Prevalence, regional disparities and associated factors of vitamin A-rich food consumption among children 6–24 months in Somaliland: Evidence from a National Survey

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While the importance of Vitamin A for immune function and development is well-established, specific data regarding the dietary intake of this micronutrient among young children in Somaliland remains limited. Objective This study aimed to assess the prevalence, regional disparities, and factors associated with the consumption of vitamin A-rich foods among children aged 6–24 months in Somaliland. Methods A secondary analysis consisted of 1,086 children was conducted using data from the 2020 Somaliland Demographic and Health Survey, a nationally representative community-based cross-sectional study. The outcome variable was the consumption of vitamin A-rich foods in the 24 hours preceding the survey. Multivariable logistic regression analyses were performed to identify predictors of consumption using Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI). Results The overall prevalence of vitamin A-rich food consumption was 56.45% (95% CI: 53.47–59.37). Fresh milk was the most common source (48.07%), while consumption of fruits and vegetables was low. Significant regional variations were observed; the Sahil region had the highest consumption (73.24%), while the Sanaag region had the lowest (49.48%). Multivariable analysis indicated that children from middle (AOR = 0.59; 95% CI: 0.38–0.93) and rich (AOR = 0.50; 95% CI: 0.36–0.71) wealth quintiles were significantly less likely to consume vitamin A-rich foods compared to those from poor households. Conversely, maternal exposure to mass media was a strong positive predictor (AOR = 5.04; 95% CI: 1.55–16.43). Conclusion Vitamin A-rich food consumption among children in Somaliland is suboptimal and varies significantly by region. The findings reveal a paradox where higher household wealth correlates with lower consumption, while media exposure significantly improves intake. Vitamin A-rich food consumption Geographical variation Children Somaliland Nutrients Figures Figure 1 Figure 2 Figure 3 Introduction Micronutrients are essential for optimal human health, playing a critical role in numerous physiological processes vital for child growth and development ( 1 , 2 ). These essential vitamins and minerals, though required in small quantities, significantly influence cellular and humoral immune responses, cellular signaling and function, and cognitive development ( 1 , 3 , 4 ). Adequate intake of micronutrients is foundational for children's survival and long-term well-being ( 5 , 6 ). Their absence and inadequacy in the diet negatively affect children’s survival and development ( 7 , 8 ). The World Health Organization (WHO) advocates for diverse complementary feeding practices, including both plant-based foods and animal products such as meat, poultry, fish, or eggs, to ensure children meet their nutrient requirements ( 1 , 9 ). The importance of various micronutrients, including vitamin A, vitamin D, iron, and zinc, for child health is widely recognized ( 6 , 10 , 11 ). Deficiencies in micronutrients among children represent a pervasive global public health challenge, predisposing them to various adverse health outcomes ( 1 , 5 , 12 ). Even marginal inadequacies in dietary intake can severely impact children’s survival and development, leading to conditions such as anemia, stunting, wasting, weakened immunity, and delayed cognitive development ( 3 , 7 , 8 ). Among these, vitamin A deficiency (VAD) is particularly critical, as it significantly contributes to child mortality from common childhood illnesses like measles, diarrhea, malaria, and other infectious diseases ( 1 , 3 , 5 , 13 , 14 ). Globally, VAD imposes a substantial public health burden, affecting millions of preschool-aged children and contributing to a significant number of preventable deaths ( 2 , 5 , 12 ). It is estimated that approximately 250 million preschool children are vulnerable to VAD, with a quarter of a million children becoming blind annually, and half of these succumbing to death before 23 months of age ( 1 , 15 ). The global prevalence of VAD in populations at risk was estimated to be 33.3% among preschool children ( 5 , 16 , 17 ). Developing regions, notably South Asia and sub-Saharan Africa, bear a disproportionately high burden of childhood malnutrition and micronutrient deficiencies ( 1 , 5 , 17 , 18 ). These regions are home to a significant number of chronically undernourished children, with over 200 million African children suffering from malnutrition and failing to achieve their full cognitive potential ( 1 , 19 ). The prevalence of VAD in Africa has been reported to range widely, from 8.5% to 79% ( 1 , 20 , 21 ). VAD is very common in the African continent, affecting more than 30 million children, most of whom are younger than five years of age ( 22 ). The Somalia Micronutrient Survey 2019 showed that good nutrition is still out of reach for large numbers of Somali children under the age of five. The survey revealed that 34% of children under the age of five suffer from vitamin A deficiency, 43% of anemia and 28.6% of iron deficiency anemia; 47% of pregnant women are also anemic. The national prevalence of VAD denotes a severe public health problem in children (> 30%) and a moderate public health problem in women (10%-20%) according to WHO criteria ( 15 ). Given Somaliland's geographical location within the Horn of Africa and its socio-economic parallels with neighboring developing countries, it is highly probable that its child population faces a similar, if not greater, risk of VAD. In Ethiopia, VAD continues to be a significant public health problem among children, with its prevalence varying considerably across different regions ( 1 , 3 ). The estimated prevalence of VAD among Ethiopian children ranges from 20% to 39% ( 13 , 18 , 21 ). Reports from the Ethiopian Demographic and Health Surveys (DHS) indicate that the intake of vitamin A-rich foods among children aged 6–23 months has been consistently low, with only 38% in 2016 and 39% in 2019 meeting the criteria for intake within a 24-hour period ( 1 , 3 , 23 , 24 ). While extensive research has documented the prevalence and determinants of vitamin A-rich food intake among children in East African nations ( 1 , 3 , 4 ), a notable gap exists in the specific context of Somaliland. Therefore, this study is justified by the critical need to understand the unique prevalence, regional disparities, and associated factors of vitamin A-rich food intake among young children aged 6–24 months in Somaliland, using robust multivariate analytical approaches to guide effective nutritional programming and policy. Methods Study Area Somaliland is a self-declared autonomous region located in the Horn of Africa, geographically positioned along the southern coast of the Gulf of Aden. The region is administratively divided