Time trends in socio-economic and geographic-based inequalities in childhood wasting in Guinea over 2 decades: a cross-sectional study

被引:3
作者
Zegeye, Betregiorgis [1 ]
Adjei, Nicholas Kofi [2 ]
Olorunsaiye, Comfort Z. [3 ]
Ahinkorah, Bright Opoku [4 ]
Ameyaw, Edward Kwabena [4 ]
Budu, Eugene [5 ]
Seidu, Abdul-Aziz [5 ]
Yaya, Sanni [6 ]
机构
[1] Shewarobit Field Off, HaSET Maternal & Child Hlth Res Program, Shewarobit, Ethiopia
[2] Univ Liverpool, Dept Publ Hlth & Policy, Liverpool, Merseyside, England
[3] Arcadia Univ, Dept Publ Hlth, Glenside, PA USA
[4] Univ Technol Sydney, Fac Hlth, Sch Publ Hlth, Ultimo, NSW, Australia
[5] Univ Cape Coast, Dept Populat & Hlth, Cape Coast, Ghana
[6] Univ Ottawa, Fac Social Sci, Sch Int Dev & Global Studies, 120 Univ Private, Ottawa, ON K1N 6N5, Canada
来源
INTERNATIONAL HEALTH | 2023年 / 15卷 / 01期
关键词
wasting; inequality; Guinea; DHS; MICS; global health; MALNUTRITION; NUTRITION; HEALTH; URBAN; COUNTRIES; PROGRESS; CHILDREN;
D O I
10.1093/inthealth/ihac002
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Today, an estimated 7.3% (50 million) of all children <5 y of age suffer from wasting, with more burden in African countries including Guinea. Investigating inequalities in childhood wasting is essential for designing efficient programs and interventions, but no related evidence exists in Guinea. This study aimed to examine the trends in the prevalence of childhood wasting and the extent of sex, socio-economic and geographic-based disparities in Guinea. Methods Data from the 1999, 2005 and 2012 Guinea Demographic and Health Surveys and the 2016 Guinea Multiple Indicator Cluster Survey, with a total of 16 137 children <5 y of age were included for analysis. For inequality analysis, we used the 2019 updated World Health Organization Health Equity Assessment Toolkit (HEAT) software. Inequality was measured using four summary measures (difference [D], population attributable risk [PAR], ratio [R] and population attributable fraction [PAF]) for five equity stratifiers (economic status, education, place of residence, sex and subnational region). We computed 95% confidence intervals (CIs) around the points estimates to measure statistical significance. Results The findings revealed a pro-rich (R=1.68 [95% CI 1.11 to 2.24]), pro-urban (PAR=-1.04 [95% CI -1.90 to -0.18]) and subnational region (D=8.11 [95% CI 4.85 to 11.36]) inequalities in childhood wasting across all surveys. Except in 2005, education-based disparities (PAF=-18.2 [95% CI -36.10 to -0.26]) were observed across all survey years, but not sex-based disparities. An approximately constant inequality pattern was seen across all dimensions. Conclusions This study showed inequalities in childhood wasting in Guinea with a disproportionately higher risk of wasting among children from disadvantaged subpopulations/mothers, including uneducated, poorest/poor, rural residents and regions. Policies that target disadvantaged populations need to be considered in order to ensure social protection, access to a wholesome diet and universal and quality health services.
引用
收藏
页码:10 / 18
页数:9
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