| Literature DB >> 28860640 |
Piotr Sorokowski1, Agata Groyecka2, Maciej Karwowski2, Upma Manral3, Amit Kumar3, Agnieszka Niemczyk2, Michalina Marczak2, Michał Misiak2, Agnieszka Sorokowska2,4, Thomas Huanca5, Esther Conde5, Bogdan Wojciszke6, Bogusław Pawłowski7.
Abstract
The effect of free mate choice on the relative magnitude of fitness benefits has been examined among various species. The majority of the data show significant fitness benefits of mating with partners of an individual's own choice, highlighting elevated behavioral compatibility between partners with free mate choice. Similarities between humans and other species that benefit from free mate choice led us to hypothesize that it also confers reproductive benefits in Homo sapiens. To test this hypothesis, we conducted a study among three indigenous societies-the Tsimane', Yali, and Bhotiya-who employ natural birth control. In all three samples, we compared the marriages arranged by parents with the non-arranged ones in terms of number of offspring. Here, we show that there were no significant relationships between type of marriage and the total number of alive children and number of dead children among the three sampled groups. The presented study is the first to date to examine the fitness benefits of free mate choice in humans. In discussion we present limitations of our research and discuss the possibility of love having a beneficial influence in terms of the number of offspring.Entities:
Mesh:
Year: 2017 PMID: 28860640 PMCID: PMC5578983 DOI: 10.1038/s41598-017-10484-x
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Descriptive statistics for main variables used in the study.
| Total ( | Min | Max | M | SD |
|---|---|---|---|---|
| Children | 0 | 12 | 3.83 | 2.71 |
| Children-dead | 0 | 7 | 0.59 | 0.99 |
| Children-dead (log transformed) | 0 | 2.08 | 0.33 | 0.47 |
| Arranged (0 = no, 1 = yes) | 0 | 1 | 0.44 | 0.50 |
| Age | 15 | 80 | 34.89 | 13.55 |
| Wealth* | −1.43 | 4.89 | 0 | 1 |
|
| ||||
| Children | 0 | 5 | 2.31 | 1.25 |
| Children-dead | 0 | 2 | 0.25 | 0.56 |
| Children-dead (log transformed) | 0 | 1.1 | 0.16 | 0.33 |
| Arranged (0 = no, 1 = yes) | 0 | 1 | 0.60 | 0.50 |
| Age | 18 | 40 | 29.39 | 5.24 |
| Wealth | −0.70 | 4.37 | 0 | 1 |
|
| ||||
| Children | 0 | 12 | 4.64 | 3 |
| Children-dead | 0 | 3 | 0.56 | 0.84 |
| Children-dead (log transformed) | 0 | 1.39 | 0.33 | 0.46 |
| Arranged (0 = no, 1 = yes) | 0 | 1 | 0.39 | 0.49 |
| Age | 15 | 80 | 32.68 | 12.86 |
| Wealth | −1.43 | 4.89 | 0 | 1 |
|
| ||||
| Children | 0 | 12 | 3.33 | 2.29 |
| Children-dead | 0 | 7 | 0.80 | 1.30 |
| Children-dead (log transformed) | 0 | 2.08 | 0.42 | 0.53 |
| Arranged (0 = no, 1 = yes) | 0 | 1 | 0.44 | 0.50 |
| Age | 18 | 75 | 41.24 | 15.21 |
| Wealth | −1.08 | 4.24 | 0 | 1 |
*Wealth index was calculated for each population separately and standardized within each population.
A summary of moderated-regression analyses with free-choice-versus-arrangement marriage and control variables explaining the number of living children, and the number of dead children.
| Alive Children | Dead Children (log-transformed) | |||||
|---|---|---|---|---|---|---|
|
| 95% |
|
| 95% |
| |
| Constant | 2.19 (0.46) | 1.30–3.09 | <0.001 | 0.24 (0.09) | 0.05–0.43 | 0.01 |
| Arranged (0 = | 0.51 (0.59) | −0.65–1.66 | 0.39 | −0.001 (0.12) | −0.24–0.24 | 0.99 |
| Age | 1.08 (0.13) | 0.82–1.33 | <0.001 | 0.20 (0.03) | 0.15–0.25 | <0.001 |
| Wealth | 0.39 (0.12) | 0.15–0.63 | 0.0003 | 0.04 (0.03) | −0.02–0.08 | 0.17 |
| Tsimane’ | 2.03 (0.50) | 1.05–3.01 | <0.001 | 0.13 (0.10) | −0.08–0.33 | 0.23 |
| Yali | −0.49 (0.55) | −1.58 - 0.59 | 0.37 | 0.08 (0.11) | −0.14–0.31 | 0.46 |
| Arranged × Tsimane’ | −0.41 (0.68) | −1.74–0.92 | 0.54 | −0.01 (0.14) | −0.29–0.26 | 0.94 |
| Arranged × Yali | 0.23 (0.72) | −1.19–1.65 | 0.75 | 0.01 (0.07) | −0.28–0.31 | 0.92 |
| R2 | 0.33 | 0.21 | ||||
Note B = unstandardized regression coefficient. SE = standard error of B; CI = 95% confidence intervals; R2 – the percentage of dependent variable’s variance explained.
Figure 1The Summary of Bayesian Analyses Results. Panels A1, and B1 present prior’s and posterior’s distribution in Bayesian Analysis as well as provide the values of Bayes Factors: BF10: providing the relative evidence for alternative hypothesis and BF01: providing the relative evidence for null hypothesis. In the case of the number of living children (panel A1), and the number of dead children (panel B1) the probability that the null hypothesis is more plausible based on data at hand is several times higher than that the probability that the alternative hypothesis is true. Panels A2, and B2 present Bayes Factor Robustness Check analysis, showing how the effect changes depending on the Cauchy prior probability. In the case of the number living of children (panel A2), the number of dead children (panel B2) the evidence for the null hypothesis under the default prior (d = 0.707) is moderate. Bayes factor analyses were conducted in JASP statistical software[60].