The health of nations in a global context: Trade, global stratification, and infant mortality rates

Article (PDF Available)inSocial Science [?] Medicine 63(1):165-78 · August 2006with585 Reads
DOI: 10.1016/j.socscimed.2005.12.009 · Source: PubMed
Despite the call for a better understanding of macro-level factors that affect population health, social epidemiological research has tended to focus almost exclusively on national-level factors, such as Gross Domestic Product per capita (GDP/c) or levels of social cohesion. Using a world-systems framework to examine cross-national variations in infant mortality, this paper seeks to emphasize the effects of global trade on national-level population health. Rather than viewing national-level health indicators as autonomous from broader global contexts, the study uses network analysis methods to examine the effects of international trade on infant mortality rates. Network data for countries were derived from international data on the trade of capital-intensive commodities in 2000. Using automorphic equivalence to measure the degree to which actors in a network perform similar roles, countries were assigned into one of six world-system blocks, each with its own pattern of trade. These blocks were dummy-coded and tested using ordinary least squares (OLS) regression. A key finding from this analysis is that after controlling for national-level factors, the two blocks with the lowest density in capital-intensive exchange, i.e., the periphery, are significantly and positively associated with national-level infant mortality rates. Results show the effects of peripherality and stratification on population health, and highlight the influence of broader macro-level factors such as trade and globalization on national health.
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Social Science & Medicine 63 (2006) 165178
The health of nations in a global context: Trade, global
stratification, and infant mortality rates
Spencer Moore
, Ana C. Teixeira
, Alan Shiell
de Montre
al Montreal, Que., Canada
University of North Carolina, NC, USA
University of Calgary, Canada
Available online 2 February 2006
Despite the call for a better understanding of macro-level factors that affect population health, social epidemiological
research has tended to focus almost exclusively on national-level factors, such as Gross Domestic Product per capita
(GDP/c) or levels of social cohesion. Using a world-systems framework to examine cross-national variations in infant
mortality, this paper seeks to emphasize the effects of global trade on national-level population health. Rather than
viewing national-level health indicators as autonomous from broader global contexts, the study uses network analysis
methods to examine the effects of international trade on infant mortality rates. Network data for countries were derived
from international data on the trade of capital-intensive commodities in 2000. Using automorphic equivalence to measure
the degree to which actors in a network perform similar roles, countries were assigned into one of six world-system blocks,
each with its own pattern of trade. These blocks were dummy-coded and tested using ordinary least squares (OLS)
regression. A key finding from this analysis is that after controlling for national-level factors, the two blocks with the
lowest density in capital-intensive exchange, i.e., the periphery, are significantly and positively associated with national-
level infant mortality rates. Results show the effects of peripherality and stratification on population health, and highlight
the influence of broader macro-level factors such as trade and globalization on national health.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Global health; Health inequalities; Trade; World-systems theory; Infant mortality; Automorphic equivalence
Despite the relative proliferation of studies
examining cross-national variations in population
health, recently greater attention has been given to
the development of contextual understand ings of
global health inequalities (Coburn, 2004, 2000;
Labonte & Torgerson, 2002; Shandra, Nobles,
London, & Williamson, 2004). The development
of such understandings has led scholars to examine
inter- rather than intra-national factors that influ-
ence population health. While more recent studies
have led us to think critically about the effects of
international factors and pro-market ideologies
such as ‘‘neo-liberalism’’ on population health, they
have yet to provide a framework that we might use
to measure how countries are differentially posi-
tioned within the global system and examine how
this global stratification among countries influences
0277-9536/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
Corresponding author. Tel.: +514 890 8000.
E-mail addresses: (S. Moore), (A.C. Teixeira),
(A. Shiell).
population health. There has thus been a tendency
within the literature on cross-national variations in
population health to neglect the importance of
systemic-level factors on national-level health,
thereby treating nations as individual actors auton-
omous from broader global contexts.
Contradicting this model and the assumption that
nations are independent and relatively equal actors
in the global system, this study demonstrates the
effects of world-system role and global stratification
on infant mortality rates. We argue that population
health is not simply a reflection of national-level
factors but must be understood contextually as a
product of the differential positions that countries
have in the global system. Our approach builds on a
world-systems framework to understand, measure,
and assess the effects of global stratification and
hierarchical trading structures on population health.
This conception of global contexts is based on a
structural instead of a geographical understanding
of contexts. In this case, world-system role refers to
the structural position that nations have within a
global pattern of trade relations; the concept of
global stratification refers to the inequalities and
dependencies that ensue from countries being
differentially located within this global pattern. By
assessing cross-national variations in infant mortal-
ity through such a lens, we demonstrate the utility in
thinking about systemic influences on population
health and studying how global trade affects
population health.
Despite the potential strength of political econo-
my approaches for studyi ng global stratification and
health, such approaches have yet to be fully
appreciated within the health sciences literature.
When such approaches have been applied, they have
raised critical attention to the effects of macro-level
social factors on national-, community-, and in-
dividual-level health (Baer, Singer, & Susser, 2003).
We see the application of a political economy
approach as providing a conceptual framework in
which the linkages between global-level factors and
population health can be identified and measured.
While national-level economic, social, and political
factors have significant effects on population health,
our analysis focuses primarily on the global level
and the effects of trade on health.
At the expense of macro-level factors, current
cross-national research on population health has
tended to focus on the effects of national-level
factors such as income distribution, strength of
labor, or social capital on population health (cf.
Kawachi & Kennedy, 2002; Kennelly, O’Shea, &
Garvey, 2003; Macinko, Shi, & Starfield, 2004;
Wilkinson, 2002, 1996). Such analyses commonly
treat nation-states as if they are equal with regard to
power and influence in the global system. If a
distinction is made among countries, it is frequently
expressed in terms of a ‘‘high/low income’’ division
based on national Gross Domestic Product per
capita (GDP/c). For example, Wilkinson divides
high- and low-income countries at $5000 annual
GDP/c (Wilkinson, 1996).
