Gestational Weight Gain: How to “Institute” New Guidelines

Presented as part of the Senior Scholars Program at the University of Massachusetts Medical School, May 3, 2010

Treatment and Management of Depression Symptoms in Pregnant Veterans: Varying Experiences of Mental Health Care in the Prenatal Period

Depression screening is recommended for all pregnant veterans; however, little is known on how often symptomatic women receive care, how depression treatment presents in practice, and whether women veterans are utilizing treatment during the appreciable perinatal period. Our sample included 142 pregnant veterans from 15 Veterans Health Administration (VA) medical facilities with Edinburgh Postnatal Depression Scale (EPDS) scores \u3e/=10. Sociodemographic characteristics, military service, health utilization, and pregnancy related factors were collected as part of a telephone survey. A majority of our sample (70%) had 1 or more mental health visits or antidepressant prescriptions during pregnancy. Women with a history of depression had more mental health visits and a higher percentage of antidepressant use before and during pregnancy than women without a history of depression. Pregnant women veterans without a history of depression may be less likely to receive care for depression during pregnancy. However, the majority of our veterans showing depression symptoms prenatally had at least one mental health visit or an antidepressant medication fill during their pregnancy window, suggesting that mental health care is readily available for women veterans

Effects of Dry Matter Content and Microbial Additive on Tifton 85 \u3ci\u3e(Cynodon dactylon ssp.)\u3c/i\u3e Wilted Silage Fermentation Parameters

The objective of this study was to evaluate the wilting and the addition of a bacterial-enzymatic additive effects on the fermentation parameters of Tifton 85 (Cynodon dactylon spp.) silage. Forage was stored as 326 kg bales wrapped with a plastic film. Treatments consisted of 5 forage dry matter levels (20-30%, 30-40%, 40-50%, 50 -60% e 60 a 70%) without additive and 3 dry matter levels (20-30%, 40-50%, e 60-70%) with additive. Buffered propionic acid solution was sprayed onto 60-70% dry matter bales, prior to wrapping, determining an additional treatment. Core samples were taken at 0, 6, 12 hours and 1, 2, 4, 8, 16, and 32 days after wrapping to establish silage pH and temperature trends. Field dry matter losses during the baling process were also evaluated. Bale weight with no additive decreased (364 kg to 254 kg) with increased forage DM content, which in turn resulted in lower bale bulk density (310 to 216 kg/m3 ). Lower field DM losses (281 to 177 kg/ha) were associated with higher forage DM content. Final silage pH and temperature peaks were increased at higher DM content, whereas the presence of microbial additive prevented temperature surge

Adipose Tissue Architecture and Gestational Weight Gain in Normoglycemic Pregnancies

Objective: To investigate histologic architecture of subcutaneous (SQAT) and visceral adipose tissue (VAT) growth in relationship to gestational weight gain (GWG). Epidemiological data suggest that SQAT expansion may be protective of obesity related co-morbidities, whereas VAT expansion is associated with Type-2 diabetes risk. We hypothesized that in normal gravidas, GWG would be associated with hypertrophy of SQAT and not VAT. Methods: A subset of subjects enrolled in the Pregnancy & Postpartum Observational Dietary Study (PPODS) and undergoing Cesarean delivery had SQAT (midline superior edge Pfannenstiel incision) and VAT (inferior omental periphery) biopsies after neonatal delivery, uterine closure and hemostasis achievement. Excised tissues were fixed and stained. Average adipocyte size and capillary density were assessed in 10 independent sections per AT depot per subject. GWG determined by the difference of weight at first visit and immediately postpartum (1-4 days post-op). GWG plotted vs mean SQAT or VAT adipocyte size. Results: Table illustrates general clinical characteristics of the 5 subjects. Figure A demonstrates SQAT and VAT mean adipocyte size with representative sections from patient E depicted above bar graphs representing means and SEM from 5 patients. SQ adipocytes were significantly larger than those from VAT. Significant positive correlation was noted between GWG and SQAT adipocyte size (Figure B), but not VAT adipocyte size (Figure C). Discussion: Preliminary results reveal that in normal pregnancies, GWG is associated with changes in SQAT but not VAT architecture, which reflects lipid accumulation. These results are consistent with the model that SQAT is specifically adapted for healthy lipid storage, and provides a basis for comparison between normal gravidas and those with GDM

A Comparison of Recruitment Strategies for a Long-Term Study at Two Maternal Stages: Effectiveness of Recruitment During Pregnancy vs. After Childbirth

Introduction. National Children’s Study (NCS) Provider Based Sampling (PBS) aims to conduct a pilot study to test cost, acceptability and feasibility of recruiting a representative sample of women/children using two recruitment strategies: through prenatal providers and hospitals. Methods. A sampling frame consisting of all providers of prenatal and delivery care within and 10-miles outside Worcester County, 16 provider and 3 hospital locations were selected as point of entry for study recruitment. During 1st prenatal care visits or post-delivery at these locations, face-to-face contact was utilized to: a) identify study eligibility and b) assess study recruitment. Preliminary Results. Certified Data Collectors made contact with prescreened women. Consent rates of women at prenatal provider locations were lower than the consent rates in hospital locations. On average, results have shown twice as many consents could be obtained per day at hospital locations than at provider locations. Preliminary Conclusions. Although both strategies utilized direct rapport, the two recruitment methods were associated with different consent rates. Consideration of preliminary results may lead one to consider recruitment after childbirth for several reasons: 1) greater likelihood of having opportunity to discuss study with the woman and partner from outset; 2) opportunity to check back with undecided women easily 3) longer periods to answer questions and conduct screening and consent; 4) support of nursing staff to foster participation; 5) daily presence of NCS staff; and 6) reality of infant’s birth to spur mother to consent. Recruitment during pregnancy visits may yield lower rates; further examination may be necessary to overcome challenges such as: 1) burden of adding recruitment session to often long and anxiety-laden1st prenatal visit; 2) need to develop rapport quickly during brief time periods; 3) making contact with potential participants outside of provider office when recruitment is not completed

