The impact of the Thai motorcycle transition on road traffic injury: Thai cohort study results

OBJECTIVES The aim of this study was to investigate the impact of motorcycle to car transitioning and urbanisation on traffic injury rates in Thailand. DESIGN Analysis of two consecutive surveys of a large national cohort study. SETTING Thailand. PARTICIPANTS The data derived from 57,154 Thai Cohort Study (TCS) participants who provided relevant data on both the 2005 and 2009 surveys. PRIMARY AND SECONDARY OUTCOME MEASURES Motorcycle and car traffic crash injury self-reported in 2009, with twelve months' recall. RESULTS In 2009, 5608(10%) participants reported a traffic crash injury. Most crashes involved a motorcycle (74%). Car access increased and motorcycle use decreased between 2005 and 2009. Among those who used a motorcycle at both time points, traffic injury incidence was 2.8 times greater compared to those who did not use a motorcycle at either time point. Multivariable logistic regression models were used to test longitudinal and cross sectional factors associated with traffic crash injury: in the adjusted model, cars were negatively and motorcycles positively associated with injury. Living in an urban area was not injury protective in the adjusted model of traffic crash injury. CONCLUSIONS Ongoing urbanisation in Thailand can be expected to lead to further reductions in road traffic injuries based on transition from motorcycles to cars in urban areas. Cities, however, do not provide an intrinsically safer traffic environment. To accommodate a safe transition to car use in Thailand, traffic infrastructural changes anticipating the growing car density in urban areas is warranted.The Thai Cohort Study is funded by the International Collaborative Research Grants Scheme with joint grants from the Wellcome Trust UK (GR071587MA) and the Australian National Health and Medical Research Council (NHMRC) (268055) and as a global health grant from the NHMRC (585426)

Predictors of injury mortality: findings from a large national cohort in Thailand

OBJECTIVE To present predictors of injury mortality by types of injury and by pre-existing attributes or other individual exposures identified at baseline. DESIGN 5-year prospective longitudinal study. SETTING Contemporary Thailand (2005-2010), a country undergoing epidemiological transition. PARTICIPANTS Data derived from a research cohort of 87 037 distance-learning students enrolled at Sukhothai Thammathirat Open University residing nationwide. MEASURES Cohort members completed a comprehensive baseline mail-out questionnaire in 2005 reporting geodemographic, behavioural, health and injury data. These responses were matched with national death records using the Thai Citizen ID number. Age-sex adjusted multinomial logistic regression was used to calculate ORs linking exposure variables collected at baseline to injury deaths over the next 5 years. RESULTS Statistically significant predictors of injury mortality were being male (adjustedOR 3.87, 95% CI 2.39 to 6.26), residing in the southern areas (AOR 1.71, 95% CI 1.05 to 2.79), being a current smoker (1.56, 95% CI 1.03 to 2.37), history of drunk driving (AOR 1.49, 95% CI 1.01 to 2.20) and ever having been diagnosed for depression (AOR 1.91, 95% CI 1.00 to 3.69). Other covariates such as being young, having low social support and reporting road injury in the past year at baseline had moderately predictive AORs ranging from 1.4 to 1.6 but were not statistically significant. CONCLUSIONS We complemented national death registration with longitudinal data on individual, social and health attributes. This information is invaluable in yielding insight into certain risk traits such as being a young male, history of drunk driving and history of depression. Such information could be used to inform injury prevention policies and strategies.This study was supported by the International Collaborative Research Grants Scheme with joint grants from the Wellcome Trust UK (GR071587MA) and the Australian National Health and Medical Research Council (268055), and as a global health grant from the NHMRC (585426)