For present purposes, we identify two limitations
in current cross-national studies on population
health. First, based as they are on a single attribute
of a country, GDP/c, the ‘‘high/low income’’
typology does not capture the overall structure of
international relationships through which global
inequalities emerge. We argue that an income-based
typology is unidimensional and limited in its
capacity to measure power and global stratification.
Second, cross-national studies tend to focus on
either high- or low-income countries, thereby
removing from analysis the broader global context
in which high- and low-income status develops.
Instead, we suggest that a critical conceptualization
of the global system rooted in the study of
international trade and global stratification leads
to a fuller understanding of cross-national varia-
tions in population health and the potential inter-
action between global contexts and national
institutions and policies.
World-systems perspectives
Central to world-systems perspectives is a con-
ception of the global system as consisting of
‘‘intersocietal networks in which the interactions
(e.g., trade, warfare) are important for the repro-
duction of the internal structures of the composite
units (e.g., nation-states)’’ (Chase-Dunn & Hall,
1993, p. 855). Within these inter-soci etal networks,
three structural positions can be identified: core,
periphery, and semi-periphery (Wallerstein, 1974).
The core is seen as being rich and economically
diversified, having powerful and strong state in-
stitutions, and independent of external controls; the
periphery is economically overspecialized, more
dependent on foreign capital, and subject to
exploitation and control by core states (Hall, 1996;
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178166
Wallerstein, 1974); the semi-periphery rests midway
between the core and periphery on a series of
dimensions including the complexity and diversity
of economic activities and strength of state institu-
tions (Hall, 1996; Van Rossem, 1996; Wallerstein,
1974). These zo nes are linked to one another in
various asymmetric exchange relationship s through
which a global division of labor and a hierarchical
system of political, economic, and cultural relations
While nation-states may within certain limits
change zones within the system, the hierarchical
core/periphery structure of the system remains.
Peripheral states remain in a structurally dependent
relationship that perpetuates their subord inate
position to the core (Hall, 1996). The world-system
roles, or strata, thus reflect underlying global power
relations that structure the opportunities for those
strata. A country’s role is more than a product of its
GDP, it is a measure of its interaction within an
overall hierarchy of relationships. The particular
characteristics of nation-states are seen as influ-
enced by the role that those states play in this
hierarchical structure (Smith & White, 1992; Snyder
& Kick, 1979). For example, changes in national
levels of economic development and the degree of
inequality within countries have been suggested to
be a product of a state’s position in the world
system (London & Smith, 1988 ; Snyder & Kick,
1979). In other words, cross-national variations are
to be understood context ually, as the historical
product of the complex interaction of local societies
with an expanding world system (Chase-Dunn &
Grimes, 1995). The focus is thus on the interactions
among the different zones of the system, rather than
the nation-state itself. These interactions affect the
internal dynamics and social structures of nation-
states (Hall, 1996).
Political economy and world-systems perspec-
tives, although underrepresented in cross-national
studies of population healt h, have found limited
empirical application in the health sciences litera-
ture (Dyches & Rushing, 1996, 1993; Elling, 1994;
Lena & London, 1993). For example, Dyches and
Rushing (1996) argue that the status of women’s
health must be understood within the context of
international stratification and the global division of
labor; Elling (1994) argues that the cross-national
study of health systems requires those national
health systems to be understood in relation to their
position in the ‘‘capitalist political economic world
system.’’ World-system perspectives have also been
applied to the study of infant mortality (cf., Lena &
London, 1993; Shandra et al., 2004).
In terms of our current analysis, howeve r, earlier
applications have been incomplete in several ways.
First, those studies have yet to examine the direct
effects of world-system role on infant mortality
rates. For example, Shandra et al. (2004) use a non-
core/peripheral country typology based on the work
of Snyder and Kick (1979) to examine if economic
and sociopolitical factors have unique effects in
non-core as compared to core countries. While this
is a useful method to examine if different dynamics
exist in the two groups, it does not specifically
address the question of the overall effects of world-
system role on infant mortality. Second, previous
studies have relied on world-system position mea-
sures that originate from 1960s international trade
data (Bollen, 1983; Snyder & Kick, 1979). While
such measures are well-established, they do not
reflect the geopolitical changes that have occurred
since the 1960s. Finally, previous world-system
position measures in the health literature have been
based on a structural rather than an automorphic
measure of equivalence. Structural equivalence
measures have been shown to conflate geographical
proximity with a country’s role in the system
(Borgatti & Everett, 1992; Smith & White, 1992;
Van Rossem, 1996). The world-system position
measures that we develop are based on recent
2000 international trade data and an automorphic
equivalence measure, and thus provide a more up-
to-date and accurate picture of global stratification.
Fig. 1 illustrates the conceptual model underlying
our analysis. To examine if world-system perspec-
tives contribute to our understanding of the effects
of the global system on population health, we
combine network and ordinary least squares (OLS)
regression methods. First, our study employs
established network analysis proced ures to assign
countries to specific roles in the world system. These
assignments derive from blockmodeling techniques
using circa 2000 international trade data. After
assigning countries to these roles, we use OLS
regression to test the effects of world-system role on
infant mortality rates while controlling for national-
level socioeconomic and geographical factors.
Although we recognize possible recipr ocal effects
occurring between global- and national-level fac-
tors, our analysis and discussion focuses primarily
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178 167
on the effects of world-system role on population
Network analysis
Network data
International trade data were collected from the
United Nations Commodity Exchange Database
(United Nations Statistics Division, 2004), which
contains over 40 years of trade data on over 1000
commodities. These data follow the Standard
International Trade Classification (SITC), which
organizes commodity items into diverse commodity
groupings. Such data are frequently used to measure
world-system position (Breiger, 1982; Nemeth &
Smith, 1985). Although some studies supplement
trade data with political or cultural ties among
countries (Snyder & Kick, 1979; Van Rossem,
1996), we collected international trade data exclu-
sively on four capital-intensive, production-based
commodities. Our choice of commodities is based
on a factor analysis of international commodity
trading from 1965–1980 (Smith & Nemeth, 1988).
