Commuting Analysis in a Small Metropolitan Area - A Case Study of Bowling Green/Warren County, Kentucky

In previous studies of urban commutes, little attention has been paid to commute patterns in smaller urban areas. In this study, the concept of excess commute (EC) is applied to the Bowling Green-Warren County Metropolitan Statistical Area (BGWCMSA) in Kentucky. EC quantifies the portion of commute distance explained by the overall spatial separation of jobs and households. Results in this thesis research show that approximately 65% of commute distance by persons driving alone in the study area can be explained by the physical locations of homes relative to job sites as well as the existing roadway network, leaving an EC of 35% attributable to other factors. This EC of 35% is less than those of larger metropolitan areas in previous studies, suggesting that EC does decline with the sizes of urban areas to a certain degree. I low ever, the analysis of used commute potential (UCP) reveals that workers in the study area on average use a higher percentage of its total potential in comparison to larger cities. A possible explanation is that BGWCMSA is the regional employment center for south central Kentucky. There is a relatively large percentage of commuters living in the rural areas and the surrounding counties, causing a significant number of commutes with long distances. In addition, the analysis of job distribution shows that BGWCMSA has developed a number of specialized employment subcenters. With some subcenters located in the outskirts of the urbanized area, cross-commuting between suburbs also accounts for a substantial portion of the overall commutes in the region, leading to trips with longer distances as well. Both EC and UCP are also applied to the data disaggregated by household income levels to determine if workers with lower household income are more likely to be spatially separated from their workplaces, necessitating longer commutes. In the disaggregate analysis, all workers in the study area are assigned to four household income groups; 1) those with less than $30,000 annually; 2) between$30,000 and $49,999 annually; 3) between$50,000 and $74,999; and 4)$75,000 or more. Results show that it is not the first income group but the second and third income groups of workers that, on average, travel the longest distances with the highest EC and UCP. Workers in the $75,000 or more income group are, on average, the most efficient commuters by both excess commute and commute potential measures. In summary, this work, by highlighting the presence of excess commuting methodology in the smallest metropolitan statistical area yet studied, provides an impetus for planning agencies in smaller urban areas to obviate the negative effects inherent in automobile use. As cities grow, there is a unique opportunity to develop policies and programs to reduce nonspatial factors that affect the amount of time and distance spent in the automobile in the journey to work (JTW). Nonspatial factors that may be impacted by policies include congestion, lack of transit, and parking availability, among many others. The prevailing trend of urban growth in recent decades is the emergence of employment subcenters on the urban fringe, with some being very specialized in employment type and others of a more mixed nature. Results from this stud} confirm the findings of previous work that smaller urban areas are more likely to use more of their commute capacity and are thus less efficient than larger ones, due to the lack of exurban centers with mixed land use types. Specifically, where there is already a regional jobshousing imbalance, the lack of such centers exacerbates the condition of longer commutes and higher UCP. This suggests that the placement and type of employment centers are critical to the commuting characteristics of a given area

Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction.

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability

Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction

International audienceWhereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research