| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
ORIGINAL RESEARCH |
From the Departments of *Obstetrics and Gynecology and Medical Biostatistics, University of Vermont College of Medicine, Burlington, Vermont.
 |
ABSTRACT |
|---|
TOP
 ABSTRACT METHODSRESULTSDISCUSSIONREFERENCES |
|---|
METHODS: Between January 1995 and August 2003, we identified 142 primiparous women with singleton pregnancies who met the American College of Obstetricians and Gynecologists’ definition for preeclampsia and compared them with 7,762 primiparous control deliveries. We analyzed rates of preeclampsia by individual month and 3-month seasonal blocks based on conception and delivery. Data were analyzed with the 
2 test, and logistic regression and odds ratios were calculated where appropriate.
RESULTS: Preeclampsia occurred in 1.8% of singleton primiparous gestations (142/7,904). Cases were younger than controls (26.5 ± 5.6 versus 28.0 ± 0 6.0 years, P < .003), of similar race (97% white versus 96% white, P = .69), and equally likely to have a female child (45% versus 48%, P = .41). We found no significant association of month (logistic regression P = .20) of delivery with the risk of preeclampsia. There was a significant association of month (P = .003) of conception with risk of preeclampsia. Conception during the summer months had the highest risk (incidence 2.3%; odds ratio 1.7; 95% confidence limits 1.06, 2.75) compared with spring (incidence 1.4%). Fall (1.7%) and winter (1.6%) conceptions were associated with intermediate rates of preeclampsia.
CONCLUSION: We identified a seasonal variation in preeclampsia that appears to be more strongly related to timing of conception than to the timing of delivery. The highest incidence of preeclampsia was associated with conception in the summer months.
LEVEL OF EVIDENCE: II-2
Additional evidence supportive of a central role for plasma volume in the etiology of preeclampsia comes from studies examining sympathetic tone. Investigators have observed that an autonomic balance favoring increased sympathetic nervous system activity can be identified in women 1) in whom preeclampsia develops, 2) in whom preeclampsia is diagnosed, or 3) who had experienced preeclampsia and were postpartum at the time of evaluation.10–12 We have observed an inverse relationship between sympathetic activity and plasma volume in young healthy women before a first pregnancy where elevated sympathetic tone is associated with low plasma volume.13
In humans, plasma volume demonstrates seasonal variation, with plasma contraction observed during the cold winter months and expansion in warm summer months.14–16 Differences in incidences of preeclampsia, examined exclusively on the basis of delivery timing, have also been noted to have seasonal variation, but results have been inconsistent.17–20 Based on our belief that preconceptional factors, specifically plasma volume and sympathetic tone, are central to the development of preeclampsia, we hypothesized that the incidence of preeclampsia would show seasonal variation in our population and that the incidence would be highest if conception occurred as ambient temperatures rise after the prolonged plasma volume constriction of winter. This would account for a potentially accelerated volume expansion in early pregnancy (during the summer) superimposed on a volume-restricted condition. These are conditions that we have suggested contribute to the etiology of preeclampsia.3 We also specifically hypothesized that the seasonal variation in preeclampsia would be better defined by the timing of conception rather than by the timing of delivery.
|
METHODS |
|---|
|
TOP
ABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
For each case and control, we recorded delivery date and best obstetric estimate of gestational age and back-calculated the date of last menstrual period as an estimate of the timing of conception. All subjects had ultrasonographic confirmation of gestational age. Potential confounding variables including maternal age, race, and newborn sex were recorded. Smoking status was not reliably recorded in the database and could not be evaluated as a confounder.