into six major regions: Awdal, Marodijeh, Sahil, Togdheer, Sool, and Sanaag, with Hargeisa serving as the capital and largest city. The area is characterized by a semi-arid climate and faces significant public health challenges, including food insecurity and micronutrient deficiencies, which are often exacerbated by recurrent droughts and limited healthcare infrastructure (Fig. 1 ). Source of data and Study design This study utilized secondary data derived from the 2020 Somaliland Demographic and Health Survey (SLDHS), which serves as a nationally representative household survey. The survey employed a community-based cross-sectional study design to generate updated health and demographic indicators for the population. Population and sample size The source population for this study included all children aged 6 to 24 months residing in the selected households across the six administrative regions of Somaliland during the survey period. The final sample size consisted of 1,086 children for whom complete data regarding dietary intake and relevant maternal and household characteristics were available in the dataset. Inclusion criteria The analysis included all living children aged 6 to 24 months who were residing with their mothers or primary caregivers at the time of the interview. Children who had missing values for the dietary recall outcome variable or significant missing data for key explanatory socio-demographic variables were excluded to ensure the accuracy of the statistical modeling. Study Variables The outcome variable, consumption of foods rich in Vitamin A, was constructed using eight dietary recall variables that capture whether the child consumed specific vitamin-A–rich food items in the past 24 hours, namely eggs (V414G), fresh milk (V411B), cheese or other milk products (V414P), meat (V414H), pumpkin/carrot/squash (V414I), fish or shellfish (V414N), organ meats such as liver (V414M), and vitamin-A–rich fruits such as mangoes or papayas (V414K). These individual items were combined to classify children into “Good consumption” (if they consumed at least one of these vitamin-A–rich foods) and “No consumption” (if they consumed none of them). The predictor variables selected for this analysis were identified based on previous literature regarding determinants of child nutrition, data availability and sample size representativeness within the SLDHS. These included the region, residence, household wealth quintile, mother’s age, mother’s educational level, marital status, employment status, pregnancy status, age of child (months), child sex birth order (parity), household's exposure to mass media. Data management and data analysis All data management steps were conducted using a statistical software of STATA 16.0 to prepare the final dataset for rigorous testing. Descriptive statistics, including frequencies and percentages, were used to summarize the socio-demographic characteristics of the study participants. Bivariable logistic regression was initially performed to assess the crude association between each predictor variable and the outcome variable, with those having a p-value < 0.25 considered for further analysis. A multivariable logistic regression model was then employed to identify statistically significant predictors while controlling for confounding factors. The strength of association was measured using Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI), and statistical significance was declared at a p-value < 0.05. Multi-collinearity among independent variables was also assessed using variance inflation factor (VIF) and a value of 10 was used as cut off. Ethics approvals As this study involved a secondary analysis of the 2020 SLDHS, its publicly available secondary data. Informed consent was obtained from all participants during primary data collection. Formal permission to access and analyze this dataset was granted by the DHS Program. Results Socio-demographic and economic characteristics A total of 1,086 children aged 6–24 months participated in the study. The majority of mothers (74.40%) were between the ages of 20 and 34 years. Educational attainment among mothers was notably low, with 85.17% having no formal education. In terms of economic status, the majority of households (66.21%) were classified as poor, and 99.82% of mothers reported not working. The study participants were fairly evenly distributed between rural (52.30%) and urban (47.70%) settings (Table 1 ). Table 1 Descriptive Statistics of children aged 6–24 months in Somaliland, n = 1086 Variable Category Frequency Percent Mother's Age < 20 years 84 7.73% 20–34 years 808 74.40% 35–49 years 194 17.86% Mother's Education No Education 925 85.17% Primary 133 12.25% Secondary 23 2.12% Higher 5 0.46% Wealth Quintile Poor 719 66.21% Middle 95 8.75% Rich 272 25.05% Work Status Yes 2 0.18% No 1,084 99.82% Parity < 3 births 296 27.26% 3–4 births 344 31.68% 5 + births 446 41.07% Marital Status Married 1,029 94.75% Divorced 35 3.22% Widowed 22 2.03% Pregnant Status Yes 208 19.15% No 878 80.85% Child Age 6–8 months 193 17.77% 9–11 months 144 13.26% 12–17 months 419 38.58% 18–24 months 330 30.39% Child Sex Female 495 45.58% Male 591 54.42% Media Exposure No exposure 1,067 98.25% Have exposure 19 1.75% Region Awdal 46 4.24% Marodijeh 48 4.42% Sahil 71 6.54% Togdheer 130 11.97% Sool 403 37.11% Sanaag 388 35.73% Residence Rural 568 52.30% Urban 518 47.70% Prevalence and sources of Vitamin A-rich food consumption The overall prevalence of adequate Vitamin A-rich food consumption was found to be 56.45% (n = 613), while 43.55% (n = 473) of children had inadequate consumption (Fig. 2 ). Regarding specific food sources, fresh milk was by far the most consumed Vitamin A source, consumed by 48.07% of children. Consumption of other Vitamin A-rich foods was significantly lower. Only 7.73% consumed dairy products like cheese or yogurt, 7.09% consumed meat, and 7% consumed organs. Plant-based sources were also low, with only 6.63% consuming pumpkins/carrots and 6.17% consuming Vitamin A-rich fruits (Table 2 ). Table 2 Sources of Vitamin A-rich food consumption among children aged 6–24 months in Somaliland, n = 1086. Variable (Food Item) Category n % Eggs Yes 40 3.68 No 1,046 96.32 Fresh milk Yes 522 48.07 No 564 51.93 Cheese, yogurt, milk products Yes 84 7.73 No 1,002 92.27 Meat Yes 77 7.09 No 1,009 92.91 Pumpkin, carrots, squash Yes 72 6.63 No 1,014 93.37 Fish or shellfish Yes 29 2.67 No 1,057 97.33 Organs Yes 76 7 No 1,010 93 Vitamin A fruits Yes 67 6.17 No 1,019 93.83 Regional Distribution of Vitamin A Consumption Figure 3 illustrates the spatial distribution of Vitamin A consumption prevalence across the regions of Somaliland. There is notable regional heterogeneity in dietary habits. The Sahil region exhibited the highest prevalence of Vitamin A-rich food consumption at 73.24%, followed closely by Togdheer (69.23%) and Maroodi Jeex (64.58%). Conversely, the eastern regions showed lower consumption rates, with Sanaag recording the lowest