Two-Year Evolution of Frailty Status and Predictive Factors in Chinese Older Adults: A National Longitudinal Study

doi:10.21203/rs.3.rs-4820545/v1

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Two-Year Evolution of Frailty Status and Predictive Factors in Chinese Older Adults: A National Longitudinal Study

https://doi.org/10.21203/rs.3.rs-4820545/v1

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Background

With the global aging population, frailty in older adults has become a frontier and hotspot in health and aging research. As a dynamic process, the transition to frailty is

influenced not only by biological factors but also by various social, psychological, and environmental factors. Identifying the factors that influence the progression of frailty is key to achieving preventive interventions for at-risk individuals and implementing better health practices and healthcare strategies for older adults.

Methods

The data used in this study were obtained from the Fourth Sample Survey of the Aged

Population in Urban and Rural China database, organized by the ChinaNational Committee on Ageing. The baseline data used in this study was from elderly individuals who participated in the survey in 2017, and the follow-up data were from the 2019 survey. Frailty in older adults was assessed using the frailty index (FI) model to analyze the current frailty status among older adults in China and to prospectively analyze the developmental trajectory of frailty. Multivariate logistic regression was used to identify the factors that influence the progression of frailty.
Results

A total of 9,093 older adults were included in the analysis. FI values increased with age and were higher in women than in men at any age, suggesting that older women had higher levels of frailty than men. During the 2-year follow-up, most of the older adults' frailty remained stable (56.2%, 5,111/9,093), 1,292 (14.2%, 1,292/9,093) older adults' frailty improved, and 2,690 (29.6%, 2,690/9,093) older adults' frailty worsened. Transitions to a more frail status (i.e., worsening) were more common among older adults than transitions to an improved frailty status. Additionally, transitions between adjacent frailty statuses were more frequent than transitions across several frailty statuses (3,669 (40.3%) versus 313 (3.4%)). The results of multivariate logistic regression analyses revealed that age, sex, place of residence (general status), living alone, medical health status (co-morbidities among older adults, number of hospitalizations, frequency of exercise, activity of daily living function), care in case of illness, economic status (still working in an income-generating job, ownership of old-age pension or property rights, financial situation), and social participation status (participation in public service activities, participation in gerontological associations, regular access to the Internet) as factors that influence the progression of frailty status in older adults.

Conclusion

The worsening of frailty with age is more common in older adults than the transition to improved frailty. Among robust and pre-frail older adults, women are more likely to experience a worsening of their frailty status. Factors that influence the transition to frailty encompass multiple and complex elements. Therefore, when intervening in the progression of frailty in older adults, it is necessary to comprehensively assess the risk of frailty and the factors that influence it based on the multifaceted characteristics and current status of specific individuals. Individualized, comprehensive, and targeted interventions and management strategies tailored to different stages of frailty and transition pathways can improve frailty in older adults.

Frailty status

Predictive factors

Longitudinal study

National survey

Frailty has gained widespread attention as a common syndrome among older adults. With global aging, the harm of frailty is becoming more prominent. Frailty, as a complex geriatric syndrome, is a nonspecific state in which multiple functions of the body are abnormal or physiologic reserves decline, resulting in increased vulnerability and decreased stress resistance. Frailty affects 4–59% of older adults, depending on socioeconomic conditions [1]. It has been shown to be associated with adverse health outcomes such as falls, fractures, hospitalization, disability, and death in older adults [2–4]. Furthermore, the frailty status in older adults is recognized as a dynamic and evolving process. Unlike increasing age, which is inevitable, frailty is reversible [5]. Frailty may represent an intermediate stage of biological age between health and the end of life [6]. Identifying the factors that influence the progression of frailty is key to realizing preventive interventions for at-risk individuals and will help implement better health practices and healthcare strategies for older adults.

Natural transitions of frailty status and the factors influencing them have been reported. These factors are mainly related to sociodemographic characteristics and health status. Older individuals, those with fewer years of education, diabetes mellitus and previous strokes, poorer functional performance, and cognitive impairments have been associated with worsening frailty [7–9]. However, while these findings may not be sufficient to develop health promotion programs for community-based elderly populations, they can be useful for healthcare workers in identifying susceptible individuals. In China, most of the current research on frailty has focused on screening and assessing frailty, with relatively few studies conducted on frailty transition, particularly on large samples of community-dwelling older adults. In this study, the frailty trajectory in Chinese community-dwelling older adults was analyzed based on the Fourth Sample Survey of the Aged Population in Urban and Rural China (SSAPUR) database. We conducted a prospective cohort study to explore the transitions of frailty status and the factors influencing frailty progression in older adults. The findings provide a foundation for improving the prognosis of older adults, implementing targeted interventions to prevent frailty, and delaying frailty progression.

