Evidence map›Paper›PMID 38674914›Full record

ArticleNutrients2024

Weight Loss Trajectories and Short-Term Prediction in an Online Weight Management Program.

Bingjie Zhou, Susan B Roberts, Sai Krupa Das, Elena N Naumova

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Weight Loss Responses to Pharmacotherapy in Breast Cancer Survivors: Results from the Adaptive Nutrition and Exercise Weight Loss (A-NEW) Study.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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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 2 institutions in 1 country.

Bingjie ZhouFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA.ORCID 0000-0002-9776-0414
Susan B RobertsGeisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA.
Sai Krupa DasJean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA.
Elena N NaumovaFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA.ORCID 0000-0002-9562-4734
Tufts University · USDartmouth College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The extent to which early weight loss in behavioral weight control interventions predicts long-term success remains unclear. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. We utilized data from 667 de-identified individuals who participated in a commercial weight loss program (Instinct Health Science), comprising 69,363 weight records. Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. Next, we applied multinomial logistic models to evaluate if early weight loss in the first 14 days and prolonged duration of participation were significantly associated with long-term weight loss patterns. The mean percentage of weight loss was 7.9 ± 5.1% over 133 ± 69 days. Our analysis revealed four main weight loss trajectory patterns: a steady decrease over time (30.6%), a decrease to a plateau with subsequent decline (15.8%), a decrease to a plateau with subsequent increase (46.9%), and no substantial decrease (6.7%). Early weight change rate and total participating duration emerged as significant factors in differentiating long-term weight loss patterns. These findings contribute to support the provision of tailored advice in the early phase of behavioral interventions for weight loss.

Indexed as

Weight LossWeight Reduction ProgramsAdultAlgorithmsBehavior TherapyBody-Weight TrajectoryFemaleHumansMaleMiddle AgedObesityTime Factorsearly predictionlongitudinal datasequential modelingweight lossweight trajectory

Identifiers

PMID38674914
PMCPMC11055013
OpenAlexW4395009962

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.