Air Pollution and Long Term Mental Health
Abstract
1. Introduction
2. Materials and Methods
3. Results and Discussion
4. Robustness Checks and Threats to Identification
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Emmanuel, S. Impact to Lung Health of Haze from Forest Fires: The Singapore Experience. Respirology 2000, 5, 175–182. [Google Scholar] [CrossRef]
- Romieu, I.; Samet, J.; Smith, K.; Bruce, N. Outdoor air pollution and acute respiratory infections among children in developing countries. J. Occup. Environ. Med. 2002, 44, 640–649. [Google Scholar] [CrossRef]
- Chauhan, A.; Johnston, S. Air Pollution and Infection in Respiratory Illness. Br. Med Bull. 2003, 68, 95–112. [Google Scholar] [CrossRef]
- Beckwith, T.; Cecil, K.; Altaye, M.; Severs, R.; Wolfe, C.; Percy, Z.; Maloney, T.; Yolton, K.; LeMasters, G.; Brunst, K.; et al. Reduced gray matter volume and cortical thickness associated with traffic-related air pollution in a longitudinat studied pediatric cohort. PLoS ONE 2020, 15, e0228092. [Google Scholar] [CrossRef]
- Chay, K.; Greenstone, M. The impact of air pollution on infant mortality: Evidence from geographic variation in pollution shocks induced by a recession. Q. J. Econ. 2003, 118, 1121–1167. [Google Scholar] [CrossRef]
- Currie, J.; Neidell, M. Air Pollution and Infant Health: What Can We Learn from California’s Recent Experience? Q. J. Econ. 2005, 120, 1003–1030. [Google Scholar]
- Bobak, M.; Leon, D. Air Pollution and Infant Mortality in the Czech Republic, 1986–1988. Lancet 1992, 340, 1010–1014. [Google Scholar] [CrossRef]
- Hajdu, T.; Hajdu, G. Smoking ban and health at birth: Evidence from Hungary. Econ. Hum. Biol. 2018, 30, 37–47. [Google Scholar] [CrossRef]
- Loomis, D.; Castillejos, M.; Gold, D.; McDonnell, W.; Borja-Aburto, V. Air Pollution and Infant Mortality in Mexico City. Epidemiology 1999, 10, 118–123. [Google Scholar] [CrossRef]
- Hausman, J.; Ostro, B.; Wise, D. Air Pollution and Lost Work; NBER Working Paper 1263. National Bureau of Economic Research, 1984. Available online: https://www.nber.org/papers/w1263 (accessed on 11 December 2020).
- Hanna, R.; Oliva, P. The effect of pollution on labor supply: Evidence from a natural experiment in Mexico City. J. Public Econ. 2015, 122, 68–79. [Google Scholar] [CrossRef]
- Aragon, F.; Miranda, J.; Oliva, P. Particulate matter and labor Supply: The role of caregiving and non-linearities. J. Environ. Econ. Manag. 2017, 86, 295–309. [Google Scholar] [CrossRef]
- Graff-Zivin, J.; Neidell, M. The impact of pollution on worker productivity. Am. Econ. Rev. 2012, 102, 3652–3673. [Google Scholar] [CrossRef]
- Chang, T.; Graff-Zivin, J.; Gross, T.; Neidell, M. Particulate Pollution and the Productivity of Pear Packers. Am. Econ. J. Econ. Policy 2016, 8, 141–169. [Google Scholar] [CrossRef]
- Peterson, B.; Rauh, V.; Bansal, R.; Hao, X.; Toth, Z.; Nati, G.; Walsh, K.; Miller, R.; Arias, F.; Semanek, D.; et al. Effects of Prenatal Exposure to Air Pollutants (Polycyclic Aromatic Hydrocarbons) on the Development of Brain White Matter, Cognition, and Behavior in Later Childhood. JAMA Psychiatry 2015, 72, 531–540. [Google Scholar] [CrossRef]
- Kim, Y.; Knowles, S.; Manley, J.; Radoias, V. Long-run health consequences of air pollution: Evidence from Indonesia’s forest fires of 1997. Econ. Hum. Biol. 2017, 26, 186–198. [Google Scholar] [CrossRef]