prevalence at 49.48%, followed by Sool (55.33%) and Awdal (54.35%). This geographic variation implies that factors such as regional climate, access to markets, or local pastoral practices specifically regarding milk availability may influence consumption levels. Factors associated with consumption of vitamin A-rich food Bivariable and multivariable logistic regression analyses were performed to identify predictors of Vitamin A consumption (Table 3). In the multivariable analysis, wealth quintile and media exposure were found to be statistically significant predictors (p < 0.05). Children from households in the middle wealth quintile (AOR = 0.59; 95% CI: 0.38–0.93) and rich wealth quintile (AOR = 0.50; 95% CI: 0.36–0.71) were less likely to consume Vitamin A-rich foods compared to those in the poor wealth quintile. Media exposure showed a strong positive association. Children of mothers who had exposure to media were 5.04 times more likely (AOR = 5.04; 95% CI: 1.55–16.43) to have good Vitamin A consumption compared to those with no exposure. Other factors, including maternal age, education level, parity, and marital status, did not show statistically significant associations with Vitamin A consumption in the multivariable model (p > 0.05). Table 4 Bivariate and multivariate Analysis of Factors Associated with Vitamin A-Rich Food Consumption among children aged 6–24 months in Somaliland, n = 1086 Variable Category Vitamin A Consumption COR (95% CI) AOR (95% CI) P-value No (%) Yes (%) Mother's Age < 20 years 38.10% 61.90% 1 20–34 years 43.69% 56.31% 0.79 (0.49–1.29) 0.65 (0.39–1.10) 0.108 35–49 years 45.36% 54.64% 0.74 (0.44–1.25) 0.56 (0.30–1.04) 0.067 Mother's Education No Education 42.59% 57.41% 1 Primary 48.87% 51.13% 0.78 (0.54–1.12) 0.96 (0.64–1.45) 0.843 Secondary 47.83% 52.17% 0.81 (0.35–1.85) 1.20 (0.49–2.92) 0.690 Higher 60.00% 40.00% 0.49 (0.08–3.02) 0.70 (0.11–4.53) 0.704 Wealth Quintile Poor 37.41% 62.59% 1 Middle 53.68% 46.32% 0.52 (0.34–0.79)** 0.59 (0.38–0.93) 0.023 Rich 56.25% 43.75% 0.47 (0.35–0.62)** 0.50 (0.36–0.71)** 0.000 Work Status Yes 100.00% 0.00% 1 No 43.45% 56.55% -† -† - Parity < 3 births 45.27% 54.73% 1 3–4 births 43.60% 56.40% 1.07 (0.78–1.46) 1.20 (0.86–1.69) 0.288 5 + births 42.38% 57.62% 1.12 (0.83–1.52) 1.37 (0.96–1.94) 0.080 Marital Status Married 42.66% 57.34% 1 Divorced 60.00% 40.00% 0.50 (0.25–0.99) 0.64 (0.31–1.32) 0.223 Widowed 59.09% 40.91% 0.52 (0.22–1.22) 0.46 (0.19–1.12) 0.087 Pregnant Status Yes 40.87% 59.13% 1 No 44.19% 55.81% 0.87 (0.64–1.19) 0.89 (0.64–1.24) 0.488 Child Age ( months) 6–8 47.15% 52.85% 1 9–11 38.89% 61.11% 1.40 (0.91–2.17) 1.48 (0.93–2.35) 0.098 12–17 42.48% 57.52% 1.21 (0.87–1.68) 1.24 (0.86–1.79) 0.254 18–24 44.85% 55.15% 1.10 (0.76–1.58) 1.07 (0.73–1.57) 0.742 Child Sex Female 42.83% 57.17% 1 Male 44.16% 55.84% 0.95 (0.74–1.21) 0.99 (0.77–1.28) 0.938 Media Exposure No exposure 43.96% 56.04% 1 Exposure 21.05% 78.95% 2.94 (0.97–8.91) 5.04 (1.55–16.43)** 0.007 Region Awdal 45.65% 54.35% 1 Marodijeh 35.42% 64.58% 1.53 (0.68–3.46) 1.42 (0.61–3.30) 0.411 Sahil 26.76% 73.24% 2.30 (1.05–5.03) 2.03 (0.92–4.49) 0.080 Togdheer 30.77% 69.23% 1.89 (0.95–3.77) 1.90 (0.94–3.84) 0.074 Sool 44.67% 55.33% 1.04 (0.56–1.93) 1.20 (0.63–2.26) 0.584 Sanaag 50.52% 49.48% 0.82 (0.43–1.58) 1.00 (0.53–1.91) 0.990 Residence Rural 41.37% 58.63% 1 Urban 45.95% 54.05% 0.83 (0.65–1.06) 0.85 (0.66–1.09) 0.190 **Significant at p < 0.05 †Could not be estimated due to sparse data (only 2 observations in "Yes" category for work status) Discussion According to the World Health Organization (WHO), people should receive vitamin A supplements two times per year ( 9 ). This study confirmed that 56.45% (95% CI: 53.47 59.37) of children aged 6–24 months had vitamin A rich foods intake within, or in the last 24 h in Somaliland. This finding is higher than study done in rural Burundi (16%) and Rwanda (23%) ( 25 ), Ghana (52%) ( 18 ), and Ethiopia (13.3%-24%) ( 26 ). The possible reason for this variation may be due to socio-demographic variation, recent advancements in health care delivery, and accessibility of health care services. However, this finding is lower when we compared with studies done in different areas such as India (58.1%) ( 27 ), Malawi (79.1%) ( 28 ), and Uganda (66.5%) ( 29 ). The possible justification for variation may be due to differences in socio-demographic and economic characteristics, study setting, and maternal healthcare characteristics. In multivariable logistic regression analysis, household wealth status, and Media exposure were statistically significant factors for vitamin A rich foods intake among children aged from 6–24 months in Somaliland. Mothers in the middle wealth category (AOR = 0.59; 95% CI: 0.38–0.93) and those in the rich wealth category (AOR = 0.50; 95% CI: 0.36–0.71) were 41% and 50% less likely, respectively, to consume adequate vitamin A–rich foods compared with mothers in the poor wealth category. Unexpectedly, this study found that adequate vitamin A consumption was higher among women in the poor wealth category compared to those in the middle and rich categories. This finding is inconsistent with previous research ( 5 , 15 , 30 – 32 ). A possible explanation is that women from wealthier households, despite having economic access, may prioritize Vitamin A–rich foods less than their counterparts. In the present study, media significantly affects the intake of vitamin A rich foods among children aged from 6 to 24 months in Somaliland. Those children whose mothers had exposure to media were 5.04 times more likely (AOR = 5.04; 95% CI: 1.55–16.43) to intake vitamin A rich foods than children whose mother had no exposure. This finding is in line with studies done in different parts of Ethiopia ( 26 , 33 – 37 ), Bangladesh ( 38 ), and Indonesia ( 39 ). This might be the impact of media for promoting child feeding practice and mothers’ exposure to media able to feed different foods groups to their children. Strengths and Limitation Since the study is done through using SLDHS national datasets which the finding may have good generalizability. Conducting multivariate logistic regression model and the larger sample size proved important in maintaining the internal validity of the study by helping provide precise descriptive and analytic findings are considered as the strength of this study. As a limitation, since the data was collected retrospectively it may prone recall bias. As long as the 2020 SLDHS dataset has no observation for some variables, important variables which determine vitamin A rich foods intake among children may not be included under this study. Conclusion The magnitude of Vitamin A rich foods intake among children aged 6–24 months across the regions of Somaliland is insufficient at national level. Independent variables such as wealth status of mother, and Media exposure were significantly associated with vitamin A rich foods intake among children aged 6–24 months. Therefore, policymakers should give due attention to the poor wealth status, and media non-exposed mothers, to improve good consumption of foods rich in vitamin A among children aged 6–24 months in Somaliland. Abbreviations AOR - Adjusted Odds Ratio CI - Confidence Interval SLDHS - Somaliland Demographic and Health Survey VAD - Vitamin A Deficiency VIF - Variance Inflation Factor WHO - World Health Organization Declarations Acknowledgments The authors are grateful to the Demographic and Health Surveys Program for granting them access to the dataset. Authors’ contribution statement AIM: Conceptualization, Methodology, Data analysis, Investigation, Writing – Original Draft, Writing – Review & Editing. Data availability The data used in this study, while not publicly available, can be obtained from the corresponding author upon reasonable request. Declaration of competing interest The authors have no competing interests to declare that are relevant to the content of this article. 