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Introduction
1.1 Background
Although it has declined substantially over the past two decades, the pregnancy rate among girls and women 15 to 19 years of age remains a stubborn public health problem. Each year, more than 600,000 teens become pregnant and 3 in 10 teens will become pregnant before they reach 20 years of age. According to community studies, 10%-40% of young girls have had unintended pregnancies and 14 million children worldwide are born every year to young married and unmarried women aged 15-19 years. Similarly, teenage pregnancy accounts for about 70,000 deaths annually. The teenage pregnancy rate is higher in Africa than its surrounding continents; as it is a fact that of the 20 countries in the world that have the highest teenage pregnancy rates, 18 countries are from Africa. Uganda has one of the highest levels of teenage pregnancy ranked 14th out of 54 countries in Africa, with 24% of adolescents (13-19 years) in 2011; who were already mothers or pregnant with their first child. Currently, the average prevalence of teenage pregnancy in Uganda is as high as 25%, with 27% in rural areas and 19% in urban areas. These studies show that teenage pregnancy is still at a high prevalence and particularly most of these cases come from developing countries. Unintended pregnancy is seen as a key concept for understanding fertility and the unmet need for family planning. It has been a major challenge in developing countries including Uganda. However, there is scarce representative information on its determinants among teenagers in Uganda. Data for this study were extracted from the 2016 Uganda Demographic and Health Survey. The prevalence of unintended pregnancies among teenagers between 12-19 was computed. Chi-square and multivariate logit regression analysis methods were used to measure association and predict the factors influencing unintended pregnancies in Uganda.
1.2 Problem statement
Unintended pregnancy can be defined as the kind of pregnancy that is reported to be either unwanted or mistimed. it is a major problem in developing countries, Uganda being one of them. For instance, in the late 1980s, a comparison of demographic and health survey data from 11 developing African countries showed that in Uganda 68% of women aged 20-24 years and 73% of those 35-39 years had given birth in their teens. Uganda is the leading country in teenage motherhood among the 11 countries. Our study involved teenagers between 12-19 years in Uganda as a majority of these unintended pregnancies occur in these age groups. This has led to an increase in school dropout rates among teenage girls and lower enrolment of girls than boys in secondary schools. Therefore, this study aims to identify the determinants of unintended pregnancy among teenagers in Uganda and provide their applicable solutions.
1.3 Research questions
Could religion be a factor contributing to unintended pregnancy among youths in Uganda?
Is there a relationship between the wealth index and unintended pregnancy among youths in Uganda?
Is there adequate access to media on sex education for youths of Uganda?
1.4 Objectives
1.4.1 General Objective
To establish the determinants of unintended pregnancy among teenagers in Uganda and determine factors that can reduce the prevalence of unwanted pregnancies among teenagers.
1.4.2 Specific objectives
- To determine to what extent these determinants influence unintended teenage pregnancy.
- To guide reproductive health program planners and policymakers to implement effective reproductive health programs that can reduce the risk incurred by these unwanted teenage pregnancies.
1.5 Justification of the study
The determinants of unintended pregnancy among teenagers in Uganda have not been delved into and analyzed. From the study, the findings intend to provide policy and program recommendations that will help policymakers, health service providers, and the government to develop effective programs to alleviate unintended pregnancies among teenagers in Uganda. This can further aid in the reduction of cases of pregnancy-related complications in Ugandan teenagers such as abortion, maternal and infant morbidity and mortality.
Literature review
2.1 Introduction
This chapter reviews the relevant literature on the overview of unintended pregnancy among youths and also related works done by other researchers on the subject matter. Hence the literature review will address the various issues under investigation, providing a clearer background to the problem studied.
Unplanned pregnancy in adolescents constitutes an important health problem worldwide and has been associated with a great number of negative health outcomes. Giving birth during the teenage leads to bearing more children than would be expected after the teenage years. (Brhane, G. et al.)The outcome of this phenomenon results in an exponential increase in population growth. Unwanted adolescent pregnancy is also associated with stigmatization, low birth weight, stillbirth, and maternal death. Also, lack of access to health care, the inadequacy of skilled delivery personnel, and delayed access to antenatal care (ANC) deprive teenage mothers and their born babies of essential health care services. Research on the determinants of teenage pregnancy in Uganda is minimal. At least one research has linked adolescent pregnancy with early marriage; this single factor alone cannot constitute all determinants of unwanted teenage pregnancy. It, therefore, becomes essential to do pertinent research and seek the answers to causes and solutions to unintended adolescent pregnancy and eventually help health care authorities, program managers, and policymakers improve their decision-making in planning and problem-solving in Uganda.
The prevalence of unintended pregnancy in Uganda continues to be high. Unintended adolescent pregnancy can have lasting social, economic, and health outcomes. Due to the increasing number of teenage pregnancies in developing countries, a lot of studies have been done to alleviate this phenomenon. Using multilevel logistic regression with the MLwiN program to establish the influence of social disadvantage on teenage pregnancy in West, East, and Southern Africa, results showed that teenage pregnancy decreased in East Africa, plateaued in West Africa, and increased slightly in Southern Africa between 1992-2011. Teenage pregnancy was found to be major associated with family disruption, community level of female unemployment, and community poverty (Odimegwu. C & Mkwananzi. S, 2016 ). The prevalence of teenage pregnancy in Uganda was found to be high (from Uganda Health and Demographic Health Survey 2016 data). Thus the a need to study the determinants of teenage pregnancy in Uganda.
