ArticleAmerican journal of epidemiology2021
Invited Commentary: Methods for Estimating Effects of Minimum Wages on Health.
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Income trajectories and self-rated health status in the UK.SSM - population health · 2022Article
- Buszkiewicz et al. Respond to "Methods to Estimate Minimum Wage Health Effects".American journal of epidemiology · 2021Article
- RE: "INVITED COMMENTARY: METHODS FOR ESTIMATING EFFECTS OF MINIMUM WAGES ON HEALTH".American journal of epidemiology · 2020Article
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Economists have been researching effects of minimum wages on unemployment, poverty, income inequality, and educational attainment for over 60 years. Epidemiologists have only recently begun researching minimum wages even though unemployment through education are central topics within social epidemiology. Buszkiewicz et al. (Am J Epidemiol. 2021;190(1):21-30) offer a welcome addition to this nascent literature. A commanding advantage of Buszkiewicz et al.'s study over others is its distinction between a "likely affected" group comprised of workers with ≤12 years of schooling versus "not likely affected" groups with ≥13 years of schooling. But there are disadvantages, common to other studies. Buszkiewicz et al. use cross-sectional data; they include the self-employed as well as part-time and part-year workers in their treatment groups. Their definitions of affected groups based on education create samples with 75% or more of workers who earn significantly above minimum wages; definitions are not based on wages. Inclusion of workers not subject to (e.g., self-employed) or affected by minimum wages biases estimates toward the null. Finally, within any minimum wage data set, it is the state-not federal-increases that account for the lion's share of increases and that form the natural experiments; however, state increases can occur annually whereas the development of chronic diseases might take decades.
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What OpenQuestion holds
Registered trials
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.