Framing Hospital Engagement for the Recruitment of a Birth Cohort for the NCS: Lessons Learned for Ensuring Collaboration in Worcester County

In 2011, three designated NCS Study Centers began preparatory work for field implementation of a planned recruitment strategy called Provider Based Sampling (PBS). In each PBS primary sampling unit, three hospitals were selected to test the feasibility of recruiting a cohort of 125 women and their babies around delivery time. The selected hospitals for Worcester account for nearly 80% of County births and can be categorized into three distinct facility types and patient catchment areas: an academic medical center; a university-affiliated but independent community hospital; and a private for-profit community hospital with market share competitor of the academic medical center. Methods: We used tailored negotiations and engagement strategies to gain the cooperation and engagement of targeted hospitals/birthing centers. Preliminary Conclusions: The lessons learned from this exercise are:• Time to gain hospital engagement and clearance to initiate study activities ranges anywhere from 2 weeks to 2 months and depends largely upon the type of the institution, the profile of the Negotiator, and the nature of the scope of work.• A greater likelihood of hospital engagement in the NCS seems to be associated with the depth of existing relationships between the Study Center and targeted hospitals.• Thoughtful interactions and timely discussions with the key institutional stakeholders (either individually or in groups) are important to achieve collaboration and engagement.• Balancing sensitivity to clinical cultures and settings while preserving research integrity is essential for study implementation in busy hospital/clinical environments.• Planning for site compensation and/or the ability to support local clerical staff to help with study activities must be considered as a means to facilitate negotiations and site engagement.• Adequate resources must be planned for successful implementation and execution of research activities in settings (e.g community hospitals) unfamiliar with research activities.• Involvement of nursing personnel is crucial for successful implementation of any protocol

The Accuracy of Recalled versus Measured Pre-Pregnancy Weight for the Calculation of Pre-Pregnancy Body Mass Index

Background: In 2009, the Institute of Medicine (IOM) published gestational weight gain (GWG) guidelines with the goal of optimizing maternal and fetal outcomes. GWG recommendations are specific to pre-pregnancy body mass index (BMI): 28-40 lbs for underweight (UW; BMI2), 25-35 lbs for normal weight (NW; 18.5≤BMI/m2), 15-25 lbs for overweight (OW; 25 ≤BMI/m2), and 11-20 lbs for obese (OB; BMI≥30 kg/m2) women. With upwards of 50% of pregnancies in the U.S. unplanned, measured pre-pregnancy weight is often unavailable in clinical and research settings. Evaluating the accuracy of recalled pre-pregnancy weight early in prenatal care is important in order to establish accuracy of pre-pregnancy BMI calculations in order to counsel about GWG accurately. Objective: To examine differences in recalled versus measured pre-pregnancy weight and to examine factors associated with accuracy of recalled weights. Methods: Medical record review of 1,998 randomly selected pregnancies. Eligible women received prenatal care in faculty and resident clinics at UMass Memorial Health Care (UMMHC), delivered between January 2007 and December 2012, and had available both: (1) a measured weight within one year of conception and (2) a pre-pregnancy weight self-reported at first prenatal visit. Data were obtained from the UMMHC paper or electronic prenatal record and the Allscripts EMR. We calculated the difference in weights as recalled pre-pregnancy weight minus most recent measured weight within one year of conception. Subjects were excluded if they received care at a non-faculty or non-resident practice, charts not available after three separate retrieval attempts, both weights of interest not available, or if measured weight occurred at a prenatal visit for a prior pregnancy. For women with more than one pregnancy during the study time frame, one was randomly selected for inclusion in the analytic data set. Results: Of the 1,998 pregnancy charts reviewed, 400 records met eligibility criteria and were included in this analysis. Women were mean age 29.7 (SD: 6.2) years, 69.3% multigravida, 64.4% non-Hispanic white, 65.2% married, and 62.4% had a college or greater education. Based on recalled weight, 3.3% of women were underweight, 46.6% were normal weight, 25.9% overweight, and 24.2% obese. 63% received care in the faculty obstetric clinic. Recorded recalled weights were mean 2.4 (SD: 11.1) pounds lower than measured pre-pregnancy weight. This difference did not differ by age, location of care, pre-pregnancy BMI, marital status, race/ethnicity, primary language, gravity, education, or time between measured weight and conception, in unadjusted and adjusted models. For 88.7% of women, calculating pre-pregnancy BMI based on weight measured up to a year prior to conception or based on recalled pre-pregnancy weight reported at the first prenatal visit resulted in the same classification of pre-pregnancy BMI. Conclusion: Prenatal care providers may calculate pre-pregnancy BMIs using recalled pre-pregnancy weights early in prenatal care and use such calculated BMIs to accurately provide GWG recommendations regardless of demographic variables, gravity, or location of care