Search

Toxicology studies suggest that neonicotinoids may be associated with adiposity development via thyroid hormone disruption and increased oxidative stress. Prior epidemiological studies report mixed results for the association between neonicotinoids and adiposity measures. To examine the association between detectable concentrations of parent neonicotinoids (imidacloprid, acetamiprid, clothianidin) and neonicotinoid metabolites (5-hydroxy-imidacloprid, N -desmethyl-acetamiprid) with adiposity measures among US adults, and whether sex modifies the associations for neonicotinoid metabolites with adiposity. National Health and Nutrition Examination Survey (NHANES) 2015–2016 data was utilized to estimate covariate-adjusted associations between detectable neonicotinoids and fat mass index (FMI), lean mass index (LMI), waist circumference, body fat percentage, and body mass index (BMI) using multiple linear regression. We estimated incidence rate ratios (IRRs) for overweight or obese status with detectable neonicotinoid concentrations using Poisson's modified regression. Sampling strategies were accounted for in the regression models. Detectable levels of acetamiprid were associated with a decrease in FMI (β = −3.17 kg/m2, 95% CI [-4.79, −1.54]), LMI (β = −3.17 kg/m2, 95% CI [-5.17, −1.17]), body fat percentage (β = −4.41, 95% CI [-8.20, −0.62]), waist circumference (β = −9.80 cm, 95% CI [-19.08, −0.51]), and BMI (β = −3.88kg/m2, 95% CI [-7.25, −0.51]) among adults. In contrast, detectable levels of 5-hydroxy-imidacloprid were associated with greater rates of being overweight/obese (IRR = 1.11, 95% CI [1.04, 1.18)) and increased LMI (β = 0.67 kg/m2, 95% CI [0.04, 1.29]). Sex modified the association between N -desmethyl-acetamiprid and LMI (p int = 0.075) with a positive association among males (β = 1.14 kg/m2, 95% CI [0.38, 1.90]), and an insignificant inverse association in females. Sex also modified the association for N -desmethyl-acetamiprid with FMI (p int = 0.095) and body fat percentage (p int = 0.072), with suggestive evidence showing positive associations for males and inverse associations for females. Detectable concentrations of acetamiprid were inversely associated with adiposity, while there were mixed findings for 5-hydroxy-imidacloprid. Findings suggest sex differences, though results are not clear with regard to the directionality of the association by sex. • Neonicotinoid compounds may be associated with the pathogenesis of adiposity. • Acetamiprid was inversely associated with all the adiposity measures examined. • 5-hydroxy-imidacloprid was positively associated with being overweight/obese. • Sex differences were seen with N -desmethyl-acetamiprid and some adiposity measures. [ABSTRACT FROM AUTHOR]

Objective: Understanding the factors associated with senior food insecurity is key to understanding senior-specific needs to develop targeted interventions and ultimately lower the prevalence and the incidence of food insecurity. We aimed to systematically review published literature and summarise the associated factors of food insecurity in older adults in the USA.Design: We searched PubMed, Scopus, Web of science, EconLit and JSTOR databases for peer-reviewed articles published in English between January 2005 and September 2019 that assessed food security or its associated factors for US adults aged 60 years and older. After a two-step screening process, twenty articles were retained and included in the review.Setting: NA.Participants: NA.Results: The majority of studies were cross-sectional (70 %), consisted of data from one state (60 %), and had large sample sizes. Food-insecure individuals were more likely to be younger, less educated, Black or African American, female, a current smoker, low income, and self-report fair/poor health, have chronic conditions, and utilise government assistance programmes. Food insecurity was associated with medication non-adherence, poor mental health outcomes and limitations in physical functioning. Results were mixed for overweight/obesity status. There was no discernable pattern related to the consistency of findings by the assessed quality of the included studies.Conclusions: Food insecurity is a prevalent and pervasive issue for older adults. The numerous correlates identified suggest that interventions aimed at enhancing food and nutrition safety net and medication assistance programmes are warranted, and upstream, systemic-level interventions may be best suited to deal with the correlates of food insecurity. [ABSTRACT FROM AUTHOR]

The article reports on the results of a study regarding the implications of stigmatizing attitude prevalence among urban middle class in Maharashtra, India for HIV/AIDS education strategy. It states that there is correlation between the stigmatizing attitude and discrimination and the knowledge of people about HIV/AIDS.

