Overview of the webinar• Using averages in

population health & health equity research

• What do averages hide?

• Why go beyond and possible ways

• Key messages

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Measuring population health using averages

Typically proxy of health status, disease prevalence or health services coverage and/or utilisation

• Allow comparison across or within population across space and time

• Identify inequalities across populations

• Identify priorities for population health interventions and essential tool for health services monitoring and planning

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Balarajan Y, Selvaraj S, Subramanian S. Health care and equity in India. Lancet 2011;377:505–15. doi:10.1016/S0140-6736(10)61894-6

Understanding averages • a number expressing the

central or typical value in a set of data, in particular the mode, median, or (most commonly) the mean…

• A summary measure for a population health attribute – decontextualised by design

• Averages over time does not tell us anything about “for whom”

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What do averages hide?• Aggregations of

unrelated and non-uniform population groups

• Contexts

• Unevenly distributed advantages and disadvantages

• Social structures that operate unfairly across time, space and/or person

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What do averages hide

(Not) all (wo)men are “created” equal

•Bio-medical (cf. Barker hypothesis)

•Psycho-social (cf. poor households, biological and social effects of discrimination)

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Not all opportunities are accessible equally

•Myth of equality=equity (cf. accumulation of disadvantages)

•Environmental (cf. distribution of parks and recreation, town resources allocation)

•Socio-political (cf. access to social networks and power structures)

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What do averages hide 2

What do averages hide

Not all contexts affect processes or outcomes equally

•Differing contexts: Multiple interacting contexts ranging from individual, to household to society

•Differing interactions between contexts and processes: All household members are not similarly affected by the same biological illness/health problem

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why go beyond• the more interesting question: From how much to why or how?

• Health inequity as a wicked problem, Complexity

• Social construction (norms, values, social structures) and path dependence

• Macro processes (cf. macro-economic changes or policy) producing micro-effects

• Action/implementation/solution orientation

• Ethical imperative: not only an issue of disparity, but of equity i.e., not only ”Is there a difference”, but is it unfair and/or acceptable

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Possible ways of looking beyond

• Going beyond individual risk: Situating the individual (risk) within a household, neighborhood, geography, society and time – going beyond public health as risk-modification approaches to engaging with public health as a socio-cultural and political phenomenon

• Tapping into current body of knowledge across disciplines. Eg. Theory-driven inquiry, using conceptual frameworks, life-course epidemiology, psycho-social processes, qualitative and social science methods

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Key messages

• Averages are useful comparison tools for population health

• Averages hide various individual, household, geo-spatial and social differences in contexts

• Health equity research needs to move beyond describing disparity to explaining inequity

• Both for scientific and ethical reasons, health equity research needs to engage with why/how questions than only unpacking individual risk

• Many disciplines outside mainstream bio-medicine have engaged with the issue of social inequity, which can be used for health equity research

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