Abstract
We examined social, demographic, and behavioral predictors of specific forms of hypertensive disorders in pregnancy in New York State. Administrative data on 2.3 million births over the period 1995–2004 were available for New York State, USA, with linkage to birth certificate data for New York City (964,071 births). ICD-9 hospital discharge diagnosis codes were used to assign hypertensive disorders hierarchically as chronic hypertension, chronic hypertension with superimposed preeclampsia, preeclampsia (eclampsia/severe or mild), or gestational hypertension. Sociodemographic and behavioral predictors of these outcomes were examined separately for upstate New York and New York City by calculating adjusted odds ratios. The most commonly diagnosed conditions were preeclampsia (2.57 % of upstate New York births, 3.68 % of New York City births) and gestational hypertension (2.46 % of upstate births, 1.42 % of New York City births). Chronic hypertension was much rarer. Relative to non-Hispanic Whites, Hispanics in New York City and Black women in all regions had markedly increased risks for all hypertensive disorders, whereas Asian women were at consistently decreased risk. Pregnancy-associated conditions decreased markedly with parity and modestly among smokers. A strong positive association was found between pre-pregnancy weight and risk of hypertensive disorders, with slightly weaker associations among Blacks and stronger associations among Asians. While patterns of chronic and pregnancy-induced hypertensive disorders differed, the predictors of gestational hypertension and both mild and severe preeclampsia were similar to one another. The increased risk for Black and some Hispanic women warrants clinical consideration, and the markedly increased risk with greater pre-pregnancy weight suggests an opportunity for primary prevention among all ethnic groups.
Keywords: Chronic hypertension, Gestational hypertension, Preeclampsia
Introduction
Hypertensive disorders are common complications of pregnancy, with a wide range of severity, ranging from chronic or gestational hypertension to severe preeclampsia and eclampsia, which can be life-threatening for the mother and fetus and may result in very preterm birth [1]. Birth records provide comprehensive data on the population, but with limited specificity of diagnosis and substantial misclassification as compared to medical record review [2, 3]. Hospital discharge diagnoses are superior to birth certificates for this purpose [3]. A distinct but largely unexploited advantage of discharge diagnoses over birth certificates is the ability to examine specific hypertensive disorders, not well developed in previous studies [4, 5]. We combined the advantages of administrative data for diagnostic accuracy with the wide range of predictors available from linkage to birth certificates to conduct a comprehensive evaluation of the relationship between sociodemographic factors, behaviors, and reproductive history and the full spectrum of specific hypertensive disorders that can occur in pregnancy.
Methods
Hospital discharge data for all births in New York State (including New York City) for the period 1995–2004 were obtained from the Statewide Planning and Research Cooperative System. We restricted analyses to singleton, live births. Starting with the 2,285,108 births in all of New York State, they were divided into subsets based on residence in New York City or upstate New York. We linked birth certificate information to the hospital discharge data for the subset of births to residents of New York City who were born in New York City Hospitals and had birth certificate information available. Out of 1,098,664 births to New York City residents, 964,091 were in New York City hospitals (87.8 %) and had birth certificates available for linkage. We also examined 1,186,444 births in upstate New York that did not have birth certificates available for linkage. Birth hospitalizations were identified based on ICD diagnostic codes, with information available on the mother’s age, ethnicity, county of residence, insurance status, and up to 15 ICD codes for medical conditions, which included diagnostic codes for the full range of hypertensive disorders of interest. Urban/rural status was categorized according to National Center for Health Statistics guidelines based on county population size) listed from most urban to most rural: metropolitan area: large central counties in metro area greater than 1 million population; metropolitan area: large fringe counties in metro area greater than 1 million population; medium metropolitan area: counties in metro area 250,000–999,999 population; small metropolitan area: counties in metro area 50,000–249,999 population; micropolitan counties; non-core counties [6]. For births to residents of New York City only, the linkage to birth certificate data yielded additional predictors of interest, including more detailed ethnicity, parity, education, tobacco use, and pre-pregnancy weight. (Restrictions on access precluded linkage of birth certificate data for upstate residents.)
Women were identified as having been diagnosed with a given hypertensive disorder if a corresponding ICD code appeared in any of the 15 medical diagnosis fields (Table 1). We developed a hierarchy for assigning each pregnancy to one and only one outcome group, necessary because some women had more than one type of hypertensive disorder assigned. We first prioritized based on whether chronic hypertension was present or not. Then among women whose onset of hypertension occurred during pregnancy, we considered severity, assigning the most severe diagnosis that was listed. Starting with those diagnosed with chronic hypertension, we distinguished those with “chronic hypertension with no superimposed preeclampsia” (Table 1) and “chronic hypertension with superimposed preeclampsia”. Among women without chronic hypertension, we began by identifying women with an assignment of “eclampsia or severe preeclampsia”. Among remaining women, we then assessed whether “mild preeclampsia” was reported, and if it was not, whether “gestational hypertension” was reported. This resulted in the following categories, each compared to the referent with “no hypertensive disorders”: chronic hypertension alone, preeclampsia superimposed on chronic hypertension, severe preeclampsia/eclampsia and mild preeclampsia (aggregated and separated), and gestational hypertension.
Table 1.
ICD-9 codes used to classify hypertensive disorders before and during pregnancy
| Condition | ICD-9 codes |
|---|---|
| Chronic hypertension with no superimposed preeclampsia | 401.0, 401.1, 401.9, 405.01, 405.09, 405.11, 405.19, 405.91, 405.99, 416.0, 459.30, 459.31, 459.32, 459.33, 459.39, 642.00–642.04, 642.10–642.14, 642.20–642.24, but excluding codes 642.70–642.74 |
| Chronic hypertension with superimposed preeclampsia | 642.70–642.74 |
| Eclampsia or severe preeclampsia | 642.50–642.54, 642.60–642.64 |
| Mild preeclampsia | 642.40–642.44 |
| Gestational hypertension | 642.30–642.34, 642.90–642.94 |
The predictors of hypertensive disorders were distinctive for upstate New York and New York City based on data availability. For upstate New York, predictors evaluated included calendar time, maternal age, maternal race/ethnicity, insurance type, and urban/rural county of residence. For New York City, these same predictors (except urban/rural county of residence) were studied, with the addition of parity, maternal education, detailed ethnicity, prenatal smoking, onset of prenatal care, and pre-pregnancy weight. The association between prepregnancy weight and hypertensive disorders was examined in subgroups defined by ethnicity (non-Hispanic White, Black, Hispanic, and Asian).
