An age structured model for obesity prevalence dynamics in populations
Rev. MVZ Córdoba
;
15(2): 2051-2059, mayo-ago. 2010.
Artículo
en Inglés
| LILACS
| ID: lil-621938
ABSTRACT
Objective. Modeling the correlation of the development of obesity in a population with age and time and predict the dynamics of the correlation of the development of obesity in a population with age and time under different scenarios in Valencia (Spain). Materials and methods. An age structured mathematical model is used to describe the future dynamics of obesity prevalence for different ages in human population with excess weight. Simulation of the model with parameters estimated using the Health Survey of the Region of Valencia 2000 (4.319 interviews) and Health Survey of the Region of Valencia 2005 (4.012 interviews). The model considers only overweight and obese populations since these subpopulations are the most relevant on obesity health concern. Results. The model allows predicting and studying the prevalence of obesity for each age. Results showed an increasing trend of obesity in the following years in well accordance with the trend observed in several countries. Conclusions. Based on the numerical simulations it is possible to conclude that the age structured mathematical model is suitable to forecast the obesity epidemic in each age group in different countries. Additionally, this type of models may be applied to study other characteristics of other populations such animal populations.
Texto completo:
Disponible
Índice:
LILACS (Américas)
Asunto principal:
Población
/
Modelos Teóricos
/
Obesidad
Tipo de estudio:
Estudio de prevalencia
/
Estudio pronóstico
/
Investigación cualitativa
/
Factores de riesgo
Límite:
Humanos
Idioma:
Inglés
Revista:
Rev. MVZ Córdoba
Asunto de la revista:
Medicina Veterinaria
Año:
2010
Tipo del documento:
Artículo
País de afiliación:
Colombia
/
España
Institución/País de afiliación:
Universidad Politécnica de Valencia/ES
/
Universidad de Córdoba/CO
/
Universidad de Los Andes/VE
Similares
MEDLINE
...
LILACS
LIS