<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="letter"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Form Res</journal-id><journal-id journal-id-type="publisher-id">formative</journal-id><journal-id journal-id-type="index">27</journal-id><journal-title>JMIR Formative Research</journal-title><abbrev-journal-title>JMIR Form Res</abbrev-journal-title><issn pub-type="epub">2561-326X</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v10i1e81581</article-id><article-id pub-id-type="doi">10.2196/81581</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Letter</subject></subj-group></article-categories><title-group><article-title>Association Between Availability of Fruits and Vegetables in Neighborhood Food Stores and Weight Among Residents of Low-Income Urban Public Housing: Cross-Sectional Study</article-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Leung</surname><given-names>Robert</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Frank</surname><given-names>Allison</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Ranker</surname><given-names>Lynsie R</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Murillo</surname><given-names>Jennifer</given-names></name><degrees>MS</degrees><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Lane</surname><given-names>Kevin J</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Popp</surname><given-names>Zachary T</given-names></name><degrees>MPH</degrees><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Kane</surname><given-names>John</given-names></name><degrees>MPP</degrees><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Xuan</surname><given-names>Ziming</given-names></name><degrees>SCD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Borrelli</surname><given-names>Belinda</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff6">6</xref></contrib><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Quintiliani</surname><given-names>Lisa M</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="aff" rid="aff7">7</xref></contrib></contrib-group><aff id="aff1"><institution>Veterans Administration Boston Healthcare System</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff2"><institution>Department of Community Health Sciences, Boston University School of Public Health</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff3"><institution>Division of General Internal Medicine, Tufts Medical Center</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff4"><institution>Department of Environmental Health Sciences, Boston University School of Public Health</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff5"><institution>Boston Housing Authority</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff6"><institution>Center for Behavioral Science Research, Boston University Henry M Goldman School of Dental Medicine</institution><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><aff id="aff7"><institution>Department of Medicine, Tufts University</institution><addr-line>185 Harrison Ave, Center Building, 2nd Floor</addr-line><addr-line>Boston</addr-line><addr-line>MA</addr-line><country>United States</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Stone</surname><given-names>Alicia</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Melnick</surname><given-names>Emily M</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>DeWeese</surname><given-names>Robin</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Lisa M Quintiliani, PhD, Department of Medicine, Tufts University, 185 Harrison Ave, Center Building, 2nd Floor, Boston, MA, 02111, United States, 1 617-636-5346, 1 617-636-8568; <email>lisa.quintiliani@tuftsmedicine.org</email></corresp></author-notes><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>9</day><month>2</month><year>2026</year></pub-date><volume>10</volume><elocation-id>e81581</elocation-id><history><date date-type="received"><day>31</day><month>07</month><year>2025</year></date><date date-type="rev-recd"><day>17</day><month>12</month><year>2025</year></date><date date-type="accepted"><day>06</day><month>01</month><year>2026</year></date></history><copyright-statement>&#x00A9; Robert Leung, Allison Frank, Lynsie R Ranker, Jennifer Murillo, Kevin J Lane, Zachary T Popp, John Kane, Ziming Xuan, Belinda Borrelli, Lisa M Quintiliani. Originally published in JMIR Formative Research (<ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>), 9.2.2026. </copyright-statement><copyright-year>2026</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://formative.jmir.org/2026/1/e81581"/><abstract><p>This cross-sectional study examined the presence of food stores and availability of fruits and vegetables in food stores with weight among urban public housing residents. While there was no association between average number of fruits or vegetables in food stores and weight, there were positive associations between number of convenience stores and weight and between number of general merchandise stores and weight.