We collected national trade data on the four
commodities having the highest loadings on the
hi-tech and heavy-manufacturing factor. Those
commodities were (1) non-electrical machinery
(SITC ]71), (2) plastics and synthetics (SITC ]58),
(3) transportation equipment (SITC ]71), and (4)
metal manufactures (SITC ]69). Compared to the
four other factors in the Smith & Nemeth analysis,
the hi-tech/heavy-manufacturing factor represents
capital-intensive, production-based commodities
(Smith & Nemeth, 1988). Since commodities falling
into this factor are capital-intensive, the use of these
particular commodities to measure global trade
structures incorporates certain dimensions of na-
tional economic development beyond GDP/c and
provides arguably a better measure of global
stratification than the other factors.
Trade data for the year 2000 were sought for all
nations with a population over one million. To
maximize available trade data, we used a two-year
reporting window around 2000. If there were no
data available for a nation in 2000, we sought data
for that country in 1999. If no data were reported
Global-Level Context National-Level Variables Population Health
World-System Role
Core 2
Semi-Periphery 1
Semi-Periphery 2
Periphery 1
Periphery 2
Economic, Social, Political Factors
GDP per capita
Aid per capita
Trade as percentage of GDP
Female Literacy Rates
Voice and Accountability
Political Stability
Population Health Outcome
Infant Mortality Rates
Geographical Control Variables
Tropical Country
Landlocked Country
Fig. 1. Conceptual model of world-system effects on IMR.
Smith and Nemeth (1988) identify five factors—(1) hi-tech/
heavy manufacture, (2) low-wage/light manufacture, (3) sophis-
ticated extracted, (4) simple extractive, and (5) food products—
(footnote continued)
located along a capital—labor-intensive and production—extrac-
tion-based scale.
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178168
for a country in 2000 or 1999, we sought exchange
data for 1998, followed by 2001. In total, we
obtained data on the trade of hi-tech and heavy
manufacture commodities for 128 co untries: 117 for
2000, six for 1999, four for 2000, and one for 1998.
We used these data to construct a network data set,
which consists of an n n matrix X, where n equals
the number of countries in the analysis (128 128).
Each cell in the non-valued data matrix, X
, records
simply the occurrence or non-occurrence of trade
between countries i and j, and not the specific value
of the trade. Since the data revealed differences
among countries between import and export ties,
the X matrix was asymmetrical, meaning that some
countries might import but not export (or vice
versa) to another country.
Blockmodeling techniques
Blockmodeling can be seen as both an approach
to the analysis of netw ork data in which theore-
tical importance is given to the concept of social
roles and positions and a set of analytic proce-
dures to delineate those roles within a social
network (Doreian, Batagelj, & Ferligoj, 2005). A
blockmodel consists of a matrix that describes
the ties among the different roles and a descrip-
tion of which actors, e.g., countries, are assigned to
which roles (White, Boorman, & Brieger, 1976;
Wasserman & Faus t, 1994). To identify specific
national roles within the global system, we apply
blockmodeling techniques to the network trade
data. Those techniques involve: (1) the derivation
of automorphic equivalence measures for each
country–country relationship, (2) the use of corre-
spondence analysis to represent graphically the
degree of automorphic equivalence among coun-
tries and begin assignment of national roles, (3) the
application of a hierarchical clustering procedure
to refine assigned country roles, and (4) testing
the reliability of the blockmodel against core–
periphery blockmodel structures. Although we
employ certain methodological variations, our
general approach replicates established procedures
for conducting positional network analyses and
delineating world-system roles (Smith & Nemeth,
1988; Smith & White, 1992; Van Rossem, 1996;
Wasserman & Faust, 1994). In contrast to earlier
work, however, we (1) update national role assign-
ments using international trade data circa 2000,
(2) apply an automorphic equivalence measure
that reduces the conflation of geographical proxi-
mity with role structures, and (3) assign world-
system role according to the international
trade in capital-intensive, production-based com-
In contrast to structural equivalence, which
measures role similarity based on actors’ ties to
the same specific actors, automorphic equivalence
measures role according to how comparable actors’
ties are in a network (Borgatti & Everett, 1992; Van
Rossem, 1996). For example, to be considered
equivalent, Honduras and Moldova do not both
need to trade with the United States (although they
might), they both only need to trade with countries
that themselves have similar roles in the network,
i.e., Honduras may trade with the US and Moldova
with Germany. We used the MAXSIM algorithm in
the netwo rk analysis software package UCINET
(Borgatti, Everett, & Freeman, 2002) to measure the
maximal (dis)similarity of the 128 countries. The
result was a symmetrical matrix Z in which the
value in each cell, Z
, equals the degree of
automorphic equivalence between countries i and j
¼ Z
A correspondence analys is was then conducted
on the resulting automorphic equivalence matrix.
The analysis converts a matrix of data into a
graphical representation such that its rows and
columns are depicted as points in a space (Gatrell,
Popay, & Thomas, 2004; Salisbury & Barnett, 1999;
van der Heijden & de Leeuw, 1989). Points that lie
closer together in space have a higher degree of
automorphic equivalence. Since the equivalence
matrix was symmetrical, the analysis results in an
identical set of coord inates for the rows and
columns (Salisbury & Barnett, 1999). The graphical
display was visually examined for distinct clusters of
points, i.e., countries. Based on the visual inspec-
tion, we classified countries into different roles
according to the world-system division of co re,
semi-peripheral, and peripheral zones.
To refine the groupings derive d from visual
inspection, we complemented the correspondence
analysis with a hierarchical clustering procedure.
