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Birth Weight, Gestational Age, and Risk of Cardiovascular Disease in Early Adulthood: Influence of Familial Factors

Birth Weight, Gestational Age, and Risk of Cardiovascular Disease in Early Adulthood: Influence... Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 American Journal of Epidemiology Submitted Manuscript Title: Birth weight, gestational age and risk of cardiovascular disease in early adulthood: Influence of familial factors Authors: Donghao Lu*, Yongfu Yu*, Jonas F. Ludvigsson, Anna Sara Oberg, Henrik Toft Sørensen, Krisztina D. László, Jiong Li#, Sven Cnattingius# * These authors contributed equally. # These authors jointly supervised this work. Correspondence Address: Donghao Lu, Institute of Environmental Medicine, Karolinska Institutet, Nobels väg 13, Stockholm 17177, Sweden, Email: donghao.lu@ki.se; and Jiong Li, Department of Clinical Epidemiology, Aarhus University, Olof Palmes Allé 43-45, Aarhus 8200, Denmark, Email: jl@clin.au.dk © The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of  Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution  License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted reuse, distribution, and  reproduction in any medium, provided the original work is properly cited.  ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Affiliations: Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden (Donghao Lu); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Donghao Lu, Jonas F. Ludvigsson, and Anna Sara Oberg); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA (Donghao Lu and Anna Sara Oberg); Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China (Yongfu Yu); Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark (Yongfu Yu, Henrik Toft Sørensen, and Jiong Li); Department of Pediatrics, Örebro University Hospital, Örebro, Sweden (Jonas F. Ludvigsson); Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden (Krisztina D. László); and Division of Clinical Epidemiology, Department of Medicine Solna, Karolinska Institutet, Stockholm Sweden (Sven Cnattingius). Funding: This work was supported by the Independent Research Fund Denmark (grant numbers: DFF-6110-00019B,9039-00010B and 1030-00012B, to Dr. Li), the Nordic Cancer Union (R275- A15770, to Dr. Li), the Karen Elise Jensens Fond (2016, to Dr. Li), Novo Nordisk Fonden (NNF18OC0052029, to Dr. Li), the Swedish Research Council for Health, Working Life and Welfare (2015-00837 to Dr. László), the Karolinska Institutet Research Foundation (2018-01547 to Dr. László), Heart and Lung Foundation (20180306 to Dr. László), the Swedish Research Council (2020-01003 to Dr. Lu), the Shanghai Rising-Star Program (21QA1401300 to Dr. Yu), and Karolinska Institutet (2368/10-221, Distinguished Professor Award to Dr. Cnattingius). Data Availability Statement: The data underlying this article cannot be shared publicly due to the Danish and Swedish laws. Any researchers interested in obtaining registry data should send ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 their applications and ethical approval to the Danish Data Protection Agency, National Board of Health in Denmark, Statistics Sweden, and the National Board of Health and Welfare in Sweden. Thanks: N/A Conference presentation: N/A Preprint Information: N/A Disclaimer: The funders had no role in the design and conduct of the study; in the collection, analysis or interpretation of the data; or in the preparation, review, or approval of the manuscript. Conflict of Interest: Dr. Ludvigsson coordinates a study on behalf of the Swedish IBD quality register (SWIBREG) which has received funding from the Janssen corporation. The other authors report no conflict of interest. Running Head: Birth weight, gestational age and CVD Key words: Cardiovascular diseases, fetal growth retardation, preterm birth, cohort studies, siblings. Abbreviations: AGA, appropriate for gestational age; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; ICD, International Classification of Diseases; IUGR, intrauterine growth restriction; LGA, large for gestational age; MBR, Medical Birth Register; PIN, personal identification number; PPV; positive predictive value; SGA, small for gestational age. ABSTRACT The association between intrauterine growth restriction (IUGR) and cardiovascular disease (CVD) later in life might be confounded by familial factors. We conducted a bi-national register- based cohort study to assess associations of birthweight for gestational age (GA), a proxy for ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 IUGR, and GA with CVD risk in early adulthood, before and after addressing familial factors via sibling comparison. We included 3,410,334 live non-malformed singleton births in Sweden (1973-1996) and Denmark (1978-1998). During a median follow-up of 10 years from age 18 onwards, 29,742 individuals developed incident CVD (hypertensive, ischemic heart, and cerebrovascular diseases). Compared with individuals born with appropriate birthweight for GA (AGA, 10th-90th percentiles) or full term (39-40 gestational weeks), individuals born severely small for GA (SGA, <3rd percentile) or preterm (22-36 weeks) were at increased risk of CVD [HRs (95% CIs): 1.38 (1.32-1.45) and 1.31 (1.25-1.38), respectively]. The association was attenuated when comparing individuals born SGA with their AGA siblings (1.11, 0.99-1.25), but remained robust when comparing individuals born preterm with their term siblings (1.21, 1.07- 1.37). Our findings suggest that both SGA and preterm birth are associated with CVD risk in early adulthood, with greater familial confounding noted for SGA. INTRODUCTION Cardiovascular disease (CVD) remains the leading contributor to the global burden of disease(1). Rapid progress in both prevention and treatment has produced a decline in CVD mortality in recent decades in high-income countries(2). In some regions previously having decreasing CVD rates, improvements in cardiovascular health have slowed down(2). This trend is particularly concerning in young adult populations(3), in which the incidences of acute myocardial infarction and ischemic stroke are increasing(4, 5). Identification of at-risk individuals is important for targeted prevention strategies. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 A long-standing hypothesis proposes that intrauterine growth restriction (IUGR) can increase the risk of CVD later in life(6). However, most research over the past decades has focused on the influence of low birth weight(7, 8), which may be the result of short gestation length and is a poor proxy for fetal growth(9). Small for gestational age (SGA), i.e., low birth weight for gestational age, is a better proxy for IUGR(10), yet less investigated for CVD risk(11). Moreover, about half of the variation in birth weight or SGA is reported to be attributable to genetic factors(12, 13) that may link smallness at birth with CVD in adulthood(14). A Swedish twin study has indicated a strong genetic influence on the association between birth weight and CVD(15); but such influence has not been studied for singletons. The survival rate of preterm infants has dramatically increased over the past decades(16). Long- term follow-up studies have found that individuals born preterm are more likely to have increased left ventricular mass, abnormal ventricular functions, systemic arterial stiffness, and higher mean blood pressure, which may predispose them to elevated risk of CVD later in life(17, 18). Accumulating evidence has also documented the association between preterm birth and subsequent risk of hypertension(19), although it is less certain whether it is confounded by SGA and/or maternal conditions(20). Moreover, conflicting results have been reported for associations between preterm birth and ischemic heart disease(21-24) and stroke(22, 23), possibly due to small numbers of events. Using nationwide population-based Swedish and Danish registers, we investigated the associations of gestational age and birth weight for gestational age with CVD risk in early adulthood in a bi-national cohort of about 3.5 million individuals. In addition to the population ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 analysis, we compared the risk between siblings to address the potential influence of familial (e.g., genetic and environmental) factors shared by siblings. METHODS Study design We conducted a population-based cohort study of liveborn singletons without malformations who were born in Sweden during 1973-1996 and in Denmark during 1978-1998, as recorded in the nationwide Swedish and Danish Medical Birth Registers (MBRs). The MBRs contain prospectively collected information from standardized antenatal, obstetric, and neonatal records and cover virtually all births in Sweden(25) and Denmark(26). All Swedish and Danish residents are assigned unique personal identification numbers (PINs) at birth or upon immigration(27), and are offered free tax-supported health care(27). Using the PINs, we linked individual information in the MBRs to the Patient-, Causes of Death-, and Migration Registers in Sweden and Denmark, respectively. Within the bi-national population-based cohort, we further performed sibling comparisons among cohort members with at least one full sibling in our database. We identified full siblings using the maternal PIN recorded in the MBRs and the paternal PIN obtained from the Swedish Multi-Generation Register (28) and the Danish Civil Registration System (29), which include information on first-degree relatives (i.e., parents, siblings, and children). It contains information on virtually all mothers and on 95% and 99% of fathers in Sweden and Denmark, respectively(28, 29). During the study period, we identified 2,420,647 liveborn singletons in Sweden and 1,243,198 in Denmark. We excluded births with no or erroneous information on sex (n=1,018), gestational ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 age (n=70,843), and birth weight (n=11,944). Individuals with congenital heart disease, non- specific malformations, or chromosomal abnormalities (n=38,157) were further excluded [International Classification of Diseases (ICD) codes are provided in Web Table 1]. We followed all individuals from 18 years until emigration, death, or December 31, 2014 in Sweden or December 31, 2016 in Denmark, whichever came first. Individuals who died (n=24,733), emigrated (n=100,282), or had a diagnosis of CVD (n=6,534) before 18 years were excluded. In total, 3,410,334 individuals were included in the population analysis. In sibling analyses, we included 2,371,230 individuals having at least one full sibling (70% of those included in population analyses). Inclusions/exclusions were summarized in Web Figure 1. This study was approved by the Regional Ethics Committee in Stockholm (No. 2016/288-31/1, 2020/01381) and the Danish Data Protection Agency (Record No. 2013-41-2569). Individual informed consent is not required for register-based studies in Sweden or Denmark. Exposures We obtained information on gestational age and birth weight from the MBRs. In the 1970s, gestational age was primarily estimated based on the last menstrual period in both countries. As the study period progressed, this approach was gradually