On the contrary, several studies [ 16 , 17 ] have shown that postponement of first childbirth to later ages leads to fertility reductions since women would have fewer years of reproduction window which may introduce parity specific controls even after the initiation of child birth.
On the other hand, women who had many years of education had significantly lower fertility as compared to those who had never been enrolled into any formal education system. This corroborates with similar studies [ 13 , 17 - 19 ] and may be attributable to the postponement of childbirth due to longer schooling. Educated women might be more worried to have many children if their area of usual residence had been stricken by frequent food shortage [ 7 ]. Nonetheless, a study among Sidamas in Southern Ethiopia indicated that fertility was higher among women with primary level of education compared to those who never attended any formal education.
Higher educational level of women gives an opportunity of social and economic empowerments. Thus, able women might feel that they could take care of many children and opted for large family size. This is consistent with the claim by some researchers that increased family income leads to increased fertility when family planning use is low [ 17 ].
Education might also have impacts to bring about change in the knowledge and attitude towards low fertility. By the same token, women who did not know the time at which they could be pregnant had higher fertility as compared to those who knew it.
Disparities in level of fertility between urban and rural communities in this study population were similar to the finding in Gondar [ 18 ] that could be attributed to differences in contraceptive prevalence and age at first marriages between urbanites and rural residents in Ethiopia since women in urban areas had better access to media, general knowledge and services.
It was however difficult to document reasons for the change in the direction of associations between residence ecology type and fertility when other factors were controlled.
Meanwhile, informed urbanites might have a positive attitude towards smaller family size besides having better access to family planning services. For instance the urban fertility level of 3.
In a similar context, fertility was significantly lower among women whose major livelihoods are based on trade or services compared to those households who got their main incomes from subsistence farming. Most of the households who relied on trade or services as main source of household income could be influenced by urban culture and practice which showed a low fertility norm. Although food security was widely misunderstood, researchers considered it as shortages in the quality and quantity of food at any time while others defined it as shortage or absence of edible food [ 20 ].
In this study, encounter to household food scarcity in the past calendar year was collected. This variable might not precisely measure the household food security which could be cited as a limitation. However, it indirectly showed the household economic status and risk to vulnerability. Fertility was significantly higher among women whose households suffered from food shortages. There could be an egg-chicken dilemma in this claim since the food shortage might be caused by the large family size which in turn could mainly be triggered by higher fertility.
In a resource constrained environment such as the study area, people had to share the scarce food and could probably be exposed to shortages particularly in rainy seasons, the time at which grain foods of farming households would be depleted [ 21 ]. Fertility was also found to be lower among malnourished mothers compared to nourished ones in a similar study done for Sidamas in Southern Ethiopia [ 22 ]. An in-migrant to the DSA is a person who went there to live or stayed in it for 6 or more months if did not have such intention.
No significant association has been shown between migration status of women and fertility in this study. This could be due to the fact that the duration of residence of in-migrants may not be long enough to influence fertility and reproductive health behavior in the study area as migration was categorized broadly.
It may also that in-migrant women could have come from rural villages in the same or nearby districts of the country which had similar socio-cultural and behavioral characteristics. Nevertheless, a study in China had indicated that rural-urban return migrants from middle and large cities had adapted positive fertility behavior towards small family size norm compared to their rural-rural return migrant counterparts [ 23 ].
The same study had also revealed that areas with higher prevalence of rural-urban return migrants particularly from middle and mega cities would have a positive effect to adapt small family size. Studies done on fertility responses to childhood mortality have focused on insurance and replacement effects [ 24 ]. Couples in high-mortality settings anticipate the death of some of their children that might dictate them to change their reproductive preferences and behavior.
Childhood mortality could also have the combined biological and volitional replacement effects to reduce the time to subsequent conception if the death occurs within a given interval.
The time to conception could also be reduced if a childhood death occurs during a prior birth interval. Accordingly, this study had revealed child mortality as a strong and significant predictor of fertility as documented for the same study population a decade ago and elsewhere [ 17 - 19 ]. Epidemic and frequent episodes of drought in the study community, which might have claimed the lives of their children, provoked mothers to replace the lost ones [ 7 ]. Contrary to the findings of many studies, fertility was significantly higher among women who had no preference to the sex of their children.
Conversely, studies done in Ethiopia and Asia had revealed more preference towards sons compared to daughters because males inherit properties from their ancestors in a patrilineal society. A similar study in USA indicated a stable marital union or request for the custody of their child by fathers if the marriage was dissolved when couples had sons instead of daughters [ 22 , 25 , 26 ].
Religiosity among women in the study community had probably dimmed their decision. The use of Butajira DSS database to recruit study participants and administration of standard maternity history questionnaire by clinical nurses could be mentioned as strengths for the current study. The demographic surveillance staffs knew study participants for a long time and this built trust on the participants side to provide reliable information.
The study was also conducted in a peak harvesting season which reduced the participation of certain community groups that could be away from their home by virtue of their work. Local government authorities should play pivotal role to make women stay more years at school thereby increase the age at first marriage to reduce fertility in the area.
