Evidence map›Paper›PMID 30421388›Full record

ArticleInternational journal of health economics and management2019

Genetic variation in health insurance coverage.

George L Wehby, Dan Shane

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of health economics and management, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Folk Classification and Factor Rotations: Whales, Sharks, and the Problems With the Hierarchical Taxonomy of Psychopathology (HiTOP).Clinical psychological science : a journal of the Association for Psychological Science · 2022
    Article
  3. Article
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

2 authors.

George L WehbyDepartment of Health Management and Policy, University of Iowa, 145 N. Riverside Dr., 100 College of Public Health Bldg., Room N250, Iowa City, IA, 52242-2007, USA. george-wehby@uiowa.edu.
Dan ShaneDepartment of Health Management and Policy, University of Iowa, 145 N. Riverside Dr., 100 College of Public Health Bldg., Room N250, Iowa City, IA, 52242-2007, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We provide the first investigation into whether and how much genes explain having health insurance coverage or not and possible mechanisms for genetic variation. Using a twin-design that compares identical and non-identical twins from a national sample of US twins from the National Survey of Midlife Development in the United States, we find that genetic effects explain over 40% of the variation in whether a person has any health coverage versus not, and nearly 50% of the variation in whether individuals younger than 65 have private coverage versus whether they have no coverage at all. Nearly one third of the genetic variation in being uninsured versus having private coverage is explained by employment industry, self-employment status, and income, and together with education, they explain over 40% of the genetic influence. Marital status, number of children, and available measures of health status, risk preferences, and prevention effort do not appear to be important channels for genetic effects. That genes have meaningful effects on the insurance status suggests an important source of heterogeneity in insurance take up.

Indexed as

Genetic VariationInsurance CoverageInsurance, HealthAdultAgedFemaleHumansMaleMiddle AgedTwin Studies as TopicUnited StatesGenetic variationHealth determinantsHealth insuranceRisk taking

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.