Skip to Content
Wednesday 6 November 2019

Ground-breaking study shows fitter bodies could lead to fitter economies

  • An extra 15 minutes of walking each day could grow the world economy by an estimated $100bn a year.
  • Meeting the recommended physical activity guidelines could significantly improve life expectancy and make employees up to 5 days more productive each year.
RAND Europe and Vitality publish a ground-breaking, global study on the economic impact of physical inactivity, illustrating the significant influence of regular exercise on economic growth, workforce productivity and life expectancy. 
  • The study determines the economic benefits of increased physical activity globally, and for 23 individual countries.
  • It shows that if all adults aged 18-64 walked just 15 minutes more a day, the world economy would grow by an estimated $100bn a year until 2050.
  • Further findings show that if the physically inactive were to reach the World Health Organization’s recommended levels of exercise, employees would gain up to 5 additional days of productive time each year, and the global economy would grow by an estimated $220bn every year. Vitality estimates that life expectancy could increase by at least 2.5 years, on average, for a person aged 40 years in this scenario.
  • In addition to getting inactive people active, if currently active people increased their physical activity levels by 20%, the global economy could grow by in excess of $360bn every year; equivalent to the size of Singapore’s economy. Economic gains for the US economy would add $95bn (£73bn) a year to the economy until 2050, and $11bn (£8.5bn) a year for the UK economy, in this scenario.
  • Economic gains can be attributed to the reduction of premature deaths in the working age population, improving rates of sick leave and improved levels of workplace productivity associated with regular exercise. 
6 November 2019 - The results of a ground-breaking academic study on the relationship between global economic growth and exercise, carried out by Vitality and RAND Europe, reveal significant benefits to the economy and life expectancy if physical activity levels increase globally. 

The study finds that the world’s GDP would gain more than $100bn (£80bn) each year until 2050 if people:
- walked 15 minutes more a day, or
- did a slow jog of half a mile (one kilometre) a day, or;
- took 1 500 extra steps a day.

The economic improvement arises from lower mortality rates (more people alive and contributing to the economy), reduced absenteeism, and lower presenteeism[1] driven largely by the impact of physical activity on mental health. 

Adrian Gore, Discovery Group Chief Executive, says; “Vitality has been successfully incentivising people to lead fitter and healthier lives and ultimately transforming the way insurance works for over 20 years. The insurers connected by Vitality, now collectively accountable for more than 35% of the world’s individual protection market, are committed to encouraging positive behaviour change to not only drive individual improvements, but offer sustainable solutions to global challenges. This study shows the massive benefits of that approach.” 

Vitality’s platform of the world’s leading insurers is uniquely well-positioned to address significant global challenges like inactivity, as evidenced by the network’s commitment last year to make 100m people 20% more active by 2025. 

Gore continues: “This ground-breaking study provides proof of the relationship between exercise, productivity, mortality and economic growth. It strengthens our resolve to continue to encourage people to Move More and become part of a global health movement.”

The study, authored by Vitality and Rand Europe, aims to enhance the understanding of how inactivity affects all parts of the economy, beyond simply the traditional considerations of healthcare and mortality. It analysed three scenarios[2] that sketch a global picture of how increased physical activity can benefit not only individuals, but also businesses and global economies.

RAND Europe used a dynamic, multi-country macro-economic model to comprehensively assess the impact of physical inactivity on national economies on a consistent basis, allowing for an aggregation of the effect to the global economy. The study uses a novel approach to synthesise the existing evidence on physical activity and mortality risk by taking study design and publication bias into account. It utilises Vitality’s extensive proprietary dataset on workplace health, derived from its Healthiest Workplace initiative in seven countries, to assess the relationship between physical activity and performance at work. And it combines the mortality and productivity effects into a single model to project the true economic cost of physical inactivity over time.

Hans Pung, President of RAND Europe, comments on the significance of the study; “This is the first time that a multi-country macroeconomic model has been applied to the area of physical activity, facilitating a detailed assessment of the current and future implications of insufficient physical activity.” 

Pung also highlights the significance of the study for policymakers and employers alike, “The study points to a significant relationship between inactivity and productivity loss, driven largely by ill-health related presenteeism. We hope that these insights will support policy makers and employers with new perspectives on how to enhance the productivity of their populations.”

The study also found that by meeting at least the minimum World Health Organization (WHO) guidelines, up to five productive working days can be added every year. This is associated with physical and mental health gains, improved lifestyle behaviours (such as improved sleep quality) and even better engagement at work. 

In addition to productivity, individuals also benefit from improved mortality rates – ranging from 17% to 34% for the physically inactive moving to a state of becoming highly active. Vitality estimates this to result in 2.5 years of additional life (based on an average 40-year-old).

