Determinants of stunting in children under five years in dibate district of Ethiopia: A case-control study

Fufa, Dinaol Abdissa

doi:10.1016/j.hnm.2022.200162

Cited by 15 publications

(17 citation statements)

References 9 publications

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“…Several factors that can cause children to experience stunting are nutritional intake and genetic factors (Fufa, 2022;Paintsil et al, 2022;Wardoyo et al, 2022). Other findings also state that several determinants of children under five who experience stunting are nutritional intake factors in children and genetic factors, in other words, following the short stature of their parents (Lestari et al, 2014;Paintsil et al, 2022).…”

Section: Discussionmentioning

confidence: 95%

Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas

Christyanti

Sulaiman

Utomo

et al. 2022

IJNSE

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Stunting is a chronic nutritional problem that occurs in toddlers, defined based on height for age (TB/U) which is less than two negative standard deviations or a toddler's height is shorter than it should be. Stunting is a chronic nutritional problem in toddlers, characterized by a shorter height than the height of children his age. Bulungan Regency is one of 160 urban regencies in Indonesia that is intervened to focus on reducing stunting. Based on these problems, this study aims to determine the cluster of stunting vulnerabilities in Bulungan Regency. The method used is Fuzzy C-Means (FCM). The results of this study are that the area in cluster 1 has a high level of vulnerability because it has the lowest level of adequacy of posyandu (active) and high incidence of LBW in infants, cluster 2 has a moderate level of vulnerability because it has an adequate level of puskesmas, adequacy of posyandu (active), the adequacy of doctors, the adequacy of nutritionists, the adequacy of midwives, the percentage of moderate LBW, and cluster 3 have a low level of vulnerability because they have a low average percentage of LBW and a high level of adequacy of posyandu (active) in the area.

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Section: Discussionmentioning

confidence: 95%

Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas

Christyanti

Sulaiman

Utomo

et al. 2022

IJNSE

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“… 31 In contrast to the research, a study in the Dibate District of Ethiopia reported that child gender is not associated with stunting. 1 …”

Section: Discussionmentioning

confidence: 99%

“…Stunting is a symptom of chronic undernutrition and is frequently linked to poverty, affecting 149.2 million young children under five in 2020. 1 , 2 Stunting is a condition in which children have a low height for their age. Stunted toddlers have a low height for their age, reflecting nutritional deficiencies (long-term malnutrition) and poor health, which impact nerve cell maturity.…”

Section: Introductionmentioning

confidence: 99%

Stunting Among Children Under Two Years in the Islands Areas: A Cross-sectional Study of the Maluku Region in Indonesia, 2021

Kusumawardani,

Laksono,

Hidayat

et al. 2023

J Res Health Sci

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Background: The Maluku region encompasses thousands of islands. The study analyzed factors related to stunting among children under two years old in the Maluku Region of Indonesia. Study Design: A cross-sectional study. Methods: This cross-sectional study examined 4764 children under two years. In addition to nutritional status (stature), the study analyzed ten independent variables (province, residence, maternal age, marital status, maternal education, employment, wealth, children’s age, gender, and early initiation of breastfeeding [EIBF]). Finally, the contribution of various factors to stunting was examined using logistic regression. Results: Children in Maluku province were 1.13 times more likely than those in North Maluku province to become stunted. In addition, children aged 12-13 months were 4.09 times more likely than<12 months, and boys were 1.87 times more likely than girls to have the patterns of stunting. Children in rural areas were 1.10 times more likely to become stunted than those in urban areas (95% confidence interval: 1.06, 1.14). Divorced/widowed mothers were 1.88 times more likely than married mothers. Mothers of all education levels were more likely than those without formal education, and unemployed mothers were 1.07 times more likely than employed mothers to have stunted children. The possibility of becoming stunted was lower when the children were wealthier. Conclusion: Nine variables were related to stunted incidence, including province, residence, maternal age, marital status, maternal education, employment, wealth, children’s age, and gender.

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“…Stunting disebabkan oleh kekurangan nutrisi dalam jangka waktu yang lama, khusunya selama 1000 hari pertama kehidupan. Kekurangan nutrisi ini disebabkan oleh keragaman pangan keluarga yang rendah, sumber pangan protein hewani yang dikonsumsi serta ukuran keluarga (Fufa, 2022). Kekurangan nutrisi yeng terjadi sejak masa konsepsi, yaitu sejak terjadi kehamilan menyebabkan pertumbuhan dan perkembangan janin terganggu an berdampak pada risiko kejadian stunting.…”

Section: Pendahuluanunclassified

Analisis Faktor Risiko Maternal terhadap Keluarga Berisiko Stunting

Permatasari¹,

Ratnawati²,

Baroya³

et al. 2022

MGI

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Background. In 2021, stunting in Indonesia remains high at 24.4%. Indonesian government has a target to decrease stunting prevalence become 14% in 2024. Jember is one of district in East Java with high stunting prevalence 23,4%. First thousand days of life influenced stunting, and maternal risk factor is one of determinants of stunting. In Indonesia was known as 4T, which is Too young, Too old, Too closed and Too much. Objectives. To analyze Maternal Risk Factor (4T) in families at risk of stunting in Jember district, East Java, Indonesia. Method. This research was ecological study by using secondary data with unit of analysis were 286344 families with stunting risk in Jember district. Source data collection using PK21 (Family Data base 2021) and child monitoring status 2019-2021. Data was analyzed by pearson and spearman correlation. Result. Based on Family data base 2021 in Jember showed that there were 84.19% family at risk of stunting. Maternal risk factor (4T) showed: Too young (age of wife < 19 years) 1.18%; Too old (age of wife > 35 years) 52.50%; too close (birth spacing < 2 years) 1.34%; too much (number of birth > 3) 18.03%. And there were corellation between maternal risk factor too young (0,003), too old (0,000), too close (0,000) and too much (0,000) with family at stunting risk. Conclusion. Stunting in Jember remains high and need prevention by reducing maternal risk factor including: too young, too old, too close, and too much. Keywords: Stunting, Maternal Risk Factor, 4T

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Determinants of stunting in children under five years in dibate district of Ethiopia: A case-control study

Cited by 15 publications

References 9 publications

Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas

Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas

Stunting Among Children Under Two Years in the Islands Areas: A Cross-sectional Study of the Maluku Region in Indonesia, 2021

Analisis Faktor Risiko Maternal terhadap Keluarga Berisiko Stunting

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