4.4. Parasite-Stress
4.4.1. Cross-national: Infectious Disease DALY. We used the World Health
Organization (WHO) variable Infectious Disease DALY, a cross-national measure of
morbidity and mortality (Disability Adjusted Life Years; DALY) attributed to 28
different “infectious and parasitic diseases” for the year 2002 (e.g., tuberculosis, measles,
leprosy, dengue; WHO 2004). The DALY measure combines the time lived with
disability and the time lost due to premature mortality. One Infectious Disease DALY is
equivalent to one lost year of healthy life with the burden of infectious disease as a
measurement of the gap between current health status and an ideal situation where
everyone lives into old age free of disease and disability (ES 1.G).
4.4.2. Cross-national: Nonzoonotic vs. Zoonotic Parasite Prevalence. An important
element of the parasite-stress theory of sociality is the costs associated with acquiring
diseases from out-group humans. Thus infectious diseases that are transmissible between
humans are predicted to be more important for assortative sociality than human infectious
diseases that are not transmitted between humans (Thornhill et al. 2010). Human-to-
human transmitted infectious diseases are of two types, referred to as human-specific and
multihost diseases. Human-specific diseases are ones that humans are only able to
acquire from other humans (e.g., measles, cholera, hookworm) and multi-host diseases
are those that humans contract from other humans but multi-host diseases can use human
or other animals as hosts to carry out their reproductive life (e.g., leishmaniasis, leprosy,
dengue fever). These two types of infectious diseases contrast with zoonotic diseases
(e.g., lyme disease, rabies, tularemia) that humans are only able to acquire from species
other than humans (livestock and wildlife). Using, basically, Smith et al.'s (2007)
classification of these disease types, we determined the prevalence (number of cases) of
human-specific and multi-host infectious diseases per country (called ‘nonzoonotic’) and
of zoonotic diseases based on data from the GIDEON database (Global Infectious
Disease & Epidemiology Network; www.gideononline.com). The earlier cross-national
study of cultural variation by Thornhill et al. (2010) used a different measure of these
diseases: the number of diseases of each type, not the prevalence (Thornhill et al. 2010).
Prevalence measures are likely better assays of the impact of parasitic diseases than the
number of such diseases (Dunn et al. 2010). Nonzoonotic Parasite Prevalence was
correlated positively with Zoonotic Parasite Prevalence (r = .61, n = 226, p < .0001).
Nonzoonotic Parasite Prevalence was correlated positively with Infectious Disease
DALY (r = .76, n = 192, p < .0001) as was Zoonotic Parasite Prevalence (r = .16, n =
192, p = .03). See ES 1.H for further details on the construction of this measure.
Electronic Supplement 4 contains the list of infectious diseases and their classification.
Electronic Supplement 2 contains the national values for the nonzoonotic and zoonotic
parasite prevalence variables.
4.4.3. Cross-national: Combined Parasite-Stress. Because there is overlap and
covariation in our infectious disease measures we standardized Infectious Disease DALY,
and Nonzoonotic Parasite Prevalence, and then summed these scores for each country to
become Combined Parasite-Stress (Cronbach’s α = .76, n = 192). Zoonotic Parasite
Prevalence was not included because of its minimal relationship with the dependent
variables (see section 5.1.1.). Combined Parasite-Stress was the focal variable used in the
cross-national multivariate analyses (see section 4.5.1.). These scores are in ES 2.
4.4.4. United States: Parasite-Stress USA. We obtained the annual Morbidity and
Mortality Weekly Report’s “Summary of Notifiable Diseases, United States” from the
Centers for Disease Control for the years 1993 to 2007 (available at www.cdc.gov). For
each year we adjusted the number of cases of all infectious diseases tracked by CDC for
which there was information for all states for that year by the CDC-reported population
size for each state (i.e., for some diseases, not all states reported whether cases occurred
; these diseases were not included in the tally). For each
state, we determined the average z-score of this population-adjusted disease incidence
score for the 15-year time-span. This approach was necessary because the infectious
diseases tracked by the CDC can vary between years, though there was often great
similarity between years. The standardization allowed us to pinpoint a state’s position
along a parasite gradient relative to the other states. See ES 1.I for validation of this
index. Electronic Supplement 5 contains the list of diseases included in our index for each
year and the data are in ES 3.
They go on to caution that there may be other features besides parasite-stress (e.g., economic development) that have been proposed as explanations of strength of family ties and religiosity, but they found zero-order correlations between the potentially confounding factors, detailed in full later on in the paper.
A fascinating read, really.