Lifecourse biological pathways underlying social differences in healthy ageing

Project Information

LIFEPATH

Grant agreement ID: 633666

DOI

10.3030/633666

Project closed

EC signature date 13 April 2015

Start date 1 May 2015

End date 30 April 2019

Funded under

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Total cost

€ 7 259 113,16

EU contribution

€ 5 999 756,00

Coordinated by

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
United Kingdom

Periodic Reporting for period 3 - LIFEPATH (Lifecourse biological pathways underlying social differences in healthy ageing)

Reporting period: 2018-05-01 to 2019-04-30

Summary of the context and overall objectives of the project

In the final period of the project we have proceeded in disentangling the different components of the impact of low socio-economic position (SEP) on health, by analysing multiple population cohorts and multiple biomarkers including omics. The questions we aimed to answer in this period were related to a reconstruction of the whole causal chain from low SEP to health outcomes, including the role of parental education, children ACEs, behavioural risk factors and biomarkers. We modeled Health Impact Assessment models.

We also addressed potential policy implications, developing some guidelines targeted to different age groups. Our studies showed that early interventions have a critical importance, as their consequences may span the whole life-course. This has important implications for policy making, since appropriate policies can reverse the embodiment of socioeconomic disadvantage, thus reducing health inequalities and resulting in healthier ageing.
For policy purposes, LIFEPATH suggests (a) that the effects of preventive interventions in early life are complementary to interventions in adulthood, (b) that intervening on poor socioeconomic conditions is complementary and quantitatively comparable to well-known risk factors like tobacco and alcohol consumption, obesity or a sedentary lifestyle, and (c) that more needs to be done to attenuate psycho-social factors in addition to material factors.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Compared to the second period we have extended the same measures of age acceleration from epigenetics to metabolomics data based on 35,000 subjects from the UCLEB consortium. In addition, we have produced further evidence on the role of biomarkers in health inequalities, by publishing a series of papers on the allostatic load and inflammation.

We studied ACEs and obesity in childhood. Low SEP in early life may shape lifestyle and health-related behaviours, which then affect health in adulthood. In fact, low SEP may be associated with poor early life nutrition; tobacco exposure in utero, infancy and childhood; foetal growth restriction or premature birth. A child’s development is clearly sensitive to the surrounding environment in early childhood and to the availability of sufficient economic resources. Psychosocial stress is also a key factor, since is thought to affect brain development in childhood by affecting glucocorticoid and catecholamine levels which impact executive function, emotional and behavioural control and analytical thinking. Low socioeconomic advantage in childhood may result in educational disadvantage, which in turn drives economic disadvantage in adulthood (Layte, 2017).

