Risk factors for the development of cardiovascular diseases among 5-year-old low birth weight children

Risk factors for the development of cardiovascular diseases among 5-year-old low birth weight children | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk factors for the development of cardiovascular diseases among 5-year-old low birth weight children Patrik Konopásek, Aneta Kodytková, Peter Korček, Monika Pecková, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4164128/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2026 Read the published version in Bratislava Medical Journal → Version 1 posted You are reading this latest preprint version Abstract Background Low birth weight (LBW) is associated with cardiovascular diseases (CVD); however, the roles of specific clinical and biochemical attributes remain unknown. Methods In this two-center study, we investigated risk factors (RFs) for the development of CVD among 5-year-old LBW children. The assessed RFs were low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride (TG) levels; urine protein/creatinine ratio (PCR); masked hypertension (HT); and non-dipping blood pressure (BP). Results A total of 110 children participated in this study (eight with a BW < 2500g, 58 with a BW < 1500g, and 44 with a BW < 1000g) and all six factors were successfully collected in 51 of the children. Over half (58.8%) of the children had at least one RF. Masked HT, elevated LDL, TG, PCR, decreased HDL and the presence of non-dipping BP were found in 13.2%, 16.7%, 13.6%, 17.8%, 8.2%, and 37.7% of participants, respectively. Increased growth velocity (GV) was associated with decreased HDL (OR 1.36, P = 0.045) and lower risk of non-dipping BP (OR 0.83, P = 0.0384). Small for gestational age (SGA) status (OR 3.59, P = 0.0323), maternal anemia (OR 6.41, P = 0.0356), and greater gestational age (GA) (OR 2.43 per 1 week of age, P = 0.0004) were associated with proteinuria, while male sex was a protective factor (OR 0.16, P = 0.0203). Conclusion There was a high prevalence of CVD RFs in 5-year-old LBW children. SGA status at birth, maternal anemia, female sex, and higher GA were associated with proteinuria. The role of GV in the etiopathogenesis of CVD remains controversial. Prematurity Low birth weight Cardiovascular disease Risk factors Hypertension Figures Figure 1 Introduction Cardiovascular diseases (CVD) are the principal cause of mortality worldwide. The risk factors (RF) for CVD such as hypertension (HT), hyperlipidemia, and diabetes mellitus (DM) lead to the formation of atherosclerosis with subsequent episodes of myocardial infarction, cardiac arrhythmias, and stroke. A healthy lifestyle and specific treatments targeting RFs reduce the risk of CVD and improves public health [ 1 ]. In the early nineties, Brenner et al. [ 2 , 3 ] postulated that a decreased number of nephrons is associated with the development of HT. They explained their hypothesis by the decreased filtration surface area, which leads to sodium retention and development of systemic HT. Subsequently, glomerular capillary HT causes glomerulosclerosis and a further reduction in the filtration surface area, creating a vicious cycle. They supported their hypothesis with the previous knowledge of increased risk of HT in individuals with a naturally reduced number of nephrons, such as those with unilateral renal agenesis [ 2 , 3 ]. Normally, 60% of all nephrons develop in the third trimester. In preterm children, nephrogenesis may continue after birth but appears to be abnormal due to the formation of defective glomeruli. Such glomeruli may be more susceptible to subsequent damage from events such as acute kidney injury (AKI) [ 4 , 5 , 6 ]. A positive correlation was found between birth weight (BW) and total number of nephrons [ 7 , 8 ]. Therefore, based on Brenner's theory, individuals born with a low birth weight (LBW) should have a higher risk of HT than those born with a normal birth weight (NBW). This has been demonstrated by many studies [ 4 ]. Chronic kidney disease (CKD) is a significant RF for HT and CVD, and has also been found to be associated with a LBW [ 4 ]. These characteristics predispose a large proportion of the global population to HT, CKD, and subsequently CVD. Based on the United Nations International Children's Emergency Fund data, around 15–20% of people are born LBW around the world [ 9 ]. Besides HT and CKD, other CVD RFs such as hyperlipidemia and DM have also been found to be associated with LBW and prematurity [ 10 , 11 ]. The purpose of this paper was to evaluate CVD RFs in a cohort of 5-year-old LBW children. Patients and methods This was a two-center, cross-sectional, observational and prospective study conducted in Prague, Czech Republic ( Institute for the Care of Mother and Motol University Hospital ) between 2021 and 2023. The goal was to evaluate CVD RFs at 5 years of age in children born with a very low birth weight (VLBW). Caregivers of all VLBW children aged 5 years born between 01.01.2016 and 31.09.2017 in one of the centers, without any known pathogenic variants and living within a 1 hour travel radius of Prague, were contacted and offered participation in the study. In the case of twins, both were automatically offered to be involved in the study even if the BW for one of them was ≥ 1500g. LBW was defined as BW < 2500g, VLBW as BW < 1500g, extremely low birth weight (ELBW) as BW < 1000g, and small for gestational age (SGA) as BW < 2 standard deviations (SDs) below the mean. Six RFs (four measured by laboratory tests) were examined: serum low-density lipoprotein (LDL); serum high-density lipoprotein (HDL); serum triglycerides (TG); urine protein/creatinine ratio (PCR); masked HT; and non-dipping blood pressure (BP) diagnosed by ambulatory blood pressure monitoring (ABPM). The blood samples were obtained after 12 hours of fasting and urine samples were collected from a first morning urine collection. Samples were analyzed immediately after being transported to the laboratory. Photometric analyses of LDL, HDL, and TG in the serum and total protein and creatinine in the urine were performed using the Atellica Solutions CH 930 analyzer (Siemens, USA). Cut-off values for elevated blood lipid levels were used from the National Cholesterol Education Program Expert Panel on Blood Cholesterol Levels in Children [ 12 ]. A PCR > 20 mg/mmol was considered to be pathologic proteinuria. BP values measured during periodic pediatric follow-ups were evaluated for office HT, and prenatal and perinatal data were obtained from the medical record. ABPM was performed according to the American Heart Association statement on ABPM, with daytime and nighttime measurements every 20 minutes and 30 minutes, respectively [ 13 ]. The OnTrak ABPM machine (from Spacelabs healthcare, Snoqualmie, United states of America) was used for ABPM and the data were evaluated on the ABPM Report Management System version 3.1.0 (from Spacelabs healthcare, Snoqualmie, United states of America). Results with fewer than 40 successful measurements were considered invalid. Non-dipping BP was defined as a