Birth Weight of Term Born Offspring in relation to Long-Term Maternal Cardiovascular Morbidity and Mortality

Birth Weight of Term Born Offspring in relation to Long-Term Maternal Cardiovascular Morbidity and Mortality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Birth Weight of Term Born Offspring in relation to Long-Term Maternal Cardiovascular Morbidity and Mortality Pauline Kromann Reim, Line Engelbrechtsen, Lise Geisler Bjerregaard, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6749003/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Feb, 2026 Read the published version in European Journal of Epidemiology → Version 1 posted 4 You are reading this latest preprint version Abstract Background Previous studies have identified associations between offspring birthweight and future maternal cardiovascular health, but many studies lack sufficient adjustment for confounders such as pregnancy complications, gestational age, maternal body mass index (BMI), and smoking. This study aimed to assess whether the association between term offspring BW and maternal cardiovascular risk is independent of these factors. Methods We used data from the Copenhagen Perinatal Cohort (1959–1961). After excluding women with diabetes, preeclampsia, preterm births, and twin pregnancies, 5,766 women remained. Cardiovascular outcomes were obtained from Danish national registries with up to 45 years of follow-up. Hazard ratios (HR) with 95% confidence intervals (CI) were estimated using Cox regression, adjusting for smoking during pregnancy, maternal BMI, hypertension, and gestational age. Additional analyses were conducted in populations stratified by smoking status and adjusted for cigarette consumption per day. Results Offspring BW below 3000 grams was associated with higher maternal cardiovascular mortality (< 2500 grams: 2.16 [1.54–3.03], 2500–2999 grams: 1.41 [1.09–1.81]) compared to the reference category (offspring BW 3500–3999 grams). The risk of maternal major cardiovascular events and stroke was higher when offspring BW was below 2500 grams (1.35 [1.01–1.79], 1.51 [1.09–2.08]) and lower if offspring BW was above 3999 (0.78 [95% CI 0.61–0.99], 0.78 [0.59–1.03]) compared to the reference. No association was found with ischemic heart disease. Associations persisted after stratification by smoking. Conclusions Lower BW of term offspring from uncomplicated, singleton pregnancies is inversely associated with long-term maternal cardiovascular risk, independent of smoking during pregnancy. Birth weight pregnancy maternal health cardiovascular disease Figures Figure 1 Introduction The accommodation of the maternal body to the physiological demands and cardiovascular adaptations of pregnancy can enhance or expose underlying disease risk, and has been suggested to offer an early-life stress-test predicting future maternal health[1, 2]. As such, pregnancy may provide a window of opportunity to postpone or prevent development of manifest disease[3–5]. Being the endpoint of intrauterine growth, offspring birth weight (BW) may serve as an indicator of the extent to which these maternal adaptations have succeeded and hereby provide valuable information about the future health of the mother. Observational studies have revealed an inverse association between offspring BW and subsequent maternal cardiovascular disease (CVD)[6–8]and mortality [9–11]. However, the underlying mechanisms behind these associations remain unclear and are likely affected by pregnancy characteristics and shaped by a combination of genetic and environmental factors[12]. Most previous studies evaluating the association between offspring BW and maternal health and disease are limited by factors possibly introducing significant bias to the results: either lack of reliable information about offspring BW[13], gestational age (GA) at birth[6, 9] or insufficient adjustment for potential confounding factors such as maternal medical conditions during pregnancy (including pregnancy complications)[7, 8, 10], and smoking during pregnancy[6–10]. The fetus has the most substantial weight gain during the third trimester with a fetal weight velocity peak around week 35[14]. If GA is not accounted for, premature offspring may be categorized as growth restricted even when they are appropriate in size or large for their GA[7]. In addition, fetal growth as well as future maternal health[2] is known to be affected by maternal BMI[15], preeclampsia[16], hypertension[17], and diabetes[18]. Consequently, the associations observed between offspring BW and maternal health outcomes could be due to other pregnancy complications known to affect both exposure and outcome and not fetal growth restriction per se, resulting in inflation of the strength of the association[19]. Lastly, smoking during pregnancy is also a potential confounder in the association, as it is known to strongly associate with both lower offspring birth weight[20, 21] and increased long-term morbidity and mortality in the mother[22]. In addition, smoking during pregnancy may modify the association between offspring birth weight and maternal cardiovascular disease risk, potentially reflecting different underlying mechanisms of fetal growth restriction and maternal vascular dysfunction in smokers versus non-smokers. Yet, few previous studies have included data on smoking during pregnancy[11, 23]. One study excluded smoking from their mortality analyses because the data were available for only about 25% of participants and suggested that unmeasured confounding could explain the observed associations[11]. Moreover, none of these studies examined the associations specifically among women who did not smoke during pregnancy or evaluated whether smoking modified the relationship between offspring birth weight and maternal long-term health. Accurately assessing the association between offspring BW and long-term maternal health requires careful consideration of the factors that may partially drive this relationship. If offspring BW is indeed a marker of future maternal CVD risk, this would suggest that the mechanisms contributing to maternal CVD also influence fetal growth. We hypothesized that offspring BW is inversely associated with maternal all-cause and cardiovascular mortality and morbidity, even after adjusting for known confounding factors, suggesting that birth weight may represent an independent marker of future maternal health. This hypothesis was investigated in a pregnancy cohort with detailed maternal health information collected before and during pregnancy, and linked to national registries, enabling up to 45 years of follow-up. The study also assessed whether smoking during pregnancy modified the observed associations. Materials and methods Population This study used data from the Copenhagen Perinatal Cohort (CPC[24, 25]) consisting of 8949 women from the Capital Region, Denmark, included during pregnancy and giving birth at Copenhagen University Hospital, Rigshospitalet, Denmark, from September 1959 to December 1961. Information on maternal age at inclusion (years), marital status (married yes/no), employment status (employed in pregnancy yes/no), pre-pregnancy body-mass-index (BMI, weight (kg)/height (m) 2 ), twin pregnancy (yes/no), pre-eclampsia (yes/no), eclampsia (yes/no), diabetes (yes/no), hypertension (yes/no), and smoking during pregnancy was available. Information on smoking during pregnancy was registered in the third trimester as either yes or no and as cigarette consumption per day divided into five categories: 0 cigarettes, 20 cigarettes. Information on diabetes did not specify the type of disease (type 1 or 2 diabetes or gestational diabetes). It was not recorded whether hypertension was present before pregnancy or not. GA was calculated based on the number of days between the date of the first day in the woman’s last menstrual period and the date of delivery divided by seven to obtain GA in weeks. The following women were excluded from the final analyses: Women who died during pregnancy or delivery (n = 7), women with missing information on GA (n = 1564), with invalid information on GA (either negative values or values > 50 weeks) (n = 73), with missing information on offspring BW (n = 14), with pre-eclampsia or eclampsia (n = 284), women with diabetes (n = 75), twin births (n = 110), premature births (defined as GA < 37 weeks) (n = 825), still births (n = 1), women with no available Central Person Register number (CPR-number) (n = 17), and with missing information on smoking during pregnancy (n = 115). For the mortality analyses we excluded women who either died, emigrated or were lost-to-follow-up before follow-up start (n = 98), and for the morbidity analyses we also excluded women who either died, emigrated or where lost-to-follow-up before follow-up start (n = 176). The final population consisted of 5766 women for the mortality analyses and 5688 for the morbidity analyses. An overview of the exclusion flow is provided in Fig. 1 . Exposure indicator The exposure was indicated by BW of offspring delivered at term or post-term (GA > = 37 weeks). Offspring BW was divided into a categorical variable of 5 five categories: 3999 grams. An offspring BW of 3500–3999 was defined as the reference category. Outcome To obtain information on mortality and cause of death, the women in the final study population were linked to the Danish Cause of Death Registry (DCDR)[26] by their personal identification number from the Danish Central Person Register (CPR). Variables extracted from the register per December 31st, 2015, included information on date and cause of death based on the International Classification of Diseases (ICD). We evaluated all-cause mortality and cardiovascular mortality, defined as cause of death by either hypertension (I10-11), ischemic heart disease (IHD) (I20-21 and I24-25), stroke (ischemic and hemorrhagic) (I60-69), and diseases in the arteries, arterioles, and capillaries (I70-79). In addition, we evaluated smoking-related mortality, defined as cause of death by smoking-related cancers (cancers of the oral cavity (C00-14), esophagus (C15) and airways (C33-34)), chronic obstructive pulmonary disease and asthma (J41-47). Information on cardiovascular morbidity was obtained from the Danish National Patient Register (DNPR)[27] and included information on cardiovascular diagnoses received upon or during an admission to a hospital unit in Denmark. Diagnoses were based on the ICD8 (1977–1993) and ICD10 (1994–2017). Diagnoses before January 1st, 1977, were not available for analysis. Cardiovascular diagnoses included: ischemic heart disease (IHD) (I20-21 and I24-25), hypertension (I10-11), stroke (ischemic and hemorrhagic) (I60-66), and a combined outcome of major cardiovascular events (MACE) defined as the diagnosis of either acute myocardial infarction (I21), stroke (I60-69), cardiac arrest or sudden cardiac death (I46). The dates of first-time diagnoses for each disease entity were included in the analyses. The analyses were conducted separately for each diagnosis (IHD, hypertension, stroke, MACE) allowing the individuals to be part of the at-risk population for all the evaluated CVD outcomes. Variables were extracted in August 2017 and were available from both registers until December 31st, 2015. Follow-up started on January 1st, 1970, for DCDR data and January 1st, 1977, for DNPR data providing follow-up periods of up to 45 years and 38 years respectively. Follow-up ended on the date of death, emigration, loss to follow-up (changed CPR-number, disappeared, no registered residence in Denmark), diagnosis of the CVD in question, or December 31st, 2015, whichever came first. Ethics According to Danish law (§ 14, part 2 of the Danish Act on Ethical Conduct of Health Research), this study did not require approval from a scientific ethics committee, as it was based on information retrieved from health registries. Women were enrolled in the Copenhagen Perinatal Cohort during routine admission procedures at Copenhagen University Hospital between 1959 and 1961, and most data were obtained through standard clinical care. At that time, formal consent procedures were not in place, but participants were thoroughly informed about the investigations and assured of confidentiality. Statistics All analyses were carried out using R version 4.4.2 ( http://www.r-project.org ). Linearity in the association between exposure (offspring BW) and outcome (maternal all-cause mortality) was assessed using splines and revealed a non-linear relationship (Linear vs. Spline Model plot is available in Supplementary Fig. S1 a and S1b). Offspring BW according to each category of number of cigarettes smoked per day in pregnancy was assessed in the total population and illustrated in a boxplot. The difference between groups was assessed using ANOVA and the post-hoc analyses tool, Tukey’s Honest Significant Difference (HSD) test, was performed to assess pairwise differences while adjusting for multiple comparisons. Crude survival was illustrated in Kaplan-Meier Plots and Log-Rank tests were used to conduct pairwise comparisons of survival according to offspring BW. All-cause