صورة الغلاف المخصصة
صورة الغلاف المخصصة

Association between fertility rates and socioeconomic status in Tunisia [Ressource électronique] / Nour Chida

بواسطة:نوع المادة : نصنصوصف:1 vol. (35 p.)الموضوع:تصنيف DDC:
  • 304.63209611 23E
تصنيفات أخرى:
  • 304.6
موارد على الانترنت:ملاحظة الأطروحة:Master of arts : Public health : University of Washington : 2014 ملخص:After the launching of a family planning program in Tunisia in 1964, the fertility rate dropped from 7.2 births per women to 2.02 births per women in 2004. Tunisia has also experienced a significant improvement of its economy and its social indicators. However, marked disparities still persist between the industrialized coast and the disadvantaged western inland. Objective: To examine the association between 12 socioeconomic status (SES) indicators and the fertility rates of Tunisian women in each of the 24 governorates. Methods: This descriptive, cross-sectional study used data collected and published by the Tunisian National Statistics Institute. Association between SES indicators and fertility rates variables were determined by the Pearson correlation coefficient and linear regression. Results: Bivariate results show two indicators of high SES, percentage of women with higher education (slope = -.191) and percentage of villa type housing (slope = -.185), were negatively associated with fertility rates (p < .05). Two indicators of low SES, percentage of illiterate women (slope = .131) and percentage of dwellings with only one room (slope = .169), were positively associated with fertility rates (p < .05). Surprisingly, in a multivariate analysis, after adjusting for the other SES indicators, the lack of access to potable water was negatively associated with fertility rates (slope = -.222; p = .014). Among all SES indicators, the percentage of women with higher education showed the strongest bivariate association (R2 = 36.7%). Conclusions: The fertility rate in Tunisia is low, with some of the poorest regions in the country having lower fertility rates than the national rate, mostly due to impressive family planning efforts. The Tunisian family planning program can be considered a successful model for other developing countries
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Master of arts : Public health : University of Washington : 2014

Bibliogr. p. 32-34

After the launching of a family planning program in Tunisia in 1964, the fertility rate dropped from 7.2 births per women to 2.02 births per women in 2004. Tunisia has also experienced a significant improvement of its economy and its social indicators. However, marked disparities still persist between the industrialized coast and the disadvantaged western inland. Objective: To examine the association between 12 socioeconomic status (SES) indicators and the fertility rates of Tunisian women in each of the 24 governorates. Methods: This descriptive, cross-sectional study used data collected and published by the Tunisian National Statistics Institute. Association between SES indicators and fertility rates variables were determined by the Pearson correlation coefficient and linear regression. Results: Bivariate results show two indicators of high SES, percentage of women with higher education (slope = -.191) and percentage of villa type housing (slope = -.185), were negatively associated with fertility rates (p < .05). Two indicators of low SES, percentage of illiterate women (slope = .131) and percentage of dwellings with only one room (slope = .169), were positively associated with fertility rates (p < .05). Surprisingly, in a multivariate analysis, after adjusting for the other SES indicators, the lack of access to potable water was negatively associated with fertility rates (slope = -.222; p = .014). Among all SES indicators, the percentage of women with higher education showed the strongest bivariate association (R2 = 36.7%). Conclusions: The fertility rate in Tunisia is low, with some of the poorest regions in the country having lower fertility rates than the national rate, mostly due to impressive family planning efforts. The Tunisian family planning program can be considered a successful model for other developing countries

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