Community support, social isolation and older adults' life satisfaction: evidence from a national survey in China.

OBJECTIVES: Despite the recognized importance of community social service and community built facility for enhancing older adults' life satisfaction, the mechanisms underlying their relationship have not been thoroughly examined. This study aims to complement the existing knowledge by investigating the mediating role of social disconnectedness and loneliness in the association between community support and life satisfaction among older adults. METHODS: Using data from the 2018 China Longitudinal Aging Social Survey, the study analyzes responses from 9,874 Chinese older adults (mean age = 71.30 years, SD = 7.30). We conducted descriptive statistics and Pearson's correlation to explore the variables. This study also used Mplus 8.0 to conduct a path analysis model that evaluated both the direct and indirect effects of community social service and built facility on life satisfaction. Social disconnectedness and loneliness were included as mediating variables in this model. RESULTS: The present study results show that both community social service and community built facility are positively associated with life satisfaction among older adults, and community social service is more imporatant for enhancing the life satisfaction. In addition, these associations are mediated by social disconnectedness and loneliness. CONCLUSION: Our research suggests that strengthening community social service programs and improving the built environment can reduce social disconnectedness and loneliness among older adults, ultimately enhancing their life satisfaction. Specifically, policymakers can invest in targeted interventions to enhance social connectedness and reduce loneliness, with the goal of improving the overall well-being of older adults.

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health.

Importance: Social determinants of health (SDOH) influence child health. However, most previous studies have used individual, small-set, or cherry-picked SDOH variables without examining unbiased computed SDOH patterns from high-dimensional SDOH factors to investigate associations with child mental health, cognition, and physical health. Objective: To identify SDOH patterns and estimate their associations with children's mental, cognitive, and physical developmental outcomes. Design, Setting, and Participants: This population-based cohort study included children aged 9 to 10 years at baseline and their caregivers enrolled in the Adolescent Brain Cognitive Development (ABCD) Study between 2016 and 2021. The ABCD Study includes 21 sites across 17 states. Exposures: Eighty-four neighborhood-level, geocoded variables spanning 7 domains of SDOH, including bias, education, physical and health infrastructure, natural environment, socioeconomic status, social context, and crime and drugs, were studied. Hierarchical agglomerative clustering was used to identify SDOH patterns. Main Outcomes and Measures: Associations of SDOH and child mental health (internalizing and externalizing behaviors) and suicidal behaviors, cognitive function (performance, reading skills), and physical health (body mass index, exercise, sleep disorder) were estimated using mixed-effects linear and logistic regression models. Results: Among 10 504 children (baseline median [SD] age, 9.9 [0.6] years; 5510 boys [52.5%] and 4994 girls [47.5%]; 229 Asian [2.2%], 1468 Black [14.0%], 2128 Hispanic [20.3%], 5565 White [53.0%], and 1108 multiracial [10.5%]), 4 SDOH patterns were identified: pattern 1, affluence (4078 children [38.8%]); pattern 2, high-stigma environment (2661 children [25.3%]); pattern 3, high socioeconomic deprivation (2653 children [25.3%]); and pattern 4, high crime and drug sales, low education, and high population density (1112 children [10.6%]). The SDOH patterns were distinctly associated with child health outcomes. Children exposed to socioeconomic deprivation (SDOH pattern 3) showed the worst health profiles, manifesting more internalizing (ß = 0.75; 95% CI, 0.14-1.37) and externalizing (ß = 1.43; 95% CI, 0.83-2.02) mental health problems, lower cognitive performance, and adverse physical health. Conclusions: This study shows that an unbiased quantitative analysis of multidimensional SDOH can permit the determination of how SDOH patterns are associated with child developmental outcomes. Children exposed to socioeconomic deprivation showed the worst outcomes relative to other SDOH categories. These findings suggest the need to determine whether improvement in socioeconomic conditions can enhance child developmental outcomes.

COVID-19 Policies, Pandemic Disruptions, and Changes in Child Mental Health and Sleep in the United States.

