ArticleHuman nature (Hawthorne, N.Y.)2016
The Reproductive Ecology of Industrial Societies, Part II : The Association between Wealth and Fertility.
Article in Human nature (Hawthorne, N.Y.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Socio-economic status is a social construct with heritable components and genetic consequences.Nature human behaviour · 2025Review
- Iranian single-child couples' perceptions and experiences regarding childbearing incentives.Reproductive health · 2024Article
- The interplay of race/ethnicity and education in fertility patterns.Population studies · 2022Article
- Article
- Disentangling wealth effects on fertility in 64 low- and middle-income countries.Evolutionary human sciences · 2020Article
- Sex Differences in the Association of Family and Personal Income and Wealth with Fertility in the United States.Human nature (Hawthorne, N.Y.) · 2019Article
- When Everyone Wins? Exploring Employee and Customer Preferences for No-Haggle Pricing.Frontiers in psychology · 2018Article
- Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.Evolution, medicine, and public health · 2017Article
- Ethnically Tibetan women in Nepal with low hemoglobin concentration have better reproductive outcomes.Evolution, medicine, and public health · 2017Article
- The Reproductive Ecology of Industrial Societies, Part I : Why Measuring Fertility Matters.Human nature (Hawthorne, N.Y.) · 2016Article
- Modernizing Evolutionary Anthropology : Introduction to the Special Issue.Human nature (Hawthorne, N.Y.) · 2016Article
- Understanding variation in human fertility: what can we learn from evolutionary demography?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016Review
- Wealth, fertility and adaptive behaviour in industrial populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016Review
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
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.
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