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Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults

October 22, 2026
in Medicine, Science News
Glenn Wilkins
By Glenn Wilkins Scienmag Editorial Profile - Clinical Psychology
Reading Time: 5 mins read
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Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults

Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults

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Among older adults living with several chronic conditions, a greater number of illnesses was associated with more depressive symptoms, while lower psychological resilience and poorer sleep quality helped explain part of that association, according to a cross-sectional survey of 1,759 people in two Chinese provinces. Statistical mediation analysis estimated that the pathway through psychological resilience accounted for 30.05% of the total association, the pathway through sleep quality for 20.66%, and a sequential pathway linking resilience to sleep for another 5.16%. The findings identify potentially important correlates of depressive symptoms, but because every variable was measured at one point in time, they do not establish which came first or prove that any factor caused another.

The survey was conducted from October 2024 to January 2025 through a multistage stratified random sampling design. Researchers selected two provinces regarded as representing different levels of economic development, then chose one prefecture-level city in each, three counties or districts within each city, four townships in each county and six villages in each township. Between 20 and 25 patients with chronic diseases were randomly selected per village. Of 3,233 questionnaires distributed, 3,216 were returned, a response rate of 99.5%. After the researchers applied their eligibility and exclusion criteria, the analytical sample comprised people aged 60 or older who had at least two chronic conditions.

The participants were predominantly women, married and educated at primary-school level or below, which limits how broadly the results can be generalized. Women represented 1,150 participants, or 65.38%, while 1,241, or 70.55%, were married. Most had no more than primary education: 1,195 participants, or 67.94%. Health insurance coverage was 99.37% and pension insurance coverage 98.07%. Half of the sample, 884 people or 50.26%, had two chronic conditions, 542 had three, and 333 had four or more. The mean reported number of conditions was 2.794, with a standard deviation of 1.006. The sample also had a mean depressive-symptom score of 9.800 on the 10-item Center for Epidemiologic Studies Depression Scale, on which a score of 10 or above was classified as depressive symptoms.

Depressive symptoms were more common among participants who were older, female, widowed, less educated or living with more chronic conditions. The largest contrast involved disease burden: 347 of 884 participants with two conditions had depressive symptoms, compared with 271 of 542 with three conditions and 210 of 333 with four or more. In the full correlation analysis, the number of chronic conditions was positively associated with depressive symptoms, with a Spearman correlation of 0.211. More conditions were also associated with poorer sleep quality, with a correlation of 0.179, and with lower psychological resilience, for which the correlation was −0.151. All three relationships were statistically significant at p less than 0.001.

The strongest bivariate relationships involved psychological resilience and depressive symptoms, which were negatively correlated at −0.564, and sleep quality and depressive symptoms, which were positively correlated at 0.478. Because the Pittsburgh Sleep Quality Index assigns higher scores to poorer sleep, its positive correlation with depressive symptoms indicates that poorer sleep was associated with more depressive symptoms. Resilience and sleep quality were also negatively correlated at −0.295. The mean scores were 18.832 for psychological resilience on the five-item resilience scale and 7.872 for sleep quality on the Pittsburgh index, which ranges from 0 for better to 21 for poorer sleep. These pairwise results describe the pattern among the variables but, on their own, cannot show whether one formed a causal sequence.

To examine the proposed mediation pathways, the researchers used Model 6 of the PROCESS macro for SPSS, treating the number of chronic conditions as the independent variable, psychological resilience and sleep quality as mediators, and depressive symptoms as the outcome. The analysis controlled for age, gender, marital status, education, smoking, alcohol consumption, health insurance and pension insurance. All continuous variables were standardized before analysis, and the reported regression coefficients were standardized estimates. Consequently, a one-standard-deviation increase in the number of conditions, rather than necessarily one additional diagnosis, was the exposure unit for interpreting those coefficients. Bias-corrected percentile bootstrap estimates with 5,000 resamples generated the confidence intervals, while generalized estimating equations with township as the clustering unit provided a sensitivity analysis.

In the adjusted mediation model, a one-standard-deviation increase in condition count was associated with lower psychological resilience, with a standardized coefficient of −0.131; poorer sleep quality, at 0.138; and more depressive symptoms, at 0.094. All three coefficients had p values below 0.001. Greater resilience was associated with better sleep quality, with a coefficient of −0.255, and fewer depressive symptoms, at −0.483. Poorer sleep quality was associated with more depressive symptoms, with a coefficient of 0.317. The generalized estimating equation sensitivity analysis produced closely similar estimates: −0.132 for the condition-count and resilience association, 0.138 for condition count and sleep quality, 0.095 for condition count and depressive symptoms, −0.254 for resilience and sleep quality, −0.482 for resilience and depressive symptoms, and 0.319 for sleep quality and depressive symptoms.