The crude odds ratio was used to estimate relative risks for each of the specific hypertensive disorders compared to no hypertensive disorders (excluding women with more severe/chronic forms of hypertensive disorders). An adjusted odds ratio with 95 % confidence interval that incorporated all the other predictors was derived by multinomial logistic regression using SAS v. 9.3. Access to the data required approval from Institutional Review Boards of the New York City Department of Health and Mental Hygiene, New York State Department of Health, and the Data Protection Review Board of the Statewide Cooperative Research and Evaluation System; and the research was approved by the Brown University Institutional Review Board.
Results
The results for upstate New York and New York City are presented separately. The most commonly diagnosed conditions were preeclampsia (2.57 % of upstate New York births, 3.68 % of New York City births) and gestational hypertension (2.46 % of upstate births, 1.42 % of New York City births). Isolated chronic hypertension was rarer (0.83 and 0.85 %, respectively), as was preeclampsia superimposed on chronic hypertension (0.23 and 0.38 %, respectively).
Risk of chronic hypertension, especially without superimposed preeclampsia, increased over the time period of the study, and rose markedly with advancing maternal age. Chronic hypertension was notably more common among Black women and less common among Hispanic and Asian women in upstate New York (Table 2) whereas in New York City (Table 3), Hispanic women had increased risk. Chronic hypertension was more common among women with public insurance relative to those with private insurance. In upstate New York, there was evidence of greater risk in more rural areas of the state. In New York City, risk declined with advancing parity (especially for preeclampsia superimposed on chronic hypertension), and declined with increased education, with little association with smoking or prenatal care onset. Risk increased markedly with higher pre-pregnancy weight; a clear, monotonic dose–response gradient culminating in greater than sixfold increased risks. The magnitude of increase was somewhat greater for Asian women (though high prepregnancy weight was rarer) and more muted among Black women (Tables 4 and 5). The differences in pattern between isolated chronic hypertension and preeclampsia superimposed on chronic hypertension were modest, with isolated chronic hypertension showing a greater increase over time, and somewhat weaker associations with maternal ethnicity, insurance status, and parity among New York City births.
Table 2.
Predictors of chronic hypertension, with and without superimposed preeclampsia, and gestational hypertension in upstate New York, 1995–2004
| % of all births | Isolated chronic hypertension
|
Chronic hypertension with preeclampsia
|
Gestational hypertension
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 1,171,131 | 9,880 (0.83) | 2,692 (0.23) | 28,117 (2.46) | |||
| Year | |||||||
| 1995–1998 | 38.7 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1999–2001 | 30.9 | 1.1 | 1.1 (1.1, 1.2) | 1.2 | 1.1 (1.0, 1.2) | 1.2 | 1.2 (1.2, 1.3) |
| 2002–2004 | 30.4 | 1.4 | 1.4 (1.3, 1.4) | 1.2 | 1.1 (1.0, 1.3) | 1.4 | 1.4 (1.4, 1.4) |
| Maternal age (years) | |||||||
| < 20 | 7.9 | 0.4 | 0.3 (0.2, 0.3) | 0.4 | 0.3 (0.3, 0.4) | 1.1 | 1.1 (1.0, 1.1) |
| 20–24 | 18.5 | 0.6 | 0.5 (0.5, 0.5) | 0.7 | 0.6 (0.5, 0.7) | 1.0 | 1.0 (0.9, 1.0) |
| 25–29 | 25.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 30–34 | 29.7 | 1.3 | 1.4 (1.4, 1.5) | 1.2 | 1.3 (1.2, 1.5) | 0.9 | 0.9 (0.9, 1.0) |
| ≥35 | 18.1 | 2.4 | 2.7 (2.5, 2.8) | 2.3 | 2.6 (2.3, 2.9) | 1.0 | 1.0 (1.0, 1.1) |
| Maternal race/ethnicity | |||||||
| Non-Hispanic White | 63.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Black | 8.6 | 2.1 | 2.8 (2.7, 3.0) | 2.9 | 3.7 (3.3, 4.1) | 1.1 | 1.2 (1.2, 1.3) |
| Hispanic | 6.6 | 0.6 | 0.7 (0.7, 0.8) | 0.7 | 0.9 (0.7, 1.1) | 0.7 | 0.8 (0.8, 0.9) |
| Asian | 1.9 | 0.6 | 0.5 (0.4, 0.6) | 0.5 | 0.5 (0.3, 0.7) | 0.6 | 0.6 (0.5, 0.7) |
| Unknown/other | 19.6 | 1.0 | 1.0 (1.0, 1.1) | 1.4 | 1.4 (1.3, 1.6) | 0.9 | 0.9 (0.8, 0.9) |
| Insurance | |||||||
| Private | 70.2 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Public | 27.3 | 0.9 | 1.2 (1.1, 1.2) | 1.0 | 1.2 (1.0, 1.3) | 0.8 | 0.8 (0.8, 0.8) |
| Self-pay | 2.6 | 0.7 | 0.8 (0.7, 1.0) | 0.8 | 0.9 (0.7, 1.1) | 0.8 | 0.8 (0.7, 0.9) |
| Urban/rural county | |||||||
| Large central counties of metro area > 1 million pop | 15.3 | 1.1 | 1.1 (1.1, 1.2) | 1.0 | 1.0 (0.9, 1.2) | 1.3 | 1.2 (1.2, 1.3) |
| Large fringe counties of metro area > 1 million pop | 44.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Medium metro: pop 250,00–999,999 | 21.7 | 1.2 | 1.4 (1.3, 1.5) | 1.2 | 1.3 (1.2, 1.5) | 1.3 | 1.3 (1.3, 1.3) |
| Small metro: pop 50,000–249,999 | 6.0 | 0.9 | 1.2 (1.1, 1.3) | 0.9 | 1.2 (1.0, 1.5) | 1.5 | 1.6 (1.5, 1.7) |
| Micropolitan counties | 9.7 | 1.1 | 1.6 (1.4, 1.7) | 0.8 | 1.2 (1.0, 1.4) | 1.3 | 1.3 (1.3, 1.4) |
| Non-core counties | 3.3 | 1.1 | 1.5 (1.4, 1.7) | 1.2 | 1.8 (1.4, 2.2) | 1.5 | 1.5 (1.5, 1.6) |
Mutually adjusted for all other variables in the table
Table 3.