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Eshete T, Kumera G, Bazezew Y, Mihretie A, Marie T. Determinants of inadequate minimum dietary diversity among children aged 6–23 months in Ethiopia: secondary data analysis from Ethiopian Demographic and Health Survey 2016. Agric Food Secur. 2018;7(1):1–8. Blackstone S, Sanghvi T. A comparison of minimum dietary diversity in Bangladesh in 2011 and 2014. Matern Child Nutr. 2018;14(4):e12609. Sekartaji R, Suza DE, Fauziningtyas R, Almutairi WM, Susanti IA, Astutik E, et al. Dietary diversity and associated factors among children aged 6–23 months in Indonesia. J Pediatr Nurs. 2021;56:30–4. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9010321","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599724560,"identity":"da65a9d6-21d4-4d1b-a1b0-5006d0100016","order_by":0,"name":"Abdifatah Ibrahim Mouse","email":"data:image/png;base64,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","orcid":"","institution":"Amoud University","correspondingAuthor":true,"prefix":"","firstName":"Abdifatah","middleName":"Ibrahim","lastName":"Mouse","suffix":""}],"badges":[],"createdAt":"2026-03-02 12:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9010321/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9010321/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104403710,"identity":"5668699b-25e3-419d-9f32-5be86d438947","added_by":"auto","created_at":"2026-03-11 12:18:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":418972,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy area\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9010321/v1/171f0139e82ae97d12beb956.png"},{"id":104179605,"identity":"f785abfa-da83-4db5-b144-324b0f6d824b","added_by":"auto","created_at":"2026-03-08 17:06:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32940,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVitamin A-rich food consumption\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9010321/v1/77a61b228d3b3a1030005307.png"},{"id":104179608,"identity":"1497b4f4-0171-4acb-ab02-9eb88aeeb9c2","added_by":"auto","created_at":"2026-03-08 17:06:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112992,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial distribution of Vitamin A consumption in Somaliland\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9010321/v1/1d859df25da426e1de35710d.png"},{"id":104408894,"identity":"ebadec64-f8e6-4505-8101-efb3e09c14ff","added_by":"auto","created_at":"2026-03-11 12:43:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1665679,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9010321/v1/cd99de9a-32f6-41f8-b765-2c3351111dab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence, regional disparities and associated factors of vitamin A-rich food consumption among children 6–24 months in Somaliland: Evidence from a National Survey","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicronutrients are essential for optimal human health, playing a critical role in numerous physiological processes vital for child growth and development (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). These essential vitamins and minerals, though required in small quantities, significantly influence cellular and humoral immune responses, cellular signaling and function, and cognitive development (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Adequate intake of micronutrients is foundational for children's survival and long-term well-being (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Their absence and inadequacy in the diet negatively affect children\u0026rsquo;s survival and development (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The World Health Organization (WHO) advocates for diverse complementary feeding practices, including both plant-based foods and animal products such as meat, poultry, fish, or eggs, to ensure children meet their nutrient requirements (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The importance of various micronutrients, including vitamin A, vitamin D, iron, and zinc, for child health is widely recognized (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDeficiencies in micronutrients among children represent a pervasive global public health challenge, predisposing them to various adverse health outcomes (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Even marginal inadequacies in dietary intake can severely impact children\u0026rsquo;s survival and development, leading to conditions such as anemia, stunting, wasting, weakened immunity, and delayed cognitive development (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Among these, vitamin A deficiency (VAD) is particularly critical, as it significantly contributes to child mortality from common childhood illnesses like measles, diarrhea, malaria, and other infectious diseases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobally, VAD imposes a substantial public health burden, affecting millions of preschool-aged children and contributing to a significant number of preventable deaths (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). It is estimated that approximately 250\u0026nbsp;million preschool children are vulnerable to VAD, with a quarter of a million children becoming blind annually, and half of these succumbing to death before 23 months of age (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The global prevalence of VAD in populations at risk was estimated to be 33.3% among preschool children (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDeveloping regions, notably South Asia and sub-Saharan Africa, bear a disproportionately high burden of childhood malnutrition and micronutrient deficiencies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These regions are home to a significant number of chronically undernourished children, with over 200\u0026nbsp;million African children suffering from malnutrition and failing to achieve their full cognitive potential (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The prevalence of VAD in