BP reduction of less than 10% during the night. Masked HT was defined as ambulatory HT and a normal office BP. The office HT was defined as a BP ≥ 95th percentile for age, sex, and height based on general pediatrician (GP) follow-up. Growth and weight parameters measured by GPs during periodic follow-up were collected, as well as prenatal and perinatal data from the obstetrics records. The anthropometry was performed by a single experienced anthropologist. The height was obtained using a wall-mounted Seca stadiometer (A-226 manufactured by Trystom in Olomouc, Czech Republic) with an accuracy of 1 mm. Body mass index (BMI) was based on values measured on the calibrated weighing electronic scale with an accuracy of 0.1 kg (TH200, manufactured by Tonava in Upice, Czech Republic). Arm, abdomen, and calf circumferences were measured with a tape measure with an accuracy of 1 mm. The BMI was calculated using the standard formula as weight (in kg) divided by height (in meters) squared. Height, BMI, and arm, abdomen and calf circumference SDs were generated from the RustCZ software using the learning management system (LMS) method based on the 6th Czech National-wide Anthropological Survey of Children and Adolescents [ 14 , 15 ]. GF was defined as height < − 2 SDs and growth below the midparental height range and/or lag-down growth by more than 2 percentile zones after the 2nd year of age. Malnutrition was defined as BMI < − 2 SDs and/or arm circumference < − 2 SDs and/or calf circumference < − 2 SDs. Growth velocity (GV) in the first year of life was calculated from the first measured body length and the body length measured at the time of the first birthday. The evaluated period did not exceed 12 months. In total, of the 233 children with VLBW were eligible for the study, 110 were enrolled (with the inclusion of eight LBW twin siblings with BW ≥ 1500g). Fifty-six were twins and 54 were singletons. In 51 children, all six factors were successfully collected and in 105, only the four laboratory RF were collected (Fig. 1 ). Statistical analysis was performed in the statistical package R. A P-value ≤ 0.05 was considered to be statistically significant. Analyses of the associations were performed separately in twins and singletons because the twins consisted of dependent data and they had different distributions of investigated parameters in our cohort (Table 1 ). Associations of risk factors with CVD RFs were tested for. These risk factors were BW, GA, body-mass index (BMI), GV, SGA, sex, BW < 1000g, family history of HT, type of birth, antenatal corticosteroids use, coffee drinking during pregnancy, hypertensive disorders of pregnancy (HDP), maternal anemia, bronchopulmonary dysplasia (BPD), neonatal sepsis, use of furosemide, aminoglycosides, and patent ductus arteriosus (PDA). Gestational diabetes, smoking, alcohol use during pregnancy, use of nonsteroidal analgesics (NSAID), neonatal AKI, and necrotizing enterocolitis were excluded because of the insignificant numbers of pregnancies with these factors. Table 1 Distributions of some of the investigated parameters in the twins and singletons groups. Risk factor Singletons group (mean) Twins group (mean) Birth weight (g) 1003.5 1212.0 Gestational age (weeks) 28.0 29.9 Singletons group (%) Twins group (%) Males 57.4 39.3 Birth weight < 1000g 53.7 26.8 Gestational age < 29 weeks 61.1 17.9 Coffee drinking during pregnancy 42.6 21.4 Maternal anemia 14.9 21.4 Bronchopulmonary dysplasia 40.7 23.2 Hypertensive disorder of pregnancy 37.0 21.4 Absolute numbers with percentage and mean values with SDS were used for descriptive statistics. In the twins group, the logistic models with generalized estimating equations to correct for the dependencies between the twins were used. Logistic models were also used in the singletons group. In case of categorical variables being present only in one compared group in the singleton group, P-values were analyzed using Fisher tests. Results Complete cohort In our cohort, 8 (7.3%) children were born with LBW, 58 (52.7%) with VLBW and 44 (40%) with ELBW. Fifty-seven (51.8%) were girls and 53 (48.2%) were boys, mean BW was 1109.7 g ± 315.4 (370–1890) g and mean GA was 29.0 ± 2.8 (23–34) weeks. All children were of Caucasian ethnicity. All children were normotensive during regular pediatric check-up. Mean BW in the excluded group was 1105.1 ± 260 g, GA 29.2 ± 2.7 weeks, and 39.7% had ELBW. Differences of BW and GA between both groups were not significant ( P = 0.9397 and P = 0.4864, respectively). Table 2 presents the prevalence of each RF, Table 3 presents the number of children with 0–4 RF separately for all measured RF with and without ABPM results. In patients where all six RF were obtained, 58.8% had at least 1 of the CVD RF presented. In the group without ABPM results, 40.1% had at least 1 of the CVD RF. Table 2 The number of children with each risk factor for cardiovascular disease. Risk factor (missing values) All patients (110) n (%) Singletons (54) n (%) Twins (56) n (%) LDL ≥ 3.4 (2) 18 (16.7) 5 (9.6) 13 (23.2) TG ≥ 1.1 (0) 15 (13.6) 6 (11.1) 9 (16.1) HLD 20 (3) 19 (17.8) 9 (17.6) 10 (17.9) Masked HT (57) 7 (13.2) 4 (16.7) 3 (10.4) Non-dipping (57) 20 (37.7) 6 (25.0) 14 (48.3) *HLD – High density lipoprotein, HT – Hypertension, LDL – Low density lipoprotein, PCR – Protein/creatinine ratio (in mg/mmol), TG – Triglycerides. Table 3 Number of children with 0 to 4 risk factors. All risk factors measured (n = 51) All risk factors measured but ABPM (n = 105) Risk factors (n) n (singletons/twins) % (singletons/twins) n (singletons/twins) % (singletons/twins) 0 21 (10/11) 41.2 (45.5/37.9) 63 (30/33) 60.0 (61.2/58.9) 1 12 (6/6) 23.5 (27.3/20.7) 30 (16/14) 28.6 (32.6/25.0) 2 10 (4/6) 19.6 (18.2/20.7) 9 (3/6) 8.6 (6.1/10.7) 3 7 (2/5) 13.7 (9.1/17.2) 3 (0/3) 2.9 (0.0/5.4) 4 1 (0/1) 2.0 (0/3.4) 0 (0/0) 0.0 (0.0/0.0) *ABPM – Ambulatory blood pressure monitoring. In the singletons’ group, there was a higher prevalence of masked HT and decreased HDL than in the twins’ group (Table 2 ). An increased GV was associated with decreased HDL (OR 1.36, 95% CI 1.03–1.92, P = 0.045). No other associations were found in the singletons’ group (Table 4 ). Table 4 Associations with cardiovascular disease risk factors. Risk factor Associations (singletons) Associations (twins) Masked hypertension x x Non-dipping blood pressure x Decreased GV Decreased HDL Increased GV x Proteinuria x SGA, maternal anemia, female, higher gestational age Elevated LDL x x Elevated TG x x *HDL – High density lipoprotein, LDL – Low density lipoprotein, TG – Triglycerides. In the twins’ group, there was a higher prevalence of LDL hypercholesterolemia and non-dipping compared to singletons (Table 2 ). Three children had masked HT, each from a different twin couple. Elevated LDL was found in 6 twin couples and in 1 twin with a sibling with normal LDL value. Increased GV was a protective factor for non-dipping BP (OR 0.83, 95% CI 0.70–0.99, P = 0.0384). SGA (OR 3.59, 95% CI 1.11–11.59, P = 0.0323), maternal anemia (OR 6.41, 95% CI 1.13–36.23, P = 0.0356) and higher GA (OR 2.43 for 1 week