Study design and participants

This study utilized data from the SSAPUR, an extensive and large-scale survey study of older adults in China. The survey, conducted from August 1 to 31, 2015, was nationally representative of permanent residents aged 60 and older. The survey employed a stratified multi-stage probability proportional sampling (PPS) method, with regional sample sizes selected based on the proportion of the population aged 60 and over in each region. This nationwide survey included all provinces, autonomous regions, municipalities directly under the central government, and the Xinjiang Production and Construction Corps, covering 466 counties (districts), 1,864 townships (streets), and 7,456 administrative villages (neighborhoods), resulting in a substantial amount of data [10, 11]. Elderly individuals who refused to participate, passed away, could not be contacted (after at least three attempts), or lived in long-term care facilities were excluded. The final sample included 224,142 older adults. The study protocol was approved by the Beijing Hospital Ethics Review Committee (No. 2021BJYYEC-294-01) and the National Bureau of Statistics (No. [2014] 87). All participants provided written informed consent. Subsequently, the China National Committee on Ageing conducted continuous monitoring of the Fourth Survey sample obtained in 2015 in subsequent years, including 2016, 2017, 2018, and 2019 to dynamically grasp the living conditions and health of older adults. In this study, the database of older adults who participated in the survey in 2017 was used as the baseline data. The database of the 2019 survey served as the follow-up database to analyze the changes in the frailty status of older adults from 2017 to 2019 (frailty transition).Of the 12,788 older adults assessed at baseline in 2017, 3,695 were lost to follow-up through 2019. Eventually, 9,093 older adults were enrolled in this study, with an age range of 62–101 years and a mean age of (71.2 ± 7.0) years. Out of these, 4,598 (50.6%) were men and 4,495 (49.4%) were women. The majority of older adults were Han Chinese (95.9%, 8,720 cases). The proportion of urban elderly subjects was slightly greater than that of rural elderly subjects [4,656 cases (51.2%) versus 4,437 cases (48.8%)].Most older adults had a low level of education, with 6,633 cases (72.9%) being illiterate. Additionally, 72.6% (6,599 cases) of older adults had 1–3 co-morbidities. The vast majority of older adults (8,807 cases, 96.9%) had at least one activity of daily living (ADL) disability. At baseline in 2017, 9,093 older adults had a frailty index (FI) of 0.14 ± 0.09. The numbers of healthy (robust), pre-frail, and frail older adults were 3,572 (39.3%), 4,098 (45.1%), and 1,423 (15.6%), respectively.

Survey contents

Data were collected through home-based interviews and questionnaires. The survey included various indicators, including demographic characteristics (age, sex, ethnicity, educational attainment, marital status, and so on), family status (living alone or not, children's status, and so on), health and medical status (vision, hearing, exercise, use of health care products, participation in medical checkups, chronic diseases, medical consultations for illnesses, medical insurance, self-assessment of health status, and so on), caregiver service status (ADL, incontinence status, use of assistive devices, life care and nursing care, willingness to receive life care and nursing care, and so on), economic status (income, expenditure, own housing, and so on), living environment (housing area, housing conditions, satisfaction with housing, and so on), social participation status (participation in public welfare activities, willingness to help elderly people in difficulty), rights protection status (understanding of the rights and interests of older adults, protection of their legal rights and interests), and spiritual and cultural life status (participation in community activities, regular access to the Internet, and so on). Notably, diseases had to be diagnosed by hospitals at or above the county level, and participants who experienced symptoms but did not receive a definitive diagnosis were not included in the statistics.

Assessment of frailty and FI transitions

Frailty was assessed using the FI model developed by Prof. Kenneth Rockwood's team. The FI was

constructed using a total of 31 variables selected from the survey content. These variables included ADL (6 items), chronic diseases (11 items), geriatric syndromes (5 items), health status and emotion (4 items), and use of assistive devices (5 items) [see Appendix 1]. Values were assigned to the health variables based on their type, such as 0 and 1 for dichotomous variables, 0, 0.5, and 1 for tricotomous variables, and so on. The assigned values ranged from 0 to 1, with larger values indicating more severe health deficits [12].To calculate the FI, the number of scores for the presence of health deficits was divided by the total number of items considered health deficits (31 in this study). The FI represents the proportion of potential indicators of poor health among all the health measures for an individual. Similar to the assigned values, the FI value also ranges from 0 to 1, with larger values indicating more health deficits and a more severe frail status for the individual [12].Based on previous studies by Thompson et al. and Hoover et al. [13, 14], frailty was categorized into three levels using cut-off points of 0.10 and 0.21 for the FI values. These levels are as follows: robust (FI ≤ 0.10), pre-frail (0.10 < FI ≤ 0.21), and frail (FI > 0.21). A transition in frailty (FI transition) for older adults during a two-year follow-up was defined as a change in frailty status, including worsening, stabilization, or improvement.

Predictors

Demographic factors included age (in years), sex (male/female), ethnicity (Han Chinese/minority),

place of residence (urban/rural), educational attainment (illiterate/elementary or junior high school/high school and above), and marital status (married/widowed or divorced/never married). Family status included living alone (yes/no). Health and medical status included the frequency of exercise per week (never/1–2 times/3–5 times/≥6 times), consumption of health supplements (never/occasionally/frequently), co-morbidities (0/1–3/≥4), incidence of diseases in the preceding 2 weeks (yes/no), receipt of medical checkups in the past year (yes/no), incidence of hospitalization in the past year (0/1/≥2), possession of medical insurance (yes/no), and access to convenient reimbursement for medical expenses (very convenient/moderately convenient/fair/moderately inconvenient/very inconvenient). Caregiving service status included normal activities of daily living (yes/no) and caregiving when sick (yes/no). Economic status included having income-generating work (yes/no), having pension money (yes/no), having a house of their own (yes/no), and self-rating of economic status (very rich/moderately rich/basically enough/moderately poor/very poor). Social participation included participation in public welfare activities (yes/no), participation in senior citizen associations (yes/no), willingness to help elderly people in need in the community (yes/no), participation in activities such as playing ball games and fishing (yes/no), regular access to the Internet (yes/no), and participation in university for older adults/distance education for older adults (yes/no).

