Cities, Climate and Inequalities

Mylène Riva

April 2024

Mylène Riva, Associate Professor in the Department of Geography, McGill University


Canada is both one of the largest and most diverse producers of energy in the world as well as one of the largest consumers of energy. Overall, when considering the abundance and reliability of energy resources, Canada ranks high in terms of energy security (World Energy Council, 2020). Its high energy intensity is attributed to a combination of factors, including a generally cold climate, increasingly warm summers, a dispersed population, affordable energy costs and a high standard of living (Canada Energy Regulator, 2019a). 

Despite this favourable perspective, not all Canadians can attain levels of domestic energy services required to meet their needs, maintain healthy indoor temperatures and live with dignity—a situation known as energy poverty (Bouzarovski & Petrova, 2015; Thomson et al., 2017; Simcock & Mullen, 2016). Indeed, one in five Canadian households are facing energy poverty (Riva et al., 2021). This proportion exceeds that of several European countries where, unlike in Canada, energy poverty has been a policy and research priority for many years (Bouzarovski et al., 2012). Energy poverty is a crucial issue in the effort to pursue the energy transition of the residential sector as well as climate adaptation strategies, since households facing energy poverty enter the energy transition at a disadvantage (Middlemiss, 2022). Using data from a representative pan-Canadian population survey, our study published in Energy Research and Social Science sheds light on the prevalence of energy poverty in Canada and on its social and geographical patterning (Riva et al., 2021). The results, summarized in this report, underscore the urgency of addressing the issue of energy poverty within the country.

Literature review

Energy poverty occurs when households cannot access sufficient energy services to maintain healthy indoor temperatures, meet their needs and live with dignity (Bouzarovski & Petrova, 2015; Thomson et al., 2017; Simcock & Mullen, 2016). These energy services are essential for everyday domestic activities such as heating and cooling, lighting rooms, using appliances (such as refrigeration and cooking) and communication. As a result, the restriction to the access to energy services can impact health and well-being (Ballesteros-Arjona et al., 2022; O’Sullivan, 2019). Energy poverty is a multi-faceted issue influenced by various factors. Among these are housing conditions (energy-inefficient dwellings, type and source of heating), household-level factors (income, housing tenure, household size and composition, needs and practices of household members) and factors related to energy systems (type of energy supply, tariffs). Energy poverty can be exacerbated by extreme weather events, which may necessitate increased energy use to stay warm or cool or lead to disruptions in energy services due to events like flooding, wildfires and storms. The relative importance of these factors in driving energy poverty can vary depending on the context (Mashhoodi et al., 2019). 

In high-income countries, two types of indicators are generally used to measure energy poverty: expenditure-based indicators and self-reported indicators. Expenditure-based indicators assess the energy cost burden relative to household income against fixed or relative thresholds. The most commonly used indicator of this type classifies households as facing energy poverty if they spend more than 10% of their annual income on domestic energy (fixed threshold). Developed in 1991 in England, the indicator using the 10% threshold represented, at the time, about twice the national median share of energy cost to income (Boardman, 1991). Since then, different jurisdictions, including in Canada, have applied the 10% threshold in both research and policy. Another expenditure-based indicator categorizes households in energy poverty if their share of energy spending relative to household income is more than twice the national median share (about 6% in Canada; relative threshold). Self-reported indicators of energy poverty, by contrast, involve individuals’ self-assessment of the thermal comfort and energy efficiency of their dwelling (e.g., ability to maintain the house adequately warm or cool; humidity and mold problems) as well as their experience of energy-related financial difficulties such as accumulating arrears in utility bills, receiving disconnection notices or being disconnected from utilities. 

Significant social inequalities exist in the distribution of energy poverty, with some groups more likely to face energy poverty than others. These include lower-income households, women, younger and older adults, racialized and Indigenous peoples, and people with a long-term illness or disability (Robinson, 2019; Cronin de Chavez, 2017; Jessel et al., 2019; Chard & Walker, 2016; Kwon & Jang, 2017; O’Sullivan et al., 2017). Urban-rural inequalities in energy poverty are also observed in several countries (Bouzarovski & Tirado Herrero, 2017; Mulder et al., 2023; Robinson et al., 2018; Mould & Baker, 2017).

