Predicting the short and long term effects of food price inflation, armed conflicts, and climate variability on global acute malnutrition in Somalia.

BACKGROUND: Malnutrition poses a substantial challenge in Somalia, impacting approximately 1.8 million children. This critical issue is exacerbated by a multifaceted interplay of factors. Consequently, this study seeks to examine the long-term and short-term effects of armed conflicts, food price inflation, and climate variability on global acute malnutrition in Somalia. METHODS: The study utilized secondary data spanning from January 2015 to December 2022, sourced from relevant databases. Two distinct analytical approaches were employed to comprehensively investigate the dynamics of global acute malnutrition in Somalia. Firstly, dynamic autoregressive distributed lag (ARDL) simulations were applied, allowing for a nuanced understanding of the short and long-term effects of armed conflicts, food price inflation, and climate variability on malnutrition. Additionally, the study employed kernel-based regularized least squares, a sophisticated statistical technique, to further enhance the robustness of the findings. The analysis was conducted using STATA version 17. RESULTS: In the short run, armed conflicts and food price inflation exhibit positive associations with global acute malnutrition, particularly in conflict-prone areas and during inflationary periods. Moreover, climatic variables, specifically temperature and rainfall, demonstrate positive associations. It is important to note that temperature lacks a statistically significant relationship with global acute malnutrition in the short run. In the long run, armed conflicts and food price inflation maintain persistent impacts on global acute malnutrition, as confirmed by the dynamic ARDL simulations model. Furthermore, both temperature and rainfall continue to show positive associations with global acute malnutrition, but it is worth noting that temperature still exhibits a non-significant relationship. The results from kernel-based regularized least squares were consistent, further enhancing the robustness of the findings. CONCLUSIONS: Increased armed conflicts, food price inflation, temperature, and rainfall were associated with increased global acute malnutrition. Strategies such as stabilizing conflict-prone regions, diplomatic interventions, and peace-building initiatives are crucial, along with measures to control food price inflation. Implementing climate adaptation strategies is vital to counter temperature changes and fluctuating rainfall patterns, emphasizing the need for resilience-building. Policymakers and humanitarian organizations can leverage these insights to design targeted interventions, focusing on conflict resolution, food security, and climate resilience to enhance Somalia's overall nutritional well-being.

Prevalence of anemia and associated factors among pregnant women at Hargeisa Group Hospital, Somaliland.

BACKGROUND: Anemia remains a major global public health issue, affecting around 24.8% of the world's population in both developing and developed countries. Pregnant women in developing countries are particularly susceptible, with 38.2% affected worldwide. Anemia is also a major contributor to maternal mortality, with 510,000 maternal deaths globally, of which 20% occur in developing countries and are related to anemia. Iron deficiency anemia is the most prevalent form, impacting 1.3 to 2.2 billion individuals, with 50% being women of reproductive age. AIM: This study aimed to assess the prevalence and associated factors of anemia in pregnant women attending antenatal care (ANC) at Hargeisa Group Hospital (HGH), Somaliland. METHODS: A cross-sectional study included 360 pregnant women, who sought ANC at HGH from July 15 to August 6, 2023. The study subjects were selected using systematic random sampling. Data were collected through structured questionnaires and participants' current medical charts, including hemoglobin levels. Data analysis was performed using SPSS software (version 20). RESULTS: The study revealed an overall prevalence of anemia among pregnant women at 50.6% (95% CI: 45.40 - 55.72%). Anemia severity was categorized as mild (33.0%), moderate (54.9%), and severe (12.1%). Factors statistically associated with anemia included gestational age in the third trimester (AOR = 3.248, 95% CI: 1.491-7.074), lack of ANC visits (AOR = 6.828, 95% CI: 1.966-23.721), and absence of iron supplementation (AOR = 29.588, 95% CI: 2.922-299.713). Notably, a higher consumption of meat per week was associated with a reduced risk of anemia (AOR = 0.198, 95% CI: 0.104-0.379). CONCLUSION: The study underscores the severity of anemia in pregnant women within the range considered as severe public health problem by WHO. It is crucial to emphasize effective prenatal care, improve dietary practices, and promote the provision of iron supplements. Enhanced maternal education on Anemia during ANC visits has the potential to reduce Anemia prevalence and mitigate adverse maternal and neonatal outcomes.