- Isen, A.; Rossin-Slater, M.; Walker, W. Every breath you take-every dollar you’ll make: The long term consequences of the clean air act of 1970. J. Political Econ. 2017, 125, 848–902. [Google Scholar] [CrossRef]
- Kim, Y.; Manley, J.; Radoias, V. Medium- and long-term consequences of pollution on labor supply: Evidence from Indonesia. IZA J. Labor Econ. 2017, 6, 5. [Google Scholar] [CrossRef]
- Li, Z.; Hu, B. Perceived health risk, environmental knowledge, and contingent valuation for improving air quality: New evidence from the Jinchuan mining area in China. Econ. Hum. Biol. 2018, 31, 54–68. [Google Scholar] [CrossRef]
- Thielke, S.M.; Diehr, P.; Unutzer, J. Prevalence, incidence, and persistence of major depressive symptoms in the cardiovascular health study. Aging Ment. Health 2010, 14, 168–176. [Google Scholar] [CrossRef]
- Arbelaez, J.J.; Ariyo, A.A.; Crum, R.M.; Fried, L.P.; Ford, D.E. Depressive symptoms, inflammation, and ischemic stroke in older adults: A prospective analysis in the cardiovascular health study. J. Am. Geriatr. Soc. 2007, 55, 1825–1830. [Google Scholar] [CrossRef]
- Binder, M.; Buenstorf, G. Smile or Die: Can subjective well-being increase survival in the face of substantive health impairments? Econ. Hum. Biol. 2018, in press. [Google Scholar] [CrossRef]
- Glymour, M.M.; Maselko, J.; Gilman, S.E.; Patton, K.K.; Avendano, M. Depressive symptoms predict incident stroke independently of memory impairments. Neurology 2010, 75, 2063–2070. [Google Scholar] [CrossRef]
- Janssen, I.; Powell, L.H.; Matthews, K.A.; Cursio, J.F.; Hollenberg, S.M.; Sutton-Tyrrell, K.; Bromberger, J.T.; Everson-Rose, S.A. Depressive symptoms are related to progression of coronary calcium in midlife women: The Study of Women’s Health Across the Nation (SWAN) Heart Study. Am. Heart J. 2011, 161, 1186–1191. [Google Scholar] [CrossRef]
- Ahsan, N.; Maharaj, R. Parental human capital and child health at birth in India. Econ. Hum. Biol. 2018, 30, 130–149. [Google Scholar] [CrossRef]
- Black, M.M.; Baqui, A.M.; Zaman, K.; El Arifeen, S.; Black, R.E. Maternal depressive symptoms and infant growth in rural Bangladesh. Am. J. Clin. Nutr. 2009, 89, 951S–957S. [Google Scholar] [CrossRef]
- Surkan, P.J.; Kennedy, C.E.; Hurley, K.M.; Black, M.M. Maternal depression and early childhood growth in developing countries: Systematic review and meta-analysis. Bull. World Health Organ. 2011, 287, 607–615. [Google Scholar] [CrossRef]
- Noonan, K.; Corman, H.; Reichman, N. Effects of maternal depression on family food insecurity. Econ. Hum. Biol. 2016, 22, 201–215. [Google Scholar] [CrossRef]
- Bandiera, F.C.; Richardson, A.K.; Lee, D.J.; He, J.; Merikangas, K.R. Secondhand smoke exposure and mental health among children and adolescents. Arch. Pediatr. Adolesc. Med. 2011, 165, 332–338. [Google Scholar] [CrossRef]
- Taha, F.; Goodwin, R.D. Secondhand smoke exposure across the life course and the risk of adult-onset depression and anxiety disorder. J. Affect. Disord. 2014, 168, 367–372. [Google Scholar] [CrossRef]
- Jung, S.; Shin, A.; Kang, D. Active smoking and exposure to secondhand smoke and their relationship to depressive symptoms in the Korea national health and nutrition examination survey (KNHANES). BMC Public Health 2015, 15, 1053. [Google Scholar] [CrossRef]
- Kim, N.; Choi, H.; Kim, N.; Shin, J.; Kim, H. Secondhand smoke exposure and mental health problems in Korean adults. Epidemiol. Health 2016, 38, e2016009. [Google Scholar] [CrossRef] [PubMed]