The demographic characteristics of preeclampsia cases and controls were compared by using t tests for continuous variables and 2 tests for categorical measures. Raw rates of preeclampsia were computed for each calendar month and season, which was defined as winter (December through February), spring (March through May), summer (June through August), and fall (September through November). Summer and winter seasons were defined as the 3 consecutive months with the warmest and coldest average monthly temperatures, respectively. All 95% confidence intervals (CIs) presented for monthly and seasonal rates of preeclampsia are exact CIs. The odds of developing preeclampsia across months and seasons based on both delivery date and conception date (last menstrual period) were examined using logistic regression. Logistic regression was used to adjust for differences between preeclampsia cases and controls with respect to maternal age. Odds ratios for month of conception and month of delivery are based on March being defined as the reference month. Estimated odds ratios (ORs) presented for seasons are relative to spring. This study was reviewed and approved by the University of Vermont Institutional Review Board for Human Research.
|
RESULTS |
|---|
|
TOP
ABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Statistically significant differences were noted in the maternal age of the preeclampsia and control groups. The women in whom preeclampsia developed were significantly younger than the controls (26.5 ± 5.6 versus 28.0 ± 6.0 years, respectively, t test, P < .003). We found no significant differences between preeclamptic and control groups in race (97% versus 96% white, respectively) or the sex of the child (45% versus 48% female, respectively). In addition, we examined for the presence of known risk factors for the development of preeclampsia, including underlying diseases such as diabetes mellitus, hypertension, chronic renal disease, and known thrombophilias. For each of the entities identified there were very few women affected, and there were no significant differences between groups.
The first set of analyses focused on examining the relationship between month of delivery or conception and the odds of developing preeclampsia. Adjusting for age differences between preeclampsia cases and controls using logistic regression, we found no significant association of the incidence of preeclampsia with month of delivery (logistic regression Wald 211 = 14.6, P = .20) of delivery. Raw rates of preeclampsia ranged from 1.1% to 2.8% per month. In contrast, there was a significant relationship between month of conception, as defined by the last menstrual period, and the odds developing preeclampsia (logistic regression Wald 211 = 28.7, P = .002). The incidence for each month of conception is displayed in Fig. 1. The incidence of preeclampsia was highest when the date of the last menstrual period was in June (3.5%; 95% CI 2.3–5.1%). The incidence was at its lowest in March (0.7%; 95% CI 0.2– 1.8%) and showed a steady increase through June.
|
Seasonal rates of preeclampsia were also evaluated based on both delivery and conception. When defined by season of delivery, the rates of preeclampsia were as follows: winter 2.0% (95% CI 1.4–2.8%), spring 2.2% (95% CI 1.7–3.0%), summer 1.4% (95% CI 1.0–2.1%), fall 1.4% (95% CI 0.9–2.1%). Winter and spring deliveries showed no significant differences in the rates of preeclampsia. Summer delivery was associated with a reduced odds of developing preeclampsia when compared with spring delivery (OR = 0.63, 95% CI 0.39–0.99). Delivery in the fall was also associated with a reduced incidence of preeclampsia relative to spring delivery (OR = 0.60, 95% CI 0.37–0.98).
The seasonal rates associated with the incidence of preeclampsia based on last menstrual period are displayed in Fig. 2. We identified the highest incidence of preeclampsia when conception occurred in the summer months, 2.3% (95% CI 1.8–3.1%). The incidence of preeclampsia associated with spring, fall and winter conceptions were 1.4% (95% CI 0.9–2.1%), 1.7% (95% CI 1.2–2.4%) and 1.6% (95% CI 1.1–2.3%) respectively. Results based on logistic regression indicated that last menstrual period during the summer was associated with significantly increased odds of developing preeclampsia, (OR 1.7; 95% C.I 1.1–2.8) compared with last menstrual period during spring. The odds for the occurrence of preeclampsia with last menstrual periods occurring in the fall or winter were not significantly increased relative to spring, fall (OR 1.2; 95% CI 0.7–2.1), or winter (OR 1.1; 95% CI 0.7–1.9).
