Association between Socioeconomic Status and Longitudinal Sleep Quality Patterns Mediated by Depressive Symptoms.
Ontology highlight
ABSTRACT: Study objectives
We aimed to examine whether associations between socioeconomic status (SES) and longitudinal sleep quality patterns are mediated by depressive symptoms.Methods
We utilized data on 3,347 participants in the Korean Genome and Epidemiology Study aged 40-69 years at baseline from 2001-2002 who were followed up for 16 years. A group-based modeling approach was used to identify sleep quality trajectories using the Pittsburgh Sleep Quality Index (year 2, 6, 8, 10, and 12). Educational attainment (college graduated or less), monthly household income (≥$2,500 or less), and occupation (unemployed, manual labor, and professional labor) at baseline (year 0) were used for analyses. Depressive symptoms were assessed using Beck's Depression Inventory at year 4. Associations between SES and sleep quality patterns were examined using a multinomial logistic regression model. The mediation effect of depressive symptoms was further examined using PROC CAUSALMED.Results
We identified five distinct sleep quality trajectories: "normal-stable" (n=1,697), "moderate-stable" (n=1,157), "poor-stable" (n=320), "developing to poor" (n=84), and "severely poor-stable" (n=89). Overall, associations between SES levels and longitudinal sleep patterns were not apparent after full adjustment for socio-demographic and lifestyle factors measured at baseline. Depressive symptoms, however, tended to fully mediate associations between SES levels and sleep quality patterns (odds ratio range for indirect effects of depressive symptoms: for education, 1.05-1.17; for income, 1.05-1.15).Conclusion
A significant mediating role for depressive symptoms between SES levels and longitudinal sleep quality warrants consideration among mental health care professionals.
SUBMITTER: Lee GB
PROVIDER: S-EPMC8361348 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundPoor sleep quality and maternal mood disturbances are common during pregnancy and may play pivotal roles in the development of postpartum depression. We aim to examine the trajectories of sleep quality and mental health in women from early pregnancy to delivery and explore the mediating effects of sleep quality and mental status on the link between antepartum depressive symptoms and postpartum depressive symptoms.MethodsIn an ongoing prospective birth cohort, 1301 women completed questionnaires in the first, second and third trimesters and at 6 weeks postpartum. In each trimester, sleep quality was measured utilizing the Pittsburgh Sleep Quality Index (PSQI), and mental health was assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), the Self-Rating Anxiety Scale (SAS) and the Perceived Stress Scale (PSS). Postpartum depressive symptoms were evaluated by the Edinburgh Postnatal Depression Scale (EPDS). The bootstrap method was used to test the mediation effect.ResultsThe PSQI, CES-D, and SAS scores presented U-shaped curves across the antenatal period while the PSS score followed a descending trend. Antenatal sleep quality, depressive symptoms, anxiety symptoms and perceived stress all predicted depressive symptoms at 6 weeks postpartum. The influence of antepartum depressive symptoms on postpartum depressive symptoms was mediated by antepartum sleep quality and anxiety symptoms, which accounted for 32.14%, 39.25% and 31.25% in the first, second and third trimesters (P = 0.002, P = 0.001, P = 0.001, respectively).ConclusionsPoor sleep quality and anxiety symptoms in pregnancy mediated the relationship between antepartum depressive symptoms and postpartum depressive symptoms. Interventions aimed at detecting and managing sleep quality and elevated anxiety among depressed women in pregnancy warrant further investigation as preventative strategies for postpartum depression.
| S-EPMC9344627 | biostudies-literature
Project description:Background: Previous studies have suggested that sleep quality is associated with depressive symptoms. However, associations between overall sleep quality and depressive symptoms in Chinese resident physicians remain unclear. Therefore, we aimed to determine whether overall sleep quality is associated with depressive symptoms in Chinese resident physicians. Methods: This cross-sectional study included 1,230 resident physicians. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Logistic regression analysis was applied to estimate the associations between the PSQI and PHQ-9. Results: Among all participants, the prevalence of mild (PHQ-9 ≥ 5) and moderate or severe (PHQ-9 ≥ 10) depressive symptoms were 48.28 and 12.93%, respectively. PSQI score was positively associated with PHQ-9 score before and after adjustments of socio-demographic, behavioral, and psychologic confounding factors (all P < 0.0001). After adjustments, the regression coefficients (standard error) between PSQI scores and PHQ-9 scores were 0.95 (0.04), 0.88 (0.09), and 0.96 (0.05) in all participants, men, and women, respectively. Compared to physicians with good sleep quality (PSQI scores ≤ 5), the adjusted odds ratios (ORs) [95% confidence intervals (CIs)] for mild (PHQ-9 ≥ 5) and moderate or severe (PHQ-9 ≥ 10) depressive symptoms in physicians with poor sleep quality were 7.15 (5.44, 9.46) and 6.17 (4.03, 9.71) in all participants, respectively. Conclusions: Our findings suggest that poor sleep quality was associated with a higher prevalence of depressive symptoms in Chinese resident physicians.