</p></abstract><kwd-group><kwd>food environment</kwd><kwd>fruits</kwd><kwd>vegetables</kwd><kwd>low-income</kwd><kwd>weight</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Though food environments are recognized as determinants of socioeconomic diet&#x2013;related health disparities, there is less evidence delineating specific elements of food environments that contribute to bodyweight [<xref ref-type="bibr" rid="ref1">1</xref>]. Previous literature is limited by variability in measurement approaches and a lack of capturing multiple food retail environments [<xref ref-type="bibr" rid="ref1">1</xref>]. Among adults, a systematic review or meta-analysis assessing impact of food environments on obesity included only two studies with general merchandise stores as part of their analyses [<xref ref-type="bibr" rid="ref1">1</xref>]. Furthermore, much research about general merchandise stores focuses on rural areas and children or adolescent populations, prompting evaluation among adults in urban areas [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref3">3</xref>]. This study&#x2019;s objective was to examine associations between two measures of food access: (1) presence of food stores (overall and by store types) and (2) availability of fruits and vegetables with weight at study enrollment among residents of urban public housing developments participating in a clinical trial for weight management [<xref ref-type="bibr" rid="ref4">4</xref>].</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Design</title><p>This is a cross-sectional analysis of baseline data from a clinical trial (<xref ref-type="table" rid="table1">Table 1</xref>) [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref4">4</xref>] along with neighborhood food store audit data collected by research personnel.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Description of the Path to Health Behavioral Clinical Trial for Weight Management (Recruitment period: 2021-2024; ClinicalTrials.gov #NCT04852042) [<xref ref-type="bibr" rid="ref4">4</xref>]</p></caption><table id="table1" frame="hsides" rules="groups"><tbody><tr><td align="left" valign="top">Randomized groups</td><td align="left" valign="top">&#x2022; Participants were randomized to:<break/>&#x00BA; Assessment only control (Control);<break/>&#x00BA; mHealth weight management intervention (Text messaging program and weight monitoring via digital scale) (mHealth only);<break/>&#x00BA; mHealth intervention plus motivational interviewing-based behavioral counseling delivered by a community health worker (mHealth+CHW)</td></tr><tr><td align="left" valign="top">Primary objective</td><td align="left" valign="top">&#x2022; To evaluate if the mHealth+CHW intervention demonstrates efficacy for weight loss<break/>&#x2022; Primary hypothesis: Both mHealth+CHW and mHealth only will outperform assessment only control and mHealth+CHW will outperform mHealth only in terms of weight loss at 12 months.</td></tr><tr><td align="left" valign="top">Eligibility criteria</td><td align="left" valign="top">&#x2022; Trial inclusion criteria were: age &#x003E;=18 years old; residents of Boston public housing; BMI &#x003E;=27.0, and read/write English or Spanish (full criteria available [<xref ref-type="bibr" rid="ref4">4</xref>]).</td></tr><tr><td align="left" valign="top">Study setting</td><td align="left" valign="top">&#x2022; Our study setting consisted of family-designated housing developments (n=17) in the City of Boston managed by the Boston Housing Authority (n=9) or private property management companies (n=8) which receive subsidies for renting to low-income households.</td></tr><tr><td align="left" valign="top">Baseline characteristics</td><td align="left" valign="top">&#x2022; Among 286 participants, 83.2% were female, 70.6% were Hispanic, 63.6% with up to high school education, with mean age of 53.6 (SD 14) years and mean weight of 188.1 (SD 42.9) pounds.</td></tr></tbody></table></table-wrap></sec><sec id="s2-2"><title>Measures</title><sec id="s2-2-1"><title>Weight</title><p>Research personnel measured participant (n=286) weight via scale during in-person, in-home baseline study visits [<xref ref-type="bibr" rid="ref4">4</xref>].</p></sec><sec id="s2-2-2"><title>Food Store Audit Instrument</title><p>Pairs of research personnel conducted in-store audits using the Food Environment Audit for Diverse Neighborhoods to identify food availability [<xref ref-type="bibr" rid="ref5">5</xref>].</p></sec></sec><sec id="s2-3"><title>Data Analysis</title><p>Food access measures (number of food stores; total count of available fruits and vegetables or audited food store) were assigned to individual participants in the clinical trial, based on their public housing development of residence. We used separate generalized linear models examining associations between each access metric and participant weight at baseline. Specifically, we used generalized estimating equations to account for clustering of participants within housing developments (adjusted for resident age, gender, Hispanic ethnicity, and education). The model coefficient represents the difference in weight at baseline enrollment with a one-unit increase in count (ie, one additional store, or one additional fruit and vegetable available). Additional models adjusting for height were conducted (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). See <xref ref-type="table" rid="table2">Table 2</xref> footnotes for details.