Prevalence of Stunting and Its Associated Factors Among Children Residing in Internally Displaced Persons (IDP) Camps in Hargeisa, Somaliland: A Community-Based Cross-Sectional Study.

Background: Stunting, a consequence of prolonged malnutrition, remains a critical global health issue affecting 165 million children under the age of five, with 10.6 million associated deaths. Its stunting prevalence is particularly pronounced in developing nations, notably Sub-Saharan Africa. Chronic protein-energy malnutrition, identified as a major cause of morbidity and mortality in displaced settings, underscores the urgency of understanding its impact in such contexts. Objective: This study aimed to assess the prevalence and associated factors of stunting among children aged 12-59 months and residing in IDP camps in Hargeisa, Somaliland. Methods: A community-based cross-sectional study was conducted in Hargeisa from May 5 to July 30, 2022, utilizing systematic random sampling, online mobile surveys, and caregiver interviews with anthropometric measurements. The SPSS version 25 was utilized in handled data entry, processing and analysis. Multivariable logistic regression, with p < 0.05 significance, included variables from bivariate analysis (p < 0.2). Stunting assessment utilized WHO AnthroPlus software, categorizing HAZ scores < -2.0 SD. Results: The prevalence of stunting among children living in IDP camps was found to be 21.1% [95% CI: 17.0-24.91%]. Vaccination status (adjusted odds ratio [aOR] = 0.19, 95% CI: 0.09-0.38), deworming practice (aOR = 6.5, 95% CI: 2.91-14.52), place of delivery (aOR = 0.14, 95% CI: 0.07-0.30), measles experience in the last year (aOR = 0.12, 95% CI: 0.04-0.34), ANC visits (aOR = 0.33, 95% CI: 0.14-0.81), and maternal insufficient extra food intake (aOR = 2.15, 95% CI: 1.11-4.15) were significantly associated with stunting. Conclusion: The observed stunting prevalence in IDP camps (21.1%) was substantial, highlighting the need for targeted interventions. Future efforts should aim to reduce stunting from the current rate to an estimated 5-10%, emphasizing comprehensive measures such as deworming, maternal nutrition, postnatal care improvement, robust immunization, and promoting healthcare facility deliveries.

Prevalence and factors associated with immunization coverage among children under five years in Mohamed Mooge health center, Hargeisa, Somaliland: a cross-sectional study.

BACKGROUND: Routine immunization contributes greatly to reduction in mortality from vaccine preventable diseases among children. The Somaliland Demographic and Health survey, 2020 revealed that only 13.7% of children in Marodijeh (Hargeisa) region had received all recommended vaccines, which is far below the World Health Organization (WHO) target of 80%. We therefore, assessed factors associated with immunization coverage among children under five years at Mohamed Mooge Health Center in Hargeisa, Somaliland. METHODS: Institutional based cross-sectional study was conducted on 174 systematically sampled, consented mothers that visited Mohamed Mooge Health Center for antenatal care during December 2022 to May 2023. Data was collected using a structured questionnaire. Data was analysed using SPSS and the relationship between dependent and independent variables was checked chi-square test at p ≤ 0.05. Finally, candidate variables were tested by using multivariate logistic regression in order to control potential confounders and the result was presented using AOR and 95% confidence interval. Model fitness was checked using Hosmer-Lemeshaw goodness of fit test with P > 0.05 for fitness. Multicollinearity between variables was checked using correlation coefficients at 0.80 or higher.  RESULT: Among 174 study participants, the prevalence of overall vaccine completion in this study was 55.3%. Women who had being aware about childhood immunization on BCG vaccination (AOR = 3.887; 95% CI: 1.275, 6.844), pentavalent (AOR = 11.385; 95% CI: 5.424-14.464), and measles (AOR = 3.074; 95% CI: 1.822-6.130) had higher odds of having immunized their children. Mothers who had employment had higher odds of having their children immunized against measles (AOR = 4.069; 95% CI: 1.822-6.130) compared to those who had not. CONCLUSIONS: Full immunization coverage was lower than the target set by the World Health Organization in this study area. The current study revealed that, the mother's awareness of childhood vaccinations on BCG, pentavalent, measles and employment status of mothers were positively associated with immunization coverage. To promote vaccination coverage, the government should implement a national awareness campaign on childhood immunization and increase the number of outreach services.

