Obesity in the Pediatric Population of the National (Nationwide) Inpatient Sample (NIS), USA
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Notice bibliographique
Résumé
BACKGROUND: The incidence of childhood obesity has received a lot of attention lately, especially in the United States. The increased prevalence of pediatric obesity and its association with comorbidities has piqued the attention of more scientists in the epidemic's patterns. Our research examined the National (Nationwide) Inpatient Sample (NIS) data set for hospitalized persons aged 18 years or younger with primary or secondary obesity between 2016 and 2019 to investigate the prevalence, risk factors, and related diseases. METHODS: We retrospectively examined individuals with primary or secondary obesity from 2016 to 2019 using the NIS database. To extract the weighted samples, we utilized the International Classification of Diseases (ICD)-10 diagnostic codes E66, E660, E6601, E6609, E662, E668, and E669. Individuals with drug-related obesity or obesity caused by a recognized pathologic disease unrelated to high-calorie intake were excluded. First, we queried the total population, then separated them by age category and picked our population of interest, i.e., those aged 18 and under. The NIS is a deidentified database available to the public. It collects data on around 8 million hospitalizations annually, accounting for roughly 20% of all admissions in the United States. Results: The findings show that between 2016 and 2019, prevalence rates of childhood obesity were still on the rise and plateaued in 2019. There were 28,484,087 study subjects in this weighted sample between 2016 and 2019. Of these, 13.9% (3,946,889) were diagnosed with obesity. The sample population for those 18 years of age or under was 62,669 (1.5%) children with obesity with a mean age of 14 (SD = 4). Also, there was a 64.2% female preponderance. The obtained yearly showed a steady and significant rise from 2016 to 2018 (24% vs. 26%), with a slight decline in 2019 (25%; p < 0.001). Even though the white population had the highest overall prevalence of childhood obesity (40.9%), the Hispanic and black people had a higher prevalence per population, with a 0.5% and 0.33% prevalence, respectively, compared to 0.14% in the white population (p < 0.0001). When geographical regions were considered, south had the highest rate (36.40%), followed by the west (24.71%) and the midwest (23.56%). The analysis also showed that people with lower median household income (0-25th percentile) had the highest rate of childhood obesity (38.17%) compared to higher-income earners (13.19%). CONCLUSION: In our finding, obesity in the pediatric population is still increasing, continuing on its previously recorded trajectory. Various recommendations from health policymakers have bolstered efforts to tackle this escalating pandemic. However, additional information on the compliance, use, and adherence to these policies by healthcare professionals and members of the public, as well as the consequence of utilization or compliance to these guidelines, is needed. Nevertheless, given the continuous growth of childhood obesity, despite the avalanche of these recommendations, the issue of compliance arises, or other essential risk factors might have been overlooked. Additional studies may be needed to unmask this looming phenomenon.
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Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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