|
|
DISCUSSION |
|---|
|
TOP
ABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Most contemporary data have examined the seasonal variation in the incidence of preeclampsia by examining the timing of clinical recognition of disease. In Zimbabwe, a peak incidence of preeclampsia was found in women delivering in December and January. This period corresponded to the end of the dry season and the beginning of the rainy season.18 In Norway, cases of preeclampsia peaked in the winter months,17 and similarly, the incidence of preeclampsia peaked in women delivering in November in Kuwait20 and between January and March in Israel.19 These studies chose to focus on the seasonal variation of preeclampsia based on timing of delivery. We chose to study its incidence based on timing of conception as estimated by last menstrual period, to better examine our theory that preconceptional factors contribute importantly to the development of preeclampsia, and in support of the many studies showing that subclinical evidence of preeclampsia can be identified long before clinical recognition of disease. Our data are consistent with the majority of previously published reports that have examined either the timing of delivery or conception and have identified a high incidence of preeclampsia with summertime conception and delivery in the winter to spring. There is normally a high correlation between conception and delivery timing, but this typically consistent relationship may be disrupted by the high and variable degree of preterm delivery associated with preeclampsia. The increased frequency of preeclampsia at the time of delivery, predominantly noted during winter and spring, is consistent with a high contribution of prematurity and summertime conception.
The specific contribution of season to the incidence of preeclampsia remains unknown, but seasonal effects could include dietary changes, humidity changes, changes in circadian rhythms, or differences in ambient temperature. Numerous studies have pointed to an increased incidence of preeclampsia in women delivering in winter months, and these findings have all been roughly consistent in implying late spring and/or summer conceptions.17–20 Regional variations identified between studies may be dependent on local climatic factors. The data for the current study were collected in Burlington, Vermont, which is located at 44.5 degrees north latitude and at sea level. Average monthly temperatures and rainfall, for the time frame matching the study data collection, were acquired from the U.S. National Weather Service station in Burlington, Vermont. The results are depicted in Figs. 3 and 4 for comparison with other databases. As can be observed in these figures, the average monthly temperature varies approximately 3-fold over the course of the year and shows remarkable consistency between years. Average rainfall is highly correlated to average temperature (r = 0.89, P < .01) but shows less variation throughout the year and greater variability between months.
|
|
It might be argued that our study identified a relatively low overall frequency of preeclampsia, based on some published estimates of the frequency of preeclampsia, and that this introduced a selection bias that might account for the findings of seasonal variation.27 We believe, however, that our detection rate is consistent with existing literature examining the frequency of well-documented preeclampsia. Saftlas et al,28 reviewing 7 years worth of data from the U.S. National Hospital Discharge Survey (in which patient records are individually evaluated), found a frequency of preeclampsia of 2.6%, representing approximately 100,200 cases of preeclampsia per year. Odegard et al29 found a frequency of preeclampsia of 2.4% after examining the Norwegian Medical Birth Registry, which uses standardized forms to record information on all deliveries, and reviewing delivery data for a 3-year period encompassing 12,804 births. In the current study, we excluded women with HELLP syndrome with the goal of narrowly defining the phenotype that we believed to be at risk for seasonal effects. If we include those with HELLP in our diagnosis of preeclampsia, the current study has an incidence of 2.2%. We suspect that the occasionally higher estimates of the rates of preeclampsia are the result of databases in which there may be a high incidence of miscoding of preeclampsia, as has been recently identified or in unique populations.27,30 We do not have a clear explanation for the low and apparently outlying frequency of preeclampsia associated with July conception other than to note that with a low overall rate of preeclampsia, a small change in the number of cases in 1 month may contribute disproportionately to apparent rates of disease.
In this dataset, we did not segregate those patients who were referred to our institution for care from those who had ongoing local care. It is therefore possible that a seasonal variation in the identification of preeclampsia is the result of a seasonal change in referral patterns. Interpreted in this light, these data suggest that we receive more referrals during the winter and early spring months, when the preeclampsia is clinically identified. To address this possibility, we examined the frequency of transports by season during the period of data collection and found no association of transport with season (winter, 11 + 5 transports per month; spring, 13 + 4; summer, 11 + 3; fall, 11 + 3; P = .154, analysis of variance). Overall, the relative consistency of the findings of seasonal variations in preeclampsia suggests a real and sustained environmental impact.
|
Footnotes |
|---|
Reprints are not available. Address correspondence to: Ira Bernstein, MD, Department of Obstetrics and Gynecology, Burgess 217, FAHC, 111 Colchester Avenue, Burlington VT 05401–1435; e-mail: ira.bernstein{at}uvm.edu.
