Effects of personal and health characteristics on the intrinsic capacity of older adults in the community: A cross-sectional study using the healthy aging framework

doi:10.21203/rs.3.rs-2193768/v1

Background

Intrinsic capacity can better reflects the physical functioning of older adults, however, few studies have been able to systematically and thoroughly examine its influencing factors and provide limited evidence for improvement of intrinsic capacity. This study aimed to describe the status of intrinsic capacity of older adults in the community, compare the decline rate of older adults, explore the its influencing factors, and analyze the correlation between each of the five domains of intrinsic capacity and the factors.

Methods

This was a cross-sectional study conducted in the Chinese community. The self-designed general characteristics questionnaire was created based on the healthy aging framework and a systematic review. Intrinsic capacity was assessed with the Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS-15), self-reported visual and hearing status, Mini Nutritional Assessment Brief Form (MNA-SF), and Short Physical Performance Battery (SPPB). The influencing factors of intrinsic capacity were investigated using stepwise logistic regression. The correlation between the five domains of intrinsic capacity and the factors using Spearman correlation.

Results

A total of 968 older adults with a mean age of 71.00 (68.00, 76.75) were examined, and 704 older adults (72.7%) showed a decline in intrinsic capacity. There was a decline in at least one domain in 39.3% of older adults, with declines in each domain ranging from 5.3% (psychological) to 52.4% (sensory). Older adults had a higher risk of intrinsic capacity decline if they were 75–89 years old (95% CI: 1.153–2.293), had a low education level (95% CI: 0.284–0.652), lived alone (95% CI: 1.130–3.210), smoked (95% CI: 0.307–0.858), high Charlson Comorbidity Index (CCI) (95% CI: 1.246–1.810) scores, did not regular exercise (95% CI: 0.324–0.869), with lower handgrip strength (95% CI: 0.946–0.983). All the above factors influenced most of the domains of intrinsic capacity except smoking, and CCI can negatively influenced all domains of intrinsic capacity.

Conclusions

We found a relatively high prevalence of intrinsic capacity; more attention should be paid to olde adults who are older, less educated, live alone, and have more comorbidities. A healthy lifestyle should be emphasized for older adults with smoking, no regular exercise, and low handgrip strength.

Intrinsic capacity

Prevalence

Influencing factors

Older adults

Community

Population aging is currently one of the most important medical and social issues [1]. By 2020, 99 had reached an aging status globally, and the elderly population is expected to reach nearly 90 million by 2050. This phenomenon will significantly increase the proportion of older adults requiring long-term care [2]. Research shows that health disorders cause about a quarter of the global economic burden of disease in people over the age of 60 [3].

The ability to perform a specific function is the essence of health in old age [4]. To emphasize the significance of function ability, the World Health Organization (WHO) proposed healthy aging in 2015 as the process of acquiring and maintaining the functional abilities that allow older adults to achieve well-being. Among them, intrinsic capacity is a key concept that defines healthy aging as the sum of individual physical and mental abilities. It contains five domains: locomotor, psychological, sensory, cognitive, and vitality [4], all of which are crucial in maintaining and enhancing functional abilities and promoting healthy aging in the older adult [5]. According to the healthy aging framework, intrinsic capacity is a combination of physical and mental health functions that are genetically based and influenced by personal and healthy characteristics. That is, intrinsic capacity is influenced by three categories: personal characteristics, genetic inheritance, and healthy characteristics [4].

International researchers have attracted the concept of intrinsic capacity as a way to improve care for older adults. The WHO recommends screening older people for declining intrinsic capacity as early as possible. The measurement of intrinsic capacity has not been standardized, and various measures have been used to assess intrinsic capacity in different settings and populations, which may lead to different outcomes. The prevalence of declining intrinsic capacity ranges from 19.23% [6] to 89.3% [7], but most studies show this to be more severe. Lower intrinsic capacity is significantly associated with increasing age, female gender, lower educational level, lower wealth and more chronic diseases, and subjective social status [8, 9]. Aging affects almost all the physiological processes, but changes in body composition are most observable [10]. Anthropometric measures such as body mass index and waist-to-hip ratio, and body composition measures such as skeletal muscle mass and body fat mass can objectively measure the nutritional and energy metabolic status of older adults are important predictors of physical health in older adults [11], but few studies have been conducted to validate their relationship with intrinsic capacity. A survey of 376 geriatric patients was conducted, and IC scores were performed independently with body composition variables such as skim mass, body fat percentage, or visceral fat area, but there was no significant association between them [6]. Since older adults in the community had better health than inpatients, we need to verify the relationship in older adults living in the community with a larger sample.

