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Living in groups, dying alone: A population health perspective on resilience

Supported by CIS-HDGEC, Carnegie Mellon University, Pittsburgh. NSF Center of Excellence, SBR-9521914. Living in groups, dying alone: A population health perspective on resilience. James Tansey SDRI, UBC. Overview. Introduction and justification Central messages in population health

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Living in groups, dying alone: A population health perspective on resilience

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  1. Supported by CIS-HDGEC, Carnegie Mellon University, Pittsburgh. NSF Center of Excellence, SBR-9521914 Living in groups, dying alone: A population health perspective on resilience James Tansey SDRI, UBC

  2. Overview • Introduction and justification • Central messages in population health • Social networks and health • Study design • Initial results • Conclusions

  3. Climate change and health:External factors • Mosquito born diseases • Increased heat waves • Extreme events • Urban air quality • Range and seasonality of infectious diseases • Biotoxins from marine environmental change • Changes in food supply affecting nutrition • Economic decline affecting health indirectly (Watson et al, 2001: 259)

  4. Adaptation options Source: Watson et al, 2001: 261.

  5. Social dimensions of health? ‘There is little published evidence that changes in population health status actually have occurred in response to observed trends in climate over recent decades. A recurring difficulty in identifying such impacts is that the causation of most human health disorders is multifactorial, and the “background” socioeconomic, demographic, and environmental context changes significantly over time’ (Watson et al, 2001: 259)

  6. Environmental and social risk Risks and hazards as external ‘natural’ events with human health impacts Exposure and vulnerability to risk determined by social and institutional conditions Social risk and resilience: population health perspective on human health and well being

  7. Inequality and mortality Ross et al, 2000 in Evans

  8. Class and health Similar trend seen in Whitehall study Longitudinal study showed raised mortality and morbidity by job grade Included controls for smoking etc. Source: Marmot et al, 1998

  9. Social networks and mortality Social network measures: Marriage, contact with friends and family, church membership and formal/ informal memberships 9 year prospective study Berkman and Syme in House et al 1988.

  10. Central message of population health literature • Social factors are at least as important as external factors in determining health and well-being • Not simply health transition effects • Inequality, mastery, demand, control, sense of agency all significant • Impacts on hypertension, stress reactivity, immune system integrity, mental health.

  11. Relevance to climate change • Increase resilience to uncertain climate change and variability impacts by addressing known social factors:- reduce stress and resulting strain especially in childhood- inequality may be a proxy for social isolation and vulnerability, esp. in US- social networks as insurance in crises

  12. Macro Income/inequality, social exclusion and capital, status Meso Parental stress, mental health, nutrition Working conditions, control, employment security, socially mediated health behaviours Social support and survival rates Micro Social support and biological embedding Kin based social support, psychological state Individual Lifecourse Childhood Adulthood Old-age Lifecourse health model

  13. Invention of ‘social capital’ • Capital as kind of power: money makes things happen • Human capital: value in people • Social capital: value in social groups • Coleman’s three key arguments • Social relations as insurance • Social relations as common language • Social relations create predictability • Is Social Capital like other forms of capital?

  14. Definitions • ‘the aggregate of actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance or recognition’ (Bourdieu 1985: 248) • ‘features of social life – networks, norms and trust – that enable participants to act together more effectively to pursue shared objectives’ (Putnam, 1995: 664–65).

  15. Social networks and health • Problems with social capital: too much baggage, confuses means with ends, narrow measures, only sees benefits. • Emphasis on social networks instead • Ecological studies in US show strong links with health: 1% rise in inequality = 21.7% rise in SMR • Individual level studies show no effect in Canada • Multi-level and multi-strategic approaches essential

  16. Social networks and resource dependent forest communities • Highly dependent on health of natural systems • Exposed to acute crises and structural change over two decades • Methods: nation survey with oversample (6500/1500), detailed contextual data (health, census, economic, educational), intensive analysis of clusters • Follow-up survey underway

  17. Overview of data

  18. Key variables at sawmill scale • Dependent: Self-rated health • Individual independent: Contact with family, neighbours, economic security, income, education, membership of service, recreational, religious, helping, youth clubs, trust, ethnicity • Aggregate independent: census variables

  19. Clubs and societies

  20. Charity and church Attend church, religious services

  21. Education levels

  22. Commu-nity Nanaimo Powell River Port Alberni Squam-ish Tahsis Youbou Chemai-nus Aggregate deviation 4.56 3.87 5.62 4.96 13.45 2.61 3.59 Disruption index

  23. Contact with family

  24. Recreational clubs

  25. Economic security in 12 months

  26. Tahsis Labour force composition

  27. Tahsis Government transfers

  28. Tahsis Male income

  29. Tahsis Home owners

  30. Conclusions • When the going gets tough, the poor get going • Need to understand whether and how resource communities different • Significant differences between communities • National level analysis showed weak but significant relationship between social capital and health • Need to drill down through qualitative analysis

  31. Conclusions • Social networks strongly related to traditional demographic variables • Educational factors very significant • Multi-level model of health underway • Second survey underway • Multistrategic methods required

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