Evidence map›Paper›PMID 36397061›Full record

ArticleBMC public health2022

Quantifying differences in packaged food and drink purchases among households with diet-related cardiometabolic multi-morbidity: a cross-sectional analysis.

Iben M Ricket, Jeremiah R Brown, Todd A MacKenzie, Yu Ma, Dhruv Grewal, Kusum L Ailawadi, Jennifer A Emond

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 78% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 2 countries.

Iben M RicketDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. iben.sullivan@dartmouth.edu.
Jeremiah R BrownDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Todd A MacKenzieDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Yu MaDesautels Faculty of Management, McGill University, Montreal, Quebec, Canada.
Dhruv GrewalMarketing Division, Babson College, Babson Park, MA, USA.
Kusum L AilawadiTuck School of Business at Dartmouth, Hanover, NH, USA.
Jennifer A EmondDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Dartmouth College · USBabson College · USMcGill University · CA

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Information Extraction from EMRs to Predict Readmission following Acute Myocardial InfarctionR01HL130828 · NHLBI · DARTMOUTH COLLEGE · PI BROWN, JEREMIAH R, MATHENY, MICHAEL E. · 2016 to 2019
$3.1M
Quantitative Biomedical Sciences at DartmouthT32LM012204 · NLM · DARTMOUTH COLLEGE · PI TOSTESON, TOR D · 2016 to 2020
$876k
NCI NIH HHS P30 CA023108NHLBI NIH HHS R01 HL130828
6 · The paper itself

Abstract

backgroundDiet is important for chronic disease management, with limited research understanding dietary choices among those with multi-morbidity, the state of having 2 or more chronic conditions. The objective of this study was to identify associations between packaged food and drink purchases and diet-related cardiometabolic multi-morbidity (DRCMM).

methodsCross-sectional associations between packaged food and drink purchases and household DRCMM were investigated using a national sample of U.S. households participating in a research marketing study. DRCMM households were defined as household head(s) self-reporting 2 or more diet-related chronic conditions. Separate multivariable logistic regression models were used to model the associations between household DRCMM status and total servings of, and total calories and nutrients from, packaged food and drinks purchased per month, as well as the nutrient density (protein, carbohydrates, and fat per serving) of packaged food and drinks purchased per month, adjusted for household size.

resultsAmong eligible households, 3795 (16.8%) had DRCMM. On average, households with DRCMM versus without purchased 14.8 more servings per capita, per month, from packaged foods and drinks (p < 0.001). DRCMM households were 1.01 times more likely to purchase fat and carbohydrates in lieu of protein across all packaged food and drinks (p = 0.002, p = 0.000, respectively). DRCMM households averaged fewer grams per serving of protein, carbohydrates, and fat per month across all food and drink purchases (all p < 0.001). When carbonated soft drinks and juices were excluded, the same associations for grams of protein and carbohydrates per serving per month were seen (both p < 0.001) but the association for grams of fat per serving per month attenuated.

conclusionsDRCMM households purchased greater quantities of packaged food and drinks per capita than non-DRCMM households, which contributed to more fat, carbohydrates, and sodium in the home. However, food and drinks in DRCMM homes on average were lower in nutrient-density. Future studies are needed to understand the motivations for packaged food and drink choices among households with DRCMM to inform interventions targeting the home food environment.

Indexed as

Cardiovascular DiseasesMultimorbidityBeveragesCarbohydratesCross-Sectional StudiesDietFamily CharacteristicsFood PackagingHumansNutritive ValueCarbohydratesDiet and multi-morbidityDiet-related cardiometabolic multi-morbidityEnergy and nutrient-densityPackaged food, and drinks

Identifiers

PMID36397061
PMCPMC9670385
OpenAlexW4309507071

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Registered trials

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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.