mortality, cardiovascular mortality, smoking-related mortality, and cardiovascular morbidity were estimated using Cox proportional hazard models providing hazard ratios (HRs) and 95% confidence intervals in relation to offspring BW category. Age was used as the underlying time variable. The analysis was adjusted for maternal age at inclusion, pre-pregnancy BMI, sex of the offspring, GA, marital status, employment status, hypertension and smoking status in pregnancy (smoking yes/no). The proportional hazards assumption was assessed for each covariate in the models using Schoenfeld residuals. Likelihood Ratio Tests were performed to evaluate the potential confounding effect of smoking during pregnancy (yes/no) on the exposure (offspring BW) and the outcomes (maternal mortality and morbidity). A reduced model, not including smoking as a covariate, and a full model, including smoking, were compared. To explore the possible modifying effect of smoking during pregnancy, all analyses were carried out in the total population as well as in populations stratified by smoking during pregnancy (yes/no). To account for the potential dose-dependent effects of smoking on both fetal growth[21, 28] and maternal cardiovascular disease risk, the analyses of the population of women who smoked during pregnancy were adjusted for cigarette consumption per day in pregnancy. Likelihood ratio tests were used to compare a model with smoking as a covariate to a model with offspring BW and smoking as an interaction term. Results A total of 5766 women were included in the mortality analyses and 5688 in the cardiovascular morbidity analyses (Fig. 1). The women in the total population (n = 5766) were on average 25.3 years old (SD=6.50) at inclusion and had a pre-pregnancy BMI of 21.75 (SD=2.81). The mean offspring BW was 3320 grams (SD=493), mean GA was 40.5 weeks (SD=1.88), and 49.6% of the offspring were females. Table 1 provides a full overview of population characteristics. More than half of the women smoked during pregnancy (51.8%). The women in the smoking and non-smoking populations were similar in age, pre-pregnancy BMI, female/male offspring ratio, and duration of pregnancy (GA at birth). The mean offspring BW was higher for women who did not smoke during pregnancy than for women who did (3430 grams vs. 3220 grams) and there was a higher proportion of hypertension during pregnancy in the population of women who did not smoke during pregnancy (25% vs. 15%). Characteristics of the sub-populations are available in Supplementary table S1. Offspring birth weight was significantly higher among women who smoked fewer than three cigarettes per day during pregnancy compared to those who smoked more than three per day. Beyond this distinction, no significant differences in offspring birth weight were observed with increasing levels of maternal cigarette consumption during pregnancy (Supplementary Fig. S2 and table S2). No major violations of the proportional hazard’s assumption were observed for most covariates (p-values > 0.05, Supplementary Table S3); however, smoking during pregnancy, maternal age at birth, and maternal pre-pregnancy BMI showed significant evidence of non-proportionality (p = 0.00044, 0.00016, and 0.00004, respectively). Visual inspection of the Schoenfeld residuals suggested only minor deviations, with no substantial time-dependent trends for any of the covariates (plots in Supplementary Fig. 3a-c). Therefore, the covariates were retained in the model without time-varying adjustment. The Likelihood Ratio Test revealed that smoking during pregnancy was a significant confounding factor in the associations between offspring BW and all outcomes evaluated in the study, except for hypertension. Only for the associations between offspring BW and risk of MACE the model with the interaction term between smoking and offspring BW appeared to be slightly superior (p = 0.032) compared to the model with smoking as a covariate (Supplementary table S4a+b). Crude survival At the end of follow-up, 3128 out of 5766 (~54%) women were deceased and 93 were censored due to either emigration or loss to follow-up before the event of death occurred. In the population of women who smoked during pregnancy ~64% (1911/2989) were deceased at end of follow-up, and in the population who did not smoke during pregnancy ~44% (1217/2777) were deceased. In the total population and the population of women who smoked during pregnancy, crude survival analysis showed a lower survival rate in women giving birth to offspring with a BW below 3000 grams compared to women giving birth to offspring with a BW above 3000 grams (Supplementary Fig. S4 and S5). The lowest survival rate was observed in women giving birth to offspring with BW of <2500 grams in both populations (Supplementary Fig. S4 and S5). In the population of women who did not smoke during pregnancy, crude survival analysis showed a lower survival rate in women giving birth to offspring with a BW of <2500 grams compared with women giving birth to offspring between 2500-3999 grams (Supplementary Fig. S6). Mortality In the total population, we found a higher all-cause mortality and cardiovascular mortality in women giving birth to offspring below 3000 grams compared to women giving birth to offspring with a BW in the reference category (3500-3999 grams) (Table 2). In women giving birth to offspring with a BW of <2500 grams and 2500-2999 grams, the HRs for all-cause mortality were 1.71 (95% CI 1.45-2.00) and 1.23 (95% CI 1.20-1.38), and for cardiovascular mortality 2.16 (95% CI 1.54-3.03) and 1.41 (95% CI 1.09-1.81), respectively (Table 2). For cardiovascular mortality there was a tendency towards a lower mortality in women giving birth to offspring above 3999 grams, though this was non-significant (HR 0.87 [95% CI 0.62-1.20]). Smoking-related mortality was higher in women giving birth to offspring in all BW categories below 3500 grams compared with the reference category (Table 2). In the population of women who smoked during pregnancy, cardiovascular mortality was higher in the groups of women giving birth to offspring with a BW < 2500 grams (HR 1.96 [1.29-2.97]) or between 2500-2999 grams HR 1.42 [95% CI 1.02-1.97]) and lower in the group of women giving birth to offspring above 3999 grams (HR 0.47 [95% CI 0.24-0.90]) (Table 2). Estimates for all-cause and smoking-related mortality mirrored those in the total population (Table 2). In the population of women who did not smoke during pregnancy, we observed a higher all-cause mortality and cardiovascular mortality in women giving birth to offspring with a BW below 2500 grams compared with women giving birth to offspring with a BW within the reference category (all-cause mortality: HR 1.51 [95%CI 1.08-2.10], cardiovascular mortality: HR 2.33 [95%CI 1.28-4.23]) (Table 2). We did not observe lower all-cause or cardiovascular mortality in the group of women giving birth to offspring with a BW above 3999 grams. There were no associations between offspring BW and smoking-related mortality in this population (Table 2). Morbidity In the total populations, the hazards of MACE and stroke were higher in women giving birth to offspring with a BW below 2500 grams (MACE: HR 1.35 [95% CI 1.01-1.79], stroke: HR 1.51 [95% CI 1.09-2.08]) and lower in women giving birth to offspring with a BW above 3999 grams (MACE: HR 0.78 [95% CI 0.61-0.99], stroke: HR 0.78 [95% CI 0.59-1.03]) compared with the group of women giving birth to offspring with a BW within the reference category (3500-3999 grams) (Table 3). Compared to women giving birth to offspring with a BW within the reference category, women giving birth to offspring with a BW above 3999 grams had a lower hazard for hypertension (HR 0.82 [95% CI 0.68-0.99]). After stratification into two populations by smoking status during pregnancy, the overall pattern of associations remained. However, slight differences were observed. In the population of women who smoked during pregnancy, the hazard for MACE in women giving birth to offspring below 2500 grams was now borderline significant (HR 1.39 [95% CI 0.97-1.99]) but the hazards for stroke in the group of women giving birth to offspring below 2500 grams or above 3999 grams remained significant (HR 1.68 [95% CI 1.13-2.51], HR 0.56 [95% CI 0.33-0.97], respectively) (Table 3). The association between offspring birth weight and hypertension was not observed in this population (HR 0.91 [95% CI 0.65-1.28]). In the population of women who did not smoke during pregnancy, a higher risk of MACE and stroke was observed for the group of women who gave birth to offspring with a BW below 2500 grams compared with the reference, although estimates no longer reached statistical significance (MACE: HR 1.37 [95% CI 0.83-2.27], stroke: HR 1.34 [95% CI 0.76-2.38]) (Table 3). A significantly lower risk of hypertension in women giving birth to offspring above 3999 grams compared with the reference (HR 0.77 [95%CI 0.61-0.98]) reappeared in this population (Table 3). For IHD, no significant associations or patterns of associations with offspring BW were observed for any of the populations. Discussion In this study, we aimed to assess the relation between delivery of a small infant born at term and long-term maternal cardiovascular mortality and morbidity. We included women with previous singleton pregnancies, that were not complicated by diabetes, preeclampsia or preterm birth, adjusted our analyses for key confounding factors, and found that offspring BW was strongly inversely associated with long-term all-cause and cardiovascular mortality as well as cardiovascular morbidity. When we assessed women smoking and not smoking during pregnancy separately, the associations remained. Future maternal health after giving birth to a small baby Women who had given birth to an infant with a BW below 3000 grams had a higher all-cause and cardiovascular mortality compared with women who had given birth to infants within the reference BW category. The highest estimates were observed in women giving birth to babies below 2500 grams, who had a 71% higher all-cause mortality and a 116% higher cardiovascular mortality. This inverse association is consistent with previous findings in women giving birth to small babies[6, 9, 23, 29], and suggests that giving birth to a small baby may reveal an underlying maternal vulnerability to developing CVD, thus offering a window of opportunity for timely intervention[4, 5]. Our analyses of cardiovascular morbidity confirm this potential underlying vulnerability as we observed a 35% higher risk of MACE and 51% higher risk of stroke in women giving birth to offspring with a BW below 2500 grams compared to the reference. Previous studies have found strong inverse associations between offspring birth weight and subsequent risk of IHD in the mother[29–31], however, we did not replicate this finding in any of the populations studied, nor did we observe any consistent pattern of association, as all risk estimates were close to 1. The exclusion of women with pre-eclampsia and preterm delivery from the study population may explain the absence of associations with IHD, given that both conditions are established risk factors for low offspring birthweight and subsequent maternal IHD[32, 33]. Our findings suggest that the higher risk of maternal IHD observed in previous studies in women giving birth to small babies, may be mainly due to confounding effects of other pregnancy complications. A low offspring BW, if not accompanied by other pregnancy complications such as preeclampsia or preterm birth, is mainly caused by placental insufficiency[34], which may be indicative of a vulnerable maternal cardiovascular system. However, a large proportion of fetal growth restriction cases involve placentas that appear normal, which may suggest that the baby has reached its genetically determined growth potential and is therefore constitutionally small rather than truly growth restricted[34]. Delivery of a small infant may still reflect increased maternal disease risk if genetic variants associated with elevated cardiovascular risk, carried by the maternal genome, will restrict fetal growth when transmitted to the offspring[35]. Unfortunately, we were unable to explore this distinction, as placental weight, function, and pathology data were not available in this study. Future maternal health after giving birth to a large baby Giving birth to an infant above 3999 grams was found to be associated with lower cardiovascular mortality (16% lower in the total population and 54% lower in the population of women who smoked during pregnancy) compared to the reference. In addition, we found a 22% lower risk of MACE and stroke, and 18% lower risk of hypertension in women giving birth to offspring above 3999 grams. These findings contrast with most previous studies, which have reported higher mortality in women giving birth to large babies[36, 37]. We excluded women with diabetes, which is also known to be increasing offspring birth weight[38] and subsequent maternal cardiovascular risk[18, 39], from our study population. Moreover, a previous study reported that a high offspring BW