Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions of obesity trends

التفاصيل البيبلوغرافية
العنوان: Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions of obesity trends
المؤلفون: Alexander Huang, Samuel Y. Huang
بيانات النشر: Research Square Platform LLC, 2023.
سنة النشر: 2023
الوصف: Importance: The prevalence of obesity among United States adults has increased from 30.5% in 1999 to 41.9% in 2020. However, despite the recognition of long-term weight gain as an important public health issue, there is a paucity of studies studying the long-term weight gain and building models for long-term projection. Methods: A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES 2017–2020) was conducted in patients who completed the weight questionnaire and had accurate data for both weight at time of survey and weight ten years ago. Multistate gradient boost modeling classifiers were used to generate covariate dependent transition matrices and Markov chains were utilized for multistate modeling. Results: Of the 6,146 patients that met the inclusion criteria, 3,024 (49%) of patients were male and 3,122 (51%) of patients were female. There were 2,252 (37%) White patients, 1,257 (20%) Hispanic patients, 1,636 (37%) Black patients, and 739 (12%) Asian patients. The average BMI was 30.16 (SD = 7.15), the average weight was 83.67 kilos (SD = 22.04), and the average weight change was a 3.27 kg (SD = 14.97) increase in body weight (Fig. 1). A total of 2,411 (39%) patients lost weight, and 3,735 (61%) patients gained weight (Table 1). We observed that 87 (1%) of patients were underweight (BMI 30). From analysis of the transitions between normal/underweight, overweight, and obese, we observed that after 10 years, of the patients who were underweight, 65% stayed underweight, 32% became normal weight, 2% became overweight, and 2% became obese. After 10 years, of the patients who were normal weight, 3% became underweight, 78% stayed normal weight, 17% became overweight, and 2% became obese. Of the patients who were overweight, 71% stayed overweight, 0% became underweight, 14% became normal weight, and 15% became obese. Of the patients who were obese, 84% stayed obese, 0% became underweight, 1% became normal weight, and 14% became overweight. Conclusions: United States adults are at risk of transitioning from normal weight to becoming overweight or obese. Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::7a36892e693d7c9e90f8d45d0c3217ae
https://doi.org/10.21203/rs.3.rs-2316692/v1
حقوق: OPEN
رقم الأكسشن: edsair.doi...........7a36892e693d7c9e90f8d45d0c3217ae
قاعدة البيانات: OpenAIRE