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.

The relationship of body mass index and mid-upper arm circumference with anemia in non-pregnant women aged 19-49 years in Indonesia: Analysis of 2018 Basic Health Research data.

BACKGROUND AND OBJECTIVES: Anemia remains a major public health problem worldwide. This study examined the relationship between anemia and the nutritional status of non-pregnant women aged 19-49 years in Indonesia. METHODS AND STUDY DESIGN: The data were derived from the 2018 Basic Health Research Data of Indonesia. We used information from 11,471 non-pregnant women aged 19-49 years. The dependent variable was anemia (hemoglobin level <12 g/dL). The independent variable was women's nutritional status, a combined indicator of body mass index (BMI) and mid-upper arm circumference (MUAC). Our analysis controlled for women's age, education, physical activity, fruit and vegetable consumption, and the presence of communicable or non-communicable diseases. We performed logistic regression analyses. RESULTS: The prevalence of anemia in non-pregnant women aged 19-49 years was 22.3% (95% confidence interval [CI]: 21.4-23.3). Women with overweight and obesity were less likely to develop anemia than those with a normal BMI, regardless of their MUAC score. The highest odds for developing anemia were observed in underweight women with low MUAC scores (adjusted odds ratio [aOR] = 2.83, 95%CI: 2.19-3.68). Higher odds ratios were also observed in women with insufficient physical activity, despite their sufficient consumption of fruits or vegetables (aOR = 1.87, 95%CI: 1.06-3.28). However, women who had been diagnosed with a non-communicable disease had a reduced likelihood of developing anemia (aOR = 0.75, 95%CI: 0.67-0.83). CONCLUSIONS: Strengthening health promotion activities to improve nutritional status and healthy behaviors, particularly a healthy diet, remains important for women in Indonesia to reduce the prevalence of anemia and improve their overall health status.

Geographic and Socioeconomic Disparity in Child Undernutrition across 514 Districts in Indonesia.

BACKGROUND: Globally, in 2020, 45 million children were estimated to be wasted, and 149 million children under five years of age were estimated to be stunted. Undernutrition makes children in particular much more vulnerable to disease and death. Our study aims to examine geographic and socioeconomic disparities in child undernutrition across 514 districts in Indonesia. METHODS: Employing both geospatial and quantitative analyses (descriptive statistics and Ordinary Least Squares regressions), we analyzed the disparities in the prevalence of underweight, severe underweight, wasting, severe wasting, stunting, and severe stunting among districts. Child undernutrition data were from Indonesia Basic Health Survey (Riskesdas) 2018, which included a sample of 93,620 children under five years. Socioeconomic data were from the World Bank. RESULTS: We found a relatively large geographic and socioeconomic disparity in child undernutrition in Indonesia. By region, districts in the Papua region (including Maluku and Nusa Tenggara) had a significantly higher prevalence of underweight and wasting than those in the Java region (including Bali). Districts in Papua had 44%, 121%, 38%, and 57% higher prevalence of underweight, severe underweight, wasting, and severe wasting, respectively. Similarly, the poorest districts had a significantly higher prevalence of underweight, wasting, and stunting than the wealthiest districts. The poorest districts had 30%, 83%, 16%, 21%, and 74% higher prevalence of underweight, severe underweight, wasting, stunting, and severe stunting, respectively. These results were similar among rural districts. CONCLUSION: There is a significant disparity in child undernutrition across districts in Indonesia. The government needs to prioritize the reduction of child undernutrition, especially in rural areas, districts outside of Java and Bali, and the poorest and least educated areas.

Determinants of the Stunting of Children Under Two Years Old in Indonesia: A Multilevel Analysis of the 2013 Indonesia Basic Health Survey.

Indonesia is ranked fifth among countries with the highest burden of stunting in children under five. This study aims to examine the determinants of stunting in children aged 0-2 years in Indonesia using data derived from the 2013 Indonesia Basic Health Survey. Twenty potential predictors of stunting, categorized into household and housing characteristics; maternal and paternal characteristics; antenatal care services and child characteristics were analyzed. Multilevel analyses were performed to examine the role of cluster/district/provincial differences, as well as individual/household level characteristics and stunting status. Of 24,657 children analyzed, 33.7% (95%CI: 32.8%-34.7%) were stunted. The odds of stunting increased significantly among children living in households with three or more children under five-years-old (aOR = 1.33, 95%CI: 1.03-1.72), households with five to seven household members (aOR =1.11; 95%CI: 1.03-1.20), children whose mothers during pregnancy attended less than four antenatal care services (aOR = 1.22, 95%CI: 1.08-1.39), boys (aOR = 1.33, 95%CI: 1.22-1.45), children aged 12-23 months (aOR = 1.89; 95%CI: 1.54-2.32), and children who weighed <2500 g at birth (aOR = 2.55; 95%CI: 2.05-3.15). The odds also increased significantly with the reduction of household wealth index. Integrated interventions to address environment, an individual level associated with stunting in Indonesia, from the environment- to individual-level factors are important.