Hierarchical linear models on abdominal circumference research data using generalized least square

Hierarchical Linear Models (HLM) is one of multilevel statistical analysis which is the development of a linear regression analysis on individual data, where data structured hierarchical (tiered). The dependent variable was measured at level-1 or at the lowest level only, whereas the independent variables measured at level-1 and level higher. In this study will use data from Riskesdas and Susenas on 2013 in the province of East Java. With the unit analysis in level 1 is 54.101 individuals and the unit analysis in level-2 is 38 regencies/cities in East Java. The data related to the obesity which is a condition of abnormal or excess accumulation of fat in adipose tissue. Physical activity affects the central obesity, especially abdominal circumference. Consumption of fruit and vegetables are also thought to affect the abdominal circumference. To improve the health status of the community, needs to be studied in-depth the factors that affect the abdominal circumference. This study is using Hierarchical Linear Models analysis for estimating the factors that affect obesity by estimation approach Generalized Least Square (GLS). The results obtained by applying the GLS approach for modeling linear hierarchical to determine the factors that affect the abdominal circumference is for level-1 (individual), the results obtained were each respective district/city has a significant variable that is different. As for the level-2, variable that affects age showed that the abdominal circumference, where the age variable influenced by spending purchase vegetables and fruits.