Pre-eclampsia rates in the United States, 1980-2010: age-period-cohort analysis

Cande V Ananth, Katherine M Keyes, Ronald J Wapner, Cande V Ananth, Katherine M Keyes, Ronald J Wapner

Abstract

Objective: To estimate the contributions of biological aging, historical trends, and birth cohort effects on trends in pre-eclampsia in the United States.

Design: Population based retrospective study.

Setting: National hospital discharge survey datasets, 1980-2010, United States.

Participants: 120 million women admitted to hospital for delivery.

Main outcome measures: Temporal changes in rates of mild and severe pre-eclampsia in relation to maternal age, year of delivery, and birth cohorts. Poisson regression as well as multilevel age-period-cohort models with adjustment for obesity and smoking were incorporated.

Results: The rate of pre-eclampsia was 3.4%. The age-period-cohort analysis showed a strong age effect, with women at the extremes of maternal age having the greatest risk of pre-eclampsia. In comparison with women delivering in 1980, those delivering in 2003 were at 6.7-fold (95% confidence interval 5.6-fold to 8.0-fold) increased risk of severe pre-eclampsia. Period effects declined after 2003. Trends for severe pre-eclampsia also showed a modest birth cohort effect, with women born in the 1970s at increased risk. Compared with women born in 1955, the risk ratio for women born in 1970 was 1.2 (95% confidence interval 1.1 to 1.3). Similar patterns were also evident for mild pre-eclampsia, although attenuated. Changes in the population prevalence of obesity and smoking were associated with period and cohort trends in pre-eclampsia but did not explain the trends.

Conclusions: Rates of severe pre-eclampsia have been increasing in the United States and age-period-cohort effects all contribute to these trends. Although smoking and obesity have driven these trends, changes in the diagnostic criteria may have also contributed to the age-period-cohort effects. Health consequences of rising obesity rates in the United States underscore that efforts to reduce obesity may be beneficial to maternal and perinatal health.

Conflict of interest statement

Competing interests: None of the authors report any potential conflict of interest.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Figures

https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4793346/bin/anac012786.f1_default.jpg
Fig 1 Temporal changes in prevalence of pre-eclampsia: United States, 1980 to 2010
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4793346/bin/anac012786.f2_default.jpg
Fig 2 Age-period-cohort influences on trends in mild pre-eclampsia: United States, 1980 to 2010. Open circles refer to reference group for birth cohort and period. Adjusted risk ratio (red dot) for 1970 birth cohort (relative to reference cohort 1955) is 1.2 (95% confidence interval 1.1 to 1.2). Similarly, risk ratio (blue dot) for 2003 birth period (relative to reference period 1980) is 1.7 (95% confidence interval 1.6 to 1.8). Small hash marks on bottom x-axis pertain to knot locations for birth cohort, and hash marks on top axis refer to knot locations for period. Estimates for period effect are second order derivatives, indicating that slope of period effect for mild pre-eclampsia has been decelerating since 2003
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4793346/bin/anac012786.f3_default.jpg
Fig 3 Age-period-cohort influences on trends in severe pre-eclampsia: United States, 1980 to 2010. Open circles refer to reference group for birth cohort and period. Adjusted risk ratio (red dot) for 1970 birth cohort (relative to reference cohort 1955) is 1.2 (95% confidence interval 1.1 to 1.3). Similarly, risk ratio (blue dot) for 2003 birth period (relative to reference period 1980) is 6.7 (95% confidence interval 5.6 to 8.0). Small hash marks on bottom x axis pertain to knot locations for birth cohort, and hash marks on top axis refer to knot locations for period. Estimates for period effect are second order derivatives, indicating that slope of period effect for severe pre-eclampsia has been decelerating since 2003

