[Cluster sampling in health surveys]
Helmer de Jesús Zapata-Ossa1, Angela M Cubides-Munévar, María C López
1Facultad de Medicina, Fundación Universitaria San Martín, Cali, Colombia. zapatahelmer@gmail.com
Objective:
Describing how the cluster sampling statistical technique can be applied to health surveys.
Methods:
The article describes the most important aspects for each methodological step, emphasising cluster sampling's foundations. It was applied to a population of around 100,000 inhabitants from commune 18 in Cali. The sample covered 30 city blocks and 3,026 people were interviewed. The information was gathered using the Community-based Information System for Primary Health Attention.
Results:
The sampling technique produced precise and reliable information for estimating population health event prevalence in a cross-sectional study. Sampling error was 2.5 % in the general population, 10% in children aged less than 5 years, 5.7% in children aged 5 to 14, around 3.0% in those aged 10 to 59 and 7.2% in the population aged more than 60.
Conclusion:
The method guaranteed a 2.5% sampling error in estimating general population prevalence and less than 10% sampling errors for established population groups.
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