Prevalence and recognition of depressive disorders among Chinese older adults receiving primary care: A multi-center cross-sectional study

et al. 2020

Preprint

Background: To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China.Methods: A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratiﬁed cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression.Results: Totally, 1,810 older people aged ≥ 60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22 - 0.48), social support (coefficient:0.18, 95% CI:0.07 - 0.28), social connection (coefficient: 0.76, 95% CI:0.53 - 1.00), trust (coefficient:0.62, 95% CI:0.33 - 0.92), cohesion (coefficient:0.31, 95% CI:0.17 - 0.44) and reciprocity (coefficient:0.30, 95% CI:0.11 - 0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities.Conclusions: Our study suggests that improving social capital could aid in the prevention of depression among older adults.

Section: Discussionmentioning

confidence: 99%

Association between social capital and depression among older people: evidence from Anhui Province, China

et al. 2020

Preprint

“…The GLM model can be specified as follows: where depression score is the dependent variable; α is the intercept; social capital dimensions refer to the above-mentioned six dimensions of social capital and β 1 is the corresponding coefficient; β 2 Confounders 1 + … + β n Confounders n indicate potential confounders in the model and their corresponding coefficients were β 2 … β n . In this model, we considered age, gender, body mass index, residence, living status, marriage status, education, smoking, and drinking status as potential confounders as previous studies have shown that these confounders are associated with depression in later life [ 4 , 5 , 22 , 23 ]. Other confounders such as shorter sleeping time and physical disability [ 23 ] were not included as no data was available for this study.…”

Section: Methodsmentioning

confidence: 99%

“…China has the highest number of older people in the world with a rapidly aging population [2], and geriatric depression remains a great public health challenge [3]. Recent evidence has suggested approximately one-fifth of older adults in China have depressive disorders [4]. Depression cannot only impair functional ability, reduce the quality of life and increase the mortality of older adults, but also inflicts a heavy economic burden upon older adults themselves, the society, and the healthcare system [5].…”

Section: Introductionmentioning

confidence: 99%

Association between social capital and depression among older people: evidence from Anhui Province, China

et al. 2020

BMC Public Health

Background To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China. Methods A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratified cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression. Results Totally, 1810 older people aged ≥60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22–0.48), social support (coefficient:0.18, 95% CI:0.07–0.28), social connection (coefficient: 0.76, 95% CI:0.53–1.00), trust (coefficient:0.62, 95% CI:0.33–0.92), cohesion (coefficient:0.31, 95% CI:0.17–0.44) and reciprocity (coefficient:0.30, 95% CI:0.11–0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities. Conclusions Our study suggests that improving social capital could aid in the prevention of depression among older adults.

“…where depression score is the dependent variable; is the intercept; social capital dimensions refer to the above-mentioned six dimensions of social capital and is the corresponding coe cient; (see Equation 2 in the Supplemental Files) indicate potential confounders in the model and their corresponding coe cients were . In this model, we considered age, gender, body mass index, residence, living status, marriage status, education, smoking, and drinking status as potential confounders as previous studies have shown that these confounders are associated with depression in later life [4,5,22,23]. Other confounders such as shorter sleeping time and physical disability [23] were not included as no data was available for this study.…”

Section: Discussionmentioning

confidence: 99%

Association between social capital and depression among older people: evidence from Anhui Province, China

et al. 2020

Preprint

Background: To examine the relationship between social capital and depression among community-dwelling older adults in Anhui Province, China.Methods: A cross-sectional study was conducted among older people selected from three cities of Anhui Province, China using a multi-stage stratiﬁed cluster random sampling method. Data were collected through questionnaire interviews and information on demographic characteristics, social capital, and depression was collected. The generalized linear model and classification and regression tree model were employed to assess the association between social capital and depression. Results: Totally, 1,810 older people aged ≥ 60 years were included in the final analysis. Overall, all of the social capital dimensions were positively associated with depression: social participation (coefficient: 0.35, 95% CI: 0.22 - 0.48), social support (coefficient:0.18, 95% CI:0.07 - 0.28), social connection (coefficient: 0.76, 95% CI:0.53 - 1.00), trust (coefficient:0.62, 95% CI:0.33 - 0.92), cohesion (coefficient:0.31, 95% CI:0.17 - 0.44) and reciprocity (coefficient:0.30, 95% CI:0.11 - 0.48), which suggested that older people with higher social capital had a smaller chance to develop depression. A complex joint effect of certain social capital dimensions on depression was also observed. The association with depression and the combinative effect of social capital varied among older adults across the cities. Conclusions: Our study suggests that improving social capital could aid in the prevention of depression among older adults.