Examining Racial/Ethnic Disparities in Diabetes Diagnosis, Care Access, and Glycemic Control: Results from 10 years of NHANES data
Matthew Campos
Author
07/28/2021
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As public health experts examine the trajectory of chronic disease in the United States, health equity researchers continue to examine the disproportional impact chronic disease has on racialized minority communities. The current presentation explores racial/ethnic disparities in diabetes diagnosis and glycemic control as a function of routine care access using national public health data. Results from the study are used to inform the author's suggestions for future directions of health equity research.
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- [00:00:00.810]Hello, my name is Matthew Campos
- [00:00:02.760]and today I'll be presenting on "Examining Racial and Ethnic Disparities in
- [00:00:06.450]Diabetes Diagnosis, Care Access,
- [00:00:08.940]and Glycemic Control" analyzing results from 10 years of National Health and
- [00:00:13.260]Nutrition Examination Survey data.
- [00:00:17.160]Currently in the United States, racial/
- [00:00:19.560]ethnic minority populations have higher rates of diabetes compared with non-
- [00:00:23.670]Latinx whites.
- [00:00:25.230]Previous research suggests that some factors that account for these disparities
- [00:00:29.370]are that racial/
- [00:00:30.030]ethnic minority populations also tend to have lower access to routine care that
- [00:00:34.950]is critical for diagnosing and managing diabetes.
- [00:00:38.820]A similar trend is apparent with those with undiagnosed diabetes.
- [00:00:43.080]Those with undiagnosed diabetes are less likely to have access to and utilize
- [00:00:47.190]healthcare within the past year. However, it remains unclear in literature
- [00:00:52.050]if this is true at similar rates across race and ethnicity.
- [00:00:56.130]The current study aimed to fill this gap in literature,
- [00:00:59.010]clarifying the interaction between routine care access and race/
- [00:01:02.100]ethnicity on undiagnosed diabetes and glycemic control.
- [00:01:07.350]To examine these relationships
- [00:01:08.880]we came up with three main hypothesis to guide our research. First,
- [00:01:12.510]we hypothesized the non-Hispanic black, Mexican origin,
- [00:01:16.110]other Latinx, and Asian origin participants will exhibit higher rates of
- [00:01:20.070]poor and very poor glycemic control compared to non-Hispanic whites.
- [00:01:25.050]For our second hypothesis,
- [00:01:26.700]we noted that these same racialized minority groups would also exhibit higher
- [00:01:31.230]rates of undiagnosed diabetes compared to non Hispanic whites.
- [00:01:35.760]For our third hypothesis, we hypothesized that reporting access to routine care
- [00:01:40.680]will reduce the probability of having poor glycemic control and undiagnosed
- [00:01:45.330]diabetes across racial and ethnic groups.
- [00:01:49.260]We used the present flow chart to guide our analyses.
- [00:01:52.440]We were most interested in the interaction between race/ethnicity
- [00:01:55.770]and routine care access and how that affected the probability of having
- [00:02:00.270]undiagnosed diabetes and uncontrolled diabetes and how race ethnicity
- [00:02:04.920]magnified the within and between group differences in these two outcomes
- [00:02:13.400]We collected the sample from the National Health and Nutrition Examination
- [00:02:17.120]Survey compiling 10 years of data from 2007 to 2016.
- [00:02:22.670]Then we coded for participants with poor glycemic control HbA1c,
- [00:02:26.960]glycohemoglobin levels,
- [00:02:29.660]or best known as blood sugar levels above or equal to 8%.
- [00:02:34.100]Then we coded for participants with very poor glycemic control.
- [00:02:38.180]Those who had HbA1c levels above or equal to 9%.
- [00:02:42.440]This allowed us to make racial and ethnic comparisons of severity of diabetes.
- [00:02:47.660]Then we coded for participants with undiagnosed diabetes. To do that
- [00:02:51.980]we analyze lab results of those who had HbA1c levels above or equal to
- [00:02:56.450]6.5%, meeting the American Diabetes Association diagnostic
- [00:03:01.420]criteria for diabetes.
- [00:03:03.550]And those within that group who reported 'no' that they have not been diagnosed by
- [00:03:07.870]a medical professional or a doctor with diabetes.
- [00:03:11.080]This allowed us to create a variable of those with undiagnosed diabetes.
- [00:03:15.730]Then we use these three variables to create frequency distributions by race/
- [00:03:19.840]ethnicity
- [00:03:20.350]for diabetic outcomes and perform binary logistic regressions to assess the
- [00:03:24.760]interaction of routine care access and race/ethnicity on diabetic outcome.
