Estimating Trends in Fertility in Kenya from Non Birth History Data

Author:

Ngugi Paul WaweruORCID

Abstract

AbstractThis 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 method (OCM) and reverse survival (RS) method in estimating fertility trend in the country. The study used data from 2015/16 Kenya Integrated Household and Budget Survey (KIHBS) and 2014 Kenya Demographic and Health Survey (KDHS). Data evaluation was done in order to obtain optimal fertility estimates. 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. Results from 2015/16 KIHBS showed that RS estimated Total Fertility Rate to be 3.5 as compared to OCM that estimated it to be 3.8. The results from 2014 KDHS dataset were consistent when using both RS and OCM. 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 RS tends to systematically overstate fertility as compared to OCM. This study found out that in the absence of full birth history data, RS and OCM can reliably estimate consistent fertility estimates and trend.

Publisher

Cold Spring Harbor Laboratory

Reference21 articles.

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