Determinants of workplace injury among Thai Cohort Study participants

OBJECTIVES: To explore individual determinants of workplace injury among Thai workers. DESIGN: Cross-sectional analysis of a large national cohort. SETTING: Thailand. PARTICIPANTS: Thai Cohort Study participants who responded to the 2009 follow-up survey were included if they reported doing paid work or being self-employed (n=51 751). OUTCOME MEASURES: Self-reported injury incidence over the past 12 months was calculated. Multivariate logistic regression models were used to test associations between individual determinants and self-reported workplace injury. RESULTS: Workplace injuries were reported by 1317 study participants (2.5%); the incidence was 34 (95% CI 32 to 36)/1000 worker-years for men, and 18 (17–20) for women. Among men working ≥41 h and earning <10 000 Baht, the injury rate was four times higher compared with men working <11 h and earning ≥20 001 Baht; differences in injury rates were less pronounced in women. Multivariate modelling showed that working ≥49 h/week (23%) and working for ≤10 000 Bath/month (37%) were associated with workplace injury. The increase in injury risk with increased working hours did not exceed the risk expected from increased exposure. CONCLUSIONS: Reductions in occupational injury rates could be achieved by limiting working hours to 48/week. Particularly for Thai low wage earners and those with longer workdays, there is a need for effective injury preventive programmes.NHMRC (National Health and Medical Research Council of Australia

Impact of the HIV-1 genetic background and HIV-1 population size on the evolution of raltegravir resistance

Background: Emergence of resistance against integrase inhibitor raltegravir in human immunodeficiency virus type 1 (HIV-1) patients is generally associated with selection of one of three signature mutations: Y143C/R, Q148K/H/R or N155H, representing three distinct resistance pathways. The mechanisms that drive selection of a specific pathway are still poorly understood. We investigated the impact of the HIV-1 genetic background and population dynamics on the emergence of raltegravir resistance. Using deep sequencing we analyzed the integrase coding sequence (CDS) in longitudinal samples from five patients who initiated raltegravir plus optimized background therapy at viral loads > 5000 copies/ml. To investigate the role of the HIV-1 genetic background we created recombinant viruses containing the viral integrase coding region from pre-raltegravir samples from two patients in whom raltegravir resistance developed through different pathways. The in vitro selections performed with these recombinant viruses were designed to mimic natural population bottlenecks. Results: Deep sequencing analysis of the viral integrase CDS revealed that the virological response to raltegravir containing therapy inversely correlated with the relative amount of unique sequence variants that emerged suggesting diversifying selection during drug pressure. In 4/5 patients multiple signature mutations representing different resistance pathways were observed. Interestingly, the resistant population can consist of a single resistant variant that completely dominates the population but also of multiple variants from different resistance pathways that coexist in the viral population. We also found evidence for increased diversification after stronger bottlenecks. In vitro selections with low viral titers, mimicking population bottlenecks, revealed that both recombinant viruses and HXB2 reference virus were able to select mutations from different resistance pathways, although typically only one resistance pathway emerged in each individual culture. Conclusions: The generation of a specific raltegravir resistant variant is not predisposed in the genetic background of the viral integrase CDS. Typically, in the early phases of therapy failure the sequence space is explored and multiple resistance pathways emerge and then compete for dominance which frequently results in a switch of the dominant population over time towards the fittest variant or even multiple variants of similar fitness that can coexist in the viral population

Beyond Signal and Noise: Unraveling Scale Invariance in Neuroscience and Financial Networks with Topological Data Analysis

