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Hum Nat ; 35(1): 1-20, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38480584

ABSTRACT

Historical demographic research shows that the factors influencing mortality risk are labile across time and space. This is particularly true for datasets that span societal transitions. Here, we seek to understand how marriage, migration, and the local economy influenced mortality dynamics in a rapidly changing environment characterized by high in-migration and male-biased sex ratios. Mortality records were extracted from a compendium of historical vital records for the Baja California peninsula (Mexico). Our sample consists of 1,201 mortality records spanning AD 1835-1900. Findings from Cox proportional hazard models indicate that (1) marriage was associated with a protective effect for both sexes; (2) residing in a mining town was associated with higher mortality for men, but not women; (3) migration was associated with decreased mortality risk for women, but not men; and (4) the risk of mortality increased in the face of infectious disease, but decreased over time. Despite the early initiation of reproduction for women, marriage had a protective effect, likely because marriage linked women to resources. Although mining boomtowns were associated with elevated risk factors generally, only men experienced greater mortality risk, likely due to dangerous working conditions that women did not experience. Last, female, but not male, migrants experienced greater longevity, possibly because exposure to harsh labor conditions eroded the protective effect of selection bias for men. Together, these results shed light on an understudied historical population and broaden our understanding of demographic dynamics in preindustrial settings.


Subject(s)
Communicable Diseases , Marriage , Mining , Mortality , Humans , Male , Female , Mexico/ethnology , Mexico/epidemiology , History, 19th Century , Mortality/trends , Mortality/history , Communicable Diseases/mortality , History, 20th Century , Adult , Middle Aged , Sex Factors , Emigration and Immigration/statistics & numerical data
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