Prevalence Of Stunting In Indonesia Research Articles

Analisis Pengaruh Variabel Makro Ekonomi Terhadap Prevalensi Stunting Di Indonesia

This study aims to analyze the influence of Poverty, Economic Growth Rate, Government Policy and Exclusive Breastfeeding on Stunting Prevalence in Indonesia. This study uses a panel data regression analysis method with a Random Effect Model (REM). The results of the study show that Poverty has a significant positive effect on Stunting Prevalence, and Government Policy and Exclusive Breastfeeding have a significant negative effect on Stunting Prevalence, and Economic Growth Rate has no effect on Stunting Prevalence in Indonesia.

The Effect of Animation Video-Based Education Toward Stunting Knowledge and Attitude Among Female Adolescents in Jakarta

Aims: The prevalence of stunting in Indonesia is one of the crucial problems that will have an impact on the next generation, so it needs to be prevented. Increasing stunting prevention knowledge and attitudes in adolescents related to health investment in the first 8000 days of life is important in reducing stunting rates. The aims of the study to identify the effect of investment education for the first 8000 days of life with animated videos as an effort to break the stunting cycle. Methods: This study used the Quasi Experiment method with a two-group pre-posttest design with 214 respondents divided into an intervention group and a control group with 107 people in each group. The research analysis used Wilcoxon Rank and Manova. Results: This study after being given the intervention showed that there were significant differences in the knowledge and attitude scores between the control group and the intervention group with a p-value of 0.000 (p <α 0.05). Conclusion: This study shows that providing education on health investment in the first 8000 days of life with animated videos affects increasing knowledge and attitudes of young women in preventing stunting.

Spatially Varying Regression Coefficient Model For Predicting Stunting Hotspots In Indonesia

Stunting is a significant issue, particularly in the context of Indonesia. Identifying crucial risk factors is crucial for mitigating and developing effective strategies to control stunting. A Bayesian approach was employed to develop a regression model that incorporates spatial variation, allowing risk factors to vary across different districts and cities. The aim was to obtain the most optimal regression model. The analysis revealed that the impact of immunization varies across districts and cities in Indonesia when it comes to explaining the differences in stunting prevalence. The hotspot prediction results indicate that most urban districts in Indonesia remain hotspot areas, with a stunting risk exceeding 20%. The government must ensure the effective implementation of the immunization program in order to mitigate the prevalence of stunting in Indonesia. The novelty of this research lies in the use of Bayesian approaches to spatial analysis in identifying and understanding stunting risk factors as well as the prediction of stunting hotspots in Indonesia. This approach provides in-depth insight into local variations in the prevalence of stunting and the effectiveness of health interventions, which supports more effective and targeted policy development.

Effectiveness of The Culture-Based Anti-Stunting Education Package on Family Behavioral Changes in Stunting Prevention

Stunting remains a pressing global health concern, as evidenced by the prevalence of stunting in Indonesia. The Pasuruan Regency Government continues its efforts to reduce the stunting rate. Coastal areas are characterized by a relatively high incidence of stunting, which stands at 22.8%. The urgency of this research lies in the need for a change in family behavior toward stunting prevention through education optimalization in coastal areas. Stunting prevention education within the family can be summarized into the "Anti-Stunting Education Package", consisting of education on nutritious maternal food intake starting from 1000 days before childbirth, exclusive breastfeeding, adolescent health, and access to clean water. This research aims to demonstrate the effectiveness of anti-stunting education package in changing family behavior to prevent stunting in coastal areas. This was pre-experimental study with a pretest-posttest design approach. The research is conducted in coastal areas with a sample size of 30 stunting families selected through purposive sampling. The results of the research indicate that the Anti-Stunting Education Package is highly effective in improving knowledge, attitudes, and behavioral changes among mothers in supporting stunting prevention in coastal areas. This study falls under TKT 3, which demonstrates the analytical concept and experimental functions, providing stunting education through booklets with a focus on local culture to prevent stunting in coastal areas. The outcomes of this research serve as an innovation and technological development for maritime community well-being.