replaced with ultrasound assessments of fetal size no later than early in the second trimester. It has been shown that gestational age estimates using both approaches do not differ significantly in register data(30). Gestational age was categorized into 22-36 weeks (preterm), 37-38 weeks (early term), 39-40 weeks (full term), and >41 weeks (late term to post-term). Gestational ages of 22-36 weeks were further categorized as 22-31 weeks (very preterm) and 32-36 weeks (moderately preterm), when ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 subgroup analyses were possible. There were too few events to study extremely preterm births (22-28 weeks). The percentile of birth weight for gestational age was calculated according to a reference curve for fetal growth based on ultrasound-estimated fetal weights in both Swedish and Danish samples(31). As described elsewhere(32-34), individuals were then grouped into <3rd percentile (severe SGA), 3rd to <10th percentile (moderately SGA), 10th to 90th percentile (appropriate for gestational age [AGA]), >90th to 97th percentile (moderately large for gestational age [LGA]), and >97th percentile (severe LGA) of birth weight for gestational age. Outcomes Our primary outcome was composite CVD, consisting of hypertensive disease, ischemic heart disease, and cerebrovascular disease. We identified inpatient/specialized outpatient diagnoses of CVD from the Patient Registers, using the specific ICD codes provided in Web Table 1. The Swedish Patient Register has collected inpatient discharge records since 1964 (nationwide since 1987) and records of hospital-based outpatient care since 2001(35). The Danish Patient Registry has maintained hospital discharge records since 1977 and outpatient clinic and emergency records since 1995(36). We identified deaths due to CVD from the nationwide Causes of Death Registers (37, 38). We used both primary and secondary diagnoses or causes of death to identify CVD. As secondary outcomes, we separately analysed three contributing CVD subtypes: hypertensive disease, ischemic heart disease, and cerebrovascular disease (including hemorrhagic stroke, ischemic stroke, and others). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 A range of CVD diagnoses/causes of death has been validated in the Swedish and Danish Patient Registers and Causes of Death Registers and the overall quality of these registers are considered high. For instance, in the Swedish Patient Register, the positive predictive value (PPV) is 98% for myocardial infarction(39) and 98.6% for stroke(35). In the Danish Patient Registry, the PPV is >90% for myocardial infarction(40). In the Causes of Death Registers, the PPV is more than 80% for ischemic heart disease and cerebrovascular disease in Sweden(41) and 97.2% for myocardial infarction in Denmark(42). Covariates We used the MBRs to obtain demographic information on cohort members, including sex and year of birth. We also extracted information on their parents, including maternal age, maternal country of birth, parity, maternal marital status, and maternal smoking in early pregnancy. Missingness in covariates was coded as “unknown”, given the relatively small missing rates. Using the MBRs, Patient Registers, and the Danish National Diabetes Register (available since 1995), we identified maternal complications during pregnancy, including maternal hypertensive disease (essential hypertension, gestational hypertension, preeclampsia, and eclampsia) and diabetes (pregestational and gestational diabetes). We also obtained information on maternal and paternal CVD history at the time of the individual’s birth from the Patient Registers. Relevant ICD codes are listed in Web Table 1. Statistical analysis ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 We first calculated incidence rates (IRs) of CVD by birth and parental characteristics. We also estimated age-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of CVD by contrasting these characteristics, using Cox regression with attained age as the underlying timescale. In the population analysis, we employed Cox regression to compute HRs and 95% CIs of CVD among severe or moderately SGA and LGA individuals compared with AGA individuals. We also estimated HRs of CVD among individuals born very preterm, moderately preterm, early term, and late to post-term compared to individuals born full term. Estimates were crude or adjusted for demographic characteristics, including attained age (as the underlying timescale), sex, country, and year of birth; factors associated with SGA or preterm birth, including parity, maternal age at birth, maternal country of birth, and maternal marital status; as well as predictors of CVD risk in offspring, i.e., maternal and paternal history of CVD. To illustrate the independent effect, we mutually adjusted for continuous gestational age and birth weight for gestational age in an additional model. The proportional hazards assumption was not violated according to Schoenfeld residual plots. To shed light on the impact of familial factors, we performed a sibling comparison using stratified Cox regression analysis allowing the baseline hazard to vary between families (i.e., stratifying by families). Briefly, this analysis contrasted the rates within each set of full siblings discordant on birth weight for gestational age or gestational age and CVD, although non- discordant siblings were also included in the analysis and contributed to the point estimates of covariates. This approach inherently controls for familial (e.g., genetic, lifestyle, and ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 socioeconomic) factors that siblings share (43). We adjusted for the aforementioned covariates except for country and maternal country of birth (no variation within siblings). We then estimated the HRs of CVD for each percentile of birth weight for gestational age and week of gestational age, where we applied restricted cubic splines and used the 50th percentile and 40 weeks as the reference for birth weight for gestational age and gestational age, respectively. To explore different effects on CVD subtypes, we separately examined the associations for hypertensive disease, ischemic heart disease, and cerebrovascular disease. We performed several additional analyses to test the robustness of our findings. Firstly, to illustrate the comparability between the entire cohort and the sibling cohort, we compared the baseline characteristics between two cohorts and conducted a population analysis restricted to individuals with at least one sibling. Secondly, to understand whether hypertensive disease dominated the observed associations, we repeated the primary analysis by limiting outcomes to CVD other than hypertensive disease. Thirdly, to address the concern that secondary diagnoses or causes of death had lower validity, we repeated the analyses only using the primary diagnosis or cause of death. Fourthly, to better control for confounding, we restricted analyses to those whose mothers had no record of hypertensive or diabetic disease or of smoking early in pregnancy; and to individuals born during 1992-1994 in Sweden for the adjustment of maternal body mass index (BMI). In addition, because of different rates of CVD in Sweden vs. Denmark, as well as the known sex disparity in CVD occurrence, we performed analyses stratified by country and sex. Finally, we assessed potential carryover effect in sibling analysis, i.e. if the exposure to SGA/preterm birth in the first sibling may influence the risk of being SGA/preterm ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 for the second sibling. To this regard, we performed analysis by separating sibling pairs with the first sibling exposed to SGA/preterm birth from those with the second sibling exposed. Data were processed using SAS 9.4 (SAS Institute) and analysed using STATA 14.2 (StataCorp). RESULTS During a median follow-up of 10 years (mean age at the end of follow-up was 29 years, range 18-41 years), 29,742 individuals developed incident CVD (IR 0.81 per 1,000 person-years). After controlling for attained age, individuals born in Denmark or those who were born in more recent years had a higher risk of CVD compared with other cohort members (Web Table 2). Slightly elevated CVD risk was observed among individuals whose mothers were young at childbirth (≤19 years), from the Nordic countries, unmarried, or smoked during pregnancy. Maternal pregestational diabetes, hypertensives disease before and during pregnancy, and maternal/paternal history of CVD were associated with an elevated risk of CVD in the offspring. Primary analysis In the primary population analysis, individuals born with severe SGA (<3rd percentile) were found to be at higher risk of CVD in early adulthood, compared to individuals born AGA (adjusted-HR 1.38, 95% CI 1.32-1.45; Table 1, Model 1). In the sibling comparison, this association was substantially attenuated (by 71%; to adjusted-HR 1.11, 95% CI 0.99-1.25). Similar associations were noted for moderately SGA (3rd to <10th percentile), although the estimates were lower. Compared to individuals born AGA, a lower risk of CVD was found for moderately but not severe LGA, in both the population and the sibling analyses. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Preterm birth (22-36 weeks) was associated with an elevated risk of CVD (Table 1, Model 1, adjusted-HR 1.31 (1.25-1.38)), compared to full-term birth (39-40 weeks). Estimates were robust, yet moderately attenuated (by 32%) in sibling analysis. Of note, the magnitude of associations gradually declined by increasing gestational age (from 22-31 weeks to >41 weeks). Mutual adjustments for birth weight for gestational age and gestational age yielded similar results (Table 1, adjusted-HRs in Model 2). Figure 1 further confirms the quasi-linear relationships of both birth weight for gestational age and gestational age with CVD risk. The attenuation of associations appeared greater for birth weight for gestational age than for gestational age. The estimates are presented in Web Table 3. CVD subtypes Severe SGA was associated with elevated risks of hypertensive disease, ischemic heart disease, and cerebrovascular disease in population analyses. However, these associations were attenuated in the sibling comparisons (Table 2). Of note, in sibling analyses, such attenuation was observed for ischemic stroke but not for hemorrhagic stroke. A similar pattern with lower estimates was found for moderately SGA. Preterm birth (22-36 weeks) was associated with elevated risks of hypertensive disease and ischemic stroke in both population and sibling analyses. Preterm birth was associated with elevated risks of ischemic heart disease and hemorrhagic stroke in the population analysis but not in the sibling analyses (Table 3). