- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03920098
Chilean Maternal & Infant Cohort Study II (CHiMINCs-II) (CHiMINCs-II)
February 4, 2022 updated by: Dr. Maria Luisa Garmendia, Instituto de Nutrición y Tecnología de los Alimentos
The Chilean Maternal and Infant Nutrition Cohort Study II
The Chilean Maternal & Infant Cohort Study II (ChiMINCs II) is an ongoing cohort that is part of the Chilean Maternal and Infant Nutrition Observatory of the South-East area of Santiago, Chile.
In total, 1927 pregnant women beneficiaries of the public health systems and their offspring were recruited before 12 weeks of gestation and are followed across pregnancy (<15, 26-28, and 35-37 weeks of gestation) and up to 2 years of age of their offspring.
Two studies are currently nested in ChiMINCs II: 1) Breast Cancer Risk Assessment in Mothers (BRECAM) study, and 2) the ChiMINCs-COVID study.
The primary objective of BRECAM study is to test the association between maternal metabolic indicators (i.e., insulin, glucose, IGF-1, and HbAc1 concentrations) at early pregnancy (i.e., <15 and 26-28 weeks of gestation) and breast density 3 months after the cessation of lactation.
For this purpose, we collect maternal obstetric, lifestyle, dietary intake, anthropometric, and biochemical information.
The aim of the ChiMINCs-COVID study is to assess dietary-related risks and mental health problems derived from the COVID-19 pandemic and their influence on maternal and infant's health and nutrition.
Thus, we collected detailed information on dietary behaviors, mental health and COVID-related information at each trimester, along with neonatal and infant nutritional information.
The purpose of the present work is to describe the design, methods, and descriptive information at recruitment of ChiMINCs-II, also discussing the implications that this study can have to better understand maternal and infant nutrition and health during the COVID-19 era.
Study Overview
Status
Active, not recruiting
Intervention / Treatment
Study Type
Observational
Enrollment (Actual)
1927
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Puente Alto
-
Santiago de Chile, Puente Alto, Chile, 8210269
- Corporación de Salud Municipal de Puente Alto
-
-
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
18 years to 50 years (ADULT)
Accepts Healthy Volunteers
Yes
Genders Eligible for Study
Female
Sampling Method
Probability Sample
Study Population
We identified pregnant women who received primary prenatal care within PHCC located in the South East area of Santiago.
After, offspring of pregnant women were followed postnatally.
Description
Inclusion Criteria:
- 18 or more years of age
- Gestation <15 weeks at first prenatal visit
- No intention to move outside the city of Santiago in the next to years
Exclusion Criteria:
- High-risk pregnancy (i.e., preeclampsia, pre- existing diabetes)
- Pre-existing cancer or family history of breast cancer
- Intended to migrate from the public to the private health care system
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
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Mother-infant dyads
|
Altered metabolic milieu is defined as a fasting glucose level >100 mg/dL at the first trimester of pregnancy by national guidelines.
Altered metabolic milieu during the second trimester (24-28 weeks of pregnancy) is defined as a fasting glucose levels > 92 mg/dL and/or plasma glucose levels > 153 mg/dL two hours after load in the oral glucose tolerance test according to ADA guidelines or a fasting glucose >100 mg/dL and/or > 140 mg/dL two hours after load in the oral glucose tolerance test according to national guidelines.
The COVID-19 pandemic is considered as a natural nutritional and mental health exposure.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Breast absolute (AFGV) fibro-glandular volume measured by DXA technique
Time Frame: Three months after breastfeeding cessation
|
cm3
|
Three months after breastfeeding cessation
|
Breast absolute percentage (%FVG) of fibro-glandular volume measured by DXA technique
Time Frame: Three months after breastfeeding cessation
|
percentage
|
Three months after breastfeeding cessation
|
Gestational weight gain
Time Frame: At delivery
|
kg
|
At delivery
|
Gestational Diabetes
Time Frame: At delivery
|
Percentage of mothers diagnosed
|
At delivery
|
Pregnancy Risk Assessment Monitoring System
Time Frame: Through the gestation, up the delivery
|
Score
|
Through the gestation, up the delivery
|
Edinburg Postnatal Depression Scale
Time Frame: Through the gestation, up to 6 months
|
Score
|
Through the gestation, up to 6 months
|
Glucose concentration
Time Frame: Through the gestation, up the delivery
|
mg/dL
|
Through the gestation, up the delivery
|
Insulin concentration
Time Frame: Through the gestation, up the delivery
|
uIU/mL
|
Through the gestation, up the delivery
|
Pandemic Anxiety Scale
Time Frame: Through the gestation, up the delivery
|
Score
|
Through the gestation, up the delivery
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Offspring weight
Time Frame: At 6 months of age
|
g
|
At 6 months of age
|
Offspring length
Time Frame: At 6 months of age
|
cm
|
At 6 months of age
|
Offspring head circumference
Time Frame: At 6 months of age
|
cm
|
At 6 months of age
|
Offspring body fat
Time Frame: At 6 months of age
|
Percentage
|
At 6 months of age
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: María L Garmendia, PhD, Instituto de Nutrición y Tecnología de Alimentos
- Principal Investigator: Camila L Corvalán Aguilar, PhD, Institute of Nutrition and Food Technology (INTA), University of Chile, Chile
- Principal Investigator: María F Mujica Coopman, PhD, Institute of Nutrition and Food Technology (INTA), University of Chile, Chile
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, Jong RA, Hislop G, Chiarelli A, Minkin S, Yaffe MJ. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007 Jan 18;356(3):227-36. doi: 10.1056/NEJMoa062790.
- McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2006 Jun;15(6):1159-69. doi: 10.1158/1055-9965.EPI-06-0034.
- Boyd N, Berman H, Zhu J, Martin LJ, Yaffe MJ, Chavez S, Stanisz G, Hislop G, Chiarelli AM, Minkin S, Paterson AD. The origins of breast cancer associated with mammographic density: a testable biological hypothesis. Breast Cancer Res. 2018 Mar 7;20(1):17. doi: 10.1186/s13058-018-0941-y.
- Li T, Sun L, Miller N, Nicklee T, Woo J, Hulse-Smith L, Tsao MS, Khokha R, Martin L, Boyd N. The association of measured breast tissue characteristics with mammographic density and other risk factors for breast cancer. Cancer Epidemiol Biomarkers Prev. 2005 Feb;14(2):343-9. doi: 10.1158/1055-9965.EPI-04-0490.
- Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, Giles GG, Tritchler D, Chiarelli A, Yaffe MJ, Hopper JL. Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med. 2002 Sep 19;347(12):886-94. doi: 10.1056/NEJMoa013390.
- Varghese JS, Thompson DJ, Michailidou K, Lindstrom S, Turnbull C, Brown J, Leyland J, Warren RM, Luben RN, Loos RJ, Wareham NJ, Rommens J, Paterson AD, Martin LJ, Vachon CM, Scott CG, Atkinson EJ, Couch FJ, Apicella C, Southey MC, Stone J, Li J, Eriksson L, Czene K, Boyd NF, Hall P, Hopper JL, Tamimi RM; MODE Consortium; Rahman N, Easton DF. Mammographic breast density and breast cancer: evidence of a shared genetic basis. Cancer Res. 2012 Mar 15;72(6):1478-84. doi: 10.1158/0008-5472.CAN-11-3295. Epub 2012 Jan 19.
- Nazari SS, Mukherjee P. An overview of mammographic density and its association with breast cancer. Breast Cancer. 2018 May;25(3):259-267. doi: 10.1007/s12282-018-0857-5. Epub 2018 Apr 12.
- Rice MS, Rosner BA, Tamimi RM. Percent mammographic density prediction: development of a model in the nurses' health studies. Cancer Causes Control. 2017 Jul;28(7):677-684. doi: 10.1007/s10552-017-0898-7. Epub 2017 May 6.
- Yaghjyan L, Colditz GA, Rosner B, Bertrand KA, Tamimi RM. Reproductive factors related to childbearing and mammographic breast density. Breast Cancer Res Treat. 2016 Jul;158(2):351-9. doi: 10.1007/s10549-016-3884-y. Epub 2016 Jun 28.
- Rice MS, Bertrand KA, Lajous M, Tamimi RM, Torres G, Lopez-Ridaura R, Romieu I. Reproductive and lifestyle risk factors and mammographic density in Mexican women. Ann Epidemiol. 2015 Nov;25(11):868-73. doi: 10.1016/j.annepidem.2015.08.006. Epub 2015 Aug 29.
- Collaborative Group on Hormonal Factors in Breast Cancer. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet. 2002 Jul 20;360(9328):187-95. doi: 10.1016/S0140-6736(02)09454-0.
- Gabrielson M, Chiesa F, Behmer C, Ronnow K, Czene K, Hall P. Association of reproductive history with breast tissue characteristics and receptor status in the normal breast. Breast Cancer Res Treat. 2018 Aug;170(3):487-497. doi: 10.1007/s10549-018-4768-0. Epub 2018 Mar 30.
