↓ Skip to main content

Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities

Overview of attention for article published in Environmental Health, January 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
31 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities
Published in
Environmental Health, January 2017
DOI 10.1186/s12940-016-0208-y
Pubmed ID
Authors

Lisa K. Baxter, James L. Crooks, Jason D. Sacks

Abstract

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate. The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001-2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates. Associations between a 2-day (lag 0-1 days) moving average of PM2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from -3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m(3) increase in PM2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effects estimates in cities with older, smaller homes with less AC (Cluster 1) and cities with newer, smaller homes with a large prevalence of AC (Cluster 3) were significantly lower than the cluster consisting of cities with older, larger homes with a small percentage of AC. This is the first study that attempted to examine whether multiple exposure factors could explain the heterogeneity in PM2.5-mortality associations. The results of this study were found to explain a small portion (6%) of this heterogeneity.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Researcher 6 19%
Student > Master 6 19%
Other 2 6%
Professor 1 3%
Other 3 10%
Unknown 7 23%
Readers by discipline Count As %
Environmental Science 6 19%
Medicine and Dentistry 4 13%
Engineering 3 10%
Nursing and Health Professions 2 6%
Agricultural and Biological Sciences 1 3%
Other 6 19%
Unknown 9 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 April 2017.
All research outputs
#14,893,675
of 22,925,760 outputs
Outputs from Environmental Health
#1,076
of 1,498 outputs
Outputs of similar age
#242,858
of 421,125 outputs
Outputs of similar age from Environmental Health
#15
of 26 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,498 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.3. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 421,125 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.