Changes in quantity and sources of dietary fiber from adopting healthy low-fat vs. Healthy low-carb weight loss diets: Secondary analysis of dietfits weight loss diet study

The daily intake of dietary fiber is well below the recommended levels in the US. The effect of adopting a low-fat vs. a low-carbohydrate weight loss diet on fiber intake is of interest but not well-documented, especially when both approaches promote high-quality food choices. The objective of this paper is to compare the quantity and sources of dietary fiber between a healthy low-fat (HLF) vs. healthy low-carbohydrate (HLC) diet group when consumed over 12 months in a weight loss diet study. In this secondary analysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study, the amount and sources of dietary fiber were examined in generally healthy adults, 18–50 years of age, Body Mass Index (BMI) 28–40 kg/m2, randomized to HLF or HLC for 12 months, who had available 24-h recalls at 0 (n = 609), 3 (n = 549), 6 (n = 491), and 12 (n = 449) months. The dietary intake was estimated by the Nutrition Data System for Research (NDS-R). The sources of fiber were determined for the major food groups. Significantly more total dietary fiber was consumed by HLF at every post-randomization time point, and, at 12 m, was 23.04 ± 9.43 g vs. 18.61 ± 8.12 g for HLF vs. HLC, respectively, p \u3c 0.0001. In both diet groups at 12 months, the highest amount of dietary fiber came from non-starchy vegetables (4.13 ± 3.05 g and 5.13 ± 3.59 g). The other primary sources of fiber at 12 months for the HLF group were from whole grains (3.90 ± 3.13 g) and fruits (3.40 ± 2.87 g), and, for the HLC group, were from plant protein and fat sources, such as nuts and seeds, their butters, and avocados (2.64 ± 2.64 g). In the DIETFITS study, the difference in the total fiber intake for the HLF vs. HLC groups was more modest than expected. The HLC group consumed reasonably high amounts of fiber from high-protein and high fat plant-based sources

Development and evaluation of a novel dietary bisphenol A (BPA) exposure risk tool

Background: Exposure to endocrine disrupting chemicals such as bisphenol A (BPA) is primarily from the diet through canned foods. Characterizing dietary exposures can be conducted through biomonitoring and dietary surveys; however, these methods can be time-consuming and challenging to implement. Methods: We developed a novel dietary exposure risk questionnaire to evaluate BPA exposure and compared these results to 24-hr dietary recall data from participants (n = 404) of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study, a dietary clinical trial, to validate questionnaire responses. High BPA exposure foods were identified from the dietary recalls and used to estimate BPA exposure. Linear regression models estimated the association between exposure to BPA and questionnaire responses. A composite risk score was developed to summarize questionnaire responses. Results: In questionnaire data, 65% of participants ate canned food every week. A composite exposure score validated that the dietary exposure risk questionnaire captured increasing BPA exposure. In the linear regression models, utilizing questionnaire responses vs. 24-hr dietary recall data, participants eating canned foods 1–2 times/week (vs. never) consumed 0.78 more servings (p \u3c 0.001) of high BPA exposure foods, and those eating canned foods 3+ times/week (vs. never) consumed 0.89 more servings (p = 0.013) of high BPA exposure foods. Participants eating 3+ packaged items/day (vs. never) consumed 62.65 more total grams of high BPA exposure food (p = 0.036). Conclusions: Dietary exposure risk questionnaires may provide an efficient alternative approach to 24-hour dietary recalls to quantify dietary BPA exposure with low participant burden. Trial registration: The trial was prospectively registered at clinicaltrials.gov as NCT01826591 on April 8, 2013

Practices for Sharing Drug Recognition Expert Resources

This report presents the findings of research to understand how State and local law enforcement agencies have successfully shared resources for drug recognition experts (DREs). Sharing DRE resources refers to making DREs from one agency or jurisdiction available to other nearby agencies or jurisdictions to respond to DRE callout requests. The researchers conducted a literature review and interviewed DRE coordinators from five State and three law enforcement agencies to learn more about their DRE callout programs. The report summarizes key aspects of successfully sharing DRE resources and includes examples demonstrating how agencies share DREs and respond to callouts. Agencies and jurisdictions of all sizes and geographic localities can use this report to enhance existing DRE callout programs or implement new programs that involve sharing DREs across multiple organizations

Novel <i>IRF6 </i>mutations in families with Van Der Woude syndrome and popliteal pterygium syndrome from sub-Saharan Africa

Orofacial clefts (OFC) are complex genetic traits that are often classified as syndromic or nonsyndromic clefts. Currently, there are over 500 types of syndromic clefts in the Online Mendelian Inheritance in Man (OMIM) database, of which Van der Woude syndrome (VWS) is one of the most common (accounting for 2% of all OFC). Popliteal pterygium syndrome (PPS) is considered to be a more severe form of VWS. Mutations in the IRF6 gene have been reported worldwide to cause VWS and PPS. Here, we report studies of families with VWS and PPS in sub-Saharan Africa. We screened the DNA of eight families with VWS and one family with PPS from Nigeria and Ethiopia by Sanger sequencing of the most commonly affected exons in IRF6 (exons 3, 4, 7, and 9). For the VWS families, we found a novel nonsense variant in exon 4 (p.Lys66X), a novel splice-site variant in exon 4 (p.Pro126Pro), a novel missense variant in exon 4 (p.Phe230Leu), a previously reported splice-site variant in exon 7 that changes the acceptor splice site, and a known missense variant in exon 7 (p.Leu251Pro). A previously known missense variant was found in exon 4 (p.Arg84His) in the PPS family. All the mutations segregate in the families. Our data confirm the presence of IRF6-related VWS and PPS in sub-Saharan Africa and highlights the importance of screening for novel mutations in known genes when studying diverse global populations. This is important for counseling and prenatal diagnosis for high-risk families