Facing energy poverty can have serious health and well-being consequences. Exposure to energy poverty is associated with increased risks of hospitalization and mortality for respiratory and cardiovascular diseases and can worsen certain chronic conditions (Liddell & Morris, 2010; Marmot Review Team, 2011; O’Sullivan, 2019; World Health Organization, 2018). Individuals facing energy poverty can experience multiple stressors, including having to limit energy use or compromise on other necessities such as food, leading to the “heat-or-eat” dilemma (Bhattacharya et al., 2003; Burlinson et al., 2022).

The overall objective of the study was to quantify the proportion of Canadian households facing energy poverty. In doing so, we aimed to identify who is most at risk of facing energy poverty based on household composition, dwelling conditions and socioeconomic characteristics and to explore geographic disparities in energy poverty distribution across provinces and along the urban-rural continuum (Riva et al., 2021).


Data used for this study are from the 2017 Survey of Household Spending (SHS), a biennial survey conducted by Statistics Canada (Statistics Canada, 2017) and completed by one individual from each participating household. In the SHS, participants report the amount of their last payments for electricity, for natural gas and/or for other fuels (heating oil, propane for heating and cooking, wood and other fuel for heating and cooking). This information is then adjusted to represent annual energy expenditure. Household income and income taxes data are drawn from Individual Tax Return files from the Canada Revenue Agency and then linked to the SHS via the Social Data Linkage Environment of Statistics Canada (with the consent of participants for their income data to be linked). 

Energy poverty was assessed using two expenditure-based indicators: the 10% threshold and the high share of energy expenditure in income, the latter of which is hereafter referred to as 2M (more than twice the national median). These indicators were calculated based on household income after taxes and after accounting for other housing costs, such as rent and mortgage. We then assessed the variation in energy poverty by housing conditions and characteristics, by the socioeconomic characteristics of the respondent to the SHS, by province, and between urban and rural areas. For brevity, this summary presents results for the 2M indicator only. Descriptive results were estimated as counts and were transformed into percentages before being released from the McGill-Concordia Research Data Centre RDC. We employed logistic regression models to compare the relative contribution of household composition, dwelling characteristics and socioeconomic and demographic characteristics in influencing energy poverty. Analyses were limited to the ten provinces. Statistics Canada granted access to SHS microdata. The analyses were performed at the RDC, a secure physical environment available to accredited researchers to access anonymized microdata for research purposes.


Overall, 19% of Canadian households are facing energy poverty, as measured using the 2M indicator. However, there is notable variation across provinces (Fig. 1), with the highest proportion of households experiencing energy poverty found in the Atlantic provinces, exceeding 30%. This is followed by Ontario and Saskatchewan. At 30%, the proportion of households facing energy poverty is considerably higher among rural households compared to their urban counterparts (Fig. 1).

Figure 1. Proportion of Canadian households facing energy poverty a
Source: Figure adapted from Riva et al., 2021; Data from the 2017 Survey of Household Spending

aHouseholds considered as facing energy poverty if their ratio of home energy costs to household income is greater than twice the national median ratio (more than ~6%)

Figure 2 provides a description of the distribution of energy poverty by household, dwelling and socioeconomic characteristics (a * next to the variable indicates that the difference within each variable is statistically significant at p<0.05). We see a higher proportion of energy poverty in one-person households, in households where at least one person is aged 65 years or older, and in households where at least one member is living with a long-term illness or disability. Conversely, a lower prevalence of energy poverty is observed in households with children. Regarding dwelling characteristics, energy poverty is more prevalent among those residing in detached dwellings, in dwellings constructed before 1960 and in dwellings in need of major repairs. The difference in energy poverty between homeowners and renters in not statistically significant. A greater proportion of energy poverty is observed in the reference person (i.e., the person who participated in the SHS) identifying as woman, reporting a lower educational level (less than high school diploma) or being unemployed the week before the survey. Energy poverty is overrepresented in households in the two lowest income quintiles. However, the distribution across quintiles of household income illustrates that energy poverty is faced not only by those from the lower-income spectrum.

A clear social patterning of energy poverty exists in Canada, aligning with findings from international studies. International evidence demonstrates that specific populations such as older adults, those living alone, single-parent families, people with fewer years of education, and those who are unemployed and/or receiving social assistance are more susceptible to experience energy poverty (Healy & Clinc, 2002; Ruse et al., 2019; Sunikka-Blank, 2020; Robinson, 2019). One-person and lone-parent households, households with older adults and with someone living with a long-term illness or disability are also at greater risk of facing energy poverty. Our results support previous research indicating a gendered experience of energy poverty. Compared to men, women are more vulnerable to energy poverty because of (among other factors) gendered household practices (domestic responsibilities, caring for children) and lower participation in the workforce (Johnson, 2020; Teariki et al., 2020; Healy, 2004; Petrova & Simcock, 2019; Robinson, 2019; Sunikka-Blank, 2020). 