We used the Johnson complete-link algorithm on
the automorphic equivalence matrix to cluster
countries with similar patterns of trade. The
algorithm begins with each country as its own
cluster (identity partition) and then joins pairs of
countries together that are considered most similar.
It continues to join together pairs until all countries
are a single cluster (the complete partition). The
clustering procedure indicates the degree of similar-
ity among countries at different levels of association
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178 169
(Borgatti et al., 2002). We used the number of
groupings found in the correspondence analysis to
establish the significant level of association in the
partition. For example, if visual inspection of the
correspondence analysis revealed six groupings, we
set the level of association at six partitions higher
than the identity partition. This level was used as
the ‘‘cutoff point.’’ If a country was found clustered
below that level with a different block of countries
than suggested by the correspondence analysis, we
reassigned that country into the role indicated by
the hierarchical clustering procedure.
The final step in our blockmodeling procedures
was to test our blockmodel against previous
specifications of core–periphery blockmodel struc-
tures (Breiger, 1982; Snyder & Kick, 1979; Wasser-
man & Faust, 1994 ). A central concept in
blockmodel analyses is density, which refers to the
degree of interconnectivity among actors in a
network. Den sity is a proportional measure of the
number of ties present in a network over the number
of all possible ties in the network. A network
characterized by perfect density means that each
actor is connected to all other actors in the network.
In terms of core–periphery specifications, core areas
are characterized by high internal density whereas
peripheral areas tend to maintain lower internal
densities (Wasserman & Faust, 1994). In world-
system terms, core areas have a high level of
horizontal and vertical exchange ties, i.e., they tend
to be well-connected to core and non-core countries.
Peripheral areas are better characterized by vertical
exchange. In other words, peripheral nations tend to
exchange with core countries rather than maintain-
ing a high density of exchange with other peripheral
countries (Chase-Dunn & Hall, 1993).
For the blockmodels to compare reliably with
world-systems theory, intra-block trading, i.e.,
the horizontal ties among members of specific
blocks, should be the most dense in core 1 and
decrease steadily tow ard the periphery (Wasserman
& Faust, 1994). The block with the least intra-block
density should be the peripher y, which would
represent the relative lack of exchange of hi-tech
and heavy manufactures among peripheral na-
tions. In addition, the core should have the highest
inter-block density of trade with the other blocks,
thereby showing the strength of its vertical ties
with other world-system areas. The periphery
should have the lowest overall inter-block density
of trade, but its inter-block ties should be the
highest with the core.
OLS regression analysis
Using the roles assigned, the OLS regression
analysis tests the direct effects of world-systems role
on infant mortality rates. We build two models: (1)
the control model in which we regress infant
mortality rates on six national-level socioeconomic
and two geographical variables, and (2) the test
model in which we add world-system role along
with any significant interaction variables to model 1.
In addition to examining the significance of specific
world-system roles, we use an incremen tal F-test to
determine if the overall R
change between models 1
and 2 is significant, thereby indicating the signifi-
cance of world-system role itself as a predictor of
infant mortality rates. Several regression diagnostic
procedures were used to test for the presence of
outliers and influential cases, multicollinearity, and
heteroscedasticity (Fox, 1991).
Data and measurement
Dependent variable. Infant mortality rates: Infant
mortality is seen as a sensitive mortality indicator
that is in general highly correlated with overall
mortality rate (Wahdan, 1996) and one of the best
indicators of a nation’s overall health status (Shen &
Williamson, 2001). While other indicators of na-
tional health status may reflect a latency period
between the indicator and earlier social conditions,
infant mortali ty rates are commonly assumed to
reflect present conditions (Coburn, 2004).
Infant mortality rates were obtained from the United
Nations Development Programme and are from 2001
(UNDP, 2004). Infant mortality rates represent the
probability of dying between birth and one year of
age, expressed per 1000 live births. Following previous
applications of infant mortality rates as a dependent
variable, we logged the national infant mortality rates
to reduce the potential problem of heteroscedasticity
(Shandra et al., 2004).
Independent variables. World-system role: To test
the effects of world-system role on infant mortality
rates, we dummy-code countries into the previously
assigned roles. We exclude the core 1 role from the
regression as reference.
National-level economic variables
Economic development
Using World Bank data (2004), we measure
economic development based on a country’s GDP/c
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178170
adjusted for Purchasing Power Parity (PPP) values.
GDP/c has been shown to be a significant predictor
of infant mortality rates (Bradshaw & Tshandu,
1990; Frey & Field, 2000; Lena & Londo n, 1993;
Shandra et al., 2004; Shen & Williamson, 2001).
To reduce the effect of incidental transactio ns of
unusual size (cf. Kim & Shin, 2002), we averaged a
country’s reported GDP/c figures from 1991–2000.
As is standard in such analyses, the GDP/c
variable was logged to correct for its highly skewed
distribution (Fr ey & Field, 2000; Lena & London,
1993; Shandra et al., 2004; Shen & Williamson,
Economic dependency
In contrast to relational data, dependency per-
spectives tend to use national attribute data to
measure specific two-way relationships between
countries, countries and a corporation, or countries
and international lending agencies (van Ross em,
1996). Economic dependency measures have been
shown to have indirect effects on infant mortality
and act as potentially significant intervening vari-
ables affecting child mortality (Bradshaw, Noonan,
Gash, & Sershen, 1993), infant mortality (Wimber-
ley, 1990), infant survival (Shen & Williamson,
2001), and life expectancy (Wimberley, 1990). We
use two measures of economic dependency: (i) aid
dependency and (ii) trade market dependency. Data
for both come from the World Bank, and represent
an average value for each country from 1991–2001.
Aid dependency was measured using national levels
of aid per capita. Aid per capita is seen to capture
the degree to which countries are dependent on
extra-territorial capital an d financing to ensure a
minimal functioning of the national system. The
adverse effects of aid dependency on national health
outcomes have been linked to such factors as (1)
reduced governmental financial capacities to spend
in the social, educational, and health fields and (2)
reduced flexibility in responding to economic or
social crises (Shen & Williamson, 1997).
