Table of Contents
Supplementary Material
Supplementary Material PDF Document
This appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors.
Supplement to: Swinburn BA, Kraak VI, Allender S, et al. The Global Syndemic of Obesity, Undernutrition, and Climate Change: The Lancet Commission report. Lancet 2019; published online Jan 27. http://dx.doi.org/10.1016/S0140-6736(18)32822-8.
Appendix 1: The Lancet Commission on Obesity and the Sustainable Development Goals
The 17 Sustainable Development Goals (SDGs) were adopted in 2015 by the UN General Assembly and they set out the agenda, vision, targets and indictors for the global community to achieve global common goods. We have aligned what we have called the four main global outcomes (achieving environmental health and well-being, human health and well-being, social equity, and economic prosperity) with the SDGs. The specific focus of this report in conceptualizing malnutrition in all its forms and climate change as The Global Syndemic sits within that framework. Five of the SDGs relate directly to obesity, undernutrition, and climate change:
- Goal 2: End hunger, achieve food security, and improve nutrition, and promote sustainable agriculture. The goal includes ending malnutrition in all its forms, and ensuring sustainable food productions systems.
- Goal 3: Ensure healthy lives and promote well-being for all at all ages. The goal includes ending preventable deaths in children under five years, almost 50% of which are attributable to undernutrition. The goal also calls for reducing premature mortality from NCDs, such as those related to obesity.
- Goal 11: Make cities and human settlements inclusive, safe, resilient and sustainable. This goal includes access to safe and sustainable transport systems, reducing the adverse environmental impact of cities, and inclusive and accessible green and public spaces.
- Goal 13: Take urgent action to combat climate change and its impacts. The goal includes integrating climate change measures into policies and planning, improving awareness and institutional capacity on climate change mitigation, including in LMICs, with a particular focus on women, youth, and marginalized communities.
- Goal 15: Protect, restore, and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and biodiversity loss. This goal includes efforts to combat desertification and restore land affected by drought. Desertification and drought are direct consequences of climate change.
However, all of the SDGs are interconnected through common deep drivers and solutions, and achieving progress for one SDG can support progress for other SDGs, as long as interactions are understood and tradeoffs are managed. The deeper the transformational changes to the political economy towards achieving better global outcomes, the greater the synergistic effects of achieving the SDG agenda.
