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

Ikoona, Eric Nzirakaindi; Toure, Macoumba; Njenga, Amon; Namulemo, Lucy; Kaluya, Ronald; Kamara, Kassim; Oyat, Freddy Wathum Drinkwater; Aloyo, Judith; Matovu, John Bosco; Kitara, David Lagoro

doi:10.21203/rs.3.rs-2570369/v1

Cited by 3 publications

(14 citation statements)

References 64 publications

(50 reference statements)

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“…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.…”

Section: Methodsmentioning

confidence: 99%

“…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.…”

Section: Methodsmentioning

confidence: 99%

“…[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.…”

Section: Methodsmentioning

confidence: 99%

“…[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.…”

Section: Methodsmentioning

confidence: 99%

“…[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.…”

Section: Methodsmentioning

confidence: 99%

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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

Atim¹,

Alema

Pebolo

et al. 2023

Preprint

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Background: Overweight and obesity are emerging public health problems globally and are independent risk factors for heart, blood vessels, reproductive health, and metabolic disorders. This study aimed to determine the correlates and prevalence of overweight and obesity among women of reproductive age (15-49 years) in Sierra Leone using secondary data analysis of the Demographic Health Survey of 2019. Methods: This study was based on the 2019 Sierra Leone Demographic Health Survey (SLDHS) that used a two-stage stratified cluster sampling technique. A total of 7514 non-pregnant women of reproductive age (15-49 years) were used in the analysis. Simple descriptive, bivariable, and multivariable regression analyses were conducted with a significant p-value set at <0.05. Results: The prevalence of overweight and obesity among women of reproductive age in Sierra Leone was 19.7% and 7.4%, respectively. Overweight was more likely among women of 15-19 age group (adjusted Odds Ratios, aOR=1.933,95%CI:1.532-2.348;p<0.001); women from the north (aOR=1.308,95%CI:1.104-1.581;p<0.006); women without formal education (aOR=1.211,95%CI:1.009-1.454;p<0.040); in poorest (aOR=1.501,95%CI:1.231-1.853;p<0.001) and poorer (aOR=1.419,95%CI:1.154-1.745;p=0.001) wealth indices. However, overweight was 39.9% less likely among 30-39-year (aOR=0.601,95%CI:0.507-0.713;p<0.001) and 49% less likely among 40-49-year (aOR=0.510,95%CI:0.415-0.628;p<0.001) age-groups. It was 27.3% less likely among married women (aOR=0.727,95%CI:0.613-0.863;p<0.001), 24.9% less likely in the south (aOR=0.751,95%CI:0.623-0.911;p=0.002), 38.2% and 48.7% less likely in richer (aOR=0.618,95%CI:0.494-0.773;p<0.001) and richest (aOR=0.513,95%CI:0.389-0.677;p<0.001) wealth indices, respectively. Also, obesity was more likely among women 15-19-year (aOR=2.051,95%CI:1.316-3.198;p=0.002); from the north (aOR=1.426,95%CI:1.038-1.958;p=0.044); in poorest (aOR=2.390,95%CI:1.618-3.532;p<0.001) and poorer (aOR=1.667,95%CI:1.151-2.415;p=0.007) wealth indices. However, it was 68.3% and 79.6% less likely among women 30-39-year (aOR=0.317,95%CI:0.241-0.419;p<0.001) and 40-49-year (aOR=0.204,95%CI:0.149-0.278;p<0.001) age-groups, respectively. It was 36.8% less likely among female-headed households (aOR=0.732,95%CI:0.590-0.909;p=0.005) and 24% less likely among married women (aOR=0.760,95%CI:0.580-0.995;p=0.046); 26.2% less likely in the south (aOR=0.738,95%CI:0.550-0.992;p=0.044); 62.1% and 75.9% less likely in richer (aOR=0.379,95%CI:0.266-0.540;p<0.001) and richest (aOR=0.241,95%CI:0.159-0.367;p<0.001) wealth indices, respectively; and 39.9% less likely among women who listened to radios (aOR=0.601,95%CI:0.507-0.713;p<0.001). Conclusion: The prevalence of overweight and obesity among women of reproductive age (15-49 years) in Sierra Leone was higher compared to world data. Younger age groups, northern region, poorest and poorer wealth indices, and women without formal education were more likely to be overweight and obese. However, overweight and obesity were less likely among older age-groups, married, southern region, richer and richest wealth indices, female-headed households, and listening to radios. There is an urgent need for policymakers in Sierra Leone to tackle overweight and obesity among women of reproductive age (15-49 years) if the current trends are to be reversed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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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

