Calculation of smoking rates by dong/eup/myeon unit using small-area estimation in the Community Health Survey

Abstract

The Korean Community Health Survey (CHS), a community-based nationwide annual survey with the objective of providing important health indicators, is conducted through stratified cluster sampling and computer-assisted personal interviewing. Using the dong/eup/myeon administrative units (hereafter units) and residential structures (apartment or single house) as stratification variables, 900 adults (age≥19 years) per community health center district (hereafter district) are sampled and proportionally distributed across the units and according to residential structures, followed by selecting tong/ban/ri-level sample points via probability proportionate sampling based on the number of households. From each selected sample point, five households on average are selected by systematic sampling, and individual interviews are conducted with all adults in each household [1]. Although district-level health indicators are produced with a specific level of precision, there is an increasing demand for producing unit-level health indicators. However, the unit sample size varies considerably ranging between tens and several hundreds, and health indicators such as smoking rate for units with fewer than 30 samples produced using conventional statistical estimation methods cannot be used, owing to an exceedingly large sample variance of the estimates. This problem can be addressed by calculating unit-level statistics using a special estimation method such as small-area estimation [2]. This paper presents an optimized estimation method using Statistical Analysis System (SAS) codes. Small-area estimation Small-area estimation is an estimation method designed to produce statistics for small survey areas not included in the sample design for statistics and having unusable high-variance estimates owing to excessively small sample sizes, through supplementary use of surrounding area survey information, auxiliary information from other sources, or statistical model of the population [3,4]. Given that the sample design for the Community Health Service is intended to produce district-level health indicators, small-area estimation is needed for producing reliable unit-level health indicators. The following describes the small-area estimation methods for producing unit-level health indicators [5]. Direct estimator A direct estimator uses only data obtained from the units concerned to produce unit-level health indicators. Each observation included in the survey data sets is given a weight item by item; the sample design-based direct estimator and its variance can be expressed by the following estimation equation, using weighted and observed values: Y¯⏜Di=∑j=1niwjiyji∑j=1niwji (1) where ni is the sample size of unit i, Wji is the multiplier reflecting sample and response rates, and yji is the observed value. The variance of the estimator shown in Equation (1) can be obtained using Equation (2), as follows: Var⏜Y¯⏜Di=1nini-1w¯i2∑j=1niwji2yji-Rt⏜2 (2) Where Rt⏜=∑j=1niwjiyji∑j=1niwji and wi=1ni∑j=1niwji