| Literature DB >> 30100622 |
Evert Van de Vliert1, Christian Welzel2,3, Andrey Shcherbak3, Ronald Fischer4, Amy C Alexander5.
Abstract
The roots and routes of cultural evolution are still a mystery. Here, we aim to lift a corner of that veil by illuminating the deep origins of encultured freedoms, which evolved through centuries-long processes of learning to pursue and transmit values and practices oriented toward autonomous individual choice. Analyzing a multitude of data sources, we unravel for 108 Old World countries a sequence of cultural evolution reaching from (a) ancient climates suitable for dairy farming to (b) lactose tolerance at the eve of the colonial era to (c) resources that empowered people in the early industrial era to (d) encultured freedoms today. Historically, lactose tolerance peaks under two contrasting conditions: cold winters and cool summers with steady rain versus hot summers and warm winters with extensive dry periods (Study 1). However, only the cold/wet variant of these two conditions links lactose tolerance at the eve of the colonial era to empowering resources in early industrial times, and to encultured freedoms today (Study 2). We interpret these findings as a form of gene-culture coevolution within a novel thermo-hydraulic theory of freedoms.Entities:
Keywords: climato-economic; encultured freedoms; gene-culture coevolution; lactose tolerance; thermo-hydraulic theory
Year: 2018 PMID: 30100622 PMCID: PMC6056908 DOI: 10.1177/0022022118778336
Source DB: PubMed Journal: J Cross Cult Psychol ISSN: 0022-0221
Correlations Among Main Variables (108 Countries).
| Main variable | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| 1. Cold stress | |||||
| 2. Heat stress | −.68 | ||||
| 3. Steady rain | .67 | −.60 | |||
| 4. Lactose tolerance in 1500 | .41 | −.33 | .65 | ||
| 5. Empowering resources in 1800 | .51 | −.46 | .70 | .62 | |
| 6. Encultured freedoms in 2000 | .42 | −.46 | .62 | .66 | .70 |
p < .001 (two-sided tests).
Figure 1.The thermo-hydraulic theory of freedoms.
Note. The theory proposes that (a) thermo-hydraulic stress has historically shaped lactose tolerance in 1500 which, over subsequent centuries, (b) has first interacted with steady rain in shaping empowering resources in 1800, and (c) has then interacted with empowering resources in shaping encultured freedoms in 2000.
Rain-Mediated Effects of Cold Stress (CS) and Heat Stress (HS) on Lactose Tolerance in 1500 (108 Countries).
| Regression model | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Predictor[ |
|
|
|
|
|
| Cold stress (CS) | .051 | −.149 | −.132 | −.299 | −.672 |
| Heat stress (HS) | −.369 | −.089 | −.008 | −.064 | −.219 |
| CS × HS | −.469 | −.275 | −.164 | −.299 | −.298 |
| Steady rain[ | .647 | .658 | .538 | −.226 | |
| Arable land[ | .119 | ||||
| Nonzoonotic diseases[ | −.217 | ||||
| Zoonotic diseases | −.193 | ||||
| Latitude (LAT)[ | .862 | ||||
| Longitude (LON)[ | −.495 | ||||
| LAT × LON | −.361 | ||||
| Δ | .266 | .036 | .079 | .131 | |
| Total | .266 | .465 | .414 | .544 | .675 |
Predictors are standardized variables and products of standardized variables.
Bs shown are unstandardized regression coefficients. There is no problematic multicollinearity, neither in Models 1 to 3 (Variance inflation factors ≤ 3.073), nor in Models 4 and 5 (Variance inflation factors ≤ 8.841), and there are no outliers (Cook’s distances ≤ .164).
In a conservative reanalysis, we checked whether the interaction effect of thermo-hydraulic stress on lactose tolerance in 1500 results from a violation of the assumption of independent observations because 26 small and geographically adjacent countries, nested in seven climatic regions (source: Cline, 2007), have similar thermo-hydraulic circumstances and subsistence conditions. Regression weights were assigned on the basis of the number of countries in each region. Specifically, we assigned a weight of .143 to seven countries in Southeastern Europe (Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Macedonia, Serbia, and Slovenia), a weight of .250 to four countries in Scandinavia (Denmark, Finland, Norway, and Sweden), a weight of .250 to four countries in Central Europe (Austria, Czech Republic, Hungaria, and Switzerland), a weight .333 to three countries in Central Asia (Kyrgyzstan, Tajikistan, and Turkmenistan), a weight of .333 to three countries in West Africa (Guinea, Guinea-Bissau, and Liberia), a weight of .500 to two countries in Equatorial Africa (the Congo’s and Gabon), a weight of .500 to two countries in Southern Africa (Botswana and Namibia), and a weight of 1.000 to countries that are not problematically nested in a climatic region.
