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Women's status and child well-being: a state-level analysis
Karestan C Koenen1, Alisa Lincoln, Allison Appleton
1Harvard School of Public Health Boston, MA, USA. kkoenen@hsph.harvard.edu <kkoenen@hsph.harvard.edu>
Improving women's status in the United States is linked to better child well-being. Higher political, economic, and social status for women correlates with improved child health and reduced negative outcomes.
Area of Science:
- Sociology
- Public Health
- Women's Studies
Background:
- Child well-being is influenced by various societal factors.
- Understanding the impact of women's status on child outcomes is crucial for public health initiatives.
Purpose of the Study:
- To analyze the association between state-level women's status and child well-being across the 50 United States.
- To investigate specific indicators of women's status and their relationship with child health and developmental outcomes.
Main Methods:
- Ecologic analysis correlating state-level composite indices of women's status with child well-being indicators.
- Indices for women's status included political participation, economic autonomy, employment/earnings, and reproductive rights.
- Child well-being outcomes comprised low birthweight, infant mortality, teen mortality, high school dropout rates, and teen birth rates.
Main Results:
- Higher women's status across all indicators was significantly associated with better child well-being.
- Associations persisted after adjusting for income inequality and state racial composition.
- Specific findings include links between women's political participation and lower low birthweight/teen birth rates; employment/earnings and lower infant/teen birth rates; economic/social autonomy and better outcomes across all measures; reproductive rights and lower infant mortality.
Conclusions:
- Child well-being is demonstrably worse in states with lower political, economic, and social status for women.
- Women's status is a significant component of the social context influencing child well-being.
- Further multi-level analyses are recommended to explore these associations in greater depth.
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