title: A categorical data analysis of contacts with the Family Health Clinic, Calabar, Nigeria.
abstract: The relationships of population, environmental and accessibility variables to registration and attendance by mothers of children under 6 at the Family Health Clinic in Calabar, Nigeria are investigated. The technique used to analyze the data collected is categorical data analysis which proceeds in two stages, variable selection to reduce the variable set and fitting a log-linear model to the reduced set. Details of the statistical procedures used are provided to indicate how categorical data analysis can be used as a valuable tool of analysis in medical geographical studies that employ count or frequency data. It was found that younger mothers and Ibibio women registered more often at the clinic than did their counterparts. However, if the relatively sparse data on fathers is accepted, the association between age and registration is found to be spurious and a model can be substituted which shows younger fathers and fathers who spoke a non-Efik/Ibibio language to be associated with higher clinic registration of mothers. It was further found that for registered mothers the probability of a clinic visit was decreased by mother's age, increased by distance given no travel cost, unaffected by distance given some travel cost, increased by travel cost given a short distance to the clinic and decreased by travel cost given a longer distance from the clinic. These results are discussed in relation to population characteristics such as socio-economic status, clinic procedures such as health worker activities, transportation availability in Calabar, the spatial ecology of the city and local environmental conditions.
mesh_terms: D000328:Adult; D000367:Age Factors; D003153:Community Health Services / Q000706:statistics & numerical data*; D005006:Ethnicity; D005190:Family; D005192:Family Health; D005260:Female; D006801:Humans; D008297:Male; D009549:Nigeria; D010290:Parents; D010343:Patient Admission; D012959:Socioeconomic Factors