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Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model

Overview of attention for article published in PLOS ONE, May 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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Article details
Title
Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model
Published in
PLOS ONE, May 2018
DOI 10.1371/journal.pone.0195734
Pubmed ID
Authors
Abstract

Recent studies have examined the risk of poverty throughout the life course, but few have considered how transitioning in and out of poverty shape the dynamic heterogeneity and mortality disparities of a cohort at each age. Here we use state-by-age modeling to capture individual heterogeneity in crossing one of three different poverty thresholds (defined as 1×, 2× or 3× the "official" poverty threshold) at each age. We examine age-specific state structure, the remaining life expectancy, its variance, and cohort simulations for those above and below each threshold. Survival and transitioning probabilities are statistically estimated by regression analyses of data from the Health and Retirement Survey RAND data-set, and the National Longitudinal Survey of Youth. Using the results of these regression analyses, we parameterize discrete state, discrete age matrix models. We found that individuals above all three thresholds have higher annual survival than those in poverty, especially for mid-ages to about age 80. The advantage is greatest when we classify individuals based on 1× the "official" poverty threshold. The greatest discrepancy in average remaining life expectancy and its variance between those above and in poverty occurs at mid-ages for all three thresholds. And fewer individuals are in poverty between ages 40-60 for all three thresholds. Our findings are consistent with results based on other data sets, but also suggest that dynamic heterogeneity in poverty and the transience of the poverty state is associated with income-related mortality disparities (less transience, especially of those above poverty, more disparities). This paper applies the approach of age-by-stage matrix models to human demography and individual poverty dynamics. In so doing we extend the literature on individual poverty dynamics across the life course.

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X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 7 13%
Student > Ph. D. Student 7 13%
Student > Master 5 9%
Student > Doctoral Student 3 5%
Professor > Associate Professor 3 5%
Other 6 11%
Unknown 25 45%
Readers by discipline
Readers by discipline Count As %
Social Sciences 11 20%
Economics, Econometrics and Finance 7 13%
Medicine and Dentistry 3 5%
Decision Sciences 2 4%
Veterinary Science and Veterinary Medicine 1 2%
Other 5 9%
Unknown 27 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 15 May 2022.
All research outputs
#4,037,878
of 33,150,931 outputs
Outputs from PLOS ONE
#41,505
of 219,413 outputs
Outputs of similar age
#61,208
of 364,065 outputs
Outputs of similar age from PLOS ONE
#709
of 3,418 outputs
Altmetric has tracked 33,150,931 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 219,413 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.1. This one has done well, scoring higher than 80% of its peers.
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 364,065 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 3,418 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.