Factors associated with health-promoting lifestyles among community-dwelling older adults in Zigong, China: a cross-sectional study

Abstract

[Purpose]

The aging population in China faces significant challenges in maintaining health-promoting lifestyles, with disparities between life expectancy and healthy life expectancy. In this study, we aimed to assess health-promoting lifestyles and identify factors associated with them among community-dwelling older adults in Zigong, China.

[Methods]

A cross-sectional study was conducted with 768 participants aged 60 years and older, selected via multistage stratified random sampling. Standardized instruments, including the Health-Promoting Lifestyle Profile II, the Health Literacy Scale-Short Form, and the General Self-Efficacy Scale, were used to assess health-promoting behaviors, health literacy, and self-efficacy. Statistical analyses included descriptive statistics and stepwise regression analyses.

[Results]

Participants demonstrated moderate levels of health-promoting lifestyles, with physical activity scoring the lowest among all domains. Policy awareness, health literacy, self-efficacy, and education level were notably associated with health-promoting lifestyles, collectively explaining 71.6 % of the variance.

[Conclusion]

The findings underscored the associations of policy awareness and psychological factors with healthy aging. Targeted interventions to enhance health literacy and self-efficacy, particularly among socioeconomically disadvantaged older adults, are recommended.

INTRODUCTION

The global population is rapidly aging, with the number of people aged 65 years and older reaching 761 million in 2021 and projected to increase to 1.6 billion by 2050 [1]. China mirrors this trend, with 280 million people aged 60 years and older by the end of 2023, accounting for 19.8% of the total population [2]. By 2050, this proportion is expected to increase to 38.81% [3]. This demographic shift is driven by increased life expectancy resulting from improvements in healthcare and education, as well as declining fertility rates. However, healthy life expectancy has not kept pace. The World Health Organization (WHO) reports that while global life expectancy increased from 66.8 years in 2000 to 73.3 years in 2019, healthy life expectancy increased only from 58.3 to 63.7 years, reflecting a widening gap between longevity and healthy living [4]. In China, the average life expectancy is 78.2 years, whereas healthy life expectancy is only 68.7 years, highlighting the challenge of longer life expectancy accompanied by illness and reduced quality of life [5,6].

Owing to physiological, psychological, and social changes, older adults are particularly vulnerable to health problems. Chronic non-communicable diseases are the leading causes of death and disability among older adults, with more than 78% affected by at least one chronic condition [7,8]. Age-related physical decline also results in impairments such as arthritis, vision and hearing loss, and mobility limitations [9]. Mental health concerns are also prevalent: 34.9% of Chinese older adults experience depressive symptoms, with the prevalence increasing to 38.6% among empty-nest older adults [10,11]. Unhealthy lifestyles are major contributors to these health problems. The WHO estimates that 53% of deaths and over 60% of poor quality of life are attributable to unhealthy behaviors [12]. Adopting a health-promoting lifestyle can delay the onset of complications and improve well-being [13,14]. Among health-promoting behaviors, physical activity is particularly effective in reducing the risk of chronic conditions, improving balance, promoting gut health, and supporting mental well-being [15-18]. However, physical activity consistently receives the lowest scores among lifestyle dimensions in older adults, mainly because of traditional beliefs, low health literacy and self-efficacy, declining physical function, and a lack of professional exercise guidance [19-22].

To address these challenges, the WHO Global Strategy for the Health of Older People emphasizes physical activity, and countries like Germany, Japan, and Australia have implemented policies integrating diet, exercise, and healthcare [23]. In China, the “Healthy China 2030” plan advocates combining physical activity with medical care, and in 2021, the country introduced the “integration of physical and health” model, which focuses on prevention, health promotion, and intervention across the life course [24,25]. Subsequently, Sichuan Province issued specific guidelines to improve older adults’ health through integrated development [26].