Using logistic regression models, we assessed the relative influence of household composition, dwelling characteristics as well as socioeconomic and demographic factors on energy poverty (Fig. 3). Results are presented using odds ratios and 95% confidence intervals (see the footnote of Fig. 3 for an explanation). Compared to family households (couple with children), the odds of living in energy poverty are over four times higher for people living alone (one-person household) and more than twice as high for single-parent families. The odds are also significantly higher for households with at least one member living with a long-term illness or disability and for households with at least one member aged 65 years and older. 

Regarding dwelling characteristics, energy poverty is more prevalent in all types of dwellings compared to apartments. This likely reflects the increased heating costs associated with larger living spaces. Apartments benefit from reduced exposure to external walls, floors, roofs and windows, resulting in lower energy requirements per apartment household (Papada & Kaliampakos, 2016). Consistent with findings from other studies (Ambrose, 2015; Howden-Chapman et al., 2012; Hernández & Bird, 2010), energy poverty is significantly higher among renters compared to homeowners with a mortgage. This discrepancy is likely due to renters having less control over their dwelling and heating system and limited ability to make energy-efficient modifications to their homes due to their tenure status (Healy, 2004). Energy poverty also prevails in households living in older dwellings (constructed before 1960) and those requiring significant repairs, which can be attributed to the lower energy efficiency of these types of homes.

Figure 2. Energy poverty by household, dwellings and socioeconomic characteristics, 2017 Survey of Household Spending

a Estimates with coefficients of variation between 16.6% and 33.3%; estimates should be interpreted with caution.
b Estimates reported for the reference person, i.e., the household member who responded to the SHS.
* Indicates that the distribution of energy poverty within each variable is statistically significant at p<0.05.

Figure 3. Association between energy poverty, household composition, dwelling characteristics and geography, 2017 Survey of Household Spendinga

a Results of logistic regression models are presented using odds ratios alongside a 95% confidence interval. An odds ratio greater than 1 indicates that there is a higher likelihood of energy poverty being associated with the household, housing and geographical variables examined (adjusting for other variables). An odds ratio lower than 1 indicates a lower likelihood of observing energy poverty. The confidence interval (CI) informs on the precision of the estimated odds ratio. A large CI indicates a low level of precision of the OR, whereas a small CI indicates a higher precision of the odds ratio. The statistical significance level is set at p<0.05. In Fig. 2, the lighter shaded bars indicate that the association is not statistically significant.

Clear geographical patterns in the distribution of energy poverty are evident across Canada, with the odds of energy poverty being higher in rural areas compared to large population centres, and in the Atlantic provinces and Ontario in comparison to British Columbia. These geographic disparities indicate a strong regional influence on the distribution of energy poverty in Canada. In the Atlantic provinces, heating oil and biomass are more frequently used as primary heating sources compared to the rest of Canada (Canada Energy Regulator, 2019b). Lower median household income and a larger share of the population aged 65 years and older also characterize Atlantic Canada. More than 40% of the population in the Atlantic provinces resides in rural areas, where the cost of electricity distribution is often higher and houses tend to be larger, leading to increased heating costs. 

Further research is required to conceptualize and operationalize energy poverty indicators that are tailored to the Canadian context and to track trends over time. Emphasis should be placed on modeling energy requirements and developing indicators capable of capturing hidden energy poverty or overspending on energy (Papada & Kaliampakos, 2020). Indeed, expenditure-based measures like those employed in our study focus on quantifying the amount spent on utilities rather than assessing how much should be spent to meet energy needs (Hills, 2012). This approach may not capture households that intentionally limit their energy consumption to reduce expenses, known as ‘hidden energy poverty’ (Meyer et al., 2018), potentially leading to an underestimation of energy poverty. Renters for whom energy bills are included in their rent are excluded from expenditure-based measures, potentially resulting in an underestimation of the prevalence of energy poverty in urban areas, where there is a higher concentration of renters. Further research, including qualitative investigations, is necessary to gain insight into how energy poverty impacts the daily lives of Canadians, particularly subgroups of the population that may be more susceptible to energy poverty.


