Many provinces in Indonesia have some well known traditional foods that are widely consumed, but it remains unknown whether traditional ethnic dietary patterns can confirm healthy diets. High quality diet is associated with reduced risk of metabolic diseases and modulated gut microbiota. Moreover, the relationship between dietary quality and microbiota, a potential mediator of metabolic disease, has not been studied.
This study was conducted in specific villages and hamlets that were randomly selected by multi-stage random cluster sampling in 2 provinces. The investigators randomly selected 36 villages (18 villages in each provinces) by using probability proportional to size cluster sampling to admit the total 360 women who met the criteria and consented. While Bifidobacterium, Advanced Glycation End Products (AGE) and lipid profile were examined in a subgroup of 120 participants from each province (n=240). Field enumerators were trained to standardize 24 hours food recall, food frequency questionnaire for 1 month back, and for stool sampling technique procedure. Anthropometric measurement was performed by performing weight and height measurement. Fasting blood sampling and fecal Bifidobacterium examination were done in collaboration with professional laboratories. Hemoglobin was assessed by using hemocue. Lipid profile was quantified using calorimetric method, fasting blood glucose (FBG) was quantified using enzymatic colorimetric method glucose oxidase - phenol aminophenazone, HbA1c was using high performance liquid chromatography (HPLC) hexokinase, malondialdehyde level was quantified using will's spectrophotometry, blood advance glycation end products was done by using enzyme linked immunosorbent assay (ELISA), carboxymethyl lysine plasma was done by ultra performance liquid chromatography-tandem mass spectometry (UPLC-MS/MS), and plasma tumor necrosis factor-alpha was done by ELISA. Fecal sample were collected in 2 pots, each contain 5-10 gram of stool, and store in cooler box (2-9 degree celcius) until sample was transported to laboratory as soon as possible to store in -80 degree celcius freezer.
Study Type
OBSERVATIONAL
Enrollment
360
Dietary or nutritional intake
Usual dietary intake was done by using semi quantitative food frequency questionnaire for 1 month, and actual intake was done by nonconsecutive repeated 24-hour food recall (weekday and weekend). The investigators was analyse the dietary intake by Nutrisurvey 2007 software. Nutritional intake was reported as total daily intake (energy, macronutrients, and micronutrients). Energy intake is showed in kkal/day. Macronutrients include carbohydrate, protein, fat, and fiber intake are showed in gram/day. Micronutrients include vitamins and minerals are showed in gram/milligram/microgram per day. The value of nutrient intake are very diverse from 0 to high intake.
Time frame: September - November 2016
Total fecal microbiota
Microbiota that examined in this study was total Bifidobacterium, quantified by real time-polymerase chain reaction, reported as log Bifidobacterium/gram feces. There is no official cut off for this measurement.
Time frame: September - December 2016
Weight
Body weight in kilograms
Time frame: September - November 2016
Height
Height in metres
Time frame: September - November 2016
Body mass index
Calculated from body weight divided by square of height, reported in kg/m2. Normal range 18.5-22.9 kg/m2.
Time frame: September - November 2016
Obesity
Classified using body mass index Asia Pacific standard. Score body mass index below 18.5 kg/m2 is underweight, 18.5-22.9 kg/m2 is normal range, 23-24.9 kg/m2 is overweight, 25-29.9 kg/m2 is obese 1, higher than 30 kg/m2 is obese 2
Time frame: September - November 2016
Waist circumference
Waist circumference in centimetres. Normal value is below 80 centimetres for women.
Time frame: September - November 2016
Hip circumference
Hip circumference in centimetres
Time frame: September - November 2016
Hemoglobin level
Blood hemoglobin was assessed by hemocue, reported in gram/decilitre. Normal value for blood hemoglobin is 12-15.5 gram/decilitre.
Time frame: September - November 2016
HbA1c
HbA1c was quantified using high performance liquid chromatography (HPLC) hexokinase, reported in %. Normal value is 4%-5.6%. Score 5.7%-6.4% means high risk of diabetes. Score 6.5% or higher for diagnose diabetes.
Time frame: September - November 2016
Lipid profile
Blood lipid profile was quantified using calorimetric method, reported as cholesterol total (normal value is less than 200 milligrams/decilitre)/ low density lipoprotein cholesterol (normal value is less than 100 milligrams/decilitre)/ high density lipoprotein cholesterol (normal value is higher than 40 milligrams/decilitre)/ triglyceride (normal value is less than 150 milligrams/decilitres).
Time frame: September - November 2016
Fasting blood glucose
Fasting blood glucose was quantified using enzymatic colorimetric method glucose oxidase - phenol aminophenazone. Normal value is less than 100 milligrams/decilitre.
Time frame: September - November 2016
Malondialdehyde (MDA) level
Blood MDA was quantified using spectrophotometry, reported in micromol/litre. There is no official cut off for this measurement.
Time frame: September - November 2016
Total advanced glycation end products (AGE)
Blood AGE was quantified by using enzyme linked immunosorbent assay (ELISA), reported in kilo unit/millilitre. There is no official cut off for this measurement.
Time frame: September - December 2016
Plasma carboxymethyl lysine (CML)
Plasma CML was quantified by ultra performance liquid chromatography-tandem mass spectometry (UPLC-MS/MS), reported in nanograms/millilitre. There is no official cut off for this measurement.
Time frame: July - December 2017
Tumor necrosis factor-alfa (TNF-alfa)
Plasma tumor necrosis factor-alpha was done by ELISA, reported in IU/millilitre. There is no official cut off for this measurement.
Time frame: July - December 2017
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