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Living in groups, dying alone: A population health perspective on resilience James Tansey SDRI, UBC Supported by CIS-HDGEC, Carnegie Mellon University, Pittsburgh. NSF Center of Excellence, SBR-9521914
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Overview Introduction and justification Central messages in population health Social networks and health Study design Initial results Conclusions
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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)
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Adaptation options Health outcome LegislativeTechnicalEdu- cational Cultural and Behavioural ThermalBuilding guidelines Housing, public buildings, urban planning to reduce heat island effects, air conditioning Early warning systems Clothing, siesta Vector-borne diseases Vector control, Vaccination, impregnated bednets. Sustainable surveillance, prevention and control programs Health education Water Storage practices Water borne diseases Watershed protection laws Water quality regulation Genetic/molecular screening of pathogens. Improved water treatment (e.g., filters). Improved sanitation (e.g., latrines) Boil water alerts Washing hands and other hygiene behavior. Use of pit latrines Source: Watson et al, 2001: 261.
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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)
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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
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Inequality and mortality Ross et al, 2000 in Evans
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Class and health Source: Marmot et al, 1998 Similar trend seen in Whitehall study Longitudinal study showed raised mortality and morbidity by job grade Included controls for smoking etc.
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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.
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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.
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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
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Lifecourse health model Social support and survival rates Working conditions, control, employment security, socially mediated health behaviours Parental stress, mental health, nutrition Social support and biological embedding Individual Lifecourse Kin based social support, psychological state Income/inequality, social exclusion and capital, status Micro Meso Macro ChildhoodAdulthoodOld-age
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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?
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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).
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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
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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
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Overview of data
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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
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Clubs and societies
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Charity and church Attend church, religious services
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Education levels Highest Education level Vancouver (big metro) All SawmillsNanaimo (large mixed rural) Port Alberni (medium rural) Tahsis (small Pre- university 60.1277.6469.3187.3791.00 University/ prof. 39.8822.3630.6912.639
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Disruption index Commu- nity Nanaim o Powell River Port Alberni Squam- ishTahsisYoubou Chemai -nus Aggregate deviation4.563.875.624.9613.452.613.59
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Contact with family
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Recreational clubs
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Economic security in 12 months
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Labour force composition Tahsis
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Government transfers Tahsis
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Male income Tahsis
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Home owners Tahsis
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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
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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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