Appendix 2: Complex pathways from climate/weather variability to undernutrition in poor rural farming households

Appendix 3: Indicators by region and country of obesity, underweight, greenhouse gas emissions, gross domestic product, and income inequalities (GINI coefficient)
Region | Female obesity pre-valence 1+ | 5-19 year old girl under-weight pre-valence 2* | Carbon footprint (GHG emissions per capita) 3# | GDP per capita (constant 2011 inter-national dollars) 4^ | GINI co-efficient 5 |
Andean Latin America | 24% | 7% | 3.7 | 10,407 | 45.2 |
Bolivia | 23% | 7% | 5.2 | 6,325 | 45.8 |
Ecuador | 24% | 7% | 4.1 | 10,901 | 46.5 |
Peru | 25% | 7% | 2.9 | 11,545 | 44.3 |
Caribbean | 28% | 17% | 4.2 | 5,855 | 20.8 |
Antigua and Barbuda |
36% | 16% | 6.1 | 19,574 | |
Bahamas | 37% | 14% | 7.3 | 22,015 | |
Barbados | 33% | 17% | 5.1 | 16,361 | |
Belize | 28% | 16% | 2.7 | 8,050 | |
Bermuda | 43% | 14% | 9.6 | ||
Cuba | 29% | 17% | 4.3 | ||
Dominica | 31% | 15% | 2.7 | 10,255 | |
Dominican Republic |
28% | 16% | 3.0 | 12,639 | 44.9 |
Grenada | 31% | 17% | 2.9 | 12,038 | |
Guyana | 30% | 19% | 8.3 | 6,911 | |
Haiti | 17% | 18% | 0.9 | 1,653 | 40.9 |
Jamaica | 33% | 15% | 3.3 | 8,051 | |
Puerto Rico | 39% | 14% | 0.7 | ||
Saint Kitts and Nevis |
34% | 17% | 5.2 | 23,483 | |
Saint Lucia | 30% | 18% | 2.8 | 11,769 | |
Saint Vincent and the Grenadines |
29% | 16% | 2.4 | 10,316 | |
Suriname | 32% | 16% | 5.5 | 15,307 | |
Trinidad and Tobago |
34% | 19% | 45.4 | 31,596 | |
Central Africa | 9% | 22% | 3.9 | 2,815 | 42.0 |
Angola | 13% | 22% | 2.2 | 6,260 | 42.7 |
Central African Republic | 8% | 22% | 41.6 | 602 | 56.2 |
Congo (Republic of the) |
14% | 22% | 2.8 | 5,538 | 48.9 |
Democratic Republicof the Congo |
8% | 22% | 2.1 | 726 | 42.1 |
Equatorial Guinea | 20% | 22% | 7.6 | 31,194 | |
Gabon | 20% | 19% | 5.5 | 16,678 | |
Central Asia | 20% | 14% | 8.7 | 10,824 | 17.8 |
Armenia | 21% | 12% | 3.6 | 7,971 | 32.4 |
Azerbaijan | 25% | 13% | 6.4 | 16,715 | 31.8 |
Georgia | 22% | 14% | 4.3 | 8,749 | 38.5 |
Kazakhstan | 24% | 13% | 19.7 | 23,586 | 26.5 |
Kyrgyzstan | 17% | 14% | 2.7 | 3,182 | 29.0 |
Mongolia | 18% | 13% | 10.6 | 11,349 | 32.0 |
Tajikistan | 16% | 15% | 1.6 | 2,547 | 34.0 |
Turkmenistan | 22% | 14% | 17.7 | 14,332 | |
Uzbekistan | 19% | 14% | 5.5 | 5,371 | |
Central Europe | 21% | 15% | 8.0 | 21,738 | 30.4 |
Albania | 17% | 13% | 3.3 | 10,701 | 29.0 |
Bosnia and Herzegovina | 16% | 15% | 7.6 | 10,517 | 33.8 |
Bulgaria | 21% | 14% | 8.2 | 16,302 | 37.4 |
Croatia | 20% | 13% | 5.8 | 20,136 | 32.2 |
Czech Republic | 23% | 14% | 11.3 | 29,120 | 25.9 |
Hungary | 20% | 13% | 5.6 | 24,161 | 30.9 |
Macedonia (TFYR) | 18% | 15% | 4.6 | 12,298 | 35.6 |
Montenegro | 19% | 15% | 3.6 | 14,797 | 31.9 |
Poland | 23% | 15% | 10.0 | 24,347 | 32.1 |
Romania | 20% | 16% | 5.3 | 19,667 | 27.5 |
Serbia | 18% | 14% | 8.2 | 13,113 | 29.1 |
