The research aimed at investigating factors associated with modern contraceptive use in Zambia. Data from the 2007 Zambia Demographic Health Survey (ZDHS) was utilized in order to investigate the above topic. Only data on women aged 15-49 was used in this study. Statistical tests, specifically bivariate correlations analysis and binary logistic regression analysis were performed in order to analyse the relationships between/among variables (residence, age, education, employment, wealth quintile, fertility preference and marital status), using Stata software. Contingency tables and graphs were used to facilitate presentation of findings.
The findings show that knowledge levels of contraceptive are very high (97 percent) among women. The modern contraceptive prevalence is however, about 30percent. The modelling of the variables was based on the constructed conceptual framework that basic variables (age, residence) work through intermediate variables (education, employment, wealth quintile) which work through immediate variables (marital status, knowledge of contraceptives). Analysis of the variables shows that only six variables can be used to explain variations in modern contraceptive use. These are age, education, employment, wealth quintile, fertility preference and marital status. The multivariate regression results indicate that residence is not statistically significant to the model. Among the significant explanatory variables, much variation is observed in marital status as those currently married are 4 times more likely to use contraceptives with reference to the never married. The formerly married are almost twice more likely to use contraceptives with reference to the never married. This shows that there is high contraceptive use among the currently married as they are at risk of child bearing. With regard to age, age groups 30-34 and 35-39 are almost twice more likely to use contraceptives with reference to those aged 15-19.
Fertility preference and marital status can be used to explain the influence of residence, age, education and employment on modern contraceptive use as the odds drop when these are introduced in the regression. With regard to education, secondary education is more statistically significant. However, the results also show that the influence of education on modern contraceptive use can be explained by wealth quintile. In terms of employment, those with professional employment are almost twice (1.72) more likely to use modern contraceptives in the final model. The odds in wealth quintile increase when fertility preference and marital status are introduced in the model, with the richest being almost twice (1.68) as likely to use contraceptives as the poorest. In the final model, the odds in marital status also reduce with the currently married being almost 4 times (3.84) more likely to use modern contraceptives than the never married. The final fitting model accounts for 9.2percent, R2, variations in modern contraceptive use.
In conclusion only six of the seven variables in the conceptual framework can be used to explain variations in modern contraceptive use.
Based on the findings, recommendations made include ensuring that all women attain at least secondary level of education and that services providing contraceptive use are made more user friendly to accommodate those in the younger age groups