Statistical analysis

SPSS 24.0 and MATLAB 2020 software were used for data analysis and graphing. Missing values were imputed using the Markov Chain Monte Carlo method in themultiple imputation method [15]. Measurement data were expressed as x ± s, and the analysis of variance was used to compare multiple groups. Enumeration data were expressed as the number of cases (percentage), and the χ²test was used to compare groups. Histograms were used to characterize the distribution of frailty index values. Bar graphs were used to compare the FI of men and women among different age groups and to analyze changes in the frailty status of older adults with varying degrees of frailty at baseline. Nonlinear regression techniques were used to fit age-specific frailty index values as a function of age (an exponential function) for elderly people of different sexes at baseline and follow-up. Factors influencing the frailty transition status of older adults were analyzed using binary logistic regression and multinomial logistic regression according to different levels of frailty at baseline. Differences were considered statistically significant at P < 0.05.

Comparison of general characteristics and related factors of older adults with different frailty statuses

A total of 9,093 older adults were included in this study, ranging in age from 62 to 101 years, with a mean age of 71.2±7.0 years. Among the participants, 4,495 were women, with a mean age of 71.47±7.20 years, and 4,598 were men, with a mean age of 70.90±6.76 years. The proportions of robust, pre-frail, and frail older adults were 39.3% (3,572/9,093), 45.1% (4,098/9,093), and 15.6% (1,423/9,093), respectively. The proportion of pre-frailty and frailty was higher in older adults who were older, female, classified as an ethnic minority, lived in rural areas, and had low educational attainment.

The general characteristics of older adults with different frailty statuses were further compared according to sex. Except for the ethnicity and place of residence of elderly men, the effects of the remaining variables such as age, and educational attainment on the frailty statuses of elderly men and women were statistically significant (all P<0.05). Moreover, all other relevant factors, except for consumption of health supplements, participation in a medical checkup in the past year, access to health care coverage, and participation in university or distance education for older adults, had an effect on the frailty status in old adults, both in men and women (Table 1).

Analysis of frailty status in older adults at baseline and follow-up

At baseline in 2017, the 9,093 older adults had a minimum FI value of 0, a maximum FI value of 0.76, a median of 0.12, a mode of 0.09, and a mean value of 0.14±0.09. Specifically, men had a median FI value of 0.10 and a mean of 0.12±0.08, whereas women had a median FI value of 0.14 and a mean of 0.15±0.09. At the 2019 follow-up, the minimum FI value was 0, the maximum value was 0.77, the median was 0.14, the median was 0.13, and the mean FI value was 0.16±0.11. Specifically, men had a median FI value of 0.13 and a mean value of 0.15±0.10, whereas women had a median FI value of 0.15 and a mean value of 0.18±0.11 (Figure1A–B). FI values were compared in older adults of different sexes according to age. FI values increased with age, and women were more frail than men in all age groups (Figure 2A–B).

Subsequently, trends in FI values according to age were analyzed in older adults of different sexes. The FI values increased exponentially with age in both older men and women, represented as Ln(FI)=A+BXage. Women had higher FI values than men at any age, both at baseline in 2017 and at the follow-up in 2019. Meanwhile, the frailty status in older men at the follow-up in 2019 was comparable to that of older women at the baseline in 2017 (Figure 3). On a logarithmic scale, at the baseline in 2017, older women had a slightly lower rate of health deficit accumulation than men; however, the difference was statistically insignificant (B=0.020 versus B=0.021, t=1.049, P=0.639). However, in 2019, the mean annual relative growth rate of FI values was higher in women than in men (B=0.023 versus B=0.020, t=5.100, P<0.001). In other words, older women

accumulated health deficits at a faster rate than men (Figure 3).

Changes in frailty status

At baseline in 2017, the proportions of robust, pre-frail, and frail older adults were 39.3% (3,572/9,093), 45.1% (4,098/9,093), and 15.6% (1,423/9,093), respectively. In 2019, these values were 30.6% (2,784/9,093), 45.0% (4,089/9,093), and 24.4% (2,220/9,093). During the 2-year follow-up, the majority of older adults' frailty remained stable (56.2%, 5,111/9,093), while 14.2%(1,292/9,093) experienced an improvement in their frailty, and 29.6%(2,690/9,093) experienced a worsening in their frailty. Among these, 54.3% (1,939/3,572) of robust older adults, 55.1% (2,259/4,098) of pre-frail older adults, and 64.2% (913/1,423) of frail older adults remained unchanged from their baseline frailty statuses. In terms of frailty transitions, 38.7% (1,383/3,572) of baseline robust older adults progressed to pre-frailty, 25.8% (1,057/4,098) of pre-frail older adults became frail at the 2-year follow-up, and 7.0% (250/3,572) of robust older adults progressed directly to frailty. Notably, 31.4% (447/1,423) of frail older adults improved to a pre-frail status at the 2-year follow-up, 19.1% (782/4,098) of pre-frail older adults improved to a robust status, and 4.4% (63/1,423) of frail older adults returned to a robust status. Overall, transitions to more frail statuses (i.e., deterioration) were more common among older adults than transitions to improvements in frail statuses. Furthermore, transitions between adjacent frail statuses were more frequent than transitions across several frail statuses [3,669 (40.3%) versus 313 (3.4%)] (Figure 4).

