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The impact of retirement on health: quasi-experimental methods using administrative data

Overview of attention for article published in BMC Health Services Research, February 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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5 news outlets
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10 X users
facebook
1 Facebook page

Citations

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25 Dimensions

Readers on

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114 Mendeley
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Title
The impact of retirement on health: quasi-experimental methods using administrative data
Published in
BMC Health Services Research, February 2016
DOI 10.1186/s12913-016-1318-5
Pubmed ID
Authors

Elizabeth Mokyr Horner, Mark R. Cullen

Abstract

Is retirement good or bad for health? Disentangling causality is difficult. Much of the previous quasi-experimental research on the effect of health on retirement used self-reported health and relied upon discontinuities in public retirement incentives across Europe. The current study investigated the effect of retirement on health by exploiting discontinuities in private retirement incentives to test the effect of retirement on health using a quasi-experimental study design. Secondary data (1997-2009) on a cohort of male manufacturing workers in a United States setting. Health status was determined using claims data from private insurance and Medicare. Analyses used employer-based administrative and claims data and claim data from Medicare. Widely used selection on observables models overstate the negative impact of retirement due to the endogeneity of the decision to retire. In addition, health status as measured by administrative claims data provide some advantages over the more commonly used survey items. Using an instrument and administrative health records, we find null to positive effects from retirement on all fronts, with a possible exception of increased risk for diabetes. This study provides evidence that retirement is not detrimental and may be beneficial to health for a sample of manufacturing workers. In addition, it supports previous research indicating that quasi-experimental methodologies are necessary to evaluate the relationship between retirement and health, as any selection on observable model will overstate the negative relationship of retirement on health. Further, it provides a model for how such research could be implemented in countries like the United States that do not have a strong public pension program. Finally, it demonstrates that such research need-not rely upon survey data, which has certain shortcomings and is not always available for homogenous samples.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Switzerland 1 <1%
Unknown 112 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 21%
Researcher 23 20%
Student > Master 17 15%
Student > Doctoral Student 11 10%
Student > Bachelor 7 6%
Other 18 16%
Unknown 14 12%
Readers by discipline Count As %
Social Sciences 25 22%
Psychology 19 17%
Medicine and Dentistry 13 11%
Economics, Econometrics and Finance 12 11%
Nursing and Health Professions 8 7%
Other 18 16%
Unknown 19 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. 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 18 December 2020.
All research outputs
#741,101
of 23,881,329 outputs
Outputs from BMC Health Services Research
#167
of 7,949 outputs
Outputs of similar age
#13,503
of 300,366 outputs
Outputs of similar age from BMC Health Services Research
#4
of 89 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,949 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 98% 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 300,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.