Prevalence and factors associated with ever had road traffic accidents among drivers in Hargeisa city, Somaliland, 2022.

Road traffic accidents (RTAs) are a major cause of morbidity in Somaliland. This study aimed to determine the prevalence and factors associated with traffic-related incidents in Hargeisa city. A cross-sectional study was conducted between January and March 2022, utilizing a mixed approach involving quantitative and qualitative research approaches. Key informant interviews were conducted with 15 government officials, and structured questionnaires were administered to 387 drivers. Cluster sampling and purposive sampling were employed to select drivers and government officials, respectively. Data collection was performed using the Kobo Collect application, followed by cleaning and analysis using IBM SPSS version 25. Descriptive statistics, binary logistic regression, and chi-square tests were utilized for data analysis. The findings revealed an increasing trend of RTAs in Somaliland over the past 11 years (2011-2021). Moreover, the prevalence of RTAs in the past two years alone was determined to be 28.17% (CI: 23.67, 32.63). Factors significantly associated with RTAs in the research area included the type of vehicle, particularly Minibus (AOR = 3.249, CI: 1.022, 10.322) and Vitz (AOR = 2.325, CI: 1.092, 5.494), encountering aggressive behavior from other drivers (AOR = 1.790, CI: 1.013, 3.162), vehicles less than 4 years (AOR = 0.446, CI: 0.258, 0.771), traffic law violations (AOR = 2.726, CI: 1.296, 5.735), and the presence of traffic campaigns (AOR = 0.465, CI: 0.236, 0.917). The study recommends increasing awareness of RTAs among drivers and pedestrians, regular vehicle maintenance checks, enforcement of traffic laws, and increased police presence in road management to reduce fatalities associated with RTAs.

Evaluation of prediction models for the malaria incidence in Marodijeh Region, Somaliland.

Malaria is a major public health concern in tropics and subtropics. Accurate malaria prediction is critical for reporting ongoing incidences of infection and its control. Hence, the purpose of this investigation was to evaluate the performances of different models of predicting malaria incidence in Marodijeh region, Somaliland. The study used monthly historical data from January 2011 to December 2020. Five deterministic and stochastic models, i.e. Seasonal Autoregressive Moving Average (SARIMA), Holt-Winters' Exponential Smoothing, Harmonic Model, Seasonal and Trend Decomposition using Loess (STL) and Artificial Neural Networks (ANN), were fitted to the malaria incidence data. The study employed Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Scaled Error (MASE) to measure the accuracy of each model. The results indicated that the artificial neural network (ANN) model outperformed other models in terms of the lowest values of RMSE (39.4044), MAE (29.1615), MAPE (31.3611) and MASE (0.6618). The study also incorporated three meteorological variables (Humidity, Rainfall and Temperature) into the ANN model. The incorporation of these variables into the model enhanced the prediction of malaria incidence in terms of achieving better prediction accuracy measures (RMSE = 8.6565, MAE = 6.1029, MAPE = 7.4526 and MASE = 0.1385). The 2-year generated forecasts based on the ANN model implied a significant increasing trend. The study recommends the ANN model for forecasting malaria cases and for taking the steps to reduce malaria incidence during the times of year when high incidence is reported in the Marodijeh region.