Predictors of chronic hypertension, with and without superimposed preeclampsia, and gestational hypertension in New York City, 1995–2004
| %of all births | Isolated chronic hypertension
|
Chronic hypertension with preeclampsia
|
Gestational hypertension
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 788,454 | 8,192 (0.85) | 3,633 (0.38) | 12,999 (1.42) | |||
| Year | |||||||
| 1995–1998 | 35.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1999–2001 | 30.1 | 1.0 | 1.0 (0.9, 1.1) | 0.9 | 0.9 (0.8, 1.0) | 1.1 | 1.1 (1.1, 1.2) |
| 2002–2004 | 34.6 | 1.2 | 1.2 (1.1, 1.2) | 0.9 | 0.9 (0.9, 1.0) | 1.3 | 1.3 (1.3, 1.4) |
| Maternal age (years) | |||||||
| < 20 | 9.2 | 0.5 | 0.5 (0.4, 0.5) | 0.7 | 0.5 (0.4, 0.6) | 1.3 | 1.1 (1.0, 1.2) |
| 20–24 | 22.4 | 0.6 | 0.6 (0.5, 0.7) | 0.8 | 0.7 (0.6, 0.8) | 1.0 | 1.0 (0.9, 1.0) |
| 25–29 | 26.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 30–34 | 24.9 | 1.6 | 1.7 (1.6, 1.9) | 1.6 | 1.7 (1.5, 1.9) | 1.2 | 1.2 (1.1, 1.3) |
| ≥35 | 17.0 | 3.6 | 3.7 (3.5, 4.0) | 3.4 | 4.0 (3.6, 4.4) | 1.6 | 1.7 (1.6, 1.8) |
| Maternal race/ethnicity | |||||||
| Non-Hispanic White | 23.3 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Black | 21.7 | 2.8 | 2.3 (2.1, 2.5) | 4.3 | 3.2 (2.8, 3.6) | 1.4 | 1.3 (1.2, 1.4) |
| Hispanic | 20.0 | 1.1 | 1.4 (1.2, 1.5) | 1.7 | 1.8 (1.5, 2.0) | 1.1 | 1.3 (1.2, 1.3) |
| Asian | 8.2 | 0.7 | 1.1 (0.9, 1.3) | 1.1 | 1.3 (1.0, 1.6) | 0.6 | 0.9 (0.8, 0.9) |
| Unknown/other | 26.7 | 1.5 | 1.7 (1.6, 1.8) | 2.1 | 2.0 (1.8, 2.3) | 1.3 | 1.4 (1.3, 1.5) |
| Insurance | |||||||
| Private | 41.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Public | 54.7 | 0.9 | 1.2 (1.1, 1.2) | 1.3 | 1.5 (1.4, 1.7) | 1.0 | 1.1 (1.0, 1.1) |
| Self-pay | 3.4 | 1.0 | 1.2 (1.0, 1.3) | 1.4 | 1.5 (1.2, 1.8) | 0.7 | 0.8 (0.7, 0.9) |
| Parity | |||||||
| 0 | 45.3 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1 | 30.4 | 1.1 | 0.8 (0.7, 0.8) | 0.9 | 0.6 (0.6, 0.7) | 0.6 | 0.5 (0.5, 0.6) |
| ≥2 | 24.3 | 1.9 | 0.8 (0.7, 0.8) | 1.5 | 0.6 (0.5, 0.6) | 0.7 | 0.5 (0.5, 0.5) |
| Maternal education (years) | |||||||
| < 12 | 24.9 | 0.8 | 1.0 (0.9, 1.1) | 1.0 | 1.2 (1.1, 1.3) | 0.9 | 1.0 (1.0, 1.1) |
| 12 | 32.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 13–16 | 31.5 | 1.0 | 0.9 (0.9, 1.0) | 1.0 | 0.9 (0.9, 1.0) | 1.1 | 1.0 (1.0, 1.1) |
| > 16 | 10.9 | 0.8 | 0.7 (0.7, 0.8) | 0.7 | 0.7 (0.6, 0.8) | 1.0 | 0.9 (0.8, 1.0) |
| Prenatal smoking | |||||||
| No | 96.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Yes | 3.2 | 1.3 | 1.0 (0.9, 1.2) | 1.3 | 1.0 (0.8, 1.2) | 0.8 | 0.8 (0.7, 0.9) |
| Prenatal care | |||||||
| None or started in 3rd trimester | 7.7 | 0.9 | 0.9 (0.8, 1.0) | 1.2 | 1.0 (0.9, 1.1) | 0.9 | 1.0 (0.9, 1.1) |
| Started 1st trimester | 66.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Started 2nd trimester | 25.5 | 0.9 | 1.0 (0.9, 1.0) | 1.1 | 1.0 (0.9, 1.1) | 0.9 | 1.0 (0.9, 1.0) |
| Pre-pregnancy weight quintiles (lbs) | |||||||
| ≤118 | 21.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 23.0 | 1.7 | 1.6 (1.4, 1.8) | 1.7 | 1.6 (1.3, 1.9) | 1.3 | 1.3 (1.2, 1.4) |
| > 130 to ≤142 | 16.0 | 2.7 | 2.3 (2.0, 2.6) | 2.4 | 2.2 (1.8, 2.6) | 1.6 | 1.6 (1.5, 1.7) |
| > 142 to ≤165 | 20.8 | 4.2 | 3.4 (3.0, 3.8) | 3.7 | 3.0 (2.5, 3.5) | 2.2 | 2.2 (2.1, 2.4) |
| > 165 | 18.7 | 12.0 | 8.9 (7.9, 10.0) | 8.7 | 6.3 (5.4, 7.4) | 3.9 | 4.0 (3.8, 4.3) |
Mutually adjusted for all other variables in the table
Table 4.