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Additional analyses Individuals with at least one sibling were highly comparable to the entire cohort (Web Table 4) and restricting to these individuals yielded very similar results in population comparisons for SGA and preterm birth (Web Table 5). Analyses of CVD risk after excluding hypertensive disease; after excluding CVD as secondary diagnoses or secondary causes of death; or after restricting the analyses to individuals of mothers without maternal hypertensive disease, diabetes, or smoking during pregnancy, yielded comparable results, with widely overlapping CIs (Web Tables 6-7). Adjustment for maternal BMI also did not change the results among individuals born during 1992-1994 in Sweden (Web Table 8). In addition, we observed similar associations in men and women, and in Danes and Swedes (Web Table 9). Finally, we observed similar results between sibling pairs with different exposure orders (Web Table 10). DISCUSSION In this bi-national cohort study of about 3.4 million individuals in Sweden and Denmark, we found that those born SGA or preterm were at elevated risk of CVD in early adulthood, compared with those born AGA or at full term, respectively. Importantly, when SGA individuals were compared with their AGA full siblings, the elevated risk of early-onset CVD was substantially reduced or even eliminated. In contrast, preterm birth was associated with a robust risk increase in the sibling analysis despite of a moderate attenuation of the point estimate. Similar risk patterns were observed for the linear relationship with CVD risk, and for most CVD subtypes. Birth weight for gestational age ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Most previous studies in this area have investigated the risk of CVD later in life in relation to birth weight or birth weight with adjustment for gestational age(7, 8). However, these approaches may not accurately classify infants not reaching their gestational growth potential. Moreover, adjustment for gestational age, a common practice in previous studies, may lead to collider bias(44), and cannot distinguish IUGR from constitutionally small fetuses who have reached their growth potential(33). Although a handful of studies have illustrated positive associations between SGA and risk factors or preclinical signs of CVD(45-47), we are aware of only two studies that defined SGA based on fetal growth curves and showed that individuals with birth weight for gestational age < 2 standard deviations below the mean were at increased risk of ischemic heart disease(21, 48). Our population analyses further showed consistent associations between SGA and risks of CVD overall, hypertensive disease, ischemic heart disease, and ischemic stroke in early adulthood. To the best of our knowledge, this is the first study to show that, when SGA individuals were compared with AGA siblings, these associations were attenuated towards the null, which indicates a substantial influence of familial (genetic and environmental) factors shared by siblings. Genetic factors influence both fetal growth and risk of CVD(49). The genetic predisposition for low birth weight has been associated with ischemic heart disease(50). Positive, although statistically non-significant, associations have been noted between genetic variants of low birth weight and risks of ischemic stroke(50) and hypertension(51). These findings are supported by our results in sibling comparisons, which showed attenuated associations between SGA and CVD and its subtypes (except for hemorrhagic stroke). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 On the other hand, IUGR has been suggested to lead to functional alterations in the fetal development, including in the cardiovascular system (11, 52), which may predispose them to CVD in adulthood. It is also possible that IUGR results in a higher risk of renal disease(53) and subsequently increased CVD risk(54). Although the association between SGA and CVD risk was attenuated after controlling for familial factors, we also found a quasi-linear positive relationship with CVD risk across birth weight percentiles for gestational age, particularly in sibling comparisons. This relationship might be explained by the residual confounding in sibling comparison. It is also plausible that there could be a causal relation between IUGR and CVD development in adulthood. Previous studies often report a J- or U-shaped association between birth weight and CVD(7). However, we did not observe increased CVD risk among LGA individuals. This inconsistency could be explained by earlier studies failing to adequately adjust for maternal history of or propensity for cardiometabolic disease(7). Indeed, the linear trend was even more evident in sibling comparisons, which better control for the influence of familial factors, including genetic and lifestyle factors, and unmeasured maternal chronic diseases, on CVD risk in offspring. However, our analysis cannot distinguish whether the influence is from parental genetic makeup, familial environmental influence, and/or their interaction. Future research is needed to understand the complexity of contributors. It is also worth noting that our group has found that low birth weight was associated with increased risk of hemorrhagic stroke within twin pairs(15). In the present study, we also found consistent associations between severe SGA and hemorrhagic stroke in both population and sibling analyses, although statistical precision was limited for siblings. Taken together, our ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 findings suggest that IUGR may increase subsequent risk of hemorrhagic stroke independent of familial factors. Gestational age In line with previous investigations(19, 20), our data confirmed the association between preterm birth and risk of hypertensive disease in early adulthood. This association was fairly robust in analyses controlling for birth weight for gestational age and in sibling comparison, confirming a previously noted association in an underpowered study of Swedish siblings(19). With adjustment for parental history of CVD and maternal factors stable across pregnancies, our finding supports that preterm birth confers an elevated risk of hypertension independent of SGA and maternal chronic diseases that may lead to preterm delivery(20). Our finding that preterm birth was also associated with elevated risks of ischemic heart disease and ischemic stroke in population analyses is in agreement with some(24, 55, 56), but not all(21-23), previous studies. In line with a recent report on stroke using both population and sibling comparisons(56), the largely comparable estimates between both comparisons in our data suggest no substantial familial confounding, although statistical precision was hampered in sibling comparisons. We are not aware of any studies of preterm birth and ischemic heart disease using sibling comparisons. Furthermore, we found that preterm birth was associated with an increased risk of CVD overall in both population and sibling analyses, and the overall risk of CVD increased linearly with decreasing gestational age. Together, these findings indicate a causal relation between preterm birth and CVD development later in life, although a contribution of familial confounding to the association was also observed. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 They corroborate current knowledge about the subclinical structural and functional alterations in essential organs among individuals born preterm, increasing vulnerability to CVD in adulthood(17). However, alternative mechanisms, such as preterm birth-induced aberrant lipid levels or gut microbiota, may also contribute to the observed associations(57). Moreover, renal disease may mediate the observed association between preterm birth and CVD(54, 58). Furthermore, preterm birth is often a consequence of pregnancy complications, and the responsible pathology may itself contribute to later health problems in offspring(59-61). It is therefore plausible that more factors than just immaturity could explain our findings concerning the association between preterm birth and CVD risk. Strengths and limitations This large-scale bi-national cohort with long and virtually complete data capture up to 41 years of age allowed us to investigate cardiovascular outcomes in early adulthood. The nationwide, prospectively collected, and high-quality register data minimized common biases in observational studies (e.g., recall bias). The sibling comparison rigorously controlled for familial factors (e.g., genetics and early environment) shared between full siblings. Last, our findings are robust as similar associations were found in two independent countries/populations, although a higher absolute risk of CVD was observed in Denmark than in Sweden. This may be due to differences in registration(35, 36) and lifestyle factors(62). Our study has several limitations. Firstly, to better capture CVD cases, we also used information from secondary diagnoses or causes of death, which may have lower validity and represent other underlying diseases leading to the healthcare visit or death (e.g., hospitalized due to renal disease ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 but comorbid with hypertension(54)). Reassuringly, we observed comparable associations when limiting outcomes to primary diagnoses or causes of death. Secondly, we missed CVD cases (e.g., hypertensive disease) treated only in the general practice setting. However, such misclassification is likely to be non-differential with respect to the exposure and would have attenuated the associations. Most individuals with ischemic heart disease or cerebrovascular disease are treated in specialist hospital clinics or emergency departments, which are well covered by national registers. When we restricted the analysis to these two diseases and obtained similar results. Thirdly, we cannot rule out the influence of residual confounding. For instance, information on maternal gestational diabetes is available only from 1987 in Sweden. However, about 30-84% of women with gestational diabetes have a recurrent gestational diabetes in their next pregnancy(63). This should have been partly controlled for among siblings who shared the exposure to maternal gestational diabetes. Information on maternal BMI is available only for births from 1992 onward in Sweden and from 2004 in Denmark. However, we performed population analyses by restricting to individuals born during 1992-1996 in Sweden for additional adjustment for maternal BMI, which yielded materially unchanged results. Fourthly, sibling comparison cannot address unmeasured confounding from factors that vary between pregnancies(64) and may be subject to carryover effects(65). The latter may occur if the exposure to SGA/preterm birth in the first sibling influences the risk of being SGA/preterm for the second sibling. However, we have performed analysis by separating sibling pairs with different exposure orders, which yielded comparable results. Moreover, not all individuals had a sibling and individuals included in the sibling analysis (70%) may be a selected group. Reassuringly, the birth and parental characteristics in the sibling analysis were highly comparable to those included in the population analysis, although it is not considered definitive ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 evidence on generalizability(66). Lastly, our study examined the CVD risk during age 18-41 years with a median follow-up of 10 years. Future studies with longer follow-up are needed to understand the SGA- or preterm birth-associated CVD risk in middle and late adulthood when most CVD diagnoses emerge. However, until such large-scale prospective data are available, our findings may provide new insights into the shared familial influences linking IUGR to CVD with onset in early adulthood. Conclusions Our findings suggest that SGA and preterm birth are associated with an elevated risk of CVD in early adulthood. Familial confounding might play a greater role on the association between SGA and CVD risk. Although familial factors would also contribute to the association between preterm birth and CVD, the robust association in sibling comparison supports the hypothesis of a causal relationship. References 1. Roth GA, Mensah GA, Johnson CO, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol 2020;76(25):2982-3021. 