of age, 95% CI 1.49–3.98, P = 0.0004) were associated with pathologic proteinuria, male sex was protective factor (OR 0.16, 95% CI 0.03–0.75, P = 0.0203). No other associations were found in the twins’ group (Table 4 ). Discussion In our study, we found a high prevalence of risk factors for the development of CVD in 5-year-old LBW children: 58.8% had at least one RF. The association between LBW and CVD has already been described by Barker et al. [ 16 ]. This concept of an early origin of noncommunicable diseases, known as developmental origins of health and disease (DOHAD), has been studied during the last decades and continues to be a hot topic because early detection of RFs and implementation of preventive measures may have a huge impact on public health [ 17 ]. HT is one of the most studied RFs for CVD associated with LBW. Many studies have found an association between prematurity, LBW, SGA, and increased growth velocity (GV) and higher BP [ 18 – 24 ]. Adults born with a VLBW were found to have a higher BP, with female sex and maternal preeclampsia being additional RFs [ 18 ]. In a longitudinal study by Jounala et al. [ 19 ], adults born preterm and SGA had a higher BP than those born preterm and appropriate for gestational age. Interestingly, GV, in contrast to BW, was found to be better associated with increased BP [ 20 ]. Based on the recent metanalysis, LBW was associated with CVD, HT, and DM [ 21 ]. In a study of children younger than 5 years, those born preterm had a higher BP than term-born control [ 22 ]. A study of Vohr et al. [ 23 ] reported a high prevalence of HT and high BP in extremely preterm infants at age 6 to 7 years, with GV and maternal DM being RFs. In a prospective study by Lurbe et al. [ 24 ], BW was a positive determinant of BP in newborns born at term; later, current weight was the strongest determinant for BP. In our study, there was a high prevalence of masked HT (13.7%) and non-dipping BP (37.7%). In the twins groups, all of the individuals with HT were from different twins’ couples, which shows that genetic predisposition and environment had little impact on the development of HT. We did not find any association with HT, likely due to the low total number of patients in each group; on the other hand, increased GV was associated with a decreased risk of non-dipping BP in the twins group. Non-dipping BP was found to be associated with CVD [ 25 ]. This protective effect of GV on night dipping found in twins group may imply that the possible effect of GV on BP and other CVD RFs is more complex and some subgroups of patients may even benefit from that. Many studies have reported an association between abnormal lipid metabolism and LBW. LBW/premature individuals may have different adiposity, with intra-abdominal and intrahepatocellular fat which could be explained by different growth patterns in these children [ 26 , 27 ]. Rapid gain in weight for length in the first 3 months after term age was found to be positively associated with total cholesterol and LDL in early adulthood [ 28 ]. A study by Pehkonem et al. [ 29 ] reported that both GV and LBW were associated with TG level, but not with LDL. A metanalysis in 2017 reported that LBW is associated with total cholesterol in adult women younger than 50 years and in adult men [ 30 ]. In our study, there was a high prevalence of serum lipid pathologies, especially of elevated LDL values (Table 2 ). Despite the emerging result, the LDL values must be taken with caution, because in the twins group the elevation was present in almost all cases in twin couples, which suggests a possible genetic predisposition, although no parents reported dyslipidemia in the family. The only association found in our study was between an increased GV and decreased HDL, which supports previous results of an association between GV and lipid metabolism abnormalities. Few studies examined the association between LBW and proteinuria. In a study by Shinzava et al. [ 31 ], LBW was associated with proteinuria and the odds were higher in VLBW individuals than in their LBW counterparts [ 31 ]. Ramirez et al. [ 32 ] did not find any significant association between lower BW and proteinuria, which was only associated with the current body weight. In our study, almost 18% of children were found to have pathologic proteinuria (defined as PCR > 20 mg/mmol), which is higher than the prevalence reported in the general population in children and similar to the previous studies on LBW [ 33 , 34 ]. Pathologic proteinuria is a sign of CKD, which is a known RF for CVD and was found to be associated with LBW [ 35 ]. The proteinuria in our LBW cohort was associated with SGA, maternal anemia, and female sex in the twins group. The association between SGA, LBW, prematurity, and CKD was found in many studies [ 4 ]. We found no study reporting an association between maternal anemia and subsequent proteinuria in the offspring, but iron deficiency and poor nutritional status during pregnancy are known RFs for LBW [ 4 ]. Sex-specific differences in kidney diseases are well known: the higher prevalence of proteinuria in females in our study is therefore not surprising [ 36 ]. Interestingly, a higher GA was also associated with proteinuria in the twins group. We believe that this result is only the projection of the high proportion of SGA in the twins with proteinuria, rather than a real association between higher GA and proteinuria (prevalence of 12.8% SGA in twins without proteinuria and 44.4% in twins with proteinuria). Our study has several limitations. We present only a prevalence of RFs in the studied group without a control group; on the other hand, the prevalence is much higher than expected and still gives us valuable information about RFs for CVD in LBW children. Another factor was the presence of twins, which required separation of the patients into two groups. Because of this, some associations may have been missed due to the reduced number of patients in each group. On the other hand, twins allowed us to study associations in a very specific population with similar genetic and environmental backgrounds. Many ABPM recordings were invalid due to an insufficient number of successful measurements, which allowed us to study the prevalence of all RFs in only about a half of the examined children. Due to the character of the study, there may be selection bias, but the birth parameters of the children in our cohort had a very similar distribution to those who were excluded. We therefore believe that our group of patients represents the standard distribution in population. In conclusion, 5-year-old children born with a LBW have a high prevalence of CVD RFs. Early intervention with closer follow-up is required even in early childhood in individuals born with LBW. The association between CVD RFs and GV appears to be both negative and protective in different populations and needs to be studied more thoroughly. SGA status at birth, female sex, and maternal anemia are associated with proteinuria in LBW twins. Declarations Acknowledgements No acknowledgements. Funding This work was supported by Charles University Research Project Cooperation (Maternal and Childhood care section). Conflicts of interest The authors declare no conflict of interest. Ethics approval The study was approved by the Ethics Committee for Multi-Centric Clinical Trials of the University Hospital Motol and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Authors' contributions The study design and research ideas were created by Patrik Konopásek. Data acquisition from the perinatal period was performed by Martina Frantová and Peter Korček. The tables and figures were created by Patrik Konopásek and Monika Pecková. Statistical analysis was performed by Monika Pecková. Karel Kotaška provided laboratory investigation management and text revision. The first draft was written by Patrik Konopásek. Monika Pecková, Aneta Kodytková, Peter Korček, Karel Kotaška, and Zbyněk Straňák critically reviewed the article, and Jakub Zieg critically reviewed the article and supervised the study. 