Professor Ulf Ekelund
Norwegian School of Sport Sciences, Oslo Norway
Dose-response associations between physical activity and risk for mortality - lessons learned from self-reported and device-measured physical activity
ABSTRACT
In the first Lancet series on physical activity in 2012, Lee et al (1) estimated that physical inactivity caused more than 5 million deaths (9% of total deaths) globally every year. More recent updates suggest that 7.2% and 7.6% of all-cause and cardio-vascular deaths, respectively, are attributable to physical inactivity, operationalised as not meeting the WHO 2020 physical activity guidelines (2). The relative burden of physical inactivity is greatest in high income countries whereas the absolute number of deaths due to inactivity is highest in middle-income countries (2).
In contrast, the Global Burden of Disease study (3) estimates considerably lower numbers of deaths, equal to less than 1 million deaths, attributable to physical inactivity annually. These previous studies estimated the number of deaths that could be prevented using self-report physical activity data and estimated the population attributable fraction as a dichotomous variable, meeting or not meeting the physical activity recommendations (1, 2) or using methods that deviate substantially from established thresholds for optimal levels of physical activity (3).
Despite almost global coverage, self-report data used to estimate the prevalence of physically inactive individuals are likely biased due to misclassification. For example, the reported prevalence of physical activity is substantially larger from self-report than from device-measured physical activity. Further, the does-response association between physical activity and risk of death suggest a maximal risk reduction that is larger in magnitude at lower levels of physical activity from device-measured physical activity compared with self-report (4).
The aim of this key note is to discuss differences in methodology (self-report vs device-based methods) when examining the associations between physical activity and risk for morbidity and mortality and when estimating the number of deaths that can be adverted by physical activity on population level.
References
1. Lee et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012;380;219-29
2. Katzmarzyk et al. Physical inactivity and non-communicable disease burden in low-income, middle-income and high-income countries. Br J Sports Med 2022;56:101-06
3. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet 2020;396:1223–49.
4. Ekelund et al. Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis. BMJ 2019; 366:l4570
Norwegian School of Sport Sciences, Oslo Norway
Dose-response associations between physical activity and risk for mortality - lessons learned from self-reported and device-measured physical activity
ABSTRACT
In the first Lancet series on physical activity in 2012, Lee et al (1) estimated that physical inactivity caused more than 5 million deaths (9% of total deaths) globally every year. More recent updates suggest that 7.2% and 7.6% of all-cause and cardio-vascular deaths, respectively, are attributable to physical inactivity, operationalised as not meeting the WHO 2020 physical activity guidelines (2). The relative burden of physical inactivity is greatest in high income countries whereas the absolute number of deaths due to inactivity is highest in middle-income countries (2).
In contrast, the Global Burden of Disease study (3) estimates considerably lower numbers of deaths, equal to less than 1 million deaths, attributable to physical inactivity annually. These previous studies estimated the number of deaths that could be prevented using self-report physical activity data and estimated the population attributable fraction as a dichotomous variable, meeting or not meeting the physical activity recommendations (1, 2) or using methods that deviate substantially from established thresholds for optimal levels of physical activity (3).
Despite almost global coverage, self-report data used to estimate the prevalence of physically inactive individuals are likely biased due to misclassification. For example, the reported prevalence of physical activity is substantially larger from self-report than from device-measured physical activity. Further, the does-response association between physical activity and risk of death suggest a maximal risk reduction that is larger in magnitude at lower levels of physical activity from device-measured physical activity compared with self-report (4).
The aim of this key note is to discuss differences in methodology (self-report vs device-based methods) when examining the associations between physical activity and risk for morbidity and mortality and when estimating the number of deaths that can be adverted by physical activity on population level.
References
1. Lee et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012;380;219-29
2. Katzmarzyk et al. Physical inactivity and non-communicable disease burden in low-income, middle-income and high-income countries. Br J Sports Med 2022;56:101-06
3. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet 2020;396:1223–49.
4. Ekelund et al. Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis. BMJ 2019; 366:l4570
