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Abstract
Objective This study aims to further explore the relevant influencing factors of depression and explore the correlation between multimorbidity coexistence and depression to find the goals and methods of early intervention of depression in the elderly.
Design This study adopts a cross-sectional approach.
Setting The study population of this project came from the China Health and Retirement Longitudinal Study. Depression was grouped according to the 10-item version of Centre for Epidemiological Research Depression Scale. Chronic diseases, height, weight, grip strength, education, marital status, alcohol consumption, exercise and other indicators were included in the analysis.
Participants 2239 adults over 60 years of age were included.
Results The proportion of women in the depression group was higher (p<0.001). The depression group had a lower grip strength than the control group (p<0.05). The sleep duration was shorter in the depression group (p<0.001). There were differences in education, marital status and alcohol consumption in the depression group (p<0.05). The depression group might have more types of coexisting chronic diseases (p<0.001). The depression group was more likely to have hypertension, dyslipidaemia, chronic lung diseases, heart attack, stroke, stomach disease and memory-related disease. Grip strength was connected with the risk of depression in the elderly (0.971 (95% CI 0.959 to 0.984)). Sleep (0.827 (95% CI 0.785 to 0.872) and education level (0.790 (95% CI 0.662 to 0.942) were related to the risk of depression in the elderly. Concomitant chronic diseases could affect the risk of depression in the elderly (1.455 (95% CI 1.243 to 1.703)).
Conclusion The coexistence of multiple chronic diseases and depression is very common in the elderly. The coexistence of multiple chronic diseases is more common in older women and older depressed people. With the increase in the number of chronic diseases, the risk of depression in the elderly is significantly increased.
- aged
- China
- chronic disease
- epidemiology
- factor analysis, statistical
Data availability statement
Data are available on reasonable request. The data can be searched online or by contacting the author.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
The data included in this study are from the China Health and Retirement Longitudinal Study cohort study, which is large and reliable.
This study analyses and studies from the perspective of multidisease coexistence in the elderly and provides a basis for the management of clinical chronic diseases.
The study was a cross-sectional study and could not account for causation.
Introduction
Population ageing is an inevitable trend in global development, and the growth rate of the population over 65 in the USA is accelerating, as is the UK.1 Population ageing is inevitably associated with ageing-related diseases and will bring certain pressure to the economic burden of society.2 The advent of an ageing society is bound to lead to a gradual increase in chronic diseases related to old age. In the USA, more than 80% of older adults have at least one chronic disease and face a decline in physical function as a result.3 Even though some elderly people have multiple diseases coexisting, a person suffers from multiple chronic diseases, and the simultaneous use of multiple drugs is also a burden for the elderly.4 Today’s common chronic diseases include hypertension, diabetes, heart disease, cancer, stroke and so on, China is also facing the severe challenge of chronic diseases, and the mortality rate of chronic diseases in middle-aged people in China is also higher than that of developed countries.5 Researchers believe that chronic diseases can affect the mood of older people and cause psychological distress.6
More and more studies confirm that mood disorders are common in the elderly, with about 20% of the elderly having mood disorders, and depression is the most common.7 Depression is a common disorder and is also considered to be the leading cause of disability worldwide, with a higher incidence in women than in men, but its causes and mechanisms remain unclear.8 The researchers found that in Vietnam, most elderly people diagnosed with depression have reached the advanced stage of depression.9 Mental health conditions have a significant impact on healthcare spending in older adults, and as a result, depression increases the healthcare burden in older adults.10 Therefore, there is multidisease coexistence in the elderly population, and the accumulation of chronic diseases increases the economic burden and increases the mental burden while depression is also associated with chronic diseases and further increases the burden of the elderly. So what factors are related to depression in the elderly and is chronic disease an influencing factor of depression? This study aims to further explore the relevant influencing factors of depression and explore the correlation between multimorbidity coexistence and depression by analysing the relevant data of the elderly, in order to find the goals and methods of early intervention of depression in the elderly.
Method
Study population
The study population of this project came from the China Health and Retirement Longitudinal Study (CHARLS).11 The study was cohort, enrolling people aged 45 years and older from 2011, followed every 2–3 years, and updating data. Our study mainly included people aged 60 years and older.