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Eur J Endocrinol 25(5):511–521. https://doi.org/10.1530/EJE-21-1221 Stansfield BK, Fain ME, Bhatia J, Gutin B, Nguyen JT, Pollock NK (2016) Nonlinear Relationship between birth weight and visceral fat in adolescents. J Pediatr 174:185–192. https://doi.org/10.1016/j.jpeds.2016.04.012 Kerkhof GF, Willemsen RH, Leunissen RW, Breukhoven PE, Hokken-Koelega AC (2012) Health profile of young adults born preterm: Negative effects of rapid weight gain in early life. J Clin Endocrinol Metab 97(12):4498–4506. https://doi.org/10.1210/jc.2012-1716 Pehkonen J, Viinikainen J, Kari JT, Böckerman P, Lehtimäki T, Viikari J, Raitakari O (2022) Birth weight, adult weight, and cardiovascular biomarkers: Evidence from the Cardiovascular Young Finns Study. Prev Med 154:106894. https://doi.org/10.1016/j.ypmed.2021.106894 Chen LH, Chen SS, Liang L, Wang CL, Fall C, Osmond C, Veena SR, Bretani A (2017) Relationship between birth weight and total cholesterol concentration in adulthood: A meta-analysis. J Chin Med Assoc 80(1):44–49. https://doi.org/10.1016/j.jcma.2016.08.001 Shinzawa M, Tanaka S, Tokumasu H, Takada D, Tsukamoto T, Yanagita M, Kawakami K (2019) Association of low birth weight with childhood proteinuria at age 3 years: A population-based retrospective cohort study. Am J Kidney Dis 74(1):141–143. https://doi.org/10.1053/j.ajkd.2019.02.018 Ramirez SP, Hsu SI, McClellan W (2001) Low body weight is a risk factor for proteinuria in multiracial Southeast Asian pediatric population. Am J Kidney Dis 38(5):1045–1054. https://doi.org/10.1053/ajkd.2001.28596 Chaudhury AR, Reddy TV, Divyaveer SS, Patil K, Bennikal M, Karmakar K, Chatterjee S, Dasgupta S, Sircar D, Pandey R (2017) A cross-sectional prospective study of asymptomatic urinary abnormalities, blood pressure, and body mass index in healthy school children. Kidney Int Rep 2(6):1169–1175. https://doi.org/10.1016/j.ekir.2017.07.018 Kaze FF, Nguefack S, Asong CM, Assob JCN, Nansseu JR, Kowo MP, Nzana V, Kalla GCM, Halle MP (2020) Birth weight and renal markers in children aged 5–10 years in Cameroon: a cross-sectional study. BMC Nephrol 7;21(1):464. https://doi.org/10.1186/s12882-020-02133-9 White SL, Perkovic V, Cass A, Chang CL, Poulter NR, Spector T, Haysom L, Craig JC, Salmi IA, Chadban SJ, Huxley RR (2009) Is low birth weight an antecedent of CKD in later life? A systematic review of observational studies. Am J Kidney Dis 54(2):248–261. https://doi.org/10.1053/j.ajkd.2008.12.042 Beckwith H, Lightstone L, McAdoo S (2022) Sex and gender in glomerular disease. Semin Nephrol 42(2):185–196. https://doi.org/10.1016/j.semnephrol.2022.04.008 Supplementary Files Graphicalabstract.pptx Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2026 Read the published version in Bratislava Medical Journal → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4164128","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283777013,"identity":"900dbdc4-ede8-4d9d-a2cc-185fb035d157","order_by":0,"name":"Patrik 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fakulta","correspondingAuthor":false,"prefix":"","firstName":"Jakub","middleName":"","lastName":"Zieg","suffix":""}],"badges":[],"createdAt":"2024-03-25 14:44:22","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4164128/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4164128/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s44411-026-00556-8","type":"published","date":"2026-03-04T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53749290,"identity":"d3e91d5a-f09a-437e-9126-50c9e4e15e32","added_by":"auto","created_at":"2024-03-29 18:30:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31912,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart. LBW - Low birth weight, VLBW – Very low birth weight.\u003c/p\u003e","description":"","filename":"Figure1flowchart.png","url":"https://assets-eu.researchsquare.com/files/rs-4164128/v1/51a70700f0bd019831598216.png"},{"id":104449634,"identity":"3afccedb-f527-4076-be24-defbb74373ec","added_by":"auto","created_at":"2026-03-11 22:16:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":672996,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4164128/v1/030001a3-6f21-41bb-9aec-b3e7720e7529.pdf"},{"id":53749289,"identity":"027c1798-cf65-4e8b-8a42-dd22cb7bd110","added_by":"auto","created_at":"2024-03-29 18:30:41","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":78617,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.pptx","url":"https://assets-eu.researchsquare.com/files/rs-4164128/v1/5d68dc096f2d44cbb0df0604.pptx"}],"financialInterests":"","formattedTitle":"Risk factors for the development of cardiovascular diseases among 5-year-old low birth weight children","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases (CVD) are the principal cause of mortality worldwide. The risk factors (RF) for CVD such as hypertension (HT), hyperlipidemia, and diabetes mellitus (DM) lead to the formation of atherosclerosis with subsequent episodes of myocardial infarction, cardiac arrhythmias, and stroke. A healthy lifestyle and specific treatments targeting RFs reduce the risk of CVD and improves public health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the early nineties, Brenner et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] postulated that a decreased number of nephrons is associated with the development of HT. They explained their hypothesis by the decreased filtration surface area, which leads to sodium retention and development of systemic HT. Subsequently, glomerular capillary HT causes glomerulosclerosis and a further reduction in the filtration surface area, creating a vicious cycle. They supported their hypothesis with the previous knowledge of increased risk of HT in individuals with a naturally reduced number of nephrons, such as those with unilateral renal agenesis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Normally, 60% of all nephrons develop in the third trimester. In preterm children, nephrogenesis may continue after birth but appears to be abnormal due to the formation of defective glomeruli. Such glomeruli may be