Africa has been reported to range widely, from 8.5% to 79% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). VAD is very common in the African continent, affecting more than 30\u0026nbsp;million children, most of whom are younger than five years of age (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Somalia Micronutrient Survey 2019 showed that good nutrition is still out of reach for large numbers of Somali children under the age of five. The survey revealed that 34% of children under the age of five suffer from vitamin A deficiency, 43% of anemia and 28.6% of iron deficiency anemia; 47% of pregnant women are also anemic. The national prevalence of VAD denotes a severe public health problem in children (\u0026gt;\u0026thinsp;30%) and a moderate public health problem in women (10%-20%) according to WHO criteria (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven Somaliland's geographical location within the Horn of Africa and its socio-economic parallels with neighboring developing countries, it is highly probable that its child population faces a similar, if not greater, risk of VAD.\u003c/p\u003e \u003cp\u003eIn Ethiopia, VAD continues to be a significant public health problem among children, with its prevalence varying considerably across different regions (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The estimated prevalence of VAD among Ethiopian children ranges from 20% to 39% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Reports from the Ethiopian Demographic and Health Surveys (DHS) indicate that the intake of vitamin A-rich foods among children aged 6\u0026ndash;23 months has been consistently low, with only 38% in 2016 and 39% in 2019 meeting the criteria for intake within a 24-hour period (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile extensive research has documented the prevalence and determinants of vitamin A-rich food intake among children in East African nations (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), a notable gap exists in the specific context of Somaliland. Therefore, this study is justified by the critical need to understand the unique prevalence, regional disparities, and associated factors of vitamin A-rich food intake among young children aged 6\u0026ndash;24 months in Somaliland, using robust multivariate analytical approaches to guide effective nutritional programming and policy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area\u003c/h2\u003e \u003cp\u003eSomaliland is a self-declared autonomous region located in the Horn of Africa, geographically positioned along the southern coast of the Gulf of Aden. The region is administratively divided into six major regions: Awdal, Marodijeh, Sahil, Togdheer, Sool, and Sanaag, with Hargeisa serving as the capital and largest city. The area is characterized by a semi-arid climate and faces significant public health challenges, including food insecurity and micronutrient deficiencies, which are often exacerbated by recurrent droughts and limited healthcare infrastructure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSource of data and Study design\u003c/h3\u003e\n\u003cp\u003eThis study utilized secondary data derived from the 2020 Somaliland Demographic and Health Survey (SLDHS), which serves as a nationally representative household survey. The survey employed a community-based cross-sectional study design to generate updated health and demographic indicators for the population.\u003c/p\u003e\n\u003ch3\u003ePopulation and sample size\u003c/h3\u003e\n\u003cp\u003eThe source population for this study included all children aged 6 to 24 months residing in the selected households across the six administrative regions of Somaliland during the survey period. The final sample size consisted of 1,086 children for whom complete data regarding dietary intake and relevant maternal and household characteristics were available in the dataset.\u003c/p\u003e\n\u003ch3\u003eInclusion criteria\u003c/h3\u003e\n\u003cp\u003eThe analysis included all living children aged 6 to 24 months who were residing with their mothers or primary caregivers at the time of the interview. Children who had missing values for the dietary recall outcome variable or significant missing data for key explanatory socio-demographic variables were excluded to ensure the accuracy of the statistical modeling.\u003c/p\u003e\n\u003ch3\u003eStudy Variables\u003c/h3\u003e\n\u003cp\u003eThe outcome variable, consumption of foods rich in Vitamin A, was constructed using eight dietary recall variables that capture whether the child consumed specific vitamin-A\u0026ndash;rich food items in the past 24 hours, namely eggs (V414G), fresh milk (V411B), cheese or other milk products (V414P), meat (V414H), pumpkin/carrot/squash (V414I), fish or shellfish (V414N), organ meats such as liver (V414M), and vitamin-A\u0026ndash;rich fruits such as mangoes or papayas (V414K). These individual items were combined to classify children into \u0026ldquo;Good consumption\u0026rdquo; (if they consumed at least one of these vitamin-A\u0026ndash;rich foods) and \u0026ldquo;No consumption\u0026rdquo; (if they consumed none of them).\u003c/p\u003e \u003cp\u003eThe predictor variables selected for this analysis were identified based on previous literature regarding determinants of child nutrition, data availability and sample size representativeness within the SLDHS. These included the region, residence, household wealth quintile, mother\u0026rsquo;s age, mother\u0026rsquo;s educational level, marital status, employment status, pregnancy status, age of child (months), child sex birth order (parity), household's exposure to mass media.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData management and data analysis\u003c/h2\u003e \u003cp\u003eAll data management steps were conducted using a statistical software of STATA 16.0 to prepare the final dataset for rigorous testing. Descriptive statistics, including frequencies and percentages, were used to summarize the socio-demographic characteristics of the study participants. Bivariable logistic regression was initially performed to assess the crude association between each predictor variable and the outcome variable, with those having a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 considered for further analysis. A multivariable logistic regression model was then employed to identify statistically significant predictors while controlling for confounding factors. The strength of association was measured using Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI), and statistical significance was declared at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Multi-collinearity among independent variables was also assessed using variance inflation factor (VIF) and a value of 10 was used as cut off.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics approvals\u003c/h3\u003e\n\u003cp\u003eAs this study involved a secondary analysis of the 2020 SLDHS, its publicly available secondary data. Informed consent was obtained from all participants during primary data collection. Formal permission to access and analyze this dataset was granted by the DHS Program.