Despite these policy efforts, the relationships among health literacy, self-efficacy, policy awareness, and health-promoting lifestyles in older adults require further examination in specific local contexts. The inclusion of policy awareness is theoretically grounded in the Knowledge-Attitude-Practice (KAP) model and the Health Belief Model [27,28]. According to the KAP model, policy awareness represents the knowledge component, which is a prerequisite for attitude change and behavioral adoption. The Health Belief Model further suggests that knowledge of health resources and policy support can enhance perceived cues to action, thereby increasing the likelihood of engaging in health-promoting behaviors. Existing evidence has primarily focused on systemic perspectives or healthcare providers’ views [29]. However, empirical research that systematically quantifies health-promoting lifestyles and examines the explanatory roles of policy awareness, health literacy, and self-efficacy among older adults in rapidly aging urban communities in China remains limited. Furthermore, most previous studies in China have been conducted in eastern metropolitan areas (e.g., Shanghai and Beijing), whereas the present study was conducted in Zigong, a typical medium-sized city in western China that faces distinct aging challenges and has less developed community health resources. This context-specific evidence is essential for translating national policies into tailored and effective local interventions.

Zigong City, located in Sichuan Province, has a population of 2.489 million, including 680,500 people aged 60 years and older, accounting for 27.3% of the total population. This proportion ranks fourth among Chinese cities in terms of population aging [30]. Therefore, Zigong provides a valuable case study for addressing the aforementioned research gap. In response to population aging, Zigong has implemented a series of policies, including the “Healthy Zigong Action” and the “National Fitness Implementation Plan (2021-2025)”, to promote physical activity and healthy aging [31,32]. In this cross-sectional study, we investigated the current status of, and factors associated with, health-promoting lifestyles among community-dwelling older adults in Zigong, with a particular focus on physical activity. The findings are intended to provide localized, evidence-based insights into health-promoting behaviors in rapidly aging communities and to inform the development of municipal healthy aging strategies.

METHODS

Study Population and Sample Size

Participants were recruited between April 12, 2025, and June 29, 2025. Prior to enrollment, all participants provided written informed consent. This study employed a multistage stratified random sampling method to recruit community-dwelling older adults from Zigong City, Sichuan Province, China. The sampling process was as follows. Zigong consists of four administrative districts (Ziliujing, Gongjing, Da’an, and Yantan), which served as the initial strata. Two districts were selected using a random number table. Two subdistricts were then randomly chosen from each selected district. Subsequently, two communities were randomly selected from each subdistrict, resulting in eight communities as the final sampling sites. Within each selected community, potential participants who met the inclusion criteria were identified using official community registries. Eligible individuals were then randomly selected from these registries using computer-generated random numbers and invited to participate until the predetermined sample size for each community was reached. To enhance representativeness, the overall sample size was proportionally allocated across the eight communities according to the size of the eligible older adult population. The total population of individuals aged 60 years and older in the study area was approximately 348,000. The minimum sample size was determined using the formula for cross-sectional studies [33], assuming a 95% confidence interval (CI) and a 5% margin of error, yielding the required sample size of 384 participants. To account for potential nonresponse, incomplete data, and to improve the precision of the estimates, the sample size was doubled, resulting in a final sample size of 768 participants. The inclusion criteria were as follows: 1) aged ≥ 60 years and residing in the community for at least one year; 2) willingness to participate after receiving the study objectives; and 3) cognitive ability sufficient to complete the questionnaire, as determined by normal communication during the initial interview and the absence of apparent barriers to understanding the questionnaire.

Ethical Issues

This study was approved by the Ethics Committee of Mahasarakham University, Thailand (Approval No. 187-792/2025; approved on March 5, 2025; valid until March 4, 2026). Before the interviews, all participants were informed verbally about the study objectives and procedures. Participants were assured that their data would be kept confidential and used solely for research purposes. Participation was voluntary, and written informed consent was obtained from each participant before enrollment in the study.

Study Tools

Based on a review of the literature and consultation with relevant experts, the final questionnaire was developed and consisted of the following components:

Demographic characteristics: Data were collected on participants’ sex, age, educational level, monthly income, marital status, smoking status, alcohol consumption, presence of chronic diseases, and awareness of the physical-health integration policy.

Awareness of the physical-health integration policy: This variable was assessed using a single-item question: “Have you heard of or know about the national policy on ‘physical-health integration’, which aims to combine physical activity and health services to promote healthy aging?” Response options were “Yes” (1) and “No” (0). Similar single-item measures have been used in previous studies of health policy awareness research among older adults in China. Because this was a single-item measure, internal consistency reliability was not applicable.

Health-Promoting Lifestyle Profile II (HPLP-II): Healthpromoting lifestyles were assessed using the Chinese version of the HPLP-II, revised by Cao et al. (2016) [34]. The total score ranges from 52 to 208 and is categorized into four levels: poor (52-90), moderate (91-129), good (130-168), and excellent (169-208). In the present study, the Cronbach’s α coefficient was 0.78.