- Ranft, U.; Schikowski, T.; Sugiri, D.; Krutmann, J.; Kramer, U. Long-term exposure to traffic-related particulate matter impairs cognitive function in the elderly. Environ. Res. 2009, 109, 1004–1011. [Google Scholar] [CrossRef] [PubMed]
- Kim, K.; Lim, Y.; Bae, H.; Kim, M.; Jung, K.; Hong, Y. Long-term fine particulate matter exposure and major depressive disorder in a community-based urban cohort. Environ. Health Perspect. 2016, 124, 1547. [Google Scholar] [CrossRef] [PubMed]
- Kioumourtzoglou, M.; Power, M.; Hart, J.; Okereke, O.; Coull, B.; Laden, F.; Weisskopf, M. The association between air pollution and onset of depression among middle-aged and older women. Am. J. Epidemiol. 2017, 185, 801–809. [Google Scholar] [CrossRef] [PubMed]
- Tzivian, L.; Winkler, A.; Dlugaj, M.; Schikowski, T.; Vossoughi, M.; Fuks, K.; Weinmayr, G.; Hoffmann, B. Effect of long-term outdoor air pollution and noise on cognitive and psychological functions in adults. Int. J. Hyg. Environ. Health 2015, 218, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Banerjee, M.; Siddique, S.; Dutta, A.; Mukherjee, B.; Ray, M. Cooking with biomass increases the risk of depression in pre-menopausal women in India. Soc. Sci. Med. 2012, 75, 565–572. [Google Scholar] [CrossRef]
- Cho, J.; Choi, Y.; Suh, M.; Sohn, J.; Kim, H.; Cho, S.; Ha, K.; Kim, C.; Shin, D. Air pollution as a risk factor for depressive episode in patients with cardiovascular disease, diabetes mellitus, or asthma. J. Affect. Disord. 2014, 175, 45–51. [Google Scholar] [CrossRef]
- Fonken, L.; Xu, X.; Weil, Z.; Chen, G.; Sun, Q.; Rajagopalan, S.; Nelson, R. Air pollution impairs cognition, provokes depression-like behaviors and alters hippocampal cytokine expression and morphology. Mol. Psychiatry 2011, 16, 987–995. [Google Scholar] [CrossRef]
- Pun, V.; Manjourides, J.; Suh, H. Association of Ambient Air Pollution with Depressive and Anxiety Symptoms in Older Adults: Results from the NSHAP Study. Environ. Health Perspect. 2017, 125, 342–348. [Google Scholar] [CrossRef]
- Wang, Y.; Eliot, M.N.; Koutrakis, P.; Gryparis, A.; Schwartz, J.D.; Coull, B.A.; Mittleman, M.A.; Milberg, W.P.; Lipsitz, L.A.; Wellenius, G.A. Ambient air pollution and depressive symptoms in older adults: Results from the MOBILIZE Boston Study. Environ. Health Perspect. 2014, 122, 553–558. [Google Scholar] [CrossRef]
- Zijlema, W.L.; Wolf, K.; Emeny, R.; Ladwig, K.H.; Peters, A.; Kongsgard, H.; Hveem, K.; Kvaloy, K.; Yli-Tuomi, T.; Partonen, T.; et al. The association of air pollution and depressed mood in 70,928 individuals from four European cohorts. Int. J. Hyg. Environ. Health 2016, 219, 212–219. [Google Scholar] [CrossRef] [PubMed]
- Heil, A. The 1997–98 Air Pollution Episode in Southeast Asia Generated by Vegetation Fires in Indonesia. Int. For. Fire News 2000, 23, 68–71. [Google Scholar]
- Jayachandran, S. Air Quality and Early-Life Mortality: Evidence from Indonesia’s Wildfires. J. Hum. Resour. 2009, 44, 916–954. [Google Scholar] [CrossRef][Green Version]
- Kunii, O.; Kanagawa, S.; Yajima, I.; Hisamatsu, Y.; Yamamura, S.; Amagai, T.; Ismail, T. The 1997 Haze Disaster in Indonesia: Its Air Quality and Health Effects. Arch. Environ. Health Int. J. 2002, 57, 16–22. [Google Scholar] [CrossRef]
- Strauss, J.; Witoelar, B.; Sikoki, B.; Wattie, A. The Fourth Wave of the Indonesia Family Life Survey (IFLS4): Overview and Field Report. April 2009. WR-675/1-NIA/NICHD; RAND. Available online: https://www.rand.org/well-being/social-and-behavioral-policy/data/FLS/IFLS/download.html (accessed on 11 December 2020).
