Elderly patients with chronic obstructive pulmonary disease (COPD) often have limited respiratory function and multi-system decline. Traditional assessment methods cannot comprehensively reflect their overall functional status, and the characteristics of intrinsic capacity in this population remain unclear. This study aimed to identify latent classes of intrinsic capacity in elderly COPD patients and analyze influencing factors, providing a basis for early clinical identification and precise intervention.

A cross-sectional design was used. From July 2025 to January 2026, 423 elderly COPD patients hospitalized in the Department of Respiratory and Critical Care Medicine, Department of Geriatrics, and Department of Cardiology at the main campus and Binhu campus of Hefei First People’s Hospital were selected by convenience sampling. Face-to-face surveys were conducted using the Intrinsic Capacity Assessment Tool, a general information questionnaire, the Lubben Social Network Scale (LSNS-6), and the Chinese Adult Sedentary Behavior Questionnaire. Latent class analysis was used to identify intrinsic capacity categories, and univariate and multinomial logistic regression were used to analyze influencing factors.

The overall decline rate of intrinsic capacity in elderly COPD patients was 92.9%. Three latent classes were identified: overall preserved (n=145), functionally imbalanced (n=178), and overall impaired (n=100). Significant differences were found among the three groups in sex, age, smoking status, marital status, living arrangement, disease duration, number of comorbidities, medication use, number of hospitalizations for COPD in the past year, long-term home oxygen therapy, mMRC grade, LSNS-6 total score, family network score, friend network score, and total sedentary behavior score (P<0.05). Multinomial logistic regression analysis showed that family network score (OR=0.765, 95%CI: 0.598 to 0.978), friend network score (OR=0.561, 95% CI: 0.442 to 0.712), Chinese Adult Sedentary Behavior Questionnaire total score (OR=1.414, 95%CI: 1.030 to 1.940), age 70 to 79 years (OR=2.788, 95%CI: 1.093 to 7.111), having ≥2 other chronic diseases (OR=6.981, 95%CI: 1.701 to 28.643), long-term home oxygen therapy (OR=3.297, 95%CI: 1.147 to 9.478), and mMRC grade 2 to 4 (OR=4.060, 95%CI: 1.186 to 13.907) were independent influencing factors for the functionally imbalanced group (P<0.05). Family network score (OR=0.716, 95%CI: 0.542 to 0.945), friend network score (OR=0.396, 95%CI: 0.286 to 0.549), Chinese Adult Sedentary Behavior Questionnaire total score (OR=1.586, 95%CI: 1.121 to 2.245), age 70 to 79 years (OR=5.370, 95%CI: 1.400 to 20.598), age ≥80 years (OR=12.169, 95%CI: 2.042 to 72.511), and long-term home oxygen therapy (OR=4.695, 95%CI: 1.345 to 16.391) were independent influencing factors for the overall impaired class (P<0.05).

There is significant heterogeneity in the intrinsic capacity of elderly COPD patients, which can be classified into three latent classes. Social isolation, sedentary behavior, age, number of comorbidities, mMRC grade, and long-term home oxygen therapy are closely associated with intrinsic capacity. It is recommended that intrinsic capacity classification be incorporated into routine assessment for elderly COPD patients, and for those with functionally imbalanced and overall impaired group, comprehensive intervention strategies such as enhancing social support, reducing sedentary behavior, and optimizing oxygen therapy management should be prioritized to delay the decline of intrinsic capacity.

Stroke has become the leading cause of death and disability among Chinese adults. The long-term rehabilitation and secondary prevention of elderly patients are highly dependent on proactive health behaviors, yet existing studies largely overlook group heterogeneity. Based on Pender’s Health Promotion Model, this study used latent profile analysis to explore the latent classes of proactive health behaviors among elderly stroke patients and their influencing factors, so as to provide evidence for stratified precision nursing.

This study adopted a cross-sectional design, from July to December 2025, 403 elderly stroke patients were selected by convenience sampling from Hefei First People’s Hospital. The survey instruments included a general information questionnaire, the Active Health Behavior Scale for Patients with Chronic Diseases (AHBS), the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SES6C), the Social Support Rating Scale (SSRS), and the Brief Illness Perception Questionnaire (BIPQ). Latent profile analysis (LPA) was used to identify the latent classes of proactive health behaviors, with AIC, BIC, aBIC, entropy, LMR, and BLRT used to determine the optimal model. Univariate analysis and multinomial logistic regression (with the low proactive health behavior-passive compliance type as reference) were used to explore the influencing factors.

The proactive health behavior score of the 403 patients was 59.42±12.56. LPA identified three latent classes: low proactive health behavior-passive compliance (53.6%), moderate proactive health behavior-cognitive-behavioral imbalance (20.8%), and high proactive health behavior-active engagement (25.6%). The model demonstrated a good fit (AIC=9467.672, BIC=9555.648, aBIC=9485.840, entropy=0.953, LMR and BLRT: P<0.001). Multinomial logistic regression analysis revealed that, with the low proactive health behavior-passive compliance class as the reference, monthly income of 1000 to 2999 yuan (OR=0.139, 95%CI: 0.029 to 0.659), monthly income of 3000 to 5000 yuan (OR=0.119, 95%CI: 0.023 to 0.605), chronic disease management self-efficacy score (OR=1.238, 95%CI: 1.141 to 1.343), illness perception score (OR=1.246, 95%CI: 1.181 to 1.314), and social support score (OR=1.337, 95%CI: 1.250 to 1.431) were associated with classification into the moderate proactive health behavior-cognitive-behavioral imbalance class. Furthermore, primary school education or below (OR=0.030, 95%CI: 0.008 to 0.118), junior or senior high school education (OR=0.305, 95%CI: 0.098 to 0.939), monthly income of 1000 to 2999 yuan (OR=0.063, 95%CI: 0.015 to 0.263), monthly income of 3000 to 5000 yuan (OR=0.219, 95%CI: 0.052 to 0.923), living with spouse (OR=20.693, 95%CI: 2.620 to 163.263), living with children (OR=8.693, 95%CI: 1.523 to 49.625), family history of stroke (OR=5.688, 95%CI: 1.875 to 17.259), having 3 to 5 chronic diseases (OR=4.998, 95%CI: 1.409 to 17.656), chronic disease management self-efficacy score (OR=1.107, 95%CI: 1.046 to 1.173), illness perception score (OR=1.209, 95%CI: 1.125 to 1.301), and social support score (OR=1.383, 95%CI: 1.286 to 1.489) were associated with classification into the high proactive health behavior-active engagement class (all P<0.05).

Elderly stroke patients showed obvious group heterogeneity in proactive health behaviors. Multiple sociodemographic and psychological factors influenced their profile types, and clinical practice should implement stratified individualized interventions based on latent profile characteristics.