Trade market dependency was operationalized as
the ratio of gross trade flows (merchandise imports
and exports) to national GDP. The variable
represents the importance of trade to the national
economy and a country’s level of exposure to the
international economy (Frey & Field, 2000; Shen &
Williamson, 1997; Van Rossem, 1996; World Bank,
2005). Since the measure is based on gross flows
(value of exports plus imports) rather than net flows
(value of exports minus imports), countries may
have a gross-trade flows to GDP ratio greater than
Trade market dependency has been linked to
specific national health outcomes through the
reduced capacity of governments to raise revenues
and to spend in the social, educational, and health
fields (Shen & Williamson, 1997).
National-level sociopolitical variables
Female educational status
Gender stratification theory argues that gender
equality and female education reduces infant
mortality (Frey & Field, 2000). To operationalize
the effects of female education, we use female
literacy rates. Female literacy is based on the
reported literacy of women over the age of 15
during the 1990s. Female literacy rates were
collected from the World Bank and supplemented
with data from UNDP and the United Nations
Educational, Scientific, and Cultural Organization
(UNESCO, 2004).
Political democracy
Political democracy has been associated with
higher population health status (Lena & London,
1993). Previous studies have relied on Bollen’s
(1983) index of political democracy to measure
national levels of political democracy. As an
alternative indicator of political democracy, we use
World Bank Governance indicators of ‘‘Voice and
Accountability.’’ The measure reflects the proc esses
by which national authorities are selected and
replaced, and thus the extent to which a country’s
citizens are able to participat e in selecting their
political representatives (Kaufmann, Kray, & Mas-
truzzi, 2003). These measures are based on the
perceptions of over 18 different organizations and
derived from a country’s relative score compared to
other nations in the sample (Kaufmann et al., 2003).
World Bank governance indicators are relatively
recent and, as a result, we average estimates only
from 1996 to 2000.
Political stability
Political stability has been used in previous
studies to examine its role in the deterrence or
facilitation of foreign direct investment in countries
There are countries with a percentage greater than 100 in all
six blocks. For example, the Netherlands found in core 1 has a
value of 111, while Moldova, a periphery 2 country, has a value
of 122.
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178 171
(Bandelj, 2002; London & Ross, 1995 ). We used the
measure of political stability found in the World
Bank governance indicators to capture the per-
ceived likelihood that the government in power will
be destabilized or overthrown in the near future
(Kaufmann et al., 2003).
Control variables
Geographical context
Recent macro-economic studies of global poverty
and national development have highlighted the
importance of geographical and ecological factors
influencing economic growth and disease prevalence
(Gallup & Sachs, 1999; Sachs, 2005). Such analyses
have stressed the disadvantages in economic devel-
opment that (1) tropical countries experience
relative to temperate countries due poten tially to
higher disease burdens and limitations on agricul-
tural productivity, and (2) landlocked countries
have compared to coastal regions because of high
transport costs associated with trade (Gallup &
Sachs, 1999; Sachs, 2005). To control for the
possible effects of geographical context in our
models, we included two variables: (1) a dummy
variable representing whether a country was land-
locked, and (2) a dummy variable representing if a
country was located in the tropics. A tropical
country is defined as being located between the
Tropics of Cancer and Capricorn. Data for both are
drawn from the Center for International Develop-
ment, Harvard University (Gallup & Sachs, 1999).
Network analysis
The correspondence analysis has a flat U-shape
(Fig. 2). Moving right to left along the curve, one
moves along a continuum from core to periphery.
Visual inspection reveal s six distinct groupings ,
which are labeled core 1, core 2, semi-periphery 1,
semi-periphery 2, periphery 1, and periphery 2. This
finding conforms with other analyses that have
found subgroups among the three world-system
zones (c.f. Smith & White, 1992).
Based on the hierarchical clustering procedure,
the significant level of association in the partition
was set at 141.99. Using this partition level as the
‘‘cut-off,’’ we changed the role of countries that
were found associated below this level with a
different block of countries than suggested by the
correspondence analysis. To refine the assigned
country roles, we thus changed the position of
seven countries: Norway and South Korea were
repositioned from core 2 to core 1; Croatia was
repositioned from semi-periphery 2 to semi-periph-
ery 1; Egypt was repositioned from semi-periphery 1
to semi-periphery 2; and, Cuba, Ecuador, and
Honduras were repositioned from periphery 1 to
periphery 2.
In total, 128 countries were classified into one of
six mutually exclusive blocks. Table 1 lists countries
by world-system role assignment. There were 21
nations placed in core one; 11 in core 2; 17 in semi-
periphery 1; 17 in semi-periphery 2; 10 in periphery
1; and 52 in periphery 2.
Blockmodel reliability testing
Table 2 shows the intra- and inter-block density
of ties within and among the six blocks. The intra-
block density is shown on the diagonal of the
matrix. For example, the intra-block density for
core 1 is 1.0, thereby representing a completely
dense network. In other words, each nation in core 1
exchanges hi-tech and heavy manufacture commod-
ities with each of the other nations in core 1.
Moving from the core to the periphery, we observe a
decrease in intra-block density values. There is a
noticeable decrease in the move from semi-periph-
ery 1 to semi-periphery 2, from .938 to .460. While
semi-periphery 1 countries are relatively well-con-
nected to one another in terms of the trade of
capital-intensive commodities, trade-tie density
among semi-periphery 2 countries is slightly under
one half of that among semi-periphery 1 countries.
The intra-block density among periphery 2 coun-
tries is the lowest among all blocks at 10%,
demonstrating that periphery 2 countries do not
maintain dense trade ties in such commodities with
other periphery 2 countries.