was associated with a higher maternal cardiovascular mortality, if the baby was born prematurely but that the association was absent if the baby was born at term[7]. This finding, together with the results of the present study, may imply that women who give birth to large babies may have a lower risk of cardiovascular disease – provided the pregnancy was not complicated by hyperglycemia or preterm delivery. Stratification by smoking status in pregnancy A key finding of this study was that the pattern of an inverse associations between offspring BW and long-term maternal morbidity and mortality remained after dividing the population according to smoking status in pregnancy, reflecting that we found no significant interaction between smoking during pregnancy and offspring BW. Moreover, associations between offspring BW and maternal cardiovascular outcomes were present in both populations despite the lower power in the population of women who did not smoke during pregnancy – only 44% were deceased at follow-up vs. 64% deceased at follow-up in the population of women who smoked during pregnancy. Giving birth to a small infant (< 2500 grams) was strongly associated with higher all-cause and cardiovascular mortality in both women who smoked during pregnancy and those who did not. Although the association between offspring BW < 2500 grams and maternal risk of MACE was no longer significant, the pattern of higher maternal cardiovascular morbidity among women who gave birth to infants with a BW < 2500 grams – compared to the reference group – persisted after stratification by smoking status during pregnancy. This confirms that our and previous findings of associations between offspring BW and future maternal health, are not attributable to the adverse effects of smoking during pregnancy. Moreover, the similar pattern of associations indicates that fetal growth restriction may reflect future maternal cardiovascular health regardless of smoking behavior during pregnancy. The two populations may share a common cause of fetal growth restriction, namely placental insufficiency[34], which could imply an inherent maternal cardiovascular vulnerability, regardless of whether is it caused by maternal smoking during pregnancy[40, 41] or other underlying mechanisms. The lower risk of MACE and stroke in women who delivered infants with a birthweight above 3999 grams was most pronounced among those who smoked during pregnancy, whereas the strongest association with reduced risk of hypertension was observed among non-smoking women who delivered infants over 3999 grams. Although differences in the underlying mechanisms between the two populations cannot be ruled out, these findings may be explained by limited statistical power. A markedly lower number of women with hypertension during pregnancy was observed in the women who smoked during pregnancy (15% vs. 25%, Supplementary table S2), which is in line with the previously shown inverse association between smoking during pregnancy and hypertensive disorders in pregnancy[42]. Collectively, our findings add to the evidence that offspring BW may serve as an independent marker of maternal long-term health and disease, and not merely reflect effects of potential confounding factors. Strengths and limitations A strength of this study is the level of information about the women before and during pregnancy – especially the detailed information about maternal smoking during pregnancy. This information, along with information on smoking-related causes of death, made it possible for us to separate the effects of smoking from the effects of other factors affecting fetal growth on long-term maternal health and disease. Our analyses are also strengthened by the prospective design of the study, which minimizes recall bias, and by the long follow-up period of up to 45 years. Further, the validity and coverage of the register data[26, 27] is a strength of this study. This study also has several limitations. A major limitation is that we did not have information on the woman’s own BW, which would have been relevant to account for in the analyses as own BW has a significant impact on long-term health and disease and is strongly correlated with offspring BW[43]. Employment status in pregnancy was assessed as yes/no but it is unclear what employment during pregnancy indicated in Denmark around the year of 1960, as employment – and when in pregnancy the woman was employed – could indicate both high and low social class (e.g. could indicate both financial security and social vulnerability if employment indicated that the women was the only provider). We tried to account for this by adjusting for both employment and marital status in our analyses. The exclusion criteria applied to minimize confounding in this study reduced the statistical power of our analyses, which may have weakened observed associations or prevented detection of additional associations. The exclusion of women, who were deceased before follow-up start, could also have affected the outcomes, especially if there was a different distribution of offspring BW in the groups excluded. Conclusion Our findings reveal a higher cardiovascular mortality and risk of MACE and stroke in women with pregnancies involving fetal growth restriction, but not complicated by preterm delivery, preeclampsia or diabetes. Our findings of lower cardiovascular morbidity and mortality among women who gave birth to large babies, along with the absence of an association between offspring BW and maternal IHD, underscore the importance of accounting for confounding factors when studying such associations. Furthermore, we show that these associations are present regardless of smoking behavior during pregnancy. This highlights that, irrespective of the underlying cause of fetal growth restriction, the future health of mothers who gave birth to growth restricted babies should be carefully considered to improve long-term health, promote longevity, and prevent cardiovascular disease. Abbreviations BW Birth weight GA Gestational age CVD Cardiovascular disease DCDR Danish Cause of Death Register DNPR Danish National Patient Register CPR Central Person Register ICD International Classification of Disease MACE Major cardiovascular events IHD Ischemic heart disease HR Hazard ratio CI Confidence interval Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author contributions All authors contributed to the study conceptualization and design. Data preparation was performed by Line Engelbrechtsen and Pauline Kromann Reim and data analysis was performed by Pauline Kromann Reim. Pauline Kromann Reim wrote the first draft, and all authors reviewed and commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank all the women in the Copenhagen Perinatal Cohort for their participation. Thank you to Chief Physician, Henrik Vestergaard, for your input to the original research question, and to Lars Ängquist for your invaluable statistical support. This work was supported by a PhD scholarship granted to the first author (grant number PhD2021007-DCA) from the Danish Cardiovascular Academy, which is funded by the Novo Nordisk Foundation, grant number NNF20SA0067242 and the Danish Heart Foundation. References D. Williams, "Pregnancy: a stress test for life," Curr Opin Obstet Gynecol, vol. 15, pp. 465-471, 2003, doi: 10.1097/01.gco.0000103846.69273.ba. A. Hauspurg, W. Ying, C. A. Hubel, E. D. Michos, and P. Ouyang, "Adverse pregnancy outcomes and future maternal cardiovascular disease," Clin Cardiol, vol. 41, no. 2, pp. 239-246, Feb 2018, doi: 10.1002/clc.22887. N. Sattar, "Do pregnancy complications and CVD share common antecedents?," Atheroscler Suppl, vol. 5, no. 2, pp. 3-7, May 2004, doi: 10.1016/j.atherosclerosissup.2004.03.002. M. C. Cusimano, J. Pudwell, M. Roddy, C. 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Tables Table 1 Population Characteristics Population Characteristics n 5766 Offspring Birth Weight (g), mean (SD) 3320 (0.5) Offspring Birth Length (cm), mean (SD) 51 (2) Gestational Age at Delivery (weeks), mean (SD) 40.5 (1.88) Sex of Offspring, n (%) F 2858 (49.6) M 2908 (50.4) Caesarean Section, n (%) No 5396 (93.6) Yes 370 (6.4) Maternal Age (years), mean (SD) 25 (6.5) Pre-pregnancy BMI, mean (SD) 21.8 (2.8) Marital Status, n (%) Married 3494 (60.6) Not married 2272 (39.4) Employed in Pregnancy, n (%) No 2013 (34.9) Yes 3753 (65.1) Smoking During Pregnancy, n (%) No 2777 (48.2) Yes 2989 (51.8) Hypertension in Pregnancy, n (%) No 4594 (80.5) Yes 1115 (19.5) Offspring Birth Weight Category, n (%) 3999 531 (9.2) Table 2 Mortality in women in relation to offspring birth weight Total population of women* All-cause mortality (n events = 3128, n total = 5766) Cardiovascular mortality (n events = 621, n total = 5766) Smoking-related mortality (n events = 571, n total = 5766) BW n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value < 2500 212/298 1.71 (1.45; 2.00) 6.84e-11 51/298 2.16 (1.54; 3.03) 7.55e-06 55/298 2.49 (1.78; 3.48) 9.32e-08 2500–2999 563/965 1.23 (1.20; 1.38) 0.0004 117/965 1.41 (1.09; 1.81) 0.0081 128/965 1.65 (1.24; 2.16) 0.0002 3000–3499 1236/2335 1.06 (0.97; 1.18) 0.1895 231/2335 1.05 (0.85; 1.29) 0.6703 233/2335 1.24 (0.99; 1.57) 0.0635 3500–3999 829/1637 1.00 . . 171/1637 1.00 . . 121/1637 1.00 . . > 3999 288/531 1.06 (0.93; 1.23) 0.3794 51/531 0.87 (0.62; 1.20) 0.3913 34/531 0.97 (0.65; 1.46) 0.8942 Population of women who smoked during pregnancy ǂ All-cause mortality (n events = 1911, n total = 2989) Cardiovascular mortality (n events = 357, n total = 2989) Smoking-related mortality (n events = 475, n total = 2989) BW n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value <2500 169/220 1.73 (1.43; 2.09) 1.37e-08 36/220 1.96 (1.29; 2.97) 0.0015 53/220 2.61 (1.83; 3.74) 1.41e-07 2500–2999 417/623 1.32 (1.14; 1.53) 0.0001 79/623 1.42 (1.02; 1.97) 0.0372 113/623 1.60 (1.19; 2.15) 0.0018 3000–3499 789/1252 1.14 (1.01; 1.29) 0.0406 142/1252 1.07 (0.81; 1.42) 0.6373 197/1252 1.35 (1.04; 1.75) 0.0244 3500–3999 432/732 1.00 . . 87/732 1.00 . . 89/732 1.00 . . > 3999 104/162 0.94 (0.75; 1.18) 0.5991 13/162 0.47 (0.24; 0.90) 0.0230 23/162 1.01 (0.63; 1.64) 0.9562 Table 2 continued : Mortality in women in relation to offspring birth weight Population of women who did not smoke during pregnancy All-cause mortality (n events = 1217, n total = 2777) Cardiovascular mortality (n events = 264, n total = 2777) Smoking-related mortality (n events = 96, n total = 2777) BW n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value n events / n total HR 95% CI p-value < 2500 43/78 1.51 (1.08; 2.10) 0.0160 15/78 2.33 (1.28; 4.23) 0.0055 2/78 1.07 (0.25; 4.55) 0.9230 2500–2999 146/342 0.91 (0.74; 1.12) 0.3642 38/342 1.15 (0.77; 1.74) 0.4972 15/342 1.33 (0.68; 2.62) 0.4058 3000–3499 447/1083 0.97 (0.84; 1.12) 0.7042 89/1083 0.96 (0.70; 1.32) 0.7859 36/1083 1.06 (0.63; 1.77) 0.8374 3500–3999 397/905 1.00 . . 84/905 1.00 . . 32/905 1.00 . . > 3999 184/369 1.14 (0.95; 1.36) 0.1689 38/369 1.12 (0.75; 1.66) 0.5749 11/369 0.83 (0.39; 1.76) 0.6205 Cox proportional hazard model adjusted for maternal age at birth, pre-pregnancy BMI, sex of offspring, gestational age at birth, marital and employment status, hypertension during pregnancy. *Adjusted for smoking in pregnancy. ǂ Adjusted for cigarette consumption per day during pregnancy. BW = offspring birth weight category (grams), HR = hazard ratio, 95% CI = 95% Confidence Interval. CVD = cardiovascular disease. Cardiovascular mortality includes hypertension, ischemic heart disease, other heart diseases, diseases of the brain vessels, diseases in arteries, arterioles and capillaries, and other vascular diseases. Smoking-related mortality includes cancers in the oral cavity, oesophagus and airways, and chronic obstructive lung disease, asthma and bronchitis. Table 3 Cardiovascular morbidity in women in relation to offspring birth weight Total population of women* (n total = 5688) Women who smoked during pregnancy ǂ (n total = 2935) Women who did not smoke during pregnancy (n total = 2753) BW Diagnosis n events / n total HR 95% CI p-value Diagnosis n events / n total HR 95% CI p-value Diagnosis n events / n total HR 95% CI p-value < 2500 MACE (n = 1139) 61/291 1.35 (1.01; 1.79) 0.0430 MACE (n = 610) 43/214 1.39 (0.97; 1.99) 0.0690 MACE (n = 529) 18/77 1.37 (0.83; 2.27) 0.2157 2500–2999 180/949 0.97 (0.80; 1.17) 0.7324 114/609 1.04 (0.80; 1.35) 0.7611 66/340 0.86 (0.64; 1.16) 0.3250 3000–3499 470/2302 1.02 (0.88; 1.18) 0.8196 277/1230 1.20 (0.97; 1.47) 0.0883 193/1072 0.84 (0.68; 1.04) 0.1032 3500–3999 335/1620 1.00 . . 151/722 1.00 . . 184/898 1.00 . . > 3999 93/526 0.78 (0.61; 0.99) 0.0423 25/160 0.55 (0.35; 0.88) 0.0118 68/366 0.89 (0.66; 1.19) 0.4199 < 2500 IHD (n = 957) 37/291 0.95 (0.66; 1.35) 0.7648 IHD (n = 500) 25/214 0.91 (0.58; 1.42) 0.5157 IHD (n = 457) 12/77 1.02 (0.55; 1.90) 0.9386 2500–2999 163/949 1.06 (0.86; 1.30) 0.5767 91/609 0.95 (0.71; 1.26) 0.6852 72/340 1.15 (0.85; 1.55) 0.3604 3000–3499 382/2302 0.97 (0.83; 1.14) 0.7449 217/1230 1.09 (0.87; 1.37) 0.1149 165/1072 0.85 (0.68; 1.08) 0.1830 3500–3999 284/1620 1.00 . . 131/722 1.00 . . 