Health survey: comparison of interviewees according to ownership of a residential telephone line - Segri, Neuber José (2010)
OBJECTIVE: To analyze differences in sociodemographic characteristics associated with health in individuals with and without a residential telephone line. METHODS: Data from the ISA-Capital 2003 (2003 Health Survey), a study performed in the city of São Paulo, Southeastern Brazil, were analyzed. Residents who had a residential telephone line were compared to those who reported not having a telephone line, according to sociodemographic, lifestyle, health status and health service use variables. Bias associated with non-coverage of the population without a telephone line was estimated, decreasing after the use of post-stratification adjustments. RESULTS: Of all the 1,878 interviewees aged more than 18 years, 80.1% had a residential telephone line. By comparing groups, the main sociodemographic differences among individuals who did not have a residential telephone line were the following: younger age, greater proportion of black and mixed individuals, smaller proportion of married interviewees, and greater proportion of unemployed individuals with a lower level of education. Residents without a residential telephone line had fewer health tests performed and smoked and drank more. In addition, this group took less medication, considered themselves to be in worse health conditions and used the SUS (National Health System) more frequently. When excluding the population without a telephone line from the analysis, estimates of dental consultations, alcoholism, drug use and SUS use to have a Papanicolaou test performed were those showing the highest bias. After post-stratification adjustment, there was a decrease in the bias of estimates for the variables associated with ownership of a residential telephone line. CONCLUSIONS: The exclusion of residents without a telephone line was one of the main limitations to the studies performed in this way. However, the use of statistical techniques of post-stratification adjustment enables a reduction in non-coverage bias.