12-item Short-Form Health Literacy Questionnaire (HLS-SF12): Health literacy was assessed using the HLSSF12, which comprises 12 items rated on a 4-point Likert scale (1 = very difficult, 2 = difficult, 3 = easy, and 4 = very easy). The standardized health literacy index (range, 0-50; higher scores indicate better health literacy) was calculated using the following formula: index = (mean - 1) * (50/3), where 1 represents the minimum possible mean, 3 represents the range of the mean, and 50 is the predefined maximum value [35]. In the present study, the Cronbach’s α coefficient was 0.83.

General Self-Efficacy Scale (GSES): General self-efficacy was assessed using the Chinese version of the GSES, revised by Zhang et al. (1995) [36]. The scale consists of 10 items that assess an individual’s confidence in coping with setbacks and challenges. Responses are rated on a 4-point Likert scale, with higher scores indicating greater general self-efficacy. In the present study, the Cronbach’s α coefficient was 0.81.

Reliability and adaptation: All instruments used established Chinese versions that had undergone translation, cultural adaptation, and validation in the target population. In the current study, the internal consistency (Cronbach’s α) of the scales ranged from 0.78 to 0.83, indicating acceptable reliability for group-level comparisons in social and behavioral research. A pilot test was conducted with 30 older adults from a community that was not included in the main study to evaluate the clarity, relevance, and completion time of the questionnaire. Minor wording adjustments were made based on participant feedback. Pilot participants were excluded from the main analysis.

Statistical Analysis

The completed questionnaires were processed using a standardized data management protocol. Raw data were independently double-entered into Microsoft Excel by two researchers to ensure accuracy before being imported into SPSS version 18.0 for statistical analysis. Demographic characteristics were summarized using descriptive statistics, and scale scores were presented as the mean ± standard deviation (SD). Spearman correlation analysis was performed to examine the relationships among HLS-SF12 scores, GSES scores, and both the domain-specific and total HPLPII scores.

Stepwise multiple linear regression analysis was performed to identify factors associated with the total HPLP-II score. Variables that showed statistically significant differences in the univariate analysis (educational level, monthly income, marital status, presence of chronic diseases, and awareness of the physical-health integration policy), together with the HLS-12 total score and GSES total score, were entered as independent variables. The stepwise method (entry criterion, P < 0.05; removal criterion, P > 0.10) was used as an exploratory approach to identify the most parsimonious set of predictors because no previous study has examined this specific combination of variables, including policy awareness, health literacy, and self-efficacy, in this population. Before the regression analysis, multicollinearity was assessed using the variance inflation factor (VIF) to ensure that correlations among the independent variables did not distort the model estimates. A relatively high R² was anticipated given that the model incorporates multiple established correlates of health-promoting lifestyles (health literacy, self-efficacy) alongside a novel policy awareness variable. All statistical tests employed a significance threshold of α = 0.05, with P < 0.05 considered statistically significant.

Figure 1. Flow diagram of participant recruitment and sampling.

RESULTS

Sample Characteristics

A total of 768 older adults were included in this study, comprising 335 men (43.62%) and 433 women (56.38%). Participants ranged in age from 60 to 95 years, with a mean age of 71.42 years (SD = 7.606). Only 19.4% had attained a high school education or higher. Most participants (89.06%) reported a monthly income ≤ 5,000 CNY. Chronic diseases were common, with 483 participants (62.89%) reporting one or more chronic conditions. Regarding health policy awareness, 52.86% of participants were unaware of China’s physical-health integration policy.

Scores on the Core Study Scales

Based on the HPLP-II scoring criteria, participants demonstrated a moderate level of health-promoting lifestyle (total score: 128.69 ± 21.04). For the six HPLP-II subscales, standardized scores were calculated to account for the different numbers of items in each dimension. The analysis showed that Nutrition, Health Responsibility, and Interpersonal Relations were the three highest-scoring dimensions, whereas Spiritual Growth and Physical Activity ranked second lowest and lowest, respectively.

Participants also showed moderate levels of health literacy (HLS-12: 34.70 ± 3.615) and self-efficacy (GSES: 30.08 ± 4.401). The complete results are presented in Table 1.

Table 1.