more susceptible to subsequent damage from events such as acute kidney injury (AKI) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A positive correlation was found between birth weight (BW) and total number of nephrons [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, based on Brenner's theory, individuals born with a low birth weight (LBW) should have a higher risk of HT than those born with a normal birth weight (NBW). This has been demonstrated by many studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Chronic kidney disease (CKD) is a significant RF for HT and CVD, and has also been found to be associated with a LBW [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These characteristics predispose a large proportion of the global population to HT, CKD, and subsequently CVD. Based on the United Nations International Children's Emergency Fund data, around 15\u0026ndash;20% of people are born LBW around the world [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Besides HT and CKD, other CVD RFs such as hyperlipidemia and DM have also been found to be associated with LBW and prematurity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe purpose of this paper was to evaluate CVD RFs in a cohort of 5-year-old LBW children.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003eThis was a two-center, cross-sectional, observational and prospective study conducted in Prague, Czech Republic (\u003cem\u003eInstitute for the Care of Mother and Motol University Hospital\u003c/em\u003e) between 2021 and 2023. The goal was to evaluate CVD RFs at 5 years of age in children born with a very low birth weight (VLBW). Caregivers of all VLBW children aged 5 years born between 01.01.2016 and 31.09.2017 in one of the centers, without any known pathogenic variants and living within a 1 hour travel radius of Prague, were contacted and offered participation in the study. In the case of twins, both were automatically offered to be involved in the study even if the BW for one of them was \u0026ge;\u0026thinsp;1500g. LBW was defined as BW\u0026thinsp;\u0026lt;\u0026thinsp;2500g, VLBW as BW\u0026thinsp;\u0026lt;\u0026thinsp;1500g, extremely low birth weight (ELBW) as BW\u0026thinsp;\u0026lt;\u0026thinsp;1000g, and small for gestational age (SGA) as BW\u0026thinsp;\u0026lt;\u0026thinsp;2 standard deviations (SDs) below the mean.\u003c/p\u003e \u003cp\u003eSix RFs (four measured by laboratory tests) were examined: serum low-density lipoprotein (LDL); serum high-density lipoprotein (HDL); serum triglycerides (TG); urine protein/creatinine ratio (PCR); masked HT; and non-dipping blood pressure (BP) diagnosed by ambulatory blood pressure monitoring (ABPM). The blood samples were obtained after 12 hours of fasting and urine samples were collected from a first morning urine collection. Samples were analyzed immediately after being transported to the laboratory. Photometric analyses of LDL, HDL, and TG in the serum and total protein and creatinine in the urine were performed using the Atellica Solutions CH 930 analyzer (Siemens, USA). Cut-off values for elevated blood lipid levels were used from the National Cholesterol Education Program Expert Panel on Blood Cholesterol Levels in Children [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A PCR\u0026thinsp;\u0026gt;\u0026thinsp;20 mg/mmol was considered to be pathologic proteinuria.\u003c/p\u003e \u003cp\u003eBP values measured during periodic pediatric follow-ups were evaluated for office HT, and prenatal and perinatal data were obtained from the medical record. ABPM was performed according to the American Heart Association statement on ABPM, with daytime and nighttime measurements every 20 minutes and 30 minutes, respectively [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The OnTrak ABPM machine (from Spacelabs healthcare, Snoqualmie, United states of America) was used for ABPM and the data were evaluated on the ABPM Report Management System version 3.1.0 (from Spacelabs healthcare, Snoqualmie, United states of America). Results with fewer than 40 successful measurements were considered invalid. Non-dipping BP was defined as a BP reduction of less than 10% during the night. Masked HT was defined as ambulatory HT and a normal office BP. The office HT was defined as a BP\u0026thinsp;\u0026ge;\u0026thinsp;95th percentile for age, sex, and height based on general pediatrician (GP) follow-up.\u003c/p\u003e \u003cp\u003eGrowth and weight parameters measured by GPs during periodic follow-up were collected, as well as prenatal and perinatal data from the obstetrics records. The anthropometry was performed by a single experienced anthropologist. The height was obtained using a wall-mounted Seca stadiometer (A-226 manufactured by Trystom in Olomouc, Czech Republic) with an accuracy of 1 mm. Body mass index (BMI) was based on values measured on the calibrated weighing electronic scale with an accuracy of 0.1 kg (TH200, manufactured by Tonava in Upice, Czech Republic). Arm, abdomen, and calf circumferences were measured with a tape measure with an accuracy of 1 mm. The BMI was calculated using the standard formula as weight (in kg) divided by height (in meters) squared. Height, BMI, and arm, abdomen and calf circumference SDs were generated from the RustCZ software using the learning management system (LMS) method based on the 6th Czech National-wide Anthropological Survey of Children and Adolescents [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. GF was defined as height\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2 SDs and growth below the midparental height range and/or lag-down growth by more than 2 percentile zones after the 2nd year of age. Malnutrition was defined as BMI\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2 SDs and/or arm circumference\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2 SDs and/or calf circumference\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2 SDs. Growth velocity (GV) in the first year of life was calculated from the first measured body length and the body length measured at the time of the first birthday. The evaluated period did not exceed 12 months.