Micronutrients and Nutrition Status of School-Aged Children in Indonesia.

Micronutrient deficiencies (MNDs) in school-aged children are still a major health problem in Indonesia. This study was designed to examine the status of micronutrients and their relationship to the nutritional status of children aged 5-12 years since an up-to-date database on the micronutrient status of children aged 5-12 years is needed. Data from the 2018 Indonesian Basic Health Research (Riskesdas) were used in this study, with 2456 subjects for analysis. Micronutrient analysis was carried out, including iron status (ferritin, C reactive protein (CRP)), levels of zinc, vitamin D, calcium, and vitamin A (retinol) in school-aged children (5-12 years). The ELISA measurement was applied to measure CRP, ferritin, and vitamin D. Zinc levels were analysed with atomic absorbance spectroscopy (AAS). Moreover, high-performance liquid chromatography (HPLC) was applied to calculate vitamin A. In addition, stunting and thinness data were also obtained from the Riskesdas study. The results showed that the prevalence of stunting and thinness in school-aged children was 11.4% and 9.2%, respectively, showing that the stunting prevalence in the city was lower than in the village (4.5% vs. 6.9%, P = 0.000, respectively). In addition, the prevalence of MNDs in Indonesian children was 13.4%, 19.7%, 4.2%, 3%, and 12.7% for ferritin, zinc, calcium, vitamin A, and vitamin D, respectively. The mean serum level of vitamin A and zinc was significantly lower in stunted children compared to normal school children (P = 0.010 and P = 0.014). The serum concentration of vitamin D was significantly lower in overweight children compared to thin and normal children (P = 0.000). Serum values of ferritin, zinc, and vitamin A were significantly higher in overweight children compared to thin and normal children (P = 0.000). A poor correlation was observed between the z-score of height-for-age (HAZ) and the levels of zinc (r = 0.089, P = 0.000), vitamin A (r = 0.105, P = 0.000), and vitamin D (-0.073, P = 0.000). In addition, very weak correlations between z-scores of body mass index-for-age (BAZ) and the serum concentrations of ferritin (0.091, P = 0.000), zinc (r = 0.115, P = 0.000), vitamin A (r = 0.137, P = 0.000), and vitamin D (r = -0.112, P = 0.000) were also seen. In conclusion, school-aged children in Indonesia experienced stunting, thinness, and micronutrient deficiency. Furthermore, stunting and thinness were also related to micronutrient deficiencies.

Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm.

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.

Spatial distribution and identifying biochemical factors affecting haemoglobin levels among women of reproductive age for each province in Indonesia: A geospatial analysis.

Anaemia is still a public health problem in Indonesia. The iron supplement program, known as Tablet Tambah Darah (Blood Add Tablet) has not yet produced optimal results. This study aimed to identify the cause of anaemia and the factors that influence it. Biochemical indicator data are haemoglobin (Hb), C-reactive protein (CRP), ferritin and serum transferrin receptor (sTfR) from 9,463 women of reproduction age. Data from the Basic Health Research (Riskesdas) project of 2013 were used for the study. ANOVA as well as global and local regression approaches (classical regression and geo-weighted regression) were used to compare the mean Hb and CRP values between provinces and to determine the factors that influence Hb concentrations. The results showed that the distribution of anaemia in Indonesia is uneven and not always caused by iron deficiency. The lowest Hb mean coupled with the highest iron deficiency was found in Papua, where there are high rates of parasitic infections. In contrast, the highest mean Hb coupled with low iron deficiency, and also low infection rates, was found in North Sulawesi. The Hb concentrations were significantly associated by ferritin, CRP and sTfR and there were varying magnitudes between provinces. Although anaemia is mainly influenced by the iron concentration, CRP, ferritin and sTfR can also affect it through their association with inflammatory reactions. Identification of all causes of anaemia in each province needs to be done in the future, while blanket iron supplementation should be reviewed.