Slovakia | 21% | 14% | 7.2 | 27,285 | 26.1 |
Slovenia | 21% | 13% | 8.5 | 28,418 | 25.7 |
Central Latin America | 29% | 10% | 4.8 | 14,255 | 42.7 |
Colombia | 25% | 12% | 3.8 | 12,716 | 51.1 |
Costa Rica | 29% | 10% | 2.5 | 14,392 | 48.2 |
El Salvador | 27% | 9% | 1.7 | 7,707 | 40.8 |
Guatemala | 24% | 9% | 2.0 | 7,147 | 48.7 |
Honduras | 24% | 11% | 2.1 | 4,231 | 50.1 |
Mexico | 32% | 9% | 5.3 | 16,460 | 48.2 |
Nicaragua | 25% | 10% | 2.5 | 4,785 | 46.6 |
Panama | 30% | 10% | 3.5 | 19,872 | 51.0 |
Venezuela | 29% | 9% | 8.6 | ||
East Africa | 8% | 19% | 1.5 | 2,044 | 33.8 |
Burundi | 5% | 20% | 0.4 | 803 | 39.2 |
Comoros | 11% | 18% | 0.7 | 1,432 | 45.0 |
Djibouti | 13% | 17% | 1.8 | 2,997 | 44.1 |
Eritrea | 7% | 20% | |||
Ethiopia | 6% | 23% | 1.3 | 1,425 | 33.2 |
Kenya | 11% | 19% | 1.2 | 2,753 | |
Madagascar | 7% | 20% | 1.4 | 1,37 | 42.7 |
Malawi | 8% | 17% | 0.6 | 1,090 | 46.1 |
Mauritius | 23% | 19% | 3.7 | 18,256 | 35.8 |
Mozambique | 8% | 16% | 0.8 | 1,080 | 45.6 |
Rwanda | 6% | 16% | 0.5 | 1,616 | 50.4 |
Seychelles | 31% | 19% | 6.0 | 25,218 | 46.8 |
Somalia | 7% | 19% | 1.7 | ||
Sudan | 12% | 19% | 5.5 | 4,188 | 35.4 |
United Republic of Tanzania |
11% | 19% | 1.1 | 2,402 | 37.8 |
Uganda | 7% | 17% | 1.1 | 1,637 | 41.0 |
Zambia | 14% | 18% | 1.3 | 3,633 | 57.1 |
East Asia | 8% | 20% | 9.3 | 12,737 | 41.2 |
China | 8% | 19% | 9.5 | 12,759 | 42.2 |
China (Hong Kong SAR) | 9% | 22% | 6.9 | 52,789 | |
Democratic People’s Republic of Korea |
4% | 22% | 2.7 | ||
Taiwan | 8% | 19% | |||
Eastern Europe | 25% | 16% | 13.7 | 20,894 | 34.3 |
Belarus | 24% | 16% | 10.0 | 17,944 | 26.7 |
Estonia | 20% | 16% | 17.3 | 27,114 | 34.6 |
Latvia | 24% | 16% | 6.4 | 22,217 | 35.1 |
Lithuania | 27% | 17% | 8.0 | 26,252 | 37.7 |
Republic of Moldova |
18% | 18% | 2.6 | 4,763 | 27.0 |
Russian Federation |
26% | 16% | 16.5 | 25,285 | 37.7 |
Ukraine | 22% | 17% | 7.0 | 8,243 | 25.5 |
High-Income Asia Pacific |
4% | 13% | 11.2 | 37,526 | 31.0 |
Japan | 3% | 14% | 10.6 | 37,323 | 32.1 |
Singapore | 7% | 14% | 11.8 | 80,305 | |
Republic of Korea | 6% | 11% | 12.7 | 33,426 | 31.6 |
High-Income English-speaking countries |
33% | 6% | 18.5 | 48,617 | 38.6 |
Australia | 28% | 6% | 23.7 | 43,315 | 34.7 |
Canada | 29% | 7% | 20.0 | 42,958 | 34.0 |
Ireland | 25% | 6% | 12.4 | 49,327 | 31.9 |
New Zealand | 30% | 5% | 17.2 | 34,469 | |
United Kingdom | 28% | 6% | 8.1 | 38,252 | 34.1 |
United States of America | 35% | 6% | 20.1 | 51,932 | 41.0 |
Melanesia | 25% | 6% | 1.8 | 3,930 | 40.9 |
Fiji | 35% | 9% | 2.5 | 8,222 | 36.4 |
Papua New Guinea | 24% | 6% | 1.3 | 3,616 | 41.8 |
Solomon Islands | 23% | 6% | 7.8 | 2,021 | 37.0 |
Vanuatu | 29% | 6% | 2.1 | 2,892 | 37.3 |
Middle East and North Africa |
34% | 18% | 7.4 | 17,573 | 27.0 |
Algeria | 30% | 18% | 5.2 | 13,483 | 27.6 |
Bahrain | 37% | 18% | 26.4 | 43,837 | |
Egypt | 40% | 13% | 3.1 | 9,880 | 31.8 |