Decarbonizing the buildings sector is critical for Canada to meet its emission reduction targets for 2030 (Environment and Climate Change Canada, 2022) and achieve net-zero by 2050 (Government of Canada, 2023). While it is essential for new construction to meet energy efficiency standards, over 80% of the buildings expected to exist in 2050 have already been built. Substantial efforts are thus required to retrofit existing buildings to achieve Canada’s decarbonization goals (Environment and Climate Change Canada, 2022; McDonald et al., 2017). Residential energy efficiency programs (e.g., those providing better insulation, better air sealing and upgrades to the heating system) enhance thermal comfort, reduce energy expenditures and improve resilience to climate risks (Ribeiro et al., 2015). These programs also yield direct and indirect health and well-being benefits (Howden-Chapman et al., 2007; Poortinga et al., 2017; Rodgers et al., 2018; Sharpe et al., 2019; Thomson et al., 2013; Willand et al., 2020; Willand et al., 2015; Liddell and Morris, 2010; Thomson et al., 2009; Liddell & Guiney, 2015; Green & Gilbertson, 2008; Gilbertson et al., 2012). It is essential to ensure that these programs do not inadvertently exacerbate social inequities if access and benefits are not equitably distributed. This is especially important to consider given that nationwide investments in home energy efficiency programs, targeting both existing and new housing, have been made in the context of a national housing affordability crisis. To achieve a just transition and climate resilience in the residential sector, residential energy efficiency policies and programs should explicitly tackle energy poverty. 



The information presented in this summary are adapted from the following article: Riva M, Kingunza Makasi S, Dufresne P, O’Sullivan KC, Toth M (2021) Energy poverty in Canada: Prevalence, social and spatial distribution, and implications for research and policy. Energy Research and Social Sciences 81: 102237. The analyses presented in the original paper (and reproduced in part in the current summary) were conducted at the McGill-Concordia Research Data Centre, a branch of the Quebec Interuniversity Centre for Social Statistics (QICSS), which is part of the Canadian Research Data Centre Network (CRDCN). The services and activities provided by the QICSS are made possible by the financial or in-kind support of the Social Sciences and Humanities Research Council, the Canadian Institutes of Health Research, the Canada Foundation for Innovation, Statistics Canada, the Fonds de recherche du Québec ‒ Société et culture, the Fonds de recherche du Québec ‒ Santé and the Quebec universities. The views expressed in the original paper and in this summary are those of the authors and do not necessarily reflect those of the CRDCN or its partners.

To cite this article

Riva, M. (2024). Energy poverty in Canada: Social and geographic inequalities. In Cities, Climate and Inequalities Collection. VRM – Villes Régions Monde.


Reference text
Riva M, Kingunza Makasi S, Dufresne P, O’Sullivan KC, Toth M (2021) Energy poverty in Canada: Prevalence, social and spatial distribution, and implications for research and policy. Energy Research and Social Sciences 81: 102237.

Ambrose AR (2015) Improving energy efficiency in private rented housing: Why don’t landlords act? Indoor and Built Environment 24: 913-924.

Ballesteros-Arjona V, Oliveras L, Bolívar Muñoz J, et al. (2022) What are the effects of energy poverty and interventions to ameliorate it on people’s health and well-being?: A scoping review with an equity lens. Energy Research and Social Science 87.

Bhattacharya J, DeLeire T, Steven Haider S, et al. (2003) Heat or Eat? Cold-Weather Shocks and Nutrition in Poor American Families. American Journal of Public Health 93: 1149–1154.

Boardman B (1991) Fuel Poverty: From Cold Homes to Affordable Warmth. London: Belhaven Press.

Bouzarovski S and Petrova S (2015) A global perspective on domestic energy deprivation: Overcoming the energy poverty–fuel poverty binary. Energy Research & Social Science 10: 31-40.

Bouzarovski S, Petrova S and Sarlamanov R (2012) Energy poverty policies in the EU: A critical perspective. Energy Policy 49: 76-82.

Bouzarovski S and Tirado Herrero S (2017) Geographies of injustice: the socio-spatial determinants of energy poverty in Poland, the Czech Republic and Hungary. Post-Communist Economies 29: 27-50.

Burlinson A, Davillas A and Law C (2022) Pay (for it) as you go: Prepaid energy meters and the heat-or-eat dilemma. Social Science and Medicine 315.

