability to Perform Daily Activities Independently | ||||
| Yes | 1.484 (0.857 2.568) | 0.159 | ||
| No | ref. | |||
Table 5.
Multivariate analysis for attitude dimension.
| Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|
| OR (95%CI) | P | OR (95%CI) | P | |
| Knowledge score | 1.059 (1.037 1.082) | < 0.001 | 1.062 (1.038 1.087) | < 0.001 |
| Age (years) | 1.007 (0.983 1.031) | 0.574 | ||
| Gender | ||||
| Male | ref. | |||
| Female | 1.218 (0.848 1.748) | 0.285 | ||
| Residence | ||||
| Urban | ref. | ref. | ||
| Rural | 0.556 (0.326 0.949) | 0.031 | 0.734 (0.404 1.332) | 0.309 |
| Education | ||||
| Primary school and below | ref. | ref. | ||
| Junior high school | 1.770 (0.983 3.189) | 0.057 | 1.437 (0.762 2.709) | 0.262 |
| High school/technical school | 1.332 (0.746 2.376) | 0.332 | 0.958 (0.503 1.824) | 0.895 |
| College/undergraduate and above | 1.960 (1.025 3.748) | 0.042 | 1.400 (0.669 2.930) | 0.371 |
| Current employment status | ||||
| Retired | ref. | ref. | ||
| Currently employed | 0.354 (0.192 0.651) | 0.001 | 0.291 (0.150 0.562) | < 0.001 |
| Average monthly income | ||||
| < 5,000 | ref. | |||
| 5,000–10,000 | 0.772 (0.481 1.240) | 0.285 | ||
| > 10,000 | 0.961 (0.557 1.657) | 0.886 | ||
| Smoking | ||||
| Yes | 0.808 (0.535 1.220) | 0.311 | ||
| No | ref. | |||
| Drinking | ||||
| Yes | 0.840 (0.531 1.329) | 0.456 | ||
| No | ref. | |||
| Living Arrangements with Children or Other Relatives | ||||
| Yes | 0.912 (0.622 1.335) | 0.634 | ||
| No | ref. | |||
| Ability to Perform Daily Activities Independently | ||||
| Yes | 1.284 (0.765 2.156) | 0.345 | ||
| No | ref. | |||
Table 6.
Multivariate analysis for practice dimension.
| Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|
| OR (95%CI) | P | OR (95%CI) | P | |
| Knowledge score | 1.151 (1.119 1.184) | < 0.001 | 1.127 (1.094 1.161) | < 0.001 |
| Attitude score | 1.221 (1.164 1.280) | < 0.001 | 1.189 (1.124 1.259) | < 0.001 |
| Age (years) | 0.987 (0.964 1.010) | 0.270 | ||
| Gender | ||||
| Male | ref. | |||
| Female | 0.992 (0.698 1.410) | 0.965 | ||
| Residence | ||||
| Urban | ref. | |||
| Rural | 0.616 (0.353 1.077) | 0.089 | ||
| Education | ||||
| Primary school and below | ref. | |||
| Junior high school | 0.741 (0.410 1.337) | 0.319 | ||
| High school/technical school | 1.123 (0.628 2.007) | 0.696 | ||
| College/undergraduate and above | 1.659 (0.879 3.130) | 0.118 | ||
| Current employment status | ||||
| Retired | ref. | ref. | ||
| Currently employed | 1.895 (1.037 3.464) | 0.038 | 2.759 (1.284 5.933) | 0.009 |
| Average monthly income | ||||
| < 5,000 | ref. | |||
| 5,000–10,000 | 1.180 (0.746 1.865) | 0.479 | ||
| > 10,000 | 1.005 (0.594 1.698) | 0.986 | ||
| Smoking | ||||
| Yes | 0.693 (0.458 1.048) | 0.082 | ||
| No | ref. | |||
| Drinking | ||||
| Yes | 0.903 (0.573 1.423) | 0.660 | ||
| No | ref. | |||
| Living Arrangements with Children or Other Relatives | ||||
| Yes | 1.024 (0.707 1.483) | 0.902 | ||
| No | ref. | |||
| Ability to Perform Daily Activities Independently | ||||
| Yes | 0.866 (0.519 1.446) | 0.583 | ||
| No | ref. | |||
SEM
The results of SEM showed the direct effect of K on A was significant (β = 0.210, 95% CI [0.174, 0.266], p = 0.006), as was its direct (β = 0.396, 95% CI [0.317, 0.463], p = 0.018) and indirect effects on P (β = 0.116, 95% CI [0.088, 0.160], p = 0.004). Additionally, A directly influenced P significantly (β = 0.551, 95% CI [0.462, 0.655], p = 0.002) (as shown in Fig. 1, Table S3). Table S4 showed that all fit indexes were good.
Fig. 1.
Structural Equation Model.