It is noticed that settings and wealth can significantly influence intrinsic capacity, whereas low- and middle-income countries will bear a greater burden caused by population aging. To the best of our knowledge, the studies were mostly focused on high-income countries, or even if intrinsic capacity studies were conducted in low- and middle-income areas, the setting was chosen cities with higher economic levels, such as Beijing, China [12], and Nagoya, Japan [13], resulting in limited evidence for economically disadvantaged areas. China is a developing country and one of the most rapidly aging countries divided into four regions: the east, west, south, and north, with the west having the lowest per capita disposable income. The Xinjiang Uyghur Autonomous Region is located in western China, and its residents have distinct lifestyles. We conducted this study in Urumqi, the capital of Xinjiang, and randomized whole-group selected elderly adults to participate in our study, aimed to describe the status of the intrinsic capacity of older adults, compare the decline in intrinsic capacity of older adults with different characteristics, and explore the influencing factors of the intrinsic capacity of older adults in the community. Furthermore, the relationship between the 5 domains of intrinsic capacity and the above factors were explored.

Study design and participants

We used the randomized whole-group sampling method. Three of the nine districts were randomly selected based on the administrative division of Xinjiang Urumqi, with one community health service center chosen randomly from each district to conduct a whole-group survey of older adults in January, June, and July 2022. The inclusion criteria were (a) being over the age of 65 years and (b) with basic communication skills. The exclusion criteria were (a) severe mental system diseases, (b) metabolic diseases, (c) vital organ failure, and (d) severe disability that prevented participants from cooperating with the test. This study was approved by the Ethics Committee of Xinjiang Medical University (approval no.: XJYKDXR20220117021).

Data Collection

Initially, older adults were recruited using telephone appointments, resident WeChat group publicity, and on-site publicity. Second, with the consent of older adults, we conducted a face-to-face investigation. Professionally trained surveyors conducted one-to-one surveys for older adults. The surveyor asked for the paper version of the questionnaire, the elderly responded and then recorded, and the surveyor completed physical measurements, too. Finally, the research assistant verified the completeness of the items. This study included 1042 older adults, 74 of whom had missing critical information, and the response rate was 92.9%.

Measures

Intrinsic capacity

The measurement consisted of 5 domains proposed by WHO, and the tool selection was based on a combination of the WHO Integrated Care for Older People (ICOPE) screening tool [14] and research appropriate to the purpose of this study [15].

The short physical performance battery (SPPB) measured the locomotor domain, which contained a walking test, chair stands, and standing balance. For the walking test, people were required to complete the test at the usual walking speed of 4 m and repeat it twice. People had to stand up from a chair five times while keeping their feet flat on the ground and their arms folded across their chest. For the standing balance, we assessed whether it is feasible to stand side by side, in a semi-tandem stance and full-tandem for 10 s separately. The SPPB score ranges from 0 to 12; a score below 8 represents a decrease in the locomotor domain.

The cognitive domain was measured using the Mini-Mental State Examination (MMSE). The thresholds for education are 17, 20, and 24 points for primary, junior-middle, and senior high school, respectively; a score below the threshold indicates a decline in the cognition domain.

The psychological domain was assessed using the Geriatric Depression Scale (GDS-15), which has a total score of 0–15; a score less than 8 indicates a decline in the psychological domain.

The vitality domain was scored from 0 to 14 on the Mini Nutritional Assessment Brief Form (MNA-SF), a score of 11 or less indicates vitality domain decline.

The sensory domain was assessed by self-reported visual and hearing decline, which may cause difficulties in daily life. We asked the elderly, "Do you have trouble looking far or reading?” and “Do you suffer from eye disease, or are you receiving eye treatment?". For hearing, we ask the elderly, "Can you hear whisper clearly?" A score of 1 is given for "yes" answer in either vision or hearing, implying a decrease in the sensory domain.

