Observable, but Not Unobservable Health Numbers are Associated With Self-Reported Health: NHANES 2017-2020.

Michael DeDonno, Bella-Christina Objio, Alexis Crowder

Abstract read

In one paragraph

Article in American journal of lifestyle medicine, 2024. 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

3 authors.

Michael DeDonnoCollege of Education, Florida Atlantic University, Boca Raton, FL, USA (MD).ORCID https://orcid.org/0000-0001-6596-6904

Bella-Christina ObjioCharles E Schmidt, College of Medicine, Florida Atlantic University, Boca Raton, FL, USA (BO).

Alexis CrowderCharles E. Schmidt, College of Science, Florida Atlantic University, Boca Raton, FL, USA (AC).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePresent study explored the influence of self-reported health on diff between observable and unobservable health factors.

methodData obtained through the 2017-2020 pre-pandemic dataset of the National Health and Nutrition Examination Survey (NHANES). A series of analyses of covariance were conducted with self-reported health as the independent variable, and measures of blood pressure, waist-to-hip ratio, fasting glucose and total cholesterol as dependent variables. Family income served as a covariate.

resultsResults revealed significant differences in self-reported health and blood pressure, waist-to-hip ratio, and fasting glucose. Individuals who rated their health excellent or very good tended to have better health numbers than those who rated their health as fair or poor. No statistically significant difference was found with self-reported health and cholesterol.

conclusionIt is possible that health numbers that can be observed (or assessed) at home, without a health care professional, may be more aligned with how individuals perceive their own health. Health care professionals may want to further help patients recognize their own health status. The use of wearable technologies may provide added health information resulting in more accurate perception of health. A more accurate perception of a patient's own health may aid health care professionals in further improving patient care.

Indexed as

blood pressurecholesterolfasting glucoseperceived healthself-reported healththe four health numberswaist-to-hip ratio (WHR)

Identifiers

PMID39540167

DOI10.1177/15598276241291451

PMCPMC11556545

What OpenQuestion holds

Textmetadata

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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.