Improving traffic-related air pollution estimates by modelling minor road traffic volumes

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia. We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models’ performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman’s correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were − 0.001 (− 0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman’s correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data

Improving traffic-related air pollution estimates by modelling minor road traffic volumes

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia. We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models' performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman's correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were -0.001 (-0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman's correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data

Breastfeeding and the risk of dental caries: a systematic review and meta-analysis

Aim To synthesise the current evidence for the associations between breastfeeding and dental caries, with respect to specific windows of early childhood caries risk. Methods Systematic review, meta-analyses and narrative synthesis following searches of PubMed, CINAHL and EMBASE databases. Results Sixty-three papers included. Children exposed to longer versus shorter duration of breastfeeding up to age 12 months (more versus less breastfeeding), had a reduced risk of caries (OR 0.50; 95%CI 0.25, 0.99, I2 86.8%). Children breastfed > 12 months had an increased riskof caries when compared with children breastfed 12 months, those fed nocturnally or more frequently had afurther increased caries risk (five studies, OR 7.14; 3.14, 16.23, I2 77.1%). There was a lack of studies on children aged > 12 months simultaneously assessing caries risk in breastfed, bottle-fed and children not bottle or breastfed, alongside specific breastfeeding practices, consuming sweet drinks and foods, and oral hygiene practices limiting our ability to tease out the risks attributable to each. Conclusion Breastfeeding in infancy may protect against dental caries. Further research needed to understand the increased risk of caries in children breastfed after 12 month

Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status

Traffic-related air pollution (TRAP) is associated with lower cognitive function and diabetes in older adults, but little is known about whether diabetes status moderates the impact of TRAP on older adult cognitive function. We analysed cross-sectional data from 4141 adults who participated in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study in 2011–2012. TRAP exposure was estimated using major and minor road density within multiple residential buffers. Cognitive function was assessed with validated psychometric scales, including: California Verbal Learning Test (memory) and Symbol–Digit Modalities Test (processing speed). Diabetes status was measured using oral glucose tolerance tests. We observed positive associations of some total road density measures with memory but not processing speed. Minor road density was not associated with cognitive function, while major road density showed positive associations with memory and processing speed among larger buffers. Within a 300 m buffer, the relationship between TRAP and memory tended to be positive in controls (β = 0.005; p = 0.062), but negative in people with diabetes (β = −0.013; p = 0.026) and negatively associated with processing speed in people with diabetes only (β = −0.047; p = 0.059). Increased TRAP exposure may be positively associated with cognitive function among urban-dwelling people, but this benefit may not extend to those with diabetes

Boganmeldelser

Intet resum

Satori 2018

The Satori is a student literary publication that expresses the artistic spirit of the students of Winona State University. Student poetry, prose, and graphic art are published in the Satori every spring since 1970. The Satori 2018 editors are Sajda Omar (Editor-in-Chief), Kylie Hoff, Keyanna Hultman, Audrey Sitte, Elyse Hoffmann. Art Director and Designer by Elyse Hoffmann. The 2018 Faculty advisor is Dr. Elizabeth Oness, Professor of English.https://openriver.winona.edu/satori/1012/thumbnail.jp

Study protocol: Evaluating the impact of a rural Australian primary health care service on rural health

BACKGROUND: Rural communities throughout Australia are experiencing demographic ageing, increasing burden of chronic diseases, and de-population. Many are struggling to maintain viable health care services due to lack of infrastructure and workforce shortages. Hence, they face significant health disadvantages compared with urban regions. Primary health care yields the best health outcomes in situations characterised by limited resources. However, few rigorous longitudinal evaluations have been conducted to systematise them; assess their transferability; or assess sustainability amidst dynamic health policy environments. This paper describes the study protocol of a comprehensive longitudinal evaluation of a successful primary health care service in a small rural Australian community to assess its performance, sustainability, and responsiveness to changing community needs and health system requirements. METHODS/DESIGN: The evaluation framework aims to examine the health service over a six-year period in terms of: (a) Structural domains (health service performance; sustainability; and quality of care); (b) Process domains (health service utilisation and satisfaction); and (c) Outcome domains (health behaviours, health outcomes and community viability). Significant international research guided the development of unambiguous reliable indicators for each domain that can be routinely and unobtrusively collected. Data are to be collected and analysed for trends from a range of sources: audits, community surveys, interviews and focus group discussions. DISCUSSION: This iterative evaluation framework and methodology aims to ensure the ongoing monitoring of service activity and health outcomes that allows researchers, providers and administrators to assess the extent to which health service objectives are met; the factors that helped or hindered achievements; what worked or did not work well and why; what aspects of the service could be improved and how; what benefits have been realised and for whom; the level of community satisfaction with the service; and the impact of a health service on community viability. While the need to reduce the rural-urban health service disparity in Australia is pressing, the evidence regarding how to move forward is inadequate. This comprehensive evaluation will add significant new knowledge regarding the characteristics associated with a sustainable rural primary health care service

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression