Intraclass correlation and design effect in BMI, physical activity and diet: a cross-sectional study of 56 countries

被引:19
|
作者
Masood, Mohd [1 ,2 ]
Reidpath, Daniel D. [1 ]
机构
[1] Monash Univ, Jeffrey Cheah Sch Med & Hlth Sci, Dept Global Publ Hlth, Bandar Sunway, Australia
[2] Univ Teknol MARA, Ctr Studies Populat Oral Hlth & Clin Prevent, Fac Dent, Shah Alam, Malaysia
来源
BMJ OPEN | 2016年 / 6卷 / 01期
关键词
HEALTH SURVEYS; MULTICOUNTRY; INTERVENTION; VARIABILITY; INEQUALITY; NUTRITION; CONTEXT; PROGRAM; CLUSTER; ADULTS;
D O I
10.1136/bmjopen-2015-008173
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives: Measuring the intraclass correlation coefficient (ICC) and design effect (DE) may help to modify the public health interventions for body mass index (BMI), physical activity and diet according to geographic targeting of interventions in different countries. The purpose of this study was to quantify the level of clustering and DE in BMI, physical activity and diet in 56 low-income, middle-income and high-income countries. Design: Cross-sectional study design. Setting: Multicountry national survey data. Methods: The World Health Survey (WHS), 2003, data were used to examine clustering in BMI, physical activity in metabolic equivalent of task (MET) and diet in fruits and vegetables intake (FVI) from low-income, middle-income and high-income countries. Multistage sampling in the WHS used geographical clusters as primary sampling units (PSU). These PSUs were used as a clustering or grouping variable in this analysis. Multilevel intercept only regression models were used to calculate the ICC and DE for each country. Results: The median ICC (0.039) and median DE (1.82) for BMI were low; however, FVI had a higher median ICC (0.189) and median DE (4.16). For MET, the median ICC was 0.141 and median DE was 4.59. In some countries, however, the ICC and DE for BMI were large. For instance, South Africa had the highest ICC (0.39) and DE (11.9) for BMI, whereas Uruguay had the highest ICC (0.434) for MET and Ethiopia had the highest ICC (0.471) for FVI. Conclusions: This study shows that across a wide range of countries, there was low area level clustering for BMI, whereas MET and FVI showed high area level clustering. These results suggested that the country level clustering effect should be considered in developing preventive approaches for BMI, as well as improving physical activity and healthy diets for each country.
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页数:9
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