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic and economic characteristics\u003c/h2\u003e \u003cp\u003eA total of 1,086 children aged 6\u0026ndash;24 months participated in the study. The majority of mothers (74.40%) were between the ages of 20 and 34 years. Educational attainment among mothers was notably low, with 85.17% having no formal education. In terms of economic status, the majority of households (66.21%) were classified as poor, and 99.82% of mothers reported not working. The study participants were fairly evenly distributed between rural (52.30%) and urban (47.70%) settings (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics of children aged 6\u0026ndash;24 months in Somaliland, n\u0026thinsp;=\u0026thinsp;1086\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.73%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.05%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWork Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.82%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3 births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;+\u0026thinsp;births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.07%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePregnant Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.15%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;8 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026ndash;11 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u0026ndash;17 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.58%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.39%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.58%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedia Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHave exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwdal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarodijeh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSahil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.54%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTogdheer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.97%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSanaag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.73%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.30%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence and sources of Vitamin A-rich food consumption\u003c/h2\u003e \u003cp\u003eThe overall prevalence of adequate Vitamin A-rich food consumption was found to be 56.45% (n\u0026thinsp;=\u0026thinsp;613), while 43.55% (n\u0026thinsp;=\u0026thinsp;473) of children had inadequate consumption (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding specific food sources, fresh milk was by far the most consumed Vitamin A source, consumed by 48.07% of children. Consumption of other Vitamin A-rich foods was significantly lower. Only 7.73% consumed dairy products like cheese or yogurt, 7.09% consumed meat, and 7% consumed organs. Plant-based sources were also low, with only 6.63% consuming pumpkins/carrots and 6.17% consuming Vitamin A-rich fruits (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSources of Vitamin A-rich food consumption among children aged 6\u0026ndash;24 months in Somaliland, n\u0026thinsp;=\u0026thinsp;1086.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable (Food Item)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEggs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFresh milk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCheese, yogurt, milk products\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMeat\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePumpkin, carrots, squash\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFish or shellfish\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrgans\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVitamin A fruits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRegional Distribution of Vitamin A Consumption\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the spatial distribution of Vitamin A consumption prevalence across the regions of Somaliland. There is notable regional heterogeneity in dietary habits. The Sahil region exhibited the highest prevalence of Vitamin A-rich food consumption at 73.24%, followed closely by Togdheer (69.23%) and Maroodi Jeex (64.58%). Conversely, the eastern regions showed lower consumption rates, with Sanaag recording the lowest prevalence at 49.48%, followed by Sool (55.33%) and Awdal (54.35%). This geographic variation implies that factors such as regional climate, access to markets, or local pastoral practices specifically regarding milk availability may influence consumption levels.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with consumption of vitamin A-rich food\u003c/h2\u003e \u003cp\u003eBivariable and multivariable logistic regression analyses were performed to identify predictors of Vitamin A consumption (Table\u0026nbsp;3). In the multivariable analysis, wealth quintile and media exposure were found to be statistically significant predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Children from households in the middle wealth quintile (AOR\u0026thinsp;=\u0026thinsp;0.59; 95% CI: 0.38\u0026ndash;0.93) and rich wealth quintile (AOR\u0026thinsp;=\u0026thinsp;0.50; 95% CI: 0.36\u0026ndash;0.71) were less likely to consume Vitamin A-rich foods compared to those in the poor wealth quintile. Media exposure showed a strong positive association. Children of mothers who had exposure to media were 5.04 times more likely (AOR\u0026thinsp;=\u0026thinsp;5.04; 95% CI: 1.55\u0026ndash;16.43) to have good Vitamin A consumption compared to those with no exposure. Other factors, including maternal age, education level, parity, and marital status, did not show statistically significant associations with Vitamin A consumption in the multivariable model (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate and multivariate Analysis of Factors Associated with Vitamin A-Rich Food Consumption among children aged 6\u0026ndash;24 months in Somaliland, n\u0026thinsp;=\u0026thinsp;1086\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eVitamin A Consumption\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.49\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65 (0.39\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74 (0.44\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56 (0.30\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.87%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78 (0.54\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.64\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81 (0.35\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20 (0.49\u0026ndash;2.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49 (0.08\u0026ndash;3.