The Lancet

Data is derived from the article "Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy" (Lee et al., Lancet 2012). The study is aimed to quantify the effect of physical inactivity on these major non-communicable diseases by estimating how much disease could be averted if inactive people were to become active and to estimate gain in life expectancy at the population level. The focus is made on the major non-communicable diseases emphasised by the UN as threats to global health: coronary heart disease; cancer, specifically breast and colon cancers, which are convincingly related to physical inactivity; and type 2 diabetes. For the analysis of burden of disease, population attributable fractions (PAFs) associated with physical inactivity were calculated using conservative assumptions for each of the major non-communicable diseases, by country, to estimate how much disease could be averted if physical inactivity were eliminated. Life-table analysis was used to estimate gains in life expectancy of the population. The population attributable fraction (PAF) is a measure used by epidemiologists to estimate the effect of a risk factor on disease incidence in a population. It estimates the proportion of new cases that would not occur, absent a particular risk factor. Thus, it provides policy makers with useful quantitative estimates of the potential effect of interventions to reduce or eradicate the risk factor. Data are 95% CI. Gain in life expectancy is estimated gains in life expectancy if physical inactivity were eliminated. Note: Uncertainty interval calculated on the basis of the lower and upper bounds of the 95% CI.

Global estimated deaths (millions) due to pollution risk factors from the Global Burden of Disease study (GBD; 2015) versus WHO data (2012)

Data from the article "The economic burden of physical inactivity: a global analysis of major non-communicable diseases" by Ding, Ding et al. published in the Lancet journal. This research represents the first detailed quantification of the global economic burden of physical inactivity. It provides key information to help researchers and decision makers tackle the global pandemic of physical inactivity. Physical inactivity is defined as not meeting the WHO recommendations of 150 min of moderate-to-vigorous physical activity per week. Using consistent methods, authors of the research estimated direct health-care costs and indirect productivity costs for 142 countries, representing 93% of the world’s population. The dataset includes country-specific estimates and an overall global estimate of the economic burden of physical inactivity by taking into account both direct costs (health-care expenditure) and indirect costs (productivity losses), the distribution of costs across the public and private sectors and households as well as the lifetime disease burden attributable to physical inactivity in terms of disability-adjusted life-years (DALYs). All costs were estimated for the year 2013. Following standard practice, to enable comparison of the economic burden between countries, all costs were converted to international $ (INT$) using purchasing power parity (PPP) conversion factors in 2013. Direct health-care costs. Health-care costs attributable to physical inactivity were estimated using a population attributable fraction (PAF) approach. Indirect productivity costs. Physical inactivity related diseases indirectly cost society in many ways. These costs were estimated as the financial value of lost productivity due to premature mortality using a friction cost approach. Lifetime disease burden: DALYs. DALYs sums the years of life lost due to premature mortality (years of life lost [YLLs]) and to morbidity or disability, while alive (years lost due to disability [YLDs]). An "analysis of extremes" was performed to generate a base estimate, a lower estimate, and a higher estimate, based on mean, lower, and upper limits of all input variables. Notes: Direct health-care cost data are incomplete for Zimbabwe due to the lack of WHO health expenditure data; the current total direct costs were estimated based on type 2 diabetes only. The Region of the Americas is further divided into Latin America and the Caribbean and North America (Canada and the USA only) due to different patterns of disease burden, levels of economic development, and health-care expenditure.