Double Burden of Malnutrition Among Women in Reproductive Age (15-49 years) in Sierra Leone: A Secondary Data Analysis of the Demographic Health Survey of 2019 (SLDH-2019).

Abstract

Background The double burden of Malnutrition globally, particularly in sub-Saharan Africa, is on the rise. In Sierra Leone, the incidence of overweight, obesity (OWOB), and overnutrition among women have recently sharply increased, in addition to undernutrition which has been prevalent for decades. This study aimed to determine the prevalence of the different Malnutrition categories (underweight, overweight, obesity, and overnutrition) with Malnutrition among women of reproductive age (15–49 years) in Sierra Leone and associated factors using secondary data analysis of the Demographic Health Survey of 2019 (SLDHS-2019). Methods We conducted a secondary data analysis of the Sierra Leone Demographic Health Survey (2019-SLDHS) of 7,514 women aged 15 to 49. We excluded pregnant, post-natal, lactating, and post-menopausal women. Data was collected using a validated questionnaire, and participants were selected through a multistage stratified sampling approach. A multivariable logistic regression analysis was performed to determine factors associated with the different Malnutrition categories among 15–49-year-old women in Sierra Leone. Results Among 15–49-year-old women in Sierra Leone, the prevalence of the different categories of Malnutrition was as follows: underweight, 6.7%(95%CI:4.5%-8.9%); overweight, 19.7%(95%CI:17.7%-21.7%); obesity, 7.4%(95% CI:5.2%-9.6%); and overnutrition, 27.1%(95%CI:25.2%-29.0%). The independent predictors of not being underweight included: age group of 25–34 years (AOR = 1.670, 95%CI:1.254–2.224;p < 0.001) unmarried (AOR = 0.594,95%CI:0.467–0.755;p < 0.001) women from the North (AOR = 0.734,95%CI:0.559–0.963;p = 0.026), and not listening to a radio (AOR = 0.673;95%CI:0.549–0.826;p < 0.001). The 25–34 years (AOR = 0.609,95%CI:0.514–0.722;p < 0.001) and 35–49 years (AOR = 0.480,95%CI:0.403–0.571;p < 0.001) age groups, unmarried women (AOR = 1.470,95%CI:1.249–1.730;p < 0.001), working-class (AOR = 0.840,95%CI:0.720–0.980;p = 0.026) coming from the North (AOR = 1.325,95%CI:1.096–1.602;p = 0.004) and South (AOR = 0.755,95%CI:0.631–0.903;p = 0.002), middle wealth index (AOR = 0.656,95%CI:0.535–0.804;p < 0.001), richer wealth index (AOR = 0.400,95%CI:0.309–0.517; p < 0.001), richest wealth index (AOR = 0.317,95%CI:0.234–0.431;p < 0.001), and not listening to a radio (AOR = 1.149; 95%CI:1.002–1.317;p = 0.047) were the independent predictors of overweight. The independent predictors of overweight among Sierra Leone women 15–49 years are the same as those of obesity or overnutrition, in addition to female-headed households (AOR = 0.717,95%CI:0.578–0.889;p < 0 .001). Conclusion The prevalence of all the Malnutrition categories among women of reproductive age in Sierra Leone was high, affirming the double burden of Malnutrition in this group. It was more likely to be underweight among the 15–24-year age group compared to the 25–34 and 35–49-year age groups. The independent predictors of overweight, obesity, and overnutrition were age groups of 25–34 and 35–49, unmarried/single women, working class, women from the North and South, female headed households, middle to richest wealth index, and do not listen to a radio. There is an urgent need for policymakers in Sierra Leone to design comprehensive educational campaigns for women in the reproductive age group on healthy lifestyles and the dangers of being underweight or over-nutrition.

Correlates and prevalence of overweight and obesity among women of reproductive age (15-49 years) in Sierra Leone. A secondary data analysis of the demographic health survey of 2019

“…Study participants and sampling methods: Sampling of participants for the 2019 SLDHS was based on a sampling frame provided by Statistics Sierra Leone (Stats SL) for the 2015 population and housing census of the Republic of Sierra Leone. [47][48][49][50][51][52][53] Sierra Leone is administratively divided into four provinces and sixteen districts. Each district is further subdivided into chiefdoms/census wards and sections.…”

“…Each district is further subdivided into chiefdoms/census wards and sections. [47][48][49][50][51][52][53][54] Too, each locality/section was subdivided into convenient census Enumeration Areas (EAs). [47][48][49][50][51][52][53] EAs were used as the primary sampling units (PSUs) or clusters for the 2019 SLDHS.…”

“…[47][48][49][50][51][52][53][54] Too, each locality/section was subdivided into convenient census Enumeration Areas (EAs). [47][48][49][50][51][52][53] EAs were used as the primary sampling units (PSUs) or clusters for the 2019 SLDHS. [47][48][49][50][51][52][53] A list of EAs from the sampling frame formed the basis for estimating the number of households grouped as urban or rural areas.…”

“…[47][48][49][50][51][52][53] EAs were used as the primary sampling units (PSUs) or clusters for the 2019 SLDHS. [47][48][49][50][51][52][53] A list of EAs from the sampling frame formed the basis for estimating the number of households grouped as urban or rural areas. [47][48][49][50][51][52][53] The demographic health survey employed a two-stage strati ed sampling design.…”

“…[47][48][49][50][51][52][53] A list of EAs from the sampling frame formed the basis for estimating the number of households grouped as urban or rural areas. [47][48][49][50][51][52][53] The demographic health survey employed a two-stage strati ed sampling design. First, strati cation was achieved by dividing each district into urban and rural areas.…”