Relationship between housing insecurity, diabetes processes of care, and self-care behaviors

Background The aim of this analysis was to examine the influence of housing insecurity on diabetes processes of care and self-care behaviors and determine if that relationship varied by employment status or race/ethnicity. Methods Using nationally representative data from the Behavioral Risk Factor Surveillance System (2014-2015), 16,091 individuals were analyzed for the cross-sectional study. Housing insecurity was defined as how often respondents reported being worried or stressed about having enough money to pay rent/mortgage. Following unadjusted logistic models testing interactions between housing insecurity and either employment or race/ethnicity on diabetes processes of care and self-care behaviors, stratified models were adjusted for demographics, socioeconomic status, health insurance status, and comorbidity count. Results 38.1% of adults with diabetes reported housing insecurity. Those reporting housing insecurity who were employed were less likely to have a physicians visit (0.58, 95%CI 0.37,0.92), A1c check (0.45, 95%CI 0.26,0.78), and eye exam (0.61, 95%CI 0.44,0.83), while unemployed individuals were less likely to have a flu vaccine (0.84, 95%CI 0.70,0.99). Housing insecure White adults were less likely to receive an eye exam (0.67, 95%CI 0.54,0.83), flu vaccine (0.84, 95%CI 0.71,0.99) or engage in physical activity (0.82, 95%CI 0.69,0.96), while housing insecure Non-Hispanic Black adults were less likely to have a physicians visit (0.56, 95%CI 0.32,0.99). Conclusions Housing insecurity had an influence on diabetes processes of care and self-care behaviors, and this relationship varied by employment status and race/ethnicity. Diabetes interventions should incorporate discussion surrounding housing insecurity and consider differences in the impact by demographic factors on diabetes care.

The Association Between Dietary Antioxidant Micronutrients and Cardiovascular Disease in Adults in the United States: A Cross-Sectional Study

Background: Antioxidant micronutrients represent an important therapeutic option for the treatment of oxidative stress-associated cardiovascular diseases (CVDs). However, few studies have evaluated the relationship between the levels of multiple dietary antioxidants and CVDs.Objective: The study therefore aimed to evaluate associations between dietary antioxidants and total and specific CVDs among a nationally representative sample of adults in the US.Design: In total, 39,757 adults (>20 years) were included in this cross-sectional study from the 2005–2018 National Health and Nutrition Examination Survey. We analyzed dietary recall of 11 antioxidant micronutrients in this population. Multivariate logistic and weighted quantile sum (WQS) regression were both applied to examine the relationships between these antioxidants, alone and in combination, with the prevalence of all CVDs and specific CVDs. The linearity of these correlations was also explored using restricted cubic spline (RCS) regression.Results: Multivariate logistic models showed that, compared with the lowest quartile, the levels of 11 antioxidants in the highest quartile were independently associated with decreased total CVD (all P < 0.05). The WQS index showed that, when considered together, the 11 micronutrients were negatively correlated with total CVD (P < 0.001) and five specific CVDs (all P < 0.05), and selenium had the strongest association (weight = 0.219) with total CVD. Moreover, the RCS model demonstrated that iron, zinc and copper were all negatively and non-linearly correlated with total CVD, while the eight other micronutrients had non-significant, linear, negative relationships with total CVD (P for non-linearity >0.05). A piecewise binary logistic regression analysis showed that the inflection points in the relationships between CVD and iron, zinc and copper were 7.71, 6.61, and 0.74 mg/day, respectively.Conclusions: Our findings suggested that high levels of combined dietary antioxidant micronutrients are associated with decreased prevalence of CVDs, and that selenium has the greatest contribution to this association.

