Characteristics of studies that estimated the indirect costs of physical inactivity
| First author and year of publication | Country | Data sources | Definition of PA (minimal risk counterfactual) | Types of indirect costs | Methodology | Findings* (sensitivity analysis) | Time frame | Discounting costs |
| Cadilhac 201127 | Australia | National Health Survey 2004–2005, Australian Burden of Disease data 2003, Time Use Survey 2006 | ≥5×30 min MPA or ≥3×20 min VPA/week | Work-forced, home-based and leisure-based production | Workforce production: Friction Cost Approach (Human Capital Approach as sensitivity analysis); household production: ‘replacement cost’; leisure time production: ‘opportunity cost method’ approach | $A1135 million, structural and statistical sensitivity analysis conducted Converted national estimate: $882.8 million INT | Lifetime | Yes |
| Ding 20162 | 142 countries | International Labour Organization employment statistics, Global Burden of Disease Study 2013, World Bank 2013 gross domestic product data | ≥150 min/week of MVPA | Productivity losses due to premature mortality | Friction Cost Approach (Human Capital Approach as sensitivity analysis) | $13.7 billion INT worldwide, structural and statistical sensitivity analysis: $3.5–34.5 billion INT, when using unadjusted PAFs: $21.3 ($6.1–47.6) billion INT | 1 year (2013) | N/A |
| Janssen 201218 | Canada | Canadian Health Measures Survey 2007–2009, EBIC 2000 | 7-day accelerometry ≥150 min/week | Productivity losses due to illness, injuries/disability and premature deaths | Human Capital Approach | $C4.3 billion, statistical sensitivity analysis: $C2.8–6.1 billion Converted national estimate: $3.8 billion INT | Lifetime | Yes |
| Katzmarzyk 200420 | Canada | CCHS 2000–2001, EBIC 1998/93 | Energy expenditure ≥6.3 kJ/kg/day | Productivity losses due to illness, injuries/disability and premature deaths | Human Capital Approach | $C3.7 billion, statistical sensitivity analysis±20% Converted national estimate: $3.8 billion INT | Lifetime | Yes |
| Katzmarzyk 201119 | Canada | CCHS 2009, EBIC 1998 | Energy expenditure ≥6.3 kJ/kg/day | Productivity losses due to illness, injuries/disability and premature deaths | Human Capital Approach | $C2.3 billion in Ontario, Canada | Lifetime | Yes (based on checking the reference) |
| Krueger 201423 | Canada | CCHS 2009, EBIC 1998 | Not defined as ‘inactive’ (did not specify) | Productivity losses due to illness, injuries/disability and premature deaths | Human Capital Approach | $C7 billion, statistical sensitivity analysis conducted Converted national estimate: $5.8 billion INT | Lifetime | Yes (based on checking the reference) |
| Krueger 201522 | Canada | CCHS 2012, EBIC 1998/2008 | Leisure-time energy expenditure ≥1.5 kcal/kg/day | Productivity losses due to illness, injuries/disability and premature deaths | Human Capital Approach (Friction Cost Approach as sensitivity analysis) | $C7.5 billion, structural sensitivity analysis conducted: much lower estimates based on Friction Cost Approach Converted national estimate: $6.2 billion INT | Lifetime | Yes (based on checking the reference) |
| Krueger 201621 | Canada | CCHS 2012, EBIC 1998/2008 | Leisure-time energy expenditure ≥1.5 kcal/kg/day | Productivity losses due to illness, injuries/disability, and premature deaths | Human Capital Approach | $C673.5 million for British Columbia, Canada, quoted previous statistical sensitivity analysis±17% | Lifetime | Yes (based on checking the reference) |
| Martin 200125 | Switzerland | Health-enhancing PA survey 1999, a published study on costs associated with each disease, accident statistics from the Swiss Council for Accident Prevention | 5×30 min MPA or 3×20 min VPA /week | Productivity losses for cardiovascular disease, type 2 diabetes and back pain only | Human Capital Approach | 1.4 billion SFr, structural sensitivity analysis conducted Indirect cost of sports accidents: 2.3 billion SFr | Lifetime | N/A |
| Zhang 201326 | China | Chinese Behavioral Risk Factors Surveillance 2007, National Health Services Survey 2003 | 5×30 min MPA or 3×20 min VPA /week | Economic output lost because of illness, injury-related work disability or premature death before retirement | Human Capital Approach | US$3.3 billion Converted national estimate: $8.5 billion INT | Lifetime | Not stated |
| Grey literature | ||||||||
| Market Economics Limited 201324 | New Zealand | Various sources including the Ministry of Health, Statistics New Zealand, District Health Board reports, and others | ≥30 min PA×5 days/week | Monetary values for loss of productivity, pain and suffering. Also included other costs, such as promoting PA | Value of a statistical life/life years approaches | $661 million NZD, structural sensitivity analysis: $295 million–7.5 billion NZD Converted national estimate: $499.9 million INT | Lifetime | Yes |
| Colman 200416 | Canada | CCHS, EBIC 1998 | Expenditure ≥1.5 kcal/kg/day | Productivity losses due to premature death and disability | Human Capital Approach | $C362 million/year for British Columbia, Canada | Lifetime | Yes (based on checking the reference) |
| International Sports and Culture Association and Centre for Economics and Business Research 201517 | EU-28 | WHO, Organisation for Economic Cooperation and Development, Eurostat, International Development Association, EUCAN and published studies | 150 min MPA or 75 min VPA/week or combination | Value of human capital that is lost due to premature morbidity and mortality | Human Capital Approach | UK: €12.31 billion; Germany: €12.85 billion; Italy: €10.58 billion; France: €8.25 billion; Spain: €5.62 million; Poland €1.96 million; EU-28: €71.1 billion Converted national estimates: UK $15.5; Germany $16.8; Italy $14.4; France $10.2; Spain $8.5; Poland $4.7 billion INT | Lifetime | Not stated |
*Converted national estimate: we inflated the national estimates in local currency units from the year of data to 2013 using the annual consumer prices inflation indicators from the World Bank (http://data.worldbank.org/indicator/FP.CPI.TOTL.ZG) and then converted to purchasing power parity (PPP) international dollars using conversion factors provided by the World Bank (http://data.worldbank.org/indicator/PA.NUS.PPP). However, the estimate was not converted for Martin et al 25 due to the lack of SFr to PPP international dollar conversion factor from the World Bank.
A, Australian dollars; C, Canadian dollars; CCHS, Canadian Community Health Survey; EBIC, Economic Burden of Illness in Canada; EU-28, 28 member countries of the European Union; INT, international dollars; MPA, moderate physical activity; N/A, not applicable; NZD, New Zealand dollars; PA, physical activity; PAF, population attributable fraction; £, pounds sterling; SFr, Swiss francs; VPA, vigorous physical activity.