Development of Robot Feature for Stunting Analysis Using Long-Short Term Memory (LSTM) Algorithm

Stunting prevalence in Indonesia persists as a significant challenge necessitating concerted efforts from all stakeholders. We developed robot for stunting analysis using deep learning algorithm. It aligns with the Sustainable Development Goal (SDG) agenda, specifically targeting SDG 3, which focuses on ensuring good health and well-being for all. Long Short-Term Memory (LSTM) is a type of Recurrent Neural Network (RNN) designed to overcome the vanishing gradient problem in traditional RNNs. In general, either LSTM can be used in analysis. This study aims to classify stunting based on age and height using LSTM. The LSTM model was trained with 50 epochs using datasets collected from the health office and robots. The evaluation results show training accuracy of 96.65% and training validation of 96.61%, with precision, recall and f1-score varying with relevance to the f1-score and support value. This research illustrates the potential for using data classification methods in stunting diagnosis. However, it is necessary to adjust parameters and increase the amount of training data to improve model performance. With good convergence at epoch 50, these results show the model's ability to classify stunting based on age and height. However, further validation and testing on larger datasets is needed to thoroughly test the reliability and generalization of the model. This research can contribute to the development of deep learning regarding robots as a means of testing stunting. This research provides initial evidence of the potential of stunting classification methods using robots. However, parameter adjustments and increasing the amount of training data need to be done to improve the overall model performance.

Raising Awareness of the Impact of Stunting on Toddler Development Through Parental Education

In 2023, the prevalence of stunting in Indonesia remains at 21.5%, showing only a marginal decrease of 0.1% from the previous year and still exceeding the WHO standard of 20%. Stunting adversely affects children, leading to impaired physical and cognitive development, increased risk of developmental disorders, and a higher likelihood of metabolic diseases in adulthood.This study utilized a multi-stage approach: data and area analysis, educational and developmental screening, and evaluation. Participants included 44 parents with their toddlers, 5 cadres, and 3 village officials. Knowledge among participants improved significantly, with 76% demonstrating enhanced understanding. Statistical analysis revealed a significant increase in knowledge post-intervention (p=0.000). Developmental assessments showed that 11% of toddlers were classified as "doubtful" and 23% as having "deviant" results. Parents of these children received education on age-appropriate stimulation, and cases were reported to local health workers. The goal is for the acquired knowledge to be widely applied, with ongoing routine screening for early detection and timely management of developmental issues.

GROWTH MONITORING TRAINING AND CHILD DEVELOPMENT FOR PRESCHOOL TEACHERS IN THE FRAMEWORK OF STUNTING OVERCOMING

The prevalence of stunting in Indonesia fell from 24.4% in 2021 to 21.6% in 2022. The stunting figure is still quite high compared to the government's target of 14% in 2024. Stunting is one of the government's priority programs, considering the impact of stunting on the quality of human resources is very large. PAUD/Kindergarten teachers academically have the potential intellectual abilities to provide input on the importance of children's growth, in addition to children's abilities or intelligence. The service activities aim to increase the capacity of PAUD/TK teachers in monitoring children's growth and development according to standards The activity method is training in monitoring the growth and development of early childhood. Activities in collaboration with partners, namely HIMPAUDI, Sunyaragi District and Sunyaragi Community Health Center, Cirebon City. Collaboration by sharing resources between study programs and partners. The measuring parameters use the pre-post knowledge and ability values ​​of participants in carrying out practical assignments to monitor growth and development in child cases. This activity is expected to increase the capacity of PAUD teachers in monitoring the growth and development of their students according to standards. This activity was carried out at the HIMPAUDI Secretariat, Cirebon City, attended by 25 PAUD teachers representing 5 (five) sub-districts in Cirebon City. As a result of this training activity, PAUD teachers understand better about anthropometric measurements, growth and development of early childhood based on the results of the pre and post test scores carried out. The teachers were very enthusiastic about participating in the training until it was finished. The outputs that have been created are training modules, activity videos, publication drafts in newspaper media and publication journals in the Community Service Journal in the process of being prepared.