Pre-pregnancy weight as a predictor of chronic hypertension, with and without superimposed preeclampsia, and gestational hypertension in New York City, 1995–2004
| % of all births | Isolated chronic hypertension
|
Chronic hypertension with preeclampsia
|
Gestational hypertension
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 8,192 (0.85) | 3,633 (0.38) | 12,999 (1.42) | ||||
| All, quintiles (lbs) | |||||||
| ≤118 | 21.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 23.0 | 1.7 | 1.6 (1.4, 1.8) | 1.7 | 1.6 (1.3, 1.9) | 1.3 | 1.3 (1.2, 1.4) |
| > 130 to ≤142 | 16.0 | 2.7 | 2.3 (2.0, 2.6) | 2.4 | 2.2 (1.8, 2.6) | 1.6 | 1.6 (1.5, 1.7) |
| > 142 to ≤165 | 20.8 | 4.2 | 3.4 (3.0, 3.8) | 3.7 | 3.0 (2.5, 3.5) | 2.2 | 2.2 (2.1, 2.4) |
| > 165 | 18.7 | 12.0 | 8.9 (7.9, 10.0) | 8.7 | 6.3 (5.4, 7.4) | 3.9 | 4.0 (3.8, 4.3) |
| Non-Hispanic, White, quintiles (lbs) | |||||||
| ≤118 | 20.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 25.8 | 1.3 | 1.1 (0.8, 1.5) | 1.4 | 1.4 (0.8, 2.2) | 1.3 | 1.2 (1.0, 1.5) |
| > 130 to ≤142 | 17.9 | 2.1 | 1.9 (1.4, 2.6) | 2.1 | 1.8 (1.1, 3.0) | 1.7 | 1.6 (1.4, 1.9) |
| > 142 to ≤165 | 20.3 | 3.2 | 3.0 (2.3, 3.9) | 2.5 | 2.2 (1.4, 3.6) | 2.4 | 2.5 (2.1, 2.9) |
| > 165 | 15.2 | 9.8 | 8.9 (6.9, 11.4) | 9.5 | 9.0 (5.9, 13.7) | 4.6 | 5.0 (4.3, 5.9) |
| Black, quintiles (lbs) | |||||||
| ≤118 | 12.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 17.1 | 1.5 | 1.2 (0.9, 1.6) | 1.7 | 1.6 (1.1, 2.3) | 1.2 | 1.2 (1.0, 1.4) |
| > 130 to ≤142 | 14.2 | 2.1 | 1.6 (1.3, 2.1) | 2.8 | 2.4 (1.7, 3.4) | 1.3 | 1.3 (1.1, 1.5) |
| > 142 to ≤165 | 24.7 | 3.3 | 2.3 (1.8, 2.9) | 3.7 | 2.9 (2.1, 4.0) | 1.6 | 1.7 (1.4, 2.0) |
| > 165 | 31.6 | 7.9 | 5.4 (4.3, 6.7) | 6.9 | 5.1 (3.7, 7.0) | 2.9 | 3.0 (2.6, 3.5) |
| Hispanic, quintiles (lbs) | |||||||
| ≤18 | 20.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 24.1 | 1.6 | 1.5 (1.1, 2.0) | 1.4 | 1.2 (0.8, 1.8) | 1.3 | 1.4 (1.2, 1.6) |
| > 130 to ≤142 | 16.7 | 2.3 | 2.0 (1.5, 2.7) | 2.1 | 1.9 (1.3, 2.8) | 1.5 | 1.6 (1.4, 2.0) |
| > 142 to ≤165 | 21.4 | 2.9 | 2.4 (1.8, 3.2) | 2.5 | 2.3 (1.6, 3.3) | 2.0 | 2.2 (1.9, 2.6) |
| > 165 | 17.0 | 8.6 | 7.4 (5.6, 9.6) | 4.9 | 4.6 (3.3, 6.5) | 3.6 | 4.0 (3.4, 4.7) |
| Asian, quintiles (lbs) | |||||||
| ≤118 | 47.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 26.7 | 2.4 | 2.5 (1.7, 3.8) | 1.4 | 1.3 (0.7, 2.2) | 1.4 | 1.4 (1.1, 1.8) |
| > 130 to ≤142 | 12.3 | 4.8 | 4.7 (3.1, 7.3) | 2.3 | 2.2 (1.2, 3.9) | 2.3 | 2.3 (1.7, 3.0) |
| > 142 to ≤165 | 9.8 | 6.6 | 6.4 (4.2, 9.8) | 4.1 | 3.5 (2.0, 6.0) | 3.1 | 3.2 (2.4, 4.2) |
| > 165 | 3.4 | 16.4 | 14.5 (9.2, 22.8) | 9.6 | 7.8 (4.3, 14.3) | 5.8 | 5.6 (4.0, 7.8) |
Adjusted for year of birth, maternal age, maternal race/ethnicity (only when not stratified), insurance, parity, education, prenatal smoking, prenatal care
Table 5.
Pre-pregnancy weight as a predictor of aggregated preeclampsia, severe preeclampsia/eclampsia, and mild preeclampsia in New York City, 1995–2004
| % of all births | Aggregated
|
Severe/eclampsia
|
Mild
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 8,192 (0.85) | 3,633 (0.38) | 12,999 (1.42) | ||||
| All, quintiles (lbs) | |||||||
| ≤118 | 21.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 23.0 | 1.2 | 1.2 (1.1, 1.2) | 1.2 | 1.2 (1.1, 1.3) | 1.2 | 1.2 (1.2, 1.3) |
| > 130 to ≤142 | 16.0 | 1.3 | 1.4 (1.3, 1.4) | 1.3 | 1.2 (1.1, 1.4) | 1.4 | 1.4 (1.3, 1.5) |
| > 142 to ≤165 | 20.8 | 1.6 | 1.7 (1.6, 1.8) | 1.4 | 1.4 (1.3, 1.6) | 1.7 | 1.8 (1.7, 1.9) |
| > 165 | 18.7 | 2.3 | 2.4 (2.3, 2.5) | 1.8 | 1.8 (1.6, 1.9) | 2.4 | 2.6 (2.5, 2.8) |
| Non-Hispanic, White, quintiles (lbs) | |||||||
| ≤118 | 20.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 25.8 | 1.1 | 1.2 (1.1, 1.3) | 1.1 | 1.2 (1.0, 1.4) | 1.2 | 1.2 (1.1, 1.4) |
| > 130 to ≤142 | 17.9 | 1.4 | 1.5 (1.3, 1.6) | 1.3 | 1.4 (1.1, 1.7) | 1.4 | 1.5 (1.4, 1.7) |
| > 142 to ≤165 | 20.3 | 1.8 | 2.0 (1.8, 2.2) | 1.5 | 1.6 (1.3, 1.9) | 1.9 | 2.1 (1.9, 2.3) |
| > 165 | 15.2 | 2.7 | 3.1 (2.8, 3.4) | 1.7 | 1.9 (1.5, 2.3) | 3.0 | 3.5 (3.1, 3.9) |
| Black, quintiles (lbs) | |||||||
| ≤118 | 12.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 17.1 | 1.0 | 1.1 (1.0, 1.2) | 1.0 | 1.0 (0.8, 1.2) | 1.0 | 1.1 (1.0, 1.2) |
| > 130 to ≤142 | 14.2 | 1.0 | 1.1 (1.0, 1.2) | 1.0 | 1.0 (0.8, 1.2) | 1.1 | 1.1 (1.0, 1.3) |
| > 142 to ≤165 | 24.7 | 1.2 | 1.3 (1.2, 1.4) | 1.0 | 1.1 (0.9, 1.3) | 1.3 | 1.4 (1.3, 1.5) |
| > 165 | 31.6 | 1.6 | 1.8 (1.7, 2.0) | 1.2 | 1.3 (1.1, 1.5) | 1.7 | 2.0 (1.8, 2.2) |
| Hispanic, quintiles (lbs) | |||||||
| ≤118 | 20.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 24.1 | 1.1 | 1.2 (1.2, 1.4) | 1.2 | 1.3 (1.1, 1.5) | 1.1 | 1.2 (1.1, 1.4) |
| > 130 to ≤142 | 16.7 | 1.2 | 1.4 (1.3, 1.5) | 1.2 | 1.3 (1.1, 1.5) | 1.2 | 1.4 (1.3, 1.6) |
| > 142 to ≤165 | 21.4 | 1.4 | 1.7 (1.5, 1.8) | 1.2 | 1.4 (1.2, 1.6) | 1.4 | 1.8 (1.6, 1.9) |
| > 165 | 17.0 | 1.8 | 2.3 (2.1, 2.5) | 1.6 | 1.9 (1.6, 2.2) | 1.9 | 2.4 (2.2, 2.6) |
| Asian, quintiles (lbs) | |||||||
| ≤118 | 47.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 26.7 | 1.3 | 1.3 (1.2, 1.6) | 1.2 | 1.3 (1.0, 1.9) | 1.3 | 1.3 (1.1, 1.6) |
| > 130 to ≤142 | 12.3 | 1.7 | 1.9 (1.6, 2.2) | 1.4 | 1.6 (1.1, 2.3) | 1.8 | 2.0 (1.6, 2.4) |
