Participants were recruited from the latest provincial health surveillance of Hubei China (HSHC) [43]. The HSHC is an ongoing consecutive cross-sectional surveillance that collects various health indicators on a representative sample of Chinese residents living in the Hubei province of China every 5 years [43]. A self-weighted stratified cluster random sampling approach was applied in the HSHC, where participants were randomly selected from 17 municipalities of Hubei province, stratified by communities, towns (villages), and districts (counties) for each municipality. In this study, eligible participants were required to meet the inclusion criteria, including (1) age of 60-79 years, (2) adequate language skills (ie, reading and writing capabilities in Chinese), and (3) no restriction of physical mobility (eg, passed the Physical Activity Readiness Questionnaire [PAR-Q]). Participants excluded from this study were those outside the specified age range, those unable to read and comprehend Chinese, those failing the PAR-Q, and those diagnosed with cognitive or sleep disorders. A total of 32,080 participants were contacted, and 27,826 agreed to participate in the surveillance (86.7% response rate). After eligibility checks, 4953 eligible participants were invited to complete data collection.

Eligible participants were further invited to complete the study measures at a multi-function stadium, lasting approximately 30 minutes per person. To ensure assessment quality, for each municipality, the data collection was conducted by a trained health surveillance team, which consisted of 15-20 qualified assessors who passed a competency examination, according to consistent standard operating procedures. Data were collected from July 25, 2020 (3 months after the lockdown was withdrawn) to November 19, 2020.

This study followed the Declaration of the Helsinki World Medical Association [44] and the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement [45]. Ethics approval was obtained from the General Administration of Sport of China (CISS-2019-01-31) and Hubei Institute of Sport Science (HISS-2019-03-01). All participants who were interested in participating in the surveillance were asked to sign a written informed consent form before the study commencement.

Data analyses were performed using SPSS 28.0 (IBM Corp). We excluded 248 cases owing to missing demographic details (73 cases lacking age and gender information), movement behaviors (73 cases), and physical and mental health outcomes (248 cases without data on BMI, PBF, physical fitness, and 2 mental health indicators) and 143 cases owing to invalid or abnormal values in movement behaviors (122 cases) and health-related outcomes (76 cases; eg, BMI and PBF), particularly those cases with skewness and kurtosis absolute values beyond ±1.5 and z-scores exceeding the ±3 SD threshold [56]. Thus, data from 4562 participants were retained for the final analysis. Based on a retrospective power estimate, the final sample size of 4562 was adequate to detect an effect size (Cohen f²) of 0.01, with an α of .05 and a statistical power (1-β) of 0.8, in the regression model [35,41]. Odds ratios (ORs) of 1.68, 3.47, and 6.71 were considered to indicate a small, medium, and large effect size, respectively [57]. A statistical significance level of P<.05 (2-tailed) with 95% CI not covering 0 was used for all analyses.

Mean, SD, and percentage (%) have been used to present the descriptive characteristics of the study sample. Considering that the 24-hour movement guidelines propose different requirements for those aged 60-64 years and those aged ≥65 years, demographic characteristics were also reported for each subgroup. For the main analyses, generalized linear mixed models were used to examine the correlates of meeting 24-hour movement guidelines and assess the associations of guideline adherence with physical and mental health outcomes.

Finally, sensitivity analyses were performed to examine the robustness of the study findings and alternative explanations. All the association analyses were reconducted with the exclusion of participants who were obese (BMI ≥28 kg/m²) or who had moderate to severe depressive symptoms (PHQ-9 score ≥10) as suggested by previous studies [58,59]. Additionally, e-values were computed for the primary outcomes to assess the potential bias from unmeasured and residual confounding factors [58-60]. E-values estimate the magnitude of unmeasured or residual confounders that would need to be present to nullify the established relationships between independent and dependent variables, despite adjustments for all identified covariates [58-60]. E-values exceeding 1 suggest that only confounders of significant magnitude could challenge the observed relationships, including a greater robustness of these results against the influence of unmeasured confounders [58-60].