Knowledge, Attitudes, and Common Practices of Livestock and Poultry Veterinary Practitioners Regarding the AMU and AMR in Bangladesh

Current evidence indicates that more than half of all antimicrobials are used in the animal food-producing sector, which is considered a significant risk factor for the development, spread, and existence of antimicrobial resistance (AMR) pathogens in animals, humans, and the environment. Among other factors, clinical etiology and the level of knowledge, attitudes, and practices (KAP) of veterinarians are thought to be responsible for inappropriate prescriptions in the animal-source protein production sector in lower-resource settings like Bangladesh. We performed this cross-sectional study to assess factors associated with veterinarians’ antimicrobial prescription behavior and their KAP on antimicrobial use (AMU) and AMR in Bangladesh. Exploratory and multivariate logistic models were used to describe an association between knowledge, attitudes, and practices of AMU and AMR and demographic characteristics of veterinarians. The results demonstrated that when selecting an antimicrobial, there was no to minimal influence of culture and susceptibility tests and patients’ AMU history but moderate to high influence of the farmer’s economic condition and drug instructions among the veterinarians. The results also demonstrated that more than half of the veterinarians had correct KAP regarding AMU and AMR, while the rest had moderate or lower levels of KAP. The factor score analysis revealed that age, level of education, years of experience, gender, and previous training on AMU and AMR were the key influencing factors in their level of KAP. Adjusted logistic regression analysis showed that respondents’ age, current workplace, and previous training on AMU and AMR had a positive association with increased KAP. Considering the results, it is imperative to include AMR issues on vet curricula, and to provide post-education training, awareness campaigns, easy access to, and dissemination of AMR resources. Increasing the veterinary services to the outreach areas of the country and motivating veterinarians to follow the national AMR guidelines could be some other potential solutions to tackle the over-prescriptions of antimicrobials.

Sustainable Intensification Practices Reduce Food Deficit for the Best- and Worst-Off Households in Ethiopia and Mozambique

An adequate food supply is widely recognized as a necessary condition for social development as well as a basic human right. Food deficits are especially common among semi-subsistence farming households in eastern and southern Africa and farm productivity is widely regarded as the locus for enhancing household food outcomes. However, knowledge gaps surrounding benefits associated with climate smart, productivity-enhancing technologies require attention. This study evaluates benefits associated with sustainable intensification farm management practices (crop residue retention, minimum tillage, manure application and use of herbicides, pesticides, fertilizer, and improved seeds) for household calorie and protein supplies and demonstrates their scope across households with high-, moderate- and low- likelihoods of calorie and protein deficits. Household-level calorie and protein deficits were estimated from survey data on food production, acquisition and consumption for households in Ethiopia and Mozambique. Multinomial logistic models were used to identify drivers of household food deficit status and logistic model trees established “rules of thumb” to classify households by food deficit status as low, moderate or high likelihood. In Ethiopia, especially wet seasons were associated with a high likelihood of a food deficit while especially dry seasons were associated with a high likelihood of food deficit in Mozambique. The practices associated with sustainable intensification and related technologies substantially enhanced food outcomes in groups with a high- and a low-likelihood of food deficit, and associated benefits were high for the best-off households. Benefits associated with sustainable intensification technologies were not observed for households with a moderate likelihood of a food deficit and some technologies even increased risk. The sustainable intensification practices assessed here were associated with improved food outcomes yet benefits were limited in scope for households of intermediate status. Thus, there is a need to expand the technical options available to reduce food deficit.

Application of Value Stream Mapping in E-Commerce: A Case Study on an Amazon Retailer

In recent years, the e-commerce market has grown significantly, and the online retail market has become very competitive. Online retailers strive to improve their supply chain operations to reduce costs and to improve customer satisfaction. Value stream mapping (VSM), a tool created by the lean production movement to identify and reduce errors, losses, and lead time and to improve value-added activities, has been proven to be effective in many manufacturing processes. In this study, we investigate the application of value stream mapping (VSM) in the supply chain of an e-commerce retailer on Amazon. By visualizing the entire supply chain with VSM, the waste that is produced during the delivery process from the retailer to the customer was identified. The five whys method was then applied to find the root cause of the waste. Furthermore, a scoring method was developed to evaluate and compare two different supply chain logistic models to identify a strategy for improvement. This study provides a systematic methodology to understand, evaluate, and improve the entire e-commerce supply chain process utilizing VSM. It was demonstrated that the methodology could improve supply chain management efficiency, customer satisfaction, and cost reduction.