Special attention should also be given to increase the enrollment of women in secondary education to significantly reduce fertility in rural communities.
Moreover, the community should be made aware on the negative impact of large family size on the household economy, environmental degradation and the country's socio-economic development at large.
Efforts to enhance child survival have to be scaled up to curve the level of fertility in resource-constrained rural Ethiopia. WM participated from conception to the final approval of the final version of the article. AW supervised the whole exercise and made critical comments at each step in the research.
He also approved the final version of the article. We are grateful to Dr. Assefa Hailemariam who had commented on the first version of this article. Our heartfelt gratitude should go to study participants who had shared their valuable times with us. Last but not least the field staffs and data entry clerks involved in the study should be acknowledged for their contribution to the success of the project. We thank the Bill and Melinda Gates Institute for sponsoring this study.
National Center for Biotechnology Information , U. Published online Oct Wubegzier Mekonnen 1 and Alemayehu Worku 1. Received Jul 8; Accepted Oct This article has been cited by other articles in PMC. Abstract Background Fertility is high in rural Ethiopia. Results Delayed marriage, higher education, smaller family, absence of child death experience and living in food-secured households were associated with small number of children. Conclusions Policy makers should focus on hoisting women secondary school enrollment and age at first marriage.
Background The three components of population change i. Methods This study was conducted in Butajira demographic surveillance system DSS started with 10 villages 9 rural and 1 urban sampled according to probability proportional to size technique from 82 rural and 4 urban villages [ 10 ]. Table 1 The distribution of study participants by various characteristics in Butajira, Characteristics Number Percent Age at first Marriage Open in a separate window.
Parity Progression Ratio for Women in Butajira, Discussion Total fertility and marital fertility rates of 5. Conclusions Local government authorities should play pivotal role to make women stay more years at school thereby increase the age at first marriage to reduce fertility in the area. Competing interests The authors declare that they have no competing interests. Authors' contributions WM participated from conception to the final approval of the final version of the article.
Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements and Funding We are grateful to Dr. Population and Development Review. High fertility in sub-Saharan Africa. The proximate determinants of the decline to below-replacement fertility in Addis Ababa, Ethiopia.
Fertility decline driven by poverty: Ethiopia Demographic and Health Survey Vulnerability to episodes of extreme weather: Population pressure and land degradation: J Environ Econ Manage. The Butajira rural health project in Ethiopia: Scand J Prim Health Care. Desired family size, family planning and fertility in Ethiopia. Estimation of the total fertility rates and proximate determinants of fertility in North and South Gondar zones, Northwest Ethiopia: An application of the Bongaarts' model.
Bongaarts J, Zimmer Z. The National Population Policy of Ethiopia. Addis Ababa, Ethiopia; Alene GD, Worku A. Differentials of fertility in North and South Gondar zones, northwest Ethiopia: Level and differentials of fertility in Awassa town, Southern Ethiopia. Afr J Reprod Health. However, in quantitative fertility studies, the intermediate fertility variables could not be used.
John Bongaarts has also identified direct determinants of fertility which he called "proximate determinants of fertility. They are called proximate as they are nearest to the event of fertility.
It is possible to study fertility differentials among various populations or trends in fertility levels of any country over a period of time by studying the variations in one or more of the proximate variables.
The proximate determinants of fertility can be classified in two groups, viz. It is obvious that a girl becomes capable of bearing children only after menarche the first menstruation. Thus the menarche marks the beginning of the reproductive span or period and the menopause marks the end of the reproductive period.
Since in Indian and most other societies, socially sanctioned child-bearing is limited only to married women, the marriage of the girl is the starting point of her reproductive period and the disruption of marriage either by death of the husband Or divorce or separation or menopause onset of permanent sterility , whichever is earlier, is the end point of her reproductive span.
Again in India, a small percentage of girls is married before the onset of menarche. In such a situation, the onset of menarche is the beginning of the reproductive period.
Bongaarts’ aggregate model of the proximate determinants of fertility. Bongaarts (, ) and Bongaarts and Potter () refined Davis and Blake’s framework into 7 important factors, which were termed as the proximate determinants of fertility, to understand .
The proximate determinants of fertility can be classified in two groups, viz., (1) those influencing the length of the reproductive span and (2) those influencing the rate of child-bearing within the reproductive.
Read chapter 5 Proximate Determinants of Fertility: This detailed examination of recent trends in fertility and mortality considers the links between thos. Use this quiz/worksheet as an instrument to cement your awareness of the proximate determinants of fertility. If you want a hard copy assessment.
iv Determinants and Consequences of High Fertility | A Synopsis of the Evidence T his report was prepared by John B. Caster-line (Robert T. Lazarus Professor in Popu-. THE PROXIMATE DETERMINANTS DURING THE FERTILITY TRANSITION Jean-Pierre Guengant* INTRODUCTION Fertility has declined very markedly in the majority of developing countries over the past thirty to.