Further sex subgroup analyses revealed that among older women, 54.6% (2,453/4,495) had stable frailty statuses, 14.1% (635/4,495) showed improvement, and 31.3% (1,407/4,495) experienced worsening frailty statuses. Among older men, 57.8% (2,658/4,598) had stable frailty statuses, 14.3% (657/4,598) experienced improvement, and 27.9% (1,283/4,598) had worsening frailty statuses. Overall, a higher proportion of women than men experienced worsening frailty statuses (χ²=13.148, P=0.001). Specifically, among robust and pre-frail older adults, a higher proportion of men than women had stable or improved frailty statuses, while women tended to experience worsening frailty (χ²=55.849, 47.820, both P<0.001). However, among the frail elderly, the difference in frailty status transitions between men and women was not statistically significant (χ²=4.695, P=0.096) (Table 2, Figure 4A). Analyses based on age subgroups showed that in the 60+ group, 57.7% (2,595/4,499) of older adults had stable frailty statuses, 13.8% (623/4,499) exhibited improvement, and 28.5% (1,281/4,499) experienced worsening. In the 70+ age group, these values were 55.6% (1,806/3,247), 14.0% (454/3,247), and 30.4% (987/3,247), respectively. For the 80+ age group, the proportions were 52.7% (710/1,347), 16.0% (215/1,347), and 31.3% (422/1,347) (Table 2, Figure 4B). Notably, older adults had an increased risk of worsening frailty with increasing age (χ²=12.297, P=0.015). Additionally, the association between age and frailty change was significant in older adults, regardless of their baseline frailty status (robust, pre-frail, or frail) (χ²=82.809, 93.467, 15.251, all P<0.05). In other words, as age increases, older adults are more inclined to the worsened frailty status (Table 2, Figure 4B).

Multivariate logistic regression analysis of factors influencing frailty transition in older adults

The baseline FI values for older adults whose frailty status remained stable, worsened, or improved were 0.14±0.10, 0.10±0.05, and 0.19±0.07, respectively. Individuals with higher baseline frailty were more likely to experience improvements in their frailty statuses (F=423.633, P<0.001). Subsequently, logistic regression analyses were conducted to investigate the factors influencing frailty transition at different baseline frailty levels. The dependent variable in the regression model was frailty transition, and all variables potentially related to frailty transition were included. The results of the analysis are as follows:
1.General status: Among older adults with different frailty levels, increasing age, being female, and living in a rural area were associated with worsened frailty status. However, being widowed, divorced, or unmarried, as well as having a low level of education, increased the risk of worsened frailty status only among robust and pre-frail older adults; these factors did not show a correlation with improved frailty status among frail older adults. Additionally, ethnic minority older adults with frailty status had a higher likelihood of experiencing frailty improvement compared to Han Chinese older adults.
2. Family status: Living alone increased the risk of worsened frailty status among pre-frail older adults. However, for frail older adults, living alone increased the likelihood of frailty improvement.

3. Medical and health status: Having an increased number of co-morbidities and hospitalizations in the past year raised the risk of worsened frailty for both robust and pre-frail older adults. Additionally, engaging in more weekly exercise decreased the risk of worsened frailty but had no effect on frail older adults. Furthermore, being sick in the previous 2 weeks increased the risk of worsened frailty among robust older adults. Moreover, undergoing a physical checkup in the past year reduced the risk of worsened frailty in robust older adults but had no effect on pre-frail and frail older adults. Finally, performing normal activities of daily living was more beneficial for frail older adults in terms of frailty improvement. Therefore, multiple measures should be implemented to improve ADL functioning in frail older adults.
4. Caregiving status: Providing care when sick had a positive effect on frailty improvement among pre-frail and frail older adults.
5. Economic status: Robust and pre-frail older adults who were employed, had a pension, owned their own home, and were financially stable had a reduced risk of worsened frailty. However, these factors did not have an effect on frail older adults.
6. Social participation: Regular engagement in public service activities, participation in senior citizen associations, consistent Internet access, willingness to help older people in the community, and participation in activities such asplaying ball games or fishing decreased the risk of worsened frailty, especially for robust or pre-frail older adults (Table 3).

Further subgroup analysis according to sex revealed the impact of the following variables on frailty transition:

1. General status: Age and place of residence affected the transition to frailty status in both older men and women. However, ethnic minority frail men were more likely to improve their frailty status compared to Han Chinese frail men. Additionally, educational attainment only influenced the transition to frailty status among pre-frail women. Moreover, marital status mainly affected pre-frail elderly women and robust elderly men.

2. Family status: Living alone affected pre-frail elderly women and frail elderly men.

3. Medical and health status: The frequency of weekly exercises, presence of co-morbidities, and number of hospitalizations in the past year influenced the transition to frailty status in both elderly men and women. In addition, experiencing a medical condition in the previous 2 weeks only affected robust women. Moreover, a physical checkup in the past year provided protection against the transition to frailty status among robust individuals but had no effect on pre-frail and frail individuals. Overall, normal ADL had the greatest impact on improving frailty status in both older men and women.

4. Caregiving status: Caregiving when sick positively influenced frailty status improvement, particularly in frail older women and pre-frail and robust older men.

5. Economic status: All variables of economic status were associated with the transition to frailty status in both older men and women, except for having pension money, which only affected older women.

6. Social participation status: With the exception of participation in university or distance education options for older adults, social participation had a positive effect on improving frailty status among robust or pre-frail older men and women but had minimal impact on frail older individuals (Table 3).