Importance: The adverse effects of COVID-19 containment policies disrupting child mental health and sleep have been debated. However, few current estimates correct biases of these potential effects. Objectives: To determine whether financial and school disruptions related to COVID-19 containment policies and unemployment rates were separately associated with perceived stress, sadness, positive affect, COVID-19-related worry, and sleep. Design, Setting, and Participants: This cohort study was based on the Adolescent Brain Cognitive Development Study COVID-19 Rapid Response Release and used data collected 5 times between May and December 2020. Indexes of state-level COVID-19 policies (restrictive, supportive) and county-level unemployment rates were used to plausibly address confounding biases through 2-stage limited information maximum likelihood instrumental variables analyses. Data from 6030 US children aged 10 to 13 years were included. Data analysis was conducted from May 2021 to January 2023. Exposures: Policy-induced financial disruptions (lost wages or work due to COVID-19 economic impact); policy-induced school disruptions (switches to online or partial in-person schooling). Main Outcomes and Measures: Perceived stress scale, National Institutes of Health (NIH)-Toolbox sadness, NIH-Toolbox positive affect, COVID-19-related worry, and sleep (latency, inertia, duration). Results: In this study, 6030 children were included in the mental health sample (weighted median [IQR] age, 13 [12-13] years; 2947 [48.9%] females, 273 [4.5%] Asian children, 461 [7.6%] Black children, 1167 [19.4%] Hispanic children, 3783 [62.7%] White children, 347 [5.7%] children of other or multiracial ethnicity). After imputing missing data, experiencing financial disruption was associated with a 205.2% [95% CI, 52.9%-509.0%] increase in stress, a 112.1% [95% CI, 22.2%-268.1%] increase in sadness, 32.9% [95% CI, 3.5%-53.4%] decrease in positive affect, and a 73.9 [95% CI, 13.2-134.7] percentage-point increase in moderate-to-extreme COVID-19-related worry. There was no association between school disruption and mental health. Neither school disruption nor financial disruption were associated with sleep. Conclusions and Relevance: To our knowledge, this study presents the first bias-corrected estimates linking COVID-19 policy-related financial disruptions with child mental health outcomes. School disruptions did not affect indices of children's mental health. These findings suggest public policy should consider the economic impact on families due to pandemic containment measures, in part to protect child mental health until vaccines and antiviral drugs become available.

Expenditure patterns among low-income families in China: Contributing factors to child development and risks of suicidal ideation.

Low-income families in urbsan China have been benefited from the Minimum Living Standard Guarantee Assistance (dibao) policy since 1999. However, little is known about how child-specific family expenditure patterns impact child outcomes. Based on 2531 children aged 8-16 years from the National Survey of Social Policy Support System for Low-Income Families in Urban and Rural China, this is the first study of its kind to (1) identify family expenditure patterns (food, apparel, housing, transportation, pocket money, after-school education, and other educational resources) among low-income families and (2) examine their relationship with child suicide risks and developmental outcomes (academic performance, mental health, and physical health) by sex and across the dibao and marginalized families (i.e., without dibao). Latent profile analysis identified two patterns. Profile 1 (97.59%) showed low expenditure on children. Profile 2 (2.41%) prioritized expenditure in after-school programs. Mixed-effects logistic regression showed male children from marginalized families in Profile 1 are 11 times (95% confidence interval 1.10-109.52) more likely to think about suicide than female children from dibao families in Profile 2. Social policies and interventions promoting educational expenditure support and addressing the social determinants of health have the potential to reduce child suicide and improve child developmental outcomes among the urban poor.

Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu.

China's migrant population has significantly contributed to its economic growth; however, the impact on the well-being of left-behind children (LBC) has become a serious public health problem. Text mining is an effective tool for identifying people's mental state, and is therefore beneficial in exploring the psychological mindset of LBC. Traditional data collection methods, which use questionnaires and standardized scales, are limited by their sample sizes. In this study, we created a computational application to quantitively collect personal narrative texts posted by LBC on Zhihu, which is a Chinese question-and-answer online community website; 1475 personal narrative texts posted by LBC were gathered. We used four types of words, i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words, all of which have been associated with depression and suicidal ideations in the Chinese Linguistic Inquiry Word Count (CLIWC) dictionary. We conducted vocabulary statistics on the personal narrative texts of LBC, and bilateral t-tests, with a control group, to analyze the psychological well-being of LBC. The results showed that the proportion of words related to depression and suicidal ideations in the texts of LBC was significantly higher than in the control group. The differences, with respect to the four word types (i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words), were 5.37, 2.99, 2.65, and 2.00 times, respectively, suggesting that LBC are at a higher risk of depression and suicide than their counterparts. By sorting the texts of LBC, this research also found that child neglect is a main contributing factor to psychological difficulties of LBC. Furthermore, mental health problems and the risk of suicide in vulnerable groups, such as LBC, is a global public health issue, as well as an important research topic in the era of digital public health. Through a linguistic analysis, the results of this study confirmed that the experiences of left-behind children negatively impact their mental health. The present findings suggest that it is vital for the public and nonprofit sectors to establish online suicide prevention and intervention systems to improve the well-being of LBC through digital technology.