Spatio-temporal modeling to identify factors associated with stunting in Indonesia using a Modified Generalized Lasso

This study investigates the factors associated with stunting prevalence in Indonesia, utilizing a generalized lasso framework with modified penalty matrices to accommodate spatio-temporal data structures. Novel approaches are introduced to construct the penalty matrices, with particular focus on defining neighborhood structures. The proposed method is applied to data from 34 Indonesian provinces, covering the years 2019 to 2023. The primary outcome is stunting prevalence, modeled against nine predictor variables: poverty, exclusive breastfeeding, low birth weight (LBW), high school completion, access to proper sanitation, unmet health service needs, Gross Domestic Product (GDP), calorie consumption, and protein consumption. A total of nine spatio-temporal models were compared, including a modified generalized lasso with three distinct penalty matrices for each two tuning selection methods and a generalized ridge regression with three penalty matrices. Results indicate that the generalized lasso model with a 3-nearest neighbor adjacency matrix outperformed the alternatives. Temporal variations were observed in the effects of exclusive breastfeeding, LBW, high school completion, and unmet health service needs. Positive associations with stunting prevalence were identified for poverty, exclusive breastfeeding, LBW, and unmet health service needs, while negative associations were found for high school completion rates, access to proper sanitation, GDP, calorie intake, and protein consumption. The strongest associations were observed in parts of Sumatra, Sulawesi, and Jakarta. These findings suggest that government interventions aimed at improving education, healthcare access, and poverty reduction may help alleviate stunting in Indonesia, particularly in regions with the greatest need.

Factors of Child Growth Failure Based on the Composite Index of Anthropometric Failure in West Sulawesi Province

Background: The composite index of anthropometric failure (CIAF) provides a comprehensive measure of growth failure through various child anthropometric indicators. In regions with a high prevalence of stunting, several factors may contribute to the occurrence of growth failure in children under five years. Objectives: This study aims to analyze the factors influencing the incidence of child growth failure based on the CIAF in a province with high stunting prevalence in Indonesia. Methods: The cross-sectional study used the 2022 Indonesian Nutrition Status Survey (SSGI) data. The sample comprised children aged 0-23 months from West Sulawesi Province, totaling 1,573 children. The number of samples analyzed was 1,327 children, excluding incomplete data and outliers that were values outside a certain range and treated as missing values based on the World Health Organization (WHO). Multivariate analysis was conducted using logistic regression with a complex sample facility. Results: This study found that 24.9% of children experienced growth failure based on the CIAF. Factors associated with the incidence of growth failure based on the CIAF were older age between 12-23 months (OR=4.5; CI=2.36-8.43; p=0.000), birth weight less than 2,500 g (OR=6.85; CI=3.85-12.21; p=0.000), boys (OR=1.56; CI=1.13-2.15; p=0.000), incomplete immunization status (OR=1.8; CI=1.31-2.77; p=0.001), and poor economic status in quintile 1 (OR=2.1; CI=1.08-3.99; p=0.028). Conclusions: The risk factors for child growth failure based on the CIAF included older age, male sex, low birth weight, incomplete immunization status, and low economic status.

Parenting Self-Efficacy, Father Involvement, dan Stunting

This study aims to analyze the influence of parenting self-efficacy on father involvement in stunting prevention. The research is motivated by the high prevalence of stunting in Indonesia, despite recent declines. Further research is needed to explore the factors that contribute to reducing stunting, particularly the role of families in providing instrumental and emotional support. While co-parenting, where both fathers and mothers share responsibilities in raising and educating children, is ideal, the reality shows that father involvement in early childhood care remains very limited. This study employs a quantitative correlational method with a sample of 220 fathers in Semarang City, selected using convenience sampling. The study uses two measurement tools: the Self-Efficacy for Parenting Task Index (SEPTI) by Coleman & Karraker, adapted into Indonesian with 36 items. The results of a simple linear regression analysis indicate that parenting self-efficacy has a positive impact on father involvement in stunting prevention. Parenting self-efficacy plays a crucial role in stunting prevention and improving child health. The study also demonstrates that parenting self-efficacy increases father involvement in caregiving, although social and cultural differences may influence this relationship. A lack of father involvement not only increases the risk of stunting but also places a greater burden on mothers, which can negatively impact child well-being.