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70 (0.11\u0026ndash;4.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.59%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52 (0.34\u0026ndash;0.79)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59 (0.38\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47 (0.35\u0026ndash;0.62)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50 (0.36\u0026ndash;0.71)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWork Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3 births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07 (0.78\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20 (0.86\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;+\u0026thinsp;births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12 (0.83\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.37 (0.96\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50 (0.25\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64 (0.31\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.09%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52 (0.22\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46 (0.19\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePregnant Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.87%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87 (0.64\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89 (0.64\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Age (\u003c/b\u003emonths)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.40 (0.91\u0026ndash;2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.48 (0.93\u0026ndash;2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.21 (0.87\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24 (0.86\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10 (0.76\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (0.73\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95 (0.74\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.77\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.938\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedia Exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.04%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.94 (0.97\u0026ndash;8.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.04 (1.55\u0026ndash;16.43)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwdal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.35%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarodijeh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.53 (0.68\u0026ndash;3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.42 (0.61\u0026ndash;3.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSahil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.76%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.30 (1.05\u0026ndash;5.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.03 (0.92\u0026ndash;4.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTogdheer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89 (0.95\u0026ndash;3.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.90 (0.94\u0026ndash;3.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04 (0.56\u0026ndash;1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20 (0.63\u0026ndash;2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSanaag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.43\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (0.53\u0026ndash;1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83 (0.65\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.85 (0.66\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e**Significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u0026dagger;Could not be estimated due to sparse data (only 2 observations in \"Yes\" category for work status)\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to the World Health Organization (WHO), people should receive vitamin A supplements two times per year (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study confirmed that 56.45% (95% CI: 53.47 59.37) of children aged 6\u0026ndash;24 months had vitamin A rich foods intake within, or in the last 24 h in Somaliland. This finding is higher than study done in rural Burundi (16%) and Rwanda (23%) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), Ghana (52%) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), and Ethiopia (13.3%-24%) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The possible reason for this variation may be due to socio-demographic variation, recent advancements in health care delivery, and accessibility of health care services. However, this finding is lower when we compared with studies done in different areas such as India (58.1%) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), Malawi (79.1%) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and Uganda (66.5%) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The possible justification for variation may be due to differences in socio-demographic and economic characteristics, study setting, and maternal healthcare characteristics.\u003c/p\u003e \u003cp\u003eIn multivariable logistic regression analysis, household wealth status, and Media exposure were statistically significant factors for vitamin A rich foods intake among children aged from 6\u0026ndash;24 months in Somaliland.\u003c/p\u003e \u003cp\u003eMothers in the middle wealth category (AOR\u0026thinsp;=\u0026thinsp;0.59; 95% CI: 0.38\u0026ndash;0.93) and those in the rich wealth category (AOR\u0026thinsp;=\u0026thinsp;0.50; 95% CI: 0.36\u0026ndash;0.71) were 41% and 50% less likely, respectively, to consume adequate vitamin A\u0026ndash;rich foods compared with mothers in the poor wealth category.\u003c/p\u003e \u003cp\u003eUnexpectedly, this study found that adequate vitamin A consumption was higher among women in the poor wealth category compared to those in the middle and rich categories. This finding is inconsistent with previous research (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). A possible explanation is that women from wealthier households, despite having economic access, may prioritize Vitamin A\u0026ndash;rich foods less than their counterparts.\u003c/p\u003e \u003cp\u003eIn the present study, media significantly affects the intake of vitamin A rich foods among children aged from 6 to 24 months in Somaliland. Those children whose mothers had exposure to media were 5.04 times more likely (AOR\u0026thinsp;=\u0026thinsp;5.04; 95% CI: 1.55\u0026ndash;16.43) to intake vitamin A rich foods than children whose mother had no exposure.\u003c/p\u003e \u003cp\u003eThis finding is in line with studies done in different parts of Ethiopia (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), Bangladesh (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), and Indonesia (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). This might be the impact of media for promoting child feeding practice and mothers\u0026rsquo; exposure to media able to feed different foods groups to their children.