\u003c/p\u003e \u003cp\u003eIn total, of the 233 children with VLBW were eligible for the study, 110 were enrolled (with the inclusion of eight LBW twin siblings with BW\u0026thinsp;\u0026ge;\u0026thinsp;1500g). Fifty-six were twins and 54 were singletons. In 51 children, all six factors were successfully collected and in 105, only the four laboratory RF were collected (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStatistical analysis was performed in the statistical package R. A P-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered to be statistically significant. Analyses of the associations were performed separately in twins and singletons because the twins consisted of dependent data and they had different distributions of investigated parameters in our cohort (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Associations of risk factors with CVD RFs were tested for. These risk factors were BW, GA, body-mass index (BMI), GV, SGA, sex, BW\u0026thinsp;\u0026lt;\u0026thinsp;1000g, family history of HT, type of birth, antenatal corticosteroids use, coffee drinking during pregnancy, hypertensive disorders of pregnancy (HDP), maternal anemia, bronchopulmonary dysplasia (BPD), neonatal sepsis, use of furosemide, aminoglycosides, and patent ductus arteriosus (PDA). Gestational diabetes, smoking, alcohol use during pregnancy, use of nonsteroidal analgesics (NSAID), neonatal AKI, and necrotizing enterocolitis were excluded because of the insignificant numbers of pregnancies with these factors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistributions of some of the investigated parameters in the twins and singletons groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRisk factor\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSingletons group (mean)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eTwins group (mean)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1003.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1212.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age (weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSingletons group (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eTwins group (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight\u0026thinsp;\u0026lt;\u0026thinsp;1000g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age\u0026thinsp;\u0026lt;\u0026thinsp;29 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee drinking during pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal anemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchopulmonary dysplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive disorder of pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAbsolute numbers with percentage and mean values with SDS were used for descriptive statistics. In the twins group, the logistic models with generalized estimating equations to correct for the dependencies between the twins were used. Logistic models were also used in the singletons group. In case of categorical variables being present only in one compared group in the singleton group, P-values were analyzed using Fisher tests.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eComplete cohort\u003c/h2\u003e \u003cp\u003eIn our cohort, 8 (7.3%) children were born with LBW, 58 (52.7%) with VLBW and 44 (40%) with ELBW. Fifty-seven (51.8%) were girls and 53 (48.2%) were boys, mean BW was 1109.7 g\u0026thinsp;\u0026plusmn;\u0026thinsp;315.4 (370\u0026ndash;1890) g and mean GA was 29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 (23\u0026ndash;34) weeks. All children were of Caucasian ethnicity. All children were normotensive during regular pediatric check-up.\u003c/p\u003e \u003cp\u003eMean BW in the excluded group was 1105.1\u0026thinsp;\u0026plusmn;\u0026thinsp;260 g, GA 29.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 weeks, and 39.7% had ELBW. Differences of BW and GA between both groups were not significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.9397 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4864, respectively).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the prevalence of each RF, Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the number of children with 0\u0026ndash;4 RF separately for all measured RF with and without ABPM results. In patients where all six RF were obtained, 58.8% had at least 1 of the CVD RF presented. In the group without ABPM results, 40.1% had at least 1 of the CVD RF.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe number of children with each risk factor for cardiovascular disease.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factor (missing values)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients (110)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingletons (54)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTwins (56)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL\u0026thinsp;\u0026ge;\u0026thinsp;3.4 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13 (23.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u0026thinsp;\u0026ge;\u0026thinsp;1.1 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLD\u0026thinsp;\u0026lt;\u0026thinsp;1 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCR\u0026thinsp;\u0026gt;\u0026thinsp;20 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (17.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMasked HT (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (10.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-dipping (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (48.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*HLD \u0026ndash; High density lipoprotein, HT \u0026ndash; Hypertension, LDL \u0026ndash; Low density lipoprotein, PCR \u0026ndash; Protein/creatinine ratio (in mg/mmol), TG \u0026ndash; Triglycerides.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of children with 0 to 4 risk factors.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAll risk factors measured (n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAll risk factors measured but ABPM (n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factors (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (singletons/twins)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% (singletons/twins)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en (singletons/twins)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% (singletons/twins)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (10/11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.2 (45.5/37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (30/33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.0 (61.2/58.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (6/6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5 (27.3/20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (16/14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.6 (32.6/25.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (4/6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.6 (18.2/20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (3/6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.6 (6.1/10.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (2/5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.7 (9.1/17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.9 (0.0/5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0/1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (0/3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0/0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0 (0.0/0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*ABPM \u0026ndash; Ambulatory blood pressure monitoring.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the singletons\u0026rsquo; group, there was a higher prevalence of masked HT and decreased HDL than in the twins\u0026rsquo; group (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). An increased GV was associated with decreased HDL (OR 1.36, 95% CI 1.03\u0026ndash;1.92, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045). No other associations were found in the singletons\u0026rsquo; group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations with cardiovascular disease risk factors.