| S-EPMC8206480 | biostudies-literature
Project description:BackgroundThe increasing prevalence of depressive symptoms has emerged as a critical public health issue globally, highlighting the need for analyses of the factors contributing to depressive symptoms within the Chinese population and the development of targeted recommendations for improving mental well-being. We aimed to explore the correlation between internet use and depressive symptoms and the role of socioeconomic inequalities in this association.MethodsWe included data on 8019 residents aged 18 years and above, which we retrieved from the 2018 and 2020 waves of the China Family Panel Studies. We used latent profile analysis to categorise individuals' internet usage patterns and multiple linear regression to determine their association with depressive symptoms.ResultsHigher socioeconomic status (SES) was associated with fewer depressive symptoms (τ = -0.08; 95% confidence interval (CI) = -0.36, -0.18). Individuals in the high-dependence group presented a greater likelihood of developing depressive symptoms (τ = 0.04; 95% CI = 0.007, 0.66). We observed no significant difference in the interaction effect between individual-level SES and the four patterns of internet usage. However, compared with urban-dwelling respondents, those in rural areas had a stronger association between internet usage patterns and depressive symptoms, especially those in the high-dependence group (τ = -0.07; 95% CI = -1.47, -0.20).ConclusionsOur findings indicate a significant association between depressive symptoms and internet usage patterns, indicating a need for interventions related to internet use, especially those targeted at reducing the risk of depressive symptoms in individuals of lower SES.
| S-EPMC11327895 | biostudies-literature
Project description:Low objective socioeconomic status (SES) has been correlated with poor physical and mental health among older adults. Some studies suggest that subjective SES is also important for ensuring sound physical and mental health among older adults. However, few studies have been conducted on the impact of both objective and subjective SES on mental health among older adults. This study examines whether objective or subjective SES is associated with depressive symptoms in older adults in Myanmar. This cross-sectional study, conducted between September and December, 2018, used a multistage sampling method to recruit participants from two regions of Myanmar, for face-to-face interviews. The Geriatric Depression Scale (GDS) was used to evaluate the depressive symptoms. Participants were classified as having no depressive symptom (GDS score <5) and having depressive symptoms (GDS score ≥5). Objective and subjective SES were assessed using the wealth index and asking participants a multiple-choice question about their current financial situation, respectively. The relationship between objective/subjective SES and depressive symptoms was examined using a multivariable logistic regression analysis. The mean age of the 1,186 participants aged 60 years and above was 69.7 (SD: 7.3), and 706 (59.5%) were female. Among them, 265 (22.3%) had depressive symptoms. After adjusting for objective SES and other covariates, only low subjective SES was positively associated with depressive symptoms (adjusted odds ratio, AOR: 4.18, 95% confidence interval, CI: 2.98-5.87). This association was stronger among participants in the rural areas (urban areas, AOR: 2.10, 95% CI: 1.08-4.05; rural areas, AOR: 5.65, 95% CI: 3.69-8.64). Subjective SES has a stronger association with depressive symptoms than objective SES, among older adults of the two regions in Myanmar, especially in the rural areas. Interventions for depression in older adults should consider regional differences in the context of subjective SES by reducing socioeconomic disparities among the communities.