Examining the Robustness of the Graded Response and 2-Parameter Logistic Models to Violations of Construct Normality

When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait (θ) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal θ. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed distribution where the construct is low for most people, medium for some, and high for few. Failure to account for nonnormality may compromise the validity of inferences and conclusions. Although corrections have been developed to account for nonnormality, these methods can be computationally intensive and have not yet been widely adopted. Previous research has recommended implementing nonnormality corrections when θ is not “approximately normal.” This research focused on examining how far θ can deviate from normal before the normality assumption becomes untenable. Specifically, our goal was to identify the type(s) and degree(s) of nonnormality that result in unacceptable parameter recovery for the graded response model (GRM) and 2-parameter logistic model (2PLM).

The Effect of Test Length on the Accuracy of Estimating Ability Parameter in the Two- and Three-Parameter Logistic Models: Comparison by Using the Bayesian Method of Expected Prior Mode and Maximum Likelihood Estimation

This study aims to compare the effect of test length on the degree of ability parameter estimation in the two-parameter and three-parameter logistic models, using the Bayesian method of expected prior mode and maximum likelihood. The experimental approach is followed, using the Monte Carlo method of simulation. The study population consists of all subjects with the specified ability level. The study includes random samples of subjects and of items. Results reveal that estimation accuracy of the ability parameter in the two-parameter logistic model according to the maximum likelihood method and the Bayesian method increases with the increase in the number of test items. Results also show that with long and average length tests, the effectiveness is related to the maximum likelihood method and to all conditions of the sample size, whereas in short tests, the Bayesian method of prior mode outperformed in all conditions. Results indicate that the increase of the ability parameter in the three-parameter logistic model increases with the increase of test items number. The Bayesian method outperforms with respect to the accuracy of estimation at all conditions of the sample size, whereas in long tests the maximum likelihood method outperforms at all different conditions. Received: 17 September 2021 / Accepted: 24 November 2021 / Published: 3 January 2022

Analysis of safety impact of paved shoulder width on Czech secondary roads

Traffic safety is influenced, among other factors, by characteristics of the roads, which include the width of the shoulder. Shoulder width was noted to have a large effect on crash frequency, as well as on traffic speed. In this paper, we focused on paved shoulders. Previous studies confirmed that increasing the width of the paved shoulder is associated with a decrease in crash frequency. However, wider shoulders may encourage higher driving speed, which is related to an increase of impact speed and crash severity – this issue was hypothesized, but not statistically investigated. Thus, conclusions based on crashes and speeds contradict each other, and there is no simple answer to the question of the safety impact of wide shoulders. To address this gap, we analyzed a sample of two most typical categories of Czech secondary roads, which differ only in the paved shoulder width (S9.5 roads with 0.75m-wide shoulder, and S11.5 roads with 1.75m-wide shoulder) and thus present a suitable example for studying the safety impact of paved shoulder width. We used generalized linear models of crash frequency, and multinomial logistic models of crash severity (separately for single-vehicle and multi-vehicle crashes), as well as a statistical test of differences in speed for the two road categories. The results showed that: Firstly, there were fewer crashes on S11.5 roads compared to S9.5 roads; this was true for both single-vehicle and multi-vehicle crashes. Secondly, single-vehicle crashes on S11.5 roads were more severe compared to S9.5 roads; the change of severity in multi-vehicle crashes was not statistically significant. Thirdly, driving speeds on S11.5 roads were approx. by 7 km/h higher compared to S9.5 roads. These findings support the hypothesis of an association between wider shoulders, higher speeds, and increased crash severity, especially in the case of single-vehicle crashes. As a practical solution, various speed management measures, including widening to a 2+1 road, may be recommended.