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Enregistrement W3021468891

Comparing Measures of Obesity in Relation to Health Care Use in Adults from the Canadian Longitudinal Study on Aging

2020· dissertation· en· W3021468891 sur OpenAlexaboutno aff
Alessandra T. Andreacchi

Notice bibliographique

RevueMacSphere (McMaster University) · 2020
Typedissertation
Langueen
DomaineMedicine
ThématiqueNutritional Studies and Diet
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGerontologyObesityLongitudinal studyRelation (database)MedicineEnvironmental healthPsychologyComputer scienceInternal medicineData mining
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Obesity has been associated with increased health care use, but it is unclear whether this is consistent across all measures of obesity. The objectives of this thesis were to compare obesity defined by four anthropometric measures, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and percent body fat (%BF), and to estimate their associations with health care use among Canadian adults. Methods: A secondary data analysis was conducted from 30,097 individuals aged 45-85 years from the Canadian Longitudinal Study on Aging. Anthropometric measures were collected by trained research assistants and %BF, the reference standard, was measured using dual-energy x-ray absorptiometry. Obesity was defined as BMI≥30.0 kg/m2, WC≥88cm for females and ≥102cm for males, WHR≥0.85 for females and ≥0.90 for males, and %BF>35% for females and >25% for males. Approximately 18 months after baseline data collection, self-reported health care use in the past 12 months was collected, including any contact with a general practitioner, medical specialist, emergency department, and being a patient in a hospital overnight. Pearson correlation coefficients and sensitivity and specificity analyses were conducted to compare anthropometric measures to %BF. Relative risks and risk differences were calculated for measures of health care use, adjusted for sex, age, education, income, urban/rural, marital status, smoking status, and alcohol use. Secondary analyses were also stratified by sex and age. Results: The prevalence of obesity defined by BMI was 29%, by WC was 42%, by WHR was 62%, and by %BF was 73%. BMI and WC were highly correlated with %BF (r=0.75 and r=0.70, respectively) and WHR was weakly correlated with %BF (r=0.29). BMI and WC cut points demonstrated high specificity (>93%) and lower sensitivity (<58%) in predicting obesity defined by %BF. WHR cut points demonstrated high sensitivity (95%) and lower specificity (28%) in males, but lower sensitivity (44%) and high specificity (83%) in females in predicting %BF- defined obesity. There was an increased relative and absolute risk of health care use for all measures of obesity and all health care services. For example, WC-defined obesity was associated with increased relative risk (RR) of hospital overnight stay (RR: 1.40, 95% CI: 1.28- 1.54) and the risk difference (per 100) was 2.6 (95% CI:1.9-3.3). The risk of health care use was similar amongst females and males with obesity although relative risks and risk differences attenuated in the oldest adult group aged 75 and older compared to the youngest group aged 45- 54. Conclusion: The prevalence of obesity among Canadian adults varied substantially by anthropometric measure. BMI and WC have stronger correlations and concordance with %BF than does WHR, however all measures were positively associated with increased health care use. Further research should be conducted on obesity cut points to discern the best measure to predict health care use.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,360
Score d'incertitude au seuil0,691

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,069
Tête enseignante GPT0,270
Écart entre enseignants0,201 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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