Depression grouping
The 10-item version of Centre for Epidemiological Research Depression Scale (CES-D-10) was selected to assess depression, and it has been shown to be used to assess symptoms in older adults.12 13 There are 10 items on the scale, each of which can be rated from 0 to 3 points, and the higher the cumulative score, the higher the degree of depression, and if the cumulative score is greater than or equal to 10, it is evaluated as depression.14
Multimorbidity coexisted
Through the questionnaire survey, the subjects answered whether they were diagnosed with hypertension, stomach disease, diabetes, hyperlipidaemia, cancer, chronic lung disease, liver disease, kidney disease, stroke, heart disease, asthma and other diseases and divided the subjects into (1) no chronic disease, (2) 1–2 chronic diseases and (3) 3 or more chronic diseases.
Marital status and education
According to the subjects’ answers to the questionnaire, the marital status was divided into (1) married, (2) unmarried and (3) divorced or living alone. Similarly, according to the questionnaire, the educational level is divided into (1) illiteracy, (2) below high school level and (3) high school and above.
Weight-related indicators and other covariates
The study included height, weight and waist circumference as weight-related indicators. We grade the weight scale according to the body mass index (BMI) standard. BMI=weight (kg)/height (m)2. We classified participants into underweight (BMI <18.5 kg/m2), normal-weight (18.5 kg/m2≤BMI≤23.9 kg/m2), overweight and obesity (BMI ≥24 kg/m2) groups. In addition, through questionnaires and tests, we included indicators such as grip strength, alcohol consumption, exercise, napping, night sleep duration and so on.
Statistical analysis
All data were analysed by using the SPSS V.25.0. T-test or Mann-Whitney U test was used for continuous variable comparison, and χ2 test was used to compare categorical variables. We used correlation analysis to explore the relationship between depression and chronic disease, and rank correlation to assess the correlation between depression scores and various indicators. A multivariable logistic regression model was used to evaluate associated factors with depression. The mean of continuous data is expressed as mean±SD. If the continuous variable is not normally distributed, the mean is replaced with the median to quartile interval. A p<0.05 was statistically significant.
Patient and public involvement
None.
Results
Sample inclusion process
The sample data of this study were mainly from public databases, and a total of 21 578 cases were obtained by combining the 2015 and 2018 database data and removing ID duplicates and missing persons. Then, according to the data analysis needs of this study, we removed the missing data and the wrong ones and finally obtained the sample data of 2239 cases (figure 1). Missing and incorrect items include age, height, weight, chronic disease diagnosis, waist circumference, grip strength and so on. The age requirement of the included population is greater than or equal to 60 years old.
Flow diagram.
Comparison of baseline data between depression group and control group
We included people aged 60 years and older. By comparison, we found clear differences in the gender of depression group and control groups (p<0.05). The prevalence of depression is 29.48%. The depression prevalence of women is 51.2%, and the depression prevalence of men is 48.8%. The proportion of women in the depression group was higher. However, there was no statistically significant difference in age between the depressed group and control groups, the median overall age is 68. BMI and waist circumference were not statistically different between the two groups. The depression group (28.70±9.67 kg) had a lower grip strength than the control group (33.54±35.39 kg), with a statistically significant difference (p<0.05). The depression group had a statistically significant difference in sleep duration that was shorter than in the control group (p<0.05). Compared with the control group, there were differences in education, marital status and alcohol consumption in the depression group while there was no difference in exercise and napping. Comparing the two groups, there were differences in the status of coexisting chronic diseases, and the depression group may have more types of coexisting chronic diseases (p<0.05) (table 1).
Comparison of baseline data between depression group and control group
Comparison of baseline data between men and women
We compared the included populations according to gender (table 2). We found age differences between men and women, with men being relatively older. The BMI of women (25.07±2.93 kg/m2) was higher than that of men (23.35±2.96 kg/m2), and the difference was statistically significant (p<0.05). The waist circumference of women (88.90±8.41 cm) is greater than that of men (86.16±8.77 cm), and the difference is statistically significant (p<0.05). The grip strength of men (45.94±8.37 kg) is significantly greater than that of women (26.57±45.70 kg) (p<0.05). Women had significantly higher depression scores than men, and women were more likely to experience depressive symptoms than men (p<0.05). Men sleep longer than women, and the difference was statistically significant (p<0.05). In comparison, there were differences in education, marital status, weight class, alcohol consumption and napping between men and women. However, there was no difference in exercise and the chronic disease comorbid state that existed between men and women.