References

    1. Campbell DM, MacGillivray I, Carr-Hill R. Pre-eclampsia in second pregnancy. Br J Obstet Gynaecol 1985;92:131-40.
    1. Basso O, Christensen K, Olsen J. Higher risk of pre-eclampsia after change of partner. An effect of longer interpregnancy intervals? Epidemiology 2001;12:624-9.
    1. Skjaerven R, Wilcox AJ, Lie RT. The interval between pregnancies and the risk of preeclampsia. N Engl J Med 2002;346:33-8.
    1. Hernandez-Diaz S, Toh S, Cnattingius S. Risk of pre-eclampsia in first and subsequent pregnancies: prospective cohort study. BMJ 2009;338:b2255.
    1. Conde-Agudelo A, Belizan JM, Diaz-Rossello JL. Epidemiology of fetal death in Latin America. Acta Obstet Gynecol Scand 2000;79:371-8.
    1. Zhang J, Troendle JF, Levine RJ. Risks of hypertensive disorders in the second pregnancy. Paediatr Perinat Epidemiol 2001;15:226-31.
    1. Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet 2008;371:75-84.
    1. Ananth CV, Basso O. Impact of pregnancy-induced hypertension on stillbirth and neonatal mortality. Epidemiology 2010;21:118-23.
    1. Irgens HU, Reisaeter L, Irgens LM, Lie RT. Long term mortality of mothers and fathers after pre-eclampsia: population based cohort study. BMJ 2001;323:1213-7.
    1. Ray JG, Vermeulen MJ, Schull MJ, Redelmeier DA. Cardiovascular health after maternal placental syndromes (CHAMPS): population-based retrospective cohort study. Lancet 2005;366:1797-803.
    1. Ness RB, Sibai BM. Shared and disparate components of the pathophysiologies of fetal growth restriction and preeclampsia. Am J Obstet Gynecol 2006;195:40-9.
    1. Zhang J, Zeisler J, Hatch MC, Berkowitz G. Epidemiology of pregnancy-induced hypertension. Epidemiol Rev 1997;19:218-32.
    1. Wallis AB, Saftlas AF, Hsia J, Atrash HK. Secular trends in the rates of preeclampsia, eclampsia, and gestational hypertension, United States, 1987-2004. Am J Hypertens 2008;21:521-6.
    1. Bodnar LM, Ness RB, Markovic N, Roberts JM. The risk of preeclampsia rises with increasing prepregnancy body mass index. Ann Epidemiol 2005;15:475-82.
    1. Getahun D, Ananth CV, Oyelese Y, Chavez MR, Kirby RS, Smulian JC. Primary preeclampsia in the second pregnancy: effects of changes in prepregnancy body mass index between pregnancies. Obstet Gynecol 2007;110:1319-25.
    1. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA 2010;303:235-41.
    1. Reither EN, Hauser RM, Yang Y. Do birth cohorts matter? Age-period-cohort analyses of the obesity epidemic in the United States. Soc Sci Med 2009;69:1439-48.
    1. Robinson WR, Keyes KM, Utz RL, Martin CL, Yang Y. Birth cohort effects among US-born adults born in the 1980s: foreshadowing future trends in US obesity prevalence. Int J Obes (Lond) 2013;37:448-54.
    1. Robinson WR, Utz RL, Keyes KM, Martin CL, Yang Y. Birth cohort effects on abdominal obesity in the United States: the silent generation, baby boomers and generation X. Int J Obes (Lond) 2013;37:1129-34.
    1. England L, Zhang J. Smoking and risk of preeclampsia: a systematic review. Front Biosci 2007;12:2471-83.
    1. Garrett BE, Dube SR, Trosclair A, Caraballo RS, Reshacek TF; Centers for Disease Control and Prevention (CDC). Cigarette smoking—United States, 1965-2008. MMWR Surveill Summ 2011;60(Suppl):109-13.
    1. Keyes KM, March D, Link BG, Chilcoat HD, Susser E. Do socio-economic gradients in smoking emerge differently across time by gender? Implications for the tobacco epidemic from a pregnancy cohort in California, USA. Soc Sci Med 2013;76:101-6.
    1. Preston SH, Wang H. Sex mortality differences in the United States: the role of cohort smoking patterns. Demography 2006;43:631-46.
    1. DeFrances CJ, Cullen KA, Kozak LJ. National Hospital Discharge Survey: 2005 annual summary with detailed diagnosis and procedure data. Vital and health statistics Series 13, Data from the National Health Survey 2007(165):1-209.
