scholarly journals Associations of Maternal Weight Status Before, During, and After Pregnancy with Inflammatory Markers in Breast Milk

Obesity ◽  
2018 ◽  
Vol 26 (10) ◽  
pp. 1659-1660
Author(s):  
Kara M. Whitaker ◽  
Regina C. Marino ◽  
Jacob L. Haapala ◽  
Laurie Foster ◽  
Katy D. Smith ◽  
...  
Obesity ◽  
2017 ◽  
Vol 25 (12) ◽  
pp. 2092-2099 ◽  
Author(s):  
Kara M. Whitaker ◽  
Regina C. Marino ◽  
Jacob L. Haapala ◽  
Laurie Foster ◽  
Katy D. Smith ◽  
...  

Nutrients ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 358 ◽  
Author(s):  
Lindsay Ellsworth ◽  
Harlan McCaffery ◽  
Emma Harman ◽  
Jillian Abbott ◽  
Brigid Gregg

In breastfed infants, human milk provides the primary source of iodine to meet demands during this vulnerable period of growth and development. Iodine is a key micronutrient that plays an essential role in hormone synthesis. Despite the importance of iodine, there is limited understanding of the maternal factors that influence milk iodine content and how milk iodine intake during infancy is related to postnatal growth. We examined breast milk samples from near 2 weeks and 2 months post-partum in a mother-infant dyad cohort of mothers with pre-pregnancy weight status defined by body mass index (BMI). Normal (NW, BMI < 25.0 kg/m2) is compared to overweight/obesity (OW/OB, BMI ≥ 25.0 kg/m2). The milk iodine concentration was determined by inductively coupled plasma mass spectrometry. We evaluated the associations between iodine content at 2 weeks and infant anthropometrics over the first year of life using multivariable linear mixed modeling. Iodine concentrations generally decreased from 2 weeks to 2 months. We observed no significant difference in iodine based on maternal weight. A higher iodine concentration at 2 weeks was associated with a larger increase in infant weight-for-age and weight-for-length Z-score change per month from 2 weeks to 1 year. This pilot study shows that early iodine intake may influence infant growth trajectory independent of maternal pre-pregnancy weight status.


Obesity ◽  
2019 ◽  
Vol 27 (4) ◽  
pp. 621-628 ◽  
Author(s):  
Ghazaleh Sadr Dadres ◽  
Kara M. Whitaker ◽  
Jacob L. Haapala ◽  
Laurie Foster ◽  
Katy D. Smith ◽  
...  

Author(s):  
Flaminia Bardanzellu ◽  
Melania Puddu ◽  
Diego Giampietro Peroni ◽  
Vassilios Fanos

2016 ◽  
Vol 7 (1) ◽  
pp. 108 ◽  
Author(s):  
Nasrin Omidvar ◽  
Delaram Ghodsi ◽  
Hassan Eini-Zinab ◽  
Arash Rashidian ◽  
Hossein Raghfar

Author(s):  
Xueling Wei ◽  
Peiyuan Huang ◽  
Chang Gao ◽  
Songying Shen ◽  
Si Tu ◽  
...  

2011 ◽  
Vol 35 (7) ◽  
pp. 907-915 ◽  
Author(s):  
S Péneau ◽  
B Salanave ◽  
M-F Rolland-Cachera ◽  
S Hercberg ◽  
K Castetbon

2015 ◽  
Vol 39 (10) ◽  
pp. 1437-1442 ◽  
Author(s):  
D J Lemas ◽  
J T Brinton ◽  
A L B Shapiro ◽  
D H Glueck ◽  
J E Friedman ◽  
...  

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 977-977
Author(s):  
Andrew Dinsmoor ◽  
Anna Arthur ◽  
Barbara Fiese ◽  
Naiman Khan ◽  
Sharon Donovan

Abstract Objectives The extent to which early life factors predict weight status by age two is unclear. This study elucidated early life factors predictive of BMI-for-age z-score (MN24 BMI) in 2-year-olds in the ongoing STRONG Kids 2 longitudinal study. Methods At registration, 6 weeks, 3, 12, 18, and 24 months, parents (N = 126) completed online surveys (questions derived from CDC Infant Feeding Practices questionnaire, Short Form of the MOS Health survey, and Block Kids Food Frequency Questionnaire (Ages 2–7; Nutrition Quest) for diet MN21–24). Height and weight were collected at home visits. Child BMI-for age z-scores were based on WHO growth standards, and dietary patterns at MN24 were derived by principal component analysis (PCA). Mode of delivery (i.e., vaginal or caesarean), timing of introduction to solids, dietary patterns, child's BMI z-score and feeding methods (i.e., exclusive formula or breastfeeding, or both), and maternal weight were obtained. Multiple regression modelling determined the explanatory power of these factors on MN24 BMI. Results Modelling revealed a significant regression equation (P &lt; .001), with an R2 of .359. MN12 BMI-for-age z-score (MN12 BMI) (β = .555, P &lt; .001) explained 31.2% of the variance in MN24 BMI. Child feeding method at MN3 (β = –.218, P = .003) accounted for 4.7% of the variance in MN24 BMI. Conclusions Children with a greater MN12 BMI have a higher MN24 BMI, while those who undergo breastfeeding at MN3 have a lower MN24 BMI. Future studies will expand on these findings by examining if the predictive power of these early life factors on BMI persists in later life. Funding Sources Grants from the National Dairy Council to Sharon Donovan and Barbara H. Fiese (CoPI's), and the Gerber Foundation and NIH R01 DK107561 to Sharon Donovan.


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