Exposure to ambient air pollution with depressive symptoms and anxiety symptoms among adolescents: A national population-based study in China

Air and Noise Pollution Exposure in Early Life and Mental Health From Adolescence to Young Adulthood

Importance

Growing evidence associates air pollution exposure with various psychiatric disorders. However, the importance of early-life (eg, prenatal) air pollution exposure to mental health during youth is poorly understood, and few longitudinal studies have investigated the association of noise pollution with youth mental health.

Objectives

To examine the longitudinal associations of air and noise pollution exposure in pregnancy, childhood, and adolescence with psychotic experiences, depression, and anxiety in youths from ages 13 to 24 years.

Design, Setting, and Participants

This cohort study used data from the Avon Longitudinal Study of Parents and Children, an ongoing longitudinal birth cohort founded in 1991 through 1993 in Southwest England, United Kingdom. The cohort includes over 14 000 infants with due dates between April 1, 1991, and December 31, 1992, who were subsequently followed up into adulthood. Data were analyzed October 29, 2021, to March 11, 2024.

Exposures

A novel linkage (completed in 2020) was performed to link high-resolution (100 m2) estimates of nitrogen dioxide (NO2), fine particulate matter under 2.5 μm (PM2.5), and noise pollution to home addresses from pregnancy to 12 years of age.

Main outcomes and measures

Psychotic experiences, depression, and anxiety were measured at ages 13, 18, and 24 years. Logistic regression models controlled for key individual-, family-, and area-level confounders.

Results

This cohort study included 9065 participants who had any mental health data, of whom (with sample size varying by parameter) 51.4% (4657 of 9051) were female, 19.5% (1544 of 7910) reported psychotic experiences, 11.4% (947 of 8344) reported depression, and 9.7% (811 of 8398) reported anxiety. Mean (SD) age at follow-up was 24.5 (0.8) years. After covariate adjustment, IQR increases (0.72 μg/m3) in PM2.5 levels during pregnancy (adjusted odds ratio [AOR], 1.11 [95% CI, 1.04-1.19]; P = .002) and during childhood (AOR, 1.09 [95% CI, 1.00-1.10]; P = .04) were associated with elevated odds for psychotic experiences. Pregnancy PM2.5 exposure was also associated with depression (AOR, 1.10 [95% CI, 1.02-1.18]; P = .01). Higher noise pollution exposure in childhood (AOR, 1.19 [95% CI, 1.03-1.38]; P = .02) and adolescence (AOR, 1.22 [95% CI, 1.02-1.45]; P = .03) was associated with elevated odds for anxiety.

Conclusions and Relevance

In this longitudinal cohort study, early-life air and noise pollution exposure were prospectively associated with 3 common mental health problems from adolescence to young adulthood. There was a degree of specificity in terms of pollutant-timing-outcome associations. Interventions to reduce air and noise pollution exposure (eg, clean air zones) could potentially improve population mental health. Replication using quasi-experimental designs is now needed to shed further light on the underlying causes of these associations.

Analysis of the situations and influencing factors of public anxiety in China: based on Baidu index data

Background

Anxiety disorders have emerged as one of the most prevalent mental health problems and health concerns. However, previous research has paid limited attention to measuring public anxiety from a broader perspective. Furthermore, while we know many factors that influence anxiety disorders, we still have an incomplete understanding of how these factors affect public anxiety. We aimed to quantify public anxiety from the perspective of Internet searches, and to analyze its spatiotemporal changing characteristics and influencing factors.

Methods

This study collected Baidu Index from 2014 to 2022 in 31 provinces in mainland China to measure the degree of public anxiety based on the Baidu Index from 2014 to 2022. The spatial autocorrelation analysis method was used to study the changing trends and spatial distribution characteristics of public anxiety. The influencing factors of public anxiety were studied using spatial statistical modeling methods.

Results

Empirical analysis shows that the level of public anxiety in my country has continued to rise in recent years, with significant spatial clustering characteristics, especially in the eastern and central-southern regions. In addition, we constructed ordinary least squares (OLS) and geographically weighted regression (GWR) spatial statistical models to examine the relationship between social, economic, and environmental factors and public anxiety levels. We found that the GWR model that considers spatial correlation and dependence is significantly better than the OLS model in terms of fitting accuracy. Factors such as the number of college graduates, Internet traffic, and urbanization rate are significantly positively correlated with the level of public anxiety.

Conclusion

Our research results draw attention to public anxiety among policymakers, highlighting the necessity for a more extensive examination of anxiety issues, especially among university graduates, by the public and relevant authorities.

(In)Congruence in Perceived Mother-child Cohesion and Informants' Depressive Symptoms: A Dyadic Response Surface Analysis

Mother-child cohesion, reflecting the emotional connection between mothers and children, is a protective factor for individuals' mental health. The Modified Operations Triad Model suggests that children and mothers hold either congruent or incongruent views of their perceived cohesion, which reflects family functioning and is an indication of future mental health outcomes for family members. Despite increasing research on the impact of (in)congruence in perceived family functioning on children's mental health, few studies concurrently address the mental health of both mothers and children, overlooking their interdependence. This longitudinal study with multi-informant reports explored the long-term and developmental effects of (in)congruence in perceived mother-child cohesion on informants' depressive symptoms. A total of 577 families participated at the first time point, comprising 577 children (52.34% girls, Mage = 10.11 years) and 577 mothers (Mage = 37.32 years). The Dyadic Response Surface Analysis revealed that mother-child congruence at high levels of cohesion (versus low levels) predicted fewer depressive symptoms in mothers and children after three and nine months, as well as decreased depressive symptoms over nine months. Children who reported higher levels of cohesion than their mothers experienced fewer depressive symptoms after three months. Mothers with higher levels of cohesion than their children reported fewer depressive symptoms after three months. The current findings emphasize the importance of identifying and resolving discrepancies in perceived mother-child cohesion between mothers and children to promote a healthy family environment.