| > 142 to ≤165 | 9.8 | 2.3 | 2.6 (2.2, 3.1) | 2.4 | 2.6 (1.8, 1.2) | 2.3 | 2.6 (2.2, 3.2) |
| > 165 | 3.4 | 3.2 | 4.0 (3.1, 5.0) | 3.0 | 3.6 (2.3, 1.2) | 3.3 | 4.0 (3.1, 5.2) |
Adjusted for year of birth, maternal age, maternal race/ethnicity (only when not stratified), insurance, parity, education, prenatal smoking, prenatal care
The pattern for gestational hypertension showed some similarities and rather distinct differences from the pattern for chronic hypertension (Tables 2, 3). Risk increased over time, Hispanic and Asian women had decreased risk (upstate only), and rural women showed increased risk in upstate New York, consistent with results for chronic hypertension. Contrasting results included an absence of association with maternal age in upstate New York, a more modest gradient of increasing risk with advancing age in New York City, and less pronounced increased risk among Black women. There was a notably decreased risk among parous women and evidence of a decreased risk among smokers. A strong gradient was found with pre-pregnancy weight, somewhat less dramatic than for chronic hypertension.
Preeclampsia was examined in the aggregate and subdivided into “severe preeclampsia and eclampsia” (referred to as “severe”) and “mild preeclampsia,” which was more commonly diagnosed (1.86 % mild and 0.71 % severe in upstate New York, 2.83 % mild and 0.87 % severe in New York City) (Tables 6, 7). Risk of both forms of preeclampsia was stable over time, with the exception of a modest increase in severe preeclampsia in upstate New York. With regard to maternal age, adjusted odds ratios were increased for the youngest mothers (<20 years) in upstate New York and for the oldest mothers (35+) in New York City and otherwise flat. Given the inability to adjust for parity in New York State and increased unadjusted rates for young women in New York City, residual confounding by parity is likely to largely explain this pattern. In both upstate New York and New York City, Black women were at increased risk (more so for severe than mild pre-eclampsia) and Asian women were at decreased risk. Also, Hispanic women and women with public insurance showed increased risk only in New York City. A small increased risk was found with increasing rurality in New York State. In New York City, parous women had dramatically lower risk. Women with more education had a decreased risk, and smokers had modestly reduced risk. A clear, monotonic gradient of increasing risk was found in relation to pre-pregnancy weight, but more muted than that for the other hypertensive disorders (Tables 4 and 5). With the exceptions noted above, few differences were seen in the predictors for severe and mild preeclampsia.
Table 6.
Predictors of aggregated preeclampsia, severe preeclampsia/eclampsia, and mild preeclampsia in upstate New York, 1995–2004
| % of all births | Aggregated
|
Severe/eclampsia
|
Mild
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 1,171,131 | 30,116 (2.57) | 8,388 (0.71) | 21,728 (1.86) | |||
| Year | |||||||
| 1995–1998 | 38.7 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1999–2001 | 30.9 | 1.0 | 1.0 (0.9, 1.0) | 1.1 | 1.1 (1.0, 1.1) | 0.9 | 0.9 (0.9, 1.0) |
| 2002–2004 | 30.4 | 1.0 | 1.0 (1.0, 1.0) | 1.2 | 1.2 (1.1, 1.2) | 0.9 | 0.9 (0.9, 0.9) |
| Maternal age (years) | |||||||
| < 20 | 7.9 | 1.6 | 1.5 (1.5, 1.6) | 1.7 | 1.5 (1.4, 1.7) | 1.6 | 1.5 (1.5, 1.6) |
| 20–24 | 18.5 | 1.1 | 1.1 (1.1, 1.2) | 1.1 | 1.1 (1.0, 1.1) | 1.2 | 1.1 (1.1, 1.2) |
| 25–29 | 25.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 30–34 | 29.7 | 0.9 | 0.9 (0.8, 0.9) | 0.9 | 0.9 (0.9, 1.0) | 0.8 | 0.8 (0.8, 0.9) |
| ≥35 | 18.1 | 1.0 | 1.0 (0.9, 1.0) | 1.1 | 1.2 (1.1, 1.2) | 0.9 | 0.9 (0.9, 0.9) |
| Maternal race/ethnicity | |||||||
| Non-Hispanic White | 63.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Black | 8.6 | 1.6 | 1.5 (1.5, 1.6) | 1.9 | 1.9 (1.8, 2.0) | 1.5 | 1.4 (1.4, 1.5) |
| Hispanic | 6.6 | 1.1 | 1.1 (1.1, 1.2) | 1.2 | 1.3 (1.1, 1.4) | 1.1 | 1.1 (1.0, 1.1) |
| Asian | 1.9 | 0.7 | 0.8 (0.7, 0.8) | 0.8 | 0.8 (0.6, 0.9) | 0.7 | 0.8 (0.7, 0.9) |
| Unknown/other | 19.6 | 1.2 | 1.1 (1.1, 1.2) | 1.3 | 1.3 (1.2, 1.3) | 1.1 | 1.1 (1.1, 1.1) |
| Insurance | |||||||
| Private | 70.2 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Public | 27.3 | 1.2 | 0.9 (0.9, 1.0) | 1.1 | 0.9 (0.8, 0.9) | 1.2 | 1.0 (0.9, 1.0) |
| Self-pay | 2.6 | 1.0 | 0.9 (0.8, 0.9) | 1.0 | 0.9 (0.8, 1.0) | 1.0 | 0.9 (0.8, 0.9) |
| Urban/rural county | |||||||
| Large central counties of metro area > 1 million pop | 15.3 | 1.0 | 1.0 (0.9, 1.0) | 1.1 | 1.0 (1.0, 1.1) | 1.0 | 0.9 (0.9, 1.0) |
| Large fringe counties of metro area > 1 million pop | 44.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Medium metro: pop 250,00–999,999 | 21.7 | 1.1 | 1.1 (1.1, 1.1) | 1.3 | 1.3 (1.2, 1.3) | 1.1 | 1.0 (1.0, 1.1) |
| Small metro: pop 50,000–249,999 | 6.0 | 1.1 | 1.1 (1.1, 1.2) | 1.1 | 1.2 (1.1, 1.3) | 1.1 | 1.1 (1.0, 1.2) |
| Micropolitan counties | 9.7 | 1.0 | 1.0 (1.0, 1.1) | 1.1 | 1.2 (1.1, 1.3) | 1.0 | 1.0 (0.9, 1.0) |
| Non-core counties | 3.3 | 1.2 | 1.2 (1.2, 1.3) | 1.1 | 1.2 (1.1, 1.4) | 1.3 | 1.2 (1.1, 1.3) |
Mutually adjusted for all other variables in the table
Table 7.