Comparison of baseline data between men and women
Correlation analysis of depression scores in older adults
Since the depression scores are non-normally distributed, we used rank correlation for analysis. Through the analysis (table 3), we found that the variables correlated with depression scores were grip strength and length of sleep, with statistically significant differences (p<0.05).
Correlation analysis of depression scores in older adults
Association of chronic illness with gender and depression
Since our study found that depression in older adults is associated with the chronic disease comorbid state, we further analysed the various types of comorbid conditions in older adults (table 4). Through the analysis, we found that among the included older people, women had a higher chance of developing dyslipidaemia, and the difference was statistically significant (p<0.05). Similarly, women have a higher chance of heart attack, stomach disease and emotional problems (p<0.05). We also compared and analysed with or without depression and found that the depression group was more likely to have hypertension, dyslipidaemia, chronic lung diseases, heart attack, stroke, stomach disease and memory-related disease (p<0.05).
Association of chronic illness with gender and depression
Univariable logistic regression analysis and multivariable logistic regression analysis of depression and related variables
We analysed the data by univariable logistic regression analysis and multivariable logistic regression analysis (table 5). Through univariable logistic regression analysis, we found that gender, marital status and chronic disease comorbid state are related to depression in older adults (OR>1) while grip strength, sleep duration, education level and alcohol consumption are also connected with depression in older adults (OR<1). However, we adjusted for gender, grip strength, sleep, education, marital status, alcohol consumption, comorbid chronic disease by using multivariable logistic regression analysis (figure 2) and we found that grip strength was still connected with the risk of depression in the elderly (0.971 (95% CI 0.959 to 0.984)). Sleep (0.827 (95% CI 0.785 to 0.872) and education level (0.790 (95% CI 0.662 to 0.942) were also related to the risk of depression in the elderly. Concomitant chronic diseases could affect the risk of depression in the elderly (1.455 (95% CI 1.243 to 1.703)).
Multivariable logistic regression analysis of depression and related variables.
Univariable logistic regression analysis and multivariable logistic regression analysis of depression and related variables
Discussion
With the acceleration of the ageing of the population, the issue of healthy ageing has been put on the agenda. The expectation of healthy ageing is that the elderly can not only increase their life expectancy but also live healthier and happier lives.15 The current increase in chronic and degenerative diseases is a major epidemiological trend, and the current challenges faced by older people are chronic diseases and age-related problems.16 The coexistence of multiple chronic diseases is a common problem in the elderly, and it also carries a burden due to the simultaneous taking of multiple drugs.17 Chronic diseases are considered to be one of the most expensive health conditions in the USA, such as cardiovascular disease, diabetes, cancer, chronic respiratory diseases, etc, which can lead to the loss of body function in the elderly.3 Studies have found that some chronic diseases can coexist with anxiety and depression and contribute to higher rates of hospitalisation.18 Therefore, we assess the chronic disease situation and the correlation with depression in the elderly in China.
Our study found that 28.78% of elderly over the age of 60 had depressive symptoms. Older women had a higher chance of developing depression, and gender correlated with depression scores. In univariable regression analysis, it was found that gender was one of the risk factors for depression in the elderly, but no statistical significance was found after multivariable regression analysis. Studies have found that older women are more likely to have mental disorders than older men, but data on older ages over 80 years are lacking.19 Our study included older people over 80 years of age, and the results still suggest that women are more likely to develop geriatric depression, but gender is not a risk factor, possibly due to more factors interfering with depression. Studies have also suggested that men are a protective factor against depression, but this trend weakens with increasing life expectancy.20 Our study included older people, and it may be for this reason that the analysis concluded that men were less likely to have depression in the elderly.
The researchers found that women had a higher rate of depression which peaked at 40–49 years old.21 Some researchers have analysed the elderly over 65 years old in Canada and found that from 65 years old to 80 years old, the probability of depression is reduced.22 Our study showed no relationship between age and depression. Our study found that grip strength is also correlated with depression scores in older adults, and regression analysis suggested that higher grip strength is less likely to develop depression in older adults. Grip strength is considered to be an indispensable and important marker in the elderly, which can reflect the overall strength, nutritional status and cognitive status of the elderly to a certain extent and is also believed to be associated with depression.23 The study found an inverse association between grip strength and depression and anxiety,24 consistent with our results.
