Association of prevalence of active transport to work and incidence of myocardial infarction: A nationwide ecological study

Abstract

Background: There is a paucity of population-based geospatial data about the association between active transport and myocardial infarction (MI). We investigated the association between active transport to work and incidence of MI. Design: This ecological study of 325 local authorities in England included 43,077,039 employed individuals aged 25-74 years (UK Census, 2011), and 117,521 individuals with MI (Myocardial Ischaemia National Audit Project, 2011-2013).Methods: Bayesian negative binomial regression models were used to investigate the association of active transport to work and incidence of MI adjusting for local levels of deprivation, obesity, smoking, diabetes, and physical activity. Results:In 2011, the prevalence of active transportation to work for people in employment in England aged 25-74 years was 11.4% (4,531,182 active transporters; 8.6% walking and 2.8% cycling). Active transport in 2011 was associated with a reduced incidence of MI in 2012 amongst men cycling to work (incidence rate ratio (95% credible interval) 0.983 (0.967 to 0.999); and women walking to work (0.983 (0.967 to 0.999)) after full adjustments. However, the prevalence of active transport for men and women was not significantly associated with the combined incidence of MI between 2011 and 2013 after adjusting for physical activity, smoking and diabetes. Conclusions:In England, the prevalence of active transportation was associated with a reduced incidence of MI for women walking and men cycling to work in corresponding local geographic areas. The overall association of active transport with MI was, however, explained by local area levels of smoking, diabetes and physical activity.

Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom

“…The Consumer Data Research Centre engages commercial data partners for linkage of novel data sources, such as: retailer loyalty cards, physical activity apps and market research surveys (Sun & Mobasheri, 2017). Ongoing projects include using supermarket loyalty card data to investigate food purchasing behaviours (Clark et al, 2020;Jenneson et al, 2020), social media data as a source of public health surveillance (Oldroyd et al, 2018), and influence of cycle infrastructure on myocardial health outcomes (Munyombwe et al, 2020).…”

Walking or cycling to work to prevent myocardial infarction: Hope or hype?

“…In conclusion, the article by Munyombwe and colleagues 9 enlightens us as to the important findings on active transportation and incidence of MI for men and women. Public health interventions to encourage active transportation to reduce the global burden of chronic diseases are needed.…”

“…In 2011, the prevalence of active transportation to work for people in employment in England aged 25–74 years was 11.4% (4,531,182 active transporters; 8.6% walking and 2.8% cycling). 9 Active transport in 2011 was associated with a lower incidence of MI in 2012 amongst men cycling and women walking to work. However, the prevalence of active transport for men and women was not significantly associated with the combined incidence of MI between 2011–2013 after adjusting for physical activity, smoking and diabetes.…”

“…In England, the prevalence of active transportation was associated with a reduced incidence of MI for women walking and men cycling to work in corresponding local geographic areas). 9 Recent findings suggest that lifelong exercise training may preserve left ventricular systolic function and attenuate the deleterious effects of pathological left ventricular remodeling after myocardial infarction, as well as improve peak oxygen uptake in patients with arterial disease coronary artery. 10,11 Notably, the effect size is rather modest.…”

“…In England, the prevalence of active transportation was associated with a reduced incidence of MI for women walking and men cycling to work in corresponding local geographic areas). 9…”