- [00:03:31.440]For our results, when examining glycemic control,
- [00:03:34.380]we've found that our first hypothesis was supported. Mexican origin participants,
- [00:03:39.390]non-Hispanic blacks,
- [00:03:40.950]other Latinx and Asian origin participants all had significantly greater rates
- [00:03:45.600]of poor glycemic control and very poor glycemic control compared to non-
- [00:03:50.580]Hispanic whites. For poor glycemic control,
- [00:03:53.790]we saw the greatest magnitude of difference between those of Mexican origin and
- [00:03:57.540]non-Hispanic white. 4.9% of the total Mexican origin population
- [00:04:02.400]had poor glycemic control followed by 4.1% of non-Hispanic black,
- [00:04:06.930]3.8% of other Latinx,
- [00:04:08.970]and 2.6% of Asian origin participants having poor glycemic control. All
- [00:04:13.560]statistically significantly greater than those of non-Hispanic white backgrounds.
- [00:04:18.300]Similar results were exemplified with very poor glycemic control,
- [00:04:22.260]as a greatest magnitude of difference was between those of Mexican origin and
- [00:04:25.650]non Hispanic white followed by other Latinx, non-Hispanic
- [00:04:29.100]black and Asian origin.
- [00:04:32.550]Our
- [00:04:32.920]second hypothesis examining differences in undiagnosed diabetes was also
- [00:04:37.050]supported. Mexican origin participants, non-Hispanic blacks,
- [00:04:40.680]other Latinx and Asian origin participants all had statistically significantly
- [00:04:45.120]greater rates of undiagnosed diabetes compared to non-Hispanic whites. However,
- [00:04:49.950]in this analysis we've found that the greatest magnitude of difference was
- [00:04:53.070]between those of Asian origin and non-Hispanic white, with 3% of the
- [00:04:57.570]total Asian origin population
- [00:04:59.250]having undiagnosed diabetes followed by non-Hispanic black, other Latinx,
- [00:05:03.390]and Mexican origin. All racialized minority groups
- [00:05:06.510]having significantly greater values of undiagnosed diabetes than non-Hispanic
- [00:05:11.460]whites with a p-value of less than 0.001.
- [00:05:16.380]For our third hypothesis analyzing the interaction of routine care and race/
- [00:05:19.860]ethnicity on glycemic control.
- [00:05:22.140]We've found that our third hypothesis was largely not supported.
- [00:05:25.920]The effect of routine care access did differ across race/
- [00:05:29.310]ethnicity for each outcome. However, for poor glycemic control,
- [00:05:33.990]we've found that when reporting routine care access across race/ethnicity,
- [00:05:38.820]these participants were more had greater odds of having poor glycemic control
- [00:05:43.830]as noted with odds ratios above one. For very poor glycemic control,
- [00:05:48.810]we saw similar results for non- Hispanic white, non-Hispanic black,
- [00:05:52.050]Mexican origin, and other Latinx of having odds ratios above one denoting
- [00:05:56.250]greater odds of having very poor glycemic control. However,
- [00:05:59.960]for those of Asian origin,
- [00:06:01.580]we found the opposite supporting our hypothesis that those of Asian origin who
- [00:06:06.110]reported routine care access were less had lower probability of having
- [00:06:10.850]very poor glycemic control
- [00:06:13.990]For the second part of our third hypothesis,
- [00:06:16.690]the effect of routine care access did differ across race/ethnicity,
- [00:06:21.190]however,
- [00:06:22.030]Asian origin participants and Mexican origin participants who reported routine
- [00:06:26.410]care access had lower odds of undiagnosed diabetes as
- [00:06:30.940]denoted with odds ratios below one.
- [00:06:34.720]While non-Hispanic whites, non-Hispanic blacks, and those of other Latinx origin had
- [00:06:39.310]higher odds of undiagnosed diabetes.
- [00:06:42.790]All of these values were statistically significant with p less than 0.001.
- [00:06:48.850]To conclude we denoted that there are clear disparities that persist in the
- [00:06:52.570]diagnosis and severity of diabetes across racialized minority
- [00:06:56.980]groups. As public health progresses and emphasis should be placed on mobilizing
- [00:07:01.780]medicine and diagnostic testing to reduce disparities in the control of
- [00:07:06.340]diabetes as assessed with glycohemoglobin levels.
- [00:07:10.210]Future directions could further clarify the differences that we saw between
- [00:07:14.410]racial and ethnic groups in diagnosis and glycemic control,
- [00:07:18.250]analyzing variables, such as healthcare utilization, um,
- [00:07:22.330]patient/doctor communication, and quality of care. However,
- [00:07:26.590]the current study did clarify that care access may be less of a predictor of
- [00:07:30.760]better glycemic control,
- [00:07:31.960]as we thought would be the case in our hypothesis, and more accurately alluding
- [00:07:35.890]to that
- [00:07:36.400]those with more severe diabetes may potentially be more likely to interact with
- [00:07:41.320]the healthcare system to monitor their glycohemoglobin,
- [00:07:44.890]to monitor their glycohemoglobin levels and reduce the severity of their
- [00:07:48.910]diabetes.
- [00:07:51.280]I would like to thank the Minority Health Disparities Initiative and my mentor,
- [00:07:54.910]Dr. Trey Andrews for mentoring me this summer.
- [00:07:57.430]I look forward to answering any questions that you guys may have. Thank you.
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