Predictors of aggregated preeclampsia, severe preeclampsia/eclampsia, and mild preeclampsia in New York City, 1995–2004
| % of all births | Aggregated
|
Severe/eclampsia
|
Mild
|
||||
|---|---|---|---|---|---|---|---|
| Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | Crude OR | Adjusteda OR (95 % CL) | ||
| Total number of births (#, %) | 788,454 | 35,048 (3.68) | 8,316 (0.87) | 26,732 (2.83) | |||
| Year | |||||||
| 1995–1998 | 35.4 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1999–2001 | 30.1 | 0.9 | 0.9 (0.9, 1.0) | 1.0 | 1.1 (1.0, 1.1) | 0.9 | 0.9 (0.9, 0.9) |
| 2002–2004 | 34.6 | 0.9 | 0.9 (0.9, 0.9) | 1.0 | 1.0 (1.0, 1.1) | 0.9 | 0.9 (0.8, 0.9) |
| Maternal age (years) | |||||||
| < 20 | 9.2 | 1.8 | 1.1 (1.0, 1.1) | 1.4 | 0.8 (0.8, 0.9) | 2.0 | 1.1 (1.1, 1.2) |
| 20–24 | 22.4 | 1.2 | 0.9 (0.9, 1.0) | 1.0 | 0.8 (0.8, 0.9) | 1.3 | 1.0 (0.9, 1.0) |
| 25–29 | 26.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 30–34 | 24.9 | 1.0 | 1.1 (1.1, 1.1) | 1.0 | 1.1 (1.0, 1.2) | 1.0 | 1.1 (1.1, 1.1) |
| ≥35 | 17.0 | 1.2 | 1.5 (1.4, 1.6) | 1.3 | 1.6 (1.4, 1.7) | 1.2 | 1.5 (1.4, 1.6) |
| Maternal race/ethnicity | |||||||
| Non-Hispanic White | 23.3 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Black | 21.7 | 1.9 | 1.6 (1.5, 1.7) | 2.0 | 1.9 (1.8, 2.1) | 1.9 | 1.5 (1.5, 1.6) |
| Hispanic | 20.0 | 1.7 | 1.6 (1.5, 1.7) | 1.8 | 1.8 (1.7, 2.0) | 1.7 | 1.5 (1.5, 1.6) |
| Asian | 8.2 | 0.7 | 0.8 (0.7, 0.8) | 0.7 | 0.7 (0.6, 0.8) | 0.7 | 0.8 (0.7, 0.8) |
| Unknown/other | 26.7 | 1.4 | 1.3 (1.3, 1.4) | 1.6 | 1.6 (1.5, 1.8) | 1.4 | 1.2 (1.2, 1.3) |
| Insurance | |||||||
| Private | 41.9 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Public | 54.7 | 1.3 | 1.2 (1.2, 1.3) | 1.2 | 1.2 (1.1, 1.3) | 1.4 | 1.3 (1.2, 1.3) |
| Self-pay | 3.4 | 1.2 | 1.2 (1.1, 1.2) | 1.1 | 1.1 (1.0, 1.3) | 1.2 | 1.2 (1.1, 1.3) |
| Parity | |||||||
| 0 | 45.3 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 1 | 30.4 | 0.5 | 0.4 (0.4, 0.4) | 0.5 | 0.5 (0.4, 0.5) | 0.5 | 0.4 (0.4, 0.4) |
| ≥2 | 24.3 | 0.5 | 0.4 (0.3, 0.4) | 0.6 | 0.4 (0.4, 0.4) | 0.5 | 0.3 (0.3, 0.4) |
| Maternal education (years) | |||||||
| < 12 | 24.9 | 1.1 | 1.1 (1.1, 1.1) | 1.1 | 1.0 (1.0, 1.1) | 1.1 | 1.1 (1.1, 1.2) |
| 12 | 32.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 13–16 | 31.5 | 1.0 | 0.9 (0.9, 1.0) | 1.0 | 0.9 (0.8, 0.9) | 1.0 | 0.9 (0.9, 1.0) |
| > 16 | 10.9 | 0.7 | 0.7 (0.7, 0.8) | 0.8 | 0.7 (0.7, 0.8) | 0.7 | 0.7 (0.7, 0.8) |
| Prenatal smoking | |||||||
| No | 96.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Yes | 3.2 | 0.8 | 0.8 (0.8, 0.9) | 0.8 | 0.8 (0.7, 0.9) | 0.9 | 0.8 (0.8, 0.9) |
| Prenatal care | |||||||
| None or started in 3rd trimester | 7.7 | 1.0 | 0.9 (0.9, 1.0) | 1.0 | 0.9 (0.8, 1.0) | 1.1 | 0.9 (0.9, 1.0) |
| Started 1st trimester | 66.8 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| Started 2nd trimester | 25.5 | 1.0 | 0.9 (0.9, 1.0) | 0.9 | 0.9 (0.8, 1.0) | 1.0 | 0.9 (0.9, 1.0) |
| Pre-pregnancy weight quintiles (lbs) | |||||||
| ≤118 | 21.5 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| > 118 to ≤130 | 23.0 | 1.2 | 1.2 (1.1, 1.2) | 1.2 | 1.2 (1.1, 1.3) | 1.2 | 1.2 (1.2, 1.3) |
| > 130 to ≤142 | 16.0 | 1.3 | 1.4 (1.3, 1.4) | 1.3 | 1.2 (1.1, 1.4) | 1.4 | 1.4 (1.3, 1.5) |
| > 142 to ≤165 | 20.8 | 1.6 | 1.7 (1.6, 1.8) | 1.4 | 1.4 (1.3, 1.6) | 1.7 | 1.8 (1.7, 1.9) |
| > 165 | 18.7 | 2.3 | 2.4 (2.3, 2.5) | 1.8 | 1.8 (1.6, 1.9) | 2.4 | 2.6 (2.5, 2.8) |
Mutually adjusted for all other variables in the table
Discussion
Although the absolute frequencies of hypertensive disorders found in New York are broadly in the range reported in studies around the world [7–12], the patterns of hypertensive disorders by ethnicity that we were able to detect are particularly noteworthy, with Black women having markedly elevated risk of chronic hypertension (with or without superimposed preeclampsia) and increased risk of both severe and mild preeclampsia. These results were consistent in Upstate New York and New York City and expand upon the results of previous studies [4, 7, 13]. The risk ratios for Blacks tended to be greatest for the most severe forms of hypertensive disorders, pointing towards a need for research to understand the reasons and address this disparity, which has significant implications for disparities in other birth outcomes such as preterm birth and perinatal mortality.