Iran | 30% | 22% | 10.2 | 16,924 | 38.8 |
Iraq | 32% | 17% | 5.7 | 14,697 | 29.5 |
Jordan | 40% | 17% | 3.4 | 8,622 | 33.7 |
Kuwait | 44% | 14% | 29.7 | 70,832 | |
Lebanon | 34% | 18% | 4.6 | 13,831 | 31.8 |
Libya | 37% | 18% | 12.5 | ||
Morocco | 28% | 19% | 2.3 | 7,079 | |
Palestine | 34% | 16% | |||
Oman | 34% | 20% | 20.8 | 40,283 | |
Qatar | 45% | 17% | 65.1 | 120,860 | |
Saudi Arabia | 41% | 20% | 22.0 | 49,958 | |
Syria | 29% | 19% | 2.5 | ||
Tunisia | 32% | 19% | 3.6 | 10,751 | 35.8 |
Turkey | 36% | 18% | 6.1 | 22,402 | 41.2 |
United Arab Emirates |
41% | 17% | 26.7 | 64,127 | |
Yemen | 19% | 26% | 1.4 | 3,767 | 36.7 |
North Western Europe |
20% | 10% | 10.1 | 45,171 | 30.1 |
Austria | 18% | 12% | 8.7 | 44,337 | 30.5 |
Belgium | 21% | 9% | 10.2 | 41,384 | 28.1 |
Denmark | 17% | 10% | 45,057 | 28.5 | |
Finland | 20% | 10% | 11.5 | 39,018 | 26.8 |
Germany | 20% | 10% | 10.4 | 43,561 | 31.4 |
Greenland | 22% | 9% | 13.6 | ||
Iceland | 20% | 10% | 9.0 | 41,424 | 25.6 |
Luxembourg | 19% | 10% | 20.7 | 93,655 | 31.2 |
Netherlands | 19% | 10% | 11.9 | 45,668 | 28.6 |
Norway | 22% | 9% | 13.6 | 63,419 | 26.8 |
Sweden | 19% | 10% | 6.3 | 44,168 | 27.2 |
Switzerland | 17% | 9% | 5.6 | 57,218 | 32.5 |
Polynesia and Micronesia | 53% | 1% | 2.4 | 2,961 | 17.7 |
American Samoa | 58% | 1% | 0.7 | ||
Cook Islands | 58% | 1% | |||
French Polynesia | 55% | 1% | 3.4 | ||
Kiribati | 47% | 1% | 0.8 | 1,815 | |
Marshall Islands | 51% | 1% | 2.1 | 3,685 | |
Micronesia (Federated States of) |
49% | 1% | 1.9 | 3,130 | 40.1 |
Nauru | 56% | 1% | 4.4 | 12,561 | |
Niue | 56% | 1% | |||
Palau | 55% | 1% | 12.4 | 13,577 | |
Samoa | 54% | 1% | 2.0 | 5,511 | 42.0 |
Tokelau | 52% | 1% | |||
Tonga | 54% | 1% | 1.9 | 5,032 | 37.5 |
Tuvalu | 52% | 1% | 1.4 | 3,266 | 39.1 |
South Asia | 5% | 48% | 2.2 | 4,955 | 33.7 |
Afghanistan | 5% | 38% | 0.9 | 1,839 | |
Bangladesh | 5% | 41% | 1.3 | 2,973 | 32.1 |
Bhutan | 8% | 39% | 4.4 | 7,366 | 38.8 |
India | 5% | 51% | 2.4 | 5,390 | 35.2 |
Nepal | 5% | 37% | 1.3 | 2,266 | 32.8 |
Pakistan | 8% | 42% | 2.0 | 4,576 | 30.7 |
South Western Europe |
23% | 7% | 6.7 | 33,426 | 34.5 |
Andorra | 27% | 7% | 5.8 | ||
Cyprus | 25% | 7% | 6.4 | 29,786 | 35.6 |
France | 22% | 7% | 6.7 | 37,531 | 32.3 |
Greece | 24% | 6% | 7.5 | 24,082 | 35.8 |
Israel | 27% | 7% | 8.9 | 31,702 | 41.4 |
Italy | 22% | 6% | 6.5 | 33,946 | 34.7 |
Malta | 28% | 6% | 6.4 | 32,350 | |
Portugal | 20% | 6% | 6.1 | 26,024 | 35.6 |
Spain | 24% | 6% | 6.5 | 31,195 | 36.0 |
Southeast Asia | 8% | 32% | 3.6 | 9,404 | 37.9 |
Brunei Darussalam |
18% | 26% | 35.4 | 76,089 | |
Cambodia | 4% | 32% | 4.0 | 3,124 | |
Indonesia | 8% | 31% | 3.1 | 10,003 | 39.5 |
Lao People’s Democratic Republic |
5% | 30% | 4.0 | 5,436 | 36.4 |
Malaysia | 16% | 27% | 9.8 | 24,195 | 46.3 |
Maldives | 11% | 35% | 3.5 | 13,737 | 38.4 |
Myanmar | 5% | 34% | 2.5 | 4,770 | 38.1 |