Received May 28, 2004. Received in revised form July 27, 2004. Accepted August 5, 2004.
doi:10.1097/01.AOG.0000143306.88438.cf
|
REFERENCES |
|---|
|
TOP
ABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
2. Koonin LM, Mackay AP, Berg CJ, Atrash HK, Smith JC. Pregnancy-related mortality surveillance—United States, 1987–1990. MMWR CDC Surveill Summ 1997;46:17–36.[Medline]
3. Bernstein IM, Meyer MC, Osol G, Ward K. Intolerance to volume expansion: a theorized mechanism for the development of preeclampsia. Obstet Gynecol 1998;92:306–8.[Abstract]
4. Ward K, Hata A, Jeunemaitre X, Helin C, Nelson L, Namikawa C, et al. A molecular variant of angiotensinogen associated with preeclampsia. Nat Genet 1993;4:59–61.[Medline]
5. Bernstein IM, Ziegler W, Stirewalt W, Brumsted J, Ward K. Angiotensinogen genotype and plasma volume in nulligravid women. Obstet Gynecol 1998;92:171–3.[Abstract]
6. van Beek E, Ekhart THA, Schiffers PMH, Eyck J, Peeters LLH, Leeuw PW. Persistent abnormalities in plasma volume and renal hemodynamics in patients with a history of preeclampsia. Am J Obstet Gynecol 1998;179:690–6.[Medline]
7. Silver HM, Seebeck M, Carlson R. Comparison of total blood volume in normal, preeclamptic, and nonproteinuric gestational hypertensive pregnancy by simultaneous measurement of red blood cell and plasma volumes. Am J Obstet Gynecol 1998;179:87–93.[Medline]
8. Spaanderman ME, Aardenburg R, Ekhart TH, van Eyndhoven HW, van der Heijden OW, van Eyck J, et al. Non-pregnant circulatory volume status predicts subsequent pregnancy outcome in normotensive thrombophilic formerly preeclamptic women. Eur J Obstet Gynecol Reprod Biol 2001;95:218–21.[Medline]
9. Aardenburg R, Spaanderman MEA, Ekhart TH, van Eijndhoven HW, van der Hrijden OWH, Peeters LLH. Low plasma volume following pregnancy complicated by pre-eclampsia predisposes for hypertensive disease in a next pregnancy. Br J Obstet Gynaecol 2003;110:1001–6.
10. Woisetschlager C, Waldenhofer U, Bur A, Herkner H, Kiss H, Binder M, et al. Increased blood pressure response to the cold pressor test in pregnant women developing preeclampsia. J Hypertens 2000;18:399–403.[Medline]
11. Schobel HP, Fischer T, Heuszer K, Geiger H, Schmieder RE. Preeclampsia: a state of sympathetic overactivity. N Engl J Med 1996;335:1480–5.
12. Eneroth E, Westgren M, Ericsson M, Lindblad LE, Storck N. 24-hour ECG frequency-domain measures in preeclamptic and healthy pregnant women during and after pregnancy. Hypertens Pregnancy 1999;18:1–9[Medline]
13. Bernstein IM, Shapiro RE, Whitsel A, Schonberg AL. Relationship of plasma volume to sympathetic tone in nulliparous women. Am J Obstet Gynecol 2003;188:938–42.[Medline]
14. Kristal-Boneh E, Froom P, Harari G, Ribak J. Seasonal differences in blood cell parameters and the association with cigarette smoking. Clin Lab Haematol 1997;19:177–81.[Medline]
15. Shapiro Y, Hubbard RW, Kimbrough CM, Pandolf KB. Physiological and hematologic responses to summer and winter dry-heat acclimation. J Appl Physiol Respir Environ Exerc Physiol 1981;50:792–8.
