Against the current backdrop of a rapidly ageing population, public policy must anticipate the increase in the number of people losing their independence and their proportion of the population. This increase – which varies in magnitude depending on epidemiological scenarios but appears inevitable barring a therapeutic breakthrough – raises some major questions: what proportion of our shared resources do we wish to allocate to supporting older people who are losing their independence? How can we assess the merits of the various public policy options? In France, the decision has been taken to prioritise enabling older people to remain in their own homes – a choice that has been termed the ‘shift towards home care’, by analogy with the ‘shift towards outpatient care’ in the healthcare sector. The IPP has already devoted several studies to the implications of this approach, notably a paper on its cost to public finances by 2040 (Carrère et al., 2023; Mendras, 2023). This paper incorporates an aspect of this trade-off that has been overlooked until now: the environmental dimension. It forms part of the IPP’s broader objective of systematically integrating environmental considerations into the evaluation of public policies.
CO₂ emissions associated with caring for elderly people who have lost their independence
Presentation
Key Results
- At home, CO₂ emissions are 25 per cent higher for GIR 1–2 (11.7 tCO₂eq/year) than in care homes (9.1 tCO₂eq/year).
- Economies of scale in care homes reduce emissions: shared care, transport and medical equipment.
- Individual accommodation and carers’ travel account for most of the difference between home and care home settings.
- For GIR 3–4, the differences between home and care homes are small, as the need for support and care is less significant.
- Projecting the impact of the ‘shift towards home care’ remains complex: the profiles of people with reduced independence differ significantly between home and care homes, and the causal effect of admission to a care home is poorly understood.
- Reducing emissions in the home involves tackling emissions generated by transport,
and by the energy-efficient refurbishment of older people’s homes.
Method and Data
Data
Certain expenditure items (care, meal delivery, travel costs for informal and professional carers, fixed assets and energy in residential care homes) relate to issues specific to the field of independent living and have been the subject of dedicated data collection (RI-APA, the CARE-SNDS and EHPA 2019 surveys), enabling the authors to break these down precisely by degree of loss of independence, as measured by the ‘estimated GIR’. For other expenditure items, the authors draw on various databases created by organisations not specifically focused on older people with reduced autonomy. These include, amongst others, the ANSES’s INCA3 database, the Argos database provided by the UNA (National Union for Home Help, Care and Services), the 2019 Mobility of People survey (SDES), the 2017 Household Budget Survey (INSEE), the 2013 Housing Survey (INSEE), etc. Furthermore, whilst this data provides insights into behaviour, it must be supplemented by information on GHG emissions in CO₂ equivalents for a given behaviour. Here too, the authors draw on various sources depending on the sector, including ADEME’s Footprint database, FEDESAP, Citepa, etc. Finally, the authors obtain a breakdown by estimated GIR for healthcare and independent living, and by age for the other categories (except for waste, for which the authors have no breakdown). The relationship between age and GIR is then approximated based on the proportions of GIR by age derived from DREES surveys. For energy consumption and capital expenditure (housing), it is reasonable to assume that consumption does not vary significantly according to the degree of loss of independence, given a particular living situation. However, for food and other categories, the lack of information by GIR is more problematic. This is why Figure 2 shows, in colour, the four emission categories for which a breakdown by GIR is either possible (care, independence) or not essential (energy, fixed assets), and in grey the categories for which estimation by GIR is not possible or not satisfactory (food, purchases, transport of older people, waste).
Methods
The authors calculate a specific emission factor for each sub-emission category, separately for each living environment, taking care to avoid double counting. In some cases, this involves using different databases depending on the living environment (energy, fixed assets), or even using different calculation methods (food, others). In extreme cases, where specific data are unavailable and it is not possible to extrapolate estimates from the general population to older people with reduced autonomy, the authors must make assumptions about behaviour (items shown in grey in Figure 2). The authors therefore make the simplifying assumption that personal travel by older people in GIR 1–2 living at home is zero, as is that of those living in care homes. The authors also assume that purchases of certain categories of goods (furniture, bedding, tools, etc.) are zero in care homes, whilst for those living at home, they treat these purchases as equivalent to those of the general population aged 60 and over. In care homes, for the categories of food, energy and fixed assets, the authors adopt the methodology of the report by The Shift Project, 2024, making specific adjustments to ensure comparability with the home setting. For example, in the home, for energy and fixed assets, the data allow emission factors to be calculated according to people’s age, taking into account the type of accommodation, the heating system, air conditioning, floor space occupied, etc. With regard to emissions factors for healthcare, all categories, except for incontinence, are calculated on the basis of per-person expenditure according to the GIR in the CARE survey linked to the SNDS, and supplemented by average emissions factors (Ademe for medical devices, Ecovamed for
medicines and the Shift Project for hospitalisations). Finally, for travel related to independent living, the authors draw on data from IPP Report No. 45 on the number and type of full-time equivalents (FTEs) providing care to an older person, based on their age and place of residence, and combine this with data on the kilometres travelled per type of FTE (sources: UNA and DADS 2019), as well as an emissions factor per kilometre based on the mode of transport used, taken from ADEME’s ‘Empreinte’ database.
Partners
This study forms part of the PERSEPHONE research project, funded by the Drees Research Mission (MiRe) as part of a call for proposals entitled ‘Rethinking social protection in the light of environmental crises’. The authors would like to thank the Shift Project and the UNA (National Union for Home Help, Care and Services) for their expertise and for sharing the data that contributed to this study.