The risk of malnutrition in maintenance hemodialysis (MHD) patients must be monitored routinely through nutrition screening so that morbidity and mortality can be decreased. Comparing the validity of the simple nutrition screening tool (SNST) and nutritional risk screening 2002 (NRS 2002) as valid and reliable nutrition screening tools in predicting malnutrition. The data were collected from March to April 2015 in the Hemodialysis Unit of Dr. Sardjito Hospital, Indonesia as an observational study. A cross-sectional design study was used to screen 105 MHD patients using the SNST and NRS 2002, and then, the nutritional status of all individuals was assessed used the following subjective parameters: subjective global assessment (SGA) and dialysis malnutrition score (DMS). The objective parameters were the following: Body mass index (BMI), mid-upper-arm circumference (MUAC), handgrip strength (HGS), and a three-day food record. Chi-squared test, t-test, and receiving operating characteristic curve were used for the statistical analysis. In predicting malnutrition, the validity of the SNST is better than the NRS 2002 in MHD patients against either SGA (Se 94.3% vs. 82.9%; Sp 60% vs. 58.6%; and area under curve (AUC) 0.847 vs. 0.749) or DMS (Se 90.0% vs. 81.6%; Sp 74.0% vs. 62.8%; and AUC 0.833 vs. 0.746), while the NRS 2002 is better than the SNST based on BMI, MUAC, HGS, and energy intake (P<0.001). In predicting malnutrition, SNST is better than NRS 2002 based on the subjective assessments (SGA and DMS), and NRS 2002 is better than SNST based on the objective assessments (BMI, MUAC, and HGS).

No abstract

No abstract

Aim: We investigate risk factors contributing to dyslipidemia among adults. Method: A cross-sectional study on 2016 -2018 involving 543 healthy adults 19-64 years of age was conducted in three dwelling area in Yogyakarta Province, represented urban, semi-urban and rural. Adults who had no history of NCDs were included after signing informed consent. Pregnant or breastfed woman was excluded. We assessed waist circumference (WC), body mass index (BMI) and fasting blood samples to analyzed lipid profile. Dyslipidemia was defined by, as follows: total cholesterol ≥200 mg/dl, low density lipoprotein ≥130 mg/dl, high density lipoprotein b40 mg/dl, and triglyceride ≥150 mg/dl. Result: Prevalence of overweight/obese dominated in urban (38.5%) and rural (40%). Nutritional status associated with dwelling area (p=0.014). Prevalence of dyslipidemia dominated in rural (52.5%) and urban (31%). Significant association was showed by dyslipidemia and dwelling area (p=0.025). Generally, overweight/ obese and central obesity had higher prevalence of dyslipidemia compared to the other counterparts (p=b0.001 and 0.006, respectively). Three domains of correlated risk factors of dyslipidemia were constructed by Principle Components Analysis (PCA): biological and habit, nutritional status, and socio-demographic. Gender (women), overweight/obese, central obesity were more likely to be dyslipidemia (2.3 times, 3.4 times, 2.4 times, respectively). Conclusion: Different dwelling area is associated with nutritional status and dyslipidemia that might come from lifestyle and unhealthy food environment. Three domains become correlated risk factor of dyslipidemia: biological and habit, nutritional status, and sociodemographic. Women, overweight/obese, and central obesity have higher risk of dyslipidemia.

.