Participants scored 1 (IC decline) or 0 (IC normal) in each of the five domains of intrinsic capacity. The total score ranged between 0 and 5, with higher scores indicating a more severe decline.

Variables

The selection of variables was completed according to two steps. At first, we conducted a systematic review on influencing factors of intrinsic capacity (Registered on PROSPERO, No.CRD42022292609, ongoing). Identified and controversial factors were considered in this study. The variables were then classified as personal and health characteristics based on the healthy aging framework.

(1) Personal characteristics, including gender, age, education, marital status, living status, monthly income, and source of income.

(2) Health characteristics included smoking, drinking, regular exercise, Body Mass Index (BMI), Charlson Comorbidity Index (CCI), CC, HGS, body fat mass, skeletal muscle mass, body fat percentage, waist-to-hip ratio, and visceral fat area.

People who smoked continuously or cumulatively for 6 months were defined as smokers. Older adults with drinking habits were defined as drinkers. Regular exercise was defined as older adults exercising at least three times per week, at least 30 min each time, and for more than six months. CCI is the summation of the assigned weights of seventeen comorbidities.

The handgrip strength (HGS) of the elderly was measured using a grip dynamometer (EH10, CAMRY, China)), and the highest handgrip strength among the three tests was taken. With the average measurement taken, a meter ruler measured the calf circumference (CC) twice on each side. Bioelectrical impedance analysis was performed with a body composition analyzer (DBA-210, DONGHUAYUAN Medical, China) to estimate body composition, including body fat mass, skeletal muscle mass, body fat percentage, waist-to-hip ratio, and visceral fat area.

Statistical analysis

Count data were reported as frequencies, and continuous data were examined the normality by Shapiro-Wilk first, then chose to mean (standard deviation) or median (interquartile range) to describe it. The chi-square test was used to compare the decline in intrinsic capacity of older adults with different characteristics.

We considered variables that were statistically different in the chi-square test, stepwise logistic regression was incorporated to derive the factors influencing intrinsic capacity, and did the correlation analysis between the 5 domains of intrinsic capacity and the above factors.

The analysis was performed using IBM SPSS Statistics 25.0, and a p-value of less than 0.05 was considered statistically significant. We reported odds ratios (OR) and 95% confidence intervals (CI) for the regression model.

Sample characteristics

The mean age varied from 60.0 to 93.0 years, with 58.5% female. Table 1 lists the characteristics of older adults.

Intrinsic capacity among older adults

We observed 72.7% of older adults showed a decline in intrinsic capacity. The percentage of older adults who had a decline in locomotor, cognitive, psychological, vitality, sensory was 31.4% (n=304), 19.7% (n=191), 5.3% (n=51), 11.1% (n=107), and 52.4% (n=507) respectively, and the declines in 1 to 5 domains of 39.3% (n=380), 22.8% (n=221), 8.0% (n=77), 2.4% (n=23) and 0.3% (n=3) respectively.

People with 75–89 years old had a lower education level, lived alone, smoked and did not exercise regularly, had a lower handgrip strength, and had a higher CCI. Lower skeletal muscle mass were both significantly associated with the more severe intrinsic capacity decline (p <0.05), but no significant difference was observed in gender, monthly income, sources of finance, smoking history, drinking history, BMI, CC, body fat mass, fat percentage, waist-to-hip ratio, and visceral fat area (Table 1).

Influencing factors of intrinsic capacity

Stepwise logistic regression showed that the old-old (95% CI: 1.153–2.293), low education level (95% CI: 0.284–0.652), living alone (95% CI: 1.130–3.210), smoking (95% CI: 0.307–0.858), high CCI (95% CI: 1.246–1.810) scores, did not regular exercise (95% CI: 0.324–0.869), and lower handgrip strength (95% CI: 0.946–0.983) had poor intrinsic capacity (Table 2).