2. Mensah GA, Wei GS, Sorlie PD, et al. Decline in Cardiovascular Mortality: Possible Causes and Implications. Circ Res 2017;120(2):366-80. 3. Gooding HC, Gidding SS, Moran AE, et al. Challenges and Opportunities for the Prevention and Treatment of Cardiovascular Disease Among Young Adults: Report From a National Heart, Lung, and Blood Institute Working Group. J Am Heart Assoc 2020;9(19):e016115. 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Unexplained differences between hospital and mortality data indicated mistakes in death certification: an investigation of 1,094 deaths in Sweden during 1995. J Clin Epidemiol 2009;62(11):1202-9. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 42. Madsen M, Davidsen M, Rasmussen S, et al. The validity of the diagnosis of acute myocardial infarction in routine statistics: a comparison of mortality and hospital discharge data with the Danish MONICA registry. J Clin Epidemiol 2003;56(2):124-30. 43. Donovan SJ, Susser E. Commentary: Advent of sibling designs. Int J Epidemiol 2011;40(2):345-9. 44. Wilcox AJ, Weinberg CR, Basso O. On the pitfalls of adjusting for gestational age at birth. Am J Epidemiol 2011;174(9):1062-8. 45. Skilton MR, Viikari JS, Juonala M, et al. 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Birthweight, Type 2 Diabetes Mellitus, and Cardiovascular Disease: Addressing the Barker Hypothesis With Mendelian Randomization. Circ Genom Precis Med 2018;11(6):e002054. 51. Zheng Y, Huang T, Wang T, et al. Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood. Eur J Epidemiol 2020;35(7):685-97. 52. Ross MG, Beall MH. Adult sequelae of intrauterine growth restriction. Semin Perinatol 2008;32(3):213-8. 53. Gjerde A, Lillås BS, Marti HP, et al. Intrauterine growth restriction, preterm birth and risk of end-stage renal disease during the first 50 years of life. Nephrol Dial Transplant 2020;35(7):1157-63. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 54. Said S, Hernandez GT. The link between chronic kidney disease and cardiovascular disease. J Nephropathol 2014;3(3):99-104. 55. Koupil I, Leon DA, Lithell HO. Length of gestation is associated with mortality from cerebrovascular disease. J Epidemiol Community Health 2005;59(6):473-4. 56. Crump C, Sundquist J, Sundquist K. Stroke Risks in Adult Survivors of Preterm Birth: National Cohort and Cosibling Study. Stroke 2021;52(8):2609-17. 57. Bavineni M, Wassenaar TM, Agnihotri K, et al. Mechanisms linking preterm birth to onset of cardiovascular disease later in adulthood. Eur Heart J 2019;40(14):1107-12. 58. Crump C, Sundquist J, Winkleby MA, et al. Preterm birth and risk of chronic kidney disease from childhood into mid-adulthood: national cohort study. BMJ 2019;365:l1346. 59. Basso O, Wilcox AJ. Might rare factors account for most of the mortality of preterm babies? Epidemiology 2011;22(3):320-7. 60. Cairncross ZF, Chaput KH, McMorris C, et al. Roles of the underlying cause of delivery and gestational age on long-term child health. Paediatr Perinat Epidemiol 2020;34(3):331-40. 61. Gagliardi L, Rusconi F, Da Fre M, et al. Pregnancy disorders leading to very preterm birth influence neonatal outcomes: results of the population-based ACTION cohort study. Pediatr Res 2013;73(6):794-801. 62. Collaborators NBoD. Life expectancy and disease burden in the Nordic countries: results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. Lancet Public Health 2019;4(12):e658-e69. 63. Kim C, Berger DK, Chamany S. Recurrence of gestational diabetes mellitus: a systematic review. Diabetes Care 2007;30(5):1314-9. 64. Frisell T, Oberg S, Kuja-Halkola R, et al. Sibling comparison designs: bias from non- shared confounders and measurement error. Epidemiology 2012;23(5):713-20. 65. Sjolander A, Frisell T, Kuja-Halkola R, et al. Carryover Effects in Sibling Comparison Designs. Epidemiology 2016;27(6):852-8. 66. Sjolander A, Oberg S, Frisell T. Generalizability and effect measure modification in sibling comparison studies. Eur J Epidemiol 2022;37(5):461-76. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 1. Associations of birth weight for gestational age and gestational age with risk of cardiovascular disease: a bi-national cohort study in Denmark and Sweden, 1973-2016. Population Analysis Sibling Analysis a b a b Crude model Model 1 Model 2 No. Crude model Model 1 Model 2 No. of No. No. of Exposures of Individu of Individu 95% 95% 95% 95% 95% 95% HR HR HR CVD HR HR HR als CVD CI CI CI als CI CI CI Birth weight for gestational age, percentiles 1.38, 1.32, 1.30, 0.95, 0.99, 0.99, <3rd 125,306 1,865 1.44 1.38 1.36 1,710 850 1.07 1.11 1.12 1.51 1.45 1.43 1.21 1.25 1.26 3rd to 1.20, 1.18, 1.19, 0.96, 0.99, 1.00, 281,657 3,424 1.25 1.22 1.23 3,558 1,692 1.05 1.07 1.08 9th 1.29 1.27 1.27 1.14 1.17 1.18 10th to 2,690,9 22,36 Refere Refere Refere Refere Refere 1.00 1.00 1.00 9,074 3,452 1.00 1.00 1.00 90th 23 0 nt nt nt nt nt 91th to 0.84, 0.83, 0.82, 0.76, 0.74, 0.73, 222,985 1,444 0.88 0.88 0.87 2,458 792 0.85 0.82 0.81 97th 0.93 0.93 0.91 0.94 0.92 0.91 0.93, 0.92, 0.89, 0.83, 0.80, 0.78, >97th 89,463 649 1.00 1.00 0.97 1,002 339 0.98 0.95 0.93 1.09 1.08 1.04 1.16 1.12 1.10 Gestational age, weeks 1.24, 1.25, 1.23, 1.08, 1.07, 1.08, 22-36 152,339 1,634 1.30 1.31 1.29 1,742 786 1.22 1.21 1.22 1.37 1.38 1.36 1.38 1.37 1.38 1.34, 1.30, 1.23, 1.03, 1.01, 0.99, 22-31 14,747 167 1.56 1.51 1.43 176 85 1.47 1.44 1.41 1.82 1.76 1.67 2.09 2.05 2.00 1.21, 1.23, 1.21, 1.06, 1.05, 1.06, 32-36 137,592 1,467 1.28 1.29 1.28 1,633 731 1.20 1.19 1.21 1.35 1.37 1.35 1.36 1.35 1.37 1.07, 1.10, 1.11, 0.96, 0.95, 0.97, 37-38 533,517 4,655 1.10 1.14 1.15 5,702 2,210 1.03 1.02 1.04 1.14 1.18 1.19 1.11 1.09 1.12 1,777,9 15,15 Refere Refere Refere Refere Refere Refere 39-40 1.00 1.00 1.00 12,806 4,952 1.00 1.00 1.00 41 4 nt nt nt nt nt nt 0.91, 0.95, 0.93, 0.93, 0.94, 0.91, >41 946,537 8,299 0.94 0.97 0.95 8,142 3,431 0.98 1.00 0.97 0.96 1.00 0.98 1.04 1.06 1.02 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of cardiovascular disease. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth, and were additionally stratified by sibling sets. In both population and sibling analyses, HRs were mutually adjusted for gestational age or birth weight for gestational age in addition to Model 1. Only sets of siblings that were discordant on exposures and CVD were presented, which explains the numbers among individuals with gestational age 22-36 weeks are not the sum of numbers from those with 22-31 and 32-36 weeks. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 2. Associations of birth weight for gestational age with risk of cardiovascular disease subtypes: a bi-national cohort study in Denmark and Sweden, 1973-2016 Outcome and Population Analysis Sibling Analysis Percentile of No. of No. of No. of No. of a a a a Birth Weight for HR 95% CI HR 95% CI b b Individuals CVD Individuals CVD Gestational Age Hypertensive disease <3rd 125,306 1,225 1.42 1.34, 1.51 1,131 570 1.15 0.99, 1.33 3rd to 9th 281,657 2,290 1.27 1.22, 1.33 2,330 1,136 1.11 1.00, 1.24 10th to 90th 2,690,923 14,387 1.00 Referent 5,958 2,229 1.00 Referent 91th to 97th 222,985 885 0.84 0.79, 0.90 1,600 495 0.78 0.68, 0.89 >97th 89,463 417 1.00 0.91, 1.11 659 218 0.91 0.73, 1.12 Ischemic heart disease <3rd 125,306 292 1.50 1.33, 1.70 274 133 1.03 0.75, 1.41 3rd to 9th 281,657 459 1.17 1.06, 1.29 482 218 0.90 0.71, 1.13 10th to 90th 2,690,923 2,903 1.00 Referent 1,156 454 1.00 Referent 91th to 97th 222,985 190 0.90 0.78, 1.05 271 85 0.69 0.50, 0.96 >97th 89,463 75 0.90 0.72, 1.13 123 33 0.64 0.36, 1.12 Cerebrovascular disease <3rd 125,306 462 1.30 1.18, 1.43 417 204 1.11 0.87, 1.40 3rd to 9th 281,657 843 1.14 1.06, 1.22 937 411 0.99 0.85, 1.17 10th to 90th 2,690,923 6,002 1.00 Referent 2,435 902 1.00 Referent 91th to 97th 222,985 429 0.95 0.87, 1.05 681 234 0.98 0.80, 1.19 >97th 89,463 181 1.02 0.88, 1.18 264 94 1.16 0.85, 1.57 Hemorrhagic stroke <3rd 125,306 179 1.32 1.14, 1.54 164 84 1.33 0.91, 1.93 3rd to 9th 281,657 342 1.20 1.07, 1.34 371 167 1.08 0.84, 1.39 10th to 90th 2,690,923 2,351 1.00 Referent 981 365 1.00 Referent 91th to 97th 222,985 174 0.97 0.83, 1.14 281 97 0.89 0.66, 1.21 >97th 89,463 67 0.94 0.74, 1.20 100 31 0.92 0.56, 1.51 Ischemic stroke <3rd 125,306 145 1.30 1.09, 1.54 140 66 1.10 0.71, 1.70 3rd to 9th 281,657 254 1.10 0.96, 1.25 278 117 0.80 0.58, 1.11 10th to 90th 2,690,923 1,853 1.00 Referent 707 261 1.00 Referent 91th to 97th 222,985 147 1.08 0.91, 1.28 204 79 1.49 1.03, 2.17 >97th 89,463 56 1.04 0.80, 1.36 78 25 1.05 0.56, 1.94 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth and were additionally stratified by sibling sets. Only sets of siblings that were discordant on exposures and CVD were presented. In the subgroup analysis, we presented results of two major types of cerebrovascular disease; diseases other than hemorrhagic or ischemic stroke were not present. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 3. Associations of gestational age with risk of cardiovascular disease subtypes: a bi- national cohort study in Denmark and Sweden, 1973-2016 Population Analysis Sibling Analysis Outcome and No. of No. of No. of No. of a a a a Gestational Age HR 95% CI HR 95% CI b b Individuals CVD Individuals CVD Hypertensive disease 22-36 152,339 1,083 1.34 1.26, 1.43 1,144 525 1.24 1.07, 1.45 37-38 533,517 3,078 1.16 1.11, 1.21 3,731 1,441 1.05 0.96, 1.14 39-40 1,777,941 9,699 1.00 Referent 8,344 3,219 1.00 Referent >41 946,537 5,344 0.95 0.92, 0.99 5,318 2,234 0.96 0.89, 1.03 Ischemic heart disease 22-36 152,339 223 1.37 1.20, 1.58 195 91 1.11 0.75, 1.63 37-38 533,517 565 1.12 1.02, 1.23 697 254 0.86 0.70, 1.06 39-40 1,777,941 2,048 1.00 Referent 1,603 630 1.00 Referent >41 946,537 1,083 1.02 0.95, 1.10 1,000 411 0.91 0.77, 1.08 Cerebrovascular disease 22-36 152,339 421 1.28 1.16, 1.41 494 212 1.24 0.99, 1.55 37-38 533,517 1,194 1.10 1.03, 1.17 1,509 587 1.06 0.93, 1.21 39-40 1,777,941 4,051 1.00 Referent 3,445 1,282 1.00 Referent >41 946,537 2,251 1.01 0.96, 1.07 2,239 932 1.11 1.00, 1.24 Hemorrhagic stroke 22-36 152,339 157 1.18 1.00, 1.39 189 81 1.07 0.76, 1.52 37-38 533,517 467 1.07 0.96, 1.19 598 225 1.01 0.82, 1.25 39-40 1,777,941 1,592 1.00 Referent 1,353 507 1.00 Referent >41 946,537 897 1.03 0.95, 1.12 865 372 1.12 0.94, 1.33 Ischemic stroke 22-36 152,339 133 1.29 1.08, 1.55 138 67 1.70 1.11, 2.62 37-38 533,517 376 1.11 0.99, 1.25 424 182 1.31 1.01, 1.70 39-40 1,777,941 1,255 1.00 Referent 1,042 383 1.00 Referent >41 946,537 691 0.98 0.89, 1.07 744 284 0.99 0.81, 1.21 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth, and were additionally stratified by sibling sets. Only sets of siblings that were discordant on exposures and CVD were presented. In the subgroup analysis, we presented results of two major types of cerebrovascular disease; diseases other than hemorrhagic or ischemic stroke were not present. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Figure legends Figure 1. Hazard ratios (HRs) of cardiovascular disease (CVD) in individuals across birth weight for gestational age and gestational age: a bi-national cohort study in Denmark and Sweden, 1973-2016 A) Population analysis and B) sibling analysis of CVD in relation to birth weight for gestational age. C) Population analysis and D) sibling analysis of CVD in relation to gestational age. Birth weight percentile for gestational age and gestational age were splined using restricted cubic spline with 4 knots, and the 50th percentile or week 40 was used as the reference. In the population analysis, the estimates were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates, except for country and maternal country of birth, and were additionally stratified by sibling sets. Black line indicates HR and grey area denotes 95% confidence interval. Dash line indicates null association (HR=1.0). ORIGINAL UNEDITED MANUSCRIPT http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Epidemiology Oxford University Press

