Prevalence and related influencing factors of depressive symptoms among empty-nest elderly in Shanxi, China

2019 ◽  
Vol 245 ◽  
pp. 750-756 ◽  
Author(s):  
Chichen Zhang ◽  
Yaqing Xue ◽  
Huining Zhao ◽  
Xiao Zheng ◽  
Ruifang Zhu ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Influencing Factors ◽  
Empty Nest

scholarly journals Prevalence and Influencing Factors of Anxiety and Depression Symptoms Amongst Surgical Nurses During COVID-19 Pandemic: A Large-Scale Cross-Sectional Study

2020 ◽  
Author(s):  
Chun-Xia Ren ◽  
De-Cun Zhou ◽  
Yin-Guang Fan ◽  
Bao-Zhu Li ◽  
Wan-Fei Zhang ◽  
...  
Keyword(s):  
Social Support ◽  
Depressive Symptoms ◽  
Influencing Factors ◽  
Rating Scale ◽  
Depression Scale ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Cross Sectional ◽  
Self Rating ◽  
Surgical Nurses

Abstract BackgroundThe outbreak of novel 2019 coronavirus disease (COVID-19) has imposed an enormous physical and psychological pressure on people across the world. This study focused on evaluating the prevalence and influencing factors of anxiety and depression symptoms in surgical nurses during the epidemic in China. MethodA cross-sectional, multicenter quantitative study was conducted in Anhui province (China) from March 3, 2020 to March 19, 2020, with a questionnaire package which consisted of general information questionnaire，Zung's self-rating anxiety scale (SAS), Zung's self-rating Depression Scale (SDS) and social support rating scale (SSRS). A total of 3600 surgical nurses participated in the survey by Wechat and QQ. Data were analysed using multiple linear regression models. ResultsA total of 3492 surgical nurses from 12tertiary hospitals and 12 secondary hospitals in one province of mainland China completed the survey. The prevalence rates of anxiety symptoms and depressive symptoms were 24.83% and 22.39%, respectively. The average level of anxiety and depression of surgical nurses were higher than that of the Chinese norm (P< 0.05).Levels of social support for surgical nurses were significantly negatively associated with the degree of anxiety (r = -0.630, P < 0.001) and depression (r = -0.578, P < 0.001). Fertility status (β = 1.469, P = 0.003), hospital (β = -0.611, P < 0.001), participation in care for COVID-19 patients (β = 2.229, P < 0.001), likelihood of being infected with COVID-19 (β = 1.146, P < 0.001), social support (β = -0.623, P < 0.001) were significantly influencing surgical nurses’ anxiety degree. Similarly, these characteristics were significantly associated with the odds of experiencing depression symptoms in surgical nurses. Divorce and widowed surgical nurses (β = -2.654, P < 0.001) were significantly more likely to experience depressive symptoms than single nurses. ConclusionIn this survey, we found that the surgical nurses had high anxiety and depression symptoms during the COVID-19 outbreak in China. The findings suggest that targeted psychological interventions to promote the mental health of surgical nurses with psychological problems need to be immediately implemented.

scholarly journals Loneliness and depression among rural empty-nest elderly adults in Liuyang, China: a cross-sectional study

BMJ Open ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. e016091 ◽  
Author(s):  
Guojun Wang ◽  
Mi Hu ◽  
Shui-yuan Xiao ◽  
Liang Zhou
Keyword(s):  
Older Adults ◽  
Depressive Symptoms ◽  
Rural Elderly ◽  
Elderly Adults ◽  
Empty Nest ◽  
Major Depressive ◽  
Cross Sectional ◽  
Cohen’S D ◽  
Major Depressive Episodes ◽  
Depressive Episodes

ObjectiveTo compare loneliness, depressive symptoms and major depressive episodes between empty-nest and not-empty-nest older adults in rural areas of Liuyang city, Hunan, China.MethodsA cross-sectional multi-stage random cluster survey was conducted from November 2011 to April 2012 in Liuyang, China. A total of 839 rural older residents aged 60 or above completed the survey (response rate 97.6%). In line with the definition of empty nest, 25 participants who had no children were excluded from the study, while the remaining 814 elderly adults with at least one child were included for analysis. Loneliness and depressive symptoms in rural elderly parents were assessed using the short-form UCLA Loneliness Scale (ULS-6) and the Geriatric Depression Scale (GDS). Major depressive episodes were diagnosed using the Structured Clinical Interview for DSM-IV (SCID-I).ResultsSignificant differences were found between empty-nest and not-empty-nest older adults regarding loneliness (16.19±3.90 vs. 12.87±3.02, Cohen’s d=0.97), depressive symptoms (8.50±6.26 vs. 6.92±5.19, Cohen’s d=0.28) and the prevalence of major depressive episodes (10.1% vs. 4.6%) (all p<0.05). After controlling for demographic characteristics and physical disease, the differences in loneliness, depressive symptoms and major depressive episodes remained significant. Path analysis showed that loneliness mediated the relationship between empty-nest syndrome and depressive symptoms and major depressive episodes.ConclusionLoneliness and depression are more severe among empty-nest than not-empty-nest rural elderly adults. Loneliness was a mediating variable between empty-nest syndrome and depression.