For the UK, the combined impact of improved productivity and reduced mortality from getting people to meet at least the WHO recommended levels of activity would contribute to GDP gains of at least $11bn (£8.5bn) annually, or $170 (£130) per person. This excludes the cost savings to the NHS associated with improvements in physical activity, resulting from a reduced incidence of diseases linked to inactivity, such as cardiovascular disease, certain forms of cancer, diabetes and mental health issues.

Further spokesperson comments: 
 
Neville Koopowitz, CEO of Vitality UK said: “This is further compelling evidence of the far-reaching benefits of healthy, active lifestyles. Every day at Vitality we see the transformative impact of exercise on people’s live, and this is yet another example of the positive effect that regular exercise can have on society, the workforce and the wider economy.”

ENDS

  • According to the World Health Organization (WHO) insufficient physical inactivity is recognised as one of the leading risk factors for death, posing a global public health problem. Globally, it is estimated that every year, physical inactivity is associated with more than 5 million deaths(1) and is contributing to global healthcare expenditures, as well as lost productivity(2).While many countries have developed national action plans to tackle growing prevalence of physical inactivity, gaps challenges persist with their implementation, often associated with an uncoordinated or underfunded approach.
  • Physical inactivity is associated with the onset of a number of different diseases, including cardiovascular disease, stroke, diabetes and cancer (e.g. breast or colon). Physical inactivity is also associated with a mortality and morbidity burden. A healthy population has a positive effect on a country’s economic output (e.g. measured as gross domestic product). Reducing physical inactivity has a positive effect on a country’s labour force by reducing premature mortality and improving rates of sickness absence and levels of presenteeism.
  • We believe the implications of this study can be far-reaching, informing policy around the world on issues of public health and state budgets. 
  • RAND used a dynamic computational general equilibrium (DSGE) macroeconomic model in this study. DSGEs are used in macroeconomics to explain economic phenomena, such as economic growth and business cycles, and the effects of economic policy, through econometric models based on applied general equilibrium theory and microeconomic principles. The model has been extensively peer reviewed and tested.
  • The productivity data stems from data collected as part of Vitality UK’s Britain’s Healthiest Workplace (BHW) Survey, as well as AIA’s Asian Healthiest Workplace Survey. In both, employers are asked about their provision of health and well-being interventions, while employees are asked over 100 questions related to demographic factors (age, gender, education, income), lifestyle and health behaviour (nutrition, smoking habits, physical activity, sleep behaviour), health factors (mental and physical health indicators, chronic and musculoskeletal conditions), as well as workplace productivity and job and life satisfaction. Overall, the sample pool was significant, yielding a collective sample size of 120 143 across seven countries.
  • Multivariate regression models were employed to investigate the associations between physical activity and a set of outcome measures, including workplace productivity, quality of life and a set of sleep measures. Depending on the analysis, physical activity is included in the analysis as two variables. First, as a binary indicator taking the value one if the individual regularly achieves the recommended level of physical activity per week (e.g. 150 minutes of moderate or 75 minutes of vigorous physical activity[3]) or zero otherwise. Second, as a continuous variable measuring the MET minutes an individual of physical activity an individual performs every week.
  • To measure work engagement, the workplace surveys include questions that build the Utrecht Work Engagement Scale (UWES), which includes three dimensions of work engagement: vigour, dedication, and absorption. The nine questions related to the scale are measured on a 7-point Likert scale.
  • To investigate the relationship between physical inactivity and elevated mortality risk, the study uses meta-regression analysis. Meta-regression analysis is a form of systematic review employing a range of statistical methods to synthesise and evaluate specific empirical literature. It helps to better understand the existing research findings on a given empirical effect of interest.
  • The study uses the MET unit as a measure for how much energy an individual exerts in performing a physical task. It a measure which adjusts for body size, and is defined as the amount of oxygen consumed while sitting at rest, equal to 3.5 ml oxygen per kg body weight per minute. Alternatively, one MET is defined as 1 kcal/kg/hour and is roughly equivalent to the energy cost of sitting quietly. For comparison, cycling is estimated to equal 3.5-16 METs and running 6-23 METs, depending on intensity.
  • On attaining the associations between physical activity to productivity and mortality, these effects are then plugged into the DSGE model to yield the economic outcomes. The analysis on the future economic benefits of changes to physical activity at the population level is based on demographic projections on how the population of each country or region evolves over time. To that end, we demographic projections are generated using input data from the UN[4] and an adapted version of Chapin's cohort-component model, which are implemented as five-year projections using Stata. The cohort-component model starts with the current base population and is categorized for each country region by age, gender and skill level. The base population subsequently evolves by applying assumptions on mortality, fertility and migration rates. The outcome of the model is a projection of the population by (5-year) age, gender and skill groups up to thirty years, applied to each of the 24 countries or regions.