| S-EPMC7842968 | biostudies-literature
Project description:Since the novel coronavirus disease 2019 (COVID-19) outbreak, adolescents' emerging mental health and behavior issues have been an international public health concern. This longitudinal study aimed to examine the situation of poor sleep quality, anxiety, and depressive symptoms among Chinese adolescents and to explore the associations between them before and during COVID-19. A total of 1,952 middle and high school students as eligible participants at baseline (pre-COVID-19, Wave 1; response rate: 98.79%), 1,831 eligible students were followed up at Wave 2 (October 2019 to December 2019, pre-COVID-19; retention rate: 93.80%), and 1,790 completed the follow-up at Wave 3 (during the COVID-19; retention rate: 97.80%). The mean age of the baseline students was 13.56 (SD: 1.46) years. The differences in anxiety and depressive symptoms between Wave 1, Wave 2, and Wave 3 were not statistically significant. The proportion of students with poor sleep quality increased over time, from Wave 1 (21.0%) to Wave 3 (26.0%, OR = 1.37, 95% CI = 1.17-1.60, P = 0.001) and from Wave 2 (21.9%) to Wave 3 (OR = 1.29, 95% CI = 1.11-1.51, P < 0.001). The cross-lagged generalized linear mixed models revealed that the concurrent and cross-lagged associations of poor sleep quality with anxiety symptoms across the three waves were significant (P < 0.05) and vice versa. Only a marginally significant positive cross-lagged association between poor sleep quality at Wave 2 and depressive symptoms at Wave 3 was found (standardized β estimate = 0.044, SE = 0.022, P = 0.045). Sleep quality was adversely affected during COVID-19, and the bidirectional associations of poor sleep quality with anxiety symptoms could not be neglected.
| S-EPMC8795609 | biostudies-literature
Project description:BackgroundThere was little evidence concerning the association of community socioeconomic status (SES) and the cross-level interaction between community- and individual-level SES with depressive symptoms in China. This study aimed to investigate the association of community-level SES with depressive symptoms among Chinese middle-aged and older people and to examine whether individual-level SES moderates this relationship.MethodsUsing data from the China Health and Retirement Longitudinal 2011-2018 Study, the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) short form was used to measure depressive symptoms in 35,546 Chinese individuals aged 45 years and older. Community SES was calculated as a sum of z scores of the average years of schooling and household income per capita, which were derived by aggregating the individual measures to the community level. Two-level hierarchical linear regression was used.ResultsCommunity SES was negatively related to CES-D-10 scores (coef=-0.438). A 1-SD increase in individual SES was associated with lower CES-D-10 scores (coef=-0.490). The cross-level interaction on individual- and community-level SES was significantly associated with depressive symptoms, indicating that with the increase of individual-level SES, the effect of community-level SES on depression decreases. Stratified analyses observed robust associations of community SES with CES-D scores between urban and rural residents.ConclusionsThis study showed that individuals who live in lower-SES communities had more severe depressive symptoms, particularly individuals with low SES. Additional attention should be given to the community socioeconomic context of middle-aged and older adults with lower SES, which may be helpful to reduce SES inequalities in depressive symptoms in China.
| S-EPMC9047288 | biostudies-literature
Project description:BackgroundDepressive symptoms has become an increasingly important public health issue, contributing to disability and disease burden around the world. Higher socioeconomic status (SES) has been found to be associated with lower prevalence of depression, but there are few studies about the older Chinese adults with long-term follow up and rigorous prospective design. Meanwhile, there is little conclusive evidence about the mechanisms through which SES influences the onset of depressive symptoms.ObjectiveTo prospectively examine the association of baseline socioeconomic factors with the risks of developing depressive symptoms during 7-year follow up in older Chinese population, and to study the mechanism by which SES impacts the prevalence of depressive symptoms.MethodsA total of 5677 individuals over 45 years who participated in an ongoing nationally representative prospective cohort study, China Health and Retirement Longitudinal Study, were free from depressive symptoms at baseline, and completed 7-year follow-up were included. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale score. Cox proportional hazards regression models were used to examine the association of SES and the incidence of depressive symptoms in 2011 to 2018. Generalized structural equation model was used to analyze the mediation effects of social support on the relation between SES and depressive symptoms.ResultsDuring the 7-year follow-up, 2398 (42.2%) cases were identified as depressive symptoms. Compared with the lowest level of household income, participants with the highest level of household income had a 20% reduction in risk (95% CI, 0.70-0.92, P < 0.001). Participants who had junior high school or above education had a 41% lower risk of depressive disorders compared with illiterate participants (95% CI, 0.52-0.69, P < 0.001). The relationship between SES and depressive symptoms was partially mediated by the social support, where higher social support was negatively associated with depressive symptoms. The proportion of mediation effect was even larger for women compared with men.ConclusionSocioeconomic factors were independently associated with the development of depressive symptoms, and the relationship was partially mediated by social support. Social support could be an effective intervention to alleviate the negative effects of lower SES on mental health. Multiple-level policies should precisely target low-SES groups, and timely intervention to promote social support for this group should be used to reduce the influence of depression on individuals, family as well as the whole society.