16. Morimoto T, Shiraki K, Asayama M. Seasonal difference in responses of body fluids to heat stress. Jpn J Physiol 1974;24:249–62.[Medline]
17. Magnus P, Eskild A. Seasonal variation in the occurrence of preeclampsia. Br J Obstet Gynaecol 2001;108:1116–9.
18. Wacker J, Schulz M, Fruhauf J, Chiwora F, Solomayer E, Bastert G. Seasonal change in the incidence of preeclampsia in Zimbabwe. Acta Obstet Gynecol Scand 1998;77:712–6.[Medline]
19. Bider D, Sivan E, Seidman DS, Dulitzky M, Mashiach S, Serr DM, et al. Meteorological factors in hypertensive disorders, vaginal bleeding and premature rupture of membranes during pregnancy. Gynecol Obstet Invest 1991;32:88–90.[Medline]
20. Makhseed M, Musini VM, Ahmed MA, Monem RA. Influence of seasonal variation on pregnancy-induced hypertension and/or preeclampsia. Aust N Z J Obstet Gynaecol 1999;39:196–9.[Medline]
21. Chesley LC. History and epidemiology of preeclampsia-eclampsia. Clin Obstet Gynecol 1984;27:801–20.[Medline]
22. Levine RJ, Hauth JC, Curet LB, Sibai BM, Catalano PM, Morris CD, et al. Trial of calcium to prevent preeclampsia. N Engl J Med 1997;337:69–76.
23. Taufield PA, Ales KL, Resnick LM, Druzin ML, Gertner JM, Laragh JH. Hypocalciuria in preeclampsia N Engl J Med 1987;316:715–8.
24. Zemel MB, Zemel PC, Berry S, Norman G, Kowalczyk C, Sokol RJ, et al. Altered platelet calcium metabolism as an early predictor of increased peripheral vascular resistance and preeclampsia in urban black women. N Engl J Med 1990;323:434–8.[Abstract]
25. Salvig JD, Oslen SF, Secher NJ. Effects of fish oil supplementation in late pregnancy on blood pressure: a randomized controlled trial of fish oil in high risk pregnancy. Br J Obstet Gynaecol 1996;103:529–33.[Medline]
26. Chappell LC, Seed PT, Briley AL, Kelly FJ, Lee R, Hunt BJ, et al. Effect of antioxidants on the occurrence of pre-eclampsia in women at increased risk: a randomized trial. Lancet 1999;354:810–6.[Medline]
27. Hauth JC, Ewell MG, Levine RJ, Esterlitz JR, Sibai B, Curet LB, et al. Pregnancy outcomes in healthy nulliparas who develop hypertension. Calcium for Preeclampsia Prevention Study Group. Obstet Gynecol 2000;95:24–8.
28. Saftlas AF, Olson DR, Franks AL, Atrash HK, Pokras R. Epidemiology of preeclampsia and eclampsia in the United States, 1979–1986. Am J Obstet Gynecol 1990;163:460–5.[Medline]
29. Odegard RA, Vatten LJ, Nilsen ST, Salvesev KA, Austgulen R. Preeclampsia and fetal growth. Obstet Gynecol 2000;96:950–5.
30. Geller SE, Ahmed S, Brown ML, Cox SM, Rosenberg D, Kilpatrick SJ. International Classification of Disease, 9th Revision coding for preeclampsia: how accurate is it? Am J Obstet Gynecol 2004;190:1629–34.[Medline]
This article has been cited by other articles:
|
|
 |
|
  K.S. Knox and J.C. Baker Genome-wide expression profiling of placentas in the p57Kip2 model of pre-eclampsia Mol. Hum. Reprod., April 1, 2007; 13(4): 251 - 263. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