153/898 1.00 . . > 3999 91/526 0.97 (0.75; 1.24) 0.7953 36/160 1.12 (0.75; 1.66) 0.9829 55/366 0.89 (0.65; 1.23) 0.4810 < 2500 Stroke (n = 842) 49/291 1.51 (1.09; 2.08) 0.0125 Stroke (n = 435) 35/214 1.68 (1.13; 2.51) 0.0111 Stroke (n = 407) 14/77 1.34 (0.76; 2.38) 0.3130 2500–2999 134/949 1.01 (0.81; 1.27) 0.9094 87/609 1.20 (0.88; 1.62) 0.2436 47/340 0.82 (0.58; 1.15) 0.2520 3000–3499 340/2302 1.01 (0.85; 1.19) 0.9323 191/1230 1.17 (0.92; 1.50) 0.2085 149/1072 0.85 (0.67; 1.09) 0.1970 3500–3999 250/1620 1.00 . . 105/722 1.00 . . 145/898 1.00 . . > 3999 69/526 0.78 (0.59; 1.03) 0.0776 17/160 0.56 (0.33; 0.97) 0.0396 52/366 0.87 (0.63; 1.22) 0.420 < 2500 Hyper- tension (n = 1714) 66/291 0.99 (0.76; 1.28) 0.9229 Hyper-tension (n = 774) 41/214 0.98 (0.69; 1.37) 0.8908 Hyper- tension (n = 940) 25/77 1.00 (0.65; 1.51) 0.9811 2500–2999 270/949 1.04 (0.89; 1.21) 0.6202 154/609 1.09 (0.87; 1.36) 0.4441 116/340 0.94 (0.75; 1.18) 0.5985 3000–3499 699/2302 0.96 (0.85; 1.08) 0.4518 327/1230 0.98 (0.81; 1.17) 0.7916 372/1072 0.94 (0.80; 1.10) 0.4575 3500–3999 525/1620 1.00 . . 297/722 1.00 . . 318/898 1.00 . . > 3999 154/526 0.82 (0.68; 0.99) 0.0384 45/160 0.91 (0.65; 1.28) 0.5974 109/366 0.77 (0.61; 0.98) 0.02995 COX proportional hazard model adjusted for maternal age at birth, pre-pregnancy BMI, sex of offspring, marital and employment status, and hypertension during pregnancy. *Adjusted for smoking in pregnancy. ǂ Adjusted for cigarette consumption per day during pregnancy. BW = offspring birth weight category (grams), HR = hazard ratio, 95% CI = 95%. Confidence Interval. MACE = major cardiovascular events (acute myocardial infarction, stroke, cardiac arrest or sudden cardiac death, IHD = ischemic heart disease. Supplementary Files Supplementary.pdf Cite Share Download PDF Status: Published Journal Publication published 21 Feb, 2026 Read the published version in European Journal of Epidemiology → Version 1 posted Reviewers invited by journal 19 Aug, 2025 Editor invited by journal 01 Jun, 2025 Editor assigned by journal 27 May, 2025 First submitted to journal 26 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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09:05:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6749003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6749003/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10654-025-01355-1","type":"published","date":"2026-02-21T15:57:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90000364,"identity":"ef4ece98-b5bf-46c5-83eb-116ec68b4e30","added_by":"auto","created_at":"2025-08-27 08:46:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":425760,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of population exclusions\u003c/p\u003e","description":"","filename":"Picture1.png","url":"https://assets-eu.researchsquare.com/files/rs-6749003/v1/670a883ef6487bec74470428.png"},{"id":103251245,"identity":"9032e088-7441-4586-9153-0dd226b8fa01","added_by":"auto","created_at":"2026-02-23 16:07:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1733698,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6749003/v1/dd47d35b-9c3b-4d8e-853e-5350d0126046.pdf"},{"id":90000370,"identity":"2a8740de-a4ea-4fbf-ac63-9791d41c68b2","added_by":"auto","created_at":"2025-08-27 08:46:16","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1101146,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6749003/v1/7e606aa4411102ac42760457.pdf"}],"financialInterests":"","formattedTitle":"Birth Weight of Term Born Offspring in relation to Long-Term Maternal Cardiovascular Morbidity and Mortality","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe accommodation of the maternal body to the physiological demands and cardiovascular adaptations of pregnancy can enhance or expose underlying disease risk, and has been suggested to offer an early-life stress-test predicting future maternal health[1, 2]. As such, pregnancy may provide a window of opportunity to postpone or prevent development of manifest disease[3\u0026ndash;5]. Being the endpoint of intrauterine growth, offspring birth weight (BW) may serve as an indicator of the extent to which these maternal adaptations have succeeded and hereby provide valuable information about the future health of the mother. Observational studies have revealed an inverse association between offspring BW and subsequent maternal cardiovascular disease (CVD)[6\u0026ndash;8]and mortality [9\u0026ndash;11]. However, the underlying mechanisms behind these associations remain unclear and are likely affected by pregnancy characteristics and shaped by a combination of genetic and environmental factors[12]. Most previous studies evaluating the association between offspring BW and maternal health and disease are limited by factors possibly introducing significant bias to the results: either lack of reliable information about offspring BW[13], gestational age (GA) at birth[6, 9] or insufficient adjustment for potential confounding factors such as maternal medical conditions during pregnancy (including pregnancy complications)[7, 8, 10], and smoking during pregnancy[6\u0026ndash;10].\u003c/p\u003e\u003cp\u003eThe fetus has the most substantial weight gain during the third trimester with a fetal weight velocity peak around week 35[14]. If GA is not accounted for, premature offspring may be categorized as growth restricted even when they are appropriate in size or large for their GA[7]. In addition, fetal growth as well as future maternal health[2] is known to be affected by maternal BMI[15], preeclampsia[16], hypertension[17], and diabetes[18]. Consequently, the associations observed between offspring BW and maternal health outcomes could be due to other pregnancy complications known to affect both exposure and outcome and not fetal growth restriction per se, resulting in inflation of the strength of the association[19].\u003c/p\u003e\u003cp\u003eLastly, smoking during pregnancy is also a potential confounder in the association, as it is known to strongly associate with both lower offspring birth weight[20, 21] and increased long-term morbidity and mortality in the mother[22]. In addition, smoking during pregnancy may modify the association between offspring birth weight and maternal cardiovascular disease risk, potentially reflecting different underlying mechanisms of fetal growth restriction and maternal vascular dysfunction in smokers versus non-smokers. Yet, few previous studies have included data on smoking during pregnancy[11, 23]. One study excluded smoking from their mortality analyses because the data were available for only about 25% of participants and suggested that unmeasured confounding could explain the observed associations[11]. Moreover, none of these studies examined the associations specifically among women who did not smoke during pregnancy or evaluated whether smoking modified the relationship between offspring birth weight and maternal long-term health.\u003c/p\u003e\u003cp\u003eAccurately assessing the association between offspring BW and long-term maternal health requires careful consideration of the factors that may partially drive this relationship. If offspring BW is indeed a marker of future maternal CVD risk, this would suggest that the mechanisms contributing to maternal CVD also influence fetal growth.\u003c/p\u003e\u003cp\u003eWe hypothesized that offspring BW is inversely associated with maternal all-cause and cardiovascular mortality and morbidity, even after adjusting for known confounding factors, suggesting that birth weight may represent an independent marker of future maternal health. This hypothesis was investigated in a pregnancy cohort with detailed maternal health information collected before and during pregnancy, and linked to national registries, enabling up to 45 years of follow-up. The study also assessed whether smoking during pregnancy modified the observed associations.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003ePopulation\u003c/p\u003e\u003cp\u003eThis study used data from the Copenhagen Perinatal Cohort (CPC[24, 25]) consisting of 8949 women from the Capital Region, Denmark, included during pregnancy and giving birth at Copenhagen University Hospital, Rigshospitalet, Denmark, from September 1959 to December 1961. Information on maternal age at inclusion (years), marital status (married yes/no), employment status (employed in pregnancy yes/no), pre-pregnancy body-mass-index (BMI, weight (kg)/height (m)\u003csup\u003e2\u003c/sup\u003e), twin pregnancy (yes/no), pre-eclampsia (yes/no), eclampsia (yes/no), diabetes (yes/no), hypertension (yes/no), and smoking during pregnancy was available. Information on smoking during pregnancy was registered in the third trimester as either yes or no and as cigarette consumption per day divided into five categories: 0 cigarettes, \u0026lt;\u0026thinsp;3 cigarettes, 3\u0026ndash;10 cigarettes, 11\u0026ndash;20 cigarettes and \u0026gt;\u0026thinsp;20 cigarettes. Information on diabetes did not specify the type of disease (type 1 or 2 diabetes or gestational diabetes). It was not recorded whether hypertension was present before pregnancy or not. GA was calculated based on the number of days between the date of the first day in the woman\u0026rsquo;s last menstrual period and the date of delivery divided by seven to obtain GA in weeks.\u003c/p\u003e\u003cp\u003eThe following women were excluded from the final analyses: Women who died during pregnancy or delivery (n\u0026thinsp;=\u0026thinsp;7), women with missing information on GA (n\u0026thinsp;=\u0026thinsp;1564), with invalid information on GA (either negative values or values\u0026thinsp;\u0026gt;\u0026thinsp;50 weeks) (n\u0026thinsp;=\u0026thinsp;73), with missing information on offspring BW (n\u0026thinsp;=\u0026thinsp;14), with pre-eclampsia or eclampsia (n\u0026thinsp;=\u0026thinsp;284), women with diabetes (n\u0026thinsp;=\u0026thinsp;75), twin births (n\u0026thinsp;=\u0026thinsp;110), premature births (defined as GA\u0026thinsp;\u0026lt;\u0026thinsp;37 weeks) (n\u0026thinsp;=\u0026thinsp;825), still births (n\u0026thinsp;=\u0026thinsp;1), women with no available Central Person Register number (CPR-number) (n\u0026thinsp;=\u0026thinsp;17), and with missing information on smoking during pregnancy (n\u0026thinsp;=\u0026thinsp;115). For the mortality analyses we excluded women who either died, emigrated or were lost-to-follow-up before follow-up start (n\u0026thinsp;=\u0026thinsp;98), and for the morbidity analyses we also excluded women who either died, emigrated or where lost-to-follow-up before follow-up start (n\u0026thinsp;=\u0026thinsp;176). The final population consisted of 5766 women for the mortality analyses and 5688 for the morbidity analyses.\u003c/p\u003e\u003cp\u003eAn overview of the exclusion flow is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eExposure indicator\u003c/p\u003e\u003cp\u003eThe exposure was indicated by BW of offspring delivered at term or post-term (GA\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;37 weeks). Offspring BW was divided into a categorical variable of 5 five categories: \u0026lt;2500, 2500\u0026ndash;2999, 3000\u0026ndash;3499, 3500\u0026ndash;3999, and \u0026gt;\u0026thinsp;3999 grams. An offspring BW of 3500\u0026ndash;3999 was defined as the reference category.\u003c/p\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003cp\u003eTo obtain information on mortality and cause of death, the women in the final study population were linked to the Danish Cause of Death Registry (DCDR)[26] by their personal identification number from the Danish Central Person Register (CPR). Variables extracted from the register per December 31st, 2015, included information on date and cause of death based on the International Classification of Diseases (ICD). We evaluated all-cause mortality and cardiovascular mortality, defined as cause of death by either hypertension (I10-11), ischemic heart disease (IHD) (I20-21 and I24-25), stroke (ischemic and hemorrhagic) (I60-69), and diseases in the arteries, arterioles, and capillaries (I70-79). In addition, we evaluated smoking-related mortality, defined as cause of death by smoking-related cancers (cancers of the oral cavity (C00-14), esophagus (C15) and airways (C33-34)), chronic obstructive pulmonary disease and asthma (J41-47).\u003c/p\u003e\u003cp\u003eInformation on cardiovascular morbidity was obtained from the Danish National Patient Register (DNPR)[27] and included information on cardiovascular diagnoses received upon or during an admission to a hospital unit in Denmark. Diagnoses were based on the ICD8 (1977\u0026ndash;1993) and ICD10 (1994\u0026ndash;2017). Diagnoses before January 1st, 1977, were not available for analysis. Cardiovascular diagnoses included: ischemic heart disease (IHD) (I20-21 and I24-25), hypertension (I10-11), stroke (ischemic and hemorrhagic) (I60-66), and a combined outcome of major cardiovascular events (MACE) defined as the diagnosis of either acute myocardial infarction (I21), stroke (I60-69), cardiac arrest or sudden cardiac death (I46). The dates of first-time diagnoses for each disease entity were included in the analyses. The analyses were conducted separately for each diagnosis (IHD, hypertension, stroke, MACE) allowing the individuals to be part of the at-risk population for all the evaluated CVD outcomes.