The mediation estimates indicated that the total standardized association between chronic-condition count and depressive symptoms was 0.213, with a 95% confidence interval of 0.167 to 0.259. A direct association remained after the mediators were introduced, measuring 0.095, or 44.60% of the total. The combined indirect association was 0.118, representing 55.40%. The pathway from greater disease burden to lower resilience and then to more depressive symptoms was 0.064, with a 95% confidence interval from 0.042 to 0.086. The pathway through sleep quality alone was 0.044, with a 95% confidence interval of 0.030 to 0.060. The chain from greater disease burden to lower resilience, poorer sleep and more depressive symptoms was 0.011, with a 95% confidence interval of 0.007 to 0.015. None of those intervals included zero, although the sequential effect was relatively small.

The results fit a model in which accumulating chronic illness is associated with psychological and sleep-related vulnerabilities that accompany depressive symptoms. Lower resilience may make it harder to manage treatment demands, pain, fatigue, financial pressure and other stresses associated with multimorbidity. The study also notes that chronic illness can coexist with symptoms, functional decline, medication burdens and communication barriers that may erode feelings of control. At the same time, pain, disrupted circadian rhythms, polypharmacy and impaired physical function may contribute to disturbed sleep. Lower resilience is also linked in the source research with greater worry, rumination and pre-sleep arousal, offering a plausible connection between diminished coping capacity and poorer sleep. These mechanisms were discussed as interpretations of the observed model, however, rather than mechanisms directly tested by an intervention or experiment.

The most important constraint is the cross-sectional design. Depressive symptoms could plausibly precede changes in resilience or sleep, and the researchers explicitly found that an alternative pathway running from chronic-condition count to depressive symptoms and then to sleep quality was also statistically significant. This possibility means the measured sequence does not establish temporal order. Self-reported information could also introduce recall error, and some resilience items resembled aspects of depressive symptoms. Although sampling was designed to represent different socioeconomic settings, within-village correlations could not be completely excluded, and unmeasured confounding remains possible. The findings therefore support assessing psychological resilience and sleep alongside physical disease burden in comprehensive care for older adults with multimorbidity, but they do not show that intervening on resilience or sleep would reduce depressive symptoms. Longitudinal studies would be needed to determine the direction and dynamics of these relationships.

Subject of Research: Cross-sectional mediation of depressive symptoms by psychological resilience and sleep quality among older Chinese adults with multimorbidity

Article Title: The relationship between the number of chronic conditions and depressive symptoms in older adults with multimorbidity: the chain mediating role of psychological resilience and sleep quality

Article References: Xu, M., Duan, Y., Feng, Z., Li, H., Sun, X., Yue, J., Wang, J., Zhuge, X., Zhang, X., Hu, S., Chen, F., & Chen, Z. (2026). The relationship between the number of chronic conditions and depressive symptoms in older adults with multimorbidity: the chain mediating role of psychological resilience and sleep quality. Frontiers in Public Health, 14, Article 1973096. https://doi.org/10.3389/fpubh.2026.1973096

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1973096

Keywords: multimorbidity, older adults, depressive symptoms, psychological resilience, sleep quality, chronic diseases, cross-sectional study, mediation analysis, China, geriatric health, relationship, between

Cite Scienmag News

Glenn Wilkins. (October 22, 2026). Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults. Scienmag. https://scienmag.com/cross-sectional-study-links-multimorbidity-resilience-sleep-and-depressive-symptoms-in-older-adults/

Glenn Wilkins. "Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults." Scienmag, 22 October 2026, https://scienmag.com/cross-sectional-study-links-multimorbidity-resilience-sleep-and-depressive-symptoms-in-older-adults/. Accessed 22 October 2026.

Glenn Wilkins. "Cross-sectional study links multimorbidity, resilience, sleep and depressive symptoms in older adults." Scienmag. October 22, 2026. https://scienmag.com/cross-sectional-study-links-multimorbidity-resilience-sleep-and-depressive-symptoms-in-older-adults/

Tags: aging and mental health factorsassociations between chronic disease burden and psychological well-beingbetweenChinaChinese population health surveychronic diseaseschronic illness and depressioncross-sectional health studycross-sectional studydepressive symptomsdeterminants of depressive symptoms in elderlygeriatric healthimpact of resilience on mental healthmediation analysismediation analysis in health researchmultimorbiditymultimorbidity in older adultsolder adultspsychological resiliencepsychological resilience and mental healthRelationshiprole of sleep in depressionsleep qualitysleep quality and depressive symptoms
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