When we compare two populations and find a difference in a health outcome, we want to look more closely to determine if that outcome difference is due to a difference in health related characteristics or non-health related characteristics. When the difference is due to something other than health characteristics, the difference is considered a disparity.
Disparities are particularly disturbing because it means something about the health system or society is causing differences in health outcomes. Globally, disparities in maternal health have to do with the distribution of health care resources. Industrialized countries have higher rates of cesarean delivery and lower rates of maternal mortality than developing countries. Within countries, disparities may be related to access to care (who can and cannot gain entry to the health system), quality of care (being provided with appropriate and timely treatment), or acceptability of care (individuals are willing to use the treatment options available).
When studying differences in health outcomes, it is important to consider confounding variables. A confounding variable is a characteristic that was not measured, but it is related to both the stratifying variable and the outcome. If you don’t measure the confounding variable you may misunderstand the relationship between the independent and dependent variables.
For example, if you want to know if there are disparities in rate of cesarean surgery, you need to know what types of things increase the odds of cesarean delivery. This study is a nice example of controlling for variables when studying cesarean delivery.
The problem with controlling for confounding variables is that you need to measure the confounders, which means you need to understand enough about the subject to predict what factors may be related. In the studies on disparities in cesarean delivery we have several known factors we can control for. For example, in this New Zealand study, the researchers controlled for ethnicity, age, socio-economic status, height, body mass index, maternity carer, diabetes, hypertension, hemorrhage, induction and gestational age. Why? Because previous research has shown variations in body mass index, induction, gestational age, etc. are associated with variations in rates of trial of labor and vaginal birth after cesarean. As they expected, the ethnicity of the woman was associated with trial of labor and vaginal birth after cesarean. If you do not control for other factors, you might miss the underlying association between ethnicity and cesarean delivery.
Here is one more study about racial and ethic disparities and cesarean delivery. This one is particularly disturbing because it is measuring primary cesarean delivery — and we know one of the main drivers of the currently high cesarean rates in the United States is the primary cesarean rate. Disparities in primary cesarean mean minority women bear more risk for each subsequent pregnancy.
The Birth Worker Survey
The Birth Worker Survey doesn’t give us enough data to check for disparities – although it is telling that only one of the responses was from someone identifying as Hispanic and only one response was from an individual identifying as Black. These two women (yes, all respondents were female) each provided 3% of the US sample, even though they represented 13% and 16.9% of the population. I suspect this is an unfortunate reflection of the true lack of diversity in the natural birth world in the United States.
Why unfortunate? I say unfortunate because if my suspicion is true, the stories we tell ourselves about birth — the stories we use to represent what women are experiencing and what women want — are not representative of the full spectrum of experiences. Remember, disparities in care provided exist. And unfortunate because the solutions we suggest — hiring a doula, finding a different provider, eating only organic — are probably not representative of the solutions available to all women. Remember, cultural acceptability can be as big of a barrier as financial resources or accessibility of providers.
Disparities are real, but if we pay attention and include all women in our decision making and advocacy I believe we can begin to make a difference.
Next time we will start talking about the types of studies and why that matters.
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