Penilaian Status Gizi, Edukasi dan Pengenalan Inovasi Pangan sebagai Upaya Pencegahan Stunting pada Ibu Hamil di Desa Rejosari Kabupaten Demak

<p><em>Stunting is malnutrition that occurs gradually and is prolonged. In general, according to Riskesdas (2018), the prevalence of stunting in Indonesia is 30.8%, and in Demak 26.1%. Meanwhile in Rejosari Village. Based on data from local midwives, there are 15 stunted children in Karangawen, Demak. The purpose of dedication is as a preventive measure so that the incidence of stunting under five in Rejosari Village, Demak Regency does not increase. The implementation began with a health stand, and interactive discussions, and ended with a cooking demonstration for pregnant women. The activity began with an anthropometry stand, continued with education on the importance of the role of 1000 HPK, questions, and answers, and ended with a demonstration on making Moringa Chicken Tofu Balls. The results of the "Si Penting" program show that there are still pregnant women who have the potential to give birth to LBW children, as evidenced by a BMI before pregnancy of less than 18 kg/m2 and a LILA of less than 23.5 cm. Apart from that, food education and innovation activities ran smoothly, participants asked many questions and had lively discussions.</em></p>

Community empowerment in handling stunting through technology supporting food security and health

The prevalence of stunting in Indonesia, particularly in Gunung Kidul district, remains high at 23.5% in 2022. The Kosabangsa approach, integrated into the Village Development Plan (RPJM Desa) for 2020-2026, serves as a primary strategy for community empowerment, especially in agriculture and livestock. The methods employed include socialization, training, and mentoring, with a focus on functional food processing and home-based food processing. The results of this activity indicate an increase in the knowledge of PKK groups regarding infant and young child feeding practices and nutritional aspects, as well as a strengthening of their capacity to market local food products. This community service concludes that the integration of technology and a holistic approach to food security plays a crucial role in addressing stunting. Consequently, this community service not only focuses on short-term solutions to stunting but also aims to create a sustainable impact through community empowerment and overall food security enhancement.

Biofortified biscuits with indigenous plants: An innovative approach to prevent stunting in early childhood

Background: Increasing human living standards is directly proportional to demands for the quality of public health. Prevalence of stunting in Indonesia is ranked fifth in the world with a figure reaching 37.2%. Therefore, stunting is 1 of 5 health problems that the government is focusing on solving. This growth and development disorder is characterized by the body size of the baby/toddler below standard as well as delays in cognitive and psychomotor abilities. Stunting in children is the impact of nutritional deficiencies during pregnancy and the first 1000 days of life. Important micronutrients that have the potential to reduce the risk of stunting are iron and folic acid. The majority of pregnant and breastfeeding mothers with high school education or below tend not to pay attention to their intake of these 2 micronutrients, so deficiencies often occur. Pregnancy/breastfeeding supplements on the market are also expensive. Facts show that cassava leaves (Manihot esculenta) and winged bean seeds (Psophocarpus tetragonolobus) are local agricultural resources that are rich in iron and folic acid. The production of biscuits to prevent stunting from these 2 vegetable sources is certainly very promising and worth developing. The aim of writing this scientific work is to determine the right biscuit formulation so that it is suitable to be used as a biscuit to prevent stunting for the wider community. Methods: Making biscuits needs to be preceded by making cassava leaf paste and winged bean seed flour and then determining various formulations. Variations in winged bean seed flour formulation: cassava leaf paste, namely F1 (20:10), F2 (25:15), F3 (30:10). Biscuits are made using the cream method, namely mixing sugar, skim milk, margarine and egg yolks until homogeneous then adding wheat flour, winged bean seed flour, cassava leaf paste, water and leavening agent. The dough is rolled, molded and baked at 170oC for 30 minutes. Finding: after carrying out organoleptic tests to measure product quality and determine the best formulation, it turned out that F2 was the biscuit formulation that the panelists liked most. Conclusion : The development of stunting prevention biscuits from cassava leaves and winged bean seeds is a potential solution. The next step is to disseminate this product as part of a stunting prevention strategy in the community. Novelty/Originality of this Study: The use of local agricultural resources, specifically winged bean seeds and cassava leaves, to develop a nutritious and affordable biscuit aimed at preventing stunting is an innovative approach that not only addresses the chronic malnutrition problem but also supports local economies by utilizing underutilized crops.