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociations (singletons)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssociations (twins)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMasked hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-dipping blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreased GV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecreased HDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncreased GV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProteinuria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSGA, maternal anemia, female, higher gestational age\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated LDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated TG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*HDL \u0026ndash; High density lipoprotein, LDL \u0026ndash; Low density lipoprotein, TG \u0026ndash; Triglycerides.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the twins\u0026rsquo; group, there was a higher prevalence of LDL hypercholesterolemia and non-dipping compared to singletons (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Three children had masked HT, each from a different twin couple. Elevated LDL was found in 6 twin couples and in 1 twin with a sibling with normal LDL value. Increased GV was a protective factor for non-dipping BP (OR 0.83, 95% CI 0.70\u0026ndash;0.99, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0384). SGA (OR 3.59, 95% CI 1.11\u0026ndash;11.59, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0323), maternal anemia (OR 6.41, 95% CI 1.13\u0026ndash;36.23, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0356) and higher GA (OR 2.43 for 1 week of age, 95% CI 1.49\u0026ndash;3.98, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004) were associated with pathologic proteinuria, male sex was protective factor (OR 0.16, 95% CI 0.03\u0026ndash;0.75, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0203). No other associations were found in the twins\u0026rsquo; group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, we found a high prevalence of risk factors for the development of CVD in 5-year-old LBW children: 58.8% had at least one RF. The association between LBW and CVD has already been described by Barker et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This concept of an early origin of noncommunicable diseases, known as developmental origins of health and disease (DOHAD), has been studied during the last decades and continues to be a hot topic because early detection of RFs and implementation of preventive measures may have a huge impact on public health [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHT is one of the most studied RFs for CVD associated with LBW. Many studies have found an association between prematurity, LBW, SGA, and increased growth velocity (GV) and higher BP [\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Adults born with a VLBW were found to have a higher BP, with female sex and maternal preeclampsia being additional RFs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In a longitudinal study by Jounala et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], adults born preterm and SGA had a higher BP than those born preterm and appropriate for gestational age. Interestingly, GV, in contrast to BW, was found to be better associated with increased BP [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Based on the recent metanalysis, LBW was associated with CVD, HT, and DM [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In a study of children younger than 5 years, those born preterm had a higher BP than term-born control [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A study of Vohr et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] reported a high prevalence of HT and high BP in extremely preterm infants at age 6 to 7 years, with GV and maternal DM being RFs. In a prospective study by Lurbe et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], BW was a positive determinant of BP in newborns born at term; later, current weight was the strongest determinant for BP.\u003c/p\u003e \u003cp\u003eIn our study, there was a high prevalence of masked HT (13.7%) and non-dipping BP (37.7%). In the twins groups, all of the individuals with HT were from different twins\u0026rsquo; couples, which shows that genetic predisposition and environment had little impact on the development of HT. We did not find any association with HT, likely due to the low total number of patients in each group; on the other hand, increased GV was associated with a decreased risk of non-dipping BP in the twins group. Non-dipping BP was found to be associated with CVD [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This protective effect of GV on night dipping found in twins group may imply that the possible effect of GV on BP and other CVD RFs is more complex and some subgroups of patients may even benefit from that.\u003c/p\u003e \u003cp\u003eMany studies have reported an association between abnormal lipid metabolism and LBW. LBW/premature individuals may have different adiposity, with intra-abdominal and intrahepatocellular fat which could be explained by different growth patterns in these children [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Rapid gain in weight for length in the first 3 months after term age was found to be positively associated with total cholesterol and LDL in early adulthood [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A study by Pehkonem et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] reported that both GV and LBW were associated with TG level, but not with LDL. A metanalysis in 2017 reported that LBW is associated with total cholesterol in adult women younger than 50 years and in adult men [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our study, there was a high prevalence of serum lipid pathologies, especially of elevated LDL values (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Despite the emerging result, the LDL values must be taken with caution, because in the twins group the elevation was present in almost all cases in twin couples, which suggests a possible genetic predisposition, although no parents reported dyslipidemia in the family. The only association found in our study was between an increased GV and decreased HDL, which supports previous results of an association between GV and lipid metabolism abnormalities.