Based on the SSAPUR database, this study analyzed the frailty status and natural transition of frailty among community-dwelling elderly people in China through a prospective cohort study. The study also identified the factors that influence changes in the frailty status of older adults. Additionally, the frailty status of older adults was evaluated using the FI model. Systematic evaluation has shown that the FI is the most comprehensive assessment tool for frailty in older adults, covering all the associated factors. It is considered the most useful tool for assessing frailty in both routine care and community settings [16].The FI approach represents a continuum of health, which better characterizes the dynamic nature of frailty in the general elderly population [17]. The results of this study revealed that FI values in older adults increased with age, both at baseline in 2017 and at follow-up in 2019. Furthermore, regardless of age, older women were found to be more frail than men, which is in line with our previous findings [18, 19]. Men and women have differing biological, psychological, and sociological factors that could influence their risk and degree of frailty. Women may be more susceptible to social isolation, psychological stress, and negative emotions, which could increase their risk of frailty [20, 21]. Changes in sex hormone levels in older adults are also involved in the development of frailty. Decreased levels of sex hormones are directly associated with myasthenia, fatigue, and reduced function in frail older adults. Older women experience a significant decrease in estrogen levels after menopause, which predisposes them to physical symptoms such as fatigue, insomnia, and headache, and psychological symptoms such as anxiety and depression [22]. In contrast, the frailty status of elderly men is closely related to androgen levels, and high levels of serum-free testosterone and dihydrotestosterone can reduce the risk of frailty in elderly men [23]. Therefore, when intervening in frailty for older adults of different sexes, it is important to consider their specific frailty status.

Frailty is a dynamic process. Over the 2-year follow-up period of this study, the majority of older adults (56.2%) had a stable frailty status, 14.2% improved their frailty status, and 29.6% experienced worsening frailty. Notably, only 4.4% of frail older adults returned to a healthy state. Thus, it is clear that transitions to more frail states (i.e., worsening) were more common than transitions to improved frailty status. Furthermore, transitions between adjacent frailty statuses occurred more frequently than transitions across multiple status levels. These findings are consistent with other studies. In a Survey of Health, Ageing and Retirement in Europe (SHARE) study involving 11 European countries and a 2-year follow-up of 14,424 middle-aged and older adults over the age of 55, 61.8% had unchanged frailty, 22.1% had worsened frailty, and 16.1% had improved frailty [24]. A study in the United States showed similar results, with worsening frailty being more common than improvement. Specifically, the percentage of recovery from a frail to a healthy state at 18-month intervals of follow-up was only 0–0.9% [25]. These results suggest that interventions in the early stages of frailty may be more effective in clinical practice.

In this study, subgroup analyses according to sex revealed a higher proportion of worsening frailty in women than in men, particularly among robust and pre-frail older adults. However, there was no statistically significant difference in frailty status shifts between men and women among frail

older adults, which aligns with the findings of Lorenzo-López et al. [26] and Ye et al. [27]. This emphasizes that the sex disadvantage experienced by women in terms of physical and mental health must be considered. However, once an individual enters a frailty status, sex may no longer be the primary determinant of further worsening; instead, other health and social factors may play a more dominant role.

Older adults face an increased risk of worsening frailty with age, and this association between age and changes in frailty is significant among robust, pre-frail, and frail older adults at baseline. Traditionally, age has been used as a way to measure physiological aging because as people age, they accumulate various pathological factors that can negatively impact their health. Additionally, the gradual decline in organ and tissue function makes the body more susceptible to disease, which can further deteriorate overall health and increase the risk of frailty. Mental health issues are also common among older adults, possibly due to reduced socialization and social participation, as well as potential changes in their living environment and lifestyle choices. Overall, these factors can all contribute to the worsening of frailty in older individuals.

In the present study, a multivariate logistic regression analysis revealed several important factors influencing the transition to frailty in older adults. Among the general conditions, increasing age, being female, and rural residence were associated with worsening frailty in older adults, consistent with previous studies. These findings emphasize the importance of social and geographic factors in the frailty process. Specifically, in rural areas, older adults face greater frailty and health risks due to inadequate medical and healthcare resources [28].Additionally, being widowed, divorced, or unmarried and having low educational attainment increased the risk of worsening frailty in robust and pre-frail older adults; however, these factors did not appear to play a significant role in already-frail older adults. This suggests that other factors, such as biological and physiological factors, may play a greater role at some point in the frailty process [29].In particular, the finding that frail older adults from ethnic minorities have a higher chance of frailty improvement compared totheirHan Chinese counterparts is consistent with previous research on the importance of community and cultural support for improvement in frailty [30].Overall, specific social and cultural environments may provide older adults with more psychological and social support, contributing to the improvement of their frailty status and overall health .Living alone significantly increased the risk of frailty worsening in pre-frail older adults, highlighting the key role of social support in preventing frailty progression, as seen in an earlier study [31]. However, for older adults who are already frail, living alone appears to contribute to frailty improvement. This may reflect the positive coping strategies and enhanced self-management that older adults living alone may adopt in the face of debility. However, more research is needed to deepen the understanding of this complex phenomenon. In addition, medical health conditions such as co-morbidities, increased hospitalizations, and recent illnesses were found to increase the risk of frailty worsening, consistent with previous findings [32]. Ultimately, it was observed that these factors have a greater impact on robust or pre-frail older adults, emphasizing the importance of early intervention for frailty. Moreover, the finding that frail older adults with normal ADL function were more likely to improve their frailty highlights the importance of improving ADL function in frail older adults. Such improvements can enhance autonomyand quality of life and potentially halt or reverse frailty progression [33]. The present study also found that caregiving when sick has a positive effect on frailty improvement among pre-frail and frail older adults, emphasizing the importance of social and emotional support in promoting health and well-being [34]. In addition, robust and pre-frail older adults who were still employed, had pension money, owned their own houses, and were in a better financial position had a significantly lower risk of frailty worsening, consistent with previous research [35]. This highlights the importance of financial security and asset ownership in reducing the risk of deteriorating frailty. However, these factors did not appear to have a significant effect among older adults who were already frail. Mechanistically, it appears that the impact of economic factors diminishes as health declines severely. Furthermore, the results of social participation status on the transition to frailty highlight the important role of active social and leisure activities in reducing the risk of frailty worsening. Regular participation in public service activities, senior citizen associations, Internet access, and participation in community mutual aid and leisure activities (e.g., ball games and fishing) are critical in the management of older adults' health, particularly for robust or pre-frail older adults [36]. Lastly, older adults of different sexes may respond differently to risk factors for frailty and have different needs for prevention and treatment strategies. Therefore, a sex subgroup analysis was conducted to identify factors influencing the transition to frailty. Overall, the findings of the present study provide important insights into the factors influencing the transition to frailty in female and male older adults and contribute to the development of individualized intervention strategies for older adults of different sexes and frailty statuses.