Cold deviations from 22°C (B = .308, p = .028), heat deviations from 22°C (B = −.434, p < .001), and their interaction (B = −.300, p = .009) are determinants of steady rain (R2 = .526). In addition, as reflected in Models 1 to 3, steady rain mediates the relationship between thermal stress and lactose tolerance (mediation effect = −.194; confidence intervals: lower limit = −.382, upper limit = −.066).
The percentage of available arable land is retrieved from Parker (1997).
The prevalence of nonzoonotic and zoonotic parasitic diseases is retrieved from Fincher and Thornhill (2012).
Midrange distance (in latitude degrees) from the geographic equator represents a set of rival predictors including geomagnetic field, daylength variation, and parasitic disease burden.
Midrange distance (in longitude degrees) from the Greenwich meridian (west is negative, east is positive) represents another set of rival predictors including electronic density, state antiquity, religion, and fertility pattern.
p < .05. **p < .01. ***p < .001 (two-sided tests).
Figure 2.Interactive effects of cold stress and heat stress on lactose tolerance in 1500.
Note. Represented are rain-mediated effects (R2 = .465) of higher cold stress and low heat stress (squares and solid upward slope for 81 Old World countries), supplemented with direct effects of higher cold stress and high heat stress (circles and broken downward slope for 27 Old World countries; the 81 to 27 split is chosen because other splits provide less telling illustrations of the regression equation)[1].
Effects of Steady Rain (SR) and Lactose Tolerance in 1500 (LT) on Empowering Resources in 1800, Taking Account of Thermal Stress (108 Countries).
| Regression model | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Predictor[ |
|
|
|
|
|
| Cold stress (CS) | .274 | .070 | .116 | .202 | .175 |
| Heat stress (HS) | −.295 | −.007 | .021 | .129 | .158 |
| CS × HS | −.136 | .063 | .149 | .213 | .209 |
| SR | .665 | .464 | .265 | .324 | |
| LT | .311 | .291 | .235 | ||
| SR × LT | .320 | .320 | |||
| Δ | .289 | .210 | .052 | .073 | |
| Total | .289 | .499 | .551 | .624 | .564 |
Predictors are standardized variables and products of standardized variables.
Bs shown are unstandardized regression coefficients. There is no multicollinearity (Variance inflation factors ≤ 3.646), and there are no outliers (Cook’s distances ≤ .224).
Conservative reanalysis (see note c in Table 2).
p < .05. **p < .01. ***p < .001. (two-sided tests).
Effects of Lactose Tolerance in 1500 (LT) and Empowering Resources in 1800 (ER) on Encultured Freedoms in 2000, Taking Account of Thermo-Hydraulic Stress (108 Countries).
| Regression model | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Predictor[ |
|
|
|
|
|
| Cold stress (CS) | −.192 | −.133 | −.179 | −.139 | −.142 |
| Heat stress (HS) | −.313 | −.278 | −.286 | −.236 | −.222 |
| CS × HS | −.227 | −.117 | −.176 | −.169 | −.131 |
| Steady rain | .457 | .200 | .019 | −.015 | .044 |
| LT | .397 | .275 | .235 | .198 | |
| ER | .481 | .310 | .310 | ||
| LT × ER | .163 | .126 | |||
| Δ | .428 | .104 | .085 | .026 | |
| Total | .428 | .532 | .617 | .643 | .580 |
Predictors are standardized variables and products of standardized variables.
Bs shown are unstandardized regression coefficients. There is no multicollinearity (Variance inflation factors ≤ 3.609), and there are no outliers (Cook’s distances ≤ .153).
Conservative reanalysis (see Note c in Table 2).
p < .05. **p < .01. ***p < .001. (two-sided tests).
Figure 3.Interactive effects of steady rain and lactose tolerance in 1500 on empowering resources in 1800.
Note. Represented are results while controlling for thermal stress (R2 = .624). Steady rain has no effect where lactose tolerance is low (circles and broken horizontal slope for 43 Old World countries; r = −.038, p = .809), but a strong effect where lactose tolerance is high (squares and solid upward slope for 65 Old World countries; r = .759, p < .001; the 43 to 65 split is chosen because other splits provide less telling illustrations of the regression equation)[1].
Figure 4.Interactive effects of lactose tolerance in 1500 and empowering resources in 1800 on encultured freedoms in 2000.
Note. Represented are results while controlling for thermo-hydraulic stress (R2 = .643). Lactose tolerance has no effect where empowering resources are few (circles and broken horizontal slope for 51 Old World countries; r = −.117, p = .413), but a strong effect where empowering resources are many (squares and solid upward slope for 57 Old World countries; r = .824, p < .001; the 51 to 57 split is chosen because other splits provide less telling illustrations of the regression equation)[1].