Of 4953 participants, 4562 (retention rate of 92.1%) were included in the final data analysis (Figure 1). In addition, 69.2% (3157/4562) of participants were aged 65 years or older, and the mean age of the total sample was 67.68 (SD 5.03) years. Moreover, 55.8% (2544/4562) of participants were female and 53.0% (2417/4562) were living in urban areas. Participants with an education level of secondary school accounted for the largest proportion (2115/4562, 46.4%), while only 12.2% (555/4562) of participants had an education level of college or above. Furthermore, 86.9% (3964/4562) of participants were married, and 46.8% (2134/4562) reported a history of chronic diseases. Details of the study sample are presented in Table 1.

The rates of adhering to 0, 1, and 2 movement guidelines were 24.7% (1126/4562), 50.5% (2303/4562), and 23.0% (1050/4562), respectively. The proportion of participants meeting individual movement guidelines was 32.1% (1466/4562) for MVPA, 3.4% (155/4562) for SB, and 66.4% (3031/4562) for sleep. Prevalence rates of meeting a combination of 2 movement behaviors ranged from 1.8% (83/4562) to 23.3% (1063/4562), while only 1.8% (83/4562) of participants met all 3 movement guidelines (Figure 2).

Table 2 presents the correlates of meeting 24-hour movement guidelines in the study sample. Participants who were older and who were female had a comparatively poorer adherence to either individual movement guidelines or the combinations of 2 or 3 behaviors (all P<.001). The municipality economic status was positively associated with meeting all 3 movement guidelines. Participants living in urban areas were more likely to adhere to MVPA and sleep guidelines (all P<.001). A higher education level and no chronic diseases were associated with a higher adherence to MVPA, sleep, and MVPA+SB guidelines, while marital status was not associated with guideline adherence.

The associations between adherence to movement guidelines (individual and combination) and health-related outcomes are outlined in Tables 3 and 4. Adhering to either MVPA or sleep guidelines was associated with favorable physical and mental health outcomes (all P<.001), except 2 blood pressure indicators (P=.08-.57). Similar results were observed for adherence to SB guidelines, except a significant correlation with SBP (P=.02).

Adhering to both MVPA and SB guidelines was associated with greater health-related outcomes (all P<.01), except DBP (P=.88). Adhering to MVPA+sleep or SB+sleep guidelines was associated with better performance regarding physical health (all P<.05), except 2 blood pressure indicators (P=.09-.78). Adhering to MVPA+sleep guidelines was associated with lower levels of both depressive symptoms and loneliness (both P<.001), while adhering to SB+sleep guidelines was not significantly associated with loneliness (P=.18).

Relative to not meeting any movement guidelines, adherence to 1, 2, or 3 movement guidelines was associated with lower values of BMI, waist circumference, WHR, and PBF, alongside higher levels of physical fitness among participants (all P<.001). However, this association did not extend to blood pressure (both SBP and DBP; P=.17-.89). For mental health outcomes, adherence to 1, 2, or 3 movement guidelines was significantly and inversely associated with both depressive symptoms and loneliness (all P<.001) compared with not meeting any guidelines (Table 4). Dose-response associations were identified between the number of adhered guidelines and health-related outcomes (all P<.01), except blood pressure (P=.18-.64).

The outcomes of the sensitivity analyses, which excluded participants with obesity and those with moderate to severe depressive symptoms, aligned with the primary findings, except for 7 discrepancies (Multimedia Appendix 1). In particular, the association between adherence to SB guidelines and loneliness (P=.06) was not significant in the sensitivity analysis. Similarly, adhering to sleep guidelines was not significantly associated with BMI (P=.49), waist circumference (P=.78), or PBF (P=.42). Furthermore, the correlation between adherence to MVPA+SB guidelines and WHR (P=.10) and loneliness (P=.07) was not statistically significant among participants, excluding those with obesity and those with moderate to severe depressive symptoms. The e-values showed that the main findings of the association examination are unlikely to be nullified by unmeasured confounders (all e-values were >1) (Multimedia Appendix 1).

