Open Access. Powered by Scholars. Published by Universities.®

Medicine and Health Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Endocrinology, Diabetes, and Metabolism

Manuscripts, Articles, Book Chapters and Other Papers

Obesity

Articles 1 - 5 of 5

Full-Text Articles in Medicine and Health Sciences

Distinct Reproductive Phenotypes Segregate With Differences In Body Weight In Adolescent Polycystic Ovary Syndrome., Angie Chen-Patterson, Angelina Bernier, Tania S. Burgert, Vanessa Davis, Tazeena Khan, David Geller, Emily Paprocki, Rachana Shah, Selma F. Witchel, Camila Pereira-Eshraghi, Aviva B. Sopher, Melanie G. Cree, Laura C. Torchen Jan 2024

Distinct Reproductive Phenotypes Segregate With Differences In Body Weight In Adolescent Polycystic Ovary Syndrome., Angie Chen-Patterson, Angelina Bernier, Tania S. Burgert, Vanessa Davis, Tazeena Khan, David Geller, Emily Paprocki, Rachana Shah, Selma F. Witchel, Camila Pereira-Eshraghi, Aviva B. Sopher, Melanie G. Cree, Laura C. Torchen

Manuscripts, Articles, Book Chapters and Other Papers

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a heterogenous clinical syndrome defined by hyperandrogenism and irregular menses. In adult women with PCOS, discrete metabolic and reproductive subgroups have been identified. We hypothesize that distinct phenotypes can be distinguished between adolescent girls who are lean (LN-G) and girls with obesity (OB-G) at the time of PCOS diagnosis.

METHODS: Data were extracted from the CALICO multisite PCOS database. Clinical data collected at the time of diagnosis were available in 354 patients (81% with obesity) from 7 academic centers. Patients with body mass index (BMI) < 85th percentile for age and sex were characterized as lean (LN-G) and those with BMI percentile ≥ 95th percentile as obese (OB-G). We compared metabolic and reproductive phenotypes in LN-G and OB-G.

RESULTS: Reproductive phenotypes differed between the groups, with LN-G …


Progression Of Comorbidities In Youth With Overweight Or Obesity During The Covid-19 Pandemic., Erica Wee, Ashley K. Sherman, Safa Farrukh, Mark A. Clements, Kelsee Halpin, Yun Yan Sep 2023

Progression Of Comorbidities In Youth With Overweight Or Obesity During The Covid-19 Pandemic., Erica Wee, Ashley K. Sherman, Safa Farrukh, Mark A. Clements, Kelsee Halpin, Yun Yan

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Childhood obesity rates have continued to increase with the COVID-19 pandemic. However, data are limited on the impact of increasing obesity on associated comorbidities.

METHODS: We evaluated the progression of overweight- or obesity-associated comorbidities by investigating change in laboratory results pre-COVID-19 pandemic and post-COVID-19 pandemic onset in youth with overweight or obesity. We defined progression of comorbidities based on increase in category rather than absolute change in value.

RESULTS: HbA1c progression was seen in 19%, and LDL cholesterol progression was seen in 26%, as defined by categories. HbA1c progression and LDL cholesterol progression were significantly correlated. HbA1c and LDL …


Pediatric Growth Patterns In Youth-Onset Type 2 Diabetes Mellitus: Implications For Physiologically-Based Pharmacokinetic Models., Chelsea M. Hosey, Kelsee Halpin, Valentina Shakhnovich, Chengpeng Bi, Brooke Sweeney, Yun Yan, J Steven Leeder Apr 2022

Pediatric Growth Patterns In Youth-Onset Type 2 Diabetes Mellitus: Implications For Physiologically-Based Pharmacokinetic Models., Chelsea M. Hosey, Kelsee Halpin, Valentina Shakhnovich, Chengpeng Bi, Brooke Sweeney, Yun Yan, J Steven Leeder

Manuscripts, Articles, Book Chapters and Other Papers

An accurate understanding of the changes in height and weight of children with age is critical to the development of models predicting drug concentrations in children (i.e., physiologically-based pharmacokinetic models). However, curves describing the growth of a typical population of children may not accurately characterize growth of children with various conditions, such as obesity. Therefore, to develop height and weight versus age growth curves for youth who were diagnosed with type 2 diabetes, we extracted data from electronic medical records. Robust nonlinear models were parameterized to the equations describing height and weight versus age as defined by the Centers for …


Adapting The Diabetes Prevention Program For Low And Middle-Income Countries: Protocol For A Cluster Randomised Trial To Evaluate 'Lifestyle Africa'., Delwyn Catley, Thandi Puoane, Lungiswa Tsolekile, Ken Resnicow, Kandace Fleming, Emily A. Hurley, Joshua M. Smyth, Mara Z. Vitolins, Estelle V. Lambert, Naomi Levitt, Kathy Goggin Nov 2019

Adapting The Diabetes Prevention Program For Low And Middle-Income Countries: Protocol For A Cluster Randomised Trial To Evaluate 'Lifestyle Africa'., Delwyn Catley, Thandi Puoane, Lungiswa Tsolekile, Ken Resnicow, Kandace Fleming, Emily A. Hurley, Joshua M. Smyth, Mara Z. Vitolins, Estelle V. Lambert, Naomi Levitt, Kathy Goggin

Manuscripts, Articles, Book Chapters and Other Papers

Introduction: Low and middle-income countries like South Africa are experiencing major increases in burden of non-communicable diseases such as diabetes and cardiovascular conditions. However, evidence-based interventions to address behavioural factors related to these diseases are lacking. Our study aims to adapt the CDC's National Diabetes Prevention Program (DPP) within the context of an under-resourced urban community in Cape Town, South Africa.

Methods/analysis: The new intervention (Lifestyle Africa) consists of 17 weekly sessions delivered by trained community health workers (CHWs). In addition to educational and cultural adaptations of DPP content, the programme adds novel components of text messaging and …


Predictors Of Loss To Follow-Up Among Children With Type 2 Diabetes., Ashley Shoemaker, Peiyao Cheng, Robin L. Gal, Craig Kollman, William V. Tamborlane, Georgeanna J. Klingensmith, Mark A. Clements, Tamara S. Hannon, Rubina Heptulla, Joane Less, Jamie Wood, Pediatric Diabetes Consortium Jan 2017

Predictors Of Loss To Follow-Up Among Children With Type 2 Diabetes., Ashley Shoemaker, Peiyao Cheng, Robin L. Gal, Craig Kollman, William V. Tamborlane, Georgeanna J. Klingensmith, Mark A. Clements, Tamara S. Hannon, Rubina Heptulla, Joane Less, Jamie Wood, Pediatric Diabetes Consortium

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND/AIMS: Youth with type 2 diabetes (T2D) have poor compliance with medical care. This study aimed to determine which demographic and clinical factors differ between youth with T2D who receive care in a pediatric diabetes center versus youth lost to follow-up for >18 months.

METHODS: Data were analyzed from 496 subjects in the Pe-diatric Diabetes Consortium registry. Enrollment variables were selected a priori and analyzed with univariable and multivariable logistic regression models.

RESULTS: After a median of 1.3 years from enrollment, 55% of patients were lost to follow-up. The final model included age, race/ethnicity, parent education, and estimated distance to …