RESEARCH

The goal of this project is to estimate the impact of bariatric surgery versus routine non-surgical care on the incidence of cancer (all types) in all severely obese patients (men and women).

This study uses electronic health records to determine the effects of sugary beverage taxes initiated in 4 Northern California cities compared with control cities in Northern and Southern California. Outcomes include weight change trajectories and prevalence of overweight and obesity among children and adults, and incidence of diabetes among adults with prediabetes. Pre-specified sub-analyses include examining differences by race/ethnicity, age groups, and neighborhood socioeconomic status.

The PORTAL network propose to create a cohort of adults who are overweight or obese, including those who have pre-diabetes or diabetes. The cohort development activity will demonstrate that the PORTAL network is able to meet the 10 criteria for a clinical data research network specified by PCORI.

Aims: 1. Determine maternal preconception weight trajectories associated with (a) recommended GWG (total and trimester-specific) and (b) lowest PPWR at 4-6 weeks and 12 months postpartum. 2. Determine maternal preconception weight trajectories associated with the lowest risk of adverse pregnancy outcomes: gestational diabetes, gestational hypertension/preeclampsia, and cesarean section. 3. Determine maternal preconception weight trajectories associated with the lowest risk of adverse child outcomes: preterm birth, size for gestational age at birth (small [SGA], appropriate, large [LGA]), infant growth trajectory, and BMI at 3 years of age.

The goal of this study is to examine the potential relationship between antibiotic use during pregnancy and pediatric weight problems. Particular focus is given to infants exposed to intrapartum Group B streptococcus prophylaxis and its impact on a child’s body weight.

To determine the feasibility of a primary care based, telephone counseling physical activity behavioral intervention for diabetics and prediabetics.

This project is part of a series of CDC studies to better understand the association between birth factors such as delivery mode labor or rupture of membrane, and exposure to intrapartum antibiotics and childhood weight gain.

Effective treatments for severe obesity are particularly needed in racial/ethnic minority populations. Rates of severe obesity are as high as 36% for middle-aged non-Hispanic black women compared to 16% for their white counterparts in the U.S. Research on bariatric weight loss outcomes among racial/ethnic minorities is limited. What evidence does exist suggests that black patients consistently lose less weight than whites over 2–3 years of follow-up. The evidence for differences between Hispanic and white or black bariatric patients is equivocal. Hispanic patients have been shown to lose more, less, or the same amount of weight as non-Hispanic black and white patients. Across studies, the disparities in % total weight loss vary from less than 2% to 10%. This variability is twice as much as the amount of weight loss considered clinically meaningful. This study will extend the work done by our team during the Bariatric Experience Long-Term (BELONG) study which addressed how self-reported behavioral, psychosocial, and perceived environmental factors predicted weight loss over 3 years following gastric bypass and sleeve. Patients (n = 1,975) were 41% Hispanic, 17% non-Hispanic black, and 37% non-Hispanic white. The proposed study will expand the work of BELONG by incorporating: 1) A focus on weight regain during 3-5 years after surgery; 2) measures shown to contribute to health disparities in severe obesity (vigilant coping style and internalized racism); and 3) innovative qualitative methods (photo-elicitation and ethnography) to understand the patient experience.

This project measured a large panel of pro- and anti-inflammatory adipokines in existing blood samples collected from BetaGene I and II study participants, combine these data with genome-wide genetic variation, dietary and physical activity information, and elucidate the pathophysiological pathways that underlie metabolic decline leading to type 2 diabetes.

This project aims to improve the accuracy of computationally identifying high-risk asthma patients, it’s assess potential impact on outcomes and to provide automated prediction result explanations for care management.