A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Socioeconomic and geographical inequalities in adolescent fertility rates in Sierra Leone, 2008-2019. | LitMetric

Socioeconomic and geographical inequalities in adolescent fertility rates in Sierra Leone, 2008-2019.

PLoS One

REMS Consultancy Services Limited, Sekondi-Takoradi, Western Region, Ghana.

Published: December 2024

Background: Sierra Leone, like many other sub-Saharan African countries, grapples with the challenge of high adolescent fertility rates. This study examines the socio-economic and geographical inequalities in adolescent fertility rates in Sierra Leone between 2008 and 2019.

Methods: Three rounds of the Sierra Leone Demographic and Health Surveys (2008, 2013, and 2019) were analysed to examine inequalities in adolescent fertility rates. Descriptive analyses were performed using the online version of the World Health Organization's Health Equity Assessment Toolkit software. Adolescent fertility rate was stratified using four dimensions: economic status, education, place of residence, and province. Difference (D), ratio (R), population attributable risk (PAR) and population attributable fraction (PAF) were calculated as measures of inequality.

Results: The adolescent fertility rates in Sierra Leone declined from 142.5 births per 1,000 women aged 15-19 years in 2008 to 103.5 births per 1,000 women aged 15-19 years in 2019. For economic status, inequality in adolescent fertility rates decreased from 117.3 births per 1,000 adolescent girls in 2008 to 110.6 in 2019. The PAF indicated that the national adolescent fertility rate could have been 46.8% lower in 2008, 42.5% lower in 2013, and 53.5% lower in 2019 if all wealth quintiles had the same fertility rates as the wealthiest quintile (quintile 5). Educational inequality in adolescent fertility rates decreased significantly, from 135.3 births per 1,000 adolescent girls in 2008 to 75.8 in 2019. The PAF showed that the setting average of adolescent fertility rate could have been 57.9% lower in 2008, 33.1% lower in 2013, and 23.9% lower in 2019 without education-related disparities. For place of residence, inequality between urban and rural areas decreased from 82.3 births per 1,000 adolescent girls in 2008 to 74.5 in 2019. The PAF indicated that the national adolescent fertility rate could have been 32.9% lower in 2008, 30.7% lower in 2013, and 33.9% lower in 2019 if rural girls had the same fertility rates as urban girls. Our results further showed that inequality based on province decreased from 77.9 births per 1,000 adolescent girls in 2008 to 64.0 in 2019. The PAF showed that the national average of adolescent fertility rates could have been 34.6% lower in 2008, 37.6% lower in 2013, and 35.8% lower in 2019 without provincial disparities.

Conclusion: Our study found a positive decline in AFR across socioeconomic and geographic groups in Sierra Leone, but significant inequalities remain. Economic status and education are key drivers, with the poorest quintile consistently showing higher AFR. Although AFR declined among girls across all levels of education over time, it increased between 2008 and 2019 for those with primary and higher education. Rural areas had a higher AFR than urban ones, though with less national impact. Policymakers should focus on improving economic opportunities, enhancing quality education, and expanding access to family planning services to reduce adolescent pregnancy and address socioeconomic and educational inequalities.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11642959PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313030PLOS

Publication Analysis

Top Keywords

adolescent fertility
48
fertility rates
40
sierra leone
24
births 1000
24
adolescent
17
fertility rate
16
1000 adolescent
16
adolescent girls
16
girls 2008
16
2019 paf
16

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!