Fifi Retiaty

Background: Malnutrition and micronutrient deficiencies remain significant public health burdens among Indonesian children under five years of age. This study assessed the relationship between growth indicators and micronutrient status of children aged 0–59 months. Methods: A cross-sectional design was performed, utilizing the 2018 Indonesian Basic Health Research (Riskesdas) data and biological specimens, including 550 samples from children aged between 0 and 59 months old. The Riskesdas data used in this study were demographic characteristics, anthropometric measurements, and nutritional status. The biological samples were used to measure micronutrients (iron, zinc, calcium, vitamin A (VA), and vitamin D (VD). Results: Overall, 23.1% of children were stunted, and 10.5% were wasted. This study also revealed that the prevalence of micronutrient deficiency was 34.2%, 38.7%, 8.2%, 7.8%, and 0.4% for ferritin, zinc, calcium, VA, and VD, respectively. Moreover, wasting was significantly higher in girls (13.5%) than in boys (8.2%, p = 0.044). Stunted children had significantly lower ferritin values, while wasted children had lower VA concentrations. In contrast, VD was lower in overweight children. Lastly, this study found that height for age Z-scores (HAZ score) and Body Mass Index (BMI) for age Z-scores (BAZ score) correlated positively with ferritin, zinc, and calcium levels. Conclusions: Stunting, wasting, and multiple micronutrient deficiencies remain prevalent among Indonesian children under five years of age. Strengthening nutrition interventions, in particular for iron, zinc, VA, and VD, is essential to improve child growth and health outcomes in this population.

Background: Obesity, characterized by excess body fat, has been recognized as one of the main global health problems of the current times. This article, based on the data from the Cohort study of risk factors for non-communicable diseases in Indonesia (FRPTM), aims to analyze the food consumption patterns and their association with the risk of obesity and related non-communicable diseases (NCDs) in the Indonesian population. Methods: The article presents data collected from 867 respondents aged 25 years and above observed for 5 years: 2011, 2013, 2015, 2017 and 2019. It includes sociodemographic characteristics, consumption (1 × 24-h recall), anthropometry, and biomedical data (lipid profile, blood glucose, blood pressure). Results: The study identified cereals as the food group consumed in the largest amount and the largest contributor to energy, protein, carbohydrates and fiber intake. The fats and oils group exceeded the recommended intake, while vegetable and fruit consumption, and consequently the fiber intake, were far below the recommendations. The energy and macronutrient intake, and the percentage of respondents with excessive intake levels, were consequently increasing during the studied years. The consumption patterns were associated with the incidence of obesity, which increased from 43.9% in 2011 to 69.9% (central obesity) and 67.9% (BMI-based obesity) in 2019. Conclusions: The dynamics of the consumption patterns clearly impacted the obesity prevalence. At the same time, the NCDs biomarkers measured remained relatively stable despite increasing obesity and macronutrient intake over the study period. The study provides important insights into diet-related risks for obesity in Indonesia, with a potential to inform public health policies and relevant intervention strategies.

Indonesia needs to lower its high infectious disease rate. This requires reliable data and following their temporal changes across provinces. We investigated the benefits of surveying the epidemiological situation with the imax biclustering algorithm using secondary data from a recent national scale survey of main infectious diseases from the National Basic Health Research (Riskesdas) covering 34 provinces in Indonesia. Hierarchical and k-means clustering can only handle one data source, but BCBimax biclustering can cluster rows and columns in a data matrix. Several experiments determined the best row and column threshold values, which is crucial for a useful result. The percentages of Indonesia’s seven most common infectious diseases (ARI, pneumonia, diarrhoea, tuberculosis (TB), hepatitis, malaria, and filariasis) were ordered by province to form groups without considering proximity because clusters are usually far apart. ARI, pneumonia, and diarrhoea were divided into toddler and adult infections, making 10 target diseases instead of seven. The set of biclusters formed based on the presence and level of these diseases included 7 diseases with moderate to high disease levels, 5 diseases (formed by 2 clusters), 3 diseases, 2 diseases, and a final order that only included adult diarrhoea. In 6 of 8 clusters, diarrhea was the most prevalent infectious disease in Indonesia, making its eradication a priority. Direct person-to-person infections like ARI, pneumonia, TB, and diarrhoea were found in 4-6 of 8 clusters. These diseases are more common and spread faster than vector-borne diseases like malaria and filariasis, making them more important.