Evidence map›Paper›PMID 32792332›Full record

ArticleJournal of medical Internet research2020

Weight Reduction Through a Digital Nutrition and Food Purchasing Platform Among Users With Obesity: Longitudinal Study.

Emily A Hu, Viet Nguyen, Jason Langheier, Dexter Shurney

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 37 citations in OpenAlex.

  1. Trial
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  4. [Application of Digital Nutrition Technologies in Adult Weight Management].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
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  11. Online Pilot Grocery Intervention among Rural and Urban Residents Aimed to Improve Purchasing Habits.International journal of environmental research and public health · 2022
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  14. Sex and age differences in attitudes and intention to adopt personalised nutrition in a UK sample.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2021
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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 1 institution in 1 country.

Emily A HuZipongo, Inc, DBA Foodsmart, San Francisco, CA, United States.ORCID 0000-0002-2299-4072
Viet NguyenZipongo, Inc, DBA Foodsmart, San Francisco, CA, United States.ORCID 0000-0002-4741-1048
Jason LangheierZipongo, Inc, DBA Foodsmart, San Francisco, CA, United States.ORCID 0000-0001-9566-881X
Dexter ShurneyZipongo, Inc, DBA Foodsmart, San Francisco, CA, United States.ORCID 0000-0001-6880-0467
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital nutrition apps that monitor or provide recommendations on diet have been found to be effective in behavior change and weight reduction among individuals with obesity. However, there is less evidence on how integration of personalized nutrition recommendations and changing the food purchasing environment through online meal planning and grocery delivery, meal kits, and grocery incentives impacts weight loss among individuals with obesity.

objectiveThe objective of this observational longitudinal study was to examine weight loss and predictors of weight loss among individuals with obesity who are users of a digital nutrition platform that integrates tools to provide nutrition recommendations and changes in the food purchasing environment grounded in behavioral theory.

methodsWe included 8977 adults with obesity who used the digital Foodsmart platform, created by Zipongo, Inc, DBA Foodsmart between January 2013 and April 2020. We retrospectively analyzed user characteristics and their associations with weight loss. Participants reported age, gender, height, at least 2 measures of weight, and usual dietary intake. Healthy Diet Score, a score to measure overall diet quality, was calculated based on responses to a food frequency questionnaire. We used paired t tests to compare differences in baseline and final weights and baseline and final Healthy Diet Scores. We used univariate and multivariate logistic regression models to estimate odds ratios and 95% CI of achieving 5% weight loss by gender, age, baseline BMI, Healthy Diet Score, change in Healthy Diet Score, and duration of enrollment. We conducted stratified analyses to examine mean percent weight change by enrollment duration and gender, age, baseline BMI, and change in Healthy Diet Score.

resultsOver a median (IQR) of 9.9 (0.03-54.7) months of enrollment, 59% of participants lost weight. Of the participants who used the Foodsmart platform for at least 24 months, 33.3% achieved 5% weight loss. In the fully adjusted logistic regression model, we found that baseline BMI (OR 1.02, 95% CI 1.02-1.03; P<.001), baseline Healthy Diet Score (OR 1.06, 95% CI 1.05-1.08; P<.001), greater change in Healthy Diet Score (OR 1.12, 95% CI 1.11-1.14; P<.001), and enrollment length (OR 1.28, 95% CI 1.23-1.32; P<.001) were all significantly associated with higher odds of achieving at least 5% weight loss.

conclusionsThis study found that a digital app that provides personalized nutrition recommendations and change in one's food purchasing environment appears to be successful in meaningfully reducing weight among individuals with obesity.

Indexed as

AdolescentAdultAgedAged, 80 and overDiet, HealthyFemaleHumansLongitudinal StudiesMaleMiddle AgedNutritional StatusObesityRetrospective StudiesWeight LossYoung Adultappbehavioral economicsbehavior changedigitaleating behaviorfood environmentfood orderingfood purchasingmeal planningmHealthnutritionobeseweight loss

Identifiers

PMID32792332
PMCPMC7495263
OpenAlexW3049701742

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.