LIFEPATH Publications List as of April 2019

1. Berger, E., R. Castagné, M. Chadeau-Hyam, M. Bochud, A. d'Errico, M. Gandini, M. Karimi, M. Kivimäki, V. Krogh, M. Marmot, S. Panico, M. Preisig, F. Ricceri, C. Sacerdote, A. Steptoe, S. Stringhini, R. Tumino, P. Vineis, C. Delpierre, and M. Kelly-Irving. 2019. "Multi-cohort study identifies social determinants of systemic inflammation over the life course." Nat Commun 10 (1):773. doi: 10.1038/s41467-019-08732-x.
2. Castagné, R., V. Garès, M. Karimi, M. Chadeau-Hyam, P. Vineis, C. Delpierre, M. Kelly-Irving, and Lifepath Consortium. 2018. "Allostatic load and subsequent all-cause mortality: which biological markers drive the relationship? Findings from a UK birth cohort." Eur J Epidemiol 33 (5):441-458. doi: 10.1007/s10654-018-0364-1.
3. Courtin, E., P. Muennig, N. Verma, J. A. Riccio, M. Lagarde, P. Vineis, I. Kawachi, and M. Avendano. 2018. "Conditional Cash Transfers And Health Of Low-Income Families In The US: Evaluating The Family Rewards Experiment." Health Aff (Millwood) 37 (3):438-446. doi: 10.1377/hlthaff.2017.1271.
4. Kivimäki, M., J. Vahtera, A. G. Tabák, J. I. Halonen, P. Vineis, J. Pentti, K. Pahkala, S. Rovio, J. Viikari, M. Kähönen, M. Juonala, J. E. Ferrie, S. Stringhini, and O. T. Raitakari. 2018. "Neighbourhood socioeconomic disadvantage, risk factors, and diabetes from childhood to middle age in the Young Finns Study: a cohort study." Lancet Public Health 3 (8):e365-e373. doi: 10.1016/S2468-2667(18)30111-7.
5. Mackenbach, J. P., Y. Hu, B. Artnik, M. Bopp, G. Costa, R. Kalediene, P. Martikainen, G. Menvielle, B. H. Strand, B. Wojtyniak, and W. J. Nusselder. 2017. "Trends In Inequalities In Mortality Amenable To Health Care In 17 European Countries." Health Aff (Millwood) 36 (6):1110-1118. doi: 10.1377/hlthaff.2016.1674.
6. Mackenbach, J. P., J. R. Valverde, B. Artnik, M. Bopp, H. Brønnum-Hansen, P. Deboosere, R. Kalediene, K. Kovács, M. Leinsalu, P. Martikainen, G. Menvielle, E. Regidor, J. Rychtaříková, M. Rodriguez-Sanz, P. Vineis, C. White, B. Wojtyniak, Y. Hu, and W. J. Nusselder. 2018. "Trends in health inequalities in 27 European countries." Proc Natl Acad Sci U S A 115 (25):6440-6445. doi: 10.1073/pnas.1800028115.
7. Stringhini, S., C. Carmeli, M. Jokela, M. Avendaño, C. McCrory, A. d'Errico, M. Bochud, H. Barros, G. Costa, M. Chadeau-Hyam, C. Delpierre, M. Gandini, S. Fraga, M. Goldberg, G. G. Giles, C. Lassale, R. A. Kenny, M. Kelly-Irving, F. Paccaud, R. Layte, P. Muennig, M. G. Marmot, A. I. Ribeiro, G. Severi, A. Steptoe, M. J. Shipley, M. Zins, J. P. Mackenbach, P. Vineis, M. Kivimäki, and LIFEPATH Consortium. 2018. "Socioeconomic status, non-communicable disease risk factors, and walking speed in older adults: multi-cohort population based study." BMJ 360:k1046. doi: 10.1136/bmj.k1046.
8. Stringhini, S., C. Carmeli, M. Jokela, M. Avendaño, P. Muennig, F. Guida, F. Ricceri, A. d'Errico, H. Barros, M. Bochud, M. Chadeau-Hyam, F. Clavel-Chapelon, G. Costa, C. Delpierre, S. Fraga, M. Goldberg, G. G. Giles, V. Krogh, M. Kelly-Irving, R. Layte, A. M. Lasserre, M. G. Marmot, M. Preisig, M. J. Shipley, P. Vollenweider, M. Zins, I. Kawachi, A. Steptoe, J. P. Mackenbach, P. Vineis, M. Kivimäki, and LIFEPATH consortium. 2017. "Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women." Lancet 389 (10075):1229-1237. doi: 10.1016/S0140-6736(16)32380-7.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Lifestyle-related behaviours such as diet, physical inactivity, tobacco smoking and alcohol consumption are important drivers of social inequalities in healthy ageing. They track from early life and their impact accumulates through the life-course. They do not explain the entire social gradient in health, however, but policy makers often see them as easier targets for specific actions. This is not necessarily the case. In addition to behavioural factors, environmental and occupational exposures, the LIFEPATH epidemiological and mechanistic approach highlighted that psychosocial stress is likely to be an additional important factor, and that trajectories towards poor health can be modified by acting both on intermediate risky behaviours and on social deprivation itself, from the very beginning of life-course. The two types of trajectories seem to be complementary. For policy purposes the points above suggest (a) that the effects of prevention interventions in early life are complementary and quantitatively comparable to interventions in adulthood, (b) that intervening on poor socio-economic conditions is complementary and quantitatively comparable to modifying risk factors, and (c) that more needs to be done to attenuate psychosocial factors in addition to material factors.