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The association between commuting and cardiovascular disease: A biomarker-based analysis of cross-sectional cohort
Micha Kaiser1, Jan M Bauer2, Steffen Otterbach3
1El-Erian Institute of Behavioural Economics and Public Policy, University of Cambridge, Trumpington Street, Cambridge CB2 1QA, United Kingdom.
Insights
Commuting long distances by car may benefit cardiovascular health biomarkers, while active commuting like cycling and walking shows potential negative associations. This study used UK Biobank data to explore commuting's impact on cardiovascular disease biomarkers.
Area of Science:
- Epidemiology
- Biomedical Science
- Public Health
Background:
- Cardiovascular disease (CVD) risk is influenced by lifestyle factors, including commuting habits.
- Understanding the impact of different commuting modes and distances on health outcomes is crucial for public health initiatives.
- Biomarkers offer a sensitive measure of early-stage cardiovascular health changes.
Purpose of the Study:
- To investigate the association between active and passive commuting, commuting distance, and cardiovascular disease (CVD) biomarkers.
- To estimate the risk of adverse CVD biomarker levels based on commuting practices.
- To utilize UK Biobank data for a large-scale analysis of commuting and cardiovascular health indicators.
Main Methods:
- Cross-sectional analysis of UK Biobank data from 208,893 participants (aged 40-69).
- Logistic regression used to assess the risk of biomarker values outside reference intervals.
- Standard linear regression applied to examine the relationship between commuting and a composite CVD biomarker index.
Main Results:
- A small negative association was observed between the composite CVD biomarker risk index and weekly commuting distance.
- Active commuting (cycling, walking) showed a positive association with select CVD biomarkers.
- Long-distance car commuting was negatively associated with CVD-related biomarkers, suggesting a potential protective effect.
Conclusions:
- Commuting mode and distance appear to influence CVD-related biomarkers, with passive commuting potentially showing beneficial associations.
- Biomarker-based evidence provides a less confounded perspective on health outcomes compared to mortality data.
- Further research is needed to fully elucidate the complex relationship between commuting behaviors and cardiovascular health.
Abstract:
This study used cross-sectional UK Biobank data to estimate the influence of active and passive commuting modes and commuting distance on cardiovascular disease (CVD) -related biomarkers as measures of health outcomes. The analysis applied logistic regression to assess the risk of exhibiting individual biomarker values outside a predefined reference interval and standard linear regression to estimate the relation between commuting practices and a composite CVD index. The study sample comprised 208,893 UK Biobank baseline survey participants aged 40 to 69 who use various modes of transport to commute to work at least once a week. Participants were recruited and interviewed between 2006 and 2010 at 22 centers geographically dispersed across England, Scotland, and Wales. The data set included these participants' sociodemographic and health-related information, including lifestyle indicators and biological measures. The primary outcome was a shift from low to high-risk blood serum levels in eight cardiovascular biomarkers: total cholesterol, low density lipoprotein, high density lipoprotein, triglycerides, apolipoprotein A and B, C-reactive protein, and lipoprotein (a). Our results indicated a small negative association between the composite risk index for CVD biomarkers and weekly commuting distance. Although estimates for active commuting modes (cycling, walking) may admittedly be sensitive to different covariate adjustments, our specifications show them to be positively associated with select CVD biomarkers. Commuting long distances by car is negatively associated with CVD-related biomarkers, while cycling and walking might be positively associated. This biomarker-based evidence, although limited, is less susceptible to residual confounding than that from distant outcomes like CVD mortality.
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