Evidence map›Paper›PMID 29334935›Full record

ArticleBMC public health2018

Adoption and diffusion of zoning bylaws banning fast food drive-through services across Canadian municipalities.

Candace I J Nykiforuk, Elizabeth J Campbell, Soultana Macridis, Daniel McKennitt, Kayla Atkey, Kim D Raine

Abstract read
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
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  7. Policy diffusion theory, evidence-informed public health, and public health political science: a scoping review.Canadian journal of public health = Revue canadienne de sante publique · 2023
    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

6 authors.

Candace I J NykiforukSchool of Public Health, 3-300 Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue, Edmonton, AB, T6G 1C9, Canada. candace.nykiforuk@ualberta.ca.
Elizabeth J CampbellSchool of Public Health, 3-300 Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Soultana MacridisAlberta Centre for Active Living, 2-131 University Hall, University of Alberta, 8840 114 St NW, Edmonton, AB, T6G 2H9, Canada.
Daniel McKennittSchool of Public Health, 3-300 Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Kayla AtkeyAlberta Policy Coalition for Chronic Disease Prevention, 4-343 Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, AB, T6G 1C9, Canada.
Kim D RaineSchool of Public Health, 3-300 Edmonton Clinic Health Academy, University of Alberta, 11405 87 Avenue, Edmonton, AB, T6G 1C9, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthy public policy is an important tool for creating environments that support human health and wellbeing. At the local level, municipal policies, such as zoning bylaws, provide an opportunity for governments to regulate building location and the type of services offered. Across North America, there has been a recent proliferation of municipal bylaws banning fast food drive-through services. Research on the utilization of this policy strategy, including bylaw adopters and adopter characteristics, is limited within the Canadian context. The aim of this study was to identify and characterize Canadian municipalities based on level of policy innovation and nature of their adopted bylaw banning fast food drive-through services.

methodsA multiple case history methodology was utilized to identify and analyse eligible municipal bylaws, and included development of a chronological timeline and map of adopter municipalities within Canada. Grey literature and policy databases were searched for potential adopters of municipal fast food drive-through service bylaws. Adopters were confirmed through evidence of current municipal bylaws. Geographic diffusion and diffusion of innovations theories provided a contextual framework for analysis of bylaw documents. Analysis included assignment of adopter-types, extent and purpose of bans, and policy learning activities of each adopter municipality.

resultsFrom 2002 to 2016, 27 municipalities were identified as adopters: six innovators and twenty-one early adopters. Mapping revealed parallel geographic diffusion patterns in western and eastern Canada. Twenty-two municipalities adopted a partial ban and five adopted a full ban. Rationales for the drive-through bans included health promotion, environmental concerns from idling, community character and aesthetics, traffic concerns, and walkability. Policy learning, including research and consultation with other municipalities, was performed by nine early adopters.

conclusionThis study detailed the adoption of fast food drive-through bylaws across Canada. Understanding the adopter-type characteristics of municipalities and the nature of their bylaws can assist other jurisdictions in similar policy efforts. While the implications for research and practice are evolving and dynamic, fast food drive-through service bans may play a role in promoting healthier food environments. Further research is required to determine the viability of this strategy for health promotion and chronic disease prevention.

Indexed as

Constitution and BylawsFast FoodsHealth PolicyCanadaCitiesHumansRestaurantsDiffusion of innovationsDrive-through servicesDrive-thruFast foodHealth promotionMunicipal bylawPolicy adoptionPolicy diffusionZoning

Identifiers

PMID29334935
PMCPMC5769538

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.