There are several limitations to this study. Firstly, the reliance on patient self-reported data may introduce information bias, as older adults with impaired cognitive function may not accurately report their health status and lifestyle habits. Secondly, while this study compared factors influencing the transition to frailty between male and female older adults, it did not thoroughly examine the interaction between sex and other social and economic factors. Additionally, the variables included in the study were based on the content of SSAPUR questionnaire, overlooking potential confounders such as genetic factors and long-term lifestyle factors such as smoking and alcohol consumption, which can influence the development and transition of frailty. Future research should refine the questionnaire and include relevant information for more in-depth analysis.

In conclusion, this study used data from the SSAPUR database to explore the transition to frailty and its influencing factors in older adults. The study found that frailty status tends to worsen with age rather than improve. Moreover, among robust and pre-frail older adults, women showed a greater tendency to worsen their frailty status. Ultimately, the transition of frailty is influenced by multiple complex factors, including age, sex, residential status, social activity participation, and economic status. Therefore, interventions targeting frailty in older adults should consider the multifaceted characteristics and current status of individuals. Overall, comprehensive assessments of frailty risk and influencing factors, along with tailored interventions and management strategies for different frailty stages and transition pathways, can effectively alleviate frailty in older adults.

Acknowledgments

The authors thank the participants of the fourth SSAPUR study and the National Key R&D Program of China for their assistance.

Author contributions

JS: Performed statistical analysis of the data, and drafted the paper. LZ: Designed the study, assisted with the data analysis and revised the paper. YT, CG, YC: Assisted with the data analysis and manuscript preparation. SL, YL, BS, XL, QM: Data cleansing and processing. XZ: Assisted with the data analysis and result interpretation. YZ, DL: Initiated and designed the study, revised the paper, and provided final approval for the version to be published. All authors contributed to the manuscript revision as well as read and approved the submitted version.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by grants from the National Key R&D Program of China [Grant nos.2020YFC2003000 and 2020YFC2003001], the National High Level Hospital Clinical Research Funding (Grant No. BJ-2023-018).

Avaliability of data and materials

The data may be available from the corresponding author on reasonable request.

Ethics approval and consent to participate

In this study, all methods were carried out in accordance with relevant guidelines and regulations or declaration of Helsinki. This study was approved by the Ethics Review Committee of Beijing Hospital (2021BJYYEC-294-01). The participants provided their written informed consent to participate in this study.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

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Table 1 Comparison of general characteristics and related factors among older adults with different levels of frailty

