Exposure to air pollution and tobacco smoking and their combined effects on depression in six low- and middle-income countries

Lin, Hualiang; Guo, Yanfei; Kowal, Paul; Airhihenbuwa, Collins O.; Di, Qian; Zheng, Yang; Zhao, Xing; Vaughn, Michael G.; Howard, Steven W.; Schootman, Mario; Salinas‐Rodríguez, Aarón; Yawson, Alfred Edwin; Arokiasamy, Perianayagam; Manrique‐Espinoza, Betty; Biritwum, Richard; Rule, Stephen; Minicuci, Nadia; Naidoo, Nirmala; Chatterji, Somnath; Qian, Zhengmin; Ma, Wenjun; Wu, Fan

doi:10.1192/bjp.bp.117.202325

Cited by 73 publications

(47 citation statements)

References 26 publications

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“…Some studies failed to control for confounders that we considered likely to be particularly important (e.g., socioeconomic status/ deprivation, urbanity), as in the HUNT subcohort in Zijlema et al 2016, which included neither of these, or did so only partially (e.g., Kim and Kim 2017;Vert et al 2017). By contrast, several other studies controlled for socioeconomic status reasonably comprehensively (e.g., Kim et al 2016;Kioumourtzoglou et al 2017;Lin et al 2017a;Pun et al 2017;Power et al 2015). Some other potentially influential confounders were rarely included in analyses; for example, no included study adjusted for access to green space and only the substudies by Zijlema et al (2016) included noise.…”

Section: Study Qualitymentioning

confidence: 93%

“…Two eligible cohort studies (Kim et al 2016;Kioumourtzoglou et al 2017) and seven cross-sectional studies, including four substudies from Zijlema et al's paper [Kim and Kim 2017;Lin et al 2017a;Pun et al 2017;Vert et al 2017;Zijlema et al 2016 (Substudies A-D)] looked at associations between long-term PM exposure and depression. Outcomes included depression incidence (Kim et al 2016;Kioumourtzoglou et al 2017) and prevalence-based on either score on a screening instrument indicating moderate-to-severe depressive symptoms [Pun et al 2017;Zijlema et al 2016 (Substudies C and D)], or meeting diagnostic criteria on a validated diagnostic instrument [Zijlema et al 2016 (Substudies A and B)].…”

Section: Depressionmentioning

confidence: 99%

“…Outcomes included depression incidence (Kim et al 2016;Kioumourtzoglou et al 2017) and prevalence-based on either score on a screening instrument indicating moderate-to-severe depressive symptoms [Pun et al 2017;Zijlema et al 2016 (Substudies C and D)], or meeting diagnostic criteria on a validated diagnostic instrument [Zijlema et al 2016 (Substudies A and B)]. Another study (Lin et al 2017a) used the validated World Mental Health Survey version of the Composite International Diagnostic Interview (WMH-CIDI) and defined depression as any of the following: depressive symptoms within the past year, meeting diagnostic criteria for research (based on WMH-CIDI), and/or having received depression-related health care. This study partially involved self-report of diagnosis or health care utilization; however, we rated outcome assessment moderate because this selfreported outcome data was used alongside a valid and reliable instrument.…”

Section: Depressionmentioning

confidence: 99%

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Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis

Braithwaite

Zhang

Kirkbride

et al. 2019

Environ Health Perspect

438

220

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BACKGROUND: Particulate air pollution's physical health effects are well known, but associations between particulate matter (PM) exposure and mental illness have not yet been established. However, there is increasing interest in emerging evidence supporting a possible etiological link. OBJECTIVES: This systematic review aims to provide a comprehensive overview and synthesis of the epidemiological literature to date by investigating quantitative associations between PM and multiple adverse mental health outcomes (depression, anxiety, bipolar disorder, psychosis, or suicide). METHODS: We undertook a systematic review and meta-analysis. We searched Medline, PsycINFO, and EMBASE from January 1974 to September 2017 for English-language human observational studies reporting quantitative associations between exposure to PM <1:0 lm in aerodynamic diameter (ultrafine particles) and PM <2:5 and <10 lm in aerodynamic diameter (PM 2:5 and PM 10 , respectively) and the above psychiatric outcomes. We extracted data, appraised study quality using a published quality assessment tool, summarized methodological approaches, and conducted metaanalyses where appropriate. RESULTS: Of 1,826 citations identified, 22 met our overall inclusion criteria, and we included 9 in our primary meta-analyses. In our meta-analysis of associations between long-term (>6 months) PM 2:5 exposure and depression (n = 5 studies), the pooled odds ratio was 1.102 per 10-lg=m 3 PM 2:5 increase (95% CI: 1.023, 1.189; I 2 = 0:00%). Two of the included studies investigating associations between long-term PM 2:5 exposure and anxiety also reported statistically significant positive associations, and we found a statistically significant association between short-term PM 10 exposure and suicide in meta-analysis at a 0-2 d cumulative exposure lag. DISCUSSION: Our findings support the hypothesis of an association between long-term PM 2:5 exposure and depression, as well as supporting hypotheses of possible associations between long-term PM 2:5 exposure and anxiety and between short-term PM 10 exposure and suicide. The limited literature and methodological challenges in this field, including heterogeneous outcome definitions, exposure assessment, and residual confounding, suggest further high-quality studies are warranted to investigate potentially causal associations between air pollution and poor mental health.

