Abstract
Purpose
The purpose of the social Life Cycle Assessment (LCA) method is to predict the social impacts on people caused by the changes in the functioning of one product chain throughout its life cycle. Changes in health status are very important experiences for people. The aim of this paper is to build a pathway between changes in economic activity generated by the functioning of a product chain and the changes in health status of the population in the country where the economic activity takes place.
Methods
Empirical and historical factors suggest that increased economic activity through growth in income leads to improvements in the health of a country’s population. This empirical relationship is well known in economics as the Preston curve. Using this relationship, we design a pathway for social LCA impact assessment. This pathway may be used to explain or predict the potential impact caused by the modification of one product sector upon the health of a population. The Preston relationship usually is calculated for a cross section of countries. We assess whether the Preston relationship is valid when a single country is considered alone. Drawing from scientific literature regarding development, we define the context where the use of the Preston relationship is justified. We describe the general design of the Preston pathway, using a recalculated (panel based) relationship, and specify the conditions for its use. We apply it to the case of company B, a banana industry in Cameroon, for the period between 2010 and 2030.
Results
We highlight that the panel calculation of the Preston relationship remains significant when a country is considered alone. We suggest that the following conditions are required for the pathway to be used: (1) the activity is set within countries where the GDP per capita in purchasing power parity is less than $10,000 at the start of the period, (2) the assessed activity accounts for a significant part of the annual GDP and/or demonstrates obvious signs that it represents a huge stake in the country’s economy, (3) the duration of the assessed activity is regular and long enough, and (4) the added value created by the activity is shared within the country. We found that the future activity of company B would improve the potential LEX of the entire population of Cameroon by 5 days over 20 years, based on 200,000 t of bananas exported annually (in comparison with no activity).
Conclusions
When the four conditions for use are met, and provided results are interpreted by comparing them with other situations or countries, the recalculated panel-based relationship may be used to explain or predict a change in potential life expectancy generated by a change in economic activity. The Preston pathway may be useful for impact assessment in social LCA. The assessment is valid only when used for a comparative analysis and must be done within a multi-criteria framework. Complementary pathways therefore need to be designed. We suggest that the conditions for use and other research issues be discussed and fine-tuned further. Moreover, we welcome comments and criticisms.
Similar content being viewed by others
Notes
Later in the paper this abbreviation will be used to refer to GDP per capita. We never use the global GDP.
Longevity, non-fatal impacts on human health, autonomy, safety security and tranquillity, equal opportunity, participation and influence.
Entity B may be one company, or several small craft workshops, or farms, etc.
Local value added includes the direct (of the company) and indirect (generated by the inputs and suppliers) primary value added and the secondary value added (related to the allocation of income). This value added is different than accounting value added because it includes only cash flows that remain in the country and not those that are exported (unless they generate effects at local level).
There are 44 branches in the input–output matrix provided by the National Institute of Statistics of Cameroon. Each of these branches comprises hundreds or thousands of companies.
It was shown that in the most affected countries, HIV was responsible for a decline in LEX of 10 years (UNPD 2003).
We choose the period 1995–2009 because it is only since this period that the country has experienced economic development without the occurrence of major disruptive events that could bias the analysis.
Given the demographic transition, the population growth rate is positive but diminishes gradually (Pinson 2009). Thus, we calculated a decrease in the population growth rate of 0.04 % per year over the period 1989–2009. We apply it to future population growth.
We compared these results with the future gross domestic product per capita calculated from the Gapminder data, estimated for each year using the average annual growth rate over the period 1995–2009 (1.48 %). Both provide comparable results, but we preferred using data resulting from the two calculations steps (1 and 2), due to the lack of transparency of the calculations made by Gapminder.
Impact transfer is the phenomenon such as when comparing two variant scenarios, the impact X is improved, but to the detriment of the impact Y.
Triangulation is a scientific method, well known in social sciences, to get insight about the same issue from different sources and by different ways.