</p><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Descriptive information and associations between food access measures (number of food stores and availability of fruits and vegetables) and baseline weight (n=286 participants).</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Descriptive information</td><td align="left" valign="bottom">Values</td></tr></thead><tbody><tr><td align="left" valign="top">Total number of food stores within 1 mile, mean (SD)</td><td align="char" char="." valign="top">23.6 (13.9)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Supermarkets/other grocery stores</td><td align="left" valign="top">11.1 (7.1)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>General merchandise/dollar stores</td><td align="left" valign="top">2.5 (1.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Convenience stores</td><td align="left" valign="top">10.1 (6.5)</td></tr><tr><td align="left" valign="top" colspan="2">Fruits (fresh, frozen, canned, juice), vegetables (fresh, frozen, canned, juice), and beans (canned, dried) available in all audited food stores (n=31<bold>)</bold></td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>At least one type of fruits &#x0026; vegetables available, n (%)</td><td align="left" valign="top">30 (96.8)</td></tr><tr><td align="left" valign="top">&#x2003;10 or more types of fruits &#x0026; vegetables available, n (%)</td><td align="left" valign="top">24 (77.4)</td></tr><tr><td align="left" valign="top">&#x2003;Number of fruits &#x0026; vegetables, mean (SD)</td><td align="left" valign="top">32.6 (39.2)</td></tr><tr><td align="left" valign="top">Number of stores within 1 mile, unadjusted difference in weight (95% CI)</td><td align="char" char="." valign="top">0.34 (-0.06, 0.73)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Supermarkets/other grocery stores</td><td align="char" char="." valign="top">0.03 (-1.06, 1.12)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>General merchandise/dollar stores<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup></td><td align="char" char="." valign="top">3.11 (0.45, 5.76)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Convenience stores</td><td align="char" char="." valign="top">1.12 (0.34, 1.91)</td></tr><tr><td align="left" valign="top">Number of stores<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup> within 1 mile, adjusted<sup><xref ref-type="table-fn" rid="table2fn2">b</xref></sup> difference in weight (95% CI)</td><td align="left" valign="top">0.33 (&#x2212;0.05, 0.71)</td></tr><tr><td align="left" valign="top">&#x2003;Supermarkets/other grocery stores</td><td align="left" valign="top">0.25 (&#x2212;0.51, 1.01)</td></tr><tr><td align="left" valign="top">&#x2003;General merchandise/dollar stores<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup></td><td align="left" valign="top">3.08 (1.31, 4.85)</td></tr><tr><td align="left" valign="top">&#x2003;Convenience stores</td><td align="left" valign="top">0.87 (0.02, 1.72)</td></tr><tr><td align="left" valign="top">Number of fruits and vegetables,<sup><xref ref-type="table-fn" rid="table2fn3">c</xref></sup> unadjusted difference in weight (95% CI)</td><td align="char" char="." valign="top">0.09 (-0.36, 0.53)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Supermarkets/other grocery stores</td><td align="char" char="." valign="top">0.02 (-0.13, 0.17)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>General merchandise/dollar stores<sup><xref ref-type="table-fn" rid="table2fn4">d</xref></sup></td><td align="char" char="." valign="top">0.05 (-0.38, 0.49)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Convenience stores</td><td align="char" char="." valign="top">0.58 (-0.88, 1.41)</td></tr><tr><td align="left" valign="top">Number of fruits and vegetables<sup><xref ref-type="table-fn" rid="table2fn3">c</xref></sup> (Adjusted<sup><xref ref-type="table-fn" rid="table2fn2">b</xref></sup> difference in weight (95% CI)</td><td align="left" valign="top">0.08 (&#x2212;0.26, 0.41)</td></tr><tr><td align="left" valign="top">&#x2003;Supermarkets/other grocery stores</td><td align="left" valign="top">0.02 (&#x2212;0.11, 0.14)</td></tr><tr><td align="left" valign="top">&#x2003;General merchandise/dollar stores<sup><xref ref-type="table-fn" rid="table2fn4">d</xref></sup></td><td align="left" valign="top">0.10 (&#x2212;0.22, 0.41)</td></tr><tr><td align="left" valign="top">&#x2003;Convenience stores</td><td align="left" valign="top">0.30 (&#x2212;0.40, 1.00)</td></tr></tbody></table><table-wrap-foot><fn id="table2fn1"><p><sup>a</sup><italic>Identification of Food Stores</italic>: We used a commercial database called Data Axle Reference Solutions which contained location and business data on all U.S. businesses. Addresses for public housing developments and food stores were geocoded. ArcGIS Pro version 3.0 was used to model walking distance for one mile around public housing developments where participants lived. We chose one mile in order to capture a wide range of available food stores [<xref ref-type="bibr" rid="ref6">6</xref>]. We