The correlation analysis of these influencing factors and the domains of intrinsic capacity was performed, and the results are shown in Fig. 1. The level of psychological domain was positively correlated with education, living status, regular exercise habit, and handgrip strength, whereas it was negatively correlated with CCI. The level of sensory domain was positively correlated with education, living status, and handgrip strength, whereas it was negatively correlated with age and CCI. The level of vitality domain was negatively correlated with age and CCI and positively correlated with handgrip strength. The cognitive domain was positively correlated with living status and regular exercise, whereas it was negatively correlated with age and CCI. The motor domain was positively correlated with education, living status, regular exercise, and handgrip strength, whereas it was negatively correlated with age and CCI.

Condition of intrinsic capacity

This study assessed the factors associated with the decline in intrinsic capacity in the community over the age of 60, and the prevalence of decline in intrinsic capacity in older adults was relatively high. Similarly, other studies have found high rates of decline in intrinsic capacity in older adults in the community. A study found a prevalence of 77.4% of impaired intrinsic capacity in a survey of a senior-friendly community in Beijing over the age of 75 [16]. In a survey of 759 older adults aged 70–89 years with memory impairment in France, 89.3% of participants had one or more conditions related to a decline in intrinsic capacity [7]. There were older adults who showed a decline in 1–5 domains, with the highest percentage of declining in just 1 domain. As the number of declining domains increased, the number of older adults also tended to decline, very few older adults displayed a decline in 4–5 domains. Among the various domains of intrinsic capacity, about half of the older adults showed declines in the sensory domain, followed by the locomotor domain. The aging process is often accompanied by hearing and vision loss, but most older adults consider this a normal physiological change with age, thus neglecting the treatment and management of symptoms, which ultimately has a serious impact on daily life. Aging may also lead to musculoskeletal system disorders in the elderly, according to preliminary research conducted by the group, which found that the prevalence of sarcopenia in elderly people in Xinjiang Urumqi was 38.8% [17], which impaired locomotor function in the elderly and even caused adverse health outcomes such as disability and reduced quality of life [4].

Influencing Factors Of Intrinsic Capacity

We explored the effect of personal characteristics on the intrinsic capacity of older adults in the community. We found that higher age had a negative impact on intrinsic capacity, suggesting that the decline in intrinsic capacity may have occurred gradually with age, as consistent with previous research findings [18]. This could be the natural progression of underlying diseases and aging [14]. The gradual accumulation of molecular and cellular damage that occurs with aging results in a decrease in physiological reserves and an increase in disease risk, resulting in a general decline in individual abilities [4]. Although there is a tendency for intrinsic capacity to decline with age, a special population of very old adults exists with intrinsic capacity levels similar to those of younger older adults. It is also possible that the small number of very old in this study population produced some bias. Still, it suggests that we should focus on the diversity of older adults. In terms of education, the higher the level of education, the higher the level of intrinsic capacity, consistent with the study that there is a significant positive correlation between lower education levels and lower intrinsic capacity scores [19]. Older adults with better education may have a higher level of financial investment in health and also have access to health resources than those with lower education, so they are more likely to develop healthy life behavior patterns and greater self-care skills, which are conducive to maintaining a healthy state of physical functioning, cognition, and psychology [18]. Older adults who live with their spouses and children have higher intrinsic capacity scores, which may be related to the more convenient and accessible level of material support, emotional support, and life care. In order to better guide community care for older adults, the WHO issued a manual on integrated care for older adults, which suggests that caregivers should be involved in the overall care of older adults, thus inferring that living with others may be a modifiable condition for achieving healthy aging [14].

We similarly explored the impact of health characteristics on the intrinsic capacity of older adults in the community, those with smoking and higher CCI increases the risk of a decline in intrinsic capacity, which may be related to a long-term impairment of physical function in chronic diseases. In low- and middle-income countries, more than half of older adults are likely to have multimorbidity [20]. Therefore, it is crucial to emphasize the value of functional capacity even with chronic disease, as stated in the WHO World report on aging and health [4]. Notably, the health status of individuals exhibits dynamic changes. When assessing the health needs of older adults, it is critical to consider the impact of the interactions between these diseases on functional capacity, besides the specific diseases they may be experiencing [21]. Exercise has been shown to improve functional performance [22], cognitive function [23], and improve psychological problems [24]. Lack of regular physical activity increases the risk of decreased intrinsic capacity [25], and by encouraging older adults to participate in exercise, the use of unnecessary medical care can be reduced [26, 27]. Lower handgrip strength was associated with a higher risk of declining intrinsic capacity. The most significant single biomarker of health is handgrip strength, which may also evolve into a key indicator for tracking overall intrinsic capacity [28, 29]. Older adults with lower handgrip strength are more likely to experience cognitive decline and mental illness, which leads to a decrease in intrinsic capacity by maintaining muscle strength and has significant clinical implications [30].

