Can linear regression model give reliable conclusions about the postoperative recovery? Bootstrap for case study in Mitic et al. 2007

Exposure to Volatile Organic Compounds May Contribute to Atopic Dermatitis in Adults

BACKGROUND

Volatile organic compounds (VOC) are major indoor air pollutants. Previous studies reported an association between VOC exposure and allergic diseases. Here, we aimed to explore the relationship between VOC exposure and atopic dermatitis (AD) in adults.

METHODS

We prospectively enrolled 31 adult AD patients and 11 healthy subjects as controls. Urine metabolite levels of VOCs, including 1.3-butadiene, acrylamide, benzene, toluene, and xylene, were all determined with liquid chromatography-mass spectrometry. The relationship between AD and log-transformed urine levels of VOC metabolites were examined using a multivariate linear regression model adjusted for age and sex. We also treated mouse bone marrow-derived cells (BMMCs) with 1,3-butadiene and toluene and measured the release of β-hexosaminidase.

RESULTS

Our results demonstrated that creatinine-corrected urine levels of N-Acetyl-S- (3,4-dihydroxybutyl)-L-cysteine (DHBMA), N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA), and N-Acetyl-S-(benzyl)-L-cysteine (BMA) were all elevated in AD patients compared with controls. In a multivariate linear regression model, creatinine-corrected urine levels of BMA (a toluene metabolite) and DHBMA (a 1,3-butadiene metabolite) appeared elevated in AD patients, although statistical significance was not reached after correction for multiple comparisons. In addition, 1,3-butadiene and toluene could stimulate BMMCs to degranulate as much as compound 48/80.

CONCLUSIONS

Some VOCs, such as 1,3-butadiene and toluene, might be associated with AD pathogenesis in adults.

Driver-Automated Vehicle Interaction in Mixed Traffic: Types of Interaction and Drivers' Driving Styles

OBJECTIVE

This study investigated drivers' subjective feelings and decision making in mixed traffic by quantifying driver's driving style and type of interaction.

BACKGROUND

Human-driven vehicles (HVs) will share the road with automated vehicles (AVs) in mixed traffic. Previous studies focused on simulating the impacts of AVs on traffic flow, investigating car-following situations, and using simulation analysis lacking experimental tests of human drivers.

METHOD

Thirty-six drivers were classified into three driver groups (aggressive, moderate, and defensive drivers) and experienced HV-AV interaction and HV-HV interaction in a supervised web-based experiment. Drivers' subjective feelings and decision making were collected via questionnaires.

RESULTS

Results revealed that aggressive and moderate drivers felt significantly more anxious, less comfortable, and were more likely to behave aggressively in HV-AV interaction than in HV-HV interaction. Aggressive drivers were also more likely to take advantage of AVs on the road. In contrast, no such differences were found for defensive drivers indicating they were not significantly influenced by the type of vehicles with which they were interacting.

CONCLUSION

Driving style and type of interaction significantly influenced drivers' subjective feelings and decision making in mixed traffic. This study brought insights into how human drivers perceive and interact with AVs and HVs on the road and how human drivers take advantage of AVs.

APPLICATION

This study provided a foundation for developing guidelines for mixed transportation systems to improve driver safety and user experience.

Prevalence and Family Determinants of Geriatric Depression Among Elderly People in Elderly Support Groups in Rwanda

Background

The 1994 Tutsi genocide in Rwanda significantly impacted family structure, with many people growing old alone and lacking social bonds and connections with family members. However, little is known about the contribution of the family environment to geriatric depression which was highlighted by WHO as a psychological problem with a 10% to 20% prevalence rate among the elderly worldwide. This study aims to investigate geriatric depression and associated family determinants among the elderly in Rwanda.

Methods

With a community-based cross-sectional study design, we assessed geriatric depression (GD), quality-of-life enjoyment and satisfaction (QLES), family support (FS), loneliness, neglect, and attitude toward grief in a convenience sample of 107 participants (M=72.32, SD=8.79) aged between 60 and 95 years who were recruited from three groups of elderly people supported by the NSINDAGIZA organization in Rwanda. SPSS (version 24) was used for statistical data analysis; differences across various sociodemographic variables were tested for significance by an independent t-test; the relationship between study variables was tested by Pearson correlation analysis; and multiple regression analysis was performed to model the contribution of independent variables to dependent variables.

Results

A total of 64.5% of the elderly scored above the threshold of the normal range of geriatric depression (SDS>49), with higher symptoms in women than in men. Multiple regression analysis indicated that family support and quality-of-life enjoyment and satisfaction were contributors to geriatric depression in the participants.

Conclusion

Geriatric depression was relatively common in our participants. It is associated with the quality of life and family support received. Hence, adequate family-based interventions are needed to improve the well-being of geriatric people in their respective families.

Analysis of Factors Affecting the Body Mass Index in a National Sample of Iranian Children and Adolescents: Bootstrapping Regression

Background

This study aims to evaluate the effect of some factors, including birth weight, sex, age, waist circumference, family history of obesity, as well as some lifestyle factors as frequency of breakfast days and physical activity, on the body mass index among a nationally representative sample of Iranian children and adolescents by using bootstrapping regression.

Materials and Methods

This study was conducted as the third survey of a school-based surveillance system (CASPIAN-III study). Total participants were 5570 school students, aged 10-18 years, selected by multistage random cluster sampling from urban and rural areas of 27 provinces of Iran. Multiple linear regressions was used to evaluate the effect of various factors on obesity, but in our data the assumptions of this model violated, and possible solutions were not appropriate, therefore the bootstrapping regression based on the observations and errors resampling approaches was used as an alternative.

Results

The tests of significance showed that the effects of sex, age, waist circumference, family history obesity and frequency of breakfast days were clearly significant (P < 0.001). The effect of vigorous level of physical activity was significant in comparison to mild physical activity (P = 0.01). In comparison to low birth weight, medium and high birth weight had significant effect on obesity.

Conclusions

Bootstrap method is preferable in linear regression because of some theoretical properties like having any distributional assumptions on the residuals and hence allows for inference even if the errors do not follow normal distribution or constant error variance.