A recent International Journal of Epidemiology study uses an instrumental variable approach to explore whether cycle commuting alleviates adverse mental health conditions.
Study: Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path. Image Credit: LovetheLifeYouLive / Shutterstock.com
Several studies have indicated the positive effect of physical activity on mental health by reducing depression and anxiety. Likewise, incorporating a daily active commuting approach could positively contribute to maintaining a healthy physical activity level. Cycle commuting, for example, significantly reduces the risk of cardiovascular events, cancer-related mortality, and all-cause mortality risks.
Although previous studies have indicated that individuals who use bicycles for long-distance commuting found this mode mentally relaxing, a recent systematic review documented an inconsistent relationship between active commuting and depression. Poor mental health conditions also entail considerable economic loss, with one Scottish study estimating that £8.8 billion is lost every year due to decreased productivity stemming from different mental-health problems.
About the study
The current study adopted a pseudo-experimental approach based on an instrumental variable. To this end, data from the 2011 Scottish Census linked with the Scottish National Prescription Information System (PIS), which covers all National Health Service (NHS) Scotland prescriptions, was used for individuals between 16 and 74 years of age.
To estimate occurrence, rather than recurrence of anxiety or depression, individuals with a prescription for mental illnesses in the month when the census was conducted were excluded. Considering the inclusion criteria, the study cohort comprised a total of 378,253 individuals.
The census asked the mode of travel from the main place of work or study and the responses were grouped into a binary viable of bicycle and all other modes of commute. The use of antidepressants and anxiolytics obtained from the PIS data were considered the outcome measures . Based on this data, a binary variable of zero (no prescription) and one (prescription for antidepressants and anxiolytics) was created.
The distance to a cycle path was used as the instrumental variable (IV). Importantly, IV analyses are similar to randomized-controlled experiments.
According to the 2011 census, 1.85% individuals in the Glasgow City Council area cycled to work, whereas 4.8% of people living in the Edinburgh council area cycled to work. As compared to women, men were more likely to cycle to work. In the study cohort, 15.6% of females and 9.1% of males had prescriptions for anxiolytics or antidepressants.
The biprobit model was used to assess the average treatment effect of cycling to work in the study population. Among those who cycled to work, 7.5% of males and 10.2% of females had a prescription for anxiolytics or antidepressants. These numbers increased among non-cyclists, at 9.2% of males and 15.7% of females, thus implying that cycling to work reduced mental illness, which was reflected through lower prescriptions for antidepressants and/or anxiolytics.
The results of the sensitivity analyses were consistent with previous research that observed a relationship between cycle commuting and different health domains. The combination of the IV approach and linked administrative data further strengthened the study results, as this approach mitigated the limitations of previous studies, including omitted-variable bias, the use of non-representative populations, and limitations associated with subjective mental health measures.
Importantly, the daily commute is dependent on weather, season, topography, and meteorology.
The current study has some limitations including the lack of complete data. For example, the PIS database only includes prescriptions from 2009 onwards.
Furthermore, no data on the frequency of individuals using a bicycle to travel to work was available. Therefore, it was assumed that the bicycle was the usual mode of commuting for the participants.
Another limitation of this study is that the census did not capture if a person has more than one mode of commute. Furthermore, the frequency of commuting was not addressed, such as whether a person cycles to work daily or has a hybrid or part-time working regime.
This study made multiple untestable assumptions, which were essential for the instrumental variable analysis. However, a negative control outcome analysis was conducted to verify the results.
It was assumed that among many factors that govern where a person selects to live, residing close to a cycle path could be one of them. However, other factors, such as house price, local amenities, or being close to friends and family, could play a crucial role in determining the place to live.
Despite these limitations, the study indicated that cycling to work could improve mental health, in addition to lowering carbon emissions.
- Berrie, L., Feng, Z., Rice, D., et al. (2024) Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path. International Journal of Epidemiology. doi:10.1093/ije/dyad153