\u003c/p\u003e\u003cp\u003eVariables were extracted in August 2017 and were available from both registers until December 31st, 2015. Follow-up started on January 1st, 1970, for DCDR data and January 1st, 1977, for DNPR data providing follow-up periods of up to 45 years and 38 years respectively. Follow-up ended on the date of death, emigration, loss to follow-up (changed CPR-number, disappeared, no registered residence in Denmark), diagnosis of the CVD in question, or December 31st, 2015, whichever came first.\u003c/p\u003e\u003cp\u003eEthics\u003c/p\u003e\u003cp\u003eAccording to Danish law (\u0026sect;\u0026nbsp;14, part 2 of the Danish Act on Ethical Conduct of Health Research), this study did not require approval from a scientific ethics committee, as it was based on information retrieved from health registries. Women were enrolled in the Copenhagen Perinatal Cohort during routine admission procedures at Copenhagen University Hospital between 1959 and 1961, and most data were obtained through standard clinical care. At that time, formal consent procedures were not in place, but participants were thoroughly informed about the investigations and assured of confidentiality.\u003c/p\u003e\u003cp\u003eStatistics\u003c/p\u003e\u003cp\u003eAll analyses were carried out using R version 4.4.2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLinearity in the association between exposure (offspring BW) and outcome (maternal all-cause mortality) was assessed using splines and revealed a non-linear relationship (Linear vs. Spline Model plot is available in Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea and S1b).\u003c/p\u003e\u003cp\u003eOffspring BW according to each category of number of cigarettes smoked per day in pregnancy was assessed in the total population and illustrated in a boxplot. The difference between groups was assessed using ANOVA and the post-hoc analyses tool, Tukey\u0026rsquo;s Honest Significant Difference (HSD) test, was performed to assess pairwise differences while adjusting for multiple comparisons.\u003c/p\u003e\u003cp\u003eCrude survival was illustrated in Kaplan-Meier Plots and Log-Rank tests were used to conduct pairwise comparisons of survival according to offspring BW. All-cause mortality, cardiovascular mortality, smoking-related mortality, and cardiovascular morbidity were estimated using Cox proportional hazard models providing hazard ratios (HRs) and 95% confidence intervals in relation to offspring BW category. Age was used as the underlying time variable. The analysis was adjusted for maternal age at inclusion, pre-pregnancy BMI, sex of the offspring, GA, marital status, employment status, hypertension and smoking status in pregnancy (smoking yes/no). The proportional hazards assumption was assessed for each covariate in the models using Schoenfeld residuals.\u003c/p\u003e\u003cp\u003eLikelihood Ratio Tests were performed to evaluate the potential confounding effect of smoking during pregnancy (yes/no) on the exposure (offspring BW) and the outcomes (maternal mortality and morbidity). A reduced model, not including smoking as a covariate, and a full model, including smoking, were compared.\u003c/p\u003e\u003cp\u003eTo explore the possible modifying effect of smoking during pregnancy, all analyses were carried out in the total population as well as in populations stratified by smoking during pregnancy (yes/no). To account for the potential dose-dependent effects of smoking on both fetal growth[21, 28] and maternal cardiovascular disease risk, the analyses of the population of women who smoked during pregnancy were adjusted for cigarette consumption per day in pregnancy. Likelihood ratio tests were used to compare a model with smoking as a covariate to a model with offspring BW and smoking as an interaction term.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 5766 women were included in the mortality analyses and 5688 in the cardiovascular morbidity analyses (Fig. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe women in the total population (n = 5766) were on average 25.3 years old (SD=6.50) at inclusion and had a pre-pregnancy BMI of 21.75 (SD=2.81). The mean offspring BW was 3320 grams (SD=493), mean GA was 40.5 weeks (SD=1.88), and 49.6% of the offspring were females. Table 1 provides a full overview of population characteristics. \u0026nbsp;More than half of the women smoked during pregnancy (51.8%). The women in the smoking and non-smoking populations were similar in age, pre-pregnancy BMI, female/male offspring ratio, and duration of pregnancy (GA at birth). The mean offspring BW was higher for women who did not smoke during pregnancy than for women who did (3430 grams vs. 3220 grams) and there was a higher proportion of hypertension during pregnancy in the population of women who did not smoke during pregnancy (25% vs. 15%). Characteristics of the sub-populations are available in Supplementary table S1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOffspring birth weight was significantly higher among women who smoked fewer than three cigarettes per day during pregnancy compared to those who smoked more than three per day. Beyond this distinction, no significant differences in offspring birth weight were observed with increasing levels of maternal cigarette consumption during pregnancy (Supplementary Fig. S2 and table S2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo major violations of the proportional hazard\u0026rsquo;s assumption were observed for most covariates (p-values \u0026gt; 0.05, Supplementary Table S3); however, smoking during pregnancy, maternal age at birth, and maternal pre-pregnancy BMI showed significant evidence of non-proportionality (p = 0.00044, 0.00016, and 0.00004, respectively). Visual inspection of the Schoenfeld residuals suggested only minor deviations, with no substantial time-dependent trends for any of the covariates (plots in Supplementary Fig. 3a-c). Therefore, the covariates were retained in the model without time-varying adjustment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Likelihood Ratio Test revealed that smoking during pregnancy was a significant confounding factor in the associations between offspring BW and all outcomes evaluated in the study, except for hypertension. Only for the associations between offspring BW and risk of MACE the model with the interaction term between smoking and offspring BW appeared to be slightly superior (p = 0.032) compared to the model with smoking as a covariate (Supplementary table S4a+b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCrude survival\u003c/p\u003e\n\u003cp\u003eAt the end of follow-up, 3128 out of 5766 (~54%) women were deceased and 93 were censored due to either emigration or loss to follow-up before the event of death occurred. In the population of women who smoked during pregnancy ~64% (1911/2989) were deceased at end of follow-up, and in the population who did not smoke during pregnancy ~44% (1217/2777) were deceased. In the total population and the population of women who smoked during pregnancy, crude survival analysis showed a lower survival rate in women giving birth to offspring with a BW below 3000 grams compared to women giving birth to offspring with a BW above 3000 grams (Supplementary Fig. S4 and S5). The lowest survival rate was observed in women giving birth to offspring with BW of \u0026lt;2500 grams in both populations (Supplementary Fig. S4 and S5). In the population of women who did not smoke during pregnancy, crude survival analysis showed a lower survival rate in women giving birth to offspring with a BW of \u0026lt;2500 grams compared with women giving birth to offspring between 2500-3999 grams (Supplementary Fig. S6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMortality\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the total population, we found a higher all-cause mortality and cardiovascular mortality in women giving birth to offspring below 3000 grams compared to women giving birth to offspring with a BW in the reference category (3500-3999 grams) (Table 2). In women giving birth to offspring with a BW of \u0026lt;2500 grams and 2500-2999 grams, the HRs for all-cause mortality were 1.71 (95% CI 1.45-2.00) and 1.23 (95% CI 1.20-1.38), and for cardiovascular mortality 2.16 (95% CI 1.54-3.03) and 1.41 (95% CI 1.09-1.81), respectively (Table 2). For cardiovascular mortality there was a tendency towards a lower mortality in women giving birth to offspring above 3999 grams, though this was non-significant (HR 0.87 [95% CI 0.62-1.20]). Smoking-related mortality was higher in women giving birth to offspring in all BW categories below 3500 grams compared with the reference category (Table 2).\u003c/p\u003e\n\u003cp\u003eIn the population of women who smoked during pregnancy, cardiovascular mortality was higher in the groups of women giving birth to offspring with a BW \u0026lt; 2500 grams (HR 1.96 [1.29-2.97]) or between 2500-2999 grams HR 1.42 [95% CI 1.02-1.97]) and lower in the group of women giving birth to offspring above 3999 grams (HR 0.47 [95% CI 0.24-0.90]) (Table 2). \u0026nbsp;Estimates for all-cause and smoking-related mortality mirrored those in the total population (Table 2). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the population of women who did not smoke during pregnancy, we observed a higher all-cause mortality and cardiovascular mortality in women giving birth to offspring with a BW below 2500 grams compared with women giving birth to offspring with a BW within the reference category (all-cause mortality: HR 1.51 [95%CI 1.08-2.10], cardiovascular mortality: HR 2.33 [95%CI 1.28-4.23]) (Table 2). We did not observe lower all-cause or cardiovascular mortality in the group of women giving birth to offspring with a BW above 3999 grams. There were no associations between offspring BW and smoking-related mortality in this population (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMorbidity\u003c/p\u003e\n\u003cp\u003eIn the total populations, the hazards of MACE and stroke were higher in women giving birth to offspring with a BW below 2500 grams (MACE: HR 1.35 [95% CI 1.01-1.79], stroke: HR 1.51 [95% CI 1.09-2.08]) and lower in women giving birth to offspring with a BW above 3999 grams (MACE: HR 0.78 [95% CI 0.61-0.99], stroke: HR 0.78 [95% CI 0.59-1.03]) compared with the group of women giving birth to offspring with a BW within the reference category (3500-3999 grams) (Table 3). Compared to women giving birth to offspring with a BW within the reference category, women giving birth to offspring with a BW above 3999 grams had a lower hazard for hypertension (HR 0.82 [95% CI 0.68-0.99]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter stratification into two populations by smoking status during pregnancy, the overall pattern of associations remained. However, slight differences were observed. \u0026nbsp;In the population of women who smoked during pregnancy, the hazard for MACE in women giving birth to offspring below 2500 grams was now borderline significant (HR 1.39 [95% CI 0.97-1.99]) but the hazards for stroke in the group of women giving birth to offspring below 2500 grams or above 3999 grams remained significant (HR 1.68 [95% CI 1.13-2.51], HR 0.56 [95% CI 0.33-0.97], respectively) (Table 3). The association between offspring birth weight and hypertension was not observed in this population (HR 0.91 [95% CI 0.65-1.28]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the population of women who did not smoke during pregnancy, a higher risk of MACE and stroke was observed for the group of women who gave birth to offspring with a BW below 2500 grams compared with the reference, although estimates no longer reached statistical significance (MACE: HR 1.37 [95% CI 0.83-2.27], stroke: HR 1.34 [95% CI 0.76-2.38]) (Table 3). A significantly lower risk of hypertension in women giving birth to offspring above 3999 grams compared with the reference (HR 0.77 [95%CI 0.61-0.98]) reappeared in this population (Table 3).\u003c/p\u003e\n\u003cp\u003eFor IHD, no significant associations or patterns of associations with offspring BW were observed for any of the populations.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we aimed to assess the relation between delivery of a small infant born at term and long-term maternal cardiovascular mortality and morbidity. We included women with previous singleton pregnancies, that were not complicated by diabetes, preeclampsia or preterm birth, adjusted our analyses for key confounding factors, and found that offspring BW was strongly inversely associated with long-term all-cause and cardiovascular mortality as well as cardiovascular morbidity. When we assessed women smoking and not smoking during pregnancy separately, the associations remained.