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10.1007/s12110-016-9272-9

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suck abstract from ncbi


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pmid27670437
      Hum+Nat 2016 ; 27 (4 ): 445-470
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  • The Reproductive Ecology of Industrial Societies, Part II : The Association between Wealth and Fertility #MMPMID27670437
  • Stulp G ; Sear R ; Schaffnit SB ; Mills MC ; Barrett L
  • Hum Nat 2016[Dec]; 27 (4 ): 445-470 PMID27670437 show ga
  • Studies of the association between wealth and fertility in industrial populations have a rich history in the evolutionary literature, and they have been used to argue both for and against a behavioral ecological approach to explaining human variability. We consider that there are strong arguments in favor of measuring fertility (and proxies thereof) in industrial populations, not least because of the wide availability of large-scale secondary databases. Such data sources bring challenges as well as advantages, however. The purpose of this article is to illustrate these by examining the association between wealth and reproductive success in the United States, using the National Longitudinal Study of Youth 1979. We conduct a broad-based exploratory analysis of the relationship between wealth and fertility, employing both cross-sectional and longitudinal approaches, and multiple measures of both wealth (income and net worth) and fertility (lifetime reproductive success and transitions to first, second and third births). We highlight the kinds of decisions that have to be made regarding sample selection, along with the selection and construction of explanatory variables and control measures. Based on our analyses, we find a positive effect of both income and net worth on fertility for men, which is more pronounced for white men and for transitions to first and second births. Income tends to have a negative effect on fertility for women, while net worth is more likely to positively predict fertility. Different reproductive strategies among different groups within the same population highlight the complexity of the reproductive ecology of industrial societies. These results differ in a number of respects from other analyses using the same database. We suggest this reflects the impossibility of producing a definitive analysis, rather than a failure to identify the "correct" analytical strategy. Finally, we discuss how these findings inform us about (mal)adaptive decision-making.
  • |*Birth Rate/ethnology [MESH]
  • |Adult [MESH]
  • |Cross-Sectional Studies [MESH]
  • |Developed Countries/*statistics & numerical data [MESH]
  • |Female [MESH]
  • |Humans [MESH]
  • |Income/*statistics & numerical data [MESH]
  • |Longitudinal Studies [MESH]
  • |Male [MESH]
  • |Reproductive Behavior/ethnology/*statistics & numerical data [MESH]


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