Evidence map›Paper›PMID 23849239›Full record

ArticleSocial science & medicine (1982)2013

Investigating the relationship between neighborhood poverty and mortality risk: a marginal structural modeling approach.

D Phuong Do, Lu Wang, Michael R Elliott

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. How does debt shape health outcomes for older Americans?Social science & medicine (1982) · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Poverty and survival from COVID-19 in Mexico.Journal of public health (Oxford, England) · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

D Phuong DoDepartment of Health Services Policy and Management, University of South Carolina, 800 Sumter St, Columbia, SC 29208, USA. dphuong@uwm.edu
Lu Wang
Michael R Elliott

Funding

Health, Wealth, and Wellbeing over the Life Course and Across GenerationsR01AG040213 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FRIEDMAN, ESTHER M. · 2011 to 2025
$31.2M
Family Dynamics, Fertility, and Investments in Children Across Generations - Administrative SupplementR01HD069609 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Thomas Fraser Crossley · 2011 to 2026
$14.2M
Causal Estimates of Neighborhood Poverty on Health and MortalityR21HD058715 · NICHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI DO, D. PHUONG · 2009 to 2010
$382k
NIA NIH HHS R01 AG040213NICHD NIH HHS R21 HD058715
6 · The paper itself

Abstract

Extant observational studies generally support the existence of a link between neighborhood context and health. However, estimating the causal impact of neighborhood effects from observational data has proven to be a challenge. Omission of relevant factors may lead to overestimating the effects of neighborhoods on health while inclusion of time-varying confounders that may also be mediators (e.g., income, labor force status) may lead to underestimation. Using longitudinal data from the 1990 to 2007 years of the Panel Study of Income Dynamics, this study investigates the link between neighborhood poverty and overall mortality risk. A marginal structural modeling strategy is employed to appropriately adjust for simultaneous mediating and confounding factors. To address the issue of possible upward bias from the omission of key variables, sensitivity analysis to assess the robustness of results against unobserved confounding is conducted. We examine two continuous measures of neighborhood poverty - single-point and a running average. Both were specified as piece-wise linear splines with a knot at 20 percent. We found no evidence from the traditional naïve strategy that neighborhood context influences mortality risk. In contrast, for both the single-point and running average neighborhood poverty specifications, the marginal structural model estimates indicated a statistically significant increase in mortality risk with increasing neighborhood poverty above the 20 percent threshold. For example, below 20 percent neighborhood poverty, no association was found. However, after the 20 percent poverty threshold is reached, each 10 percentage point increase in running average neighborhood poverty was found to increase the odds for mortality by 89 percent [95% CI = 1.22, 2.91]. Sensitivity analysis indicated that estimates were moderately robust to omitted variable bias.

Indexed as

Poverty AreasAdultAgedFemaleHumansLongitudinal StudiesMaleMiddle AgedModels, StatisticalMortalityResidence CharacteristicsRisk FactorsSocioeconomic FactorsUnited StatesCausal modelingLongitudinal analysisMarginal structural modelingNeighborhood effectsSensitivity analysis

Identifiers

PMID23849239
PMCPMC4180500

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.