Philippines | 7% | 30% | 1.8 | 6,586 | 40.1 |
Sri Lanka | 9% | 36% | 1.6 | 10,727 | 39.2 |
Thailand | 11% | 29% | 6.7 | 14,853 | 37.8 |
Timor-Leste | 3% | 33% | 1.2 | 1,888 | |
Viet Nam | 3% | 39% | 3.5 | 5,265 | 34.8 |
Southern Africa | 34% | 17% | 8.2 | 9,967 | 58.8 |
Botswana | 29% | 18% | 6.4 | 15,915 | 60.5 |
Lesotho | 26% | 15% | 2.0 | 2,677 | 54.2 |
Namibia | 24% | 21% | 5.2 | 9,617 | 61.0 |
South Africa | 38% | 17% | 10.7 | 12,372 | 63.4 |
Swaziland | 27% | 15% | 2.5 | 7,871 | 51.5 |
Zimbabwe | 23% | 16% | 1.7 | 1,925 | 43.2 |
Southern Latin America | 26% | 13% | 6.5 | 16,238 | 49.5 |
Argentina | 30% | 10% | 8.1 | 18,798 | 42.7 |
Brazil | 24% | 14% | 6.1 | 15,371 | 51.3 |
Chile | 33% | 10% | 6.3 | 22,226 | 47.7 |
Paraguay | 22% | 13% | 4.9 | 8,502 | 48.0 |
Uruguay | 31% | 11% | 10.1 | 19,828 | 41.7 |
Western Africa | 14% | 23% | 1.6 | 3,882 | 40.9 |
Benin | 13% | 19% | 1.8 | 2,001 | 47.8 |
Burkina Faso | 8% | 23% | 1.5 | 1,582 | 35.3 |
Cabo Verde | 17% | 20% | 1.4 | 5,928 | |
Cameroon | 16% | 18% | 1.9 | 3,196 | 46.5 |
Chad | 10% | 22% | 2.7 | 2,077 | 43.3 |
Cote d’Ivoire | 14% | 18% | 1.7 | 3,055 | 41.7 |
Gambia | 14% | 21% | 1.1 | 1,550 | |
Ghana | 18% | 19% | 2.0 | 3,869 | 42.2 |
Guinea | 10% | 21% | 4.6 | 1,735 | 33.7 |
Guinea Bissau | 11% | 20% | 1.6 | 1,398 | 50.7 |
Liberia | 11% | 20% | 0.7 | 805 | 33.2 |
Mali | 11% | 21% | 1.9 | 1,865 | 33.0 |
Mauritania | 15% | 20% | 2.9 | 3,655 | 32.4 |
Niger | 7% | 23% | 0.6 | 904 | 34.0 |
Nigeria | 15% | 26% | 1.3 | 5,672 | 43.0 |
Sao Tome and Principe | 16% | 18% | 0.9 | 2,902 | 30.8 |
Senegal | 13% | 23% | 1.8 | 2,219 | 40.3 |
Sierra Leone | 12% | 20% | 0.9 | 1,692 | 34.0 |
Togo | 12% | 19% | 1.6 | 1,315 | 43.0 |
1+ Data collected from NCD-RisC , for the 2014 year.
2* Data collected from NCD-RisC , for the 2014 year. Region data was derived from rounded numbers. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet 2017; published online Oct 10.
3# Data collected from the World Bank, for the latest year available 2014. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. The World Bank source – Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States. Indicator code – EN.ATM.CO2E.PC.”
4^ Data collected from World Bank, for the latest year available 2014. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser’s prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.
Data are in constant 2011 international dollars.
5 Data collected from the World Bank, using latest data available from the 2008-2015 period. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.”
Methods for calculating figures in the table
Female obesity prevalence (1+) is the percentage calculated from data collected from NCD-RisC, for 2014.(1) The 5-19 year old girl underweight prevalence (2*) is from data collected from NCD-RisC, for 2014.(1) Region data was derived from rounded numbers.