Canada Energy Regulator (2019a) Canada’s Energy Transition: Historical and Future Changes to Energy Systems – Update – An Energy Market Assessment Reportno. Report Number|, Date. Place Published|: Institution|.

Canada Energy Regulator (2019b) Market Snapshot: Household expenditures on energy are highest in Atlantic Canada. Available at:

Chard R and Walker G (2016) Living with fuel poverty in older age: Coping strategies and their problematic implications. Energy Research & Social Science 18: 62-70.

Cronin de Chavez A (2017) The triple-hit effect of disability and energy poverty. In: Simcock N, Thomson H, Petrova S, et al. (eds) Energy Poverty and Vulnerability. Abingdon: Routledge, pp.169-187.

Environment and Climate Change Canada (2022) 2030 Emission Reduction Plan. Canada’s Next Steps for Clean Air and a Strong Economy. Reportno. Report Number|, Date. Place Published|: Institution|.

European Commission (2022) Energy Poverty Advisory Hub. Available at:

Gilbertson J, Grimsley M and Green G (2012) Psychosocial routes from housing investment to health: Evidence from England’s home energy efficiency scheme. Energy Policy 49: 122-133.

Government of Canada (2023) Government of Canada. Canadian Net-Zero Emissions Accountability Act. In: Canada Go (ed).

Green G and Gilbertson J (2008) Warm front, better health. Health impact evaluation of the Warm Front Scheme. Sheffield Hallam University, Centre for Regional Social and Economic Research. Available at: Reportno. Report Number|, Date. Place Published|: Institution|.

Healy J (2004) Housing, fuel poverty and health : a pan-European analysis. Ashgate.

Healy J and Clinc J (2002) Fuel poverty, thermal comfort and occupancy: results of a national household-survey in Ireland. Applied Energy 73: 329-343.

Hernández D and Bird S (2010) Energy Burden and the Need for Integrated Low-Income Housing and Energy Policy. Poverty & Public Policy 2: 5-25.

Hills J (2012) Getting the Measure of Fuel Poverty: Final Report of the Fuel Poverty Review. Reportno. Report Number|, Date. Place Published|: Institution|.

Howden-Chapman P, Matheson A, Crane J, et al. (2007) Effect of Insulating Existing Houses on Health Inequality: Cluster Randomised Study in the Community. BMJ: British Medical Journal 334(7591): 460-464.

Howden-Chapman P, Viggers H, Chapman R, et al. (2012) Tackling cold housing and fuel poverty in New Zealand: A review of policies, research, and health impacts. Energy Policy 49: 134-142.

Jessel S, Sawyer S and Hernández D (2019) Energy, Poverty, and Health in Climate Change: A Comprehensive Review of an Emerging Literature. Frontiers in Public Health 7:357. doi: 10.3389/fpubh.2019.00357.

Johnson C (2020) Is demand side response a woman’s work? Domestic labour and electricity shifting in low income homes in the United Kingdom. Energy Research & Social Science 68; 101558.

Kwon HJ and Jang M (2017) Housing quality, health and fuel poverty among U.S. seniors. Indoor and Built Environment 26(7): 951-963.

Liddell C and Guiney C (2015) Living in a cold and damp home: frameworks for understanding impacts on mental well-being. Public Health 129(3): 191-199.

Liddell C and Morris C (2010) Fuel poverty and human health: A review of recent evidence. Energy Policy 38(6): 2987-2997.

Marmot Review Team (2011) The Health Impacts of Cold Homes and Fuel Poverty. London: Friends of the Earth and the Marmot Review Team. Available at: Reportno. Report Number|, Date. Place Published|: Institution|.

Mashhoodi B, Stead D and van Timmeren A (2019) Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension. Annals of Gis 25(1): 19-31.

McDonald E, Langer J, Nordenstrom J, et al. (2017) Constructing our future with low-carbon buildings. Policy Options.

Meyer, S., Laurence, H., Bart, D., Middlemiss, L., & Maréchal, K. (2018). Capturing the multifaceted nature of energy poverty: Lessons from Belgium. Energy research & social science40, 273-283.

Middlemiss L (2022) Who is vulnerable to energy poverty in the Global North, and what is their experience? . WIREs Energy and environment.

Mould R and Baker KJ (2017) Uncovering hidden geographies and socio-economic influences on fuel poverty using household fuel spend data: A meso-scale study in Scotland. Indoor Built Environ 26: 914-936.

