| Literature DB >> 33291709 |
Rhys Jones1, Alexandra Macmillan2, Papaarangi Reid1.
Abstract
Climate change mitigation policies can either facilitate or hinder progress towards health equity, and can have particular implications for Indigenous health. We sought to summarize current knowledge about the potential impacts (co-benefits and co-harms) of climate mitigation policies and interventions on Indigenous health. Using a Kaupapa Māori theoretical positioning, we adapted a validated search strategy to identify studies for this scoping review. Our review included empirical and modeling studies that examined a range of climate change mitigation measures, with health-related outcomes analyzed by ethnicity or socioeconomic status. Data were extracted from published reports and summarized. We identified 36 studies that examined a diverse set of policy instruments, with the majority located in high-income countries. Most studies employed conventional Western research methodologies, and few examined potential impacts of particular relevance to Indigenous peoples. The existing body of knowledge is limited in the extent to which it can provide definitive evidence about co-benefits and co-harms for Indigenous health, with impacts highly dependent on individual policy characteristics and contextual factors. Improving the quality of evidence will require research partnerships with Indigenous communities and study designs that centralize Indigenous knowledges, values, realities and priorities.Entities:
Keywords: Indigenous health; climate change; climate policy; environmental justice; equity
Mesh:
Year: 2020 PMID: 33291709 PMCID: PMC7730028 DOI: 10.3390/ijerph17239063
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for study inclusion.
Details of included studies.
| Citation | Jurisdiction | Study Type | Indigenous Population/Methodology 1 | Policy Instrument | Sector | Description of Policy or Intervention | Implications for Indigenous Health 2 |
|---|---|---|---|---|---|---|---|
| Asikainen 2017 [ | Finland | Modeling | No | Multiple | Multiple | Energy efficiency and renewable energy | – |
| Bailey 2019 [ | Greece | Health impact assessment | No | Multiple | Buildings | Reducing residential wood burning | ↑ |
| Barrington-Leig 2019 [ | China | Cross-sectional survey | No | Multiple | Buildings | Reducing household coal use | ↑ ↓ |
| Barron 2018 [ | USA | Modeling | No | Economic Instruments —Taxes | Multiple | Carbon tax | ↑ ↓ |
| Basu 2014 [ | India | Cross-sectional survey | Population | Government Provision of Public Goods or Services | AFOLU 3 | Agro-forestry | ↑ |
| Berrueta 2017 [ | Mexico | Case study | Population | Government Provision of Public Goods or Services | Buildings | Improved cookstoves | ↑ |
| Bilbao 2010 [ | Venezuela | Experiment | Population | Government Provision of Public Goods or Services | AFOLU | Indigenous use of fire for forest protection | ↑ |
| Boyce 2013 [ | USA | Modeling | No | Scenario rather than specific policy/ies | Industry | Reducing industrial emissions | ↑ |
| Breysse 2011 [ | USA | Before–after comparison | No | Government Provision of Public Goods or Services | Buildings | Renovation of low-income housing | ↑ |
| Bubna-Litic 2012 [ | Canada and Australia | Case studies | Population | Economic Instruments —Taxes and Tradable Allowances | Multiple | Compares carbon pricing policies | ↑ ↓ |
| Caillavet 2016 [ | France | Modeling | No | Economic Instruments —Taxes | Multiple | Food taxes | ↓ |
| Champion 2017 [ | USA | Mixed methods | Population Methodology | Multiple | Buildings | Home heating in Navajo nation | ↑ |
| Chapman 2009 [ | New Zealand | Cost-benefit analysis of cluster randomized trial | No | Government Provision of Public Goods or Services | Buildings | Home insulation in low-income areas | ↑ |
| Cushing 2018 [ | USA | Before–after comparison | No | Economic Instruments —Tradable Allowances | Industry | Cap-and-trade program | ↓ |
