T-tests for continuous variables and chi-square tests for categorical variables were used for the comparisons of the rates of preeclampsia and diabetes, and the socio-demographic variables between the matched and the unmatched groups within each specific dataset. Further, for the matched birth records, we compared the influence of socioeconomic factors i.
The Memorial data contained only the lumped variable of diabetes gestational diabetes and pre-existing during pregnancy. Prior to , gestational and pre-existing diabetes were grouped into a single variable in the birth certificate data. After , gestational diabetes and pre-existing diabetes were reported separately. Therefore, we analyzed diabetes over — and conducted sensitivity analysis using — data as well. Given the potential for underreporting of adverse pregnancy outcomes on birth certificates, we did not specifically examine the agreement of the two databases using parameters such as sensitivity, specificity or Kappas.
Rather, we focused on determining if underreporting of diabetes and preeclampsia would disproportionately affect low socioeconomic status groups when level of maternal education, type of health insurance, and race were used as socioeconomic indicators. In order to explore this, we calculated the ratio of incidences of diabetes both preexisting and gestational and preeclampsia using birth certificate data compared to Memorial data.
A permutation based statistical test was used to check whether the incidence of preeclampsia and diabetes was significantly underreported on birth certificate data when compared to Memorial data. The socioeconomic variables used for the comparison were those based on birth certificate data, which have been shown to provide reliable information on these variables [ 32 — 34 ].
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Maternal education level was categorized as either high school or lower, or college or higher. Maternal race was categorized as Asian, Black, Hispanic, Non-Hispanic White, or Other, and insurance type was defined as either public or private. After removing multiple births e. After excluding these records, a total of 62, records Since the majority of records were matched by exact names, this only slightly changed the number of the final matched records data not shown.
Hence, we only reported the results based on the matching criteria listed above. The majority of women were between the ages of 30 and 39, had private health insurance, and had college or higher levels of education than did high school or lower maternal education was only available on the birth certificate data. Hispanic and Non-Hispanic White made up the two largest categories in both the Memorial and the birth certificate data and in the unmatched and matched records in each dataset.
Nevertheless, the pattern of difference in the unmatched vs. In this table, we calculated the statistic summaries based on the values reported in each specific database. It was found that the birth certificate data significantly underreported the incidence of preeclampsia when compared to the Memorial data 1. The underreporting in birth certificate data was also observed in subcategories of the socioeconomic variables we examined.
Of the mothers with known education level, the birth certificate data showed that the incidence of preeclampsia was significantly higher among mothers with education levels of college or higher compared with mothers with education levels of high school or lower 1. No difference was observed in the Memorial data.
Both the Memorial and birth certificate data indicated the highest rate of preeclampsia in Black women 4. The same held true for the birth certificate data. The Memorial data indicated a marginally significantly lower rate of preeclampsia in women with private insurance compared to those with public insurance 3. A different but insignificant pattern was observed in the birth certificate data.
Similar to preeclampsia, the birth certificate data significantly underreported the incidence of diabetes when compared to the Memorial data 1. Memorial data indicated that the incidence rate of diabetes during pregnancy was higher among women with lower socioeconomic status, but the pattern was insignificant in the birth certificate data. Sensitivity analysis showed similar results based on data in the — period results not shown.
No significant patterns were observed in birth certificate data.
However, of the women whose educational level was known, the Memorial data indicated that the incidence of diabetes was significantly higher among women with levels of education of high school or lower compared to college or higher 6. The birth certificate data showed a similar but insignificant pattern. The birth certificate data found that the incidence of diabetes was highest among Asian women 2. Memorial data found that the incidence of diabetes was significantly higher among women with public health insurance compared to women with private health insurance 6.
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We found that the birth certificate data that was analyzed significantly underreported the incidences of preeclampsia and diabetes compared to the Memorial data, which was collected specifically for research purposes. In addition, the degree of underreporting was disproportionately distributed across groups of different socioeconomic status, with certain socioeconomic indicators exhibiting higher degrees of underreporting. The degree of underreporting of both preeclampsia and diabetes using birth certificate data was significantly higher women with lower education levels compared to women with higher levels of education, in Hispanic women compared to non-Hispanic White women, in women with public insurance compared to those with private insurance.
These results indicate a disparate underreporting problem in low socioeconomic groups for pregnancy complications when race, level of education, and insurance status are used as socioeconomic indicators. Several reasons may exist to explain the discrepancies between our two datasets, such as the weaknesses of birth certificate data discovered by several other studies. These include inadequate auditing of birth certificate data by individual hospitals, variations in data collection, diagnosis, and reporting procedures across hospitals, the use of nonclinical or untrained personnel to record data, and budgetary restrictions that prevent state agencies from thoroughly assessing and ensuring the quality of birth certificate data [ 8 , 10 , 35 — 38 ].
The Memorial data, in turn, may have had better quality on pregnancy complications because it was a research database that underwent more stringent quality checks by nurses. Although the Memorial database is not a gold standard, it is believed that it is more accurate than birth certificate data because information is recorded when patients are physically present and able to verify records.