Birth Weight, Gestational Age, and Risk of Cardiovascular Disease in Early Adulthood: Influence of Familial Factors

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Oxford University Press
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© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
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1476-6256
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10.1093/aje/kwac223
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Abstract

Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 American Journal of Epidemiology Submitted Manuscript Title: Birth weight, gestational age and risk of cardiovascular disease in early adulthood: Influence of familial factors Authors: Donghao Lu*, Yongfu Yu*, Jonas F. Ludvigsson, Anna Sara Oberg, Henrik Toft Sørensen, Krisztina D. László, Jiong Li#, Sven Cnattingius# * These authors contributed equally. # These authors jointly supervised this work. Correspondence Address: Donghao Lu, Institute of Environmental Medicine, Karolinska Institutet, Nobels väg 13, Stockholm 17177, Sweden, Email: donghao.lu@ki.se; and Jiong Li, Department of Clinical Epidemiology, Aarhus University, Olof Palmes Allé 43-45, Aarhus 8200, Denmark, Email: jl@clin.au.dk © The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of  Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution  License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted reuse, distribution, and  reproduction in any medium, provided the original work is properly cited.  ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Affiliations: Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden (Donghao Lu); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Donghao Lu, Jonas F. Ludvigsson, and Anna Sara Oberg); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA (Donghao Lu and Anna Sara Oberg); Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China (Yongfu Yu); Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark (Yongfu Yu, Henrik Toft Sørensen, and Jiong Li); Department of Pediatrics, Örebro University Hospital, Örebro, Sweden (Jonas F. Ludvigsson); Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden (Krisztina D. László); and Division of Clinical Epidemiology, Department of Medicine Solna, Karolinska Institutet, Stockholm Sweden (Sven Cnattingius). Funding: This work was supported by the Independent Research Fund Denmark (grant numbers: DFF-6110-00019B,9039-00010B and 1030-00012B, to Dr. Li), the Nordic Cancer Union (R275- A15770, to Dr. Li), the Karen Elise Jensens Fond (2016, to Dr. Li), Novo Nordisk Fonden (NNF18OC0052029, to Dr. Li), the Swedish Research Council for Health, Working Life and Welfare (2015-00837 to Dr. László), the Karolinska Institutet Research Foundation (2018-01547 to Dr. László), Heart and Lung Foundation (20180306 to Dr. László), the Swedish Research Council (2020-01003 to Dr. Lu), the Shanghai Rising-Star Program (21QA1401300 to Dr. Yu), and Karolinska Institutet (2368/10-221, Distinguished Professor Award to Dr. Cnattingius). Data Availability Statement: The data underlying this article cannot be shared publicly due to the Danish and Swedish laws. Any researchers interested in obtaining registry data should send ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 their applications and ethical approval to the Danish Data Protection Agency, National Board of Health in Denmark, Statistics Sweden, and the National Board of Health and Welfare in Sweden. Thanks: N/A Conference presentation: N/A Preprint Information: N/A Disclaimer: The funders had no role in the design and conduct of the study; in the collection, analysis or interpretation of the data; or in the preparation, review, or approval of the manuscript. Conflict of Interest: Dr. Ludvigsson coordinates a study on behalf of the Swedish IBD quality register (SWIBREG) which has received funding from the Janssen corporation. The other authors report no conflict of interest. Running Head: Birth weight, gestational age and CVD Key words: Cardiovascular diseases, fetal growth retardation, preterm birth, cohort studies, siblings. Abbreviations: AGA, appropriate for gestational age; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; ICD, International Classification of Diseases; IUGR, intrauterine growth restriction; LGA, large for gestational age; MBR, Medical Birth Register; PIN, personal identification number; PPV; positive predictive value; SGA, small for gestational age. ABSTRACT The association between intrauterine growth restriction (IUGR) and cardiovascular disease (CVD) later in life might be confounded by familial factors. We conducted a bi-national register- based cohort study to assess associations of birthweight for gestational age (GA), a proxy for ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 IUGR, and GA with CVD risk in early adulthood, before and after addressing familial factors via sibling comparison. We included 3,410,334 live non-malformed singleton births in Sweden (1973-1996) and Denmark (1978-1998). During a median follow-up of 10 years from age 18 onwards, 29,742 individuals developed incident CVD (hypertensive, ischemic heart, and cerebrovascular diseases). Compared with individuals born with appropriate birthweight for GA (AGA, 10th-90th percentiles) or full term (39-40 gestational weeks), individuals born severely small for GA (SGA, <3rd percentile) or preterm (22-36 weeks) were at increased risk of CVD [HRs (95% CIs): 1.38 (1.32-1.45) and 1.31 (1.25-1.38), respectively]. The association was attenuated when comparing individuals born SGA with their AGA siblings (1.11, 0.99-1.25), but remained robust when comparing individuals born preterm with their term siblings (1.21, 1.07- 1.37). Our findings suggest that both SGA and preterm birth are associated with CVD risk in early adulthood, with greater familial confounding noted for SGA. INTRODUCTION Cardiovascular disease (CVD) remains the leading contributor to the global burden of disease(1). Rapid progress in both prevention and treatment has produced a decline in CVD mortality in recent decades in high-income countries(2). In some regions previously having decreasing CVD rates, improvements in cardiovascular health have slowed down(2). This trend is particularly concerning in young adult populations(3), in which the incidences of acute myocardial infarction and ischemic stroke are increasing(4, 5). Identification of at-risk individuals is important for targeted prevention strategies. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 A long-standing hypothesis proposes that intrauterine growth restriction (IUGR) can increase the risk of CVD later in life(6). However, most research over the past decades has focused on the influence of low birth weight(7, 8), which may be the result of short gestation length and is a poor proxy for fetal growth(9). Small for gestational age (SGA), i.e., low birth weight for gestational age, is a better proxy for IUGR(10), yet less investigated for CVD risk(11). Moreover, about half of the variation in birth weight or SGA is reported to be attributable to genetic factors(12, 13) that may link smallness at birth with CVD in adulthood(14). A Swedish twin study has indicated a strong genetic influence on the association between birth weight and CVD(15); but such influence has not been studied for singletons. The survival rate of preterm infants has dramatically increased over the past decades(16). Long- term follow-up studies have found that individuals born preterm are more likely to have increased left ventricular mass, abnormal ventricular functions, systemic arterial stiffness, and higher mean blood pressure, which may predispose them to elevated risk of CVD later in life(17, 18). Accumulating evidence has also documented the association between preterm birth and subsequent risk of hypertension(19), although it is less certain whether it is confounded by SGA and/or maternal conditions(20). Moreover, conflicting results have been reported for associations between preterm birth and ischemic heart disease(21-24) and stroke(22, 23), possibly due to small numbers of events. Using nationwide population-based Swedish and Danish registers, we investigated the associations of gestational age and birth weight for gestational age with CVD risk in early adulthood in a bi-national cohort of about 3.5 million individuals. In addition to the population ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 analysis, we compared the risk between siblings to address the potential influence of familial (e.g., genetic and environmental) factors shared by siblings. METHODS Study design We conducted a population-based cohort study of liveborn singletons without malformations who were born in Sweden during 1973-1996 and in Denmark during 1978-1998, as recorded in the nationwide Swedish and Danish Medical Birth Registers (MBRs). The MBRs contain prospectively collected information from standardized antenatal, obstetric, and neonatal records and cover virtually all births in Sweden(25) and Denmark(26). All Swedish and Danish residents are assigned unique personal identification numbers (PINs) at birth or upon immigration(27), and are offered free tax-supported health care(27). Using the PINs, we linked individual information in the MBRs to the Patient-, Causes of Death-, and Migration Registers in Sweden and Denmark, respectively. Within the bi-national population-based cohort, we further performed sibling comparisons among cohort members with at least one full sibling in our database. We identified full siblings using the maternal PIN recorded in the MBRs and the paternal PIN obtained from the Swedish Multi-Generation Register (28) and the Danish Civil Registration System (29), which include information on first-degree relatives (i.e., parents, siblings, and children). It contains information on virtually all mothers and on 95% and 99% of fathers in Sweden and