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Predictive modeling of obesity prevalence for the U.S. population

Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
LDR  00000cab a2200000 4500
001  MAP20190014601
003  MAP
005  20190524085525.0
008  190521e20190301esp|||p |0|||b|spa d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎6
1001 ‎$0‎MAPA20190006378‎$a‎Daawin, Palma
24510‎$a‎Predictive modeling of obesity prevalence for the U.S. population‎$c‎Palma Daawin, Seonjin Kim, Tatjana Miljkovic
520  ‎$a‎Modeling obesity prevalence is an important part of the evaluation of mortality risk. A large volume of literature exists in the area of modeling mortality rates, but very few models have been developed for modeling obesity prevalence. In this study we propose a new stochastic approach for modeling obesity prevalence that accounts for both period and cohort effects as well as the curvilinear effects of age. Our model has good predictive power as we utilize multivariate ARIMA models for forecasting future obesity rates. The proposed methodology is illustrated on the U.S. population, aged 2390, during the period 19882012. Forecasts are validated on actual data for the period 20132015 and it is suggested that the proposed model performs better than existing models.
650 4‎$0‎MAPA20080592059‎$a‎Modelos predictivos
650 4‎$0‎MAPA20080548421‎$a‎Obesidad
650 4‎$0‎MAPA20080555306‎$a‎Mortalidad
651 1‎$0‎MAPA20080638337‎$a‎Estados Unidos
7001 ‎$0‎MAPA20190006385‎$a‎Kim, Seonjin
7001 ‎$0‎MAPA20190006392‎$a‎Miljkovic, Tatjana
7730 ‎$w‎MAP20077000239‎$t‎North American actuarial journal‎$d‎Schaumburg : Society of Actuaries, 1997-‎$x‎1092-0277‎$g‎01/03/2019 Tomo 23 Número 1 - 2019 , p. 64-81