Results for Hispanics were more complicated, with increased risks in New York City but not in New York State, likely a reflection of the distinctive subsets of Hispanics in the two settings. As found in a detailed study of patterns in New York City [14], risks differ across Hispanic subgroups. Asian women were at consistently decreased risk for hypertensive disorders, presumably driven by the lower risk among East Asians [14]. While there is the potential for residual confounding due to limited ability to adjust for pre-pregnancy body mass index (BMI) (which tends to be increased in Hispanic women and low in Asian women), these clues to etiology based on ethnic variation have yet to be exploited, with very little prior research on ethnic groups other than Black women.
Evidence for declining risk with higher socioeconomic status was present for some measures and outcomes, as reported elsewhere [13, 15, 16], but not strongly so. The expected marked decrease in risk for parous women was found for gestational hypertension and preeclampsia [10, 11]. Smokers had a modest decrease in risk for preeclampsia and gestational hypertension, also consistent with most previous studies though the magnitude varies considerably and is sometimes not seen, perhaps reflecting different smoking intensity across populations [13, 16–18].
The association between pre-pregnancy weight and risk of hypertensive disorders was striking in magnitude across all the hypertensive disorders, consistent with the studies that have addressed BMI [7, 13, 16, 19], which we could not examine directly given the lack of data on height. The association with weight was stronger for chronic hypertension and gestational hypertension than for preeclampsia. The clear and possibly causal association has implications for understanding etiologic mechanisms and potential for prevention.
We had a large enough study to consider differences in pattern among the hypertensive disorders, and overall, there were more similarities than differences found. We did observe a rising trend over time for both chronic hypertension and gestational hypertension that was not found for preeclampsia, reflecting either unmeasured risk factors or perhaps a residual effect of increasing obesity not fully captured by pre-pregnancy weight, There are some notable differences primarily between chronic hypertension and pregnancy-associated disorders, with parity and smoking associated with reduced risk only for the latter. Advanced maternal age was strongly associated with chronic hypertension but not any of the forms of pregnancy-associated hypertension. The overall patterns for gestational hypertension and preeclampsia, both mild and severe, were quite similar, as reported by Ros et al. [20] using Swedish data. This would suggest that studies that do not clearly distinguish the disorders, or that are not large enough to isolate severe preeclampsia can nonetheless make inferences relevant to the more clinically consequential end of the spectrum. The impact clearly differs, but the etiology of the spectrum of disorders appears to have substantial similarities based on the patterns of occurrence.
There are limitations to the quality of the data that can be derived from administrative sources [3, 21], with both imperfect sensitivity of assessment and inconsistency between the subtypes of hypertensive disorders based on discharge diagnoses and full medical record review. Nonetheless, the positive predictive value and specificity have generally been in the range of 70 % or greater for preeclampsia [3, 22, 23], but there are studies that suggest values as low as 54 % [21]. These tend to be much better than for birth certificate data alone, with positive predictive values as low as 54 % reported and sensitivity of only 33 % compared to medical record review [2]. However, there are no data to assess whether the quality of information differs across subgroups of women, so that the contribution of error to the observed patterns cannot be addressed. The birth certificate predictors of interest tend to be accurate, but there is no quality control over the data collection following delivery and errors undoubtedly arise. There are inherent limitations in the scope and quality of available data: pre-pregnancy weight was reported but not pre-pregnancy height, so that BMI could not be calculated; the outcome measures are based solely on ICD codes and cannot consider timing of onset for pregnancy-induced hypertensive disorders; and stillbirths could not be included due to data limitations.
There are advantages of analyzing a resource of this nature that combines the diagnostic accuracy of hospital discharge data with the breadth of the population available and incorporates birth certificate predictors. Geographically representative populations provide information on social and demographic patterns of risk that is subject to bias when examined in clinically defined populations. The increased risks for Black and Hispanic women warrant both additional etiologic research and careful clinical management, and the marked impact of the obesity epidemic on these disorders is striking, calling for improved weight management prior to pregnancy.
Acknowledgments
The research was supported by Grant R21HD58111 from the National Institute of Child Health and Human Development.
Contributor Information
David A. Savitz, Email: david_savitz@brown.edu, Department of Epidemiology, School of Public Health, Brown University, Box G-S-121-2, Providence, RI 02912, USA
Valery A. Danilack, Department of Epidemiology, School of Public Health, Brown University, Box G-S-121-2, Providence, RI 02912, USA
Stephanie M. Engel, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
Beth Elston, Department of Epidemiology, School of Public Health, Brown University, Box G-S-121-2, Providence, RI 02912, USA.
