AIR POLLUTION AND MENTAL HEALTH: NATIONAL BUREAU OF ...

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AIR POLLUTION AND MENTAL HEALTH: EVIDENCE FROM CHINA Shuai Chen Paulina Oliva Peng Zhang Working Paper 24686



NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 June 2018

We thank Jianghao Wang for providing excellent research assistance. We thank John Strauss, and the attendees to the Biostats and Environmental Health Seminar at USC for their valuable comments. Any remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. ? 2018 by Shuai Chen, Paulina Oliva, and Peng Zhang. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including ? notice, is given to the source.

Air Pollution and Mental Health: Evidence from China Shuai Chen, Paulina Oliva, and Peng Zhang NBER Working Paper No. 24686 June 2018 JEL No. I15,I18,O53,Q51,Q53

ABSTRACT

A large body of literature estimates the effect of air pollution on health. However, most of these studies have focused on physical health, while the effect on mental health is limited. Using the China Family Panel Studies (CFPS) covering 12,615 urban residents during 2014 ? 2015, we find significantly positive effect of air pollution ? instrumented by thermal inversions ? on mental illness. Specifically, a one-standard-deviation (18.04 g/m3) increase in average PM2.5 concentrations in the past month increases the probability of having a score that is associated with severe mental illness by 6.67 percentage points, or 0.33 standard deviations. Based on average health expenditures associated with mental illness and rates of treatment among those with symptoms, we calculate that these effects induce a total annual cost of USD 22.88 billion in health expenditures only. This cost is on a similar scale to pollution costs stemming from mortality, labor productivity, and dementia.

Shuai Chen China Academy of Rural Development (CARD) Zhejiang University shuaichenyz@

Paulina Oliva Department of Economics Kaprielian Hall (KAP), 300 University of Southern California Los Angeles, CA 90089 and NBER olivaval@usc.edu

Peng Zhang School of Accounting and Finance M507C Li Ka Shing Tower The Hong Kong Polytechnic University Hung Hom Kowloon, Hong Kong peng.af.zhang@polyu.edu.hk

1 Introduction

Understanding the health costs associated with air pollution is important from a public and private perspective. From a public perspective, correctly quantifying the totality of health costs is important as regulators set air pollution standards partly based on cost-benefit calculations.1 As of today, the benefit side of the cost-benefit analysis used for policy purposes is mostly comprised of avoided mortality and morbidity costs, for which there is ample empirical evidence (Chay and Greenstone, 2003; Neidell, 2004; Currie and Neidell, 2005; Neidell, 2009; Currie and Walker, 2011; Chen et al., 2013; Anderson, 2015; Arceo et al., 2016; Deryugina et al., 2016; Knittel et al., 2016; Schlenker and Walker, 2016; Desch?nes et al., 2017; Ebenstein et al., 2017). A more comprehensive calculation of the costs associated with air pollution acknowledges that individuals optimize their level of protection through actions such as staying indoors (Neidell, 2009), medication purchases (Desch?nes et al., 2017), purchases of air purifiers and facemasks (Ito and Zhang, 2016; Zhang and Mu, 2017), and location choices (Chen et al., 2017); all of which are costly (Harrington and Portney, 1987). Up to now, most of the epidemiological and economics studies have focused on physical health outcomes, while studies of the effect on mental health are limited.2 This paper contributes to filling this research gap by estimating the short-run effect of air pollution on mental health.

Mental health refers to a state of well-being in which an individual can cope with stress, work productively, and is able to make contribution to the community (World Health

1 U.S. Environmental Protection Agency (EPA), "Benefits Mapping and Analysis Program", . 2 An important exception is the recent work by Bishop et al. (2017) on the effect of chronic air pollution exposure on dementia. Dementia and mental illness are closely related, but differ in terms of symptoms (Regan, 2016). The most common form of dementia is the Alzheimer's disease, which significantly damages the memory function in the brian and causes a variety of symptoms including difficulty in communicating, increased memory issues, general confusion, and personality and emotional changes. The Alzheimer's disease is more likely to occur for the elderly aged 65 or above. The most common symptoms of mental illness, on the other hand, are depression and anxiety.

