This study is based on Orem’s self-care theory¹⁸, which emphasizes the self-care activities individuals engage in to maintain health. The core concept of the theory is the alignment between an individual’s self-care needs and self-care abilities to sustain health and well-being. When an individual’s self-care abilities are insufficient to meet health needs, they may experience a deficiency in self-care, requiring external support or assistance¹⁹. This theory is intrinsically linked to this study in two main ways: first, elderly rural patients with CHD have various self-care needs in managing their condition, such as dietary control, exercise management, and medication adherence, all of which rely on the patients’ self-care abilities²⁰; second, elderly rural populations may have generally weak self-care abilities due to factors such as limited health knowledge, inadequate social support, and financial constraints, leading to self-care deficiencies²¹. Therefore, LPA can be used to identify distinct groups of self-care abilities, enabling the development of targeted interventions for each group to improve health management outcomes.

The relationship between self-care ability and depression is particularly prominent²². When elderly patients are unable to effectively manage their health, they may feel helpless, frustrated, and anxious, which can lead to the onset of depressive symptoms²³. Psychological factors are a crucial component of Orem’s self-care theory, and this framework provides a unique psychological perspective to understand whether different levels of self-care ability are linked to the occurrence of depression²². Thus, guided by Orem’s self-care theory, this study conducted LPA of self-care ability in elderly rural patients with CHD, explored the characteristics and influencing factors of different groups, compared depressive symptoms among different groups, and revealed the relationship between self-care ability and depression.

This study utilized data from the Elderly Health Assessment Project of Shandong Provincial Hospital Affiliated with Shandong First Medical University. From April to June 2024, investigators conducted face-to-face questionnaire surveys and medical health examinations among elderly rural residents in 33 villages in Xintai city, Shandong Province, China. This study aimed to assess the health status of elderly rural individuals comprehensively by examining various social, behavioural, environmental, and biological factors influencing their well-being. The analysis was based on the most recent 2024 baseline survey, comprising 5,389 responses.

The inclusion criteria were as follows: (1) age ≥ 60 years; (2) clinically diagnosed coronary heart disease; (3) permanent residency in the survey area for over one year; (4) participation in

medical health examinations with available health reports; (5) ability to communicate normally and cooperate in completing the survey; and (6) provision of informed consent with voluntary participation. The exclusion criteria were as follows: (1) any form of dementia; (2) severe mental disorders; (3) inability to cooperate or refusal to participate; and (4) duplicate participation. After the inclusion and exclusion criteria were applied, 999 valid samples were retained for analysis. The screening procedure is illustrated in Fig. 1.

In this study, SPSS 27.0 was employed to establish a database, and SPSS 27.0 and Mplus 8.3 were used for data analysis. A bilateral test with P < 0.05 indicated that the results were statistically significant.

The program was approved by the Ethics Committee. All participants signed an informed consent form at the time of their participation. The study follows the Declaration of Helsinki.

The Harman single-factor method was employed to test for common method bias. The results revealed that there were 5 factors with feature roots > 1, and the variance of the variance interpretation of the first factor was 24.205%, which was < 40% of the recommended standard, indicating that there was no serious common methodological bias in this study.

The results revealed that the participants were between 60 and 92 years old, with a mean age of 72.37 ± 6.47 years. Among the participants, 50.2% were older adults between 71 and 80 years of age, 70.5% were female, 69.8% were married, and 82.8% had an education level of elementary school or below. Individuals with more than 3 children accounted for 50.1%, 72.3% did not live alone, and 79.6% had an income of < 1000 yuan/month. The average self-rated health status was 34.8%, 73.8% had coronary heart disease for more than 3 years, 52.8% had hearing loss, and 69.3% had 3 or more chronic diseases. Other characteristics are detailed in Table 1.

Self-care ability was used as an exogenous indicator, and 1 to 4 latent profile models were selected for exploratory latent profile analysis of self-care ability in elderly rural patients with coronary heart disease. The results are shown in Table 2. The number of model categories increased from 1 to 4, and the AIC, BIC, and aBIC continued to decrease, with entropy being the highest among the 4-profile models. The 2-profile model LMRT had P values > 0.05 and was excluded. In the 4-profile model, the number of some subgroups accounted for only a small proportion of the total number of people, and the clinical interpretability was poor. Moreover, LMRT had P values > 0.05 in the 4-profile model, so it was excluded. The 3-profile models AIC, BIC, and aBIC were small, the entropy was > 0.8, and the LMRT and BLRT were significant. Therefore, the 3-profile model was finally chosen as the optimal potential profile model for this study. Table 4 shows the attribution probability matrix for the 3 potential profiles. The average probability of attribution of each class to its corresponding potential profile ranged from 93.3% to 99.9% (all > 90%), indicating that the results of the model for the three potential profiles in this study were plausible.

