[Data analysis from surveys using complex sampling methods].

To present statistical methods on appropriate data analysis from complex surveys and errors arising from ignorance of weights or design of samples. We took Chinese National Nutrition and Health Survey in 2002 as an example to analyze the prevalence of hypertension among population aged 15 and over. We used four combinations of analyses, including with or without weighting or considering sample designs. If weights is omitted, it would result in biased prevalence estimates and also influence the estimates of standard errors. While omitting sample designs would result in underestimating the standard error estimates and then testing the false positive hypothesis. Through appropriate analysis, we found Chinese people in large-sized cities had the highest prevalence of hypertension (28.77%, 95%CI: 25.69% - 31.84%) while people in the poorest rural area having the lowest prevalence of hypertension (14.21%, 95%CI: 12.64% - 15.79%). The prevalence of hypertension among people in small and medium-sized cities and other rural areas ranged from 20.48% to 24.37% with statistically insignificant difference. It is necessary to use appropriate methods to analyze data from complex surveys.