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Section: Study Qualitymentioning

confidence: 93%

Section: Depressionmentioning

confidence: 99%

Section: Depressionmentioning

confidence: 99%

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Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis

Braithwaite

Zhang

Kirkbride

et al. 2019

Environ Health Perspect

438

220

View full text Add to dashboard Cite

show abstract

“…For instance, in China, the prevalence of smoking is 47.2% among men whereas 2.7% among women [41]. An interaction between smoking and PM 2.5 has been proposed earlier for different chronic diseases, including cardiovascular mortality [42] and depression [43]. Another possibility is the misclassi cation of real exposure to PM 2.5 .…”

Section: Discussionmentioning

confidence: 99%

Sex differences in Associations of Fine Particulate Matter with Non-accidental Deaths: An Ecological Time-Series Study

Xia

Fang

Montgomery

et al. 2020

Preprint

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Background: Sex differences in the impact of exposure to air pollution have been reported previously and epidemiological studies indicate that fine particulate matter (PM2.5) effects on non-accidental death are modified by sex, however, the results are not conclusive. This study aimed to investigate the sex difference in the effects of PM2.5 on non-accidental death, considering the nonlinear exposure-response relationships between PM2.5 and smoking and death.Methods: Information on daily non-accidental deaths, air pollution, meteorological data, and smoking prevalence between 1 January, 2012 and 31 December, 2014 was obtained in Shanghai, China. Constrained generalized additive models were used to assess the association of interaction between sex and daily PM2.5 concentrations with daily non-accidental deaths, adjusting for weather type and smoking rate. A two-week lag analysis was conducted as a sensitivity analysis.Results: During the study period, the total number of non-accidental deaths in Shanghai was 336,379, with a daily mean of 163 deaths and 144 deaths for men and women, respectively. The average daily concentration of PM2.5 in Shanghai was 55.0 µg/m3 during the same time period. Older people and men showed a higher risk for non-accidental death (risk ratio (RR) = 1.025 per year increase in age, 95% confidence interval (CI): 1.021 – 1.029, and RR = 0.892 for women, 95% CI: 0.802 – 0.993, respectively). Compared with men, the risk for non-accidental death in relation to increasing PM2.5 concentration was smaller in women (RR = 0.998, 95% CI: 0.996 – 1.000, per 10 µg increase in PM2.5 concentration. The difference is consistent during the two lag weeks and more obvious when adjusting for the interaction between PM2.5 concentration and smoking prevalence.Conclusion: The effects of PM2.5 on daily non-accidental death are different between men and women in Shanghai, China, and women tend to have a lower risk. The underlying mechanisms of the sex difference of PM2.5 effects on death need further investigation.

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“…In addition, social circumstances and natural environment all have significant effects on depression. The results from three studies suggest that long-term exposure to air pollution may increase the risk of depression [16][17][18]. In recent decades, more researchers have concerned on the impact of social circumstances on depression.…”

Section: Department Of Health Related Social and Behavioral Science mentioning

confidence: 99%

Macro- and individual-level influence factors of depression: multilevel cross-provinces comparison in China

Gao

2020

Preprint

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Background: Rapid social change has given rise to a general increase in psychological pressure, which lead to more and more Chinese people suffering from depression over the past 30 years. However, few literatures reported the influence of macro factors on depression of Chinese .The effects of macro-level and individual-level on depression of Chinese respondents aged 16-97 years were examined in this study. Methods: We conducted a multilevel analysis of the 2018 longitudinal follow up of the Chinese Family Panel Studies (CFPS), with 19072 respondents nested within the 25 Chinese provinces. Data for macro-level are extracted from National Bureau of Statistics of China, including three predictors: gross regional product (GRP) per capita, expenditure for social security and employment (ESSE) and rural and urban household income inequality. Depression is measured with the eight-item short version of the Center for Epidemiologic Studies Depression Scale (CES-D8). Result: We found that respondents who were female,30-59 years, divorced or widowed, less educated, rural residents, less body mass index (BMI) or had lower household income tended to report higher levels of depressive symptoms. After adjustment for individual-level features, a significant macro effect of provinces survives. The respondents who lived in province that were higher GRP, higher ESSE or smaller rural and urban household income inequality reported lower levels of depressive symptoms. Conclusions: Our results have demonstrated that depression is not fully explained by individual features. Economic social factors appear to have an impact on depression and have to be considered when planning for improved public depression. Meanwhile, our research also provides a reference for some provinces to further investigation and improvement of depression. Keywords: China; Individual-level; Macro-level; Influence factors; Depression; Multilevel analysis

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Exposure to air pollution and tobacco smoking and their combined effects on depression in six low- and middle-income countries

Cited by 73 publications

References 26 publications

Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis

Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis

Sex differences in Associations of Fine Particulate Matter with Non-accidental Deaths: An Ecological Time-Series Study

Macro- and individual-level influence factors of depression: multilevel cross-provinces comparison in China

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