\u003c/p\u003e\u003cp\u003eFuture maternal health after giving birth to a small baby\u003c/p\u003e\u003cp\u003eWomen who had given birth to an infant with a BW below 3000 grams had a higher all-cause and cardiovascular mortality compared with women who had given birth to infants within the reference BW category. The highest estimates were observed in women giving birth to babies below 2500 grams, who had a 71% higher all-cause mortality and a 116% higher cardiovascular mortality. This inverse association is consistent with previous findings in women giving birth to small babies[6, 9, 23, 29], and suggests that giving birth to a small baby may reveal an underlying maternal vulnerability to developing CVD, thus offering a window of opportunity for timely intervention[4, 5]. Our analyses of cardiovascular morbidity confirm this potential underlying vulnerability as we observed a 35% higher risk of MACE and 51% higher risk of stroke in women giving birth to offspring with a BW below 2500 grams compared to the reference. Previous studies have found strong inverse associations between offspring birth weight and subsequent risk of IHD in the mother[29\u0026ndash;31], however, we did not replicate this finding in any of the populations studied, nor did we observe any consistent pattern of association, as all risk estimates were close to 1. The exclusion of women with pre-eclampsia and preterm delivery from the study population may explain the absence of associations with IHD, given that both conditions are established risk factors for low offspring birthweight and subsequent maternal IHD[32, 33]. Our findings suggest that the higher risk of maternal IHD observed in previous studies in women giving birth to small babies, may be mainly due to confounding effects of other pregnancy complications.\u003c/p\u003e\u003cp\u003eA low offspring BW, if not accompanied by other pregnancy complications such as preeclampsia or preterm birth, is mainly caused by placental insufficiency[34], which may be indicative of a vulnerable maternal cardiovascular system. However, a large proportion of fetal growth restriction cases involve placentas that appear normal, which may suggest that the baby has reached its genetically determined growth potential and is therefore constitutionally small rather than truly growth restricted[34]. Delivery of a small infant may still reflect increased maternal disease risk if genetic variants associated with elevated cardiovascular risk, carried by the maternal genome, will restrict fetal growth when transmitted to the offspring[35]. Unfortunately, we were unable to explore this distinction, as placental weight, function, and pathology data were not available in this study.\u003c/p\u003e\u003cp\u003eFuture maternal health after giving birth to a large baby\u003c/p\u003e\u003cp\u003eGiving birth to an infant above 3999 grams was found to be associated with lower cardiovascular mortality (16% lower in the total population and 54% lower in the population of women who smoked during pregnancy) compared to the reference. In addition, we found a 22% lower risk of MACE and stroke, and 18% lower risk of hypertension in women giving birth to offspring above 3999 grams. These findings contrast with most previous studies, which have reported higher mortality in women giving birth to large babies[36, 37]. We excluded women with diabetes, which is also known to be increasing offspring birth weight[38] and subsequent maternal cardiovascular risk[18, 39], from our study population. Moreover, a previous study reported that a high offspring BW was associated with a higher maternal cardiovascular mortality, if the baby was born prematurely but that the association was absent if the baby was born at term[7]. This finding, together with the results of the present study, may imply that women who give birth to large babies may have a lower risk of cardiovascular disease \u0026ndash; provided the pregnancy was not complicated by hyperglycemia or preterm delivery.\u003c/p\u003e\u003cp\u003eStratification by smoking status in pregnancy\u003c/p\u003e\u003cp\u003eA key finding of this study was that the pattern of an inverse associations between offspring BW and long-term maternal morbidity and mortality remained after dividing the population according to smoking status in pregnancy, reflecting that we found no significant interaction between smoking during pregnancy and offspring BW. Moreover, associations between offspring BW and maternal cardiovascular outcomes were present in both populations despite the lower power in the population of women who did not smoke during pregnancy \u0026ndash; only 44% were deceased at follow-up vs. 64% deceased at follow-up in the population of women who smoked during pregnancy.\u003c/p\u003e\u003cp\u003eGiving birth to a small infant (\u0026lt;\u0026thinsp;2500 grams) was strongly associated with higher all-cause and cardiovascular mortality in both women who smoked during pregnancy and those who did not. Although the association between offspring BW\u0026thinsp;\u0026lt;\u0026thinsp;2500 grams and maternal risk of MACE was no longer significant, the pattern of higher maternal cardiovascular morbidity among women who gave birth to infants with a BW\u0026thinsp;\u0026lt;\u0026thinsp;2500 grams \u0026ndash; compared to the reference group \u0026ndash; persisted after stratification by smoking status during pregnancy. This confirms that our and previous findings of associations between offspring BW and future maternal health, are not attributable to the adverse effects of smoking during pregnancy. Moreover, the similar pattern of associations indicates that fetal growth restriction may reflect future maternal cardiovascular health regardless of smoking behavior during pregnancy. The two populations may share a common cause of fetal growth restriction, namely placental insufficiency[34], which could imply an inherent maternal cardiovascular vulnerability, regardless of whether is it caused by maternal smoking during pregnancy[40, 41] or other underlying mechanisms.\u003c/p\u003e\u003cp\u003eThe lower risk of MACE and stroke in women who delivered infants with a birthweight above 3999 grams was most pronounced among those who smoked during pregnancy, whereas the strongest association with reduced risk of hypertension was observed among non-smoking women who delivered infants over 3999 grams. Although differences in the underlying mechanisms between the two populations cannot be ruled out, these findings may be explained by limited statistical power.\u003c/p\u003e\u003cp\u003eA markedly lower number of women with hypertension during pregnancy was observed in the women who smoked during pregnancy (15% vs. 25%, Supplementary table S2), which is in line with the previously shown inverse association between smoking during pregnancy and hypertensive disorders in pregnancy[42].\u003c/p\u003e\u003cp\u003eCollectively, our findings add to the evidence that offspring BW may serve as an independent marker of maternal long-term health and disease, and not merely reflect effects of potential confounding factors.\u003c/p\u003e\u003cp\u003eStrengths and limitations\u003c/p\u003e\u003cp\u003eA strength of this study is the level of information about the women before and during pregnancy \u0026ndash; especially the detailed information about maternal smoking during pregnancy. This information, along with information on smoking-related causes of death, made it possible for us to separate the effects of smoking from the effects of other factors affecting fetal growth on long-term maternal health and disease. Our analyses are also strengthened by the prospective design of the study, which minimizes recall bias, and by the long follow-up period of up to 45 years. Further, the validity and coverage of the register data[26, 27] is a strength of this study.\u003c/p\u003e\u003cp\u003eThis study also has several limitations. A major limitation is that we did not have information on the woman\u0026rsquo;s own BW, which would have been relevant to account for in the analyses as own BW has a significant impact on long-term health and disease and is strongly correlated with offspring BW[43]. Employment status in pregnancy was assessed as yes/no but it is unclear what employment during pregnancy indicated in Denmark around the year of 1960, as employment \u0026ndash; and when in pregnancy the woman was employed \u0026ndash; could indicate both high and low social class (e.g. could indicate both financial security and social vulnerability if employment indicated that the women was the only provider). We tried to account for this by adjusting for both employment and marital status in our analyses.\u003c/p\u003e\u003cp\u003eThe exclusion criteria applied to minimize confounding in this study reduced the statistical power of our analyses, which may have weakened observed associations or prevented detection of additional associations. The exclusion of women, who were deceased before follow-up start, could also have affected the outcomes, especially if there was a different distribution of offspring BW in the groups excluded.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings reveal a higher cardiovascular mortality and risk of MACE and stroke in women with pregnancies involving fetal growth restriction, but not complicated by preterm delivery, preeclampsia or diabetes. Our findings of lower cardiovascular morbidity and mortality among women who gave birth to large babies, along with the absence of an association between offspring BW and maternal IHD, underscore the importance of accounting for confounding factors when studying such associations. Furthermore, we show that these associations are present regardless of smoking behavior during pregnancy. This highlights that, irrespective of the underlying cause of fetal growth restriction, the future health of mothers who gave birth to growth restricted babies should be carefully considered to improve long-term health, promote longevity, and prevent cardiovascular disease.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBW\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBirth weight\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGestational age\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCardiovascular disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDCDR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDanish Cause of Death Register\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDNPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDanish National Patient Register\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCentral Person Register\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational Classification of Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMACE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMajor cardiovascular events\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIHD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIschemic heart disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHazard ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conceptualization and design. Data preparation was performed by Line Engelbrechtsen and Pauline Kromann Reim and data analysis was performed by Pauline Kromann Reim. Pauline Kromann Reim wrote the first draft, and all authors reviewed and commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eThe authors would like to thank all the women in the Copenhagen Perinatal Cohort for their participation. Thank you to Chief Physician, Henrik Vestergaard, for your input to the original research question, and to Lars \u0026Auml;ngquist for your invaluable statistical support.\u003c/p\u003e\u003cp\u003eThis work was supported by a PhD scholarship granted to the first author (grant number PhD2021007-DCA) from the Danish Cardiovascular Academy, which is funded by the Novo Nordisk Foundation, grant number NNF20SA0067242 and the Danish Heart Foundation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eD. Williams, \u0026quot;Pregnancy: a stress test for life,\u0026quot; \u003cem\u003eCurr Opin Obstet Gynecol, \u003c/em\u003evol. 15, pp. 465-471, 2003, doi: 10.1097/01.gco.0000103846.69273.ba.\u003c/li\u003e\n\u003cli\u003eA. Hauspurg, W. Ying, C. A. Hubel, E. D. Michos, and P. 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Xu\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Risk of all-cause and CHD mortality in women versus men with type 2 diabetes: a systematic review and meta-analysis,\u0026quot; (in eng), \u003cem\u003eEur J Endocrinol, \u003c/em\u003evol. 180, no. 4, pp. 243-255, Apr 2019, doi: 10.1530/eje-18-0792.\u003c/li\u003e\n\u003cli\u003eD. Pintican, A. A. Poienar, S. Strilciuc, and D. Mihu, \u0026quot;Effects of maternal smoking on human placental vascularization: A systematic review,\u0026quot; (in eng), \u003cem\u003eTaiwan J Obstet Gynecol, \u003c/em\u003evol. 58, no. 4, pp. 454-459, Jul 2019, doi: 10.1016/j.tjog.2019.05.004.\u003c/li\u003e\n\u003cli\u003eA. C. Holloway\u003cem\u003e et al.\u003c/em\u003e, \u0026quot;Characterization of the adverse effects of nicotine on placental development: in vivo and in vitro studies,\u0026quot; (in eng), \u003cem\u003eAm J Physiol Endocrinol Metab, \u003c/em\u003evol. 306, no. 4, pp. E443-56, Feb 15 2014, doi: 10.1152/ajpendo.00478.2013.