Carbon footprint (3#) was calculated from World Bank data(2) (indicators used include: EN.ATM.CO2E.KT.CE, EN.ATM.HFCG.KT.CE, EN.ATM.METH.KT.CE, EN.ATM.NOXE.KT.CE, EN.ATM.PFCG.KT.CE, EN.ATM.SG6G.KT.CE) for the latest year available over the period of 2008-2014. Carbon footprint was defined as CO2 emissions and all other greenhouse gases (methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6)) CO2 equivalents, given in thousand metric tonnes per capita. This method is recommended by the World Bank to gauge a comprehensive calculation of the carbon footprint for each country and associating region.
GDP per capita (4^) is from the World Bank (NY.GDP.MKTP.PP.KD) for the latest year available (2014), and is in constant 2011 international dollars(3). Data was last updated 15/02/2018. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser’s prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.
GINI coefficient (5) is from data collected from the World Bank, using latest data available from the 2008-2015 period.(4) Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
Appendix 4: Potential activities, partners and double- or triple-duty actions according to program or policy interventions
Programmes / policy interventions | Potential Activities and Partners | Double / triple duty action | |
Fiscal policies such as taxation on unhealthy foods and beverages | Junk-food taxes, taxes on sugar-sweetened beverages (e.g. Mexico, UK), high-fat / sugar foods, meats, (the short-lived “fat-tax” in Kerala state in India; turkey tails in Samoa; fatty meats in Poland), etc. These actions may also include intermediate steps such as passing of relevant regulations / legislation and establishing / strengthening capacities of regulatory bodies | Ministry of Finance; Ministry of Commerce / Industry; civil society organisations; regulatory bodies, Ministry of Health; food industry federations, etc. | Taxes on sugar-sweetened beverages is a potential triple-duty action that will likely impact both undernutrition (by eliminating empty calories from diets) as well as addressing obesity. Taxation on meats / meaty foods may reduce consumption of unhealthy meat-based foods thereby reducing obesity as well as reduced methane production by cattle. |
Active Transport / built environment | Urban redesign to promote walking / cycling (such as in The Netherlands; Poland); disincentivize driving with tariffs, improved public transport and subsidies for use of public transport (such as those offered by some of the corporate sector in the US) | Ministry of transport, Ministry of Urban / city planning; corporate business houses. | Potential double-duty actions by reducing obesity and GHG emissions by increasing physical activity and public transport. |
Subsidies for production of fruits and vegetables | Fiscal subsidies to producers for production of fruits / vegetables. | Ministry of Agriculture; Ministry of Finance. Grocery Manufacturers associations. | Subsidies are potentially triple-duty actions, with the ability to improve undernutrition, and reduce obesity and GHG produced from alternative foods such as meats. |
Nutrition labelling of foods | Food labels on all unhealthy processed foods (e.g in Chile; South Africa); or colour-coded labels for high / medium / low sugar beverages (such as in Sri Lanka) or labels for nutrient contents of all processed foods or all foods served in restaurants | Ministry of Health, Ministry of Finance; Grocery Manufacturers Associations; restaurant associations. | Potential triple-duty action, with opportunity to improve undernutrition (by encouraging consumption of healthier foods), reduce obesity (by discouraging high fat / high sugar / other unhealthy foods), and reduce GHG production linked to production of high-fat meats. |
Media restrictions | Media restrictions on advertisement of unhealthy food products akin to tobacco advertisements restrictions | Ministry of Health, National Health promotion Agency, Ministry of Commerce / Industry, National TV / Radio associations, consumer associations; regulatory bodies to monitor media. | Potential double-duty action to reduce undernutrition and overweight, especially if media restrictions are on the targeting young children; |
Public awareness campaigns | Population-based health promotion and mass media campaigns on diets (such as in Mexico, South Africa, Poland), physical activity and use of bicycles or public transport. | Ministry of Sports; Ministry of Urban / city planning, Ministry of Health, TV / Radio associations | Potential triple-duty action to reduce undernutrition: promoting a diet of healthy foods and the restriction of empty calories found in junk food can help reduce overweight / obesity as well. Physical or public transport can reduce GHG emissions by reducing car use. |
