Estimating Trends In Fertility In Kenya From Non Birth History Data
Waweru, Ngugi Paul
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This study aimed at determining the extent to which methods for estimating trends in fertility without use of birth history could be used on Kenyan surveys data by employing the own-children and reverse survival methods in estimating fertility trend in the country. This study sought to check if the estimates from OCM and reverse survival were consistent. The study used data from 2015/16 KIHBS and 2014 KDHS. Data evaluation was done in order to obtain optimal fertility estimates. When the data was examined using age ratios, there was no systematic overstating and understating of age for almost all the reproductive-aged women interviewed during the survey. 2015/16 KIHBS data reported a Whipples index of 49.0 and 57.5 for terminal digits 0 and 5 respectively. Myer’s blended index was 2.9 and this was an indication that in general the data was accurate and therefore did not require any adjustment to improve its quality before use. The data had some 17 year old women who have given birth to more than 7 children. Results from 2015/16 KIHBS showed that reverse survival estimated TFR to be 3.5 as compared to OCM that estimated it to be 3.8. To check for the consistency of the results, 2014 KDHS was used. The results from 2014 KDHS dataset were consistent when using both reverse survival and own children method and also consistent with figures obtained from birth history method. The two indirect methods can give consistent fertility estimates when the reference period is closer to the survey period but in the fourth and fifth year reverse survival vi method tends to systematically overstate fertility as compared to OCM and therefore the latter is preferred since it can give reliable and consistent current estimates and trends. This study found out that in the absence of full birth history data, reverse survival and OCM methods can reliably estimate consistent fertility estimates and trend. The study recommends that the Government should embrace the use of indirect techniques that utilize non birth history data to estimate fertility.
University of Nairobi
RightsAttribution-NonCommercial-NoDerivs 3.0 United States
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