Relative Importance of Seven Predictors of Encultured Freedoms, Listed in the Order of Decreasing Importance.
| Predictor | Relative importance | ||
|---|---|---|---|
| First step[ | Last step[ |
| |
| 1. Empowering resources in 1800 (ER) | .22 | .32 | .27 |
| 2. Lactose tolerance in 1500 (LT) | .20 | .22 | .21 |
| 3. LT × ER | .20 | .18 | .19 |
| 4. Heat stress (HS) | .10 | .14 | .12 |
| 5. Steady rain | .18 | .00 | .09 |
| 6. Cold stress (CS) | .08 | .06 | .07 |
| 7. CS × HS | .02 | .08 | .05 |
Proportionate contribution if entered separately in the first step of the regression equation.
Proportionate contribution if entered separately in the last step of the regression equation.
Mean based on consistent rank orders in the first and in the last step (rs = .74, p = .06).
Effects of Lactose Tolerance in 1500 (LT) and Empowering Resources in 1800 (ER) on Encultured Freedoms in 2000 (Model 1) Compared With Competing Influences (Models 2 to 9).
| Regression model | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | Model 9 |
|---|---|---|---|---|---|---|---|---|---|
| Number of countries | 108 | 108 | 105 | 107 | 99 | 79 | 108 | 81 | 90 |
| Predictor[ |
|
|
|
|
|
|
|
|
|
| Cold stress (CS) | −.139 | −.010 | −.096 | .015 | −.113 | −.114 | −.164 | −.147 | −.050 |
| Heat stress (HS) | −.236 | −.216 | −.224 | −.228 | −.158 | −.323 | −.244 | −.160 | −.131 |
| CS × HS | −.169 | −.131 | −.100 | −.132 | −.172 | −.050 | −.173 | −.145 | −.163 |
| Steady rain | −.015 | −.018 | −.091 | −.009 | .040 | −.071 | −.017 | −.035 | −.065 |
| LT | .235 | .287 | .344 | .277 | .250 | .154 | .230 | .219 | .289 |
| ER | .310 | .338 | .317 | .348 | .219 | .275 | .297 | .319 | .335 |
| LT × ER | .163 | .154 | .141 | .142 | .143 | .175 | .159 | .178 | .168 |
| Nonzoonotic diseases[ | .150 | ||||||||
| Zoonotic diseases | .047 | ||||||||
| Language fractionalization[ | .209 | ||||||||
| Ethnic diversity | −.139 | ||||||||
| Religious heterogeneity | .117 | ||||||||
| Colonial past[ | .450 | ||||||||
| State antiquity[ | .015 | ||||||||
| Societal industrialization[ | .157 | ||||||||
| Urbanization[ | .002 | ||||||||
| Shadow economy[ | .001 | ||||||||
| Income inequality[ | .018 | ||||||||
| Δ | .643 | .015 | .046 | .023 | .015 | .019 | .002 | .000 | .027 |
| Total | .643 | .658 | .690 | .666 | .687 | .718 | .645 | .703 | .702 |
Predictors are standardized variables and products of standardized variables.
Bs shown are unstandardized regression coefficients. There is no multicollinearity (Variance inflation factors ≤ 5.750), and there are no outliers (Cook’s distances ≤ .273).
The contemporaneous prevalence of nonzoonotic and zoonotic diseases is retrieved from Fincher and Thornhill (2012).
Language fractionalization, ethnic diversity, and religious heterogeneity in the 1980s are retrieved from Alesina, DeVleeschauwer, Easterly, Kurlat, and Wacziarg (2003).
Colonial past (no = 0, yes = 1) is retrieved from National Geographic Society (1999).
According to Schwartz (2009), “The longer a viable state has existed in the territory that currently constitutes a country, the more opportunity there has been for . . . development of secondary institutions in the wider society (e.g., formal governments, schools, courts, hospitals, armies, large corporations)” (pp. 6-7). Adopting that insight, Putterman’s (2004) state antiquity index is used as a proxy for state antiquity.
Each country’s position on the historical continuum from agriculture to industrial and service employment is proxied by the national percentages of current employment in the agrarian sector (agriculture, fishing, and hunting), the industrial sector (manufacturing, mining, building, and public utilities), and the service sector (trade, transport, restaurants, hotels, finances, communications, and community and personal services) (sources: UNDP, 2004, 2007). The three employment percentages load on a single factor that accounts for 73% of the common variation and represents the extent to which each country is engaged in industrial and service activities.
The percentage of the total population living in urban areas, as defined by the country (source: Parker, 1997).
Informal “gray” or “underground” income through concealed economic activities to avoid taxes, social security contributions, obligatory regulations, etc., retrieved from the World Bank (Schneider, Buehn, & Montenegro, 2010).
The Gini index measures inequality over the entire distribution of income or consumption (source: UNDP, 2004).
p < .05. **p < .01. ***p < .001. (two-sided tests).