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Access to quality healthcare still remains a major challenge in the efforts at reversing maternal morbidity andmortality. Despite the availability of establishedmaternal health interventions, the health of the expectantmother and the unborn child remains poor due to low utilisation of interventions. The study examined the socioeconomic determinants of antenatal care utilisation in peri-urban Ghana using pregnant women who are in their third trimester. Two-stage sampling technique was used to sample 200 pregnant women who were in their third trimester from the District Health Information Management System software. Well-structured questionnaire was the instrument used to collect data from respondents. Descriptive statistics and inferential statistics including binary logit regression model were used to analyse the data with the help of SPSS and STATA software. The results showed varying utilisation levels of ANC. From the regression result, age, household size, and occupational status were identified as the important socioeconomic determinants of antenatal care utilisation among the respondents. The important system factors which influence antenatal care utilisation by the respondents are distance to ANC, quality of service, and service satisfaction.The study concludes that socioeconomic and health system factors are important determinants of antenatal care utilisation. Stepping up of interventions aimed at improving the socioeconomic status and addressing health system and proximity challenges could be helpful in improving antenatal care utilisation by pregnant women in Ghana.
Two-stage sampling technique was adopted to sample the respondents for the study. At the first stage, purposive sampling technique was used to select four health facilities in peri-urban areas in Kumasi. The selection was based on the level of antenatal care attendance at the health facility. Using the District Health Information Management System software in the second stage, list of pregnant women in their third trimester was obtained from the antenatal units of the sampled health facilities and simple random sampling technique was used to select 200 pregnant women for the study. Structured questionnaires were used to collect data from the respondents. Data collected from respondents included demographic characteristics, health status, family planning services, social support systems, quality of service, choice of facility, level of utilisation, and views on caregivers. Data were coded and analysed using the SPSS and STATA (12), respectively. Since the study deals directly with respondents, ethical approval was sought from the Committee on Human Research, Publication and Ethics-KNUST, Kumasi, under the auspices of the Komfo Anokye Teaching Hospital, Kumasi. The pregnant women in the third trimester may either be seen as having utilised antenatal care or not depending on number of visits resulting in a binary dependent variable yi. The binary dependent variable yi takes on the values of zero (0) (if the number of visits to antenatal care is less than four) and one (1) (if the number of visits to antenatal care is greater than three as outlined by the WHO) [41]. The probability of observing a value of one is where F(·) is a cumulative distribution function; it is a continuous, strictly increasing function that takes a real value and returns a value which ranges from 0 to 1. Consequently, the probability of observing the zeros is Given the above specification, the maximum likelihood estimation approach can be used to estimate the model. The dependent variable yi is an unobserved latent variable that is linearly related to by the equation: where μi is a random disturbance term and xi is independent variable which influence the number of antenatal visits. The observed dependent variable is determined by whether yi exceeds three or otherwise: where yi∗ is the threshold value for yi. This study adopted the logit model to analyse the data, and the empirical model is specified as where variables, their description, and their expected sign are shown in Table 1.
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