Discussion
The study revealed that the elderly population exhibited insufficient knowledge, positive attitudes and proactive practices about their intrinsic capacity. Given the observed knowledge gaps among the elderly, healthcare providers and caregivers should prioritize educational interventions to enhance their understanding of intrinsic capacity, which could contribute to more informed decision-making and improved overall well-being.
The main findings of this study revealed that the elderly population exhibits inadequate knowledge but maintains positive attitudes and proactive practices regarding their intrinsic capacity. These results are consistent with existing literature that emphasizes the importance of intrinsic capacity, attitudes, and practices in enhancing the overall well-being of the elderly24. However, this study also uncovers significant variations in knowledge, attitudes, and practices among different demographic groups, shedding light on potential areas for targeted interventions.
The observed differences in knowledge, attitudes, and practices across demographic categories align with previous research. For instance, the finding that individuals aged 70 years and older exhibit higher practice scores resonates with studies emphasizing the importance of resilience and adaptability in older age25,26. This is consistent with findings from a study indicating that older adults with higher resilience were more likely to adopt proactive aging-related behaviors27,28. Additionally, the influence of education level on scores aligns with prior research demonstrating that higher education is associated with greater awareness and proactive behavior among the elderly29,30. A study also reported that elderly individuals with college-level education exhibited higher engagement in health-promoting activities due to increased health literacy31,32. Furthermore, our study found that living arrangements with children or other relatives were positively associated with knowledge and practice scores. The impact of living arrangements with children or other relatives on practice scores supports existing literature highlighting the role of social support in promoting healthy aging33,34. Multivariate logistic regression provides further insights, indicating that education level, smoking, and living arrangement are independently associated with knowledge scores. These findings reinforce the notion that educational attainment is a key determinant of knowledge in the elderly population35. Moreover, the association between smoking and lower knowledge scores is in line with studies emphasizing the detrimental effects of smoking on cognitive function36. The independent associations of knowledge and current employment status with attitude underscore the potential benefits of remaining engaged in the workforce as it may contribute to more positive attitudes37.
Correlation analyses and structural equation modeling results demonstrate the interplay between knowledge, attitudes, and practices. The significant positive correlations between knowledge and attitude, as well as between knowledge and practice, align with research emphasizing the interconnectedness of these factors38. SEM findings not only reaffirm the direct impact of knowledge on both attitude and practice but also reveal the mediating role of attitude in the relationship between knowledge and practice. The relatively high level of practice despite limited knowledge suggests the influence of external factors. Employment may contribute to better health behaviors by providing increased opportunities for social interaction, cognitive engagement, and structured daily routines. Continued workforce participation is associated with improved health literacy and proactive health management behaviors, as employment environments often facilitate access to health information and reinforce the importance of self-care practices. For instance, research on older adults’ KAP regarding chronic disease management has shown that employed individuals exhibit higher adherence to preventive health measures, likely due to workplace policies that encourage health screenings and wellness programs39,40. Additionally, studies have suggested that cognitive engagement through employment may mitigate age-related cognitive decline, thereby fostering a greater awareness of health maintenance strategies41,42. Moreover, social networks formed in the workplace can serve as a support system that reinforces positive health attitudes and practices, a factor that has been widely recognized in KAP studies on aging populations43,44. These findings align with our study, where employment was positively associated with proactive health behaviors. The role of employment in shaping elderly individuals’ intrinsic capacity management behaviors underscores the need for targeted interventions that integrate occupational health education and support systems for older workers to sustain their well-being beyond retirement. Additionally, family support plays a key role, as relatives often assist in health decision-making and encourage beneficial behaviors45,46. The health-conscious environment in Shanghai, with extensive public health initiatives and accessible healthcare resources, may further reinforce positive practices regardless of individual knowledge levels. These factors should be considered in future research to better understand their role in shaping health behaviors among older adults. In light of these findings, targeted improvements in healthcare interventions and educational programs are recommended. Specifically, interventions should focus on improving knowledge, especially among those with lower education levels, as knowledge appears to be a critical driver of attitudes and practices. Additionally, strategies to encourage continued workforce participation in the elderly should be developed, given its positive association with attitude. Furthermore, social support networks, including living arrangements with children or other relatives, should be leveraged to promote proactive practices47,48.