\u003c/li\u003e\n\u003cli\u003eJ. Wang, W. Yang, W. Xiao, and S. Cao, \u0026quot;The association between smoking during pregnancy and hypertensive disorders of pregnancy: A systematic review and meta-analysis,\u0026quot; \u003cem\u003eInt J Gynaecol Obstet, \u003c/em\u003evol. 157, no. 1, pp. 31-41, Apr 2022, doi: 10.1002/ijgo.13709.\u003c/li\u003e\n\u003cli\u003eR. E. Little, \u0026quot;Mother\u0026apos;s and father\u0026apos;s birthweight as predictors of infant birthweight,\u0026quot; \u003cem\u003ePediatric and Perinatal Epidemiol \u003c/em\u003evol. 1, no. 1, pp. 19-31, 1987, doi: https://doi.org/10.1111/j.1365-3016.1987.tb00084.x.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePopulation Characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePopulation Characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOffspring Birth Weight (g), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3320 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOffspring Birth Length (cm), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational Age at Delivery (weeks), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.5 (1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex of Offspring, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2858 (49.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2908 (50.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaesarean Section, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5396 (93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e370 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal Age (years), mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-pregnancy BMI, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.8 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarital Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3494 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2272 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed in Pregnancy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2013 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3753 (65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking During Pregnancy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2777 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2989 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension in Pregnancy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4594 (80.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1115 (19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOffspring Birth Weight Category, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e298 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e965 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2335 (40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1637 (28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e531 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMortality in women in relation to offspring birth weight\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"22\"\u003e\n \u003cp\u003eTotal population of women*\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;3128, n total\u0026thinsp;=\u0026thinsp;5766)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;621, n total\u0026thinsp;=\u0026thinsp;5766)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking-related mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;571, n total\u0026thinsp;=\u0026thinsp;5766)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e212/298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.45; 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.84e-11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e51/298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.54; 3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.55e-06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e55/298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.78; 3.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.32e-08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e563/965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.20; 1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e117/965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.09; 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0081\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e128/965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.24; 2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1236/2335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.97; 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e231/2335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.85; 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e233/2335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.99; 1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e829/1637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e171/1637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e121/1637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e288/531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.93; 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e51/531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.62; 1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e34/531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.65; 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8942\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"22\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation of women who smoked during pregnancy\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eǂ\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;1911, n total\u0026thinsp;=\u0026thinsp;2989)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;357, n total\u0026thinsp;=\u0026thinsp;2989)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking-related mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;475, n total\u0026thinsp;=\u0026thinsp;2989)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e169/220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.43; 2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.37e-08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36/220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.29; 2.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53/220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.61\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.83; 3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41e-07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e417/623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.14; 1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79/623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.02; 1.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0372\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e113/623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.19; 2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e789/1252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.01; 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0406\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142/1252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.81; 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.6373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e197/1252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(1.04; 1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0244\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e432/732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87/732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89/732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e104/162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.75; 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.5991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13/162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.24; 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0230\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23/162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e(0.63; 1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.9562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003econtinued\u003c/strong\u003e: Mortality in women in relation to offspring birth weight\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"13\"\u003e\n \u003cp\u003ePopulation of women who did not smoke during pregnancy\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;1217, n total\u0026thinsp;=\u0026thinsp;2777)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;264, n total\u0026thinsp;=\u0026thinsp;2777)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking-related mortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n events\u0026thinsp;=\u0026thinsp;96, n total\u0026thinsp;=\u0026thinsp;2777)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003en events / n total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43/78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.08; 2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0160\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.33\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.28; 4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0055\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.25; 4.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146/342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.74; 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38/342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.77; 1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.68; 2.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e447/1083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.84; 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89/1083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.70; 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36/1083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.63; 1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8374\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e397/905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84/905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32/905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e184/369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.95; 1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38/369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.75; 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11/369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.39; 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eCox proportional hazard model adjusted for maternal age at birth, pre-pregnancy BMI, sex of offspring, gestational age at birth, marital and employment status, hypertension during pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e*Adjusted for smoking in pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e\u003csup\u003e\u003cstrong\u003eǂ\u003c/strong\u003e\u003c/sup\u003eAdjusted for cigarette consumption per day during pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eBW\u0026thinsp;=\u0026thinsp;offspring birth weight category (grams), HR\u0026thinsp;=\u0026thinsp;hazard ratio, 95% CI\u0026thinsp;=\u0026thinsp;95% Confidence Interval. CVD\u0026thinsp;=\u0026thinsp;cardiovascular disease. Cardiovascular mortality includes hypertension, ischemic heart disease, other heart diseases, diseases of the brain vessels, diseases in arteries, arterioles and capillaries, and other vascular diseases. Smoking-related mortality includes cancers in the oral cavity, oesophagus and airways, and chronic obstructive lung disease, asthma and bronchitis.