- Britt K, Ashworth A, Smalley M. Pregnancy and the risk of breast cancer. Endocr Relat Cancer. 2007 Dec;14(4):907-33. doi: 10.1677/ERC-07-0137.
- Vashi R, Hooley R, Butler R, Geisel J, Philpotts L. Breast imaging of the pregnant and lactating patient: imaging modalities and pregnancy-associated breast cancer. AJR Am J Roentgenol. 2013 Feb;200(2):321-8. doi: 10.2214/ajr.12.9814.
- Sabate JM, Clotet M, Torrubia S, Gomez A, Guerrero R, de las Heras P, Lerma E. Radiologic evaluation of breast disorders related to pregnancy and lactation. Radiographics. 2007 Oct;27 Suppl 1:S101-24. doi: 10.1148/rg.27si075505.
- Loehberg CR, Heusinger K, Jud SM, Haeberle L, Hein A, Rauh C, Bani MR, Lux MP, Schrauder MG, Bayer CM, Helbig C, Grolik R, Adamietz B, Schulz-Wendtland R, Beckmann MW, Fasching PA. Assessment of mammographic density before and after first full-term pregnancy. Eur J Cancer Prev. 2010 Nov;19(6):405-12. doi: 10.1097/CEJ.0b013e32833ca1f4.
- Strange KS, Wilkinson D, Edin G, Emerman JT. Mitogenic properties of insulin-like growth factors I and II, insulin-like growth factor binding protein-3 and epidermal growth factor on human breast stromal cells in primary culture. Breast Cancer Res Treat. 2004 Mar;84(2):77-84. doi: 10.1023/B:BREA.0000018384.64326.dd.
- Rosato V, Bosetti C, Talamini R, Levi F, Montella M, Giacosa A, Negri E, La Vecchia C. Metabolic syndrome and the risk of breast cancer in postmenopausal women. Ann Oncol. 2011 Dec;22(12):2687-2692. doi: 10.1093/annonc/mdr025. Epub 2011 Mar 17.
- Agnoli C, Berrino F, Abagnato CA, Muti P, Panico S, Crosignani P, Krogh V. Metabolic syndrome and postmenopausal breast cancer in the ORDET cohort: a nested case-control study. Nutr Metab Cardiovasc Dis. 2010 Jan;20(1):41-8. doi: 10.1016/j.numecd.2009.02.006. Epub 2009 Apr 10.
- Buschard K, Thomassen K, Lynge E, Vejborg I, Tjonneland A, von Euler-Chelpin M, Andersen ZJ. Diabetes, diabetes treatment, and mammographic density in Danish Diet, Cancer, and Health cohort. Cancer Causes Control. 2017 Jan;28(1):13-21. doi: 10.1007/s10552-016-0829-z. Epub 2016 Nov 10.
- Pereira A, Garmendia ML, Uauy R, Neira P, Lopez-Arana S, Malkov S, Shepherd J. Determinants of volumetric breast density in Chilean premenopausal women. Breast Cancer Res Treat. 2017 Apr;162(2):343-352. doi: 10.1007/s10549-017-4126-7. Epub 2017 Jan 28.
- Chen YH, Ferguson KK, Meeker JD, McElrath TF, Mukherjee B. Statistical methods for modeling repeated measures of maternal environmental exposure biomarkers during pregnancy in association with preterm birth. Environ Health. 2015 Jan 26;14:9. doi: 10.1186/1476-069X-14-9.
- Mujica-Coopman MF, Corvalan C, Flores M, Garmendia ML. The Chilean Maternal-Infant Cohort Study-II in the COVID-19 Era: A Study Protocol. Front Public Health. 2022 Jul 14;10:904668. doi: 10.3389/fpubh.2022.904668. eCollection 2022.
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)
June 1, 2019
Primary Completion (ANTICIPATED)
July 30, 2022
Study Completion (ANTICIPATED)
April 30, 2023
Study Registration Dates
First Submitted
April 16, 2019
First Submitted That Met QC Criteria
April 16, 2019
First Posted (ACTUAL)
April 18, 2019
Study Record Updates
Last Update Posted (ACTUAL)
February 7, 2022
Last Update Submitted That Met QC Criteria
February 4, 2022
Last Verified
February 1, 2022
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- 1190532
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
IPD Plan Description
Data and blood samples that will be collected in this study will be under the custody of the principal investigator and a human subject protection review board will regulate its use.
Others researchers may access the data by contacting to María Luisa Garmendia (Principal Investigator).
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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