Results show that the core has the highest density
of export (rows) and import (columns) trade with
other blocks in the system. The inter-block density
values show that the periphery trades primarily with
the core. Results also demonstrate that the periph-
ery has a higher de nsity of import than export ties
with the core. Intra- and inter-block density values
Follow-up tests revealed that the reassignment of country
roles had no significant effect on final regression results. Variables
that were significant remained so after testing for changes due to
hierarchical clustering reassignment.
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178172
thus conform to previous specifications of core–per-
iphery blockmodel structures (Breiger, 1982; Snyder
& Kick, 1979; Wasserman & Faust, 1994).
Regression analysis
For the purpose of the regression analysis,
countries with missing cases for any of the variables
were dropped from the sample.
The final number
of countries in the sample was 116. The countries
were dummy-coded into six roles: core 1 (reference),
core 2, semi-periphery 1, semi-periphery 2, pe riph-
ery 1, and periphery 2.
Regression diagnostics
Outlier analysis using studentized residuals and
hat values (Freund & Littell, 2000 ; Neter, Kutner,
Nachtsheim, & Wasserman, 1996) detected the
presence of six outliers. To identify any influential
cases in our sampl e, we used Cook’s D, Dffits, and
Dfbetas (Neter et al., 1996). Ten cases were signaled
by the diagnostics. As a result, outlying and
influential cases were analyzed and then checked
for any possible data inaccuracies. Secondly, we
followed conventional procedures to rerun the
regression models omitting different combinations
of outlying and influential cases while checking for
changes in the parameter estimates and significance
levels (Bol len & Appold, 1993; Freund & Littell,
2000; Neter et al., 1996). One country (South
Africa) influenced the significance level of the core
2, i.e., when model 2 is run without this case, core 2
is no longer significant. The observation scored
among the highest in Dffits and Cook’s D statistics.
South Africa is considered a core 2 country, but it
has an infant mortality rate that is markedly higher
than the remaining core 2 countries, i.e., South
Africa has an IMR of 56 although the average
infant mortality rate for other core 2 coun tries is
15.22. Given these findings, the decision was made
to suppress this case, leaving the final sample size at
115 (Table 3).
To detect potential problems of multicollinearity,
we used Variance Inflation Factors (VIF) and
analyzed the structure of the X
X matrix, neither
of which revealed evidence of multicollinearity
(Freund & Littell, 2000; Neter et al., 1996). The
plot of residuals against estimates did not show the
presence of heteroscedasticity in the data.
OLS regression analysis
Table 4 provides the regression results. Model 1
shows the significance of our control variables. Both
geographical variables appear to be significantly
and positively associated with infant mortality,
meaning tropical and landlocked countries tend to
have higher levels of infant mortality. As expected,
GDP/c (.542, po:001) and female literacy (.002,
Fig. 2. Correspondence analysis with assigned world-system roles.
Countries dropped were Azerbaijan, Bhutan, Cuba, Czech
Republic, Gabon, Georgia, Guinea, Kyrgyz Republic, Libya,
Macedonia, Serbia and Montenegro, and Singapore.
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178 173
Table 1
Nation-state roles based on exchange of capital-intensive, production-based commodities (n ¼ 116)
Core 1 (20) Semi-periphery 1 (17) Periphery 1 (8) Periphery 2 (cont’d)
Australia Argentina Kazakhstan Gambia
Austria Bulgaria Kenya Guatemala
Belgium Croatia Mauritius Honduras
Canada Hungary Namibia Jamaica
China Indonesia Senegal Lesotho
Denmark Iran Sri Lanka Madagascar
France Lebanon Trinidad and Tobago Malawi
Germany Luxembourg Zimbabwe Mali
India Mexico Moldova
Ireland New Zealand Mongolia
Italy Pakistan Nepal
Japan Philippines Nicaragua
Netherlands Poland Niger
Norway Romania Nigeria
Spain Slovakia Panama
South Korea Slovenia Papua New Guinea
Sweden Ukraine Paraguay
Switzerland Rwanda
United Kingdom Saudi Arabia
USA Sudan
Core 2 (10) Semi-Periphery 2 (16) Periphery 2 (45) Swaziland
Brazil Belarus Albania Syria
Finland Chile Algeria Tanzania
Greece Colombia Armenia Togo
Israel Costa Rica Bangladesh Turkmenistan
Malaysia Coˆ te d’Ivoire Benin Uganda
Portugal Egypt Bolivia Uruguay
Russian Federation Estonia Botswana Viet Nam
South Africa
Jordan Burkina Faso Yemen
Thailand Kuwait Burundi Zambia
Turkey Latvia Cameroon
Lithuania Central African Rep.
Morocco Dominican Rep.
Oman Ecuador
Peru El Salvador
Tunisia Ethiopia
South Africa was excluded from regression analyses based on regression diagnostic results.
Table 2
Average intra- and inter-block density of ties
Core 1
(n ¼ 20)
Core 2
(n ¼ 12)
Semi-peri 1
(n ¼ 17)
Semi-peri 2
(n ¼ 17)
Periphery 1
(n ¼ 10)
Periphery 2
(n ¼ 52)
Core 1 1.000 1.000 .994 1.000 1.000 .982
Core 2 1.000 .991 .968 .936 .936 .846
Semi-peri 1 .997 .963 .930 .886 .706 .555
Semi-peri 2 .961 .829 .592 .460 .353 .346
Periphery 1 .883 .464 .312 .300 .244 .219
Periphery 2 .469 .206 .107 .126 .102 .101
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178174
po:05) act as significant variables influencing infant
mortality. While the economic dependency variables
are not significant, the political democracy variable
is (.120, po:001). In other words, higher levels of
economic development, female literacy, and politi-
cal democracy predict lower levels of infant
Model 2 tests the effects of world-system role on
infant mortality controlling for geographical and
national-level variables. Results indicate that per-
ipheral roles within the world system are signifi-
cantly and positively associated with infant
mortality (p1: .257, po:01; p2: .159, po:05). The
stronger effect found among periphery 1 compared
to periphery 2 countries may be due to the greater
importance that trade has for periphery 1 econo-
mies. In testing for interaction effects among
variables, we found that the interaction bet-
ween core 2 and political stability had a signifi-
cant and negative effect on infant mortality rates.
