Jennifer Shea

Dr. Jennifer Shea


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2012 in Nutrition, Metabolism and Cardiovascular Diseases
Verified
Journal Article
Closed access
JSJennifer Shea
Jennifer Shea
MKM.T.C. King
M.T.C. King
YYY. Yi
Y. Yi
WGW. Gulliver
W. Gulliver
GSG. Sun
G. Sun

1 August 2013 in Clinical Chemistry
Verified
Journal Article
Open access
PDF file
DKDanijela Konforte
Danijela Konforte
JSJennifer Shea
Jennifer Shea
LKLianna Kyriakopoulou
Lianna Kyriakopoulou
DCDavid Colantonio
David Colantonio
ACAshley H Cohen
Ashley H Cohen
KAKhosrow Adeli
Khosrow Adeli
BACKGROUND: Pediatric endocrinopathies are commonly diagnosed and monitored by measuring hormones of the hypothalamic-pituitary-gonadal axis. Because growth and development can markedly influence normal circulating concentrations of fertility hormones, accurate reference intervals established on the basis of a healthy, nonhospitalized pediatric population and that reflect age-, gender-, and pubertal stage–specific changes are essential for test result interpretation.METHODS: Healthy children and adolescents (n = 1234) were recruited from a multiethnic population as part of the CALIPER study. After written informed parental consent was obtained, participants filled out a questionnaire including demographic and pubertal development information (assessed by self-reported Tanner stage) and provided a blood sample. We measured 7 fertility hormones including estradiol, testosterone (second generation), progesterone, sex hormone–binding globulin, prolactin, follicle-stimulating hormone, and luteinizing hormone by use of the Abbott Architect i2000 analyzer. We then used these data to calculate age-, gender-, and Tanner stage–specific reference intervals according to Clinical Laboratory Standards Institute C28-A3 guidelines.RESULTS: We observed a complex pattern of change in each analyte concentration from the neonatal period to adolescence. Consequently, many age and sex partitions were required to cover the changes in most fertility hormones over this period. An exception to this was prolactin, for which no sex partition and only 3 age partitions were necessary.CONCLUSIONS: This comprehensive database of pediatric reference intervals for fertility hormones will be of global benefit and should lead to improved diagnosis of pediatric endocrinopathies. The new database will need to be validated in local populations and for other immunoassay platforms as recommended by the Clinical Laboratory Standards Institute.

1 November 2009 in Obesity
Verified
Journal Article
Closed access
PDF file
AKAaron P. Kennedy
Aaron P. Kennedy
JSJennifer Shea
Jennifer Shea
GSGuang Sun
Guang Sun

1 March 2011 in Obesity
Verified
Journal Article
Closed access
PDF file
JSJennifer Shea
Jennifer Shea
EREdward W. Randell
Edward W. Randell
GSGuang Sun
Guang Sun

1 January 2014
Verified
Book Chapter
Closed access
JSJennifer Shea
Jennifer Shea
PWPui-Yuen Wong
Pui-Yuen Wong
YCYu Chen
Yu Chen

5 March 2013 in PLOS ONE
Verified
Journal Article
Open access
PDF file
FCFarrell Cahill
Farrell Cahill
MSMariam Shahidi
Mariam Shahidi
JSJennifer Shea
Jennifer Shea
DWDanny Wadden
Danny Wadden
WGWayne Gulliver
Wayne Gulliver
GSGuang Sun
Guang Sun
Magnesium plays a role in glucose and insulin homeostasis and evidence suggests that magnesium intake is associated with insulin resistance (IR). However, data is inconsistent and most studies have not adequately controlled for critical confounding factors. The study investigated the association between magnesium intake and IR in normal-weight (NW), overweight (OW) and obese (OB) along with pre- and post- menopausal women. A total of 2295 subjects (590 men and 1705 women) were recruited from the CODING study. Dietary magnesium intake was computed from the Willett Food Frequency Questionnaire (FFQ). Adiposity (NW, OW and OB) was classified by body fat percentage (%BF) measured by Dual-energy X-ray absorptiometry according to the Bray criteria. Multiple regression analyses were used to test adiposity-specific associations of dietary magnesium intake on insulin resistance adjusting for caloric intake, physical activity, medication use and menopausal status. Subjects with the highest intakes of dietary magnesium had the lowest levels of circulating insulin, HOMA-IR, and HOMA-ß and subjects with the lowest intake of dietary magnesium had the highest levels of these measures, suggesting a dose effect. Multiple regression analysis revealed a strong inverse association between dietary magnesium with IR. In addition, adiposity and menopausal status were found to be critical factors revealing that the association between dietary magnesium and IR was stronger in OW and OB along with Pre-menopausal women. The results of this study indicate that higher dietary magnesium intake is strongly associated with the attenuation of insulin resistance and is more beneficial for overweight and obese individuals in the general population and pre-menopausal women. Moreover, the inverse correlation between insulin resistance and dietary magnesium intake is stronger when adjusting for %BF than BMI.