This exploratory study delves into persistent homology, an integral component of TDA that initially aimed at differentiating between signal and noise. We explore two methodologies for this differentiation: the conventional cycle length approach and the novel death-birth ratio method proposed by Bobrowski and Skraba. Analyzing comprehensive rs-fMRI data from the Human Connectome Project and daily S\&P 500 financial networks, our study compares these methods in identifying significant cycles. A pivotal discovery of this paper is a robust relationship between z-score thresholds applied to bar lengths or ratios and, respectively, behavioural traits in brain networks and market volatility in financial networks. In the brain, this is evident in the strong correlation between the number of significant 1-cycles in brain networks, brain volumes, and sex-based differences. In financial markets, a fractal pattern emerges, where market volatility consistently negatively correlates with the number of significant cycles, indicating that more intricate market topologies are associated with increased stability and less susceptibility to rapid shifts. Our findings also imply a fractal nature of 1-cycles at both population levels and across multiple days in the stock market. Notably, the distribution of significant loops, marked by high z-scores, remains consistent across various z-score thresholds, revealing a scale-invariant, fractal structure in both data sets. Given the scale invariance in these fractal structures, the traditional TDA distinction between signal and noise becomes less meaningful. The fractal nature of 1-cycles suggests that all scales of cycle length are relevant, challenging the conventional approach of segregating signal from noise. This realization broadens the scope of TDA, underscoring its potential to reveal intricate, scale-invariant relationships in complex systems

An anatomy-based lumped parameter model of cerebrospinal venous circulation: can an extracranial anatomical change impact intracranial hemodynamics?

Background The relationship between extracranial venous system abnormalities and central nervous system disorders has been recently theorized. In this paper we delve into this hypothesis by modeling the venous drainage in brain and spinal column areas and simulating the intracranial flow changes due to extracranial morphological stenoses. Methods A lumped parameter model of the cerebro-spinal venous drainage was created based on anatomical knowledge and vessels diameters and lengths taken from literature. Each vein was modeled as a hydraulic resistance, calculated through Poiseuille’s law. The inputs of the model were arterial flow rates of the intracranial, vertebral and lumbar districts. The effects of the obstruction of the main venous outflows were simulated. A database comprising 112 Multiple Sclerosis patients (Male/Female = 42/70; median age ± standard deviation = 43.7 ± 10.5 years) was retrospectively analyzed. Results The flow rate of the main veins estimated with the model was similar to the measures of 21 healthy controls (Male/Female = 10/11; mean age ± standard deviation = 31 ± 11 years), obtained with a 1.5 T Magnetic Resonance scanner. The intracranial reflux topography predicted with the model in cases of internal jugular vein diameter reduction was similar to those observed in the patients with internal jugular vein obstacles. Conclusions The proposed model can predict physiological and pathological behaviors with good fidelity. Despite the simplifications introduced in cerebrospinal venous circulation modeling, the key anatomical feature of the lumped parameter model allowed for a detailed analysis of the consequences of extracranial venous impairments on intracranial pressure and hemodynamics

The relationship between SF-6D utility scores and lifestyle factors across three life-stages: Evidence from the Australian Longitudinal Study on Women’s Health

Purpose: To investigate how SF-6D utility scores change with age between generations of women, and to quantify the relationship of SF-6D with lifestyle factors across life-stages. Methods: Up to seven waves of self-reported, longitudinal data were drawn for the 1973-78 (young, N=13772), 1946-51 (mid-age, N=12792), 1921-26 (older, N=9972) cohorts from the Australian Longitudinal Study on Women’s Health. Mixed effects models were employed for analysis. Results: Young and mid-age women had similar average SF-6D scores at baseline (0.63-0.64), which remained consistent over 16 year period. However, older women had lower scores at baseline at 0.57 which steadily declined over 15 years. Across cohorts, low education attainment, greater difficulty in managing on income, obesity, physical inactivity, heavy smoking, non-drinking and increasing stress levels were associated with lower SF-6D scores. The magnitude of effect varied between cohorts. SF-6D scores were lower amongst young women with high risk drinking behaviours than low-risk drinkers. Mid-age women who were underweight, never married, or underwent surgical menopause also reported lower SF-6D scores. Older women who lived in remote areas, who were ex-smokers, or were underweight reported lower SF-6D scores. Conclusion: The SF-6D utility score is sensitive to differences in lifestyle factors across adult lifestages. Gradual loss of physical functioning may explain the steady decline in health for older women. Key factors associated with SF-6D include physical activity, body mass index, menopause status, smoking, alcohol use and stress. Factors associated with poorer SF-6D scores vary in type and magnitude at different life stages