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Multinomial logistic regression model for assessing factors associated with body mass index of government employee of Gulariya Municipality, Nepal

Ramesh Prasad TharuRavi Singh Mahatra

Abstract

Obesity has become very common and an increasing health burden worldwide in recent years. Nepal's increasing trend towards urbanization presents large health challenges and government employees are more vulnerable group which are facing obesity problems since they have to work long working hours by sitting. This study attempts to examine the prevalence of overweight and obesity; and factors associated with body mass index (BMI) in government employees of Gulariya municipality of Bardiya District, Nepal. A cross sectional study design was used and 248 respondents were selected using simple random sampling. Multinomial logistic regression model was adopted to assess the factors associated with BMI of government employees. Among the total 248 employees, prevalence of obesity, overweight and underweight were 12.9%, 27% and 10.1%. Among the factors, marital status (OR: 6.249, 95% CI: 1.432 to 27.273), diet habit (OR: 0.283, 95% CI: 0.085 to 0.949), alcohol consumption: no consuming (OR: 0.183, 95% CI: 0.037 to 0.913) and occasionally consuming (OR: 0.193, 95% CI: 0.040 to 0.943) have significant association with underweight. Similarly, designation gaggated (OR:2.559, 95% CI: 1.997 to 6.565), exercise (OR:2.336, 95% CI: 1.173to 3.422), diet habit (OR:2.425, 95% CI: 1.165 to 5.048) have significant association with overweight and designation gaggated (OR:16.513, 95% CI: 3.448 to 79.075), exercise (OR:0.078, 95% CI: 0.026 to 0.232), alcohol consumption : no consuming (OR:0.200, 95% CI:0.051 to 0.789) and occasionally consuming (OR: 0.206, 95% CI: 0.050to 0.848) have significant association with obese category.

Advanced Statistical Methods and ModelsForecasting Techniques and ApplicationsFuzzy Systems and OptimizationUnderweightOverweightBody mass indexMultinomial logistic regressionObesityMedicineEnvironmental healthLogistic regressionDemographyCross-sectional study
Citations
1
FWCI
0.24
field-weighted impact
References
13
Percentile
56%
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