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCardiovascular morbidity in women in relation to offspring birth weight\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eTotal population of women*\u003c/p\u003e\n \u003cp\u003e(n total\u0026thinsp;=\u0026thinsp;5688)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eWomen who smoked during pregnancy\u003csup\u003eǂ\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(n total\u0026thinsp;=\u0026thinsp;2935)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eWomen who did not smoke during pregnancy\u003c/p\u003e\n \u003cp\u003e(n total\u0026thinsp;=\u0026thinsp;2753)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBW\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiagnosis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en events /\u003c/p\u003e\n \u003cp\u003en total\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiagnosis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en events /\u003c/p\u003e\n \u003cp\u003en total\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiagnosis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en events /\u003c/p\u003e\n \u003cp\u003en total\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMACE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1139)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61/291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.01; 1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0430\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMACE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;610)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43/214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.97; 1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMACE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;529)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18/77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.83; 2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180/949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.80; 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114/609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.80; 1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66/340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.64; 1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e470/2302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.88; 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e277/1230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.97; 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e193/1072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.68; 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e335/1620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151/722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e184/898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93/526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.61; 0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0423\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25/160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.35; 0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0118\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68/366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.66; 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;957)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37/291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.66; 1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25/214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.58; 1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;457)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12/77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.55; 1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9386\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163/949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.86; 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91/609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.71; 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72/340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.85; 1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e382/2302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.83; 1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e217/1230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.87; 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165/1072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.68; 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1830\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e284/1620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131/722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153/898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91/526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.75; 1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36/160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.75; 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55/366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.65; 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;842)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49/291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e(1.09; 2.08)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0125\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;435)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35/214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.68\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.13; 2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0111\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;407)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14/77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.76; 2.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134/949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.81; 1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87/609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.88; 1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47/340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.58; 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2520\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e340/2302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.85; 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191/1230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.92; 1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149/1072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.67; 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250/1620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105/722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145/898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69/526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.59; 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17/160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.33; 0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0396\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52/366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.63; 1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyper-\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etension\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1714)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66/291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.76; 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyper-tension\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;774)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41/214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.69; 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyper-\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etension\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;940)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25/77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.65; 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500\u0026ndash;2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e270/949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.89; 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154/609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.87; 1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116/340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.75; 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5985\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3000\u0026ndash;3499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e699/2302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.85; 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e327/1230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.81; 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e372/1072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.80; 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3500\u0026ndash;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e525/1620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e297/722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e318/898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;3999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154/526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.82\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.68; 0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0384\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45/160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.65; 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109/366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.61; 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02995\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\"\u003eCOX proportional hazard model adjusted for maternal age at birth, pre-pregnancy BMI, sex of offspring, marital and employment status, and hypertension during pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\"\u003e*Adjusted for smoking in pregnancy. \u003csup\u003e\u003cstrong\u003eǂ\u003c/strong\u003e\u003c/sup\u003eAdjusted for cigarette consumption per day during pregnancy. BW\u0026thinsp;=\u0026thinsp;offspring birth weight category (grams), HR\u0026thinsp;=\u0026thinsp;hazard ratio, 95% CI\u0026thinsp;=\u0026thinsp;95%. Confidence Interval. MACE\u0026thinsp;=\u0026thinsp;major cardiovascular events (acute myocardial infarction, stroke, cardiac arrest or sudden cardiac death, IHD\u0026thinsp;=\u0026thinsp;ischemic heart disease.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejep","sideBox":"Learn more about [European Journal of Epidemiology](https://www.springer.com/journal/10654)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejep/default.aspx","title":"European Journal of Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Birth weight, pregnancy, maternal health, cardiovascular disease","lastPublishedDoi":"10.21203/rs.3.rs-6749003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6749003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePrevious studies have identified associations between offspring birthweight and future maternal cardiovascular health, but many studies lack sufficient adjustment for confounders such as pregnancy complications, gestational age, maternal body mass index (BMI), and smoking. This study aimed to assess whether the association between term offspring BW and maternal cardiovascular risk is independent of these factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe used data from the Copenhagen Perinatal Cohort (1959\u0026ndash;1961). After excluding women with diabetes, preeclampsia, preterm births, and twin pregnancies, 5,766 women remained. Cardiovascular outcomes were obtained from Danish national registries with up to 45 years of follow-up. Hazard ratios (HR) with 95% confidence intervals (CI) were estimated using Cox regression, adjusting for smoking during pregnancy, maternal BMI, hypertension, and gestational age. Additional analyses were conducted in populations stratified by smoking status and adjusted for cigarette consumption per day.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOffspring BW below 3000 grams was associated with higher maternal cardiovascular mortality (\u0026lt;\u0026thinsp;2500 grams: 2.16 [1.54\u0026ndash;3.03], 2500\u0026ndash;2999 grams: 1.41 [1.09\u0026ndash;1.81]) compared to the reference category (offspring BW 3500\u0026ndash;3999 grams). The risk of maternal major cardiovascular events and stroke was higher when offspring BW was below 2500 grams (1.35 [1.01\u0026ndash;1.79], 1.51 [1.09\u0026ndash;2.08]) and lower if offspring BW was above 3999 (0.78 [95% CI 0.61\u0026ndash;0.99], 0.78 [0.59\u0026ndash;1.03]) compared to the reference. No association was found with ischemic heart disease. Associations persisted after stratification by smoking.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eLower BW of term offspring from uncomplicated, singleton pregnancies is inversely associated with long-term maternal cardiovascular risk, independent of smoking during pregnancy.\u003c/p\u003e","manuscriptTitle":"Birth Weight of Term Born Offspring in relation to Long-Term Maternal Cardiovascular Morbidity and Mortality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 08:46:12","doi":"10.21203/rs.3.rs-6749003/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-08-19T09:12:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"European Journal of Epidemiology","date":"2025-06-01T13:49:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-27T06:19:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Epidemiology","date":"2025-05-26T05:03:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejep","sideBox":"Learn more about [European Journal of Epidemiology](https://www.springer.com/journal/10654)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejep/default.aspx","title":"European Journal of Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"23b4ed35-4e92-4d68-b876-cb3aa220edab","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:03:48+00:00","versionOfRecord":{"articleIdentity":"rs-6749003","link":"https://doi.org/10.1007/s10654-025-01355-1","journal":{"identity":"european-journal-of-epidemiology","isVorOnly":false,"title":"European Journal of Epidemiology"},"publishedOn":"2026-02-21 15:57:51","publishedOnDateReadable":"February 21st, 2026"},"versionCreatedAt":"2025-08-27 08:46:12","video":"","vorDoi":"10.1007/s10654-025-01355-1","vorDoiUrl":"https://doi.org/10.1007/s10654-025-01355-1","workflowStages":[]},"version":"v1","identity":"rs-6749003","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6749003","identity":"rs-6749003","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}