Regarding sleep duration, we found differences between men and women, with men sleeping longer and the depression group sleeping relatively shortly. Therefore, there is a correlation between sleep duration and depression score, and multivariable regression analysis suggests that prolonged sleep duration may reduce the occurrence of depression to some extent. In addition, education level is also associated with depression, and the lower the education level, the higher the chance of developing depression in old age. Scholars have proposed that sleep disorders are risk factors that promote the development of depression and persistent symptoms.25 Studies have found that chronic sleep deprivation can lead to depression, and the mechanism is related to brain neurotrophic factor, mainly manifested by downregulation of hippocampal neurotrophic factor expression and disruption of frontal cortex expression.26 A study in the USA found that adults sleeping too little or too long were associated with episodes of depression.27 Our study also further confirms the relationship between sleep duration and depression in older adults. In terms of educational attainment, we found that the more educated people over 60 years old, the less likely they are to develop depression. However, a Brazilian study concluded that individuals with higher levels of education had a higher chance of developing psychomotor disorders.28 We believe that such differences may be related to the age group of the study samples and are subject to further research to confirm this. Studies have found that unmarried, divorced or separated and widowed are important for depression scores.29 The researchers believe that divorce/widowhood/separation are associated with an increased risk of perceived depression.30 It can be seen that in adults and the elderly, marital status is an important factor affecting depression.
Multidisease coexistence is considered to be the coexistence of two or more chronic diseases and has become a priority for global health events.31 A cross-sectional study in India suggests that it is common for multiple diseases to coexist in a person.32 Our study found that women are more likely than men to have multiple chronic conditions, and depressed people are also more likely to have multiple chronic conditions. Moreover, the coexistence of multiple chronic diseases is one of the risk factors for depression, and with the increase in coexisting chronic diseases, the incidence of depression in the elderly will also increase. Research in India has suggested that depression in adults is linked to a wide range of health problems, with people with more illnesses having a higher chance of depression.33 Although the participants were different, our study only looked at people over 60 years old, but the results were consistent. A 10-year follow-up study in middle-aged and older adults found that the risk of mild and severe depression increases significantly as chronic disease increases,34 which is consistent with our findings. The occurrence of chronic diseases is distressing on the one hand, and it is also possible to cause certain functional limitations, so with the occurrence of chronic diseases, an increase in depressive symptoms is to be expected.35 Some researchers have also found that depression is related to a variety of chronic diseases and is the core of the coexistence network of multiple chronic diseases, so it is proposed that people at risk of chronic diseases need to pay attention to early screening for depression.36 However, some researchers have found that patients with low self-management strategies have a higher chance of depression, and propose that no matter how many chronic diseases exist at the same time, good self-management can effectively reduce the incidence of depression.37 Therefore, based on our research, combined with relevant literature, we believe that chronic disease is a risk factor for depression in old age, and the increase in chronic disease, will lead to an increase in the incidence of depression. Older people at risk of chronic diseases should be screened for depression as soon as possible and managed well.
The data in this study were from well-known databases, and the content was detailed and rich, and the results of statistical analysis were reliable. Our study still has certain limitations: (1) This study is a cross-sectional study and does not really clarify cause and effect. (2) The diagnosis of depression is based on a simple scale, so the diagnosis is not accurate. (3) There was no in-depth analysis of the relationship between various chronic diseases and depression. In the following research, I hope to form prospective studies to further clarify the correlation between various chronic diseases and depression and hope to clarify the relevant mechanisms through further research.
Conclusion
The coexistence of multiple chronic diseases is very common in the elderly, and depression is also high in the elderly. The coexistence of multiple chronic diseases is more common in older women and older depressed people. Among them, increased grip strength, long sleep time and high education level are protective for geriatric depression while chronic diseases are risk factors for geriatric depression. With the increase in the number of chronic diseases, the risk of depression in old age is also significantly increased.
Data availability statement
Data are available on reasonable request. The data can be searched online or by contacting the author.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and ethical approval for all the CHARLS waves was granted from the Institutional Review Board at Peking University. The IRB approval number for the main household survey, including anthropometrics, is IRB00001052-11015; the IRB approval number for biomarker collection is IRB00001052-11014. Participants gave informed consent to participate in the study before taking part.
References
Footnotes
Contributors GC wrote the article and guided. LZ, ZZ and YB did the analysis. GC is responsible for the overall content as the guarantor.
Funding Zhejiang Provincial Clinical Research Program of Traditional Chinese Medicine (2024ZL103).
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.