Diets, Metabolic Profile and Gut Microbiota Among Indonesian Women in Minangkabau and Sundanese-ethnic Community

January 26, 2018 updated by: Rina Agustina

Association of Intake and Nutritional Status With Total Microbiota and Metabolic Marker in Minangkabau and Sundanese Women in Urban and City: A Comparative Study

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.

Study Overview

Status

Completed

Conditions

Detailed Description

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 (Actual)

360

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

19 years to 50 years (Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Female

Sampling Method

Probability Sample

Study Population

Population represent mountainous and coastal areas (Tanah Datar and Padang Pariaman districts in West Sumatera for the Minangkabau ethnic group, and Tasikmalaya District in West Java for the Sundanese ethnic group), who are known to have differences in their traditional diets. These areas have agricultural fields, and the population of farmers and fishermen is above the regional average.

Description

Inclusion Criteria:

  • healthy reproductive women aged 19-50 years old
  • having both parents from the same ethnicities (Minangkabau or Sundanese)
  • willing to participate voluntarily signed a written informed-consent.

Exclusion Criteria:

  • not being pregnant or lactating
  • not having symptoms of gastrointestinal disturbance such as diarrhea, dysentery, constipation more than 3 days, and/or abdominal pain for the last 2 weeks
  • not having nausea or vomiting or lost appetite for the last 2 days
  • no history of malignancy
  • not consuming antibiotics in the last 1 week before fecal collection
  • not consuming alcohol more than 3 times a week

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Ecologic or Community
  • Time Perspectives: Cross-Sectional

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Dietary or nutritional intake
Time Frame: September - November 2016
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.
September - November 2016

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Total fecal microbiota
Time Frame: September - December 2016
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.
September - December 2016
Weight
Time Frame: September - November 2016
Body weight in kilograms
September - November 2016
Height
Time Frame: September - November 2016
Height in metres
September - November 2016
Body mass index
Time Frame: September - November 2016
Calculated from body weight divided by square of height, reported in kg/m2. Normal range 18.5-22.9 kg/m2.
September - November 2016
Obesity
Time Frame: September - November 2016
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
September - November 2016
Waist circumference
Time Frame: September - November 2016
Waist circumference in centimetres. Normal value is below 80 centimetres for women.
September - November 2016
Hip circumference
Time Frame: September - November 2016
Hip circumference in centimetres
September - November 2016
Hemoglobin level
Time Frame: September - November 2016
Blood hemoglobin was assessed by hemocue, reported in gram/decilitre. Normal value for blood hemoglobin is 12-15.5 gram/decilitre.
September - November 2016
HbA1c
Time Frame: September - November 2016
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.
September - November 2016
Lipid profile
Time Frame: September - November 2016
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).
September - November 2016
Fasting blood glucose
Time Frame: September - November 2016
Fasting blood glucose was quantified using enzymatic colorimetric method glucose oxidase - phenol aminophenazone. Normal value is less than 100 milligrams/decilitre.
September - November 2016
Malondialdehyde (MDA) level
Time Frame: September - November 2016
Blood MDA was quantified using spectrophotometry, reported in micromol/litre. There is no official cut off for this measurement.
September - November 2016
Total advanced glycation end products (AGE)
Time Frame: September - December 2016
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.
September - December 2016
Plasma carboxymethyl lysine (CML)
Time Frame: July - December 2017
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.
July - December 2017
Tumor necrosis factor-alfa (TNF-alfa)
Time Frame: July - December 2017
Plasma tumor necrosis factor-alpha was done by ELISA, reported in IU/millilitre. There is no official cut off for this measurement.
July - December 2017

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Collaborators

Investigators

  • Principal Investigator: Rina Agustina, Indonesia University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 22, 2016

Primary Completion (Actual)

November 16, 2016

Study Completion (Actual)

December 20, 2017

Study Registration Dates

First Submitted

January 11, 2018

First Submitted That Met QC Criteria

January 19, 2018

First Posted (Actual)

January 26, 2018

Study Record Updates

Last Update Posted (Actual)

January 30, 2018

Last Update Submitted That Met QC Criteria

January 26, 2018

Last Verified

January 1, 2018

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Dietary Minangkabau-Sunda

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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