This study is one of the few examples to examine the effect of anthropometric indicators of anthropometric composition on the intrinsic capacity of older adults. Older adults with higher skeletal muscle mass were shown to have better intrinsic capacity in univariate analyses. But no significant differences were shown when this variable was included in the regression equation. A survey of 376 geriatric patients showed that IC scores were not associated with body composition variables such as fat-free mass, Percentage of body fat, and visceral fat area [6]. This further suggests that IC may have a higher association with muscle function, but not with muscle mass.

A correlation analysis was also performed between the subdomains of intrinsic capacity, personality traits, and health traits. It was found that all factors except smoking history influenced most of the domains of intrinsic capacity, with CCI negatively influencing all domains of intrinsic capacity. Some of our findings are confirmed by the previous results of Beard et al. [8], one of the few articles that analyzed the factors influencing the subdomains. The results of the present study develop evidence of the factors associated with each domain.

The present study has several advantages as it included a relatively large sample size of nearly 1000 community-dwelling older adults and used randomized whole-group sampling to select the study population, making the sample relatively representative. Intrinsic capacity was measured according to the WHO-recommended approach and other studies that have been formally validated with valid and reliable results. The study factors were included based on theoretical and systematic evaluations, and they included less-studied body measurements and body composition indicators that were measured scientifically in a rigorous manner.

The cross-sectional design of this study limited the assessment of causal relationships between variables. It is recommended that future longitudinal studies with causal variables should be conducted to assess causality. Furthermore, although we obtained a relatively high prevalence of intrinsic capacity, the majority is likely to be underestimated because the older adults could care for themselves and were concerned about their health information.

Overall, our findings show that declining intrinsic capacity is common in low- and middle-income areas, and there is growing evidence for factors influencing intrinsic capacity. Our results suggest that the prevalence of declining intrinsic capacity is higher among older adults in the community. More attention should be given to older adults, less educated, live alone, and have more comorbidities. A healthy lifestyle should be emphasized for older adults with a history of smoking, no exercise habits, and low handgrip strength.

Ethical approval and consent

This study was approved by the Ethics Committee of Xinjiang Medical University (approval no.: XJYKDXR20220117021). All study procedures involving human participants were conducted in accordance with the Declaration of Helsinki of the World Medical Association and the ethical standards of Xinjiang Medical University. Written informed consent was provided by all participants.

Consent to publish

Not applicable.

Funding information

This work was supported by the Chinese Nursing Association (ZHKY202117) and Xinjiang Medical University Doctoral (Postdoctoral) Research Initiation Program (2019-20).

Conflict of interests

The authors declare that they have no conflict of interests.

Author contributions

JX and CF contributed equally to the conception and methodology, YX contributed to the data curation and formal analysis, YM, ZX, and MX contributed to the data curation, YP contributed to the supervision and validation.

Availability of data and materials

The datasets used and analysed during the study are available from the corresponding author.

Acknowledgements

The authors would like to thank all the reviewers who participated in the review and MJEditor (www.mjeditor.com) for their linguistic assistance during the preparation of this manuscript.

Author details

¹Nursing College of Xinjiang Medical University, No.567, Shangde North Road, Shuimogou District, Urumqi 830017, China.² Xingfu Road Branch of Traditional Chinese Medicine Hospital Affiliated to Xinjiang Medical University (Xingfu Road Community Center), No.226, Xingfu Road, Tianshan District, Urumqi 830002, China