Denmark, respectively(28, 29). During the study period, we identified 2,420,647 liveborn singletons in Sweden and 1,243,198 in Denmark. We excluded births with no or erroneous information on sex (n=1,018), gestational ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 age (n=70,843), and birth weight (n=11,944). Individuals with congenital heart disease, non- specific malformations, or chromosomal abnormalities (n=38,157) were further excluded [International Classification of Diseases (ICD) codes are provided in Web Table 1]. We followed all individuals from 18 years until emigration, death, or December 31, 2014 in Sweden or December 31, 2016 in Denmark, whichever came first. Individuals who died (n=24,733), emigrated (n=100,282), or had a diagnosis of CVD (n=6,534) before 18 years were excluded. In total, 3,410,334 individuals were included in the population analysis. In sibling analyses, we included 2,371,230 individuals having at least one full sibling (70% of those included in population analyses). Inclusions/exclusions were summarized in Web Figure 1. This study was approved by the Regional Ethics Committee in Stockholm (No. 2016/288-31/1, 2020/01381) and the Danish Data Protection Agency (Record No. 2013-41-2569). Individual informed consent is not required for register-based studies in Sweden or Denmark. Exposures We obtained information on gestational age and birth weight from the MBRs. In the 1970s, gestational age was primarily estimated based on the last menstrual period in both countries. As the study period progressed, this approach was gradually replaced with ultrasound assessments of fetal size no later than early in the second trimester. It has been shown that gestational age estimates using both approaches do not differ significantly in register data(30). Gestational age was categorized into 22-36 weeks (preterm), 37-38 weeks (early term), 39-40 weeks (full term), and >41 weeks (late term to post-term). Gestational ages of 22-36 weeks were further categorized as 22-31 weeks (very preterm) and 32-36 weeks (moderately preterm), when ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 subgroup analyses were possible. There were too few events to study extremely preterm births (22-28 weeks). The percentile of birth weight for gestational age was calculated according to a reference curve for fetal growth based on ultrasound-estimated fetal weights in both Swedish and Danish samples(31). As described elsewhere(32-34), individuals were then grouped into <3rd percentile (severe SGA), 3rd to <10th percentile (moderately SGA), 10th to 90th percentile (appropriate for gestational age [AGA]), >90th to 97th percentile (moderately large for gestational age [LGA]), and >97th percentile (severe LGA) of birth weight for gestational age. Outcomes Our primary outcome was composite CVD, consisting of hypertensive disease, ischemic heart disease, and cerebrovascular disease. We identified inpatient/specialized outpatient diagnoses of CVD from the Patient Registers, using the specific ICD codes provided in Web Table 1. The Swedish Patient Register has collected inpatient discharge records since 1964 (nationwide since 1987) and records of hospital-based outpatient care since 2001(35). The Danish Patient Registry has maintained hospital discharge records since 1977 and outpatient clinic and emergency records since 1995(36). We identified deaths due to CVD from the nationwide Causes of Death Registers (37, 38). We used both primary and secondary diagnoses or causes of death to identify CVD. As secondary outcomes, we separately analysed three contributing CVD subtypes: hypertensive disease, ischemic heart disease, and cerebrovascular disease (including hemorrhagic stroke, ischemic stroke, and others). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 A range of CVD diagnoses/causes of death has been validated in the Swedish and Danish Patient Registers and Causes of Death Registers and the overall quality of these registers are considered high. For instance, in the Swedish Patient Register, the positive predictive value (PPV) is 98% for myocardial infarction(39) and 98.6% for stroke(35). In the Danish Patient Registry, the PPV is >90% for myocardial infarction(40). In the Causes of Death Registers, the PPV is more than 80% for ischemic heart disease and cerebrovascular disease in Sweden(41) and 97.2% for myocardial infarction in Denmark(42). Covariates We used the MBRs to obtain demographic information on cohort members, including sex and year of birth. We also extracted information on their parents, including maternal age, maternal country of birth, parity, maternal marital status, and maternal smoking in early pregnancy. Missingness in covariates was coded as “unknown”, given the relatively small missing rates. Using the MBRs, Patient Registers, and the Danish National Diabetes Register (available since 1995), we identified maternal complications during pregnancy, including maternal hypertensive disease (essential hypertension, gestational hypertension, preeclampsia, and eclampsia) and diabetes (pregestational and gestational diabetes). We also obtained information on maternal and paternal CVD history at the time of the individual’s birth from the Patient Registers. Relevant ICD codes are listed in Web Table 1. Statistical analysis ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 We first calculated incidence rates (IRs) of CVD by birth and parental characteristics. We also estimated age-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of CVD by contrasting these characteristics, using Cox regression with attained age as the underlying timescale. In the population analysis, we employed Cox regression to compute HRs and 95% CIs of CVD among severe or moderately SGA and LGA individuals compared with AGA individuals. We also estimated HRs of CVD among individuals born very preterm, moderately preterm, early term, and late to post-term compared to individuals born full term. Estimates were crude or adjusted for demographic characteristics, including attained age (as the underlying timescale), sex, country, and year of birth; factors associated with SGA or preterm birth, including parity, maternal age at birth, maternal country of birth, and maternal marital status; as well as predictors of CVD risk in offspring, i.e., maternal and paternal history of CVD. To illustrate the independent effect, we mutually adjusted for continuous gestational age and birth weight for gestational age in an additional model. The proportional hazards assumption was not violated according to Schoenfeld residual plots. To shed light on the impact of familial factors, we performed a sibling comparison using stratified Cox regression analysis allowing the baseline hazard to vary between families (i.e., stratifying by families). Briefly, this analysis contrasted the rates within each set of full siblings discordant on birth weight for gestational age or gestational age and CVD, although non- discordant siblings were also included in the analysis and contributed to the point estimates of covariates. This approach inherently controls for familial (e.g., genetic, lifestyle, and ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 socioeconomic) factors that siblings share (43). We adjusted for the aforementioned covariates except for country and maternal country of birth (no variation within siblings). We then estimated the HRs of CVD for each percentile of birth weight for gestational age and week of gestational age, where we applied restricted cubic splines and used the 50th percentile and 40 weeks as the reference for birth weight for gestational age and gestational age, respectively. To explore different effects on CVD subtypes, we separately examined the associations for hypertensive disease, ischemic heart disease, and cerebrovascular disease. We performed several additional analyses to test the robustness of our findings. Firstly, to illustrate the comparability between the entire cohort and the sibling cohort, we compared the baseline characteristics between two cohorts and conducted a population analysis restricted to individuals with at least one sibling. Secondly, to understand whether hypertensive disease dominated the observed associations, we repeated the primary analysis by limiting outcomes to CVD other than hypertensive disease. Thirdly, to address the concern that secondary diagnoses or causes of death had lower validity, we repeated the analyses only using the primary diagnosis or cause of death. Fourthly, to better control for confounding, we restricted analyses to those whose mothers had no record of hypertensive or diabetic disease or of smoking early in pregnancy; and to individuals born during 1992-1994 in Sweden for the adjustment of maternal body mass index (BMI). In addition, because of different rates of CVD in Sweden vs. Denmark, as well as the known sex disparity in CVD occurrence, we performed analyses stratified by country and sex. Finally, we assessed potential carryover effect in sibling analysis, i.e. if the exposure to SGA/preterm birth in the first sibling may influence the risk of being SGA/preterm ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 for the second sibling. To this regard, we performed analysis by separating sibling pairs with the first sibling exposed to SGA/preterm birth from those with the second sibling exposed. Data were processed using SAS 9.4 (SAS Institute) and analysed using STATA 14.2 (StataCorp). RESULTS During a median follow-up of 10 years (mean age at the end of follow-up was 29 years, range 18-41 years), 29,742 individuals developed incident CVD (IR 0.81 per 1,000 person-years). After controlling for attained age, individuals born in Denmark or those who were born in more recent years had a higher risk of CVD compared with other cohort members (Web Table 2). Slightly elevated CVD risk was observed among individuals whose mothers were young at childbirth (≤19 years), from the Nordic countries, unmarried, or smoked during pregnancy. Maternal pregestational diabetes, hypertensives disease before and during pregnancy, and maternal/paternal history of CVD were associated with an elevated risk of CVD in the offspring. Primary analysis In the primary population analysis, individuals born with severe SGA (<3rd percentile) were found to be at higher risk of CVD in early adulthood, compared to individuals born AGA (adjusted-HR 1.38, 95% CI 1.32-1.45; Table 1, Model 1). In the sibling comparison, this association was substantially attenuated (by 71%; to adjusted-HR 1.11, 95% CI 0.99-1.25). Similar associations were noted for moderately SGA (3rd to <10th percentile), although the estimates were lower. Compared to individuals born AGA, a lower risk of CVD was found for moderately but not severe LGA, in both the population and the sibling analyses. