Environmental Health Article Summary Table

ARTICLE SUMMARY TABLE

Citation (APA formatting)

1. Hill, T. D., Jorgenson, A. K., Ore, P., Balistreri, K. S., Clark, B. (2019). Air Quality and Life Expectancy in the United States: An Analysis of the Moderating Effect of Income Inequality. SSM Popul Health, 7, 100346.

2. Bennet, J. E., Tamura-Wicks, H., Parks, R. M., Burnett, R. T., Pope III, C. A., Bechle, M. J., Marshall, J. D., Danaei, G. & Ezzati, M. (2019). Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis. PLoS Medicine, 17(7).

Aim or Scope (problem being addressed)

To investigate whether air pollution causes harmful health effects on populations with inequitable income distribution in US.

To estimate the impacts of particulate matter air pollution on longevity and health.

Participants,

when and where

Two datasets observations

First dataset conducted from 2000-2010.

Second dataset included three yearly observations; 2000, 2005, and 2010.

Study conducted in 49 states of District of Columbia and US.

Entire population bordering United States at county and national level.

Study conducted from 1999-2015 in the United States

Context and framework

The study was based on US context.

Three theoretical principles were used, i.e. physiology, proximity, and power whereby a two-way-fixed effects model and regression estimation techniques were used.

Context was the United States.

Four models of bayesian spatiotemporal models were used, i.e. an integrated geographical regression model, covariate model, unadjusted model, and regression model.

Main results

or findings

The results showed that low-income states with high levels of fine particulate matter had lower life expectancy.

Particulate matter pollution was associated with an increased risk of unintentional injuries, malignant neoplasms, cardiovascular diseases, respiratory diseases, cerebrovascular disease, and heart disease - all of which are associated with higher mortality.

The results indicated that loss of life expectancy was high in counties with high poverty rate and lower income.

Particulate matter pollution was associated with cardiorespiratory diseases which led to high death rates in the said counties.

Implications Practice or Research

Future research should be carried out in environmental justice and social epidemiology to explore the health implications related to air pollution and income inequality.

Lowering the levels of particulate matter air pollution will likely lower health inequalities and have significant benefits on health in US population

Your comments (include limitations)

Data from the study was only limited to ten years, i.e. 2000-2010. In addition, only one indicator was used. Essentially, air quality was indicated by fine particulate matter, health was only based on average life expectancy, and inequality in income was based on top 10% income shares. Further, the model used resulted in conservative coefficients. Therefore, the results of the study are conservative estimates.

The study was based on observational studies which cannot be guaranteed as being causal. There was no annual data at county-level and other determinants of mortality such as diet, quality, and access to healthcare.

Reference

3. Finkelstein, M. M., Jerrett, M., DeLuca, P., Finkelstein, N., Verma, D. K., Chapman, K. & Sears, M. R. (2003). Relation Between Income, Air Pollution and Mortality: A Cohort Study. CMAJ, 169(5), 397-402.

4. Reddy, K. S. & Roberts, J. H. (2019). The Impact of Air Pollution on Deaths, Disease Burden, and Life Expectancy Across the States of India: The Global Burden of Disease Study 2017. The Lancet Planetary Health, 3(1), 26-39.

Aim or Scope (problem being addressed)

The aim of the study was to investigate the relationship between mortality, income levels in neighborhoods, and air pollution.

To estimate the impact of air pollution on life expectancy, disease burden, and death.

Participants,

when and where

The participants included 5228 people.

The study was carried out from 1985-1999 in Southern Ontario in Hamilton-Burlington area.

Air pollution exposure included ambient particulate matter pollution and household air pollution.

The study was carried out in 2017 in each state of India.

Context and framework

The context of the proportion hazards regression study model was used to calculate deaths from cardiovascular disease and non-accidental causes.

The study was based on every Indian state whereby the Gaussian process regression and spatiotemporal regression models were used.

Main results

or findings

The rates of mortality were high in neighborhoods with income below median levels and those above the medial levels of pollution exposure.

Of all the states studied, the northern states of India which have low socio-demographic index had high disease burden and high mortality. The diseases that led to high mortality owing to PM2.5 exposure were: diabetes, lung cancer, chronic obstructive pulmonary disease, stroke, ischaemic heart diseases, and acute lower respiratory infections

Implications Practice or Research

From the results, it would be prudent to note that income-associated factors such as physical environment, employment, and education happen to be major determinants of health leading to differences in mortality. Therefore, educating families will improve their social economic status and thus reduce mortality rate owing to pollution.

Promoting research and environmental education by coordinating air quality management will likely address various sources of air pollution

Your comments (include limitations)

There is likely to be some misclassification in the study owing to the fact that census data was used to estimate household income. This is more so the case given that no information about residence change was available. In addition, there was no data to perform intra-urban interpolations for other pollutants (i.e. ozone, nitrogen dioxide, and carbon monoxide). The said gases are also likely to be associated with mortality differences.

The main limitation in the study is that the Global Burden of Diseases method that was used to estimate risk factors happens to be rooted in a previous study. Therefore, ground monitoring stations in rural areas were not included. It would be prudent to address the said areas for adequate research and management of quality air.

LITERATURE REVIEW SYNTHESIS TABLE

Your research focus

Research Question: How does air pollution affect overall life expectancy on lower income families?