Rudnicka E, Napierala P, Podfigurna A, Meczekalski B, Smolarczyk R, Grymowicz, M. The World Health Organization (WHO) approach to healthy ageing. Maturitas. 2020;139:6–11. doi:10.1016/j.maturitas.2020.05.018.
Administration on Aging, Administration for Community Living, U.S. Department of Health and Human Services. A profile of older Americans: 2013. 2014.
Prince MJ, Wu F, Guo Y, Gutierrez Robledo LM, O’Donnell M, Sullivan R, et al. The burden of disease in older people and implications for health policy and practice. Lancet 2015;385:549–62. doi:10.1016/S0140-6736(14)61347-7.
World report on ageing and health. Geneva: World Health Organization; 2015, p. 1–30.
Li C, Tang L, Jin J, Zhou L. The influence of intrinsic capacity and external environment on healthy aging among community elders. Nurs J Chin PLA. 2021;38:22–5. (in Chinese).
Ma L, Chhetri JK, Zhang Y, Liu P, Chen Y, Li Y, et al. Integrated care for older people screening tool for measuring intrinsic capacity: Preliminary findings from ICOPE Pilot in China. Front Med 2020;7:576079. doi:10.3389/fmed.2020.576079.
González-Bautista E, de Souto Barreto P, Virecoulon Giudici K, Andrieu S, Rolland Y, Vellas B. Frequency of conditions associated with declines in intrinsic capacity according to a screening tool in the context of integrated care for older people. J Frailty Aging 2021;10:94–102. doi:10.14283/jfa.2020.42.
Beard JR, Si Y, Liu Z, Chenoweth L, Hanewald K. Intrinsic capacity: Validation of a new WHO concept for healthy aging in a longitudinal Chinese study. J Gerontol. 2022;77:94–100. doi:10.1093/gerona/glab226.
Yu R, Amuthavalli Thiyagarajan J, Leung J, Lu Z, Kwok T, Woo J. Validation of the construct of intrinsic capacity in a longitudinal Chinese cohort. J Nutr Health Aging. 2021;25:808–15. doi:10.1007/s12603-021-1637-z.
JafariNasabian P, Inglis JE, Reilly W, Kelly OJ, Ilich JZ. Aging human body: Changes in bone, muscle and body fat with consequent changes in nutrient intake. J Endocrinol. 2017;234:R37–51. doi:10.1530/JOE-16-0603.
Xiong D, Hu M, Feng H, Wu X, Chen Q, Peng L. Analysis of the current situation of the intrinsic capacity of the elderly and research progress. Chinese Journal of Geriatrics. 2020,40:3575–80. (in Chinese).
Zhao J, Chhetri JK, Chang Y, Zheng Z, Ma L, Chan P. (2021). Intrinsic capacity vs. multimorbidity: A function-centered construct predicts disability better than a disease-based approach in a community-dwelling older population cohort. Front Med. 2021;8:753295. doi:10.3389/fmed.2021.753295.
Huang CH, Okada K, Matsushita E, Uno C, Satake S, Martins BA, et al. (2021). Dietary patterns and intrinsic capacity among community-dwelling older adults: A 3-year prospective cohort study. Eur J Nutr. 2021; 60:3303–13. doi:10.1007/s00394-021-02505-3.
Integrated care for older people: Guidelines on community-level interventions to manage declines in intrinsic capacity. Geneva: World Health Organization: 2017.
Zhang J, Zhang DD, Wu J, Zhou J, Li H, Sun C. (2020). Relationship between decline of intrinsic capacity and activity of daily living of elderly patients. Chinese Journal of Modern Nursing. 2020;26:4. doi:10.3760/cma.j.cn115682-20200612-03873. (in Chinese).
Liu S, Yu X, Wang X, Li J, Jiang S, Kang L, et al. Intrinsic Capacity predicts adverse outcomes using Integrated Care for Older People screening tool in a senior community in Beijing. Arch Gerontol Geriatr. 2021;94:104358. doi:10.1016/j.archger.2021.104358.
Che Y, Yang X, Zhang K, Wang YN, Wang YS, Yan P. Prevvalence and related factors of sarcopenia among the community in Urmqu. Chin J Osteoporos Bone Miner Res. 2020;13:304–10. (in Chinese).
Tang L. Comparative research on the current situation of healthy aging among the urban and rural elderly in jining city. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CMFD&dbname=CMFD202201&filename=1021115837.nh&uniplatform=NZKPT&v=xcFIWeDgWfHnt2LZdXYyQspZnvPt3xnTFcoIFdJCw3U0BG_iABE9DGYuyzv3gya9 (2021). Accessed 22 May 2021.
Beard JR, Jotheeswaran AT, Cesari M, de Carvalho IA. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019;9:e0261. doi:https://doi.org/10.1136/bmjopen-2018-026119.
Arokiasamy P, Uttamacharya U, Jain K, Biritwum RiB, Yawson AE, Wu F, et al. The impact of multimorbidity on adult physical and mental health in low- and middle-income countries: What does the study on global ageing and adult health (SAGE) reveal? BMC Med. 2015;13:178. doi:https://doi.org/10.1186/s12916-015-0402-8.
Lordos EF, Herrmann FR, Robine JM, Balahoczky M, Giannelli SV, Gold G, et al. Comparative value of medical diagnosis versus physical functioning in predicting the 6-year survival of 1951 hospitalized old patients. Rejuvenation Res. 2008;11:829–36. doi:10.1089/rej.2008.0721.
Pahor M, Guralnik JM, Ambrosius WT, Blair S, Bonds DE, Church TS, et al. Effect of structured physical activity on prevention of major mobility disability in older adults: The LIFE study randomized clinical trial. JAMA. 2014;311:2387–96. doi:10.1001/jama.2014.5616.
Bademli K, Lok N, Canbaz M, Lok S. Effects of Physical Activity Program on cognitive function and sleep quality in elderly with mild cognitive impairment: A randomized controlled trial. Perspect Psychiatr Care. 2019;55:401–8. doi:10.1111/ppc.12324.
Catalan-Matamoros D, Gomez-Conesa A, Stubbs B, Vancampfort D. Exercise improves depressive symptoms in older adults: An umbrella review of systematic reviews and meta-analyses. Psychiatry Res. 2016;30:202–9. doi:10.1016/j.psychres.2016.07.028.
Ma L, Chhetri JK, Zhang L, Sun F, Li Y, Tang Z. Cross-sectional study examining the status of intrinsic capacity decline in community-dwelling older adults in China: prevalence, associated factors and implications for clinical care. BMJ Open. 2021;11:e043062. doi:10.1136/bmjopen-2020-043062.
Easom LR. Concepts in health promotion: Perceived self-efficacy and barriers in older adults. J Gerontol Nurs. 2003;29:11–9. doi:10.3928=0098-9134-20030501-05.
Purdie N, McCrindle A. Self-regulation, self-efficacy and health behavior change in older adults. Educ Gerontol. 2002;28:379–400. doi:10.1080=03601270290081353.
Bohannon RW. Grip strength: An indispensable biomarker for older adults. Clin Interv Aging 2019;14:1681–91. doi:10.2147/CIA.S194543.
Arokiasamy P, Selvamani Y, Jotheeswaran AT, Sadana R. Socioeconomic differences in handgrip strength and its association with measures of intrinsic capacity among older adults in six middle-income countries. Sci Rep. 2021;11:19494. doi:10.1038/s41598-021-99047-9.
Ramírez-Vélez R, Correa-Bautista JE, García-Hermoso A, Cano CA, Izquierdo M. Reference values for handgrip strength and their association with intrinsic capacity domains among older adults. J Cachexia Sarcopenia Muscle 2019;10:278–86. doi:10.1002/jcsm.12373.