Scores of various scales for the community-dwelling older adults (n = 768)

Scale	Total score	Score	Standardized score	Ranking
Nutrition	36	24.57 (± 7.52)	68.25	1
Health responsibility	36	23.09 (± 6.31)	64.14	2
Interpersonal relationships	36	22.52 (± 3.20)	62.56	3
Stress management	32	19.43 (± 2.12)	60.72	4
Spiritual growth	36	21.79 (± 2.35)	60.53	5
Physical activity	32	17.30 (± 4.18)	54.06	6
HPLP-II	208	128.69 (± 21.04)	61.87	—
HLS-12	48	34.70 (± 3.615)	—	—
GSES	40	30.08 (± 4.401)	—	—

Note: Standardized score = (Average score / Total score) × 100;“-” indicates non-participation in ranking.

Health-Promoting Lifestyles According to Participant Characteristics

The univariate analyses showed statistically significant differences (P < 0.05) in health-promoting lifestyle scores according to education level, monthly income, marital status, presence of chronic diseases, and awareness of the physical-health integration policy. Specifically, higher education levels were associated with higher health-promoting lifestyle scores. Participants with monthly incomes below 3,000 CNY had the lowest scores. Married participants had significantly higher scores than unmarried participants. Those without chronic diseases had higher lifestyle scores than those with chronic diseases, and participants who were aware of China’s physical-health integration policy scored significantly higher than those who were unaware. Detailed results are presented in Table 2.

Table 2.

Comparison of health-promoting lifestyles among older adults with different demographic characteristics (n = 768)

Variable	n	Total score	t/F value	P-value
Age
60–69 years	343	130.02 (± 20.211)	1.763	0.153
70–79 years	305	128.25 (± 21.717)
80–89 years	107	126.93 (± 21.216)
90 years and above	13	118.54 (± 22.861)
Mean = 71.42, SD = 7.606, Min = 60, Max = 95
Gender
Male	335	128.54 (± 21.097)	-0.178	0.858
Female	433	128.81 (± 21.012)
Educational level
Primary education	218	120.34 (± 20.025)	28.742	< 0.001***
Secondary education	401	130.71 (± 20.689)
Higher education	149	135.49 (± 19.700)
Monthly income
0–3,000 CNY	357	127.54 (± 20.841)	3.451	0.016*
3,000–5,000 CNY	327	128.4 (± 21.369)
5,000–10,000 CNY	72	133.29 (± 20.028)
Over 10,000 CNY	12	143.17 (± 16.214)
Marital status
Married	612	129.71 (± 20.667)	2.666	0.008***
Not currently married (including divorced, widowed, etc.)	156	124.7 (± 22.042)
Smoking status
Yes	275	127.11 (± 21.466)	-1.555	0.120
No	493	129.57 (± 20.762)
Alcohol consumption
Yes	283	127.97 (± 21.037)	-0.728	0.467
No	485	129.11 (± 21.045)
Presence of chronic diseases
Yes	483	127.33 (± 21.483)	-2.336	0.020*
No	285	130.99 (± 20.082)
Awareness of the physical-health integration policy
Yes	362	145.8 (± 8.490)	33.232	< 0.001***
No	406	113.44 (± 16.702)

Note: CNY = Chinese Yuan,

^*P < 0.05,

^**P < 0.01,

^***P < 0.001.

Stepwise Multiple Linear Regression Analysis of Factors Associated with Health-Promoting Lifestyles among Older Adults

Using the HPLP-II total score as the dependent variable, a stepwise multiple linear regression analysis was performed. Independent variables included participant characteristics that were significantly associated with HPLP-II scores in the univariate analyses (education level, monthly income, marital status, presence of chronic diseases, and awareness of the physical-health integration policy), as well as the HLS-12 total score and GSES total score. The coding methods are detailed in Table 3.

Table 3.

Assignment of variables in multiple linear regression

Independent variable	Assignment method
Education level	Primary education = 0; Secondary education = 1; Higher education = 2
Monthly income	0–3,000 CNY = 0; 3,000–5,000 CNY = 1; 5,000–10,000 CNY = 2; over 10,000 CNY = 3
Marital status	Married = 0; Not currently married = 1
Presence of chronic diseases	Yes = 0; No = 1
Awareness of the physical-health integration policy	Yes = 0; No = 1

The final regression model (Table 4) identified four significant predictors. The model explained 71.6% of the variance in the total HPLP-II score (Adjusted R² = 0.716), and the overall regression model was statistically significant (F = 484.837, P < 0.001). Diagnostic tests supported the adequacy of the model: the Durbin-Watson statistic was 1.718, indicating no substantial autocorrelation; all VIF values were below 5, suggesting the absence of multicollinearity; and the residuals met the assumptions of normality and homoscedasticity.

