Health Disparities and Infertility: Impacts of State Level Mandates

Williams College, Williamstown, New Jersey, United States
Fertility and sterility (Impact Factor: 4.59). 05/2006; 85(4):858-65. DOI: 10.1016/j.fertnstert.2005.11.038
Source: PubMed


To determine whether important racial, ethnic, or socioeconomic status (SES) health disparities exist in infertility, impaired fecundity, or infertility treatment.
Four waves of the National Survey of Family Growth (NSFG) were pooled. Measures were compared across various race/ethnicity, education, and age groups.
Data for 31,047 women 15-44 years old from the NSFG were pooled.
Outcomes were compared by whether the women's states of residence had a mandate in place (at least 1 year before the interview) to compel insurers to cover or offer to cover infertility treatment.
Infertility status, impaired fecundity, ever having sought infertility treatment.
Infertility is more common for non-Hispanic black women, non-Hispanic other race women, and Hispanic women than for non-Hispanic white women, and both infertility and impaired fecundity are more common for high school dropouts and high school graduates with no college than for 4-year college graduates, and for older women compared with women 29 and younger. Older women, non-Hispanic white women, and women who are more educated (with at least some college) are more likely to have ever received treatment. No evidence has been found that the racial, ethnic, or education disparities are ameliorated by the health insurance mandates.
Racial, ethnic, and educational disparities exist in infertility status and treatment, and educational disparities in impaired fecundity. More study of the impact of infertility treatment mandates on these disparities is needed.

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    • "Therefore we might expect to see differences in employment outcomes based on education level. It appears that women with the lowest amounts of education, those who are not high school graduates, are unlikely to be affected by the mandates (Bitler & Schmidt, 2006). Among the universe of those without a high school degree, the treated population works a statistically insignificant 0.464 fewer weeks per year (se(0.644)). "
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    ABSTRACT: This paper examines the labor market effects of state health insurance mandates that increase the cost of employing a demographically identifiable group. State mandates requiring that health insurance plans cover infertility treatment raise the relative cost of insuring older women of child-bearing age. Empirically, wages in this group are unaffected, but their total labor input decreases. Workers do not value infertility mandates at cost, and so will not take wage cuts in exchange, leading employers to decrease their demand for this affected and identifiable group. Differences in the empirical effects of mandates found in the literature are explained by a model including variations in the elasticity of demand, moral hazard, ability to identify a group, and adverse selection.
    Journal of Policy Analysis and Management 12/2012; 31(1):63-92. DOI:10.2139/ssrn.1880596 · 0.93 Impact Factor
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    • "Thus, the cost barriers to ART services significantly affect lower to middle-income women who are disproportionally non-White. Yet, even when insurance coverage is mandated, racial and ethnic disparities in utilization remain unchanged (Bitler & Schmidt, 2006; Jain & Hornstein, 2005). "
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    ABSTRACT: There is a significant increase in the use of assisted reproductive technology to treat infertility, yet access to services is not equal for all women in the United States. Some marginalized groups face significant barriers accessing assisted reproductive technology. The authors review obstacles preventing marginalized populations from procreating, based on class, race and ethnicity, age, marital status, sexual orientation, and disability. The sociopolitical climate in the United States that maintains these obstacles is evaluated by the authors in this article. Finally, suggestions are provided for structural changes to decrease disparities in access to assisted reproductive technology and recommendations for family therapists working with clients who are unable to access assisted reproductive technology.
    Journal of Feminist Family Therapy 07/2012; 24(3):197-212. DOI:10.1080/08952833.2012.648139
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    • "We include as predisposing conditions only social location variables associated with health services utilization for infertility in prior research. Although infertility is more common among Black and Hispanic women than among White women (Bitler and Schmidt 2006), Black and Hispanic woman are less likely to receive treatment (Greil et al. 2011c; Stephen and Chandra 2000). Older women are more likely to seek and receive treatment for infertility (Greil et al. 2011c), probably in part because fertility options change with age and in part because older women feel that their " biological clocks " are running out. "
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    ABSTRACT: Infertility is a discretionary health condition; although it carries with it important life course implications, treatment is rarely necessary for health reasons. Sociological theories of medical help-seeking emphasize demographic factors, perceived need, and enabling conditions in health services utilization, but we find that social cues are also strongly associated with health services utilization for infertility. Adjusted for conventional predictors of medical help-seeking, several social cue indicators have significant associations with utilization, including having friends and family with children, perceiving infertility stigma, and having a partner and/or family member who encourages treatment. Perceived need accounts for the largest portion of the variation in utilization. Enabling conditions explain less of the variance than social cues. Social cues should be especially important for discretionary health services utilization. Studies of service utilization for discretionary health conditions should explicitly incorporate a range of measures of social cues into their models.
    Sociological Inquiry 01/2012; 83(2). DOI:10.1111/soin.12000 · 0.79 Impact Factor
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