Evidence map›Paper›PMID 31216558›Full record

Observational studyObesity facts2019

Extensive Phenotyping for Potential Weight-Inducing Factors in an Outpatient Population with Obesity.

Mesut Savas, Vincent L Wester, Jenny A Visser, Lotte Kleinendorst, Bert van der Zwaag, Mieke M van Haelst, Erica L T van den Akker, Elisabeth F C van Rossum

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Obesity facts, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Views of patients with obesity on person-centred care: A Q-methodology study.Health expectations : an international journal of public participation in health care and health policy · 2022
    Article
  6. Cannabis and cannabinoid research · 2022
    Review
  7. Article
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

8 authors.

Mesut SavasObesity Center CGG (Centrum Gezond Gewicht), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Vincent L WesterObesity Center CGG (Centrum Gezond Gewicht), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Jenny A VisserObesity Center CGG (Centrum Gezond Gewicht), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Lotte KleinendorstClinical Genetics, Amsterdam UMC (AMC), Amsterdam, The Netherlands.
Bert van der ZwaagGenetics, University Medical Center Utrecht, Utrecht, The Netherlands.
Mieke M van HaelstClinical Genetics, Amsterdam UMC (AMC), Amsterdam, The Netherlands.
Erica L T van den AkkerObesity Center CGG (Centrum Gezond Gewicht), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Elisabeth F C van RossumObesity Center CGG (Centrum Gezond Gewicht), Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands, e.vanrossum@erasmusmc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity has been associated with miscellaneous weight-inducing determinants. A comprehensive assessment of known obesity-related factors other than diet and physical activity within one cohort is currently lacking.

objectivesTo assess the prevalence of potential contributors to obesity and self-reported triggers for marked weight gain in an adult population with obesity and between obesity classes.

methodsIn this observational cohort study, we assessed 408 persons with obesity (aged 41.3 ± 14.2 years, BMI 40.5 ± 6.2) visiting our obesity clinic. They were evaluated for use of weight-inducing drugs, hormonal abnormalities, menarcheal age, (high) birth weight, sleep deprivation, and obstructive sleep apnea syndrome (OSAS). We additionally assessed self-reported triggers for marked weight gain and performed genetic testing in patients suspected of genetic obesity.

resultsNearly half of the patients were using a potentially weight-inducing drug, which was also the most reported trigger for marked weight gain. For the assessed hormonal conditions, a relatively high prevalence was found for hypothyroidism (14.1%), polycystic ovary syndrome (12.0%), and male hypogonadism (41.7%). A relatively low average menarcheal age (12.6 ± 1.8 years) was reported, whereas there was a high prevalence of a high birth weight (19.5%). Sleep deprivation and OSAS were reported in, respectively, 14.5 and 13.7% of the examined patients. Obesity class appeared to have no influence on the majority of the assessed factors. Of the genetically analyzed patients, a definitive genetic diagnosis was made in 3 patients (1.9%).

conclusionsA thorough evaluation of patients with obesity yields a relatively high prevalence of various potentially weight-inducing factors. Diagnostic screening of patients with obesity could therefore benefit these patients by potentially reducing the social stigma and improving the outcomes of obesity treatment programs by tackling, where possible, the weight-inducing factors in advance.

Indexed as

AdolescentAdultBody Mass IndexCausalityCohort StudiesDietDrug-Related Side Effects and Adverse ReactionsEndocrine System DiseasesExerciseFemaleHumansMaleMedical History TakingMiddle AgedObesityOutpatientsDrugsGeneticsObesitySecondary causes

Identifiers

PMID31216558
PMCPMC6758708

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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.