Atim¹,

Alema

Pebolo

et al. 2023

Preprint

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Is nutrition‐sensitive fish farming a panacea for Africa's increasing malnutrition burden? The case of Sierra Leone

Okeke‐Ogbuafor,

Gray,

Sankoh

et al. 2024

Aquaculture Fish & Fisheries

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Fish is vital for reducing hunger and malnutrition. However, the combined impact of climate change and overfishing is increasing the hunger and malnutrition burden on the African continent and its population of over 200 million people who depend on marine capture fishing and related activities for survival. Fish farming was introduced to alleviate these problems, and our study assessed the extent to which current fish farming activities in the least developed countries (LDCs) like Sierra Leone provide sufficient micro‐ and macro‐nutrients for local communities. The present study which is based on data from 300 survey questionnaires and 77 semi‐structured interviews administered in three communities in Sierra Leone, and from two expert judgments which investigated the nutritional impact of fish farming activities in Sierra Leone, revealed that (1) there is a range of sub‐standard fish farming activities from sampled farms; (2) that these activities could diminish the nutritional quality of farmed fish; and (3) that coastal communities were suspicious of eating or investing in fish farming. To alleviate Africa's increasing malnutrition, burden, our research highlights the need for investment in nutrition‐sensitive fish farming – a refocus from an emphasis on increasing production and income. The nutritional quality of farmed fish is a more basic consideration than the quantity of production for securing a healthy and economically viable fish farming sector for LDCs like Sierra Leone.

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Double burden of Malnutrition among women in Reproductive Age (15-49 Years) in India: Evidence from National Family and Health Survey 2019-21 (NFHS-5)

Kumar,

Barik

2024

Preprint

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Background: This study explores the double burden of underweight and overnourished among reproductive-aged women (15–49 years) in India, aiming to identify key predictors and inform targeted interventions. Methods: Utilising data from a nationally representative sample of Indian women, we applied multivariate logistic regression models to calculate relative risk ratios (RRRs) and 95% confidence intervals (CIs) for various demographic, socioeconomic, and behavioural predictors of nutritional status. Results: Age significantly influences nutritional outcomes, women age group 20-24 had a higher risk of being underweight (RRR= 0.69 CI: 0.65-0.75) and the lower risk of being overnourished (RRR=1.63, CI: 1.48-1.79) conversely the women age group 45-49 have the lower risk of underweight (RRR=0.28, CI: 0.26-0.31) and higher risk of overnourished (RRR= 5.49 CI: 4.93-6.11). Residing in rural areas had a higher risk of being underweight (RRR=1.13, CI: 1.07-1.18) and a lower risk of being overnourished (RRR= 0.83 CI: 0.8-0.86). On considering zones of the country, the Southern region shows higher risk of being overnourished (RRR= 1.52, CI: 1.44-1.61) and Western region shows higher risk of being underweight (RRR= 1.61, CI 1.52-1.72) Women with a higher wealth quintile exhibited a higher risk of overnourished (RRR=3.46, CI: 3.19-3.75) and women with a poorer section have higher risk of underweight. Higher education level shows lesser risk of being underweight (RRR=0.67, CI: 0.62-0.72). In the social group, ST has a lower risk of being overnourished (RRR= 0.68, CI: 63-0.74). Smoking increased the risk of being underweight (RRR=1.31, CI: 1.15-1.50), while alcohol consumption was associated with a lower likelihood of being overnourished. Conclusion: The study highlights the determinants of malnutrition among Indian women, emphasizing the need for targeted, age-specific, and region-specific interventions. Comprehensive nutrition education and policy reforms addressing socioeconomic disparities are crucial for mitigating India's double burden of malnutrition.

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

Cited by 3 publications

References 64 publications

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

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

Is nutrition‐sensitive fish farming a panacea for Africa's increasing malnutrition burden? The case of Sierra Leone

Double burden of Malnutrition among women in Reproductive Age (15-49 Years) in India: Evidence from National Family and Health Survey 2019-21 (NFHS-5)

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