We attempted to maximally match the Memorial and birth certificate records. However, there were still 8. We found differences in the matched and unmatched groups in the rates of preeclampsia and diabetes and in socio-demographic parameters.
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But since the patterns of difference in the matched and the unmatched groups was consistent between the Memorial data and the birth certificate data, we do not expect it to change our main conclusion of the underreporting problem in the birth certificate data. Since the Memorial data did not differentiate between gestational diabetes and diabetes when reporting pregnancy outcomes, it was not possible to investigate gestational diabetes specifically in this study.
However, because the birth certificate data began reporting gestational diabetes separately starting in , we were able to perform two separate analyses on diabetes using — and — as periods of interest. Both periods showed the same patterns of underreporting of diabetes, and we thus suspect that our findings on total diabetes likely hold for gestational diabetes as well. This high degree of overlap between gestational diabetes and diabetes during pregnancy further suggests that the findings of this study regarding diabetes in general may also be applicable to cases of gestational diabetes in particular.
These results are consistent with previous studies, particularly those that determined that birth certificates are not reliable sources of information regarding preeclampsia, gestational diabetes, and other maternal complications and characteristics, particularly when compared to hospital discharge records [ 7 — 11 ]. Thus, our conclusion that the birth certificate database used in this study underreported the incidence of preeclampsia and gestational diabetes is supported by similar patterns found elsewhere in the United States.
However, to our knowledge this is the first study to assess the reliability of hospital data and birth certificates in southern California, and the first to address differential reporting of preeclampsia and diabetes during pregnancy by socioeconomic status in the United States. The socioeconomic differences seen in the underreporting of preeclampsia and gestational diabetes as specific outcomes of interest is a unique observation that has not been studied in southern California.
However, similar results have been found by studies that have analyzed related, though not identical, variables elsewhere in the United States. The authors of this study hypothesized that this observation might be explained by disparities in access to healthcare, as well as variations in personnel and birth certificate completion procedures across hospitals. Although our study did not analyze birth defects, the underreporting of adverse pregnancy outcomes we found according to racial and education level factors followed a similar pattern and can be explained by the same observations.
Further research must be performed to elucidate an explanation for the poor reliability of this particular set of birth certificate data for pregnancy complications, as well as the observed socioeconomic gradient in underreporting of such outcomes. Nevertheless, these findings have important implications for future public health research. Studies that rely solely on birth certificate data to draw conclusions regarding pregnancy complications should be aware of a potential bias towards underestimating the incidence of these conditions, particularly in low socioeconomic groups.
This is critical for the descriptive study of socioeconomic disparities in pregnancy complications, and might contribute to explain why discrepant results were reported in the past [ 17 — 28 ], beside any true difference in disparities across study settings. Such biases are also critical for etiologic research studying the relationships between pregnancy complications and potential risk factors, especially when these are unevenly distributed according to socioeconomic status.
For instance, exposure to most air pollutants e. In such a situation, a higher underreporting of maternal complications in populations with lower socioeconomic status would create a downward bias while measuring the association between air pollution and pregnancy complications. Consequently, researchers should attempt to use high quality health outcome data such as the Memorial database, either in place of or in conjunction with birth certificate data, whenever possible in order to minimize bias.
Furthermore, these findings indicate that there is a considerable need to improve the quality of birth certificate data in California, as far as pregnancy complications are concerned. There is a possibility that the quality of birth certificate has improved since , the last year of this analysis. It would be beneficial to assess the quality of current birth certificate data in order to identify areas that still require improvement.
However, historical birth certificate data are still of high importance for research studies that examine the impact of in-utero exposure on various long-term health effects e. Standardizing data collection and reporting procedures across hospitals would help minimize the discrepancies seen between birth certificate data and hospital databases such as the Memorial database. Because diabetes and preeclampsia are conditions that are oftentimes diagnosed prior to delivery and not at the hospital of delivery, there is also a need to improve the integration of prior medical records from other sources with hospital and birth certificate records.
What is more, the fact that the birth certificate data underreported both preeclampsia and diabetes and did so to a higher degree among groups of lower socioeconomic status suggests that it would be most effective to focus standardization efforts on these particular conditions and among these identified groups, including Black and Hispanic women, women with lower levels of education, and women with public insurance.
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Finally, the most disadvantaged women may not have access to health care; thus improving health care access for low-income and minority people may also improve the reporting of pregnancy complications. In summary, this comparison of two birth record databases found that the Memorial database is a more reliable source of information than birth certificate data for analyzing the incidence of preeclampsia and gestational diabetes among women in Los Angeles County. This is especially true for subpopulations of lower socioeconomic status.
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Efforts to improve the available sources of data for the study of adverse pregnancy outcomes should thus focus on improving the reliability of birth certificate data, particularly for women of lower socioeconomic status. Centinela Hospital does not provide copies of birth certificates. These must be requested in-person or via their website. Listed below are the locations to request copies of a birth certificate:. Branch offices accept requests for birth records and issue birth record copies from to the present.
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