This study provides timely evidence on the prevalence and correlates of adherence to 24-hour movement guidelines as well as its associations with physical and mental health outcomes among older adults. The results showed that only 1.8% (83/4562) of participants met all 3 movement guidelines, while 32.1% (1466/4562), 3.4% (155/4562), and 66.4% (3031/4562) met individual behavioral guidelines for MVPA, SB, and sleep, respectively (aim 1). Participants who were older, were female, and lived in municipalities with a lower economic status were less likely to comply with all 3 movement guidelines, while those who lived in urban areas, had higher education levels, and had no chronic diseases showed a higher adherence to specific individual movement guidelines or combinations of movement guidelines (aim 2). With regard to aim 3, adherence to either individual movement guidelines or combinations of movement guidelines was associated with a higher level of physical fitness and lower levels of BMI, waist circumference, WHR, PBF, depressive symptoms, and loneliness. This did not extend to the relationship between adherence to SB+sleep guidelines and loneliness. Furthermore, adherence to movement guidelines did not correlate with 2 blood pressure indicators, except when adhering to SB or MVPA+SB guidelines.

Regarding guideline adherence (aim 1), the percentage of Chinese older adults meeting all 3 movement guidelines was lower than that of other age groups as reported in previous national surveys (eg, Chinese children and adolescents: 2.1%; Chinese caregivers of preschoolers: 15.1%; Canadian adults: 7.1%; and Thailand adults: 21.3%) [36,38,41,42]. This is consistent with previous studies, which indicated a poorer adherence to 24-hour movement guidelines among older adults compared with other age groups [30,37,38]. Age-related decreases in PA and sleep and increases in sedentary time have been demonstrated in previous studies [61,62]. This is not surprising as older adults generally experience physical and cognitive hypofunction with age, coupled with worries of life transition, diseases, and death [63], which, to some extent, may weaken the antecedents of behavioral initiation (eg, perceived capability and motivation), eventually leading to unhealthy patterns of movement behaviors (eg, physical inactivity, prolonged SB, and insufficient sleep) [64]. In addition to this explanation, the time frame of data collection should be considered. The data in our study were gathered during the COVID-19 period, and at that time, local preventive measures were still being undertaken (eg, mandatory quarantine, physical distancing, and emergent closure of some public areas). This might have contributed to the low adherence rate of meeting 24-hour movement guidelines among Chinese older adults [65,66]. Overall, the above findings underline the long-term requirement of effective behavioral promotion strategies and policy making. In addition, as there is a lack of evidence on the adherence of older adults to 24-hour movement guidelines, we could not make a comparison with previous studies using the same age group, which implies that more surveillance studies on this topic are warranted.

Regarding the correlates of movement guideline adherence among Chinese older adults (aim 2), we found that participants who were female and who were older were less likely to comply with movement guidelines, which is in accordance with the findings of previous studies involving children and adults [35-38]. Interestingly, we also found a lower adherence to all 3 movement guidelines among participants who lived in municipalities ranking <9th in terms of GDP. This might reflect the fact that compared with those who lived in cities with a lower economic status and lower modernization, Chinese older adults who lived in cities with a higher GDP had a healthy lifestyle. For other covariates, some were only associated with specific guideline adherence (eg, a higher adherence to MVPA and sleep was found among participants living in urban areas, yet residence was not associated with SB guideline adherence), where mixed results were also demonstrated in previous studies with children and adults [30,35,42,67]. Overall, the above findings imply that future health promotion programs and policy making should take age, gender, and municipality economic status differences into account. For example, more effective strategies for motivating female individuals and older age groups are needed (eg, designing programs based on participants’ preferences, tailoring the intervention content based on preidentified psychosocial determinants targeting these samples, and introducing a more supportive policy for these economically disadvantaged municipalities). In addition, more research on examining the role of other demographic factors is warranted.

