![Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5931/TOC-Subject-Sample-2021-Economics-Finance-Business-Industry.jpg"})
Abstract
There is extensive evidence linking air pollution exposure to physical health. Less is known about the mental health impacts of poor air quality, especially in developing countries. We use data from India and estimate the causal impact of air pollution exposure on feeling sad, experiencing cognitive difficulties, and feeling unable to control and cope with important things in life. We instrument for air pollution exposure using the annual number of nighttime thermal inversions and show that air pollution exposure in the previous calendar year significantly worsens mental health in the current year. We examine potential mechanisms and find that air pollution exposure negatively impacts self-reported physical health, worsens respiratory conditions, and increases the likelihood of experiencing sleeping difficulties. Accounting for mental health impacts of pollution exposure is critical to accurately estimating the true health costs of air pollution and designing optimal environmental policy.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
All data and code will be available upon request.
Notes
1 According to the World Health Organization, DALY, is a measure of overall disease burden defined as the total number of years of potential life lost due to premature mortality and productive life lost due to disability.
3 See https://www.who.int/phe/health_topics/outdoorair/outdoorair_aqg/en/ and World Bank Data accessed here: https://data.worldbank.org/indicator/EN.ATM.PM25.MC.M3.
4 In the presence of information around pollution, which is common in developed countries, households are able to practice avoidance behavior including not stepping out of the house when it is anticipated to be very polluted. Studies demonstrate that avoidance behavior in response to pollution information is common (Graff Zivin & Neidell, Citation2012; Moretti & Neidell, Citation2011).
5 Similar to Tsaneva and Balakrishnan (Citation2019) we construct variables for “cannot control” and “cannot cope.” Respondents were asked how often they were unable to control important things and we create an indicator for “cannot control” if the response was “fairly often” or “very often.” Respondents were also asked how often they were unable to cope with all the things in their lives and we create an indicator for “cannot cope” if they answered, “fairly often” or “very often.”
6 We also examine impacts on three 12-month measures of depression. Specifically, respondents were asked if they felt sad, lacked energy, or have lost interest for more than two weeks in the past 12 months.
8 Pollution has seen a secular rise in India since the 1990s. As demonstrated in Balakrishnan and Tsaneva (Citation2021), pollution levels in India have increased between 2002 and 2014. In our sample, as indicated in , average PM2.5 was 44.48 µg/m3 in 2003 and 49.19 µg/m3 in 2007.
9 There is wide literature (see e.g. Angrist et al., Citation1996; Ashenfelter & Krueger, Citation1994) which documents the utility of using instruments for variables which are measured with error. In our study, there is a measurement error in measuring exposure to ambient air pollution since everyone in a PSU is assigned the same value of air pollution exposure. This could lead to a downward bias in the estimated effect of pollution as the OLS estimates measure not only the direct effect of pollution but also the effect of the measurement error. The instrumental variable, number of inversions, helps to identify the true effect of pollution since it is not correlated with the random measurement error.
10 The NCEP/NCAR temperature dataset provides data at a 2.5 x 2.5-degree grid. It can be accessed here: https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.pressure.html
11 Results available from the authors upon request.
12 Since we have four main outcomes, we perform multiple hypothesis testing using the Romano-Wolf procedure. The Romano-Wolf stepdown adjusted p-values control for the family-wise error rate and allow for dependence among p-values by bootstrap resampling. The p-values with the Romano-Wolf procedure are almost identical to the p-values without multiple hypothesis testing. Specifically, the p-values before and after using the Roman-Wolf procedure for our main outcomes are likelihood of feeling sad, low, or depressed (0.0014 vs. 0.0099); probability of experiencing cognitive difficulties (0.0000 vs. 0,0099); inability to control important things in life (0.0000 vs. 0.0099); and inability to cope with important things in life (0.0000 vs. 0.0099).
13 In Appendix Table 4 in Supplementary Materials, we examine impacts on depression outcomes measured over the last 12 months and find that a one µg/m3 increase in PM2.5 leads to 1.49 percentage point increase in the probability of feeling sad and a 2.44 percentage point increase in the probability of lacking energy for two weeks or more in the past 12 months.
14 Specifically, given a baseline value of 24% of people reporting depression symptoms, our results translate to an increase of about 10.3% in the probability of reporting depression symptoms for every 1 unit increase in PM2.5. While Chen et al. (Citation2018) study the effects of pollution on severe mental illness, they find similar results, where a 1 µg/m3 increase in PM2.5 concentrations increases the probability of having severe mental illness by 0.37 percentage points, equivalent to 8.45% of the mean.
15 The p-value for all outcomes is greater than 0.05.
16 The first stage is strong with an F-statistic of 22.
17 We use the ECMWF-Interim dataset to calculate wind speed. We calculate the magnitude of the wind vector, wind speed, in each grid cell and average over by year and PSU level.
18 The first stage is strong with an F-statistic of 15.18.
19 The onset of such respiratory conditions has been shown to increase anxiety and stress as a result of fear and/or misinterpretation of symptoms (Brenes, Citation2003).
20 It is possible that air pollution induces people to remain indoors and reduce outside exposure, thereby limiting physical activity. This reduction in physical activity can be detrimental for mental health (Stathopoulou, Powers, Berry, Smits, & Otto, Citation2006; Wolff et al., Citation2011).
21 Several studies from the U.S. and China have found a negative relationship between air quality and worker productivity in different industries (Chang, Zivin, Gross, & Neidell, Citation2019; Graff Zivin & Neidell, Citation2012). In the Indian context, Adhvaryu, Kala, and Nyshadham (Citation2022) have shown that exposure to air pollution reduces worker productivity in the garment industry in India. Reduced labor productivity may reduce income and/or lead to fear of unemployment which is known to increase anxiety and stress (Kopp, Stauder, Purebl, Janszky, & Skrabski, Citation2008; Wang, Lesage, Schmitz, & Drapeau, Citation2008).
22 Studies have shown that disturbed sleep can impact cognitive function (Diekelmann & Born, Citation2010) and subjective well-being (Hamilton, Nelson, Stevens, & Kitzman, Citation2007). Recent epidemiological findings from China (Heyes & Zhu, Citation2019) and the U.S. (Fang et al., Citation2015) have found positive correlation between air pollution and sleep.
23 See Graff Zivin and Neidell (2009) and Moretti and Neidell (Citation2011) for a detailed discussion on avoidance behavior to air pollution exposure.