Is mode of transport to work associated with mortality in the working-age population? Repeated census-cohort studies in New Zealand, 1996, 2001 and 2006

Evaluation of quantitative bias analysis in epidemiological research: A systematic review from 2010 to mid-2023

OBJECTIVE

We aimed to demonstrate the use of quantitative bias analysis (QBA), which reveals the effects of systematic error, including confounding, misclassification and selection bias, on study results in epidemiological studies published in the period from 2010 to mid-23.

METHOD

The articles identified through a keyword search using Pubmed and Scopus were included in the study. The articles obtained from this search were eliminated according to the exclusion criteria, and the articles in which QBA analysis was applied were included in the detailed evaluation.

RESULTS

It can be said that the application of QBA analysis has gradually increased over the 13-year period. Accordingly, the number of articles in which simple is used as a method in QBA analysis is 9 (9.89%), the number of articles in which the multidimensional approach is used is 10 (10.99%), the number of articles in which the probabilistic approach is used is 60 (65.93%) and the number of articles in which the method is not specified is 12 (13.19%). The number of articles with misclassification bias model is 44 (48.35%), the number of articles with uncontrolled confounder(s) bias model is 32 (35.16%), the number of articles with selection bias model is 7 (7.69%) and the number of articles using more than one bias model is 8 (8.79%). Of the 49 (53.85%) articles in which the bias parameter source was specified, 19 (38.78%) used internal validation, 26 (53.06%) used external validation and 4 (8.16%) used educated guess, data constraints and hypothetical data. Probabilistic approach was used as a bias method in 60 (65.93%) of the articles, and mostly beta (8 [13.33%)], normal (9 [15.00%]) and uniform (8 [13.33%]) distributions were selected.

CONCLUSION

The application of QBA is rare in the literature but is increasing over time. Future researchers should include detailed analyzes such as QBA analysis to obtain inferences with higher evidence value, taking into account systematic errors.

Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path

BACKGROUND

Previous studies have linked cycling with improved mental wellbeing but these studies tend to use cross-sectional survey data that have small sample sizes and self-reported health measures, and are potentially susceptible to omitted-variable bias and reverse causation. We use an instrumental variable approach and an objective measure of mental ill-health taken from linked administrative data to ask: 'Does cycle commuting reduce the risk of mental ill-health?'

METHODS

Our study links data on commuting in Edinburgh and Glasgow from the Scottish population census with mental health prescriptions from the National Health Service Prescribing Information System records. We use road distance from home to nearest cycle path as an instrumental variable for cycle commuting.

RESULTS

In total, 378 253 people aged 16-74 years living and working in the City of Edinburgh and Glasgow City council areas at the 2011 census were included in our study; 1.85% of commuters in Glasgow and 4.8% of commuters in Edinburgh cycled to work. Amongst cyclists, 9% had a prescription for mental health compared with 14% amongst non-cyclists. Using a bivariate probit model, we estimate a mean average reduction in prescriptions for antidepressants and/or anxiolytics in the 5 years following the census of -15.1% (95% CI: -15.3% to -15.0%) amongst cycle commuters compared with those who use any other mode to commute.

CONCLUSIONS

This work suggests that cycle commuting is causally related to reduced mental ill-health and provides further evidence in support of the promotion of active travel to encourage commuters travelling shorter distances to shift to cycle commutes.

The bicycle as 'constructive hope': Children, climate and active transport

Children are experiencing an increase in so-called 'eco-anxiety'. Along with others, we argue that children need more concrete, meaningful opportunities to feel they can make a difference in climate. In this article, we contend that bringing back the bicycle, and the opportunities for independent and active mobility that it affords children, is an important form of climate action for young people. We assert that as well as providing sustainability and wellbeing co-benefits for children, cycling can help bolster the neighbourhood resilience and social cohesion that will be key resources for communities adapting to new climate risks.

A paradox of traffic and extra cars in a city as a collective behaviour

Promoting walking or cycling and reducing cars' use is one of the city planners' main targets, contributing to a sustainable transport method. Yet, the number of vehicles worldwide is increasing as fast as the population, and motorized mobility has become the primary transport method in most cities. Here, we consider modal share as an emergent behaviour of personal decisions. All individuals minimize their commuting time and reach an equilibrium under which no person is willing to change their transportation mode. In terms of the minimum travel time, the best-case scenario is used to determine the extra commuting time and the excess cars, computed as a social inefficiency. Results show that commuting times could increase up to 25% with many more vehicles than optimum. Paradoxically, all individuals trying to minimize their time could collectively reach the maximum commuting times in the extreme case, with all individuals driving during rush hour.