RESUMEN
BACKGROUND: Undernutrition, which includes stunting, wasting, and underweight, is a global problem, especially among children of low- and middle-income countries. To our knowledge, this study is first of its type from Afghanistan. Its main objectives were to estimate the prevalence and associated risk factors of stunting, wasting/thinness, and underweight among urban primary school children in Kandahar city of Afghanistan. METHODS: This school-based cross-sectional study was conducted among 1205 primary school children aged 6-12 years during a period of six months (October 2022-March 2023). Anthropometric measurements and other data were collected from all the participants. Data were analyzed by using descriptive statistics, Chi square test (using crude odds ratio or COR), and multivariate logistic regression (using adjusted odds ratio or AOR). RESULTS: Among the 1205 enrolled government school students, 47.4%, 19.5%, and 25.6% had stunting, wasting/thinness, and underweight, respectively. Statistically significant factors associated with stunting were age group 6-9 years (AOR 1.3, 95% CI 1.1-1.7), being girl (AOR 2.3, 95% CI 1.8-3.0), poverty (AOR 2.2, 95% CI 1.5-3.2), large family (AOR 3.0, 95% CI 2.4-3.9), illiterate mother (AOR 1.6, 95% CI 1.0-2.6), jobless head of the family (AOR 3.3, 95% CI 2.3-4.8), and skipping breakfasts (AOR 1.7, 95% CI 1.2-2.3). Main factor associated with wasting/thinness were age group 6-9 years (AOR 30.5, 95% CI 11.8-78.7), skipping breakfasts (AOR 22.9, 95% CI 13.9-37.8), and history of sickness during the past two weeks (AOR 17.0, 95% CI 6.6-43.8). Also, main factors associated with underweight were age group 6-9 years (AOR 2.6, 95% CI 1.6-4.1), skipping breakfasts (AOR 2.6, 95% CI 1.8-3.6), and poor sanitation (AOR 1.9, 95% CI 1.1-3.2). CONCLUSIONS: Stunting, wasting/thinness, and underweight are highly prevalent among primary school children (both girls and boys) in Kandahar city. It is recommended that local government (Afghanistan Ministry of Education and Ministry of Public Health) with the help of international organizations and donor agencies should implement comprehensive school-based feeding programs especially for girls. Health and nutrition education programs should be conducted with emphasis on nutrition of children aged 6-9 years as well as importance of healthy breakfast and good sanitation.
Asunto(s)
Trastornos del Crecimiento , Delgadez , Humanos , Estudios Transversales , Femenino , Masculino , Niño , Afganistán/epidemiología , Delgadez/epidemiología , Factores de Riesgo , Prevalencia , Trastornos del Crecimiento/epidemiología , Instituciones Académicas , Síndrome Debilitante/epidemiologíaRESUMEN
This study introduces the Bayesian adaptive exponentially weighted moving average (AEWMA) control chart within the framework of measurement error, examining two separate loss functions: the squared error loss function and the linex loss function. We conduct an analysis of the posterior and posterior predictive distributions utilizing a conjugate prior. In the presence of measurement error (ME), we employ a linear covariate model to assess the control chart's effectiveness. Additionally, we explore the impacts of measurement error by investigating multiple measurements and a method involving linearly increasing variance. We conduct a Monte Carlo simulation study to assess the control chart's performance under ME, examining its run length profile. Subsequently, we offer a specific numerical instance related to the hard-bake process in semiconductor manufacturing, serving to verify the functionality and practical application of the suggested Bayesian AEWMA control chart when confronted with ME.
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In this study, we introduce an Adaptive Exponentially Weighted Moving based Coefficient of Variation (AEWMCV) control chart, designed to address situations where the process mean fluctuates over time and the standard deviation of the process changes linearly with the process mean. To enhance the efficiency and effectiveness of the control chart, we integrate the ranked set sampling method and its modified schemes, such as Simple Random Sampling, Quartile RSS, Median RSS, and Extreme RSS. The performance of the proposed AEWMCV control chart and the studied CV control charts are evaluated using the Average Run Length and Standard Deviation of Run Length metrics. Our findings reveal that the proposed control chart outperforms the existing CV control charts, especially in detecting slight to moderate changes in the process CV. To illustrate the practical applicability of the suggested control chart, we present an example demonstrating its use on a real dataset. The results highlight the superior performance of the AEWMCV control chart in accurately detecting and responding to changes in the process CV. In conclusion, our study introduces an innovative AEWMCV control chart that combines ranked set sampling and its modified schemes to enhance performance in scenarios with fluctuating process means and changing standard deviations. The proposed control chart proves to be more effective in detecting subtle variations in the process CV compared to traditional CV control charts. This research provides a valuable contribution to the field of control chart methodology, especially when dealing with challenging or costly data collection scenarios.
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The extended exponential weighted moving average (EEWMA) statistic is a memory type statistic that uses past observations along with the current information for the estimation of a population parameter to improve the efficiency of the estimators. This study utilized the EEWMA statistic to estimate the population mean with a suitable auxiliary variable. The ratio and product estimators are proposed for the surveys that are time-based by using current information along with that information. The approximate mean square errors are computed for the proposed memory type estimators and mathematical comparison is discussed to demonstrate the efficiency of the estimator. The simulation study was carried out to evaluate the performance of the proposed memory type estimators. It can be seen from the results that the efficiency of the estimator enhances by utilizing the current sample as well as past information. A real-life example is presented to illustrate the usage of proposed estimators.