Evidence map›Paper›PMID 41146834›Full record

ArticleCureus2025

Independent and Mediated Associations of Adverse Childhood Experiences With Overweight and Obesity in Adults From the United States: Insights From the 2023 Behavioral Risk Factor Surveillance System (BRFSS) Data.

Umer Maqsood, Shichen Zheng

Abstract read
In one paragraph

Article in Cureus, 2025. 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
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.

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

2 authors.

Umer MaqsoodResearch and Evaluation, California Rural Indian Health Board Inc., Roseville, USA.
Shichen ZhengResearch and Evaluation, California Rural Indian Health Board Inc., Roseville, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adult overweight and obesity remain an urgent public health concern in the United States. While adverse childhood experiences (ACEs) are recognized as risk factors, it remains unclear whether their influence persists independently of adult socioeconomic and behavioral conditions. To our knowledge, this study is among the first to analyze the 2023 Behavioral Risk Factor Surveillance System (BRFSS) data with multilevel modeling to isolate ACE effects from adult risk factors. Using data from the 2023 BRFSS (n=269,521), this study employed multilevel logistic regression to examine the relationship between ACEs and adult overweight/obesity (BMI≥25), adjusting for demographic, socioeconomic, health access, behavioral, and chronic disease variables. ACEs were categorized as 0, 1-2, or ≥3. Out of the total 269,521 respondents, 67.5% (n=182,008) were classified as overweight or obese. Participants with three or more ACEs (n=9,677) had a higher crude prevalence of overweight/obesity (69.7%) compared to those with no ACEs (n=12,786, 67.0%; p=0.02). However, in fully adjusted models, ACEs were not significantly associated with overweight/obesity (OR for ≥3 ACEs=1.08; 95% CI: 0.92-1.27). Independent predictors included race/ethnicity, income, education, physical inactivity, diabetes, and healthcare access. These findings suggest that ACEs may influence obesity indirectly, primarily through their impact on adult socioeconomic and behavioral factors. Interventions that address adult-level risk factors, particularly in populations with high ACE exposure, combined with trauma-informed care, may be more effective in reducing obesity prevalence.

Indexed as

adverse childhood experiences (aces)behavioral risk factorschronic disease riskobesitysocioeconomic factors

Identifiers

PMID41146834
PMCPMC12554332

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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.