- Ahsan, N.; Kelly, I. Earnings gaps for conspicuous characteristics: Evidence from Indonesia. South. Econ. J. 2018, 85, 121–141. [Google Scholar] [CrossRef]
- Hatton, T.; Sparrow, R.; Suryadarma, D.; van der Eng, P. Fertility and the health of children in Indonesia. Econ. Hum. Biol. 2018, 28, 67–78. [Google Scholar] [CrossRef]
- Kim, Y. The dynamics of health and its determinants among the elderly in developing countries. Econ. Hum. Biol. 2015, 19, 1–12. [Google Scholar] [CrossRef]
- Andresen, E.M.; Malmgren, J.A.; Carter, W.B.; Patrick, D.L. Screening for depression in well older adults: Evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am. J. Prev. Med. 1994, 10, 77–84. [Google Scholar] [CrossRef]
- Zhang, W.; O’Brien, N.; Forrest, J.; Salters, K.; Patterson, T.; Montaner, J.; Hogg, R.; Lima, V. Validating a shortened depression scale (10 Item CES-D) among HIV-positive people in British Columbia, Canada. PLoS ONE 2012, 7, e40793. [Google Scholar] [CrossRef]
- Radloff, L.S. CES-D scale: A self report depression scale for research in the general populations. Appl. Psychol. Meas. 1977, 1, 385–401. [Google Scholar] [CrossRef]
- Bound, J.; Krueger, A. The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right? J. Labor Econ. 1991, 12, 345–368. [Google Scholar] [CrossRef]
- Idler, E.; Benyamini, Y. Self-Rated Health and Mortality: A Review of Twenty Seven Community Studies. J. Health Soc. Behav. 1997, 38, 21–37. [Google Scholar] [CrossRef]
- Burstrom, R.; Fredlund, P. Self Rated Health: Is it as Good a Predictor of Subsequent Mortality among Adults in Lower as well as in Higher Social Classes? J. Epidemiol. Community Health 2001, 55, 836–840. [Google Scholar] [CrossRef]
- van Doorslaer, E.; Gerdtham, U.-G. Does Inequality in Self Assessed Health Predict Inequality in Survival by Income? Evidence from Swedish Data. Soc. Sci. Med. 2003, 57, 1621–1629. [Google Scholar] [CrossRef]
- Helgadottir, B.; Forsell, Y.; Hallgren, M.; Moller, J.; Ekblom, O. Long-term effects of exercise at different intensity levels on depression: A randomized controlled trial. Prev. Med. 2017, 105, 37–46. [Google Scholar] [CrossRef] [PubMed]
Pollution Variable | Mean | Std. Dev. | Range | Sample Size |
Pollution 1997 | 0.675 | 0.609 | 0.194–4.841 | 7969 |
Pollution 1996 | 0.091 | 0.081 | −0.083–0.395 | 7969 |
Depression Score in 2007 | Frequency | Percent | Males | Females |
<10 | 7479 | 93.85% | 3195 | 4284 |
≥10 | 490 | 6.15% | 157 | 333 |
Total | 7969 | 100% | 3352 | 4617 |
Explanatory Variables | Full Sample | Men | Women | |||
---|---|---|---|---|---|---|
Coefficient | (St. Error) | Coefficient | (St. Error) | Coefficient | (St. Error) | |
Pollution in 1997 | 0.2690 *** | (0.0689) | 0.2448 ** | (0.1013) | 0.2948 *** | (0.0928) |
Age in 2007 | −0.0538 ** | (0.0249) | −0.1305 *** | (0.0392) | 0.0029 | (0.0333) |
Age in 2007 | 0.0005 ** | (0.0002) | 0.0012 *** | (0.0003) | −0.000004 | (0.00030) |