The level of awareness among the elderly regarding intrinsic capacity is noteworthy, with a substantial percentage being aware of the concept and its components. It is noteworthy that awareness of intrinsic capacity was relatively low, with only 37.87% of participants being familiar with the term. This may be attributed to the limited dissemination of the concept in general health education and the lack of emphasis in routine clinical consultations. Moreover, the multidimensional nature of intrinsic capacity, encompassing cognition, mobility, vitality, mood, and sensory abilities, may contribute to difficulties in comprehension among the elderly population. However, variations in awareness, attitudes, and practices across different dimensions highlight the necessity for tailored educational initiatives. To improve the findings of this study and address the identified gaps, several targeted recommendations can be made. Firstly, educational programs should be developed to enhance awareness and knowledge about the different dimensions of intrinsic capacity, their risk factors, and their implications for overall well-being49. These programs can utilize various channels, including medical-related books and materials, hospital lectures, and new media, to reach a wider audience. In particular, digital interventions such as mobile applications tailored for the elderly could provide interactive education on intrinsic capacity. These applications should include user-friendly interfaces, voice-assisted navigation, and personalized health tracking tools to assess cognition, mobility, and nutritional status. Educational content should focus on practical strategies to maintain intrinsic capacity, such as cognitive training exercises, balance and strength workouts, and dietary recommendations for healthy aging50,51. Additionally, integrating telemedicine features within the application could facilitate regular health monitoring and professional guidance, thereby improving accessibility to preventive care. Furthermore, strategies integrating the informatization of the elderly, such as the development and widespread adoption of digital technologies and applications designed with older adults in mind, can significantly enhance their capacity to access information and manage their health independently. These technologies include easy-to-use smart devices and online health management platforms tailored specifically for the elderly52. Additionally, providing older adults with regular online health check-ups and consultation services can facilitate early identification and management of potential health issues, while simultaneously enhancing their understanding and application of health information. Practical interventions should focus on translating knowledge and attitudes into concrete actions. For instance, initiatives aimed at preventing falls, improving muscle mass, and addressing visual and hearing impairments should be promoted. Healthcare professionals can play a crucial role in assisting the elderly in assessing their intrinsic capacity and developing personalized plans for enhancement. Additionally, social engagement and communication should be encouraged, as they contribute to emotional well-being and overall resilience53,54.
Despite its valuable insights, this study has several limitations. Firstly, the cross-sectional design limits the establishment of causal relationships among variables. Secondly, the data relied on self-report measures, which may introduce response bias. Thirdly, the study was conducted in a single hospital in Shanghai, which may affect the representativeness of the findings. While the hospital serves a diverse elderly population, the results may not be fully generalizable to other regions or healthcare settings. Fourthly, the study relied on self-reported data collected through an online questionnaire, which may introduce response biases such as social desirability bias. To mitigate this, we ensured anonymity, emphasized the importance of honest responses, and supplemented data collection with face-to-face interviews for participants who preferred an alternative format. Lastly, while the self-designed questionnaire demonstrated high internal consistency and was developed based on established literature and expert consensus, further validation studies are needed to assess its cultural and educational relevance. Additionally, while this study proposed potential intervention strategies, their feasibility and effectiveness in real-world settings remain to be evaluated. Further research should refine these strategies, incorporating stakeholder input to ensure practical implementation and sustainability. However, despite these limitations, this paper contributes significantly to our understanding of the knowledge, attitudes, and practices of the elderly regarding their intrinsic capacity. The large sample size, comprehensive data collection, and application of SEM provide robust insights into the relationships between these factors.
Conclusion
In conclusion, the elderly population exhibited insufficient knowledge, positive attitudes, and proactive practices regarding their intrinsic capacity. It is imperative that healthcare providers and policymakers recognize these knowledge deficits and the interconnectedness of knowledge, attitude, and practice in this context. The findings of this study provide valuable insights for shaping elderly support policies and health education programs. By identifying key gaps in knowledge and practice, our results can inform the development of targeted educational campaigns, community-based initiatives, and digital health interventions aimed at promoting intrinsic capacity among older adults. Additionally, integrating these findings into policy frameworks could enhance resource allocation and improve access to preventive care, ultimately contributing to healthier aging populations. To address these issues, targeted interventions and educational initiatives should be implemented, focusing on improving the elderly’s understanding of their intrinsic capacity, especially among those with lower educational backgrounds.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Author contributions
Xu Zhou, Fei Gu, and Xuan Liu carried out the studies, participated in collecting data, and drafted the manuscript. Yun Li and Xiao Liu performed the statistical analysis and participated in its design. Tingting Huang and Zhirui Li participated in the acquisition, analysis and interpretation of data, as well as drafting the manuscript. All authors read and approved the final manuscript.
Data availability
All data generated or analysed during this study are included in this published article.
Declarations
Competing interests
The authors declare no competing interests.
Ethics approval and consent to participate
I confirm that all methods were performed in accordance with the relevant guidelines. This work has been carried out in accordance with the Declaration of Helsinki (2000) of the World Medical Association. This study has been approved by the Medical Ethics Committee of Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine (No. 2023SHL-KY- 86 - 02), and informed consent was obtained from each patient.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Xuan Liu, Email: liuxuan_97@126.com.
Tingting Huang, Email: 1017333244@qq.com.
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Supplementary Materials
Data Availability Statement
All data generated or analysed during this study are included in this published article.