Heather S. Lipkind, Department of Obstetrics and Gynecology, Yale University School of Medicine, New Haven, CT, USA
References
- 1.Kuklina EV, Ayala C, Callaghan WM. Hypertensive disorders and severe obstetric morbidity in the United States. Obstetrics and Gynecology. 2009;113:1299–1306. doi: 10.1097/AOG.0b013e3181a45b25. [DOI] [PubMed] [Google Scholar]
- 2.DiGiuseppi DL, Aron DC, Ranbom L. Reliability of birth certificate data: A multi-hospital comparison to medical record information. Maternal and Child Health Journal. 2002;6(3):169–179. doi: 10.1023/a:1019726112597. [DOI] [PubMed] [Google Scholar]
- 3.Lydon-Rochelle MT, Holt VL, Cardenas V, Nelson JC, Easterling TR, Gardella C, et al. The reporting of pre-existing maternal medical conditions and complications of pregnancy on birth certificates and in hospital discharge data. American Journal of Obstetrics and Gynecology. 2005;194:125–134. doi: 10.1016/j.ajog.2005.02.096. [DOI] [PubMed] [Google Scholar]
- 4.Tanaka M, Jaamaa G, Kaiser M, Hills E, Soim A, Zhu M, et al. Racial disparity in hypertensive disorders of pregnancy in New York State: A 10-year longitudinal population-based study. American Journal of Public Health. 2007;97(1):163–170. doi: 10.2105/AJPH.2005.068577. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wallis AB, Saftlas AF, Hsia J, Atrash HK. Secular trends in the rates of pre-eclampsia, eclampsia, and gestational hypertension, United States, 1987–2004. American Journal of Hypertension. 2008;21:521–526. doi: 10.1038/ajh.2008.20. [DOI] [PubMed] [Google Scholar]
- 6.Ingram DD, Franco S. NCHS urban–rural classification scheme for counties. National Center for Health Statistics; 2006. Available at: http://www.cdc.gov/nchs/r&d/rdc_urbanrural.htm. [PubMed] [Google Scholar]
- 7.Bodnar LM, Catov JM, Klebanoff MA, Ness RB, Roberts JM. Prepregnancy body mass index and the occurrence of severe hypertensive disorders of pregnancy. Epidemiology. 2007;18:234–239. doi: 10.1097/01.ede.0000254119.99660.e7. [DOI] [PubMed] [Google Scholar]
- 8.Chen XK, Wen SW, Smith G, Leader A, Sutandar M, Yang Q, et al. Maternal age, paternal age, and new-onset hypertension late pregnancy. Hypertension in Pregnancy. 2006;25:217–227. doi: 10.1080/10641950600912992. [DOI] [PubMed] [Google Scholar]
- 9.Klungsøyr K, Morken NH, Irgens L, Vollset SE, Skjærven R. Secular trends in the epidemiology of pre-eclampsia throughout 40 years in Norway: Prevalence, risk factors and perinatal survival. Paediatric and Perinatal Epidemiology. 2012;26:190–198. doi: 10.1111/j.1365-3016.2012.01260.x. [DOI] [PubMed] [Google Scholar]
- 10.Hutcheon JA, Lisonkova S, Joseph KS. Epidemiology of pre-eclampsia and the other hypertensive disorders of pregnancy. Best Practice and Research Clinical Obstetrics and Gynaecology. 2011;25:391–403. doi: 10.1016/j.bpobgyn.2011.01.006. [DOI] [PubMed] [Google Scholar]
- 11.Zhang J, Zeisler J, Hatch MC, Berkowitz G. Epidemiology of pregnancy-induced hypertension. Epidemiologic Reviews. 1997;19:218–232. doi: 10.1093/oxfordjournals.epirev.a017954. [DOI] [PubMed] [Google Scholar]
- 12.Tan KH, Kwek K, Yeo GS. Epidemiology of pre-eclampsia and eclampsia at the KK Women’s and Children’s Hospital, Singapore. Singapore Medical Journal. 2006;47(1):48–53. [PubMed] [Google Scholar]
- 13.Myatt L, Clifton RG. First-trimester prediction of preeclampsia in nulliparous women at low risk. Obstetrics and Gynecology. 2012;119:1234–1242. doi: 10.1097/AOG.0b013e3182571669. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Gong J, Savitz DA, Stein CR, Engel SM. Maternal ethnicity and pre-eclampsia in New York City, 1995–2003. Paediatric and Perinatal Epidemiology. 2012;26:45–52. doi: 10.1111/j.1365-3016.2011.01222.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Silva LM, Coolman M, Steegers E, Jaddoe V, Moll H, Hofman A, et al. Maternal educational level and risk of gestational hypertension: The Generation R Study. Journal of Human Hypertension. 2008;22:483–492. doi: 10.1038/jhh.2008.22. [DOI] [PubMed] [Google Scholar]
- 16.Coghill AE, Hansen S, Littman AJ. Risk factors for eclampsia: A population-based study in Washington State, 1987–2007. American Journal of Obstetrics and Gynecology. 2011;205:553.e1–7. doi: 10.1016/j.ajog.2011.06.079. [DOI] [PubMed] [Google Scholar]
- 17.Stone CD, Diallo O, Shyken J, Leet T. The combined effect of maternal smoking and obesity on the risk of preeclampsia. Journal of Perinatal Medicine. 2007;35(1):28–31. doi: 10.1515/JPM.2007.003. [DOI] [PubMed] [Google Scholar]
- 18.England L, Zhang J. Smoking and risk of pre-eclampsia: A systematic review. Frontiers in Bioscience. 2007;12:2471–2483. doi: 10.2741/2248. [DOI] [PubMed] [Google Scholar]
- 19.Marik PE. Hypertensive disorders of pregnancy. Postgraduate Medicine. 2009;121(2):69–76. doi: 10.3810/pgm.2009.03.1978. [DOI] [PubMed] [Google Scholar]
- 20.Ros HS, Cnattingius S, Lipworth L. Comparison of risk factors for pre-eclampsia and gestational hypertension in a population-based cohort study. American Journal of Epidemiology. 1998;147:1062–1070. doi: 10.1093/oxfordjournals.aje.a009400. [DOI] [PubMed] [Google Scholar]
- 21.Geller SE, Ahmed S, Brown ML, Cox SM, Rosenberg D, Kilpatrick SJ. International classification of diseases—9th revision coding for preeclampsia: How accurate is it? American Journal of Obstetrics and Gynecology. 2004;190:1629–1633. doi: 10.1016/j.ajog.2004.03.061. [DOI] [PubMed] [Google Scholar]
- 22.Klemmensen AK, Olsen SF, Osterdal ML, Tabor A. Validity of preeclampsia-related diagnoses recorded in a national hospital registry and in a postpartum interview of the women. American Journal of Epidemiology. 2007;166(2):117–124. doi: 10.1093/aje/kwm139. [DOI] [PubMed] [Google Scholar]
- 23.Yasmeen S, Romano PS, Schembri ME, Keyzer JM, Gilber WM. Accuracy of obstetric diagnoses and procedures in hospital discharge data. American Journal of Obstetrics and Gynecology. 2006;194(4):992–1001. doi: 10.1016/j.ajog.2005.08.058. [DOI] [PubMed] [Google Scholar]