Table 1 Comparison of intrinsic capacity in characteristics

Variables	All (N=968)	IC normal (n=264)	IC decline(n=704)	Χ²/Z	p
Gender
Male	402(41.5)	117(29.1)	285(70.9)	1.163	0.281
Female	566(58.5)	147(26.0)	419(74.0)
Age
The young old (60–74years old)	630(65.1)	202(32.1)	428(67.9)	21.221	0.000
The old-old (75–89 years old)	335(34.6)	61(18.2)	274(81.8)
The very old (>90 years old)	3(0.3)	1(33.3)	2(66.7)
Education
Primary School and below	394(40.7)	93(23.6)	301(76.4)	29.118	0.000
Middle School	452(46.7)	113(25.0)	339(75.0)
University and above	122(12.6)	58(47.5)	64(52.5)
Marital Status
Married and with a spouse	738(76.2)	205(27.8)	533(72.2)	2.824	0.244
Widowed	204(21.1)	49(24.0)	155(76.0)
Divorced/Unmarried/Unspecified	26(2.7)	10(38.5)	16(61.5)
Living Status
Live alone	150(15.5)	20(13.3)	130(86.7)	17.389	0.000
Not living alone	818(84.5)	244(29.8)	574(70.2)
Monthly Income (yuan)
<3000	226(23.3)	56(24.8)	170(75.2)	4.684	0.096
3000~9999	658(68.0)	177(26.9)	481(73.1)
≥10000	84(8.7)	31(36.9)	53(63.1)

