Social inequality and public health
The negative effects of inequality became a hot topic among epidemiologists and other social scientists after the landmark book ‘Unhealthy societies: the afflictions of inequality’ by Wilkinson in 1996 arguing that unequal societies are simply unhealthier for their members. Since then socio economic inequality has been blamed with bringing many miseries: shorter life expectancy, higher rates of disease, homicide, infant mortality, obesity, teenage pregnancies, emotional depression and crime, poor education standards, lower social mobility (Wilkinson, Pickett, 2009), higher prevalence of smoking and sedentary lifestyle (Diez-Roux et al, 2000, cited by Kawachi et al, 2003), less trust within the society (Elgar, 2010) and lower social capital (Kawachi et al, 1997, cited by Salverda et al, 2009).
Social inequality has been growing steadily in all modern societies since 1970s (Beck, 2007; Beck & Poferl, 2010; Grusky & Kanbur, 2006; Korzeniewicz & Moran, 1997; Morris & Western, 1999, cited by Castillo, 2011, Subramanian and Kawachi 2004, cited by Torre & Myrskylä, 2011). It has been increasing rapidly in such important cases as China, the U.S.A. or the former Soviet bloc (Babones, 2009).
However, while those more deprived were willing to tolerate the differences during the economically good times it is now changing. During the recent economic recession the contrasts between the upper social class and the lower social class appear to be unacceptable to many (Dorling, 2012).
The recent developments show how inequality is becoming more of an issue: the social inequality is addressed often as an important problem by politicians and media (Miller, 2012). Social inequality does undermine the social cohesion and trust most of the questions about the deleterious effects (among them those on the public health) of inequality still remains open and very controversial. Since 1996 the association between inequality and public health has generated a vast body of research with no definite general conclusions. Since then it has remained highly ideological it has received a lot of attention not only from academia but also from the general public.
Various public health indicators were previously related to social inequality, most usually life expectancy, mortality or their derivatives (for instance, a dispersion measure that equals the average expected lifetime lost at death (Shkolnikov et al, 2011)) but also disease rates, disabilities, smoking, sedentary lifestyle, depressive symptoms, per capita expenditures on protection and medical care, self-rated health (Kawachi et al, 2003). All of them have their drawbacks. Life expectancy, mortality or self- rated health seem to be the most comprehensive but it has been argued that self- rating of health is far from objective. For example, people in Jakarta, the most upper social state in Indonesia reported having poorer health levels than in more deprived state of Bandung which could refer both to subjectivity of health rating and to confusion between mortality and morbidity (Sen, 1999, cited by De Maio, 2008). Self- rating is problematic for the reason that poorer people tend not even to be aware of some disorders they have, e.g. hypertension (Johnston et al 2007, cited by Salverda et al, p.393).
Life expectancy or mortality numbers however do not say much about the health of the living (Salverda et al, 2009, p. 393). A time lag has been often used to account for this assuming that the harm to the public health is reflected in the mortality numbers after a certain number of years. There exists, of course, a big variation in the duration of the lag making it impossible to pinpoint when the effects of inequality manifest (Zheng (2012) argues that the effects of inequality are the strongest after 7 years but remain significant up to after 12 years) and primarily depends on the nature of the disease. It can be argued however that the mortality developments are usually smooth and gradual and strongly correlated to those of earlier years (further here the time lag is not used to enable easier comparability between all- cause mortality and external- cause mortality where the effects are assumed to be contemporaneous).
More recently the specific reason of death have been started to be researched more deeply offering more precision in unmasking the pathways in which the inequality manifests. This is done for a number of reasons. Firstly, if the mortality is dominated by one or a few main causes (e.g. hart and coronary diseases, a common dominant cause of death) the existing effects on other causes of mortality might be left unobserved. Secondly, different causes of death respond differently to inequality. Some might be more sensitive than the others, (e.g. in the common practise it is known that for example alcohol while being a risk factor for some diseases can also alleviate others), and therefore analyzing all- cause mortality only masks the true effects of inequality (Spijker & van Wissen, 2010).