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Preterm birth (22-36 weeks) was associated with an elevated risk of CVD (Table 1, Model 1, adjusted-HR 1.31 (1.25-1.38)), compared to full-term birth (39-40 weeks). Estimates were robust, yet moderately attenuated (by 32%) in sibling analysis. Of note, the magnitude of associations gradually declined by increasing gestational age (from 22-31 weeks to >41 weeks). Mutual adjustments for birth weight for gestational age and gestational age yielded similar results (Table 1, adjusted-HRs in Model 2). Figure 1 further confirms the quasi-linear relationships of both birth weight for gestational age and gestational age with CVD risk. The attenuation of associations appeared greater for birth weight for gestational age than for gestational age. The estimates are presented in Web Table 3. CVD subtypes Severe SGA was associated with elevated risks of hypertensive disease, ischemic heart disease, and cerebrovascular disease in population analyses. However, these associations were attenuated in the sibling comparisons (Table 2). Of note, in sibling analyses, such attenuation was observed for ischemic stroke but not for hemorrhagic stroke. A similar pattern with lower estimates was found for moderately SGA. Preterm birth (22-36 weeks) was associated with elevated risks of hypertensive disease and ischemic stroke in both population and sibling analyses. Preterm birth was associated with elevated risks of ischemic heart disease and hemorrhagic stroke in the population analysis but not in the sibling analyses (Table 3). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Additional analyses Individuals with at least one sibling were highly comparable to the entire cohort (Web Table 4) and restricting to these individuals yielded very similar results in population comparisons for SGA and preterm birth (Web Table 5). Analyses of CVD risk after excluding hypertensive disease; after excluding CVD as secondary diagnoses or secondary causes of death; or after restricting the analyses to individuals of mothers without maternal hypertensive disease, diabetes, or smoking during pregnancy, yielded comparable results, with widely overlapping CIs (Web Tables 6-7). Adjustment for maternal BMI also did not change the results among individuals born during 1992-1994 in Sweden (Web Table 8). In addition, we observed similar associations in men and women, and in Danes and Swedes (Web Table 9). Finally, we observed similar results between sibling pairs with different exposure orders (Web Table 10). DISCUSSION In this bi-national cohort study of about 3.4 million individuals in Sweden and Denmark, we found that those born SGA or preterm were at elevated risk of CVD in early adulthood, compared with those born AGA or at full term, respectively. Importantly, when SGA individuals were compared with their AGA full siblings, the elevated risk of early-onset CVD was substantially reduced or even eliminated. In contrast, preterm birth was associated with a robust risk increase in the sibling analysis despite of a moderate attenuation of the point estimate. Similar risk patterns were observed for the linear relationship with CVD risk, and for most CVD subtypes. Birth weight for gestational age ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Most previous studies in this area have investigated the risk of CVD later in life in relation to birth weight or birth weight with adjustment for gestational age(7, 8). However, these approaches may not accurately classify infants not reaching their gestational growth potential. Moreover, adjustment for gestational age, a common practice in previous studies, may lead to collider bias(44), and cannot distinguish IUGR from constitutionally small fetuses who have reached their growth potential(33). Although a handful of studies have illustrated positive associations between SGA and risk factors or preclinical signs of CVD(45-47), we are aware of only two studies that defined SGA based on fetal growth curves and showed that individuals with birth weight for gestational age < 2 standard deviations below the mean were at increased risk of ischemic heart disease(21, 48). Our population analyses further showed consistent associations between SGA and risks of CVD overall, hypertensive disease, ischemic heart disease, and ischemic stroke in early adulthood. To the best of our knowledge, this is the first study to show that, when SGA individuals were compared with AGA siblings, these associations were attenuated towards the null, which indicates a substantial influence of familial (genetic and environmental) factors shared by siblings. Genetic factors influence both fetal growth and risk of CVD(49). The genetic predisposition for low birth weight has been associated with ischemic heart disease(50). Positive, although statistically non-significant, associations have been noted between genetic variants of low birth weight and risks of ischemic stroke(50) and hypertension(51). These findings are supported by our results in sibling comparisons, which showed attenuated associations between SGA and CVD and its subtypes (except for hemorrhagic stroke). ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 On the other hand, IUGR has been suggested to lead to functional alterations in the fetal development, including in the cardiovascular system (11, 52), which may predispose them to CVD in adulthood. It is also possible that IUGR results in a higher risk of renal disease(53) and subsequently increased CVD risk(54). Although the association between SGA and CVD risk was attenuated after controlling for familial factors, we also found a quasi-linear positive relationship with CVD risk across birth weight percentiles for gestational age, particularly in sibling comparisons. This relationship might be explained by the residual confounding in sibling comparison. It is also plausible that there could be a causal relation between IUGR and CVD development in adulthood. Previous studies often report a J- or U-shaped association between birth weight and CVD(7). However, we did not observe increased CVD risk among LGA individuals. This inconsistency could be explained by earlier studies failing to adequately adjust for maternal history of or propensity for cardiometabolic disease(7). Indeed, the linear trend was even more evident in sibling comparisons, which better control for the influence of familial factors, including genetic and lifestyle factors, and unmeasured maternal chronic diseases, on CVD risk in offspring. However, our analysis cannot distinguish whether the influence is from parental genetic makeup, familial environmental influence, and/or their interaction. Future research is needed to understand the complexity of contributors. It is also worth noting that our group has found that low birth weight was associated with increased risk of hemorrhagic stroke within twin pairs(15). In the present study, we also found consistent associations between severe SGA and hemorrhagic stroke in both population and sibling analyses, although statistical precision was limited for siblings. Taken together, our ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 findings suggest that IUGR may increase subsequent risk of hemorrhagic stroke independent of familial factors. Gestational age In line with previous investigations(19, 20), our data confirmed the association between preterm birth and risk of hypertensive disease in early adulthood. This association was fairly robust in analyses controlling for birth weight for gestational age and in sibling comparison, confirming a previously noted association in an underpowered study of Swedish siblings(19). With adjustment for parental history of CVD and maternal factors stable across pregnancies, our finding supports that preterm birth confers an elevated risk of hypertension independent of SGA and maternal chronic diseases that may lead to preterm delivery(20). Our finding that preterm birth was also associated with elevated risks of ischemic heart disease and ischemic stroke in population analyses is in agreement with some(24, 55, 56), but not all(21-23), previous studies. In line with a recent report on stroke using both population and sibling comparisons(56), the largely comparable estimates between both comparisons in our data suggest no substantial familial confounding, although statistical precision was hampered in sibling comparisons. We are not aware of any studies of preterm birth and ischemic heart disease using sibling comparisons. Furthermore, we found that preterm birth was associated with an increased risk of CVD overall in both population and sibling analyses, and the overall risk of CVD increased linearly with decreasing gestational age. Together, these findings indicate a causal relation between preterm birth and CVD development later in life, although a contribution of familial confounding to the association was also observed. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 They corroborate current knowledge about the subclinical structural and functional alterations in essential organs among individuals born preterm, increasing vulnerability to CVD in adulthood(17). However, alternative mechanisms, such as preterm birth-induced aberrant lipid levels or gut microbiota, may also contribute to the observed associations(57). Moreover, renal disease may mediate the observed association between preterm birth and CVD(54, 58). Furthermore, preterm birth is often a consequence of pregnancy complications, and the responsible pathology may itself contribute to later health problems in offspring(59-61). It is therefore plausible that more factors than just immaturity could explain our findings concerning the association between preterm birth and CVD risk. Strengths and limitations This large-scale bi-national cohort with long and virtually complete data capture up to 41 years of age allowed us to investigate cardiovascular outcomes in early adulthood. The nationwide, prospectively collected, and high-quality register data minimized common biases in observational studies (e.g., recall bias). The sibling comparison rigorously controlled for familial factors (e.g., genetics and early environment) shared between full siblings. Last, our findings are robust as similar associations were found in two independent countries/populations, although a higher absolute risk of CVD was observed in Denmark than in Sweden. This may be due to differences in registration(35, 36) and lifestyle factors(62). Our study has several limitations. Firstly, to better capture CVD cases, we also used information from secondary diagnoses or causes of death, which may have lower validity and represent other underlying diseases leading to the healthcare visit or death (e.g., hospitalized due to renal disease ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 but comorbid with hypertension(54)). Reassuringly, we observed comparable associations when limiting outcomes to primary diagnoses or causes of death. Secondly, we missed CVD cases (e.g., hypertensive disease) treated only in the general practice setting. However, such misclassification is likely to be non-differential with respect to the exposure and would have attenuated the associations. Most individuals with ischemic heart disease or cerebrovascular disease are treated in specialist hospital clinics or emergency departments, which are well covered by national registers. When we restricted the analysis to these two diseases and obtained similar results. Thirdly, we cannot rule out the influence of residual confounding. For instance, information on maternal gestational diabetes is available only from 1987 in Sweden. However, about 30-84% of women with gestational diabetes