School-based interventions | Nutrition education, growth monitoring and screening children (such as in Poland), promoting physical activity and use of active transport options; banning sale of sugary drinks / junk foods in schools (such as in Mexico, Chile, Poland, South Africa, Thailand, Sri Lanka, USA) | Ministry of Education; Ministry of Health | Potential triple-duty actions by reducing both undernutrition and overweight, and reducing GHG emissions by encouraging active transport options. |
Appendix 5 Identifying double- or triple-duty policy actions
The aim of this study was to identify existing policy recommendations for governments within high-level reports on obesity, undernutrition, physical activity and/or climate change and to examine the extent to which these recommendations could act as triple duty actions. The Lancet Commission on Obesity (LCO) Commissioners were invited to identify key high-level international reports on obesity, undernutrition, climate change and physical activity published between 2007 and 2017. The reports identified (n=66) were collated and prioritized according to their level of authoritative impact, aiming to achieve a balance between United Nations (UN) and independent reports, and reflecting malnutrition in all its forms. This process refined the number of reports to eleven. Reports that did not present specific recommendations for government were then excluded, leaving six final reports for analysis. Contrary to expectations, none of the climate change reports initially identified by LCO Commissioners provided specific recommendations for government. Therefore, reports addressing obesity, undernutrition and physical activity were the focus of initial analyses, and the reports were later assessed for their potential impact on climate change, as detailed below.
All individual government recommendations were extracted from the six reports, as shown in Table 1, and categorized into overarching domains. Categorization was undertaken independently for nutrition and for physical activity. The two most recent and high-level reports were used to guide this process, namely the High Level Panel of Experts on Food Security and Nutrition (HLPE) report on Nutrition and food systems (2017), and the World Health Organization (WHO) Global action plan on physical activity, draft 2 (2017). Both these reports adopt an existing overarching structure to categorize their individual policy recommendations, and this same structure was applied to the recommendations extracted from the four other reports. Following this process, it was evident that the HLPE Nutrition and food systems report and WHO Global action plan on physical activity report captured all key government recommendations and adequately covered the domains identified in the other reports. The subsequent analysis was therefore focused on these two key reports only.
Table 1: Government recommendations extracted from key high-level reports on obesity, undernutrition and physical activity
Report focus | Title (year) | Recommendations |
Obesity | Lancet Series I. Changing the future of obesity: science, policy and action (2011) | 23 |
Obesity | WHO Global action plan for the prevention and control of NCDs, 2013-2020 (2013) | 71 |
Undernutrition | IFPRI Global Nutrition Report (2016) | 30 |
Undernutrition | FAO Synthesis of guiding principles on agriculture programming for nutrition (2013) | 20 |
Nutrition | HLPE Nutrition and food systems (2017) | 37 |
Physical Activity | WHO Global action plan on physical activity, draft 2 (2017) | 74 |
TOTAL | 255 |
Since no specific government recommendations for climate change were identified through the reports, four LCO Commissioners and Fellows (Mario Herrera, Mark Howden, Susanna Mills and Wilma Waterlander) who had extensive expertise in climate change were invited to rate the recommendations in the remaining two reports for potential impact on climate change mitigation, and adaptation. This process was undertaken independently by the Commissioners using a five-point scale (1=no impact to 5=substantial impact). The scores were amalgamated by taking the highest score for each rating. Appendix 6 shows the scoring results for the full government recommendations for nutrition and Appendix 10 shows the scoring results for physical activity. A condensed version of the recommendations and associated ratings are shown in Table 1 for nutrition and Table 2 for physical activity in the main manuscript.