Social service utilization, sense of community, family functioning and the mental health of new immigrant women in Hong Kong.

Drawing upon a sample of 296 new immigrant women in Hong Kong, this study investigated how social service utilization, family functioning, and sense of community influenced the depressive symptoms of new immigrant women. Results of the structural equation modeling suggested that family functioning and sense of community were both significantly and negatively associated with the depression of new immigrant women. Utilization of community services also influenced the depression of immigrant women indirectly through the mediating effect of sense of community. Implications of the research findings for mental health intervention were discussed.

Sense of community, neighboring, and social capital as predictors of local political participation in China.

This study examines the state of sense of community, neighboring behavior, and social capital in the People's Republic of China, and explores their ability to predict local political participation, in the form of voting in elections for Urban Resident/Rural Villager Committees. Using a nationally representative survey, rural, older and married residents and those with a primary or high school education and higher perceived socio-economic status are more likely to participate. In rural areas, men are more likely than women to vote. For urban residents, knowing one's neighbors is more important whereas in rural areas, neighboring behavior is more important, but both predict voting. Social capital does not generally predict Chinese people's local political participation. Western definitions of social capital derived from theories about networking, bonding and bridging ties may be too culturally individualistic for China, whose collectivist society and agrarian kinship networks predate Communism. Simply knowing and helping one's neighbors, rather than more abstract notions of trust, reciprocity or membership, may lead to the development of local democracy.

Racial and ethnic variations in caregiver service use.

OBJECTIVE: This article examines whether race and ethnicity contribute to the differential use of caregiver support services, when controlling for caregiver and care recipient characteristics, as represented by predisposing, enabling, and need factors included in the Behavioral Model of Health Services Use. METHODS: The study includes 1,508 individuals who provide care to an ill or disabled adult aged 50 or older, identified through a random digit dial telephone survey of California households. Logistic regression analysis is utilized to examine factors that predict use of caregiver support services. RESULTS: Race and ethnicity do not contribute significantly to caregiver service utilization, when controlling for relevant covarying factors such as age, education, emotional support, family contribution, care recipient service use, and care recipient impairment. A significant interaction exists between ethnicity and family closeness, with reduced rates of service use among Asian and Pacific Island caregivers whose families are brought closer by the caregiving experience. DISCUSSION: These findings suggest that racial and ethnic disparities in caregiver service use found at the bivariate level are attributable to covarying predisposing, enabling, and need factors. Further research and theoretical development are suggested to clarify the impact of sociocultural factors on caregiver service use.

The status of low-income neighborhoods in the post-welfare reform environment: mapping the relationship between poverty and place.

It has long been recognized that children and adults living in poverty are at risk for a number of negative outcomes. As inequality in the distribution of wealth, income and opportunity has grown in the U.S. during the post-welfare reform era, impoverished children and their families have tended to become increasingly concentrated in urban low-income neighborhoods. Research evidence demonstrates that living in these neighborhoods affects family well-being in several key areas: economic and employment opportunity, health and mental health condition, crime and safety, and children's behavioral and educational outcomes. Using the neighborhood indicator approach, public and nonprofit social service agencies will be better positioned to develop a comprehensive and integrated service delivery model at the neighborhood level by using neighborhood assessment to locate services and utilize neighborhood intervention strategies.

Racial/ethnic disparities in the use of mental health services in poverty areas.

OBJECTIVES: This study examined racial/ethnic disparities in mental health service access and use at different poverty levels. METHODS: We compared demographic and clinical characteristics and service use patterns of Whites, Blacks, Hispanics, and Asians living in low-poverty and high-poverty areas. Logistic regression models were used to assess service use patterns of minority racial/ethnic groups compared with Whites in different poverty areas. RESULTS: Residence in a poverty neighborhood moderates the relationship between race/ethnicity and mental health service access and use. Disparities in using emergency and inpatient services and having coercive referrals were more evident in low-poverty than in high-poverty areas. CONCLUSIONS: Neighborhood poverty is a key to understanding racial/ethnic disparities in the use of mental health services.