Variables	All					Women					Men
Variables	Total	Robust	Pre-frail	Frail	F/x² (P-value)	Total	Robust	Pre-frail	Frail	F/x² (P-value)	Total	Robust	Pre-frail	Frail	F/x² (P-value)
N	9093	3572	4098	1423		4495	1481	2157	857		4598	2091	1941	566
Age (x±s)	71.2±7.0	69.3±6.1	71.7±6.9	74.2±7.8	287.853 (0.000)	71.5±7.2	69.2±6.2	71.9±7.1	74.4±7.9	158.269 (0.000)	70.9±6.8	69.4±6.1	71.6±6.8	74.0±7.7	121.680 (0.000)
Agegroup					484.042 (0.000)					280.337 (0.000)					194.493 (0.000)
60-	4499	48.5%	41.2%	10.3%		2169	42.7%	44.5%	12.7%		2330	53.8%	38.1%	8.1%
70-	3247	33.4%	49.0%	17.6%		1597	26.9%	52.2%	20.9%		1650	39.7%	45.8%	14.5%
80-	1347	22.8%	48.6%	28.7%		729	17.1%	49.0%	33.9%		618	29.4%	48.1%	22.5%
Sex					173.921 (0.000)
Women	4495	32.9%	48.0%	19.1%
Men	4598	45.5%	42.2%	12.3%
Ethnicity					6.771 (0.034)					8.174 (0.017)					4.339 (0.114)
Han	8720	39.6%	44.8%	15.6%		4326	33.3%	47.6%	19.2%		4394	45.7%	42.1%	12.2%
Minority	373	33.0%	50.7%	16.4%		169	24.9%	58.6%	16.6%		204	39.7%	44.1%	16.2%
Residence place					15.795 (0.000)					16.181 (0.000)					5.293(0.071)
Urban	4656	41.2%	44.1%	14.7%		2377	35.5%	46.9%	17.7%		2279	47.1%	41.2%	11.7%
Rural	4437	37.3%	46.1%	16.6%		2118	30.1%	49.2%	20.6%		2319	43.9%	43.2%	12.9%
Education					122.004 (0.000)					108.206 (0.000)					19.583 (0.001)
Illiterate	6633	34.1%	52.5%	13.4%		2851	37.7%	46.5%	15.7%		3782	33.3%	53.0%	13.7%
Elementary/Junior high school	2273	27.8%	49.6%	22.6%		1604	24.3%	50.6%	25.1%		669	36.3%	47.1%	16.6%
high school and above	126	43.7%	45.2%	11.1%		3	66.7%	33.3%	0.0%		123	48.0%	41.5%	10.5%
Marital status					203.088 (0.000)					105.403 (0.000)					37.863 (0.000)
Married	6633	43.3%	43.3%	13.4%		2851	37.7%	46.5%	15.7%		3782	47.6%	40.9%	11.6%
Others^a	2399	28.2%	49.9%	22.0%		1607	24.4%	50.6%	25.0%		792	35.9%	48.4%	15.8%
Living alone	1480	28.9%	50.8%	20.3%	85.362 (0.000)	854	23.7%	52.6%	23.8%	44.470 (0.000)	626	36.1%	48.4%	15.5%	26.532 (0.000)
Frequency of exercise(per week)					109.592 (0.000)					49.434 (0.000)					49.915 (0.000)
Never	3693	35.1%	45.0%	19.9%		1918	29.2%	47.4%	23.4%		1775	41.4%	42.4%	16.2%
1-2 times	1564	40.1%	46.1%	13.8%		809	34.7%	48.3%	16.9%		755	45.8%	43.7%	10.5%
3-5 times	1302	41.2%	45.4%	13.4%		635	35.0%	48.7%	16.4%		667	47.1%	42.3%	10.6%
≥6 times	2523	44.0%	44.4%	11.6%		1125	36.9%	48.4%	14.7%		1398	49.6%	41.2%	9.2%
Consumption health supplements					16.749 (0.002)					3.907 (0.419)					11.491 (0.022)
Never	6995	40.3%	44.3%	15.5%		3374	33.5%	47.4%	19.1%		3621	46.6%	41.3%	12.1%
Occasionally	1534	37.0%	47.8%	15.3%		830	31.9%	49.9%	18.2%		704	42.9%	45.3%	11.8%
Frequently	538	33.5%	47.6%	19.0%		282	29.1%	49.6%	21.3%		256	38.3%	45.3%	16.4%
Co-morbidities					4834.605 (0.000)					2423.557 (0.000)					2334.340 (0.000)
0	1533	95.0%	4.8%	0.2%		608	94.4%	5.3%	0.3%		925	95.5%	4.5%	0.0%
1-3	6599	32.0%	57.0%	11.0%		3281	27.6%	59.9%	12.6%		3318	36.3%	54.2%	9.4%
≥4	950	0.0%	26.9%	73.1%		601	0.0%	26.6%	73.4%		349	0.0%	27.5%	72.5%
Have diseases in the preceding 2 weeks	1618	15.5%	49.8%	34.8%	754.925 (0.000)	964	13.7%	48.7%	37.7%	359.974 (0.000)	654	18.0%	51.4%	30.6%	348.557 (0.000)
Receipt of medical checkups in the past year	6117	38.7%	45.7%	15.6%	3.792 (0.150)	3072	33.3%	48.1%	18.6%	1.831 (0.400)	3045	44.1%	43.3%	12.6%	7.246 (0.027)
Times of hospitalization in the past year					582.164 (0.000)					279.175 (0.000)					302.815 (0.000)
0	6853	45.0%	42.7%	12.4%		3361	38.1%	46.3%	15.6%		3492	51.5%	39.2%	9.3%
1	1440	24.9%	54.2%	21.0%		707	20.7%	56.2%	23.2%		733	28.9%	52.3%	18.8%
≥2	718	13.2%	49.4%	37.3%		387	9.0%	48.3%	42.6%		331	18.1%	50.8%	31.1%
Having medical insurance	9021	39.3%	45.1%	15.6%	0.811 (0.667)	4456	33.0%	48.0%	19.0%	1.390 (0.499)	4565	45.5%	42.2%	12.3%	0.158 (0.924)
Reimbursement for medical expenses					73.479 (0.000)					40.487 (0.000)					41.561 (0.000)
Very convenient	4088	41.1%	44.7%	14.2%		2009	35.0%	48.1%	16.9%		2079	47.0%	41.4%	11.5%
Moderately convenient	2539	37.6%	45.6%	16.8%		1266	30.3%	48.3%	21.5%		1273	44.9%	43.0%	12.2%
Fair	786	31.9%	49.5%	18.6%		397	27.2%	52.4%	20.4%		389	36.8%	46.5%	16.7%
Moderately inconvenient	222	24.3%	48.6%	27.0%		109	18.3%	52.3%	29.4%		113	30.1%	45.1%	24.8%
Very inconvenient	94	23.4%	51.1%	25.5%		45	17.8%	48.9%	33.3%		49	28.6%	53.1%	18.4%
Normal ADL	8807	40.5%	46.1%	13.4%	1146.599 (0.000)	4339	34.1%	49.4%	16.6%	534.896 (0.000)	4468	46.8%	43.0%	10.2%	624.944 (0.000)
Having caregivers When sick	898	3.2%	31.8%	64.9%	87.903 (0.000)	516	2.9%	30.6%	66.5%	35.370 (0.000)	382	3.7%	33.5%	62.8%	55.324 (0.000)
Having income-generating work	917	64.2%	32.2%	3.6%	293.050 (0.000)	263	55.1%	38.8%	6.1%	71.106 (0.000)	654	67.9%	29.5%	2.6%	171.348 (0.000)
Having pension money	3092	49.9%	40.8%	9.2%	276.550 (0.000)	1428	43.3%	44.7%	12.0%	126.527 (0.000)	1664	55.6%	37.5%	6.9%	136.467 (0.000)
Having a house of their own	6572	42.5%	44.2%	13.3%	147.956 (0.000)	3033	36.7%	46.9%	16.4%	79.912 (0.000)	3539	47.4%	41.9%	10.7%	44.776 (0.000)
Economic status					954.416 (0.000)					449.852 (0.000)					512.881 (0.000)
Very rich	189	75.7%	20.1%	4.2%		80	73.8%	21.3%	5.0%		109	77.1%	19.3%	3.7%
Moderately rich	1543	56.3%	37.1%	6.5%		712	49.2%	43.0%	7.9%		831	62.5%	32.1%	5.4%
Basically enough	5389	41.1%	45.9%	13.0%		2709	34.3%	49.3%	16.4%		2680	48.0%	42.4%	9.6%
Moderately poor	1646	18.0%	52.7%	29.3%		832	14.3%	52.0%	33.7%		814	21.7%	53.4%	24.8%
Very poor	302	12.6%	44.7%	42.7%		152	11.8%	40.8%	47.4%		150	13.3%	48.7%	38.0%
Participation in public welfare activities	4874	43.9%	44.3%	11.9%	154.123 (0.000)	2258	37.2%	47.6%	15.1%	61.667 (0.000)	2616	49.6%	41.4%	9.0%	77.362 (0.000)
Participation in senior citizen associations	1595	47.1%	41.9%	11.0%	60.594 (0.000)	762	38.8%	46.6%	14.6%	19.711 (0.000)	833	54.6%	37.6%	7.8%	40.719 (0.000)
Willingness to help elderly people in need	7268	41.5%	44.5%	14.0%	110.520 (0.000)	3534	34.8%	47.8%	17.3%	42.256 (0.000)	3734	47.8%	41.3%	10.8%	63.525 (0.000)
Participation in recreational activities	8543	40.4%	45.1%	14.5%	160.874 (0.000)	4122	34.4%	48.2%	17.4%	100.350 (0.000)	4421	46.0%	42.3%	11.8%	32.656 (0.000)
Regular access to the Internet	682	53.8%	40.0%	6.2%	86.214 (0.000)	255	45.1%	48.6%	6.3%	35.335 (0.000)	427	59.0%	34.9%	6.1%	39.748 (0.000)
Participation in university /distance education for older adults	246	47.6%	43.5%	8.9%	11.766 (0.003)	118	44.1%	47.5%	8.5%	11.683 (0.003)	128	50.8%	39.8%	9.4%	1.876 (0.391)