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitation\u003c/h2\u003e \u003cp\u003eSince the study is done through using SLDHS national datasets which the finding may have good generalizability. Conducting multivariate logistic regression model and the larger sample size proved important in maintaining the internal validity of the study by helping provide precise descriptive and analytic findings are considered as the strength of this study.\u003c/p\u003e \u003cp\u003eAs a limitation, since the data was collected retrospectively it may prone recall bias. As long as the 2020 SLDHS dataset has no observation for some variables, important variables which determine vitamin A rich foods intake among children may not be included under this study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe magnitude of Vitamin A rich foods intake among children aged 6\u0026ndash;24 months across the regions of Somaliland is insufficient at national level. Independent variables such as wealth status of mother, and Media exposure were significantly associated with vitamin A rich foods intake among children aged 6\u0026ndash;24 months. Therefore, policymakers should give due attention to the poor wealth status, and media non-exposed mothers, to improve good consumption of foods rich in vitamin A among children aged 6\u0026ndash;24 months in Somaliland.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR - Adjusted Odds Ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI - Confidence Interval\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSLDHS - Somaliland Demographic and Health Survey\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVAD - Vitamin A Deficiency\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVIF - Variance Inflation Factor\u003c/p\u003e\n\u003cp\u003eWHO - World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the Demographic and Health Surveys Program for granting them access to the dataset.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAIM: Conceptualization, Methodology, Data analysis, Investigation, Writing – Original Draft, Writing – Review \u0026amp; Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study, while not publicly available, can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDemsash AW, Chereka AA, Kassie SY, Donacho DO, Ngusie HS, Tegegne MD, et al. 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Exploring spatial variations and factors associated with childhood stunting in Ethiopia: spatial and multilevel analysis. BMC Pediatr. 2016;16(1):49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAemro M, Mesele M, Birhanu Z, Atenafu A. Dietary diversity and meal frequency practices among infant and young children aged 6\u0026ndash;23 months in Ethiopia: a secondary analysis of Ethiopian demographic and health survey 2011. J Nutr Metab. 2013;2013(1):782931.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEshete T, Kumera G, Bazezew Y, Mihretie A, Marie T. Determinants of inadequate minimum dietary diversity among children aged 6\u0026ndash;23 months in Ethiopia: secondary data analysis from Ethiopian Demographic and Health Survey 2016. Agric Food Secur. 2018;7(1):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlackstone S, Sanghvi T. A comparison of minimum dietary diversity in Bangladesh in 2011 and 2014. Matern Child Nutr. 2018;14(4):e12609.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSekartaji R, Suza DE, Fauziningtyas R, Almutairi WM, Susanti IA, Astutik E, et al. Dietary diversity and associated factors among children aged 6\u0026ndash;23 months in Indonesia. J Pediatr Nurs. 2021;56:30\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Vitamin A-rich food consumption, Geographical variation, Children, Somaliland, Nutrients","lastPublishedDoi":"10.21203/rs.3.rs-9010321/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9010321/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMicronutrient deficiencies, particularly Vitamin A deficiency (VAD), pose a significant public health challenge in developing nations, contributing to increased child morbidity and mortality. While the importance of Vitamin A for immune function and development is well-established, specific data regarding the dietary intake of this micronutrient among young children in Somaliland remains limited.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to assess the prevalence, regional disparities, and factors associated with the consumption of vitamin A-rich foods among children aged 6\u0026ndash;24 months in Somaliland.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA secondary analysis consisted of 1,086 children was conducted using data from the 2020 Somaliland Demographic and Health Survey, a nationally representative community-based cross-sectional study. The outcome variable was the consumption of vitamin A-rich foods in the 24 hours preceding the survey. Multivariable logistic regression analyses were performed to identify predictors of consumption using Adjusted Odds Ratios (AOR) with 95% Confidence Intervals (CI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe overall prevalence of vitamin A-rich food consumption was 56.45% (95% CI: 53.47\u0026ndash;59.37). Fresh milk was the most common source (48.07%), while consumption of fruits and vegetables was low. Significant regional variations were observed; the Sahil region had the highest consumption (73.24%), while the Sanaag region had the lowest (49.48%). Multivariable analysis indicated that children from middle (AOR\u0026thinsp;=\u0026thinsp;0.59; 95% CI: 0.38\u0026ndash;0.93) and rich (AOR\u0026thinsp;=\u0026thinsp;0.50; 95% CI: 0.36\u0026ndash;0.71) wealth quintiles were significantly less likely to consume vitamin A-rich foods compared to those from poor households. Conversely, maternal exposure to mass media was a strong positive predictor (AOR\u0026thinsp;=\u0026thinsp;5.04; 95% CI: 1.55\u0026ndash;16.43).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eVitamin A-rich food consumption among children in Somaliland is suboptimal and varies significantly by region. The findings reveal a paradox where higher household wealth correlates with lower consumption, while media exposure significantly improves intake.\u003c/p\u003e","manuscriptTitle":"Prevalence, regional disparities and associated factors of vitamin A-rich food consumption among children 6–24 months in Somaliland: Evidence from a National Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:06:28","doi":"10.21203/rs.3.rs-9010321/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d1c985f-2e8f-436f-b71d-342cbea960e2","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-08T21:23:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:06:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9010321","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9010321","identity":"rs-9010321","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}