Table 1 Comparison of intrinsic capacity in characteristics (continued)

Variables	All (N=968)	IC normal (n=264)	IC decline(n=704)	Χ²/Z	p
Sources of Finance
Retirement pension or old-age pension	861(88.9)	227(26.4)	634(73.6)	3.238	0.072
Other subsidies	107(11.1)	37(34.6)	70(65.4)
Smoking
Smoking	114(11.8)	22(19.3)	92(80.7)	4.143	0.042
No smoking	854(88.2)	242(28.3)	612(71.7)
Drinking
Drinking	184(19.0)	51(27.7)	133(72.3)	0.023	0.880
No drinking	784(81.0)	213(27.2)	571(72.8)
Regular exercise
Yes	841(86.9)	240(28.5)	601(71.5)	5.169	0.023
No	127(13.1)	24(18.9)	103(81.1)
BMI	25.20 (23.00, 27.30)	25.20 (23.50, 27.10)	21.30(16.80,26.60)	-0.617	0.537
CCI	1.00 (0.00, 1.00)	0.00 (0.00, 1.00)	1.00(0.00,2.00)	-5.024	0.000
CC	35.00 (33.20, 37.00)	35.13 (33.50, 37.00)	35.00(33.25,36.50)	-0.986	0.324
HGS	23.70 (18.73, 29.80)	25.15 (20.73, 33.68)	25.30 (22.70, 27.50)	-5.400	0.000
Body fat mass	19.70 (15.43, 24.60)	25.70 (22.00, 29.30)	1.00 (0.00, 1.00)	-0.104	0.733
Skeletal muscle mass	24.50 (21.25, 28.70)	29.40 (23.73, 34.35)	35.00 (33.00, 37.00)	-5.400	0.000
Fat percentage	30.00 (24.20, 35.10)	19.85 (15.53, 24.20)	22.65 (18.20, 28.00)	-1.191	0.234
Waist-to-hip ratio	0.96 (0.94, 0.98)	0.96 (0.94, 0.98)	24.00 (21.10, 28.48)	-0.163	0.870
Visceral fat area	141.30 (127.10, 156.15)	141.40 (126.63, 154.78)	30.20 (24.40, 35.48)	-0.497	0.619

IC: intrinsic capacity; CCI: Charlson Comorbidity Index; CC: calf circumference; HGS: handgrip strength.

Table 2 Stepwise logistic regression of factors influencing intrinsic capacity

						95% CI(OR)
Variables	B	S.E.	Wald	p-value	OR	Lower	Upper
Age	0.486	0.175	7.686	0.006	1.626	1.153	2.293
Education	-0.844	0.212	15.799	0.000	0.430	0.284	0.652
Living status	0.644	0.266	5.858	0.016	1.905	1.130	3.210
Smoking history	-0.667	0.262	6.466	0.011	0.513	0.307	0.858
CCI	0.407	0.095	18.174	0.000	1.502	1.246	1.810
Regular exercise	-0.633	0.252	6.335	0.012	0.531	0.324	0.869
HGS	-0.037	0.010	14.227	0.000	0.964	0.946	0.983
Constant	2.666	0.454	34.465	0.000	14.384	5.906	35.030

CCI, Charlson Comorbidity Index; HGS, handgrip strength.

No competing interests reported.

Effects of personal and health characteristics on the intrinsic capacity of older adults in the community: A cross-sectional study using the healthy aging framework

Status:

Journal Publication

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Study design and participants

Data Collection

Measures

Intrinsic capacity

Variables

Statistical analysis

Results

Discussion

Condition of intrinsic capacity

Influencing Factors Of Intrinsic Capacity

Conclusion

Declarations

References

Tables

Additional Declarations

Status:

Journal Publication

Version 1