MODELING STUNTING PREVALENCE IN INDONESIA USING SPLINE TRUNCATED SEMIPARAMETRIC REGRESSION

Semiparametric regression combines parametric and nonparametric regression approaches. It is employed when the relationship pattern of the response variable is known with some predictors, while for other predictors, the relationship pattern is uncertain. The parametric regression component in this study is linear regression, while the nonparametric component utilizes a spline truncated estimator, resulting in a semiparametric spline truncated regression model. The case study focuses on the prevalence of stunting across 34 provinces in Indonesia in 2022, revealing a relatively high prevalence of 21.60%. The research aims to determine the optimal number of knots, the best model, and factors influencing stunting prevalence in Indonesia. The findings indicate that the optimal three-knot model with a GCV of 9.30 yields an RMSE of 1.70 and R2 of 92.71%. Significance tests for simultaneous and partial parameters reveal that all predictor variables significantly influence stunting prevalence.

Sistem Deteksi Stunting Sebagai Program Intervensi Gizi di Kelurahan Teluk Pucung

The prevalence of stunting in Indonesia is currently at 21.6%, which is down from the initial value of 24.4% in 2022. There is a failure in the process of improving nutritional status that causes babies and toddlers to indicate stunting. Stunting is a condition where children experience growth disorders, so that their height is not in accordance with their age as a result of chronic nutritional problems, namely lack of nutritional intake for a long time. Data shows that stunting in children can have a long-term impact on their health and development, creating serious challenges in achieving the full potential of future generations. Insufficient intake of adequate nutrition, unequal access to quality health services, and supported by healthy eating practices and lack of a supportive environment are the main factors that trigger high stunting rates, demanding integrated interventions to address the root of the problem. Bhayangkara University of Greater Jakarta as a private sector that should collaborate in efforts to improve the nutritional status of the Indonesian people carried out real lecture work (KKN) in one of the villages in Bekasi City, namely Teluk Pucung village. A holistic approach that considers social, economic, and educational factors in efforts to improve nutritional status is essential. Intervention programs should not only focus on providing nutritious food, but also on family economic empowerment, increasing mothers' knowledge about nutrition and child health and improving access to quality health services.

Comparative Analysis of Machine Learning Algorithm Performance in Predicting Stunting in Toddlers

Stunting is a condition where the growth of children and toddlers is stunted, which causes children to be shorter than they should be. In the long term, stunting can reduce reproductive health, study concentration, and work productivity, thereby causing significant state losses. The prevalence of stunting in Indonesia, which is still above 20 percent, shows that there are still chronic nutritional problems among toddlers. To prevent this from happening, identification as early as possible can be done using machine learning for predictions. The aim of this research is to conduct a comparative analysis of the performance of machine learning algorithms for predicting stunting in toddlers. Random Forest, K-Nearest Neighbors, and Extreme Gradient Boosting are the algorithms that are compared for their performance. The performance of each algorithm is measured using evaluation matrices such as accuracy, precision, recall, and f1-score. The research method starts with data collection, data preprocessing, data splitting, application of machine learning algorithms, evaluation of algorithm performance, and comparison of results. The performance evaluation matrix measurement results show that Random Forest has an accuracy of 99.95%, precision of 99.89%, recall of 99.94%, and f1-score of 99.91%. K-Nearest Neighbors has an accuracy of 99.93%, precision of 99.87%, recall of 99.88%, and f1-score of 99.88%. Meanwhile, Extreme Gradient Boosting has an accuracy of 99.36%, precision of 98.86%, recall of 98.95%, and f1-score of 98.90%. From the results of all performance evaluation matrices, it can be concluded that the random forest algorithm is the best algorithm for predicting stunting in toddlers.

Analysis of special rice farming income in supporting the reduction of stunting in Riau province

Abstract Rice is a food commodity and is the main source of carbohydrates for the majority of the world’s population. Currently the function of rice has shifted from food with a special function, especially for health. Stunting is still a serious health problem facing Indonesia. Based on data from the National Nutrition Status Survey (SSGI) for 2022, the prevalence of stunting in Indonesia is 21.6%. This number decreased compared to the previous year, which was 24.4%. New superior varieties of special rice have special characteristics, such as Inpari IR Nutri Zinc and brown rice (Pamelen) which are very beneficial for health. This research was conducted in June - December 2021, located in Sungai Tengah village, Sabah Auh District, Siak Regency. The materials used are special rice superior varieties (Pamelen, Tarabas, Baroma, Inpari Nutri Zinc, Inpari 24). This study aims to determine the income of rice farming, especially in an effort to support the reduction of stunting in Riau Province. The results showed that Pamelen and Inpari Nutri zinc varieties produced 4,452 kg/ha GKG and 4,686 kg/ha GKG higher than the average production of other rice. The BCR value of all varieties is more than 1, this explains that all varieties developed according to economic analysis are feasible and profitable. the Inpari IR Nutri Zinc variety of rice is suitable for cultivation in Siak Regency, Riau Province.

