scholarly journals Examining Spatial Association of Air Pollution and Suicide Rate Using Spatial Regression Models

2020 ◽  
Vol 12 (18) ◽  
pp. 7444
Author(s):  
Yeran Sun ◽  
Ting On Chan ◽  
Jing Xie ◽  
Xuan Sun ◽  
Ying Huang

Air pollution can have adverse impacts on both the physical health and mental health of people. Increasing air pollution levels are likely to increase suicide rates, although the causal mechanisms underlying the relationship between pollution exposure and suicidal behaviour are not well understood. In this study, we aimed to further examine the spatial association of air pollution and suicidal behaviour. Specifically, we investigated whether or how PM2.5 levels are spatially associated with the adult suicide rates at the district level across London. As the data used are geospatial data, we used two newly developed specifications of spatial regression models to investigate the spatial association of PM2.5 levels and suicide. The empirical results show that PM2.5 levels are spatially associated with the suicide rates across London. The two models show that PM2.5 levels have a positive association with adult suicide rates over space. An area with a high percentage of White people or a low median household income is likely to suffer from a high suicide rate.

2003 ◽  
Vol 66 (16-19) ◽  
pp. 1811-1824 ◽  
Author(s):  
Sabit Cakmak ◽  
Richard Burnett ◽  
Michael Jerrett ◽  
Mark Goldberg ◽  
C. Arden Pope ◽  
...  

2021 ◽  
Vol 12 (4) ◽  
pp. 58-74
Author(s):  
Ortis Yankey ◽  
Prince M. Amegbor ◽  
Marcellinus Essah

This paper examined the effect of socio-economic and environmental factors on obesity in Cleveland (Ohio) using an OLS model and three spatial regression models: spatial error model, spatial lag model, and a spatial error model with a spatially lagged response (SEMSLR). Comparative assessment of the models showed that the SEMSLR and the spatial error models were the best models. The spatial effect from the various spatial regression models was statistically significant, indicating an essential spatial interaction among neighboring geographic units and the need to account for spatial dependency in obesity research. The authors also found a statistically significant positive association between the percentage of families below poverty, Black population, and SNAP recipient with obesity rate. The percentage of college-educated had a statistically significant negative association with the obesity rate. The study shows that health outcomes such as obesity are not randomly distributed but are more clustered in deprived and marginalized neighborhoods.


Author(s):  
Zisis Mallios

Hedonic pricing is an indirect valuation method that applies to heterogeneous goods investigating the relationship between the prices of tradable goods and their attributes. It can be used to measure the value of irrigation water through the estimation of the model that describes the relation between the market value of the land parcels and its characteristics. Because many of the land parcels included in a hedonic pricing model are spatial in nature, the conventional regression analysis fails to incorporate all the available information. Spatial regression models can achieve more efficient estimates because they are designed to deal with the spatial dependence of the data. In this paper, the authors present the results of an application of the hedonic pricing method on irrigation water valuation obtained using a software tool that is developed for the ArcGIS environment. This tool incorporates, in the GIS application, the estimation of two different spatial regression models, the spatial lag model and the spatial error model. It also has the option for different specifications of the spatial weights matrix, giving the researcher the opportunity to examine how it affects the overall performance of the model.


Author(s):  
Zisis Mallios

Hedonic pricing is an indirect valuation method that applies to heterogeneous goods investigating the relationship between the prices of tradable goods and their attributes. It can be used to measure the value of irrigation water through the estimation of the model that describes the relation between the market value of the land parcels and its characteristics. Because many of the land parcels included in a hedonic pricing model are spatial in nature, the conventional regression analysis fails to incorporate all the available information. Spatial regression models can achieve more efficient estimates because they are designed to deal with the spatial dependence of the data. In this paper, the authors present the results of an application of the hedonic pricing method on irrigation water valuation obtained using a software tool that is developed for the ArcGIS environment. This tool incorporates, in the GIS application, the estimation of two different spatial regression models, the spatial lag model and the spatial error model. It also has the option for different specifications of the spatial weights matrix, giving the researcher the opportunity to examine how it affects the overall performance of the model.


Author(s):  
Yongsheng Tong ◽  
Michael R. Phillips ◽  
Yi Yin ◽  
Zhichao Lan

Abstract Aims The 2014 World Health Organization report on global suicide identified large differences in the male-to-female ratio of suicide rates between countries: most high-income countries (HICs) report ratios of 3:1 or higher while many low- and middle-income countries (LMICs) – including China and India – report ratios of less than 1.5:1. Most authors suggest that gender-based social-cultural factors lead to higher rates of suicidal behaviour among women in LMICs and, thus, to relatively high female suicide rates. We aim to test an alternative hypothesis: differences in the method and case-fatality of suicidal behaviour – not differences in the rates of suicidal behaviour – are the main determinants of higher female suicide rates in LMICs. Methods A prospective registry of suicide attempts treated in all 14 general hospitals in a rural county in China was established and data from the registry were integrated with population and mortality data from the same county from 2009 to 2014. Results There were 160 suicides and 1010 medically-treated suicidal attempts in the county; 84% of female suicides and 58% of male suicides ingested pesticides while 73% of female attempted suicides and 72% of male attempted suicides ingested pesticides. The suicide rate (per 100 000 person-years of exposure) was 8.4 in females and 9.1 in males (M:F ratio = 1.08:1) while the incidence of ‘serious suicidal acts’ (i.e. those that result in death or received treatment in a hospital) was 81.5 in females and 47.7 in males (M:F ratio = 0.59:1). The case-fatality of serious suicidal acts was higher in males than in females (19 v. 10%), increased with age, was highest for violent methods (92%), intermediate for pesticide ingestion (13%) and lowest for other methods (5%). Conclusions The incidence of medically serious suicidal behaviour among females in rural China was similar to that reported in HICs, but the case-fatality was much higher, primarily because most suicidal acts involved the ingestion of pesticides, which had a higher case-fatality than methods commonly used by women in HICs. These findings do not support sociological explanations for the relatively high female suicide rate in China but, rather, suggest that gender-specific method choice and the case-fatality of different methods are more important determinants of the demographic profile of suicide rates. Further research that involves ongoing monitoring of the changing incidence, demographic profile and case-fatality of different suicidal methods in urban and rural parts of both LMICs and HICs is needed to confirm this hypothesis.


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