| S-EPMC8633935 | biostudies-literature
Project description:Sleep duration and quality have several effects on human health. Some previous studies have shown an association between sleep duration and quality and mental health, but the results of those studies were inconsistent. Additionally, studies on sleep duration and its impact on depressive symptoms specifically among young Chinese adults are limited. Hence, this study aimed to investigate the association between duration and quality of sleep and depressive symptoms among Chinese university students. We designed a cross-sectional study comprising 9,515 Chinese university students. Sleep duration and quality were assessed using a self-reported questionnaire. Depressive symptoms were assessed based on the Self-rating Depression Scale score. Logistic regression models were used to analyze the association between sleep duration and quality and depressive symptoms. The results showed that good sleep quality was associated with a lower prevalence of depressive symptoms. In the final adjusted model, the odds ratios and 95% confidence intervals for the prevalence of depressive symptoms in those with poor sleep quality compared with those with normal and good sleep quality were 0.88 (0.77, 1.01) and 0.82 (0.81, 0.96), respectively (p for trend = 0.014). Moreover, short sleep duration was associated with a higher prevalence of depressive symptoms based on the crude model and final adjusted model (p for trend = 0.048 and 0.042, respectively). Poor sleep quality and short sleep duration were associated with a higher prevalence of depressive symptoms in this study population. These results suggest that reduced sleep duration and quality may be risk factors for mental health disorders among university students.
| S-EPMC7485879 | biostudies-literature
Project description:BackgroundThe current study explored the association between green space and depression in a deprived, multiethnic sample of pregnant women, and examined moderating and mediating variables.Method7547 women recruited to the 'Born in Bradford' cohort completed a questionnaire during pregnancy. A binary measure of depressive symptoms was calculated using a validated survey. Two green space measures were used: quintiles of residential greenness calculated using the normalised difference vegetation index for three neighbourhood sizes (100, 300 and 500 m buffer zones around participant addresses); access to major green spaces estimated as straight line distance between participant address and nearest green space (>0.5 hectares). Logistic regression analyses examined relationships between green space and depressive symptoms, controlling for ethnicity, demographics, socioeconomic status (SES) and health behaviours. Multiplicative interactions explored variations by ethnic group, SES or activity levels. Mediation analysis assessed indirect effects via physical activity.ResultsPregnant women in the greener quintiles were 18-23% less likely to report depressive symptoms than those in the least green quintile (for within 100 m of green space buffer zone). The green space-depressive symptoms association was significant for women with lower education or who were active. Physical activity partially mediated the association of green space, but explained only a small portion of the direct effect.ConclusionsHigher residential greenness was associated with a reduced likelihood of depressive symptoms. Associations may be stronger for more disadvantaged groups and for those who are already physically active. Improving green space is a promising intervention to reduce risk of depression in disadvantaged groups.
| S-EPMC4789818 | biostudies-literature
Project description:ObjectivesThe purpose of this paper is to describe the prevalence of depressive symptoms in the Chinese labor force; to explore the relationship between depressive symptoms and socioeconomic status among the Chinese labor force, including both the structural determinants and the intermediary determinants of health inequities; and to identify vulnerable populations who would benefit from intervention measures.MethodsData were from the China Labor-Force Dynamics Survey (CLDS) 2016. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to assess depressive symptoms. The World Health Organization's theoretical framework of the social determinants of health was adopted to analyze the relationship between social determinants and depressive symptoms.ResultsOf the participants in the research from the Chinese labor force, 17.34% were identified as having depressive symptoms. Depression was significantly related to socioeconomic factors such as hukou status (p < 0.05 in the age < 45 model), education (p < 0.01 in all five models), employment (p < 0.05 in the male model), income (p < 0.05 in all five models), and self-assessed social class position (p < 0.01 in all five models). Intermediary factors were also related to depressive symptoms, such as gender (p < 0.001 in the overall model), age (p < 0.05 in the overall model), marriage (p < 0.05 in the female model), occupational exposure (p < 0.01 in the overall model), exercise (p < 0.05 in all five models), and health insurance (p < 0.05 in the overall model). The results showed that low socioeconomic status was associated with an increased risk of depression and there were some gradient changes in the distribution of depressive symptoms in socioeconomic status.ConclusionsThe findings showed that depression symptoms are significantly related to structural determinants and intermediary determinants in China's labor force. There are some gradient changes in the distribution of depressive symptoms among people of different socioeconomic status. Low socioeconomic status is associated with increased risk of depression. Women, older people, and single and divorced people are the relative vulnerable groups in China's labor force.
| S-EPMC9394851 | biostudies-literature