Tingkat Pengetahuan dan Sikap Ibu dengan Praktek Pemberian Makanan dalam Pencegahan dan Penatalaksanaan Anak Stunting

Stunting or stunted growth in children is still a global problem. The prevalence of stunting in Indonesia in children under 5 years of age is 22.3%. Meanwhile, in West Sumatra, the prevalence of stunting is higher than the national prevalence, namely 25.6% in 2022. Solok Regency with the highest incidence of 40.1% in 2021. This research aims to look at the relationship between knowledge, attitudes, and feeding practices in the management of stunted children. This research uses a quantitative approach with a Case-Control design. The research was conducted in Solok Regency, specifically the working area of the Sungai Lasi Community Health Center. The population of this study was mothers who had stunted children under 5 years of age (168 people), while the sample included mothers who had stunted children under 2 years of age (17 people). The sample ratio was 1:2 (stunting (17 people) and not stunting (34 people) with a total of 51 people. Sampling was done using purposive sampling. Data analysis used univariate analysis, and bivariate analysis using the Chi-square test. The results of the bivariate analysis obtained the mother's level of knowledge (p= 0.013) and the mother's attitude (p=0.035). In conclusion, there is a relationship between a mother's level of knowledge and attitude and feeding practices in managing stunting. Efforts are needed to increase mothers' knowledge and attitudes in preventing and managing stunting.

Modeling the Stunting Prevalence Rate in Indonesia Using Multi-Predictor Truncated Spline Nonparametric Regression

Introduction/Main Objectives: Stunting is the impaired growth and development that children experience from poor nutrition, repeated infection, and inadequate psychosocial stimulation. Background Problems: Based on data from the National Nutrition Status Survey (SSGI) in 2022, the prevalence of stunting in Indonesia was 21.6%, which is still above the WHO standard of below 20%. Novelty: This study was conducted with the aim of analysing the factors that influence the stunting prevalence rate in Indonesia using multi-predictor truncated spline nonparametric regression. Research Methods: The research data is secondary data taken from Health Statistics 2022 with response variables in the form of stunting prevalence. Finding Result: Based on the analysis, the best model to model the stunting prevalence rate is a multi-predictor truncated spline with three knots. In addition, it was found that four predictor variables which are the percentage of infants under 6 months old receiving exclusive breastfeeding, the average age of a mother's first pregnancy, the percentage of married women aged 15-49 using contraception, and the percentage of mothers who gave birth to a live child in the past two years and initiated early breastfeeding had a significant effect simultaneously and partially on the stunting prevalence rate in Indonesia.

Stunting Prevalence Modeling Using Nonparametric Regression of Quadratic Splines

The nonparametric regression approach is used when the shape of the regression curve between the response variable and the predictor variable is assumed to be of unknown shape. The advantages of nonparametric regression have high flexibility. A nonparametric regression approach that is often used is truncated spline which has an excellent ability to handle data whose behavior changes at certain sub-sub intervals. The purpose of this study is to obtain the best model of multivariable nonparametric regression with linear and quadratic truncated spline approaches using the Generalized Cross Validation (GCV) and Unbiased Risk (UBR) methods and to find out the factors that influence the prevalence of stunting in Indonesia in 2021. The data used were the prevalence of stunting as a response variable and the predictor variable used was the percentage of infants receiving exclusive breastfeeding for 6 months, the percentage of households that have proper sanitation, the percentage of toddlers who get Early Initiation of Breastfeeding (IMD), the percentage of poor people, and the percentage of pregnant women at risk of SEZ. The results showed that the best quadratic truncated spline nonparametric regression model in modeling stunting prevalence was quadraic truncated spline using the GCV method with three knot points. This model has a minimum GCV value of 7.29 with an MSE value of 1.82 and a R2 value of 94.07%.