A graph was drawn using the distribution of scores on the 17 entries of the self-care ability scale for the three categories of elderly rural patients with CHD, with the horizontal coordinate being the number of entries on the self-care ability scale and the vertical coordinate being the score (Fig. 1). The three latent categories were named according to the latent profile results and the score characteristics of Fig. 1. Category 1 is named “low self-care ability—struggling to start group” because this category initially has low scores with relatively large fluctuations in the later stages, and overall, the scores remain relatively low. Category 2 is named the “moderate self-care ability—gradual adaptation group,” as this category shows moderate scores with relatively steady growth in both the early and later stages. Category 3 is named the “high self-care ability—stable mastery group,” as it has overall high and stable scores.

The chi-square test and Kruskal‒Wallis H test were employed to compare the differences in the existence of single risk factors among elderly rural patients with CHD with different potential self-care ability categories, and the results are shown in Table 1. The three potential categories of self-care ability of elderly rural patients with CHD were compared in terms of age, monthly income, smoking status, vision loss status, types of medications, duration of disease, self-rated health and depression, and the differences were statistically significant (P < 0.05), as shown in Table 1.

The variables that showed statistical significance in the univariate analysis were included in a multivariate logistic regression model, with the three latent categories as the dependent variables. (variable assignments are shown in Table 4). The low self-care ability—struggling to start group and the moderate self-care ability—gradual adaptation group were employed as the reference group to compare the groups.

The regression analysis results revealed that age, monthly income, smoking status, vision loss status, types of medications, duration of disease, self-rated health and depression affected the latent categories of self-care ability in the participants (all p < 0.05). The results are shown in Table 5. Specifically, monthly income and vision loss status predicted the pattern of the moderate self-care ability—gradual adaptation group in the comparison between the low self-care ability—struggling to start group and the moderate self-care ability—gradual adaptation group. Age, monthly income, vision loss status, duration of disease, self-rated health and depression predicted the pattern of the high self-care ability—stable mastery group in the comparison between the low self-care ability—struggling to start group and the high self-care ability—stable mastery group; smoking status, types of medications and depression predicted the pattern of the high self-care ability—stable mastery group in the comparison between the moderate self-care ability—gradual adaptation group and the high self-care ability—stable mastery group.

One-way ANOVA was used to explore the relationships between modes of self-care ability and depression in elderly rural patients with CHD. The results in Table 6 show that the differences between the different modes of self-care ability among older rural adults were significant (p < 0.001) for depression. Further post hoc test results revealed that for depression, the moderate self-care ability—gradual adaptation group scored the highest, and the high self-care ability—stable mastery group scored the lowest.

This study identified three distinct subtypes of self-care ability on the basis of the scores of 17 self-care ability items in elderly rural patients with CHD: “low self-care ability—struggling to start group”, “moderate self-care ability—gradual adaptation group”, and “high self-care ability—stable mastery group.” These findings indicate significant variability in self-care ability levels among elderly rural patients with CHD. The characteristics of these three types are as follows: “low self-care ability—struggling to start group”: this group had the lowest overall self-care ability score, accounting for 21.9% of the sample; “moderate self-care ability—gradual adaptation group”: this group had moderate overall self-care ability scores, representing 32.4% of the sample; “high self-care ability—stable mastery group”: this group had the highest overall self-care ability score, accounting for the largest proportion at 45.7%. The low self-care ability—struggling to start group represented the smallest proportion of patients, which could be attributed to recent improvements in rural health care services. Although medical resources in rural areas remain limited, increased national focus on primary health care and the development of health education programs over the past few years have contributed to better self-care ability among elderly patients, allowing them to progress into moderate or high self-care ability groups^30,31.

Furthermore, in the comparison of overall scores across the three groups, the scores for Items 1 and 12 were lower across all groups. This may be due to the physical limitations of elderly rural patients with coronary heart disease, particularly the decline in cardiovascular function, which reduces their physical activity capacity³². As a result, behaviours such as walking to distant locations (Item 1) or seeking solitude (Item 12) may become more difficult or impractical for all groups. However, a between-group comparison revealed that the low self-care ability—struggling to start group scored higher on Items 1 and 12 than did the other two groups. This could be because, despite their lower self-care ability, these patients might still recognize the benefits of walking as a gentle form of exercise and may show a greater willingness to engage in outdoor activities³³. Additionally, compared with the other groups, this group may feel more helpless in addressing their health issues, leading to more emotional responses and psychological stress. These challenges might make them more likely to seek solitude as a coping mechanism for emotional regulation.