scholarly journals Survey of Chinese persons managing depressive symptoms: Help-seeking behaviours and their influencing factors

2019 ◽  
Vol 95 ◽  
pp. 152127 ◽  
Author(s):  
Shu Fang ◽  
Xiao Qin Wang ◽  
Bing Xiang Yang ◽  
Xiu Jun Liu ◽  
Diana L. Morris ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Influencing Factors ◽  
Help Seeking

scholarly journals INFLUENCING FACTORS OF SUBJECTIVE AGE: FINDINGS FROM THE KUSATSU LONGITUDINAL STUDY ON AGING AND HEALTH

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S695-S696
Author(s):  
Tomoko Ikeuchi ◽  
Satoshi Seino ◽  
Yu Taniguchi ◽  
Miki Narita ◽  
Takumi Abe ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Longitudinal Study ◽  
Cognitive Function ◽  
Influencing Factors ◽  
Community Dwelling ◽  
Chronological Age ◽  
Social Changes ◽  
Subjective Age ◽  
Age Related ◽  
Years Of Schooling

Abstract Background: Subjective age (SA) has been found to be a biopsychosocial marker of aging, yet little is known about factors that influence SA development. This study examined factors influencing SA using longitudinal data of community-dwelling older Japanese. Methods: Data drawn from the Kusatsu Longitudinal Study were collected during annual health check-ups in 2017 and 2018 from participants (aged 65-95) who completed all the measurement items used for this analysis (N=981). SA was indexed by asking participants to specify in years how old they felt. Proportional discrepancy scores ((subjective age - chronological age)/chronological age ×100) were calculated to indicate younger or older SAs and used as a dependent variable. As influencing factors of SA, chronological age, sex, years of schooling, history of smoking, cognitive function (using MMSE scores, range 14-30 at baseline), depressive symptoms, physical function (gait speed), and social function (employment status) were examined. Analyses were performed with random-effects GLS regression models. Results: Significant partial regression coefficients were found for cognitive function (0.48%, CI: 0.18, 0.79), years of schooling (-0.42%, CI: -0.69, -0.15), depressive symptoms (0.32%, CI: 0.11, 0.53), and chronological age (-0.18%, CI: -0.30, -0.68). Implications: This study found that older age and longer years of schooling were associated with younger SA, while better cognition and depressive symptoms were linked to older SA. Better cognition being associated with older SA was inconsistent with existing studies. This may be due in part to the association of better cognition and the level of satisfaction influenced by awareness of age-related physical/social changes.

scholarly journals Comparison of Depressive Symptoms and Its Influencing Factors among the Elderly in Urban and Rural Areas: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

2021 ◽  
Vol 18 (8) ◽  
pp. 3886
Author(s):  
Haixia Liu ◽  
Xiaojing Fan ◽  
Huanyuan Luo ◽  
Zhongliang Zhou ◽  
Chi Shen ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Marital Status ◽  
Influencing Factors ◽  
Rural Areas ◽  
The Elderly ◽  
Education Level ◽  
Rural Elderly ◽  
Social Activities ◽  
Reported Health ◽  
Urban And Rural Areas

Depression amongst the elderly population is a worldwide public health problem, especially in China. Affected by the urban–rural dual structure, depressive symptoms of the elderly in urban and rural areas are significantly different. In order to compare depressive symptoms and its influencing factors among the elderly in urban and rural areas, we used the data from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS). A total of 7690 participants at age 60 or older were included in this study. The results showed that there was a significant difference in the prevalence estimate of depression between urban and rural elderly (χ2 = 10.9.76, p < 0.001). The prevalence of depression among rural elderly was significantly higher than that of urban elderly (OR-unadjusted = 1.88, 95% CI: 1.67 to 2.12). After adjusting for gender, age, marital status, education level, minorities, religious belief, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities and having income or not, the prevalence of depression in rural elderly is 1.52 times (OR = 1.52, 95% CI: 1.32 to 1.76) than that of urban elderly. Gender, education level, self-reported health, duration of sleep, chronic diseases were associated with depression in both urban and rural areas. In addition, social activities were connected with depression in urban areas, while minorities, marital status and having income or not were influencing factors of depression among the rural elderly. The interaction analysis showed that the interaction between marital status, social activities and urban and rural sources was statistically significant (divorced: coefficient was 1.567, p < 0.05; social activities: coefficient was 0.340, p < 0.05), while gender, education level, minorities, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities having income or not and urban and rural sources have no interaction (p > 0.05). Thus, it is necessary to propose targeted and precise intervention strategies to prevent depression after accurately identifying the factors’ effects.

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