    1. Kozak LJ, Owings MF, Hall MJ. National Hospital Discharge Survey: 2001 annual summary with detailed diagnosis and procedure data. Vital and health statistics Series 13, Data from the National Health Survey 2004(156):1-198.
    1. Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. Am J Obstet Gynecol 2000;183:S1-22.
    1. ACOG practice bulletin. Diagnosis and management of preeclampsia and eclampsia. No 33, Jan 2002. Obstet Gynecol 2002;99:159-67.
    1. Dennison C, Pokras R. Design and operation of the National Hospital Discharge Survey: 1988 redesign. Vital and health statistics Series 1, Programs and collection procedures 2000(39):1-42.
    1. National Health Interview Survey. National Center for Health Statistics, Centers for Disease Control and Prevention. . 2013.
    1. Glenn ND. Cohort analysis. 2nd ed. Sage, 2005.
    1. Yang Y. Age/period/cohort distinctions. In: Markides KS, ed. Encyclopedia of health and aging. Sage, 2007.
    1. Carstensen B. Age-period-cohort models for the Lexis diagram. Stat Med 2007;26:3018-45.
    1. Clayton D, Schifflers E. Models for temporal variation in cancer rates. II: age-period-cohort models. Stat Med 1987;6:469-81.
    1. Holford TR. Analysing the temporal effects of age, period and cohort. Stat Methods Med Res 1992;1:317-37.
    1. Hastie TJ, Tibshirani RJ. Generalized Additive Models. Chapman and Hall, 1990.
    1. Carstensen B, Plummer M, Hils M, Laara E. Epi: a package for statistical analysis in epidemiology (R package version 1.1.34). 2012. .
    1. Yang Y, Land K. Chapter 7. Mixed effects models: hierarchical APC-cross-classified random effects models (HAPC-CCREM), Part I: the basics. In: Yang Y, Land K, eds. Age-period-cohort analysis: new models, methods, and empirical applications. Chapman and Hall/CRC Interdisciplinary Statistics, 2013.
    1. 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. Am J Epidemiol 2007;166:117-24.
    1. Yasmeen S, Romano PS, Schembri ME, Keyzer JM, Gilbert WM. Accuracy of obstetric diagnoses and procedures in hospital discharge data. Am J Obstet Gynecol 2006;194:992-1001.
    1. Mangos GJ, Spaan JJ, Pirabhahar S, Brown MA. Markers of cardiovascular disease risk after hypertension in pregnancy. J Hypertens 2012;30:351-8.
    1. Ness RB, Roberts JM. Heterogeneous causes constituting the single syndrome of preeclampsia: a hypothesis and its implications. Am J Obstet Gynecol 1996;175:1365-70.
    1. Engel SM, Janevic TM, Stein CR, Savitz DA. Maternal smoking, preeclampsia, and infant health outcomes in New York City, 1995-2003. Am J Epidemiol 2009;169:33-40.
    1. Catov JM, Ness RB, Kip KE, Olsen J. Risk of early or severe pre-eclampsia related to pre-existing conditions. Int J Epidemiol 2007;36:412-9.
    1. Cnattingius S. The epidemiology of smoking during pregnancy: smoking prevalence, maternal characteristics, and pregnancy outcomes. Nicotine Tob Res 2004;6(Suppl 2): S125-40.
    1. Bombard JM, Dietz PM, Galavotti C, England LJ, Tong VT, Hayes DK, et al. Chronic diseases and related risk factors among low-income mothers. Matern Child Health J 2012;16:60-71.
    1. Sibai BM. Intergenerational factors: a missing link for preeclampsia, fetal growth restriction, and cardiovascular disease? Hypertension 2008;51:993-4.
    1. Roberts JM, Pearson GD, Cutler JA, Lindheimer MD. Summary of the NHLBI working group on research on hypertension during pregnancy. Hypertens Pregnancy 2003;22:109-27.
    1. Klungsoyr K, Morken NH, Irgens L, Vollset SE, Skjaerven R. Secular trends in the epidemiology of pre-eclampsia throughout 40 years in Norway: prevalence, risk factors and perinatal survival. Paediatr Perinat Epidemiol 2012;26:190-8.
    1. Roberts CL, Ford JB, Algert CS, Antonsen S, Chalmers J, Cnattingius S, et al. Population-based trends in pregnancy hypertension and pre-eclampsia: an international comparative study. BMJ Open 2011;1:e000101.

Source: PubMed

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