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Organization (WHO), 2014). According to the WHO, "Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity".3 Mental illness has received increased public attention as we learn more about the size of the population worldwide that is likely affected and the costs associated with it. The WHO estimated that 450 million people suffered from mental illness worldwide (WHO, 2007). It is estimated that mental illness is responsible for 13% of the global disease burden (Collins et al., 2011), accounts for more than 140 million disability-adjusted life years (Whiteford et al., 2013), and cost USD 2.5 trillion in 2010; which is roughly 50% of the entire global health spending for that year (WHO, 2010).

In this paper, we aim to estimate the causal effect of air pollution on mental health in China. We measure air pollution as the concentration of very fine particulate matter, or particulates with a diameter less than 2.5 micrometers (PM2.5). However, because of our research design, we will not be able to isolate the effects of different air pollutants on mental health. Our focus on PM2.5 follows the findings in health sciences, which show that PM2.5 could be inhaled into the human body and increase oxidative stress and systemic inflammation. These reactions, in turn, can exacerbate depression and anxiety (Calderon-Garciduenas et al., 2003; S?rensen et al., 2003; MohanKumar et al., 2008, Salim et al., 2012, Power et al., 2015). In addition, PM2.5 could induce respiratory or cardiac medical conditions (Delfino, 2002; United States Environmental Protection Agency (EPA), 2008, 2009; Ling and van Eeden, 2009), which may further increase depression and anxiety through several channels (Brenes, 2003; Scott et al., 2007; Yohannes et al., 2010; Spitzer et al., 2011). Because the main measure of air pollution we use is PM2.5, we use air pollution and PM2.5 interchangeably throughout the paper.

Identifying the causal effect of air pollution on mental health illness is challenging for three reasons. First, air pollution is typically correlated with confounders such as income and

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local economic conditions, which are also important determinants of mental illness (Gardner and Oswald, 2007; Charles and DeCicca, 2008). Omitting such confounders may bias the estimates downward if they are positively correlated with pollution and negatively affect the incidence of mental illness. The second empirical challenge is the reverse causality. Since mental health may have a direct effect on human productivity (WHO, 2002), this could, in turn, affect the level of emissions related to economic activity. This type of reverse causality would further bias the estimates downward. The third challenge is classic measurement error, as air pollution at a specific location is likely to be measured with error or subject to human manipulation (Ghanem and Zhang, 2014; Sullivan, 2017). This will attenuate the estimates towards zero.

To overcome the endogeneity of air pollution, we apply an instrumental variables (IV) approach, where we instrument air pollution using thermal inversions. Thermal inversions occur when a mass of hot air is above the cold air and thus air pollutants near the ground are trapped. As a meteorological phenomenon, the occurrence of a thermal inversion is independent of economic activity. Thermal inversions significantly affect air pollution concentrations and have been used as an IV for air pollution in several previous studies (Jans et al., 2014; Hicks et al., 2015; Arceo et al., 2016; Fu et al., 2017; Chen et al., 2017).

Our measure of mental health comes from the nationally representative China Family Panel Studies (CFPS) in 2014, which interviewed 15,618 rural and 12,650 urban adult residents across 162 counties from July 3rd 2014 to March 31th 2015 in China. The CFPS includes six questions which comprise the internationally validated Kessler Psychological Distress Scale (K6) ranging from 0 ? 24 on the frequency of the following mental illness symptoms over the past month prior to interview: depression, nervousness, restlessness, hopelessness, effort, and worthlessness (Kessler et al., 2002, 2003; Prochaska et al., 2012). We exploit variation in shortrun PM2.5 exposure induced by thermal inversions in the month prior to the interview date. In

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