Unintended pregnancy in Uganda has led to high levels of unplanned births, unsafe abortions, and maternal injury and death. (Hussain R, 2013). Among pregnant women in Ghana, the prevalence of unintended pregnancy is significantly predicted by a number of background characteristics such as the age of the women, marital status, education attainment, parity and region of residence, and independent and unmet need for contraception (et al Samuel H. Nyarko, 2019). However, the predictors of teenage pregnancy were overlooked.
Previous studies in Uganda have involved the research of the effects and prevalence of unintended pregnancy and abortion, but the factors influencing teenage pregnancies have not been studied. It, therefore, becomes important to do pertinent research and seek the answers to causes and solutions to unintended teenage pregnancy in Uganda.
3 Methodology
3.1 Introduction
This chapter deals with the methodology used for this study. It discusses the area of study, types and sources of data, statistical techniques employed, data analysis process, and ethical considerations.
3.2 Area of study
The survey was conducted in Uganda. Uganda is located in southeast Africa. It is bordered by Tanzania and Rwanda to the south, Zaire to the west, Sudan to the north, and Kenya to the east. Uganda is landlocked and lies 800 kilometers inland from the Indian Ocean.
3.3 Type and source of data
This study will solely rely on secondary data from Demographic and Health Surveys (DHS). Information from this survey was collected from teenage girls and women who experienced unwanted pregnancy. The surveys were designed to collect detailed information on a wide range of factors and indicators such as the age of the respondent, education level, marital status, age at first pregnancy, wealth index, religion, place of residence and exposure to media and sex education, using cox regression model we will consider the survival time that is, the time to the occurrence of the event (having the pregnancy). Time origin and event time will be clearly defined.
The explanatory variable (covariates) in our analysis will consist of education level (primary, secondary, university, no education), place of residence (rural, urban), exposure to media and sex education (yes, no), wealth index (poor, middle class, rich), religion (Christian, Muslim, others), marital status (single, married, divorced/deceased). The age of respondents must strictly be between 12-19 years since we are dealing with teenagers.
In Cox regression, the hazard function, also referred to as the hazard rate, represents the probability that a subject who is under observation at a time t has an event at that time (in our case the risk of having an unplanned pregnancy before 19 years). It is expressed by h(t) or λ(t). It corresponds to the ratio of the probability density function P(t) and the survival function:
The interpretation of the HR results is similar to RR and OR: an HR higher than 1 means an increase in the hazard, an HR lower than 1 means a reduction in the hazard, and an HR equal to 1 means there is no difference (effect) between the two groups. However, HR, RR, and OR are estimates of different natures and should not be confused.
The Cox regression model is also currently known as the Proportional hazards model. It is a semi-parametric survival model and a regression method. It can be used when investigating the relationship between dependent variables and explanatory variables, also known as covariates, independent variables, or predictors. Therefore, Cox regression permits to evaluation of simultaneously the effect of several factors (adjusted comparisons) on survival. In our cases, we will use the Cox regression model to come up with the determinants of unplanned pregnancies among teenagers in Uganda. Univariate and multivariate models can be performed. It is formulated as follows:
Where:
- t is the survival time;
- h(t) is the hazard function, determined by a set of p independent variables X1i, X2i, …, Xpi for I subjects;
- β1, β2, …, βp are the coefficients (also called parameters) that quantify the statistical relationship between the p covariates and the survival (regression coefficients);
- h0 is the baseline hazard. It corresponds to the value of the hazard if all the Xi are equal to zero.
In order to conclude we will need to check the statistical significance. We will look at the confidence intervals of the HRs, and the probability values (P value) of the covariates and their significance in unplanned teenage pregnancies.
3.4 Data analysis
The study will use statistical software such as Stata, SAS, and R. The data obtained will first be entered cleaned and collated in Excel spreadsheets. The data will then be imported into the statistical software whereby analysis will be done using the Cox regression model.
Reference
- Abdallah IM, Mone’m EFA, Abd El Sabour Hassan M. 2011. “Determinants and Outcomes of Unintended Pregnancy among Women in Helwan District” Journal of American Science, 7(11):497-505.
- Goto A., Seiji Y., Michael R.R. and Akira F. 2002. “Factors associated with unintended pregnancy in Yamagala, Japan”. Social Science& Medicine.; 54 (7): 1065- 79.
- Adetunji J. 1997. “Levels, trends, and determinants of unintended childbearing in developing countries”, paper presented at the annual meeting of the Population Association of America, Washington, DC, March 27-29, 1997.
- Ayele BG/kidan, Gebregzabher TG, Hailu TT, Assefa BA (2018).” Determinants of teenage pregnancy in Degua Tembien District, Tigray, Northern Ethiopia.” A community-based case-control study. PLoS ONE 13(7): e0200898.
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