Elderly rural patients with CHD with low monthly income, vision loss, and average self-rated health had a greater probability of belonging to the low self-care ability—struggling to start group. First, the low self-care ability of elderly rural patients with CHD with low economic levels was similar to the findings of Azam et al³⁴. The probable reason for this is that low income limits the ability of patients to seek regular medical care and timely medication and checkups, resulting in the inability of patients to receive timely treatment or purchase necessary medications, which affects the health management of the disease³⁵. Second, the main reason why vision loss leads to reduced self-care ability is that vision loss directly limits patients' ability to perform daily activities, such as basic self-care activities (e.g., eating, dressing, personal hygiene, etc.) and complex tasks (e.g., reading, writing, etc.), and this functional limitation not only increases patients' reliance on the help of others but also directly reduces their level of self-care³⁶. Finally, patients with average health status are usually physically limited and lack sufficient energy and motivation for effective self-care, such as taking medication on time, eating a healthy diet, and exercising on a regular basis, which also reflects their pessimistic attitudes towards their own health as well as disease-related psychological stress, thus affecting self-care behaviours^37,38. Therefore, relevant government departments should increase medical subsidies and financial support, provide assistive devices and design barrier-free living environments to improve medical services and living environments for elderly rural patients with CHD. In addition, healthcare providers should develop targeted self-care programs for patients with different health conditions and provide psychological support and emotional care to help patients overcome physiological and psychological barriers, establish a positive psychological state, and gradually improve their self-care ability.

Elderly rural patients with CHD who were chronic smokers had a greater probability of belonging to the moderate self-care ability—gradual adaptation group, which is consistent with the findings of Putri et al³⁹. Chronic smoking severely affects patients' cardiovascular and respiratory systems, increases the probability of other chronic diseases, and causes psychological problems such as anxiety and depression, which increase the challenges of mental health management and limit their participation in self-care and disease management^40,41. Therefore, healthcare providers should strengthen education and training on the harmful effects of smoking and actively provide smoking cessation interventions through smoking cessation clinics and alternative therapies to help patients quit smoking and reduce the negative effects of smoking on the body. In addition, family members and society should provide a more comprehensive support system for older adults who quit smoking, such as emotional care, social activities, and convenient health management services, to improve their adverse psychological state.

Elderly rural patients with CHD who are younger, take fewer types of medications, and have a longer duration of disease have a greater probability of belonging to the high self-care ability-stable mastery group. First, compared with elderly rural patients with coronary artery disease aged 70 years or older, elderly rural patients with CHD aged 60–70 years usually have better overall health and may not have significant other chronic diseases or relatively mild health problems; however, as they grow older, their physical functions continue to decline, their health problems gradually become more pronounced, and their ability to take care of themselves gradually declines⁴². Second, taking fewer types of medications usually means that their condition is more stable, the symptoms are milder or the patient is able to control the condition through health management (e.g., dietary adjustments, regular exercise, etc.), thus avoiding overreliance on medications, which requires a greater level of self-care ability⁴³.

Finally, elderly rural patients with CHD who had a long duration of disease had a greater probability of belonging to the high self-care ability—stable mastery group. This may be because they have accumulated richer self-management experience in the course of long-term disease management, gradually learned to adjust their lifestyles according to their own conditions, and are able to detect changes in their conditions and take corresponding measures in a timely manner; thus, their self-care ability has improved. Therefore, early health education on chronic disease management should be provided to elderly individuals in rural areas to help them understand the importance of early screening and disease management. Drug management programs should be developed for patients taking multiple medications on an individual basis to improve their health and reduce unnecessary drug use by improving their poor lifestyles. In addition, for patients with longer disease durations and greater self-care ability, professional guidance on the injection of medications should be provided to address the weak points of their disease management to further strengthen their self-care ability.

4.3 Differences in depression levels among elderly rural patients with CHD in different categories of self-care ability

This study also examined the level of depression in elderly rural individuals with CHD with different levels of self-care ability and revealed a significant association between different self-care abilities and depression. Higher self-care ability was associated with lower depression, which is consistent with previous findings⁴⁴. In other words, the poorer an individual's self-care ability is, the more likely their depressive symptoms are to be severe. Conversely, as self-care ability increases, patients’ self-confidence and self-efficacy increase, which may help alleviate their level of depression. The results of this study showed that the high self-care ability to stabilize mastery group had the lowest depression scores, and the other two groups were not comparable in the comparison of range values. The differences in depression scores among the three categories of patients were statistically significant (all P < 0.05), suggesting that there is a close relationship between the occurrence of depression in elderly rural patients with CHD and their self-care ability. Usually, depressive symptoms affect patients' cognitive and executive functions, and compared with severely depressed patients, patients with milder depressive symptoms are better able to plan and perform daily care tasks; however, their self-efficacy is greater, and they are more willing to actively seek support and resources¹³. These findings suggest that healthcare providers should pay attention to the negative impact of depression on patients, actively improve patients' depression through psychological intervention and social support, and enhance self-efficacy in disease management, thus strengthening self-care behaviours.