Evidence map›Paper›PMID 39208951›Full record

ArticlePreventive medicine2024

Food insecurity trends and disparities according to immigration status in the US households, 2011-2021.

Junxiu Liu, Zhiyang Zhou, Xi Cheng, Donglan Zhang, Lihua Li, Xiaotao Zhang, Nita Vangeepuram

Abstract read
In one paragraph

Article in Preventive medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Food and Nutrition Insecurity in Kidney Disease: Practitioner Considerations.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Review
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

7 authors.

Junxiu LiuDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America. Electronic address: junxiu.liu@mountsinai.org.
Zhiyang ZhouJoseph J. Zilber College of Public Health at the University of Wisconsin, Milwaukee, United States of America.
Xi ChengThe Interdisciplinary Program of Science in Analytics, Georgia Institute of Technology, Atlanta, GA, United States of America.
Donglan ZhangNew York University Langone Health, New York, NY, United States of America; Long Island School of Medicine, New York University, New York, NY, United States of America.
Lihua LiDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America; Institute for Healthcare Delivery Science, Mount Sinai Health System, New York, NY, United States of America; Tisch Cancer Institute, New York, NY, United States of America; Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Xiaotao ZhangInstitute for Translational Epidemiology & Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
Nita VangeepuramDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.

Funding

Using machine learning and causal inference approaches to investigate disparities in Alzheimer’s disease and related dementias outcomesR01MD013886 · NIMHD · UNIVERSITY OF GEORGIA · PI ZHANG, DONGLAN · 2019 to 2022
$2.4M
NIMHD NIH HHS R01 MD013886
6 · The paper itself

Abstract

backgroundFood insecurity related to immigration status remains largely underexplored. This study examined trends and disparities in household food insecurity by immigration status in the United States (US).

methodsWe analyzed data from 427,942 households from the US Current Population Survey Food Security Supplement from 2011 to 2021. Immigration status categories included recent immigrants (< 5 years), long-term immigrants (≥ 5 years), naturalized citizens, and US-born citizens. Food insecurity was assessed using validated questions on consistent access to enough food for an active and healthy life.

resultsFrom 2011 to 2021, food insecurity prevalence declined from 14.9 % (95 % CI, 14.5 %-15.3 %) to 10.2 % (95 % CI, 9.8 %-10.6 %). Among recent immigrants, prevalence decreased from 25.2 % (95 % CI, 23.1-27.4) in 2011 to 15.0 % (95 % CI, 12.8 %-17.2 %) in 2019, then increased to 17.7 % (95 % CI, 14.7 %-20.2 %) in 2020 and 17.4 % (95 % CI, 14.7 %-20.2 %) in 2021. Long-term immigrants' prevalence dropped from 20.4 % (95 % CI, 16.9 %-24.0 %) in 2011 to 10.2 % (95 % CI, 7.2 %-13.1 %) in 2018, then increased to 17.7 % (95 % CI, 13.7 %-21.7 %) in 2021. Naturalized citizens' prevalence decreased from 14.4 % (95 % CI, 12.9 %-15.9 %) to 9.5 % (95 % CI, 8.2 %-10.9 %). US-born citizens' prevalence decreased from 14.2 % (95 % CI, 13.8 %-14.6 %) to 9.7 % (95 % CI, 9.3 %-10.2 %). Compared to the US-born citizens, the adjusted prevalence ratio was 1.63 (95 % CI,1.57-1.69) for recent immigrants, 1.22 (95 % CI, 1.13-1.31) for long-term immigrants, and 0.94 (95 % CI, 0.90-0.98) for naturalized citizens. Significant disparities exist in subgroups.

conclusionsThe findings provide insights for stakeholders to address food insecurity among vulnerable immigrant groups in the US.

Indexed as

Emigrants and ImmigrantsFood InsecurityAdultEmigration and ImmigrationFamily CharacteristicsFemaleFood SupplyHumansMaleMiddle AgedPrevalenceSurveys and QuestionnairesUnited StatesYoung AdultDisparitiesFood insecurityImmigrantsUnited States

Identifiers

PMID39208951
PMCPMC12056756

What OpenQuestion holds

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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.