Note: ^aOther marital status includes widowed, divorced or never married; ADL: Activity of daily living

Table 2 Changes in frailty status among the study participants according to sex and age

Characteristics	Robust to			Pre-frail to			Frail to			Total to
Characteristics	Robust (n=1939)	Pre-frail (n=1383)	Frail (n=250)	Robust (n=782)	Pre-frail (n=2259)	Frail (n=1057)	Robust (n=63)	Pre-frail (n=447)	Frail (n=913)	Robust (n=2784)	Pre-frail (n=4089)	Frail (n=2220)
Gender
Women	703(47.5)	638(43.1)	140(9.5)	338(15.7)	1190(55.2)	629(29.2)	30(3.5)	267(31.2)	560(65.3)	1071(23.8)	2095(46.6)	1329(29.6)
Men	1236(59.1)	745(35.6)	110(5.3)	444(22.9)	1069(55.1)	428(22.1)	33(5.8)	180(31.8)	353(62.4)	1713(37.3)	1994(43.4)	891(19.4)
X²	55.849			47.820			4.695			235.822
P-value	<0.001			<0.001			0.096			<0.001
Agegroup
60-	1281(58.7)	792(36.3)	108(5.0)	429(23.1)	1044(56.3)	381(20.6)	27(5.8)	167(36.0)	270(58.2)	1737(38.6)	2003(44.5)	759(16.9)
70-	528(48.7)	463(42.7)	93(8.6)	253(15.9)	906(57.0)	431(27.1)	20(3.5)	181(31.6)	372(64.9)	801(24.7)	1550(47.7)	896(27.6)
80-	130(42.3)	128(41.7)	49(16.0)	100(15.3)	309(47.2)	245(37.5)	16(4.1)	99(25.6)	271(70.2)	246(18.3)	536(39.8)	565(41.9)
X²	82.809			93.467			15.251			500.159
P-value	<0.001			<0.001			0.004			<0.001

Table 3 is available in the Supplementary Files section.

No competing interests reported.

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Two-Year Evolution of Frailty Status and Predictive Factors in Chinese Older Adults: A National Longitudinal Study

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