El Salvador covers 21,041 kilometer dos (CIA 2016). It’s got an inhabitants of 6.1 million, one of who 29.8% slide below the federal impoverishment range (Business Lender 2014). It has a beneficial GDP away from $twenty five.dos million (Business Lender 2014), which is composed of 10.7% farming, twenty-five.5% community, and you may 63.8% characteristics (CIA 2016). Brand new try components when you look at the El Salvador was Ahuachapan (rural) and you will San Salvador (urban).
Measures and you may People
Ethical approval was received from the University of St Andrews Ethics Board. Participants were recruited through MTurk, and they provided consent online after being presented with the consent information. Participants rated the face images collected in Study 1, individually and in random order. Participants rated either the face images from Malaysia or the face images from Este Salvador. The faces from the rural and urban populations were intermixed and each face was masked with a black oval around the head to occlude clothes. The images were presented one sex at a time, and participants were instructed to rate how heavy they thought each man/woman was on a 10-point Likert scale (1 = very underpounds, 10 = very overweight). Each participant was paid $2 dollars through MTurk upon completion of the experiment. Twenty men (M age = years, SD = 5.36) and 20 women living in the United States (M age = years, SD = 9.70) successfully rated (i.e., responded “yes” to the question “Were you able to see and rate all images successfully?”) the faces from Malaysia on weight. Twenty men (M age = years, SD = ) and 19 women (M age = years, SD = 9.61) living in the United States successfully rated the faces from El Salvador on weight.
Malaysia
Adiposity preferences were calculated by taking the percentage of faces high on the selected trait across the 5 pairs of male faces and the 5 pairs of female faces. Independent samples t-tests revealed no significant effect of sex of participant on preferences (p > 0.882 for all analyses). Therefore, for all subsequent analyses, data from male and female participants were aggregated. One sample t-tests revealed that the selected faces were significantly different from chance in the urban sample (p < 0.022> 0.379 for all analyses). Age was not significantly different between the rural and urban samples (t = 1.34, p = 0.185, Cohen’s d = 0.31).
Independent samples t-tests revealed no significant effect of population (i.e., rural/urban) on weight Frau Costa Rican preferences in male faces (t 106 = ?0.75, p = 0.454, Cohen’s d = 0.15) but a significant effect of population on weight preferences in female faces (t 106 = 3.56, p < 0.01,>
Weight and level were higher among male participants from the urban area (M weight = lbs., SD = ; M height = in. SD = 1.96) than male participants from the rural area (M weight = lbs., SD = ; M height = in. SD = 7.15) but their BMIs did not differ significantly (t 41 = 0.238, p = 0.813, Cohen’s d = 0.07). Weight and height were higher among female participants from the urban area (M weight = lbs., SD = ; M height = in. SD = 3.25) than female participants from the rural area (M weight = lbs., SD = ; M height = in. SD = 5.85) but their BMIs did not differ significantly (t = 1.45, p = 0.157, Cohen’s d = 0.51).
El Salvador
Adiposity preferences were calculated as above. Since independent samples t-tests revealed no significant effect of sex of participant on preferences (p > 0.212 for all analyses), for all subsequent analyses, data from male and female participants were aggregated. One-sample t-tests revealed that the faces selected were significantly different from chance in both the rural and urban samples (p < 0.011>150 = 0.133, p = 0.895, Cohen’s d = 0.02).
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