Regarding the association between movement guideline adherence and health-related outcomes among Chinese older adults (aim 3), we found that adherence to movement guidelines, individually or in combination, was associated with greater physical health indicators, including BMI, PBF, waist circumference, WHR, and physical fitness. These findings are consistent with previous findings from children and adult populations [37-42], suggesting the broader applicability of these guidelines. Notably, our research showed that only adherence to SB or MVPA+SB guidelines was associated with a lower systolic pressure, contrasting with the lack of an association between adherence to other guidelines and blood pressure indicators. The limited evidence on the relationship between 24-hour movement guideline adherence and the health of older adults constrains a comprehensive comparison with existing studies. Notably, current research on movement behaviors and their relationships with blood pressure indicators (eg, using a compositional data analysis) has presented mixed findings among older adults [27,68,69]. This discrepancy may be attributed to different types of PAs (eg, muscle strength training and aerobic exercise) and dietary factors (eg, sodium intake) [70,71]. In relation to blood pressure among older adults, the quality of PA (eg, specific modality) and dietary patterns may serve as more sensitive and significant correlates than the quantity of PA (eg, minutes per week). Moreover, age-related physiological changes may reduce the sensitivity of blood pressure to movement behaviors [72], and the prevalent use of antihypertensive medications within the elderly population could also obscure the potential benefits of adhering to movement guidelines (eg, achieving the recommended levels of MVPA) [73]. Nevertheless, these assumptions were not explored in our study, highlighting the need for systematic investigations in future research.

For mental health outcomes, we found that adherence to movement guidelines was associated with lower levels of depressive symptoms and loneliness, except adherence to SB+sleep guidelines, which showed no significant relationship with loneliness. Engaging in a variety of physical activities, especially peer-based or group-oriented ones, significantly benefits the emotional and social well-being of elderly people [74]. The influence of SB and sleep duration on loneliness among older adults has not been convincingly demonstrated by prior research [27,75,76]. It is important to recognize that not all sedentary activities exert the same effect on mental well-being. Engaging in socially interactive sedentary activities (eg, internet-based social activities and playing chess with friends) may actually contribute to reducing depressive symptoms and feelings of loneliness [76,77]. The findings of our study support the connection between adherence to movement guidelines and mental health outcomes among older adults. However, evaluating activity solely by its duration does not provide a comprehensive understanding of its effect on mental health. Future research is needed to investigate the specific mechanisms by which movement behaviors contribute to the improvement of mental health, thereby informing the development of more effective health promotion initiatives.

Finally, the results of the sensitivity analyses corroborate the robustness of our data analyses, with certain exceptions noted in the associations between adherence to SB guidelines and loneliness; adherence to sleep guidelines and BMI, waist circumference, and PBF; adherence to MVPA+SB guidelines and WHR; and adherence to MVPA+sleep guidelines and loneliness. These exceptions suggest that the weight status and the severity of depressive symptoms might affect the solidity of our findings, warranting further investigations in future studies. Additionally, our e-value analyses consistently yielded values exceeding 1, affirming the resilience of our findings against the influence of unmeasured confounders and therefore strengthening the stability of our results. These findings validate the integrity of the associations identified in our study. It is worth noting that our observations also reveal that lower adherence to movement guidelines corresponds with reduced e-values, suggesting a comparatively increased susceptibility to unobserved confounders. This discrepancy indicates the importance of cautious interpretation and necessitates further exploration of potential unmeasured confounders, such as social and environmental factors, to enhance our comprehension of the intricate relationship between adherence to 24-hour movement guidelines and health-related outcomes.

Several limitations should be noted. First, although our study applied stratified random sampling with a large sample size, the study findings to some extent could only reflect the behavioral profiles of Chinese older adults living in the central region of China, and the generalizability to other regions (eg, the north and south of China) and different cultural contexts should be further examined. Second, the causal relationship between movement behaviors and health outcomes could not be well supported by the cross-sectional design. A further examination using longitudinal and experimental designs is warranted. Moreover, all the movement behaviors were evaluated by self-reported items. Although these kinds of measures have been well validated and have been shown to have advantages in several aspects (eg, could reach wider participants and be more feasible in a large sample surveillance), they might lead to measurement biases (eg, recall bias and social disabilities). Objective measures for movement behaviors are warranted in future research. In addition, for the correlates of movement guideline adherence, our findings could only explain a small percentage of the variance. Further examination of the potential correlates (eg, psychosocial and environmental factors) should be performed in future studies.

This study found that only 1.8% of Chinese older adults adhered to 24-hour movement guidelines. Older age, female sex, and lower municipality economic levels were associated with poor adherence to movement guidelines among Chinese older adults. Importantly, adherence to either individual or combined movement guidelines was associated with better physical and mental health outcomes. These findings suggest the potential benefits of promoting a holistic lifestyle encompassing adequate MVPA, reduced SB, and sufficient sleep for improving the physical and mental well-being of elderly populations.