Employmentweb_low

EMploYMEnt, work, And hEAlth inEquAlitiEs - a global perspective
In this book, various cross-cutting axes (i.e., social class, gender,
age, ethnicity/race, and migrant status) are employed as the key
relational mechanisms that explain why different types of
employment conditions are linked to multiple disease outcomes
through multiple risk-factor mechanisms (see Figure 1).
The definitions of the cross-cutting axes that follow are also the
product of an extensive review of specialised epidemiology and
public health journals, among other sources.
Figure 1. employment conditions and key cross-cutting axes used in this book.
social class
gender
age
ethnicity
migrant status
F u l l
t i M E p E r M A n E n t E M p l o Y M E n t
u n E M p l o Y M E n t
p r E C A r i o u s
i n F o r M A l
C h i l d
E M p l o Y M E n t
E M p l o Y M E n t
l A B o u r
s l A v E r Y A n d B o n d E d l A B o u r
source: prepared by the authors
"there are more slaves alive today than all
the people stolen from Africa in the time of
the transatlantic slave trade."
Kevin bales
Social Class. Most research on employment conditions and
population health does not include any analysis of social class, a
concept that is defined in terms of employment relations (Krieger,
Williams, & Moss, 1997). Nevertheless, social class positions
defined by employment relations (e.g., workers, managers,
employers, owners) are powerful determinants of population
health via exposure to proximal risk and protective factors such as
control over work, job demands, access to social and health
services, workplace hazards or income (Muntaner & Parsons, 1996;
Borrell, Muntaner, Benach, & Artazcoz, 2004). In social
epidemiology, the effects of social class have been shown to predict
health outcomes even when conventional "gradient" measures
such as education and occupation are taken into account (Muntaner
& Parsons, 1996; Wolhfarth, 1997; Wohlfarth & Van den Brink, 1998;
Muntaner, Eaton, Diala, Kessler, & Sorlie, 1998; Muntaner, Borrell,
Benach, Pasarín, & Fernández, 2003).
Yet, in spite of this promising evidence, most research uses only
traditional "gradient" indicators (education, occupation and income;
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