identified three food store types using the North American Industry Classification Codes [NAICS], specifically including stores coded as: grocery stores (NAICS: 445110) retailing canned and frozen foods, fresh fruits and vegetables, and fresh and prepared meats, fish, and poultry; convenience stores (NAICS: 445120) retailing a limited line of goods including milk, bread, soda, and snacks; and all other general merchandise stores (NAICS: 452319) retailing general merchandise including dry goods as well as other merchandise such as apparel, housewares, and home furnishings. These food stores were categorized according to NAICS criteria. Our data manager used a random number generator to select one store to be audited from each food store category corresponding to each public housing development included in the Path to Health trial. We also measured food access via the total number of stores (and number within each food store category) within the walking buffer. Prior to conducting the audits, research staff conducted a spot check that actual store matched the expected store. In the audit, fruits and vegetables were counted as present or not present, instead of the actual number of individual fruits and vegetables.</p></fn><fn id="table2fn2"><p><sup>b</sup>Separate generalized linear models adjusted for resident age, gender, Hispanic ethnicity, and education accounting for clustering within housing developments.</p></fn><fn id="table2fn3"><p><sup>c</sup>Data represents food audits at eleven food store locations: Three groups of two public housing developments and one group of four public housing developments located within one mile of each other were combined into a single audit location due to proximity and overlapping identification of food stores. This process resulted in eleven unique food audit locations. From 11 audit locations (which corresponded to 17 housing developments), we audited 31 food stores (2 housing developments did not have a general merchandise store available for auditing). The total count of unique fruits, vegetables, and bean types available was created for each audited store and then these counts were averaged within each audit location.</p></fn><fn id="table2fn4"><p><sup>d</sup>n=236 participants, due to the exclusion of two housing developments that did not have a general merchandise store available for auditing.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s2-4"><title>Ethical Considerations</title><p>Boston University Medical Campus Institutional Review Board approved this analysis (H-41590). The original written consent process covered this analysis without additional consent. Privacy was ensured by deidentifying data with code numbers. Participants were paid US $50 for completing baseline assessment activities.</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><p>There was no association between overall number of food stores and baseline weight nor between average number of fruits and vegetables in audited food store locations and baseline weight (adjusted difference in weight: 0.33, [95% CI &#x2212;0.05,0.71 and 0.08, 95% CI: &#x2212;0.26, 0.41 pounds, respectively). When food store type was examined, there were positive associations between number of convenience stores and baseline weight and between number of general merchandise stores and baseline weight (adjusted difference in weight: 0.87, 95% CI: 0.02, 1.72 and 3.08, 95% CI: 1.31, 4.85 pounds, respectively) (<xref ref-type="table" rid="table2">Table 2</xref>). Additional adjustment for height resulted in associations in a similar direction, with a small attenuation in magnitude (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>).</p></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>The number of convenience stores and general merchandise stores within a one-mile walking distance radius of public housing developments were associated with higher baseline weight, after adjusting for potential confounding factors. Unlike findings from systematic reviews or meta-analyses [<xref ref-type="bibr" rid="ref1">1</xref>], we did not observe associations with number of grocery stores and baseline weight or availability of fruits and vegetables at audited food stores and baseline weight. Weight status is multifactorial and therefore, auditing a larger variety of foods may have been necessary to observe an association with weight. Others also noted lack of associations between new grocery stores and healthful eating among public housing residents [<xref ref-type="bibr" rid="ref7">7</xref>]. Overall, neighborhood environment deprivation factors like lack of safe physical activity areas can all contribute to adverse health behaviors and outcomes.</p><p>Dollar stores are the fastest growing food retail type by share of household expenditure in the United States [<xref ref-type="bibr" rid="ref3">3</xref>], raising concerns about nutrition and health-related outcomes [<xref ref-type="bibr" rid="ref8">8</xref>] and impact on local businesses, staffing shortages, and overall cleanliness [<xref ref-type="bibr" rid="ref9">9</xref>]. Municipalities have taken policy actions to address concerns including: moratoriums (prohibit new store openings for specified period) and conditional use ordinances (require local government to assess how proposed store aligns with certain conditions) [<xref ref-type="bibr" rid="ref9">9</xref>]. Obtaining perspectives from key constituents and forming partnerships (eg, community members or policy makers workshops) can lead to creation of fair policies for equitable benefit [<xref ref-type="bibr" rid="ref10">10</xref>].