Years of Education | −0.0598 *** | (0.0096) | −0.04995 *** | (0.0139) | −0.0683 *** | (0.0134) |
Poor GHS in 1993 | 1.0368 *** | (0.1564) | 0.6182 *** | (0.2131) | 0.1.2904 *** | (0.2127) |
Log PCE | −0.0898 | (0.0637) | −0.0487 | (0.0923) | −0.1177 | (0.08698) |
Income Ladder 2 | −0.7396 *** | (0.2047) | −0.6413 ** | (0.3149) | −0.7753 *** | (0.2688) |
Income Ladder 3 | −1.3745 *** | (0.1983) | −1.3318 *** | (0.3046) | −1.3720 *** | (0.2610) |
Income Ladder 4 | −1.6852 *** | (0.2146) | −1.8110 *** | (0.3205) | −1.5600 *** | (0.2882) |
Income Ladder 5 | −1.7928 *** | (0.3326) | −1.2737 *** | (0.4848) | −2.1026 *** | (0.4459) |
Having Outside Kitchen | 0.0547 | (0.0766) | −0.1064 | (0.1116) | 0.1746 * | (0.1045) |
Having Outside Water | −0.2583 *** | (0.0879) | −0.3745 *** | (0.1318) | −0.1676 | (0.1175) |
Married | −0.4257 *** | (0.1120) | −0.7415 *** | (0.2477) | −0.3119 ** | (0.1312) |
Male | −0.1537 * | (0.0800) | - | − | - | − |
Constant | 8.4143 *** | (1.0343) | 10.2384 *** | (1.6112) | 7.0444 *** | (1.3646) |
Sample Size | 7969 | 3352 | 4617 |
Explanatory Variables | Full Sample | Men | Women | |||
---|---|---|---|---|---|---|
Coefficient | (St. Error) | Coefficient | (St. Error) | Coefficient | (St. Error) | |
Pollution in 1997 | 0.0121 ** | (0.0050) | 0.0082 | (0.0067) | 0.0150 ** | (0.0071) |
Age in 2007 | −0.0031 | (0.0019) | −0.0045 | (0.0028) | −0.0024 | (0.0027) |
Age in 2007 | 0.00002 | (0.00001) | 0.00003 | (0.00002) | 0.00002 | (0.00002) |
Years of Education | −0.0011 * | (0.00007) | −0.0008 | (0.0009) | −0.0014 | (0.0009) |
Poor GHS in 1993 | 0.0561 *** | (0.0122) | 0.0122 | (0.0149) | 0.0813 *** | (0.0172) |
Log PCE | 0.0107 ** | (0.0048) | 0.0061 | (0.0065) | 0.0139 ** | (0.0067) |
Income Ladder 2 | −0.0344 ** | (0.0160) | −0.0255 | (0.0230) | −0.0382 * | (0.0220) |
Income Ladder 3 | −0.0668 *** | (0.0153) | −0.0624 *** | (0.0218) | −0.0670 *** | (0.0213) |
Income Ladder 4 | −0.0702 *** | (0.0164) | −0.0773 *** | (0.0224) | −0.0624 *** | (0.0232) |
Income Ladder 5 | −0.0836 *** | (0.02199) | −0.0758 *** | (0.0294) | −0.0868 *** | (0.0310) |
Having Outside Kitchen | −0.0006 | (0.0055) | −0.0069 | (0.0074) | 0.0043 | (0.0079) |
Having Outside Water | −0.0066 | (0.0065) | −0.0078 | (0.00899) | −0.0052 | (0.0092) |
Married | −0.0249 *** | (0.0089) | −0.0269 | (0.0191) | −0.0213 ** | (0.0106) |
Male | −0.0158 *** | (0.0056) | - | − | - | − |
Constant | 0.0972 | (0.0776) | 0.1909 * | (0.1126) | 0.0245 | (0.1069) |
Sample Size | 7969 | 3352 | 4617 |
Explanatory Variables | Full Sample | Men | Women | |||
---|---|---|---|---|---|---|
Coefficient | (St. Error) | Coefficient | (St. Error) | Coefficient | (St. Error) | |
Pollution in 1997 | 0.1447 ** | (0.0463) | 0.1386 ** | (0.0702) | 0.1576 *** | (0.0617) |
Age in 2007 | −0.0269 | (0.0182) | −0.0932 *** | (0.0308) | 0.0246 | (0.0224) |
Age in 2007 | 0.00033 ** | (0.00016) | 0.00092 *** | (0.00027) | −0.00013 | (0.0002) |