| Dyer 2012 [ | Mexico | Modeling | No | Regulatory Approaches | AFOLU | REDD+ 4 | ↑ ↓ |
| Feng 2010 [ | United Kingdom | Modeling | No | Economic Instruments —Taxes | Multiple | GHG emissions taxes | ↓ |
| Garg 2011 [ | India | Modeling | No | Multiple | Multiple | Reducing air pollution | ↑ |
| Ji 2015 [ | China | Modeling | No | Scenario rather than specific policy/ies | Transport | Increased EV use | ↓ |
| Khatun 2015 [ | Tanzania | Case study | No | Regulatory Approaches | AFOLU | PFM 5 | ↑ |
| Krause 2013 [ | Ecuador | Cross-sectional survey | Population | Regulatory Approaches | AFOLU | REDD+ | ↑ ↓ |
| Li 2017 [ | Malaysia | Modeling | No | Economic Instruments —Subsidies | Multiple | Removing fossil fuel subsidies | ↑ ↓ |
| Lindsay 2011 [ | New Zealand | Modeling | Population | Scenario rather than specific policy/ies | Transport | Transport mode shift | ↑ |
| Ni Mhurchu 2015 [ | New Zealand | Modeling | Population | Economic Instruments —Taxes | Multiple | Food tax including GHG | ↑ |
| Reynolds 2019 [ | United Kingdom | Modeling | No | Scenario rather than specific policy/ies | Multiple | Dietary changes | ↑ ↓ |
| Richards 2019 [ | Canada | Case studies | Population Methodology | Voluntary Actions | Multiple | Community initiatives | ↑ |
| Richardson 2012 [ | USA | Health impact assessment | No | Economic Instruments —Tradable Allowances | Multiple | Cap-and-trade program | ↑ ↓ |
| Sánchez 2017 [ | The Dominican Republic | Case studies | Population | Government Provision of Public Goods or Services | Energy | Micro- hydropower systems | ↑ |
| Shammin 2009 [ | USA | Modeling | No | Economic Instruments —Tradable Allowances | Multiple | Cap-and-trade program | ↑ ↓ |
| Shrubsole 2016 [ | United Kingdom | Modeling | No | Government Provision of Public Goods or Services | Buildings | Energy efficiency retrofitting of homes | ↓ |
| Sikka 2013 [ | USA | Case study | Population Methodology | Voluntary Actions | Energy | Transition to biomass energy | ↑ ↓ |
| Sovacool 2015 [ | England | Case study | No | Government Provision of Public Goods or Services | Buildings | Energy efficiency retrofitting of homes | ↑ ↓ |
| Sunderlin 2017 [ | Multiple jurisdictions | Longitudinal (before–after) survey | Population | Regulatory Approaches | AFOLU | REDD+ | – |
| Tainio 2017 [ | England | Modeling | No | Scenario rather than specific policy/ies | Multiple | Diet and physical activity scenarios | ↑ ↓ |
| Williams 2018 [ | Great Britain | Modeling | No | Scenario rather than specific policy/ies | Multiple | Modeling of energy scenarios | ↑ ↓ |
| Winkler 2017 [ | South Africa | Modeling | No | Government Provision of Public Goods or Services | Multiple | Options for recycling carbon tax revenue | ↑ |
| Woodcock 2018 [ | England | Modeling | No | Scenario rather than specific policy/ies | Transport | Cycling mode share scenarios | ↑ |
1 Indicates studies that included an identifiable Indigenous population (‘Population’) and/or used Indigenous methodologies (‘Methodology’). 2 Potential implications of the policy or scenario for Indigenous health, either neutral (–), positive (↑), negative (↓) or mixed (↑ ↓). 3 AFOLU = Agriculture, Forestry and Other Land Use. 4 REDD+ = Reducing Emissions from Deforestation and forest Degradation in developing countries, plus sustainable forest management and enhancement of forest carbon stocks. 5 PFM = Participatory Forest Management.
Distribution of studies according to policy instrument and sector.
| AFOLU 1 | Buildings | Energy | Industry | Transport | Multiple Sectors | Totals | |
|---|---|---|---|---|---|---|---|
| Economic instruments | 1 | 8 | 9 | ||||
| Government provision | 2 | 5 | 1 | 2 | 10 | ||
| Regulatory approaches | 4 | 4 | |||||
| Voluntary actions | 1 | 1 | |||||
| Multiple policy types | 3 | 2 | 5 | ||||
| Scenario | 1 | 3 | 3 | 7 | |||
| Totals | 6 | 8 | 2 | 2 | 3 | 15 | 36 |
1 AFOLU = Agriculture, Forestry and Other Land Use.