References
Alderman H, Behrman JR, Lavy V, Menon R (2001) Child health and school enrollment: a longitudinal analysis. J Human Res 36(1):185–205
Ashley C (2006) Participation by the poor in Luang Prabang tourism economy: current earnings and opportunities for expansion. Working Paper 273. Overseas Development Institute, London
Bloom DE, Canning D (2000) The health and wealth of nations. Science 287(5456):1207–1209
Bloom DE, Canning D (2007) Commentary: the Preston curve 30 years on: still sparking fires. Int J Epidemiol 36(3):498–499
Canning D (2010) Progress in health around the world. Human Development Research Papers, 2010/43. United Nations Development Programme (UNDP), New York
Case A (2001) Does money protect health status? Evidence from South African Pensions. Working Papers. Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing, Cambridge
Case A (2002) Health, income and economic development. Proceedings of World Bank conference on development economics, May 1–2, 2001, World Bank, pp. 221–241
Cotis J-P (2009) Partage de la valeur ajoutée, partage des profits et écarts de rémunérations en France. INSEE, Paris
Deaton A (2002) Policy implications of the gradient of health and wealth. Health Aff 21(2):13–30
Deaton A (2003) Health, inequality, and economic development. J Econ Lit 41(1):113–158
Deaton A (2007) Global patterns of income and health: facts, interpretations, and policies. WIDER Annual Lecture 10. United Nations University/World Institute for Development Economics Research, Helsinki
Deaton A, Paxson C (2004) Mortality, income and income inequality over time in Britain and the United States. In: Wise D (ed) Perspectives on the economics of aging. University of Chicago Press, Chicago, pp 247–280
Dickson R, Awasthi S, Williamson P, Demellweek C, Garner P (2000) Effects of treatment for intestinal helminth infection on growth and cognitive performance in children: systematic review of randomised trials. BMJ 320(7251):1697–1701
Easterly W (1999) Life during growth. J Econ Growth 4(3):239–276
Eden C, Spender J (1998) Managerial and organizational cognition. Theory, methods and research. Sage, London
Filmer D, Pritchett L (1999) The impact of public spending on health: does money matter? Soc Sci Med 49(10):1309–1323
Fogel R (2004) The escape from hunger and premature death 1700–2100. Cambridge University Press, Cambridge
Garrabé M (2010) Valeur d’activité totale (V.A.T) d’une opération de développement. CIHEAM-IAMM, Montpellier
Gjølberg M (2009) Measuring the immeasurable? Constructing an index of CSR practices and CSR performance in 20 countries. Scand J Manag 25(1):10–22
Hanmer L, Lensink R, White H (2003) Infant and child mortality in developing countries: analysing the data for robust determinants. J Dev Stud 40(1):101–118
Hutchins MJ, Sutherland JW (2008) An exploration of measures of social sustainability and their application to supply chain decisions. J Clean Prod 16(15):1688–1698
Jolliet O, Müller-Wenk R, Bare J, Brent A, Goedkoop M, Heijungs R, Itsubo N, Peña C, Pennington D, Potting J, Rebitzer G, Stewart M, de Haes H, Weidema B (2004) The LCIA midpoint-damage framework of the UNEP/SETAC life cycle initiative. Int J Life Cycle Assess 9(6):394–404
Jørgensen A, Finkbeiner M, Jørgensen M, Hauschild M (2010a) Defining the baseline in social life cycle assessment. Int J Life Cycle Assess 15(4):376–384
Jørgensen A, Lai L, Hauschild M (2010b) Assessing the validity of impact pathways for child labour and well-being in social life cycle assessment. Int J Life Cycle Assess 15(1):5–16
Jørgensen A, Dreyer L, Wangel A (2012) Addressing the effect of social life cycle assessments. Int J Life Cycle Assess 17(6):828–839
Kenny C (2009) There’s more to life than money: exploring the levels/growth paradox in income and health. J Int Dev 21(1):24–41
Klugman J (2010) Rapport sur le Développement Humain 2010 - La vraie richesse des nations: les chemins du développement humain. Programme des Nations Unies pour le Développement, New York
Lenzen M (2006) Uncertainty in impact and externality assessments—implications for decision-making. Int J Life Cycle Assess 11(3):189–199
Loeillet D, de Wulf C, de Lapeyre L (2009) La banane: dossier du mois. Fruitrop 166:7–39