Years of Education | −0.0486 *** | (0.0071) | −0.0403 *** | (0.0104) | −0.0555 *** | (0.0096) |
Poor GHS in 1993 | 0.4705 *** | (0.1041) | 0.5104 *** | (0.1614) | 0.45997 *** | (0.1361) |
Log PCE | −0.1919 *** | (0.0447) | −0.1169 * | (0.06896) | −0.2427 *** | (0.0586) |
Income Ladder 2 | −0.3604 *** | (0.1338) | −0.2940 | (0.2013) | −0.40497 ** | (0.1790) |
Income Ladder 3 | −0.7215 *** | (0.1299) | −0.6686 *** | (0.1948) | −0.7609 *** | (0.1742) |
Income Ladder 4 | −1.0098 *** | (0.1427) | −0.9881 *** | (0.2132) | −1.0267 *** | (0.1922) |
Income Ladder 5 | −0.9452 *** | (0.2626) | −0.3930 | (0.4197) | −1.3023 *** | (0.3313) |
Having Outside Kitchen | 0.0534 | (0.0549) | −0.0488 | (0.08398) | 0.1273 * | (0.0725) |
Having Outside Water | −0.2242 *** | (0.0626) | −0.3042 *** | (0.0972) | −0.1636 ** | (0.0819) |
Married | −0.2681 *** | (0.0812) | −0.4881 *** | (0.1749) | −0.2013 ** | (0.0950) |
Male | −0.0166 | (0.0571) | - | − | - | − |
Constant | 7.5446 *** | (0.7321) | 8.5631 *** | (1.1942) | 6.7945 *** | (0.9307) |
Sample Size | 7479 | 3195 | 4284 |
Explanatory Variables | Clinical Depression Status | Mild Depressive Symptoms | ||
---|---|---|---|---|
Coefficient | (St. Error) | Coefficient | (St. Error) | |
Pollution in 1997 | 0.0128 ** | (0.0051) | 0.148 *** | (0.0467) |
Age in 2007 | −0.0027 | (0.0019) | −0.0297 | (0.0184) |
Age in 2007 | 0.00002 | (0.00001) | 0.00036 | (0.00016) |
Years of Education | −0.0012 * | (0.00007) | −0.0468 *** | (0.0071) |
Poor GHS in 1993 | 0.0585 *** | (0.0124) | 0.466 *** | (0.1054) |
Log PCE | 0.0102 ** | (0.0048) | −0.1948 *** | (0.0451) |
Income Ladder 2 | −0.0367 ** | (0.0161) | −0.3540 *** | (0.1353) |
Income Ladder 3 | −0.0661 *** | (0.0154) | −0.7105 *** | (0.1314) |
Income Ladder 4 | −0.0710 *** | (0.0165) | −0.9956 *** | (0.1443) |
Income Ladder 5 | −0.0897 *** | (0.02104) | −0.9275 *** | (0.2641) |
Having Outside Kitchen | 0.0002 | (0.0056) | 0.0555 | (0.0554) |
Having Outside Water | −0.0065 | (0.0066) | −0.2239 *** | (0.0634) |
Married | −0.0241 *** | (0.0090) | −0.2747 *** | (0.082) |
Male | −0.0175 *** | (0.0056) | −0.0188 | (0.0575) |
Constant | 0.0923 | (0.0785) | 7.627 *** | (0.7397) |
Sample Size | 7813 | 7338 |
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Kim, Y.; Manley, J.; Radoias, V. Air Pollution and Long Term Mental Health. Atmosphere 2020, 11, 1355. https://doi.org/10.3390/atmos11121355
Kim Y, Manley J, Radoias V. Air Pollution and Long Term Mental Health. Atmosphere. 2020; 11(12):1355. https://doi.org/10.3390/atmos11121355
Chicago/Turabian StyleKim, Younoh, James Manley, and Vlad Radoias. 2020. "Air Pollution and Long Term Mental Health" Atmosphere 11, no. 12: 1355. https://doi.org/10.3390/atmos11121355
APA StyleKim, Y., Manley, J., & Radoias, V. (2020). Air Pollution and Long Term Mental Health. Atmosphere, 11(12), 1355. https://doi.org/10.3390/atmos11121355