Dictator Games: A Meta Study

Over the last 25 years, more than a hundred dictator game experiments have been published. This meta study summarizes the evidence. Exploiting the fact that most experiments had to fix parameters they did not intend to test, the meta study explores a rich set of control variables for multivariate analysis. It shows that Tobit models (assuming that dictators would even want to take money) and hurdle models (assuming that the decision to give a positive amount is separate from the choice of amount, conditional on giving) outperform mere meta-regression and OLS

Do Genotype Patterns Predict Weight Loss Success for Low Carb vs. Low Fat Diets?

Genomics research is advancing rapidly, and links between genes and obesity continue to be discovered and better defined. A growing number of single nucleotide polymorphisms (SNPs) in multiple genes have been shown to alter an individual's response to dietary macronutrient composition. Based on prior genetic studies evaluating the body's physiological responses to dietary carbohydrates or fats, the investigators identified multi-locus genotype patterns with SNPs from three genes (FABP2, PPARG, and ADRB2): a low carbohydrate-responsive genotype (LCG) and a low fat-responsive genotype (LFG). In a preliminary, retrospective study (using the A TO Z weight loss study data), the investigators observed a 3-fold difference in 12-month weight loss for initially overweight women who were determined to have been appropriately matched vs. mismatched to a low carbohydrate (Low Carb) or low fat (Low Fat) diet based on their multi-locus genotype pattern. The primary objective of this study is to confirm and expand on the preliminary results and determine if weight loss success can be increased if the dietary approach (Low Carb vs. Low Fat) is appropriately matched to an individual' s genetic predisposition (Low Carb Genotype vs. Low Fat Genotype) toward those diets

Detection of Outbreak Signals Using R

Regression analysis is used to fit a periodic model to weekly disease counts for reportable diseases in Missouri.  These trigonometric models are then used to obtain upper control limits for the number of cases that would lead to an outbreak signal.  The methods, including graphics, are implemented in the open source statistical package R

Detection of Outbreak Signals Using R

Regression analysis is used to fit a periodic model to weekly disease counts for reportable diseases in Missouri.  These trigonometric models are then used to obtain upper control limits for the number of cases that would lead to an outbreak signal.  The methods, including graphics, are implemented in the open source statistical package R

Association of dietary adherence and dietary quality with weight loss success among those following low-carbohydrate and low-fat diets: a secondary analysis of the DIETFITS randomized clinical trial

BackgroundEating a high-quality diet or adhering to a given dietary strategy may influence weight loss. However, these 2 factors have not been examined concurrently for those following macronutrient-limiting diets.ObjectiveTo determine whether improvement in dietary quality, change in dietary macronutrient composition, or the combination of these factors is associated with differential weight loss when following a healthy low-carbohydrate (HLC) or healthy low-fat (HLF) diet.DesignGenerally healthy adults were randomly assigned to HLC or HLF diets for 12 mo (n = 609) as part of a randomized controlled weight loss study. Participants with complete 24-h dietary recall data at baseline and 12-mo were included in this secondary analysis (total N = 448; N = 224 HLC, N = 224 HLF). Participants were divided into 4 subgroups according to 12-mo change in HEI-2010 score [above median = high quality (HQ) and below median = low quality (LQ)] and 12-mo change in macronutrient intake [below median = high adherence (HA) and above median = low adherence (LA) for net carbohydrate (g) or fat (g) for HLC and HLF, respectively]. Baseline to 12-mo changes in mean BMI were compared for those in HQ/HA, HQ/LA, LQ/HA subgroups with the LQ/LA subgroup within HLC and HLF.ResultsFor HLC, changes (95 % confidence level [CI]) in mean BMI were -1.15 kg/m2 (-2.04, -0.26) for HQ/HA, -0.30 (-1.22, 0.61) for HQ/LA, and -0.80 (-1.74, 0.14) for LQ/HA compared with the LQ/LA subgroup. For HLF, changes (95% CI) in mean BMI were -1.11kg/m2 (-2.10, -0.11) for HQ/HA, -0.26 (-1.26, 0.75) for HQ/LA, and -0.66 (-1.74, 0.41) for LQ/HA compared with the LQ/LA subgroup.ConclusionWithin both HLC and HLF diet arms, 12-mo decrease in BMI was significantly greater in HQ/HA subgroups relative to LQ/LA subgroups. Neither HQ nor HA alone were significantly different than LQ/LA subgroups. Results of this analysis support the combination of dietary adherence and high-quality diets for weight loss.Clinical trial registryclinicaltrials.gov (Identifier: NCT01826591)