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The impact of the economy on health in France & Brittany

The impact of the economy on health in France & Brittany. Martine M. BELLANGER & A. JOURDAIN martine.bellanger@ensp.fr. Contents. Background Some issues to be discussed Further work to be done. Background. Starting point: findings from a previous research:

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The impact of the economy on health in France & Brittany

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  1. The impact of the economy on health in France & Brittany Martine M. BELLANGER & A. JOURDAIN martine.bellanger@ensp.fr

  2. Contents • Background • Some issues to be discussed • Further work to be done

  3. Background • Starting point: findings from a previous research: • Regional health programmes (PRS) on suicide prevention in France (Bellanger, Jourdain & Batt in Social science &Medicine 65 (2007): 431-441) • An ecological approach (i.e. contexts may influence health) was adopted to analyse factors having an impact on suicide rate in the regions with PRS. • Were included, among variables, those related to “economic, social and health capital, employment and living conditions, state of health, mental health…. Were adding some variables reflecting social fragmentation together with health care provision.

  4. Some regional features • Among economic variables likely to have a relationship with regional population health: • Regional wealth: GDP per inhabitant • Economic activity: rate of unemployment (proxy) • ‘Social assistance for depraved population’: rate of minimum revenue beneficiaries • Health state: Standardized mortality rate • In addition, weight of ageing population • See table 1 below

  5. Table 1 Some data related to economic activity and health, in some of the 22 regions Regions (Letter) for region classification in the principal component analysis (Number) for the rank among the regions

  6. Some relationships between variables • In our research, the above mentioned variables were included in addition to other ones (e.g. Gini coefficient measuring income inequality gap) • A principal component analysis (PCA) on the descriptive variables showed: • Some relationships between economic variables and population health at the regional level, • But, some results were not as expected

  7. Inverse correlation between unemployment and SMR in some regions • In some regions with low unemployment rate , i.e good level of economic activity, high SMR was found (Brittany) • Some regions with high unemployment rate enjoyed low SMR, conversely (Mediterranean regions) • See figure 1 below

  8. Axis 1 Axis 1 Total fertility rate 2000 Total fertility rate 2000 Gross birth rate 2000 Gross birth rate 2000 SMR SMR Female suicide mortality Rate Female suicide mortality Rate Child mortality rate Child mortality rate Axis 2 Axis 2 GDP /. GDP /inhab. Density 2000 inhab / km² Density 2000 inhab / km² Natural growth rate-1999 en % Natural growth rate-1999 en % Gross mortality rate 2000 Gross mortality rate 2000 Male suicide mortaliy rate Male suicide mortaliy rate Ageing rate 2000 Ageing rate 2000 inter-quartiles (€) inter-quartiles (€) Unemployment Rate ILO 2001 Unemployment Rate ILO 2001 inter-deciles inter-deciles Gini Gini Figure 1 External factors of suicide Source Social Science an Medicine p. 437

  9. In addition, the higher the revenue inequalities were founded, the lower the SMR were • e.g. pretty good health in South & South east crescent). Those specific regions have the highest level of CMU& RMA beneficiaries • e.g. Paris region • Conversely, high SMR were found in more ‘egalitarian’ regions

  10. Regions with low GDP/inhabitant were found older relatively (high rate of ageing population): • E.g. Limousin, Auvergne • Conversely, regions with high level of GDP/inhabitant were also found younger (but also with large income inequalities: • E.g. Alsace and to a less extent Rhône-Alpes • Thus a clear-cut opposition was observed among the French regions, which were grouped, with some exceptions: • Paris region (A) and North-Pas de Calais (C). See above figure 2

  11. Axis 1 Bretagne(D) Haute-Normandie(D) ) Bourgogne(D) Centre 7 Limousin(B) Pays De Loire(D) Franche-Comte(D) Picardie Auvergne(D) Poitou - (D) 1 Champagne-Ardenne Axis 2 Lorraine (D) Nord-Pas-De-Calais (c) Alsace (E) Rhône-Alpes(F) Aquitaine(D) Midi-Pyrénées(D) Languedoc-Roussillon (F) Ile De France(A) Prov.-Alpes-côtes-d'azur(F) Corse(F) Figure 2 The typology of the regions from group A to F Source Social Science an Medicine p. 437

  12. Type of activity & health status • Relationship between employment area and cancer mortality level in France: • Type of economic activity and its impact on health state • E.g. Cancer mortality rates in France, in 1973-1977 and 1995-1999 (Rican et al. 2004 see map below) • See map of Gross mortality rate in France (T in U)

  13. Map 1- Cancer mortality rate according to employment area, in France

  14. Map 2-SMR (all death causes, Male and Female)

  15. Further work to be done • Further research have to be carried out, nevertheless, at this stage, some issues could be raised: • Population components need to be included in the variables • Large discrepancies between social groups (6.5 year difference in terms of LE at age 35 were found between skilled workers and executives and members of intellectual professions during 1992-1996 period. • See for instance Brittany (good level of employment does not mean good population health. The later depends on the weight of social categories, e.g. skilled workers • Brittany is the ‘first’ region in terms of suicide & accident male mortality rate in France (in some departments, high rates for persons aged 65 and over

  16. Further work to be done • Disparities in health state (e.g. morbidity/mortality) can be due to differences in income activity, but also, to educational level, information access and social environment. • The variables have to be disentangled • Thus multilevel modeling approach could be used

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