have a recurrent gestational diabetes in their next pregnancy(63). This should have been partly controlled for among siblings who shared the exposure to maternal gestational diabetes. Information on maternal BMI is available only for births from 1992 onward in Sweden and from 2004 in Denmark. However, we performed population analyses by restricting to individuals born during 1992-1996 in Sweden for additional adjustment for maternal BMI, which yielded materially unchanged results. Fourthly, sibling comparison cannot address unmeasured confounding from factors that vary between pregnancies(64) and may be subject to carryover effects(65). The latter may occur if the exposure to SGA/preterm birth in the first sibling influences the risk of being SGA/preterm for the second sibling. However, we have performed analysis by separating sibling pairs with different exposure orders, which yielded comparable results. Moreover, not all individuals had a sibling and individuals included in the sibling analysis (70%) may be a selected group. Reassuringly, the birth and parental characteristics in the sibling analysis were highly comparable to those included in the population analysis, although it is not considered definitive ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 evidence on generalizability(66). Lastly, our study examined the CVD risk during age 18-41 years with a median follow-up of 10 years. Future studies with longer follow-up are needed to understand the SGA- or preterm birth-associated CVD risk in middle and late adulthood when most CVD diagnoses emerge. However, until such large-scale prospective data are available, our findings may provide new insights into the shared familial influences linking IUGR to CVD with onset in early adulthood. Conclusions Our findings suggest that SGA and preterm birth are associated with an elevated risk of CVD in early adulthood. Familial confounding might play a greater role on the association between SGA and CVD risk. Although familial factors would also contribute to the association between preterm birth and CVD, the robust association in sibling comparison supports the hypothesis of a causal relationship. References 1. Roth GA, Mensah GA, Johnson CO, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol 2020;76(25):2982-3021. 2. Mensah GA, Wei GS, Sorlie PD, et al. Decline in Cardiovascular Mortality: Possible Causes and Implications. Circ Res 2017;120(2):366-80. 3. Gooding HC, Gidding SS, Moran AE, et al. Challenges and Opportunities for the Prevention and Treatment of Cardiovascular Disease Among Young Adults: Report From a National Heart, Lung, and Blood Institute Working Group. J Am Heart Assoc 2020;9(19):e016115. 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ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 1. Associations of birth weight for gestational age and gestational age with risk of cardiovascular disease: a bi-national cohort study in Denmark and Sweden, 1973-2016. Population Analysis Sibling Analysis a b a b Crude model Model 1 Model 2 No. Crude model Model 1 Model 2 No. of No. No. of Exposures of Individu of Individu 95% 95% 95% 95% 95% 95% HR HR HR CVD HR HR HR als CVD CI CI CI als CI CI CI Birth weight for gestational age, percentiles 1.38, 1.32, 1.30, 0.95, 0.99, 0.99, <3rd 125,306 1,865 1.44 1.38 1.36 1,710 850 1.07 1.11 1.12 1.51 1.45 1.43 1.21 1.25 1.26 3rd to 1.20, 1.18, 1.19, 0.96, 0.99, 1.00, 281,657 3,424 1.25 1.22 1.23 3,558 1,692 1.05 1.07 1.08 9th 1.29 1.27 1.27 1.14 1.17 1.18 10th to 2,690,9 22,36 Refere Refere Refere Refere Refere 1.00 1.00 1.00 9,074 3,452 1.00 1.00 1.00 90th 23 0 nt nt nt nt nt 91th to 0.84, 0.83, 0.82, 0.76, 0.74, 0.73, 222,985 1,444 0.88 0.88 0.87 2,458 792 0.85 0.82 0.81 97th 0.93 0.93 0.91 0.94 0.92 0.91 0.93, 0.92, 0.89, 0.83, 0.80, 0.78, >97th 89,463 649 1.00 1.00 0.97 1,002 339 0.98 0.95 0.93 1.09 1.08 1.04 1.16 1.12 1.10 Gestational age, weeks 1.24, 1.25, 1.23, 1.08, 1.07, 1.08, 22-36 152,339 1,634 1.30 1.31 1.29 1,742 786 1.22 1.21 1.22 1.37 1.38 1.36 1.38 1.37 1.38 1.34, 1.30, 1.23, 1.03, 1.01, 0.99, 22-31 14,747 167 1.56 1.51 1.43 176 85 1.47 1.44 1.41 1.82 1.76 1.67 2.09 2.05 2.00 1.21, 1.23, 1.21, 1.06, 1.05, 1.06, 32-36 137,592 1,467 1.28 1.29 1.28 1,633 731 1.20 1.19 1.21 1.35 1.37 1.35 1.36 1.35 1.37 1.07, 1.10, 1.11, 0.96, 0.95, 0.97, 37-38 533,517 4,655 1.10 1.14 1.15 5,702 2,210 1.03 1.02 1.04 1.14 1.18 1.19 1.11 1.09 1.12 1,777,9 15,15 Refere Refere Refere Refere Refere Refere 39-40 1.00 1.00 1.00 12,806 4,952 1.00 1.00 1.00 41 4 nt nt nt nt nt nt 0.91, 0.95, 0.93, 0.93, 0.94, 0.91, >41 946,537 8,299 0.94 0.97 0.95 8,142 3,431 0.98 1.00 0.97 0.96 1.00 0.98 1.04 1.06 1.02 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of cardiovascular disease. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth, and were additionally stratified by sibling sets. In both population and sibling analyses, HRs were mutually adjusted for gestational age or birth weight for gestational age in addition to Model 1. Only sets of siblings that were discordant on exposures and CVD were presented, which explains the numbers among individuals with gestational age 22-36 weeks are not the sum of numbers from those with 22-31 and 32-36 weeks. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 2. Associations of birth weight for gestational age with risk of cardiovascular disease subtypes: a bi-national cohort study in Denmark and Sweden, 1973-2016 Outcome and Population Analysis Sibling Analysis Percentile of No. of No. of No. of No. of a a a a Birth Weight for HR 95% CI HR 95% CI b b Individuals CVD Individuals CVD Gestational Age Hypertensive disease <3rd 125,306 1,225 1.42 1.34, 1.51 1,131 570 1.15 0.99, 1.33 3rd to 9th 281,657 2,290 1.27 1.22, 1.33 2,330 1,136 1.11 1.00, 1.24 10th to 90th 2,690,923 14,387 1.00 Referent 5,958 2,229 1.00 Referent 91th to 97th 222,985 885 0.84 0.79, 0.90 1,600 495 0.78 0.68, 0.89 >97th 89,463 417 1.00 0.91, 1.11 659 218 0.91 0.73, 1.12 Ischemic heart disease <3rd 125,306 292 1.50 1.33, 1.70 274 133 1.03 0.75, 1.41 3rd to 9th 281,657 459 1.17 1.06, 1.29 482 218 0.90 0.71, 1.13 10th to 90th 2,690,923 2,903 1.00 Referent 1,156 454 1.00 Referent 91th to 97th 222,985 190 0.90 0.78, 1.05 271 85 0.69 0.50, 0.96 >97th 89,463 75 0.90 0.72, 1.13 123 33 0.64 0.36, 1.12 Cerebrovascular disease <3rd 125,306 462 1.30 1.18, 1.43 417 204 1.11 0.87, 1.40 3rd to 9th 281,657 843 1.14 1.06, 1.22 937 411 0.99 0.85, 1.17 10th to 90th 2,690,923 6,002 1.00 Referent 2,435 902 1.00 Referent 91th to 97th 222,985 429 0.95 0.87, 1.05 681 234 0.98 0.80, 1.19 >97th 89,463 181 1.02 0.88, 1.18 264 94 1.16 0.85, 1.57 Hemorrhagic stroke <3rd 125,306 179 1.32 1.14, 1.54 164 84 1.33 0.91, 1.93 3rd to 9th 281,657 342 1.20 1.07, 1.34 371 167 1.08 0.84, 1.39 10th to 90th 2,690,923 2,351 1.00 Referent 981 365 1.00 Referent 91th to 97th 222,985 174 0.97 0.83, 1.14 281 97 0.89 0.66, 1.21 >97th 89,463 67 0.94 0.74, 1.20 100 31 0.92 0.56, 1.51 Ischemic stroke <3rd 125,306 145 1.30 1.09, 1.54 140 66 1.10 0.71, 1.70 3rd to 9th 281,657 254 1.10 0.96, 1.25 278 117 0.80 0.58, 1.11 10th to 90th 2,690,923 1,853 1.00 Referent 707 261 1.00 Referent 91th to 97th 222,985 147 1.08 0.91, 1.28 204 79 1.49 1.03, 2.17 >97th 89,463 56 1.04 0.80, 1.36 78 25 1.05 0.56, 1.94 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth and were additionally stratified by sibling sets. Only sets of siblings that were discordant on exposures and CVD were presented. In the subgroup analysis, we presented results of two major types of cerebrovascular disease; diseases other than hemorrhagic or ischemic stroke were not present. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Table 3. Associations of gestational age with risk of cardiovascular disease subtypes: a bi- national cohort study in Denmark and Sweden, 1973-2016 Population Analysis Sibling Analysis Outcome and No. of No. of No. of No. of a a a a Gestational Age HR 95% CI HR 95% CI b b Individuals CVD Individuals CVD Hypertensive disease 22-36 152,339 1,083 1.34 1.26, 1.43 1,144 525 1.24 1.07, 1.45 37-38 533,517 3,078 1.16 1.11, 1.21 3,731 1,441 1.05 0.96, 1.14 39-40 1,777,941 9,699 1.00 Referent 8,344 3,219 1.00 Referent >41 946,537 5,344 0.95 0.92, 0.99 5,318 2,234 0.96 0.89, 1.03 Ischemic heart disease 22-36 152,339 223 1.37 1.20, 1.58 195 91 1.11 0.75, 1.63 37-38 533,517 565 1.12 1.02, 1.23 697 254 0.86 0.70, 1.06 39-40 1,777,941 2,048 1.00 Referent 1,603 630 1.00 Referent >41 946,537 1,083 1.02 0.95, 1.10 1,000 411 0.91 0.77, 1.08 Cerebrovascular disease 22-36 152,339 421 1.28 1.16, 1.41 494 212 1.24 0.99, 1.55 37-38 533,517 1,194 1.10 1.03, 1.17 1,509 587 1.06 0.93, 1.21 39-40 1,777,941 4,051 1.00 Referent 3,445 1,282 1.00 Referent >41 946,537 2,251 1.01 0.96, 1.07 2,239 932 1.11 1.00, 1.24 Hemorrhagic stroke 22-36 152,339 157 1.18 1.00, 1.39 189 81 1.07 0.76, 1.52 37-38 533,517 467 1.07 0.96, 1.19 598 225 1.01 0.82, 1.25 39-40 1,777,941 1,592 1.00 Referent 1,353 507 1.00 Referent >41 946,537 897 1.03 0.95, 1.12 865 372 1.12 0.94, 1.33 Ischemic stroke 22-36 152,339 133 1.29 1.08, 1.55 138 67 1.70 1.11, 2.62 37-38 533,517 376 1.11 0.99, 1.25 424 182 1.31 1.01, 1.70 39-40 1,777,941 1,255 1.00 Referent 1,042 383 1.00 Referent >41 946,537 691 0.98 0.89, 1.07 744 284 0.99 0.81, 1.21 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; No., number In the population analysis, HRs were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates except for country and maternal country of birth, and were additionally stratified by sibling sets. Only sets of siblings that were discordant on exposures and CVD were presented. In the subgroup analysis, we presented results of two major types of cerebrovascular disease; diseases other than hemorrhagic or ischemic stroke were not present. ORIGINAL UNEDITED MANUSCRIPT Downloaded from https://academic.oup.com/aje/advance-article/doi/10.1093/aje/kwac223/6969414 by DeepDyve user on 10 January 2023 Figure legends Figure 1. Hazard ratios (HRs) of cardiovascular disease (CVD) in individuals across birth weight for gestational age and gestational age: a bi-national cohort study in Denmark and Sweden, 1973-2016 A) Population analysis and B) sibling analysis of CVD in relation to birth weight for gestational age. C) Population analysis and D) sibling analysis of CVD in relation to gestational age. Birth weight percentile for gestational age and gestational age were splined using restricted cubic spline with 4 knots, and the 50th percentile or week 40 was used as the reference. In the population analysis, the estimates were adjusted for attained age, offspring sex, country of birth, year of birth, parity, maternal age at birth, maternal country of birth, maternal marital status, and maternal and paternal history of CVD. In the sibling analysis, HRs were adjusted for the above covariates, except for country and maternal country of birth, and were additionally stratified by sibling sets. Black line indicates HR and grey area denotes 95% confidence interval. Dash line indicates null association (HR=1.0). ORIGINAL UNEDITED MANUSCRIPT

Journal

American Journal of EpidemiologyOxford University Press

Published: Jan 4, 2023

Keywords: cardiovascular disease; cohort studies; fetal growth retardation; preterm birth; siblings

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