The Memorial Care database is a more reliable source of information than birth certificate data for analyzing the incidence of preeclampsia and diabetes among women in Los Angeles and Orange Counties, especially for subpopulations of lower socioeconomic status.
Adverse pregnancy outcomes such as gestational diabetes mellitus and preeclampsia have important consequences on the growth, development, and health of children and mothers alike. Gestational diabetes mellitus is defined as carbohydrate intolerance with onset or recognition during pregnancy [ 1 ]. It is estimated to have affected 3. Despite the fact that the incidence of both gestational diabetes and preeclampsia is on the rise, there is concern that these and other pregnancy complications are not systematically recognized, diagnosed, or reported.
In fact, numerous studies have found significant inconsistency between medical information that is reported on birth certificates and other medical records such as hospital-discharge records. A recent study found that in Washington State, most pregnancy complications in general, and gestational diabetes in particular, are substantially underreported on birth certificates compared to hospital-discharge data [ 7 ].
Another study conducted in Ohio discovered that birth certificate data was less reliable than hospital records for identifying maternal risk factors, comorbid conditions, and complications of pregnancy, labor, and delivery [ 8 ]. Moreover, a number of other studies have discovered underreporting of birth defects [ 9 ], delivery complications [ 10 ], and other standard measures taken at birth [ 8 ] using state birth certificates alone. A review of the current literature suggests that birth certificates are generally not reliable sources of information on tobacco and alcohol use, prenatal care, maternal risk, pregnancy complications, labor, and delivery [ 11 ].
In addition to the question of systematic underreporting of adverse pregnancy outcomes, there is considerable interest in determining if this underreporting varies according to socioeconomic status. The socioeconomic gradient in preeclampsia is well established, with more recent data suggesting that there is a significant negative association between socioeconomic status and preeclampsia. Studies have found such an association using maternal education level [ 12 ], census tract income level [ 13 ], and household income level [ 5 ] as socioeconomic indicators.
However, inconsistent findings have also been reported, with older studies finding no association between low socioeconomic status and preeclampsia [ 14 — 16 ].
Studies that have investigated the association between socioeconomic status and gestational diabetes, however, have generated conflicting results that vary according to the socioeconomic indicators used. Numerous studies have found low socioeconomic status to be associated with a higher risk of gestational diabetes using maternal employment status [ 17 ], neighborhood income level [ 18 , 19 ], education level [ 20 , 21 ], type of hospital services used [ 22 ], and family income level [ 23 , 24 ] as socioeconomic indicators.
In contrast, a study that measured a combination of indicators including maternal employment status, education level, parity, and monthly income level, found no association between low socioeconomic status and gestational diabetes [ 25 ]. Other studies have also found no association using neighborhood deprivation level [ 26 ], insurance status [ 27 ], and level of maternal education [ 28 ] as markers. It has not yet been determined if the discrepancies in the results of these studies may be accounted for by differential reporting rates among populations of varying socioeconomic levels, a feature that may vary across study settings.
Thus, this paper examines the possibility of underreporting of adverse pregnancy outcomes in patients in Los Angeles County and Orange County, California, using data from both birth certificates and hospital birth records, with a specific focus on possible differential rates of underreporting according to socioeconomic status. Birth record data from the period of to were obtained from the Memorial Care System, a network of four hospitals that maintains a perinatal database for research purposes [ 29 ].
Records are inputted into this database by nurses when patients are admitted to the hospital for delivery. Additionally, birth certificate data were obtained for the four hospitals and the same study period from the California Department of Public Health [ 30 ].
These variables were selected because they were the only variables available in both datasets that were specific enough to identify a particular birth. To maximize the matching rate, we conducted multiple matching procedures. We assigned a partial match on DOB of mother if two of the three fields in the date of birth i. There are respectively ten and three records with any missing values in the four matching variables in the Memorial and the birth certificate data, and they were excluded from the matching process. We summarized the basic socio-demographic variables in both the Memorial and the birth certificate data and in the matched and the unmatched groups for each dataset.
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.
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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 ].
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.
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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.
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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.
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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.