</p><p>This study benefited from a standardized validated audit data collection instrument and included diverse food stores. Limitations included: lack of consideration for sales volume; audits represented snapshots of food available that particular day or season; and inclusion of clinical trial participants potentially limited generalizability.</p><p>Our study suggests cross-sectional relationships between presence of convenience stores and general merchandise stores and higher weight among residents that were overweight or with obesity living in nearby public housing developments; findings may inform design of community-level food store policies.</p></sec></body><back><ack><p>We are grateful to Dariela Romero, Ava Herzer, Christina Morcos, and Karishma Parekh for their assistance with food store audit data collection.</p></ack><notes><sec><title>Funding</title><p>Funding is provided by the National Cancer Institute, R01CA238335 (PI: Quintiliani). The funder had no involvement in the study design, data collection, analysis, interpretation, or the writing of the manuscript. Generative AI was not used in any portion of the manuscript.</p></sec><sec><title>Data Availability</title><p>The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.</p></sec></notes><fn-group><fn fn-type="con"><p>Conceptualization: LQ</p><p>Data curation: AF (lead), LR (supporting), KL (supporting), ZP (supporting)</p><p>Formal analysis: LR (lead), AF (supporting)</p><p>Funding acquisition: LQ (lead)</p><p>Methodology: ZX (lead), BB (equal), KL (supporting), ZP (supporting)</p><p>Project administration: JM (lead)</p><p>Supervision: LQ (lead)</p><p>Writing &#x2013; original draft: RL (lead), LQ (equal)</p><p>Writing &#x2013; review &#x0026; editing: LQ (lead), RL (equal), AF (supporting), LR (supporting), JM (supporting), KL (supporting), ZP (supporting), JK (supporting), ZX (supporting), BB (supporting)</p></fn><fn fn-type="conflict"><p>None declared.</p></fn></fn-group><ref-list><title>References</title><ref id="ref1"><label>1</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Pineda</surname><given-names>E</given-names> </name><name name-style="western"><surname>Stockton</surname><given-names>J</given-names> </name><name name-style="western"><surname>Scholes</surname><given-names>S</given-names> </name><name name-style="western"><surname>Lassale</surname><given-names>C</given-names> </name><name name-style="western"><surname>Mindell</surname><given-names>JS</given-names> </name></person-group><article-title>Food environment and obesity: a systematic review and meta-analysis</article-title><source>BMJ Nutr Prev Health</source><year>2024</year><volume>7</volume><issue>1</issue><fpage>204</fpage><lpage>211</lpage><pub-id pub-id-type="doi">10.1136/bmjnph-2023-000663</pub-id><pub-id pub-id-type="medline">38966119</pub-id></nlm-citation></ref><ref id="ref2"><label>2</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Gorski Findling</surname><given-names>MT</given-names> </name><name name-style="western"><surname>Wolfson</surname><given-names>JA</given-names> </name><name name-style="western"><surname>Rimm</surname><given-names>EB</given-names> </name><name name-style="western"><surname>Bleich</surname><given-names>SN</given-names> </name></person-group><article-title>Differences in the neighborhood retail food environment and obesity among us children and adolescents by SNAP Participation</article-title><source>Obesity (Silver Spring)</source><year>2018</year><month>06</month><volume>26</volume><issue>6</issue><fpage>1063</fpage><lpage>1071</lpage><pub-id pub-id-type="doi">10.1002/oby.22184</pub-id><pub-id pub-id-type="medline">29797558</pub-id></nlm-citation></ref><ref id="ref3"><label>3</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Feng</surname><given-names>W</given-names> </name><name name-style="western"><surname>Page</surname><given-names>ET</given-names> </name><name name-style="western"><surname>Cash</surname><given-names>SB</given-names> </name></person-group><article-title>Dollar stores and food access for rural households in the United States, 2008&#x2012;2020</article-title><source>Am J Public Health</source><year>2023</year><month>03</month><volume>113</volume><issue>3</issue><fpage>331</fpage><lpage>336</lpage><pub-id pub-id-type="doi">10.2105/AJPH.2022.307193</pub-id><pub-id pub-id-type="medline">36657091</pub-id></nlm-citation></ref><ref id="ref4"><label>4</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Solar</surname><given-names>C</given-names> </name><name name-style="western"><surname>Nansubuga</surname><given-names>A</given-names> </name><name name-style="western"><surname>Murillo</surname><given-names>J</given-names> </name><etal/></person-group><article-title>Mobile