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Summary Most articles/papers for exam Population, Health and Place

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All papers for the exam Except: - Bloom & Canning (2004) - Anthamatten & Hazen (2011) - Boyle et al. (2015)

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Table of Contents
Billari (2015) – Integrating macro- and micro-level approaches in the explanation of
population change..................................................................................................................2
Ruger & Kim (2006) – Global health inequalities: an international comparison........................4
Graham et al. (2016) – Diversity and divergence: the dynamic burden of poor maternal health
...............................................................................................................................................5
Vallin & Meslé (2004) – Convergences and divergences in mortality. A new approach to
health transition.....................................................................................................................6
Bambra (2007) – Going beyond ‘The three worlds of welfare capitalism’: regime theory and
public health research.............................................................................................................8
Marmot, M., & Wilkinson, R.G. (2006). Social determinants of health...................................10
Bloom & Canning (2004) – Global demographic change: Dimensions and economic
significance...........................................................................................................................12
Vogt, Kluge & Lee (2020) – Intergenerational resource sharing and mortality in a global
perspective............................................................................................................................12
Sen (2003) – Development as capability expansion................................................................13
Mchome et al (2020) – When I breastfeed, it feels as if my soul leaves my body....................14
Popkin (2002) – An overview on the nutrition transition and its health implications..............15
Popkin et al (2020) - Dynamics of the double burden of malnutrition and the changing
nutrition reality.....................................................................................................................16
Visser & Haisma (2021) – Fulfilling food practices: applying the capability approach to
ethnographic research in the Northern Netherlands..............................................................17
Anthamatten & Hazen (2011) – Culture and identity..............................................................19
Metta et al (2015) – In a situation of rescuing life: Meaning given to diabetes symptoms and
care-seeking practices among adults in South-eastern Tanzania: a qualitative inquiry..........19
Quinn (2011) – Event sequencing as an organizing cultural principle.....................................20
Ballas (2013) – What makes a happy city?.............................................................................21
Boyle et al (2015) – Rethinking ageing in place: The ‘people’ and ‘place’ nexus.....................21
Meijering et al (2019) - “I think I’m better at it myself”: the capability approach and being
independent in later life........................................................................................................22

,Billari (2015) – Integrating macro- and micro-level approaches in the
explanation of population change

Demographic inquiry should be aimed at producing solid evidence on population trends and patterns, as
well as their associations across time and space.

 Discovering population trends and patterns is a macro-level challenge, albeit ultimately based on the
collection of micro-level data.

For the explanation stage, a micro-level life-course theoretical and empirical framework is essential in
order to explain what has been discovered.

Lee argues that along with the rise of what he calls ‘micro demography’, demography itself is
abandoning its core. Defining the core of an area of study is a challenging issue.

Lee argues that the rise of micro demography can be explained by three key developments:
1. The growing availability of survey data
2. The development of new or better statistical methods for analysing such data
3. The increase in computing power and opportunities for data storage

 If one wants to study population change, the key issues need to be defined as ‘macro demographic’
 Demographic inquiry, discovery, should remain as the ‘core’ of demography  It should comprise
the measurement, using appropriate formal methods and with the usual obsessive concern over data
quality, of population change, that is, demographic processes and their association over time and space.

Advances in formal modelling of population dynamics at the macro level also constitute discoveries. In
other words, demographers should keep the mathematical and statistical description of how the world
works, that is, of how population changes, at the centre of their scientific research.

 While discoveries should be highly valued, they also need to be seen as the starting point, or as the
target phenomena to be explained in the second stage.

In the second stage, an explanation of how population change comes about has to be rooted in models
of the action and interaction of individuals, couples, and families, as embedded in their macro-level
context.

The idea of the ‘life course’ is that demographic trajectories are shaped by life events (from birth to
death), and the timing of these life events is influenced by the historical, political and cultural context,
the development of individuals, and their relationships with significant others.
 The life-course perspective is useful in informing this second stage, together with theories on
prospective decision-making approaches that have informed recent comparative demographic surveys.

 For this second stage to be complete and fruitful, it needs to specify how macro-level population
patterns re-emerge from the action and interaction of individual life courses.

, We propose this second stage to be built according to the ‘social mechanisms’ approach  the
explanation of macro-level social change entails three parts, which we can see as the key components of
our second stage:
1. Situational mechanisms
o Are the ways through which the macro level is seen as affecting individual outcomes
o E.g., how mortality decline in a society affects individual fertility choices
2. Action-formation mechanisms
o Are the ways through which inter-individual processes affect individual outcomes
o E.g., how past fertility choices affect current fertility choices
3. Transformational mechanisms
o Are the ways through which, via the aggregation of individual outcomes or the
interactions among individuals, macro-level outcomes are generated




Situational mechanisms have implicitly been invoked in analyses that make use of multilevel models of
demographic behaviour, in which a micro-level outcome is studied as a function of macro-level factors.

Action-formation mechanisms have implicitly been invoked in life-course analyses of demographic
behaviour, in which micro-level outcomes are studied as a function of the past history of individuals and
in event-history analysis, generalized to outcomes that are more general than the timing of events as
life-course analysis.

 A focus on transformational mechanisms is therefore essential if one wants to move fully from the
discovery stage of demographic research and close the feedback by inferring an explanation of
population change, one that will allow further ‘discoveries’.

Transformational (micro  macro) mechanisms in demography:
- Mortality
o Changes in mortality can be patterned by findings made at micro level
o Model of Vaupel et al
 For each individual the ‘force’ of mortality μ = the instantaneous risk of dying at
age x , is seen as a function of the individual’s observed population group, i , her
or his exact age x at time t , and her or his unobserved ‘frailty’ z , that is, the
individual-specific chance of dying
 μ=μ i ( x , t) × z
 Individuals with a high z (high frailty) die earlier  average frailty of surviving
cohort will decline with age.
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