Annual GDP gain by country relative to the status quo (in 2019 USD billions present values), at specific years.

Based on all adults achieving a 20% increase in physical activity, as well as meeting at least the World Health Organization minimum requirements (scenario 3). For instance, assume the population of Argentina begins meeting the conditions of scenario 3 from 2020, it would gain $1.21bn in GDP in 2030 and so forth. 

2030 2040 2050 

Argentina

1.21

1.88

2.82

Australia

5.72

8.14

11.23

Austria

1.16

1.32

1.48

Canada

5.93

7.00

8.15

China

32.77

59.44

99.71

Ecuador

0.24

0.38

0.57

France

7.44

8.46

9.49

Germany

12.36

13.64

15.27

Hong Kong

0.43

0.53

0.63

Japan

9.75

10.28

10.14

Malaysia

0.80

0.98

1.16

Netherlands

2.28

2.59

2.91

New Zealand

0.88

1.25

1.72

Pakistan

1.19

1.86

2.79

Philippines

0.92

1.43

2.14

Singapore

0.46

0.57

0.67

South Africa

1.40

2.20

3.06

South Korea

3.43

4.11

4.72

Sri Lanka

0.30

0.46

0.69

Thailand

1.09

1.34

1.58

United Kingdom

9.49

12.13

15.05

United States

85.26

109.59

137.98

Vietnam

0.69

1.07

1.60

Rest of the World

89.61

132.24

188.19


Annual GDP gain averaged over 30 years, by country relative to status quo (in 2019 USD billions present values) shown for each scenario, quantifying the direct and indirect benefits.

Each scenario has a low and high value. The low values consider only the direct economic effects of physical activity improvement. The high values include all indirect effects of physical activity on the economy, indicating that improvements in activity levels can increase the estimated gains in GDP considerably more over time.

The low figures in the third table, for scenario 3, support global GDP growth of $360bn. 

Scenario 1

GDP  Gain

 

Scenario 2

GDP  Gain

 

Scenario 3

GDP  Gain

Country

Low

High

 

Country

Low

High

 

Country

Low

High

Argentina

1.2

1.6

 

Argentina

0.6

1.0

 

Argentina

1.8

2.6

Australia

4.5

6.6

 

Australia

3.3

4.9

 

Australia

7.7

11.4

Austria

0.7

1.1

 

Austria

0.5

0.8

 

Austria

1.3

1.9

Canada

3.7

5.3

 

Canada

3.1

4.7

 

Canada

6.7

10.0

China

22.9

33.1

 

China

34.1

50.7

 

China

56.2

82.7

Ecuador

0.2

0.3

 

Ecuador

0.1

0.2

 

Ecuador

0.4

0.5

France

4.8

7.0

 

France

3.5

5.2

 

France

8.2

12.1

Germany

9.4

13.8

 

Germany

4.0

5.9

 

Germany

13.4

19.6

Hong Kong

0.3

0.5

 

Hong Kong

0.2

0.3

 

Hong Kong

0.5

0.7

Japan

7.5

11.0

 

Japan

2.6

3.9

 

Japan

10.0

14.7

Malaysia

0.6

0.9

 

Malaysia

0.3

0.5

 

Malaysia

0.9

1.4

Netherlands

1.5

2.1

 

Netherlands

1.1

1.6

 

Netherlands

2.5

3.7

New Zealand

0.7

1.0

 

New Zealand

0.5

0.7

 

New Zealand

1.2

1.7

Pakistan

1.1

1.6

 

Pakistan

0.6

0.9

 

Pakistan

1.8

2.5

Philippines

0.9

1.2

 

Philippines

0.5

0.7

 

Philippines

1.4

2.0

Singapore

0.4

0.5

 

Singapore

0.2

0.3

 

Singapore

0.5

0.8

South Africa

1.6

2.1

 

South Africa

0.5

0.7

 

South Africa

2.0

2.7

South Korea

2.9

4.3

 

South Korea

1.1

1.6

 

South Korea

3.9

5.7

Sri Lanka

0.3

0.4

 

Sri Lanka

0.2

0.2

 

Sri Lanka

0.4

0.6

Thailand

0.9

1.2

 

Thailand

0.4

0.6

 

Thailand

1.3

1.8

United Kingdom

8.1

11.8

 

United Kingdom

3.6

5.4

 

United Kingdom

11.5

17.0

United States

75.4

109.0

 

United States

30.5

45.4

 

United States

104.4

152.2

Vietnam

0.7

0.9

 

Vietnam

0.4

0.5

 

Vietnam

1.0

1.5

Rest of the World

69.6

98.5

 

Rest of the World

57.7

86.0

 

Rest of the World

125

182