Mulder P, Dalla Longa F and Straver K (2023) Energy poverty in the Netherlands at the national and local level: A multi-dimensional spatial analysis. Energy Research & Social Science 96.

O’Sullivan KC, Howden-Chapman P, Sim D, et al. (2017) Cool? Young people investigate living in cold housing and fuel poverty. A mixed methods action research study. SSM – Population Health 3: 66-74.

O’Sullivan KC (2019) Health Impacts of Energy Poverty and Cold Indoor Temperature. In: Nriagu J (ed) Encyclopedia of Environmental Health. 2 ed.: Elsevier, pp.436–443.

Papada L and Kaliampakos D (2016) Measuring energy poverty in Greece. Energy Policy 94: 157-165.

Papada L and Kaliampakos D (2020) Being forced to skimp on energy needs: A new look at energy poverty in Greece. Energy Research & Social Science 64; 101450.

Petrova S and Simcock N (2019) Gender and energy: domestic inequities reconsidered. Social & Cultural Geography. DOI: 10.1080/14649365.2019.1645200. 1-19.

Poortinga W, Jones N, Lannon S, et al. (2017) Social and health outcomes following upgrades to a national housing standard: a multilevel analysis of a five-wave repeated cross-sectional survey. BMC Public Health 17(1): 927.

Ribeiro D, Mackres E, Baatz B, et al. (2015) Enhancing Community Resilience through Energy Efficiency. Reportno. Report Number|, Date. Place Published|: Institution|.

Riva M, Kingunza Makasi S, Dufresne P, et al. (2021) Energy poverty in Canada: Prevalence, social and spatial distribution, and implications for research and policy. Energy Research and Social Sciences 81: 102237.

Robinson C (2019) Energy poverty and gender in England: A spatial perspective. Geoforum 104: 222-233.

Robinson C, Bouzarovski S and Lindley S (2018) ‘Getting the measure of fuel poverty’: The geography of fuel poverty indicators in England. Energy Research & Social Science 36: 79-93.

Rodgers SE, Bailey R, Johnson R, et al. (2018) Emergency hospital admissions associated with a non-randomised housing intervention meeting national housing quality standards: a longitudinal data linkage study. Journal of Epidemiology and Community Health 72: 896–903.

Ruse J-L, Stockton H and Smith P (2019) Chapter 7 – Social and health-related indicators of energy poverty: an England case study. In: Fabbri K (ed) Urban Fuel Poverty. Academic Press, pp.143-184.

Sharpe RA, Machray KE, Fleming LE, et al. (2019) Household energy efficiency and health: Area-level analysis of hospital admissions in England. Environment International 133: 105164.

Simcock N and Mullen C (2016) Energy demand for everyday mobility and domestic life: Exploring the justice implications. Energy Research & Social Science 18: 1-6.

Statistics Canada (2017) Survey of Household Spending. Available at:

Sunikka-Blank M (2020) Why are women always cold? Gendered realities of energy injustice. In: Galvin R (ed) Inequality and Energy. Academic Press, pp.173-188.

Teariki MA, Tiatia R, O’Sullivan K, et al. (2020) Beyond home: Exploring energy poverty among youth in four diverse Pacific island states. . Energy Research & Social Science 70; 101638.

Thomson H, Bouzarovski S and Snell C (2017) Rethinking the measurement of energy poverty in Europe: A critical analysis of indicators and data. Indoor and Built Environment 26(7): 879-901.

Thomson H, Thomas S, Sellstrom E, et al. (2009) The Health Impacts of Housing Improvement: A Systematic Review of Intervention Studies From 1887 to 2007. American Journal of Public Health 99(S3): S681-S692.

Thomson H, Thomas S, Sellstrom E, et al. (2013) Housing improvements for health and associated socioeconomic outcomes (Review). The Cochrane Collaboration,.

Willand N, Maller C and Ridley I (2020) Understanding the contextual influences of the health outcomes of residential energy efficiency interventions: realist review. Housing Studies 35: 1-28.

Willand N, Ridley I and Maller C (2015) Towards explaining the health impacts of residential energy efficiency interventions – A realist review. Part 1: Pathways. Social Science & Medicine 133: 191-201.

World Energy Council (2020) World Energy Trilemma Index. Available at: Reportno. Report Number|, Date. Place Published|: Institution|.

World Health Organization (2018) WHO Housing and Health Guidelines. Reportno. Report Number|, Date. Place Published|: Institution|.