As political stability increases in core 2 countries,
infant mortality rates decrease and vice versa. An
Table 3
World-system role descriptive statistics
(PPP) $
Aid/c $ Trade/
Voice and
Core 1 9.15 20,046 .13 65.36 95.16 1.14 1.03
Core 2 15.22 10,585 27.27 73.83 88.92 .47 .25
Semi 1 20.29 8928 15.66 82.38 88.59 .24 .25
Semi 2 24.06 6136 27.92 82.79 76.02 .09 .19
Peri 1 50.0 3902 36.81 86.38 76.75 .07 .21
Peri 2 68.73 2398 38.69 69.02 58.70 .40 .29
Descriptive statistics based on final sample size of 115.
Table 4
Unstandardized regression coefficients of infant mortality rates (log) on world-systems role and selected control variables for 116 countries
Model 1: control variables Model 2: world-system role
Constant 3.524
(12.60) 3.393
Tropical climate .117
(2.91) .096
Landlocked country .136
(3.35) .117
GDP per capita (log) .542
(7.81) .494
Aid per capita .001 (1.84) .000 (.98)
Trade % GDP (log) .058 (.67) .113 (1.29)
Female literacy .002
(2.55) .002
Voice and accountability .120
(3.80) .112
Political stability .008 (.25) .041 (1.20)
Core 2 (n ¼ 9) .101 (1.33)
Semi-periphery 1 (n ¼ 17) .097 (1.56)
Semi-periphery 2 (n ¼ 16) .068 (1.00)
Periphery 1 (n ¼ 8) .257
Periphery 2 (n ¼ 45) .159
Core 2 political stability
R-Square .889 .902
Adjusted R-square .881 .889
F-change 2.211
N 115 115
Note: The numbers in parenthesis are the t-values.
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178 175
incremental F test revealed that the R
between model 1 and 2 was significant (F
At a time in whi ch attention is turning to the
effects of geography and climate on health, our
analysis highlights the sociopolitical and historical
dimensions of global disparities in health. Being
peripheral, unlike being tropical, reflects a histo-
rical and social process of marginalization in which
countries have been excluded and disempo-
wered from more symmetrical trading relationships.
Moreover, peripherality implies an ongo ing socio-
political process that weakens the capacity of
countries to maintain sovereignty over their own
borders and the health of their populations. If, as
our findings suggest, being peripheral affects popu-
lation health in a way that being in the semi-
periphery or core does not, trade and stratification
have disproportionate effects on population health
depending on the role countries play in the global
system. Rather than assuming then that economic
globalization or neoliberalist policies affect all
countries evenly, we suggest that economic globa-
lization has different implications for peripheral
than it does for core or semi-peripheral countries.
This is not only due to national-level variations in
class structure or the welfare state (Coburn, 2004)
but to global-level variations in power and influ-
ence. In this regard, we argue for a macro-level
understanding of economic globalization that views
the uneven effects of neo-liberalism at the national
level as influenced by asymmetric trading relation-
ships at a global level.
Although we emphasize macro-level influences
on health, we recognize that global processes can
not account fully for intra-national socioecono-
mic processes (Knoke, 1990). The effects of
national-level factors on population health and the
reciprocal effects occurring between global- and
national-level factors remain important areas of
research. Yet, global structures and processes
should be seen as setting the parameters for
national-level influences on health (Wood ward,
Drager, Beaglehole, & Lipson, 2001). Global
structures and processes, such as international
trade, generate systems of stratification in which
countries are differentially positioned. The multi-
dimensional character of such strata may not be
sufficiently captured with a ‘‘high/low income’’
typology based on national GDP/c. Instead of
using national attribute data to classify coun-
tries, the use of relational trade data along with
blockmodeling techniques allows us to generate
alternative typologies and approaches to the
study of global inequalities in health. In so doing,
we draw attention to the effects of trade, power,
and peripherality on global health. While a six-tier
core–periphery classification may only be an
initial step in that direction, it is one that helps
identify the effects of peripherality on population
While national-level factors play an important
role in population health outcomes, such factors
occur within particular global contexts. These
contexts are not the same for all countries.
Depending on a country’s position in the system,
globalization and trade may have disproportionate
effects on national institutions, policies, and health.
As recent commentaries on trade and public health
have argued, international trade agreements pose
challenges to the sovereignty that national govern-
ments have over public health policy (Shaffer,
Waitzkin, Brenner, & Jasso-Aguilar, 2005). For
example, World Trade Organization (WTO) agree-
ments can supersede the internal laws and regula-
tions of any WTO member country. In the event of
a trade dispute between member countries, those
countries must comply with the decision of a WTO
tribunal with regard to that dispute, or face either a
financial penalty or an autho rized trade sanction by
the ‘‘winning’’ country (Shaffer et al., 2005).
Powerful countries remain however at a consider-
able advantage over less powerful ones in the
dispute settlement process (Howse, 2004). Yet,
power is not restricted to formal bilateral and
multilateral negotiation processes, it is an inte-
gral feature of the global system. Peripheral
countries are structurally disempowered and may
be viewed as being at a higher level of vulnera-
bility to the negative effects of global ization and
trade. As a result, there may be the need for greater
attention to the disproportionate effects of interna-
tional trade on vulnerable countries and the further
development of international agreements and reg-
ulations that grant peripheral cou ntries special
rights in developi ng and protecting their public
health systems from the negative effects of globa-
S. Moore et al. / Social Science & Medicine 63 (2006) 165–178176
This work was supported through funding by the
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    • Proponents of dependency/world-systems theory contend that dependent relations between core and peripheral countries foster resource and surplus extraction, resulting in limited resources for investment in public health, family planning, nutrition, education, pre-natal and post-natal care programs, and other factors that reduce infant and child mortality (see, e.g.,Shandra et al. 2011). Research results are mixed on the link between various measures of dependence (including foreign investment, trade dependence, debt dependence and structural adjustment, and export commodity concentration) and infant and child mortality (see, e.g.,Moore et al. 2006;Ragin and Bradshaw 1992;Shandra et al. 2004Shandra et al. , 2005Shandra et al. , 2011Williamson 1997, 2001; York and Ergas 2011).
