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Association Between County-Level Natality and Income in the US, 2000-2020
IMPORTANCE: It is generally accepted that birth rates are negatively associated with income. However, less is known about the nature and evolution of natality differences between high- and low-income counties and how these differences are associated with the recent decline in the birth rate overall...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857058/ https://www.ncbi.nlm.nih.gov/pubmed/36508209 http://dx.doi.org/10.1001/jamapediatrics.2022.4814 |
Sumario: | IMPORTANCE: It is generally accepted that birth rates are negatively associated with income. However, less is known about the nature and evolution of natality differences between high- and low-income counties and how these differences are associated with the recent decline in the birth rate overall in the US. OBJECTIVE: To quantify the association between county-level income and natality between 2000 and 2020 and explore how natality inequality is associated with recent nationwide natality declines. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included all births to US women aged 15 to 44 years among county-year–level observations with at least 100 women of the same age. EXPOSURES: County-level median household income rank. MAIN OUTCOMES AND MEASURES: Association between natality and income and between natality inequality and national natality trends. Income ventiles were used to rank counties from 1 to 20, with each ventile including 5% of the female population aged 15 to 44 years. A counterfactual simulation was used to estimate natality rates while holding natality inequality constant at its year 2000 value. RESULTS: A total of 86 679 356 births were aggregated to 65 554 county-year–level observations from 2000 to 2020. The analysis yielded 2 main results. First was the changing nature of inequality. Estimates of the natality income gradient, which reflect the association between county-level natality and county-level income, changed from −0.061 (95% CI, −0.200 to 0.078) in 2000 to −0.572 (95% CI, −0.678 to −0.466) in 2020, reflecting an increase in natality inequality. Intuitively, a negative gradient reflects that natality is lower in higher-income counties compared with lower-income counties. Second, the counterfactual simulation showed that there would have been an additional 3.5 million births (an increase of 4.1%) over the remainder of the study period had natality inequality remained constant at its year 2000 value. While this counterfactual is based on strong assumptions that are unlikely to hold in practice, it suggests that natality may have been higher during this period absent the rise in natality inequality. CONCLUSIONS AND RELEVANCE: The findings of this cross-sectional study suggest that natality inequality has increased in recent years and is likely associated with nationwide natality declines. The causes of this inequality remain to be explored in future work. |
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