This study provides the first in-depth examination of the determinants and directed pathways of HRQOL in rural elderly individuals with chronic conditions based on the Wilson-Cleary model. These characteristics directly or indirectly influence patients' HRQOL through symptoms, functional state, and overall health perceptions in the model, including general demographic characteristics (gender, age, cultural status, work status, and main economic source), lifestyle characteristics (drinking, roughage, labour intensity, caring for grandchildren, and siesta), and environmental characteristics (social support, marital status, and dwelling status). This not only validates the underlying assumptions of the Wilson-Cleary model, but also clarifies the intricate directional pathways between symptom status, functional status, general health perceptions, HRQOL, and individual and environmental characteristics in older patients with chronic diseases. Based on this research, we can intervene early to effectively improve patients' HRQOL, ultimately reaching the aim of active ageing.
In all direct pathways, work status and age were risk factors for HRQOL in rural elderly chronic disease patients, which is consistent with previous studies[38, 39]; While general health perception, siesta, education, and labour intensity were protective factors. According to research, self-assessed health is significantly associated with mortality risk and quality of life in later life[40, 41]. The majority of the elderly chronic disease patients (62.6%) in this study had poor self-assessed health, and we should pay special attention to this segment of the population in health management. However, there is evidence that better self-assessed health does not imply better health status[42]. Therefore, while measuring the health state of older individuals with chronic diseases, we need include multiple indicators to better reflect their true health status.Furthermore, the education is connected to HRQOL; nevertheless, we can promote the improvement of the health status and quality of life of older people with chronic conditions living in rural areas by raising their health literacy, even if it can be challenging to do so later in life[43–46].
Significantly, in the HRQOL model for older rural patients with chronic diseases, both variables, labor intensity and siesta, can have a direct influence on symptoms, functional state, overall health perceptions, and HRQOL, all of which are statistically associated with the four model factors.After adjusting for a number of variables, Naska et al. discovered that siesta decreased mortality from chronic diseases[47]. However, several researchers disagreed, contending that siesta raises the chance of developing chronic illnesses as well as the chance of dying from them in older adults[48, 49]. While there is no clear consensus among academics on the benefits and drawbacks of siesta, this study's findings offer a possible path for enhancing HRQOL health management for elderly patients with chronic illnesses living in rural areas by introducing early targeted napping interventions.On the other hand, appropriate physical activity can lower the incidence of chronic metabolic and other diseases in the elderly, especially above moderate intensity physical activity has a positive health-promoting effect, the probability of engaging in moderate-to-high levels of physical activity declines with age[50–52]. For this reason, in order to enhance their health and reduce their risk of sickness, elderly people with chronic illnesses must be supported and encouraged to participate in appropriate physical activity.
The Wilson-Cleary model's assumptions and validity as a theoretical framework were confirmed by the statistical significance (P\(<\)0.05) of the indirect paths FS → GHP → HRQOL (β=-0.183) and Sym → FS → GHP → HRQOL (β=-0.082). Second, the relatively large effect values of social support (β = 0.081) and marital status (β = 0.050), two types of environmental characteristics that are indirectly related to HRQOL through general health perceptions, may provide partial evidence for the stress buffer model theory. Social support may function as an intermediary between stressful experiences and subjective evaluations[53, 54]. Previous research has shown that social support and involvement are closely correlated to the health of the elderly, and those who regularly participate in leisure, cultural, and spiritual activities in their family and community after retirement had a higher quality of life[55–57]. But in China today, there's a big difference in the social assistance received by older people in rural and urban areas, so it is necessary to focus on the environmental characteristics of rural old people with chronic illnesses and provide them with the necessary material and emotional support in a timely manner to promote their physical and mental health[58].
The results of the study showed significant associations between individual characteristics including BMI, smoking, and taste preference with HRQOL, which is consistent with prior research[59, 60]. However, further structural model study revealed that the three variables had no significant direct relationships with symptom status, functional status, general health perceptions, or HRQOL. This may be due to the fact that in complicated models, these variables may be moderated or masked by other variables, thus causing their direct associations with HRQOL to become insignificant[61, 62].The Wilson and Cleary model stresses the combined influence of all model components on HRQOL,and in this complex model, single factors such as BMI, smoking habits and dietary preferences may play only a relatively minor role.On the contrary, two environmental characteristic variables, marital status and residential status, which were not significant in univariate analyses, became statistically significant in the model, supporting our findings that some latent variables may not be directly related to HRQOL but can indirectly influence HRQOL in elderly rural chronic disease patients via factors such as symptoms, functional status, and overall health perceptions.As a result, we must look further into the likely link and mechanism of action between these variables in order to design more effective methods for managing the health of senior patients with chronic illnesses in the future.
Limitations
There are certain drawbacks to this study that need be addressed. First, the cross-sectional survey approach utilized in this study limits our capacity to identify causal links, thus proceed with caution when interpreting the data. Second, our study did not look at the effects of clinical variables on the model pathway, and the generic latent variables utilized may not appropriately represent the symptomatic and functional condition of older individuals with chronic conditions.In the future, we will add more relevant factors to better understand the mechanism of action of the HRQOL model in older patients with chronic conditions.