Evidence map›Paper›PMID 34697089›Full record

ArticleTobacco control2022

Using place-based characteristics to inform FDA tobacco sales inspections: results from a multilevel propensity score model.

Hongying Dai, Lisa Henriksen, Zheng Xu, Nirosha Rathnayake

Open access · hybridAbstract read
In one paragraph

Article in Tobacco control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
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

7 citing papers in PubMed, 8 citations in OpenAlex.

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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

4 authors at 4 institutions in 1 country.

Hongying DaiDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, USA daisy.dai@unmc.edu.ORCID 0000-0003-1395-7904
Lisa HenriksenStanford Prevention Research Center, Stanford UniversitySchool of Medicine, Stanford, California, USA.
Zheng XuDepartment of Mathematics and Statistics, Wright State University, Dayton, Ohio, USA.
Nirosha RathnayakeDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, USA.ORCID 0000-0001-8072-0216
Nebraska Medical Center · USStanford University · USUniversity of Nebraska Medical Center · USWright State University · US

Funding

Effects of the FDA Compliance Inspections of Tobacco Retailers on Youth E-cigarette and Cigar Use: A National StudyR03CA228909 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI DAI, HONGYING DAISY · 2018 to 2019
$165k
NCI NIH HHS R03 CA228909
6 · The paper itself

Abstract

backgroundConducting routine inspections for compliance with age-of-sale laws is essential to reducing underage access to tobacco. We seek to develop a multilevel propensity score model (PSM) to predict retail violation of sales to minors (RVSM).

methodsThe Food and Drug Administration compliance check of tobacco retailers with minor-involved inspections from 2015 to 2019 (n=683 741) was linked with multilevel data for demographics and policies. Generalised estimating equation was used to develop the PSM using 2015-2016 data to predict the 2017 RVSM. The prediction accuracy of the PSM was validated by contrasting PSM deciles against 2018-2019 actual violation data.

resultsIn 2017, 44.3% of 26 150 zip codes with ≥1 tobacco retailer had 0 FDA underage sales inspections, 11.0% had 1 inspection, 13.5% had 2-3, 15.3% had 4-9, and 15.9% had 10 or more. The likelihood of having an RVSM in 2017 was higher in zip codes with a lower number of inspections (adjusted OR (aOR)=0.988, 95% CI (0.987 to 0.990)) and penalties (aOR=0.97, 95% CI (0.95 to 0.99)) and a higher number of violations (aOR=1.07, 95% CI (1.06 to 1.08)) in the previous 2 years. Urbanicity, socioeconomic status, smoking prevalence and tobacco control policies at multilevels also predicted retail violations. Prediction accuracy was validated with zip codes with the highest 10% of the PSM 3.4 times more likely to have retail violations in 2019 than zip codes in the bottom decile.

conclusionThe multilevel PSM predicts the RVSM with a good rank order of retail violations. The model-based approach can be used to identify hot spots of retail violations and improve the sampling plan for future inspections.

Indexed as

Tobacco ProductsCommerceHumansPropensity ScoreUnited StatesUnited States Food and Drug Administrationenvironmentpublic policysurveillance and monitoring

Identifiers

PMID34697089
PMCPMC9726945
OpenAlexW3208998592

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.