Scientific Review ISSN(e): 2412-2599, ISSN(p): 2413-8835 Vol. 3, No. 4, pp: 29-42, 2017 URL: http://arpgweb.com/?ic=journal&journal=10&info=aims *Corresponding Author 29 Academic Research Publishing Group Proximate Determinants of Fertility in Eastern Africa: The case of Kenya, Rwanda and Tanzania Dawit Getnet Ayele * Department of Epidemiology, The Johns Hopkins University, Bloomberg School of Public Health, U.S.A. Sileshi Fanta Melesse School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, South Africa 1. Introduction Fertility is the principal factor in population dynamics. It is the main contributor to the change in the age and sex structure of a given population. High fertility negatively affects the health, economic and social wellbeing of any society. High fertility and the resulting population growth can cause the depletion of natural resources. The relationship between high fertility and economic growth is mostly negative as there are more mouths to feed with high population growth. Families with substantial number of children are less likely to have quality education as school expenditure per family increases [1]. The risk of child mortality is high for families with enormous number of children. The rates of population growth are not the same in all parts of the world. Developed countries have lower fertility and mortality rates. In developing countries, fertility rates are higher due to the lack of access to contraceptives and generally lower levels of female education. The main issue in developed world is population ageing [2]. The lower fertility rates coupled with low mortality rates lead to the growing number and proportion of elderly persons in developed world. Population ageing will tend to lower labor-force participation since it increases the proportion of economically inactive population. This issue raises concern among developed nations as it might slow future economic growth. Now, the issue of population ageing has received renewed attention in many developed countries. The recent abandoning of one child policy by China also indicates that China (although not categorized as developed country) has faced the problem of aging population. In Sub-Saharan Africa, total fertility was 5.1 births per woman from 2005 to 2010 [3]. This was more than twice the replacement level of fertility. In 2010, there were only five countries with a total fertility rate (TFR) of less than 4 children. These are Cape Verde (2.9), the Republic of South Africa (2.1), Lesotho (3.3), Namibia (3.6) and Swaziland (3.8). The estimated total fertility rate (TFR) for 2005-2010 has increased in several countries, including by more than 5 per cent in 15 high- fertility countries from sub-Saharan Africa [4]. Resources for supporting such population growth in terms of health, education, housing, jobs, food, water, and security do not match the current economic growth of sub-Saharan Africa. More than half of global population growth between now and 2050 is expected to occur in Africa. Africa has the highest rate of population growth among major areas, growing at a pace of 2.55 per cent annually between 2010- 2015 [3]. Therefore, high fertility rate remains a considerable problem in Sub-Saharan Africa. Abstract: This study presents some determinants of fertility for three countries in east Africa. It examines the role of the proximate determinants of fertility to total births during last five years before the surveys in Kenya, Rwanda and Tanzania. The study is based on the analysis of secondary data obtained from Demographic and Health Surveys in the three countries. The surveys were conducted between 2014 and 2016. The response variable used in this study is the number of births in the last five years before the survey. The study employed Quasi-Poisson regression model as the main method of data analysis. The results show that place of residence, working status, number of union, age at first birth, age at first cohabitation, age at first sex, contraceptive use and intention, unmet need and educational level mothers are significant determinants of fertility. Moreover, the findings of this study indicate that educational level of mothers has negative impact on fertility. For current contraceptive users, the mean birth for the last five years is highest for Kenya followed by Tanzania. For those who never use contraception, the mean births for the last five years for Rwanda is lower as compared to Tanzania and Kenya. The mean births for working mothers is also lower than that of non-working mothers for all three countries. The study suggests that improving the educational level of mothers, increasing the use of contraception, and involving more women to work force can reduce fertility in the three countries. Keywords: Children ever born; Fertility status; Negative binomial regression; Quasi-Poisson regression.