The association between ambient air pollution concentrations and psychological distress

The 2011 and 2016 iterations of the Ontario Marginalization Index: updates, consistency and a cross-sectional study of health outcome associations

OBJECTIVES

The Ontario Marginalization Index (ON-Marg) is an area-based measure used widely to measure health inequalities in Ontario. Recently, the index was updated for 2011 and 2016. The loss of the 2011 long-form census required the use of alternative data sources for the 2011 version. This paper describes the update of ON-Marg, assesses consistency in the indices across census years using Dissemination Areas, and examines associations between ON-Marg 2016 and four health and social outcomes to demonstrate its potential to measure health inequalities.

METHODS

ON-Marg was created using factor analysis. Differences in quintile assignment was compared over time to assess whether the use of taxfiler, immigration, property assessment, and health card address data in 2011 affected consistency in measurement of marginalization. Inequalities in rates of overall mortality, gonorrhea incidence, mental health emergency department visits, and alcohol retail locations across quintiles of ON-Marg 2016 were quantified using the Relative Index of Inequality.

RESULTS

Depending on the dimension, between 81% and 96% of DAs showed limited or no changes in quintiles of marginalization between 2006, 2011 and 2016. Of the 45-64% of DAs that did not change quintile between 2006 and 2016, 1.8% to 8.8% of DAs in 2011 differed by two or more quintiles. Findings showed significant differences in rates of health and social outcomes across quintiles of ON-Marg 2016, with strength and directionality varying by dimension of ON-Marg.

CONCLUSION

Alternative data sources did not substantially affect the consistency of the 2011 version of ON-Marg. The updated ON-Marg is a comprehensive tool that can be used to study health inequalities in Ontario.

Which Risk Factors Matter More for Psychological Distress during the COVID-19 Pandemic? An Application Approach of Gradient Boosting Decision Trees

BACKGROUND

A growing body of scientific literature indicates that risk factors for COVID-19 contribute to a high level of psychological distress. However, there is no consensus on which factors contribute more to predicting psychological health.

OBJECTIVES

The present study quantifies the importance of related risk factors on the level of psychological distress and further explores the threshold effect of each rick factor on the level of psychological distress. Both subjective and objective measures of risk factors are considered in the model.

METHODS

We sampled 937 individual items of data obtained from an online questionnaire between 20 January and 13 February 2020 in China. Objective risk factors were measured in terms of direct distance from respondents' housing to the nearest COVID-19 hospital, direct distance from respondents' housing to the nearest park, and the air quality index (AQI). Perceived risk factors were measured in regard to perceived distance to the nearest COVID-19 hospital, perceived air quality, and perceived environmental quality. Psychological distress was measured with the Kessler psychological distress scale K6 score. The following health risk factors and sociodemographic factors were considered: self-rated health level, physical health status, physical activity, current smoker or drinker, age, gender, marital status, educational attainment level, residence location, and household income level. A gradient boosting decision tree (GBDT) was used to analyse the data.

RESULTS

Health risk factors were the greatest contributors to predicting the level of psychological distress, with a relative importance of 42.32% among all influential factors. Objective risk factors had a stronger predictive power than perceived risk factors (23.49% vs. 16.26%). Furthermore, it was found that there was a dramatic rise in the moderate level of psychological distress regarding the threshold of AQI between 40 and 50, and 110 and 130, respectively. Gender-sensitive analysis revealed that women and men responded differently to psychological distress based on different risk factors.

CONCLUSION

We found evidence that perceived indoor air quality played a more important role in predicting psychological distress compared to ambient air pollution during the COVID-19 pandemic.