Background: Currently, the capacity to provide buprenorphine treatment (BT) is not sufficient to treat the growing number of people in the United States with opioid use disorder (OUD). We sought to examine participant retention in care rates of primary care delivered BT programs and to describe factors associated with retention/attrition for participants receiving BT in this setting. Objectives: A PRISMA-guided search of various databases was performed to identify the articles focusing on efficacy of BT treatment and OUD. Method: A systematic literature search identified 15 studies examining retention in care in the primary care setting between 2002 and 2020. Random effects meta-regression were used to identify retention rates across studies. Results: Retention rates decreased across time with a mean 0.52 rate at one year. Several factors were found to be related to retention, including: race, use of other drugs, receipt of counseling, and previous treatment with buprenorphine. Conclusions: While we only investigate BT through primary care, our findings indicate retention rates are equivalent to the rates reported in the specialty care literature. More work is needed to examine factors that may impact primary care delivered BT specifically and differentiate participants that may benefit from care delivered in specialty over primary care as well as the converse. [ABSTRACT FROM AUTHOR]

• A low-cost portable e-nose was developed integrating nine different gas sensors. • The e-nose was able to effectively discriminate different beer samples from gases. • An accurate machine learning model was developed to predict beer aromas. • Another accurate machine learning model was able to predict sensory characteristics. • This method is cost-effective, rapid, reliable and accurate applicable for other foods. The assessment of aromas in beer is critical to assess its quality since it could be used as an indicator of contamination or faults, which will directly influence consumers' acceptability. Traditional techniques to evaluate aromas are time-consuming, require special training, costly equipment, and trained personnel. Therefore, this study aimed to develop a portable, low-cost electronic nose (e-nose) coupled with machine learning modeling to predict aromas in beer. Nine different gas sensors were used i) ethanol, ii) methane, iii) carbon monoxide, iv) hydrogen, v) ammonia/alcohol/benzene, vi) hydrogen sulfide, vii) ammonia, viii) benzene/alcohol/ammonia and ix) carbon dioxide. Output data were assessed for significant differences using ANOVA and least significant differences as post hoc test (α = 0.05). Two artificial neural network (ANN) models were also developed to predict i) the peak area of 17 different volatile aromatic compounds (Model 1) obtained from gas chromatography–mass spectroscopy (GC–MS) and ii) the intensity of ten sensory descriptors acquired from a sensory session with 12 trained panelists. Results from the ANOVA showed that there were significant differences between the samples used, which showed that the e-nose was able to discriminate samples. The resulting ANN models were highly accurate with correlation coefficients of R = 0.97 (Model 1) and R = 0.93 (Model 2). The combined method using the developed e-nose and the ANN models could be used by the industry as a low-cost, rapid, reliable and effective technique for beer quality assessment within the production line. This may also be calibrated for its use in other foods and beverages. [ABSTRACT FROM AUTHOR]

• No hops-derived volatiles were found in bottom fermented beer samples. • Top and bottom fermented beers presented more volatiles than spontaneous. • 4-Ethyguaiacol and trans-β-ionone were positive towards overall liking of beers. • Styrene had a negative and significant effect on consumer liking of beers. • A highly accurate machine learning model to predict acceptability was obtained. Identification of volatiles in beer is important for consumers acceptability. In this study, triplicates of 24 beers from three types of fermentation (top/bottom/spontaneous) were analyzed using Gas Chromatograph with Mass-Selective Detector (GC-MSD) employing solid-phase microextraction (SPME). Principal components analysis was conducted for each type of fermentation. Multiple regression analysis, and an artificial neutral network model (ANN) were developed with the peak-areas of 10 volatiles to evaluate/predict aroma, flavor and overall liking. There were no hops-derived volatiles in bottom-fermentation beers, but they were present in top and spontaneous. Top and spontaneous had more volatiles than bottom-fermentation. 4-Ethyguaiacol and trans-β-ionone were positive towards aroma, flavor and overall liking. Styrene had a negative effect on aroma, flavor and overall liking. An ANN model with high accuracy (R = 0.98) was obtained to predict aroma, flavor and overall liking. The use of SPME-GC-MSD is an effective method to detect volatiles in beers that contribute to acceptability. [ABSTRACT FROM AUTHOR]