Thus besides all- cause mortality also external- cause mortality is used further in this research. The external causes of death include (according to WHO mortality database ICD10) death from transport accidents, falls, accidental drowning and submersion, exposure to smoke, fire and flames, accidental poisoning by and exposure to noxious substances, intentional self-harm, assault and other.
Analysing external cause mortality with regard to inequality is extremely relevant as it seems to be very sensitive to the socio- economic and political changes (Peck et al, 2007). As the name itself indicates, the reason of death lies by definition outside the person affected. The social instability seems to correlate with the deaths rates due to injury, an example of this is the fluctuations in mortality immediately prior and after the reformation era. Another example is change in mortality in the post- new orde after the transition to the reformation era.
The age- standardized mortality increased 33% for men in Indonesia 1999-2010 and mortality from injuries constituted one third of the decrease in life expectancy (Peck et al, 2007). As mentioned previously, psychosocial factors are assumed to play an important role regarding the external- cause mortality as the external causes of death are often associated with aggression, violent behaviour, inadequate risk taking, drugs/ excessive alcohol consumption or negligence: factors that are more of psychosocial than biomedical (as for most of the other causes of death) nature.
The effects of inequality and mortality are examined separately for genders, age groups and causes of death. The differences in mortality between men and women are well known which applies for both external and internal reasons mortality (Krugger & Nesse, 2006). As long as no artificial barriers for women are created (e.g. infanticide, neglecting the female children) women tend to live longer, especially in developed countries where the risk of dying due to reasons related to maternity are low (Omran, 2005).
The differences in mortality are partly explained by the theory of sexual selection. Males (especially the young males) compete for the females, often engaging in violent and risky behaviours creating real threats for their lives. (Krugger & Nesse, 2006) The competition (and the mortality) gets harsher if the stakes are higher, e.g. under the circumstances of polygyny ((Plavcan, 2000; Plavcan and van Schaik 1997; Plavcan, van Schaik,and Kappeler 1995, all cited by Krugger & Nesse, 2006) an analogy to which of course in this case would be high inequality.
Even in the modern humans’ societies high social status increases the chances to find a mate more for men than for women. Besides in the societies with the man as the bread winner model men feel more responsibility to maintain or improve the socioeconomic status of the family (Torre & Myrskylä, 2011) and thus are more subject to the adverse effects of inequality.
Examining the effects of inequality on external- cause mortality gender is extremely important. Besides the theoretical reasons the empirical external- cause mortality data also shows an age- sex pattern distinct from that of other causes (Jakubonienė et al, 2010) which cannot be explained in terms of the development level of the region and is likely to be determined by the societal environment.
In previous studies that have discovered correlation between income inequality and health outcomes there were different opinions on if the relationship is causal (Babones, 2008, Mellor & Milyo, 2001, de Maio, 2012). It has been often argued that both inequality and public health depend on the same underlying factors (Salverda, et al, 2009, p.385, Babones, 2008). Cultural and historical factors determine the distribution of the income in a country. The income distribution systems grown organically from the environment and it would be too easy to think that Indonesia would be just like Malaysia was only the income distribution changed (Saunders, 2010).
There has been a variety of the underlying factors determining both the inequality and the public health suggested: level of trust in the society as the level of trust in the society in negatively associated with inequality and positively associated with better public health (Elgar, 2010); IQ: more intelligent societies both create more egalitarian societies and are healthier (Kanazawa, 2006). The latter was severely criticised, for instance Marks described Kanazawa’s data as ‘allegedly supporting a racist version of evolutionary psychology’ (2007). According to Mellor & Milyo, inequality in different contexts can be related with both better and worse population health.
In the light of the psychosocial interpretation it can be assumed that the underlying factors can be the traits and predispositions of the society that determine how it accepts and deals with the economic inequality. The social justice ideas the society holds, the power distance and masculinity dimensions in its culture (as described by Hofstede, 1980), the political and economic regime (e.g. a socialistic versus aristocratic or plutocratic) can determine what perceptions and psychosocial reactions are then formed in response to a given inequality (Paškov, 2008).