health plus community health worker support for weight management among public housing residents (Path to Health): a randomized controlled trial protocol</article-title><source>Contemp Clin Trials</source><year>2022</year><month>08</month><volume>119</volume><fpage>106836</fpage><pub-id pub-id-type="doi">10.1016/j.cct.2022.106836</pub-id><pub-id pub-id-type="medline">35724842</pub-id></nlm-citation></ref><ref id="ref5"><label>5</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Izumi</surname><given-names>BT</given-names> </name><name name-style="western"><surname>Zenk</surname><given-names>SN</given-names> </name><name name-style="western"><surname>Schulz</surname><given-names>AJ</given-names> </name><etal/></person-group><article-title>Inter-rater reliability of the food environment audit for diverse neighborhoods (FEAD-N)</article-title><source>J Urban Health</source><year>2012</year><month>06</month><volume>89</volume><issue>3</issue><fpage>486</fpage><lpage>499</lpage><pub-id pub-id-type="doi">10.1007/s11524-011-9657-3</pub-id><pub-id pub-id-type="medline">22350513</pub-id></nlm-citation></ref><ref id="ref6"><label>6</label><nlm-citation citation-type="web"><article-title>Access to affordable and nutritious food: updated estimates of distance to supermarkets using 2010 data</article-title><source>Economic Research Service</source><access-date>2025-04-12</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://www.ers.usda.gov/publications/pub-details?pubid=45035#overview">https://www.ers.usda.gov/publications/pub-details?pubid=45035#overview</ext-link></comment></nlm-citation></ref><ref id="ref7"><label>7</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Datar</surname><given-names>A</given-names> </name><name name-style="western"><surname>Liu</surname><given-names>Y</given-names> </name><name name-style="western"><surname>Shier</surname><given-names>V</given-names> </name></person-group><article-title>Supermarket opening in an urban, low-income community was not found to be associated with improvements in dietary outcomes for most residents in the first year</article-title><source>J Acad Nutr Diet</source><year>2025</year><month>06</month><volume>125</volume><issue>6</issue><fpage>736</fpage><lpage>750</lpage><pub-id pub-id-type="doi">10.1016/j.jand.2024.08.005</pub-id><pub-id pub-id-type="medline">39181395</pub-id></nlm-citation></ref><ref id="ref8"><label>8</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Sundermeir</surname><given-names>SM</given-names> </name><name name-style="western"><surname>Matsuzaki</surname><given-names>M</given-names> </name><name name-style="western"><surname>Zhang</surname><given-names>A</given-names> </name><name name-style="western"><surname>Obi</surname><given-names>JC</given-names> </name><name name-style="western"><surname>Gittelsohn</surname><given-names>J</given-names> </name><name name-style="western"><surname>Winkler</surname><given-names>MR</given-names> </name></person-group><article-title>Characterizing the consumer food environment of dollar stores and exploring differences by neighborhood racial composition</article-title><source>J Nutr Educ Behav</source><year>2025</year><month>10</month><volume>57</volume><issue>10</issue><fpage>972</fpage><lpage>979</lpage><pub-id pub-id-type="doi">10.1016/j.jneb.2025.06.007</pub-id><pub-id pub-id-type="medline">40650649</pub-id></nlm-citation></ref><ref id="ref9"><label>9</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Sundermeir</surname><given-names>SM</given-names> </name><name name-style="western"><surname>Santos</surname><given-names>SR</given-names> </name><name name-style="western"><surname>Lewis</surname><given-names>EC</given-names> </name><etal/></person-group><article-title>Dollar store policy opportunities in Baltimore City: community member and policy maker perspectives</article-title><source>Front Nutr</source><year>2024</year><volume>11</volume><fpage>1399402</fpage><pub-id pub-id-type="doi">10.3389/fnut.2024.1399402</pub-id><pub-id pub-id-type="medline">38818134</pub-id></nlm-citation></ref><ref id="ref10"><label>10</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Langellier</surname><given-names>BA</given-names> </name><name name-style="western"><surname>Argibay</surname><given-names>S</given-names> </name><name name-style="western"><surname>Henson</surname><given-names>RM</given-names> </name><etal/></person-group><article-title>Participatory systems thinking to elucidate drivers of food access and diet disparities among minoritized urban populations</article-title><source>J Urban Health</source><year>2024</year><month>12</month><volume>101</volume><issue>6</issue><fpage>1235</fpage><lpage>1247</lpage><pub-id pub-id-type="doi">10.1007/s11524-024-00895-3</pub-id></nlm-citation></ref></ref-list><app-group><supplementary-material id="app1"><label>Multimedia Appendix 1</label><p>Descriptive information and associations between food access measures (number of food stores and availability of fruits and vegetables) and baseline weight.</p><media xlink:href="formative_v10i1e81581_app1.docx" xlink:title="DOCX File, 68 KB"/></supplementary-material></app-group></back></article>