Table 4.

Stepwise regression analysis of factors influencing health-promoting lifestyles among older adults

Variable	B	Std. Error	β	95% CI for B		t	P
				Lower Bound	Upper Bound
Awareness of the physical-health integration policy	22.674	0.967	0.538	20.776	24.571	23.456	< 0.001**
HLS-12	1.597	0.129	0.274	1.344	1.85	12.384	< 0.001**
GSES	1.009	0.107	0.211	0.799	1.218	9.447	< 0.001**
Educational level	1.926	0.607	0.063	0.735	3.117	3.174	0.002**

Note: F = 484.837, R² = 0.718, Adjusted R² = 0.716, P < 0.001, DW = 1.718,

^**P < 0.01,

CI = Confidence Interval.

Among the participant characteristics, awareness of the physical-health integration policy (β = 0.538, 95% CI: 20.78 to 24.57, P < 0.001) and education level (β = 0.063, 95% CI: 0.74 to 3.12, P = 0.002) were positively associated with the HPLP-II total score. Health literacy (HLS-12 total score: β = 0.274, 95% CI: 1.34 to 1.85, P < 0.001) and general self-efficacy (GSES total score: β = 0.211, 95% CI: 0.80 to 1.22, P < 0.001) were also significant influencing factors. The results revealed that the predictive strength of these variables for the HPLP-II total score followed the order awareness of the physical-health integration policy > HLS-12 total score > GSES total score > education level.

DISCUSSION

This cross-sectional study examined factors associated with health-promoting lifestyles among community-dwelling older adults in Zigong, China. The findings revealed that physical activity was the lowest-scoring dimension of the HPLP-II, a pattern consistent with findings reported in many countries. A comparison with studies from multiple countries suggested that greater awareness of relevant policies and higher health literacy were associated with higher levels of physical activity and more health-promoting lifestyles.

This study revealed that insufficient physical activity was the most prominent weakness in the health-promoting lifestyles of community-dwelling older adults in Zigong, China, a pattern consistent with findings reported in many nations. Based on a comparative analysis of research from multiple countries, we found that improving older adults’ awareness of relevant policies and improving their health literacy may be effective strategies for promoting physical activity and overall health-promoting lifestyles.

First, policy awareness was strongly associated with health-promoting lifestyles among older adults. This finding is consistent with recommendations from a study conducted in Ghana, which identified policy interventions as a priority for promoting physical activity among older adults. The authors pointed out that policy-, financial assistance-, family-, and community-level interventions are crucial for promoting and sustaining physical activity among older adults [37]. However, our findings are based on cross-sectional data from a single city in western China. Therefore, these international comparisons are intended to provide contextual background rather than direct evidence of causality or generalizability. When developing and implementing healthy aging policies in China, efforts should extend beyond high-level policy design to include targeted dissemination and interpretation for older adults and their families.

Second, health literacy was positively associated with behavioral outcomes. Evidence from Switzerland provides insight into the potential mechanisms underlying this association. Higher health literacy is associated with greater engagement in moderate and vigorous physical activity, and physical activity has been shown to partially mediate the protective effect of health literacy on mild cognitive impairment [38]. However, although these studies suggest potential mechanisms, our cross-sectional design did not allow us to examine mediation pathways. The associations observed between health literacy and health-promoting lifestyles in our sample warrant further investigation using longitudinal study designs. This conclusion aligns with research based on the extended social cognitive theory, which identifies health literacy as an important determinant of physical activity among older adults [39].

Third, the finding that physical activity was the lowest-scoring HPLP-II dimension (mean = 17.30 ± 4.18; standardized score = 54.06) warrants particular attention. This result is consistent with those of previous studies involving older Chinese adults [19-20]. Further research is needed to explore the specific barriers to physical activity in this population, including environmental factors (e.g., neighborhood walkability and the availability of exercise facilities), the implementation of relevant policies, and cultural attitudes toward physical activity.

