Suboptimal child healthcare practices and the development of multiple infectious diseases in children aged 24-59 months.

Background: Infections continue to be a major cause of death among children under the age of five worldwide. This study aimed to identify the factors associated with the development of multiple infectious diseases in children aged 24-59 months in Indonesia. Methods: Data from the 2018 Basic Health Research conducted by the Ministry of Health, Republic of Indonesia, were used. Information from 39,948 children aged 24-59 months was analyzed. The outcome variable was the development of multiple infectious diseases, that is, acute respiratory infections, pneumonia, pulmonary tuberculosis, diarrhea, and hepatitis, in the month before the survey. Factors significantly associated with multiple types of infectious diseases were examined using logistic regression. Results: The study found that 76.6% of children aged 24 to 59 months in Indonesia had at least one type of infectious disease. The likelihood of developing multiple types of infectious diseases increased in children whose parents did not practice appropriate handwashing with soap and running water [adjusted odds ratio (aOR) = 1.16, p < 0.001], those who received supplemental food (aOR = 1.38, p < 0.001), those with poor nutritional status (aOR = 1.12, p < 0.001), and those living in urban areas (aOR = 1.07, p = 0.045). Conclusion: Improving caregivers' awareness of adequate child healthcare practices, in addition to nutrition-sensitive and specific interventions to improve children's nutritional status, is required to prevent children from contracting multiple types of infectious diseases.

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.

Prevalence and associated factors for prehypertension and hypertension among Indonesian adolescents: a cross-sectional community survey.

OBJECTIVE: To estimate the prevalence and determine the associated factors for developing prehypertension and hypertension among Indonesian adolescents. DESIGN: National cross-sectional study. SETTING: This study was conducted in all the provinces in Indonesia. PARTICIPANTS: The population in this study were all household members in Basic Health Research 2013 aged 15-19 years. The sample was all members of the 2013 Riskesdas household aged 15-19 years with the criteria of not having physical and mental disabilities, and having complete data. The number of samples analysed was 2735, comprising men (n=1319) and women (n=1416). MAIN OUTCOME: Dependent variables were prehypertension and hypertension in adolescents based on blood pressure measurements. RESULTS: The results of the analysis showed that the prevalence of prehypertension in adolescents was 16.8% and hypertension was 2.6%. In all adolescents, the risk factors for prehypertension were boys (adjusted OR, aOR 1.48; 95% CI 1.10 to 1.97), 18 years old (aOR 14.64; 95% CI 9.39 to 22.80), and 19 years old (aOR 19.89; 95% CI 12.41 to 31.88), and obese (aOR 2.16; 95% CI 1.02 to 4.58). Risk factors for hypertension in all adolescents included the age of 18 years old (aOR 3.06; 95% CI 1.28 to 7.34) and 19 years (aOR 3.25; 95% CI 1.25 to 8.41) and obesity (aOR 5.69; 95% CI 2.20 to 14.8). In adolescent girls, the chance of developing prehypertension increased with increasing age and low-density lipoprotein (LDL) cholesterol levels. Several risk factors for hypertension in adolescent boys were age, central obesity and LDL cholesterol levels. CONCLUSION: This study shows that the trend of prehypertension in adolescents has appeared, besides hypertension. There are distinct patterns of factors that influence it in adolescent girls and boys, which can be useful to sharpen of planning and implementing health programmes.

Sociodemographic and Healthcare Factors Associated with Stunting in Children Aged 6-59 Months in the Urban Area of Bali Province, Indonesia 2018.

Stunting is a worldwide public health concern, including in Indonesia. Even when living in an urban area with urban characteristics, it is still possible for children to be at risk of stunting. The aim of this study was to determine the sociodemographic and healthcare factors associated with stunting in a province experiencing tourism growth, namely, Bali. Cross-sectional data on Bali Province from the Indonesian Basic Health Research Survey (Riskesdas, 2018) were used as the basis for the research analysis. A total of 846 respondents under five years of age were analyzed, indicating a stunting prevalence of 19.0%. Multivariate logistic regression demonstrated low maternal educational attainment (adjustedOR = 1.92; 95% Confidence Interval = 1.24-2.97), the inadequate consumption of iron tablets during pregnancy (adjustedOR = 1.56; 95% Confidence Interval = 1.08-2.24), and no extended family (adjustedOR = 1.55; 95% Confidence Interval = 1.07-2.26) as being significantly associated with stunting. According to these findings, sociodemographic and healthcare factors are associated with stunting in urban Bali. Improving women's education, ensuring sufficient iron tablets are consumed during pregnancy, and encouraging the involvement of the extended family in childcare are recommended.

Risk factors for the metabolic syndrome in non-obese older Indonesians.

BACKGROUND AND OBJECTIVES: The problem of metabolic syndrome among non-obese older people is often ignored. This study examines the risk factors for metabolic syndrome in non-obese older people in Indonesia. We analyzed information collected from 3323 non-obese older respondents interviewed in the 2018 Basic Health Research program. METHODS AND STUDY DESIGN: The outcome variable was the metabolic syndrome consisting of three components: high lipid profile, diabetes mellitus, and hypertension. The potential predictors analyzed were socio-demographic and behavioral factors consisting of psychomotor (cigarette smoking + physical activity) and dietary behavior (consumption of fat + fruit/vegetable). Multinomial logistic regression analysis was employed to assess metabolic syndrome risk factors in non-obese older people. RESULTS: We found that the proportion of non-obese older people in Indonesia with metabolic syndrome was 83.8% (95%CI: 82.4-85.2%). The odds of developing 2-3 components of metabolic syndrome increased in respondents from rural areas (aOR=1.26, p=0.033) and those with moderate psychomotor behavior problems (current smoker/ex-smoker with sufficient physical activity) (aOR=1.48, p=0.002). CONCLUSIONS: Health promotion activities are vital to improve awareness and promote healthy behaviors, specifically for those living in rural areas and smoking cigarettes.