Appendix 6: Nutrition recommendations, drawn from High Level Panel of Experts Nutrition and Food Systems Report, scored for potential impact on Climate Change mitigation and adaptation*
HLPE domain | Recommendation | Potential climate change impact | |
Mitigation | Adaptation | ||
Strengthen the integration of nutrition within national policies, programmes and budgets | Design context-specific policies and programmes that support the co-existence of diverse food systems and diets | 5 | 3 |
Integrate a nutrition-focused food system approach into national development, health and economic plans | 3 | 2 | |
Facilitate an inclusive dialogue and develop nutrition strategies at national and local levels, focusing on improving food environments. | 3 | 2 | |
Foster policy coherence in order to improve diets and nutrition, through enhanced coordination across sectors | 3 | 3 | |
Increase the allocation for nutrition in national budgets and identify greatest synergies for improved nutritional outcomes within existing spend | 4 | 2 | |
Improve food and nutrition literacy throughout society through popular education programmes and other schemes | 4 | 2 | |
Improve capacity by investing in a workforce of nutrition practitioners, and educating food system professionals on nutrition | 2 | 2 | |
Strengthen global cooperation to end malnutrition and hunger | Increase official development assistance (ODA) to support more sustainable food systems, address malnutrition, and prevent diet-related NCDs | 4 | 4 |
Avert famines by strengthening local food systems and longer-term development support, and investing in appropriate humanitarian aid | 3 | 5 | |
Address the impacts of trade and investment agreements on food environments and diets | Assess multilateral and bilateral trade and investment agreements to ensure they do not have a negative impact on food environments and diets | 2 | 2 |
Ensure that trade and investment agreements are consistent with nutrition policies and favour more sustainable food systems | 2 | 2 | |
Address the nutritional vulnerabilities of particular groups | Ensure that vulnerable and marginalized groups are able to achieve a sufficient, diverse, culturally appropriate nutritious diet | 2 | 3 |
Improve nutritional outcomes by enhancing women’s rights and empowerment | Ensure that laws and policies provide men and women equal access to resources | 2 | 2 |
Value the importance of, and redistribute, unpaid care work within the household | 1 | 1 | |
Strengthen rural women’s participation and representation at all levels of policy-making for Food Security and Nutrition (FSN) | 2 | 3 | |
Create an enabling environment for breastfeeding, ensuring that women’s economic security and rights are promoted | 2 | 1 | |
Recognize and address conflicts of interest | Acknowledge conflicts of interest (COIs) and imbalanced power relationships between stakeholders, and establish participatory mechanisms to address them | 2 | 2 |
Ensure transparency and accountability mechanisms through coordinated, open access monitoring systems to prevent and address COIs | 2 | 1 | |
Protect nutrition sciences against undue influence and corruption, through appropriate rules, effectively monitored and enforced | 2 | 1 | |
Improve data collection and knowledge-sharing on food systems and nutrition | Promote nutrition-focused, policy-relevant research on food systems and food demand | 2 | 2 |
Improve the availability and quality of multi-sectoral information systems that capture diet, food composition and nutrition-related data | 2 | 2 | |
Invest in participatory systems for the sharing of knowledge and best practices among stakeholders in the food supply chain | 3 | 5 | |
Draw on the knowledge, experience and insights of those who are not usually regarded as members of the nutrition community | 2 | 3 | |
Enhance opportunities to improve diet and nutrition outcomes along food supply chains | Support initiatives that contribute to the production of nutritious, locally-adapted foods and contribute to dietary quality and diversity | 3 | 3 |
Protect and enhance nutritional value along food supply chains | 2 | 2 | |
Ensure the food supply is healthy for the consumer | 1 | 2 | |
Improve the quality of food environments | Make nutritious foods more accessible and convenient in public places, school gardens, rural marketplaces and in homes | 2 | 1 |
Design and implement policies and regulations that improve the built environment to promote nutritious food | 3 | 2 | |
Regulate health claims on food packaging and adopt an easily interpreted front labelling system | 2 | 1 | |
Strengthen national food safety standards and quality assurance and develop better global surveillance systems | 1 | 1 | |
Phase-out advertising and promotion of unhealthy foods, especially to children and adolescents | 1 | 1 | |
Institute policies and practices that implement the International Code of Marketing of Breast-milk Substitutes | 1 | 1 | |
Create consumer demand for nutritious food | Develop global and national guidelines for healthy and sustainable diets and make guidelines actionable and user-friendly for consumers | 2 | 2 |
Implement economic and social policies that increase demand for nutritious foods and lower demand for nutrient-poor foods | 3 | 2 | |
Ensure that social protection programmes such as school feeding and cash transfers lead to improved nutritional outcomes | 2 | 1 | |
Promote food cultures, including cooking skills and the importance of food in cultural heritage, to promote nutrition literacy | 2 | 2 |
* Rating 1= no impact to 5 = substantial impact