Mitchell J, Faal J (2007) Holiday package tourism and the poor in the Gambia. Dev South Afr 24(3):445–464
Mitchell J, Phuc LC (2007) Participatory tourism value chain analysis in Da Nang, Central Vietnam. Final Report on Participatory Tourism Value Chain Analysis in Da Nang, Central Vietnam. Overseas Development Institute, London
Moatti J, Auquier P, Le Coroller A, Macquart-Moulin G (1995) QALYs or not QALYs: that is the question? Rev Epidemiol Sante Publique 43(6):573–583
Norris G (2006) Social impacts in product life cycles—towards life cycle attribute assessment. Int J Life Cycle Assess 11:97–104
Owens JW (1997) Life-cycle assessment in relation to risk assessment: an evolving perspective. Risk Anal 17(3):359–365
Parent J, Cucuzzella C, Revéret J-P (2010) Impact assessment in SLCA: sorting the sLCIA methods according to their outcomes. Int J Life Cycle Assess 15(2):164–171
Pinson G (2009) Atlas de la population mondiale. Alimentation, vieillissement, mobilité… quels bouleversements? Autrement, Paris
Preston SH (1975) The changing relation between mortality and level of economic development. Popul Stud 29:231–248
Preston SH (2007) The changing relation between mortality and level of economic development. Int J Epidemiol 36(3):484–490
Pritchett L, Summers L (1996) Wealthier is healthier. J Human Res 31(4):841–868
Pritchett L, Viarengo M (2010) Explaining the cross-national time series variation in life expectancy: income, women’s education, shifts and what else? Human Development Research Paper, 2010/31. United Nations Development Programme, New York
Schmidt JH, Weidema B (2009) Response to the public consultation on a set of guidance documents of the International Reference Life Cycle Data System (ILCD) Handbook. 2.-0 LCA Consultants, Aalborg
Sevestre P (2002) Econométrie des données de panel. Dunod, Paris
Udo de Haes HA, Lindeijer E (2002) The conceptual structure of life cycle impact assessment. In: Udo de Haes H et al. (eds) Life cycle impact assessment: striving towards best practice. Society of Environmental Toxicology and Chemistry (SETAC), Pensacola, pp 103–119
UNAIDS (2010) UNAIDS report on the global AIDS epidemic. Joint United Nations Programme on HIV/AIDS, Geneva
UNDP (1990) Human Development Report 1990. United Nations Development Programme, New York
UNEP/SETAC (2009) Guidelines for social life cycle assessment of products. United Nation Environment Program/Society of Environment Toxicology and Chemistry, Paris
United Nations (2000) Millennium development goals. United Nations, New York
UNPD (2003) World population prospects—the 2002 revision. United Nations Population Division, New York
Weidema B (2006) The integration of economic and social aspects in life cycle impact assessment. Int J Life Cycle Assess 11:89–96
Wilkinson RG, Pickett K (2010) The spirit level: why equality is better for everyone? Allen Lane, London
World Bank (2001) World Development Report—attacking poverty. The International Bank for Reconstruction and Development/The World Bank, Washington, DC
Acknowledgments
This work was performed as part of the Industrial Ph.D. “Development of a social LCA of pathway methodology. The case of banana supply chains” carried out at Compagnie Fruitière and at CIRAD-Department of PERSYT, in Banana, plantain and pineapple cropping systems Research Unit (Market News Service). Financial support for the study from Compagnie Fruitière and the French Ministry of Higher Education and Research is gratefully acknowledged. The authors thank the case study company for its participation. The authors are members of the ELSA group (Environmental Life Cycle and Sustainability Assessment) (www.elsa-lca.org); they thank all the other members of ELSA for their advice.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible Editor: Andreas Jørgensen
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
ESM 1
(PDF 297 kb)
Rights and permissions
About this article
Cite this article
Feschet, P., Macombe, C., Garrabé, M. et al. Social impact assessment in LCA using the Preston pathway. Int J Life Cycle Assess 18, 490–503 (2013). https://doi.org/10.1007/s11367-012-0490-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11367-012-0490-z