Chilean Maternal & Infant Cohort Study II (CHiMINCs-II)

Mental Health Issue Clinical Trial

— CHiMINCs-II  

Official title:

The Chilean Maternal and Infant Nutrition Cohort Study II

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT03920098
• Other study ID #: 1190532
• Status: Active, not recruiting
• Start date: June 1, 2019
• Est. completion date: April 30, 2023

Study information

• Verified date: February 2022
• Source: Instituto de Nutrición y Tecnología de los Alimentos
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 1927
• Est. completion date: April 30, 2023
• Est. primary completion date: July 30, 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Female
• Age group: 18 Years to 50 Years

Eligibility

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

Related Conditions & MeSH terms

• Body Composition
• Breast Density
• Mental Health Issue
• Nutritional Status

Intervention

Other:
• Nutrition and mental health during pregnancy
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.

Locations

Country	Name	City	State
Chile	Corporación de Salud Municipal de Puente Alto	Santiago de Chile	Puente Alto

Sponsors (3)

Lead Sponsor	Collaborator
Instituto de Nutrición y Tecnología de los Alimentos	Pontificia Universidad Catolica de Chile, Servicio de Salud Metropolitano Sur Oriente

Country where clinical trial is conducted

Chile, 

References & Publications (22)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

Britt K, Ashworth A, Smalley M. Pregnancy and the risk of breast cancer. Endocr Relat Cancer. 2007 Dec;14(4):907-33. Review. — View Citation

Buschard K, Thomassen K, Lynge E, Vejborg I, Tjønneland 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. — View Citation

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. — View Citation

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. — View Citation

Gabrielson M, Chiesa F, Behmer C, Rönnow 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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Review. — View Citation

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. — View Citation

Rice MS, Bertrand KA, Lajous M, Tamimi RM, Torres G, López-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. — View Citation

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. — View Citation

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. — View Citation

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. Review. — View Citation

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. — View Citation

Varghese JS, Thompson DJ, Michailidou K, Lindström 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. — View Citation

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. Review. — View Citation

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. — View Citation

* Note: There are 22 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Breast absolute (AFGV) fibro-glandular volume measured by DXA technique	cm3	Three months after breastfeeding cessation
Primary	Breast absolute percentage (%FVG) of fibro-glandular volume measured by DXA technique	percentage	Three months after breastfeeding cessation
Primary	Gestational weight gain	kg	At delivery
Primary	Gestational Diabetes	Percentage of mothers diagnosed	At delivery
Primary	Pregnancy Risk Assessment Monitoring System	Score	Through the gestation, up the delivery
Primary	Edinburg Postnatal Depression Scale	Score	Through the gestation, up to 6 months
Primary	Glucose concentration	mg/dL	Through the gestation, up the delivery
Primary	Insulin concentration	uIU/mL	Through the gestation, up the delivery
Primary	Pandemic Anxiety Scale	Score	Through the gestation, up the delivery
Secondary	Offspring weight	g	At 6 months of age
Secondary	Offspring length	cm	At 6 months of age
Secondary	Offspring head circumference	cm	At 6 months of age
Secondary	Offspring body fat	Percentage	At 6 months of age