However, interventions aimed at enhancing policy awareness and health literacy must also address structural barriers to implementation. A qualitative study from the UK noted that implementation barriers, including complex organizational networks and cross-sectoral conflicts, can hinder the scale-up of health interventions for older adults [40]. These findings suggest that the success of community-based initiatives to improve policy awareness and health literacy depends on clear implementation pathways and simplified participation processes.

Furthermore, specific barriers that affect older adults’ ability to translate awareness into action warrant particular attention. Research from Ethiopia indicates that factors such as low education levels and unemployment are significantly associated with physical inactivity [41]. A study of low-income older Black Americans found that the combination of high sedentary behavior and low leisure-time physical activity was associated with the highest mortality risk [42]. These findings suggest that older adults with lower socioeconomic status may face more difficulties in changing their behaviors. Therefore, targeted interventions could incorporate economic and social support, such as providing free or low-cost community exercise facilities [43] and organizing peer support groups [44], to reduce physical and economic barriers to participation.

Simultaneously, mental health and social support are important facilitators of health-promoting lifestyles. A systematic review indicated that negative perceptions of mental health services, stigma, and cost are major barriers to older adults seeking professional help [45]. Therefore, while encouraging physical activity and improving health literacy, it is also essential to foster a positive, stigma-free community environment that supports mental health and facilitates access to psychological support.

CONCLUSION

This cross-sectional study identified several factors associated with health-promoting lifestyles among 768 community-dwelling older adults in Zigong City, China. The findings suggest that both policy awareness and intrinsic psychological factors were associated with health-promoting lifestyles in this population. However, because of the cross-sectional design, causal relationships cannot be inferred.

To translate these insights into actionable strategies, several recommendations may be considered. For policymakers and public health planners, integrating policy education components into existing community health programs—for example, by integrating information on the physical-health integration policy into routine exercise sessions or health education workshops—may help support healthy aging. For community practitioners, developing tailored interventions that simultaneously address health literacy, self-efficacy, and policy awareness, with a particular focus on older adults with lower educational attainment, may enhance program effectiveness. Furthermore, creating supportive community environments, such as ensuring access to exercise facilities and organizing policy-informed health promotion campaigns, may facilitate the adoption of health-promoting behaviors.

Future research should prioritize: (1) longitudinal cohort studies to examine the temporal relationship between policy awareness, health literacy, self-efficacy, and subsequent changes in health-promoting lifestyles; (2) cluster-randomized controlled trials to evaluate whether community-based interventions targeting policy awareness can improve health-promoting behaviors, particularly physical activity; (3) qualitative studies to explore contextual barriers to physical activity among older adults in western Chinese cities; and (4) comparative studies across different regions of China to examine whether these associations vary by level of urbanization and healthcare resource availability.

Strengths and Limitations

The primary strengths of this study include its relatively large community-based sample, which enhanced the representativeness of the findings, and the use of well-validated measurement tools (HPLP-II, HSL-SF12, and GSES) to ensure reliability. By integrating both individual psychological factors and policy awareness, this study provides a more comprehensive perspective on the determinants of health-promoting lifestyles among older adults, thereby contributing to a better understanding of health behaviors in rapidly aging societies. These findings may help inform the development of targeted public health interventions.

However, this study has several limitations. First, the cross-sectional design precludes causal inference, and the direction of the observed associations cannot be determined. Second, the use of self-reported measures may have introduced recall bias, social desirability bias, and common method bias. The high explanatory power of the model (adjusted R² = 0.716) may partly reflect common method bias, as all main variables were self-reported, and conceptual overlap among health literacy, self-efficacy, and health-promoting lifestyles may have inflated shared variance. Future studies should incorporate objective measures or multitrait, multi-method designs to address these limitations. Third, the use of stepwise regression may have produced sample-dependent results. Future studies should validate our findings using theory-driven approaches or cross-validation techniques. Fourth, although a multistage sampling method was used, selection bias may not have been completely eliminated. In addition, because the study included only an urban population from a single city in western China, the generalizability of the findings to other settings may be limited. Fifth, cognitive status was assessed solely through communication ability rather than with a standardized instrument (e.g., MMSE); therefore, some participants with mild cognitive impairment may have been inadvertently included. Finally, the analysis did not account for important contextual factors (e.g., physical environment, healthcare accessibility, and family/social support). Future longitudinal or intervention studies with more diverse and nationally representative samples are warranted.