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    • (Moore, Teixeira, and Shiell, 2006
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    [Show abstract] [Hide abstract] ABSTRACT: Drawing from various bodies of social scientific literature and research, the authors assess the extent to which infant and child mortality rates in less developed countries are impacted by the percentage of domestic populations living in urban slum conditions. Results of two-way fixed effects panel model estimates of 80 less developed countries from 1990 to 2005 indicate that growth in the percentage of populations living in urban slum conditions positively affects both forms of mortality rate. The effects, moreover, are much more pronounced for African countries than for less developed countries in Latin America and Asia and moderately larger for the Asian nations than those in Latin America. Additional findings suggest that the magnitude of the effect of urban slum prevalence on infant and child mortality increased through time for the African countries, but not for the Latin American and Asian countries in the study.
    Full-text · Article · May 2012
    • La qualification limitée de la main-d'oeuvre locale couplée à un accès limité à l'éducation et la formation contribue à accentuer cette vulnérabilité. Puisque la récession fait peser un risque pour la santé, certains auteurs ont, à l'inverse, souligné les aspects positifs de la croissance [Moore, Teixera, Shiell, 2006] . Indiscutablement , la croissance économique soutenue des pays émergents a permis de réduire la part de l'extrême pauvreté et d'améliorer sensiblement le niveau de vie, deux macrodéterminants de la santé.
    [Show abstract] [Hide abstract] ABSTRACT: This article discusses the interactions between the concepts of risk and health, from a social sciences and humanities perspective. It provides a broad overview of the interdisciplinary literature, published in both French and English. However, given the breadth of the task, the main focus of the article is on the ‘spatiality’ and the unequal configuration of risks for health. This is supported by diverse examples, to better understand the different spatial scales, from the local to the global, at which hazards and uncertainties are constructed, perceived and amplified. To situate the processes at play within a ‘social’ context, the authors draw on two types of complementary, but often viewed as distinct, explanations: the spatio-epidemiological approach of spaces of risk and the cultural approach to risk in societies. The relationship between these two approaches contributes to a better understanding of the issues, necessary to inform and orient public health actions and interventions.
    Article · Mar 2011
    • According to the World Bank (2007), secondary education completes the provision of basic education that began at the primary level and aims at laying the foundations for lifelong learning and human development , by offering more subject-or skill-oriented instruction using more specialized teachers. Prior research links this form of human capital to lower levels of infant and child mortality rates (e.g., Frey & Field, 2000; Moore et al., 2006; Ram, 2006; Shen & Williamson, 2001).
    [Show abstract] [Hide abstract] ABSTRACT: Drawing from various bodies of social scientific literature and research, the authors assess the extent to which infant and child mortality rates in less-developed countries are affected by the percent of domestic populations living in urban slum conditions. Results of first-difference panel model estimates of 80 less-developed countries from 1990 to 2005 indicate that growth in the percent of populations living in urban slum conditions positively affects both forms of mortality, and the effects are much more pronounced for African countries than for less-developed countries in Latin America and Asia. These findings hold, net of economic development, fertility rates, world-economic integration, and other factors. Cross-sectional analyses of infant and child mortality rates in 2005 that include additional controls provide further evidence of the mortality/urban slum relationships found in the panel model estimates. The authors conclude by highlighting the theoretical implications of the results and describe the next steps in this research agenda.
    Full-text · Article · Oct 2010
    • We found no significant association between trade and population health. This concurs with previous research (Mehrtens, 2004; Moore et al., 2006) in high-income countries. However, the lack of association between higher levels of free trade and improved population health among low-income countries contrasts with previous cross-sectional findings suggesting that trade and foreign direct investment may bring improvements in infrastructure, such as better roads and telecommunication networks, and other technology spillovers essential to the promotion of population health in poorer countries (Blomstrom and Kokko, 1997).
    [Show abstract] [Hide abstract] ABSTRACT: Although there has been substantial debate and research concerning the economic impact of neo-liberal practices, there is a paucity of research about the potential relation between neo-liberal economic practices and population health. We assessed the extent to which neo-liberal policies and practices are associated with population health at the national level. We collected data on 119 countries between 1980 and 2004. We measured neo-liberalism using the Fraser Institute's Economic Freedom of the World (EFW) Index, which gives an overall score as well as a score for each of five different aspects of neo-liberal economic practices: (1) size of government, (2) legal structure and security of property rights, (3) access to sound money, (4) freedom to exchange with foreigners and (5) regulation of credit, labor and business. Our measure of population health was under-five mortality. We controlled for potential mediators (income distribution, social capital and openness of political institutions) and confounders (female literacy, total population, rural population, fertility, gross domestic product per capita and time period). In longitudinal multivariable analyses, we found that the EFW index did not have an effect on child mortality but that two of its components: improved security of property rights and access to sound money were associated with lower under-five mortality (p = 0.017 and p = 0.024, respectively). When stratifying the countries by level of income, less regulation of credit, labor and business was associated with lower under-five mortality in high-income countries (p = 0.001). None of the EFW components were significantly associated with under-five mortality in low-income countries. This analysis suggests that the concept of 'neo-liberalism' is not a monolithic entity in its relation to health and that some 'neo-liberal' policies are consistent with improved population health. Further work is needed to corroborate or refute these findings.
    Full-text · Article · Oct 2009
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