\u003c/p\u003e \u003cp\u003eFew studies examined the association between LBW and proteinuria. In a study by Shinzava et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], LBW was associated with proteinuria and the odds were higher in VLBW individuals than in their LBW counterparts [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Ramirez et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] did not find any significant association between lower BW and proteinuria, which was only associated with the current body weight. In our study, almost 18% of children were found to have pathologic proteinuria (defined as PCR\u0026thinsp;\u0026gt;\u0026thinsp;20 mg/mmol), which is higher than the prevalence reported in the general population in children and similar to the previous studies on LBW [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Pathologic proteinuria is a sign of CKD, which is a known RF for CVD and was found to be associated with LBW [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The proteinuria in our LBW cohort was associated with SGA, maternal anemia, and female sex in the twins group. The association between SGA, LBW, prematurity, and CKD was found in many studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. We found no study reporting an association between maternal anemia and subsequent proteinuria in the offspring, but iron deficiency and poor nutritional status during pregnancy are known RFs for LBW [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Sex-specific differences in kidney diseases are well known: the higher prevalence of proteinuria in females in our study is therefore not surprising [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Interestingly, a higher GA was also associated with proteinuria in the twins group. We believe that this result is only the projection of the high proportion of SGA in the twins with proteinuria, rather than a real association between higher GA and proteinuria (prevalence of 12.8% SGA in twins without proteinuria and 44.4% in twins with proteinuria).\u003c/p\u003e \u003cp\u003eOur study has several limitations. We present only a prevalence of RFs in the studied group without a control group; on the other hand, the prevalence is much higher than expected and still gives us valuable information about RFs for CVD in LBW children. Another factor was the presence of twins, which required separation of the patients into two groups. Because of this, some associations may have been missed due to the reduced number of patients in each group. On the other hand, twins allowed us to study associations in a very specific population with similar genetic and environmental backgrounds. Many ABPM recordings were invalid due to an insufficient number of successful measurements, which allowed us to study the prevalence of all RFs in only about a half of the examined children. Due to the character of the study, there may be selection bias, but the birth parameters of the children in our cohort had a very similar distribution to those who were excluded. We therefore believe that our group of patients represents the standard distribution in population.\u003c/p\u003e \u003cp\u003eIn conclusion, 5-year-old children born with a LBW have a high prevalence of CVD RFs. Early intervention with closer follow-up is required even in early childhood in individuals born with LBW. The association between CVD RFs and GV appears to be both negative and protective in different populations and needs to be studied more thoroughly. SGA status at birth, female sex, and maternal anemia are associated with proteinuria in LBW twins.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo acknowledgements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Charles University Research Project Cooperation (Maternal and Childhood care section).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee for Multi-Centric Clinical Trials of the University Hospital Motol and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study design and research ideas were created by Patrik Konop\u0026aacute;sek. Data acquisition from the perinatal period was performed by Martina Frantov\u0026aacute; and Peter Korček. The tables and figures were created by Patrik Konop\u0026aacute;sek and Monika Peckov\u0026aacute;. Statistical analysis was performed by Monika Peckov\u0026aacute;. Karel Kota\u0026scaron;ka provided laboratory investigation management and text revision. The first draft was written by Patrik Konop\u0026aacute;sek. Monika Peckov\u0026aacute;, Aneta Kodytkov\u0026aacute;, Peter Korček, Karel Kota\u0026scaron;ka, and Zbyněk Straň\u0026aacute;k critically reviewed the article, and Jakub Zieg critically reviewed the article and supervised the study. All authors contributed to the study by acquiring data, drafting the article, or interpreting the results. Each author revised the manuscript and played a role in creating its final version and approved it for submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFlora GD, Nayak MK (2019) A brief review of cardiovascular diseases, associated risk factors and current treatment regimes. Curr Pharm Des 25(38):4063\u0026ndash;4084. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2174/1381612825666190925163827\u003c/span\u003e\u003cspan address=\"10.2174/1381612825666190925163827\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrenner BM, Garcia DL, Anderson S (1988) Glomeruli and blood pressure. Less of one, more the other? 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Semin Nephrol 42(2):185\u0026ndash;196. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.semnephrol.2022.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.semnephrol.2022.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prematurity, Low birth weight, Cardiovascular disease, Risk factors, Hypertension","lastPublishedDoi":"10.21203/rs.3.rs-4164128/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4164128/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLow birth weight (LBW) is associated with cardiovascular diseases (CVD); however, the roles of specific clinical and biochemical attributes remain unknown.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this two-center study, we investigated risk factors (RFs) for the development of CVD among 5-year-old LBW children. The assessed RFs were low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride (TG) levels; urine protein/creatinine ratio (PCR); masked hypertension (HT); and non-dipping blood pressure (BP).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 110 children participated in this study (eight with a BW\u0026thinsp;\u0026lt;\u0026thinsp;2500g, 58 with a BW\u0026thinsp;\u0026lt;\u0026thinsp;1500g, and 44 with a BW\u0026thinsp;\u0026lt;\u0026thinsp;1000g) and all six factors were successfully collected in 51 of the children. Over half (58.8%) of the children had at least one RF. Masked HT, elevated LDL, TG, PCR, decreased HDL and the presence of non-dipping BP were found in 13.2%, 16.7%, 13.6%, 17.8%, 8.2%, and 37.7% of participants, respectively. Increased growth velocity (GV) was associated with decreased HDL (OR 1.36, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045) and lower risk of non-dipping BP (OR 0.83, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0384). Small for gestational age (SGA) status (OR 3.59, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0323), maternal anemia (OR 6.41, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0356), and greater gestational age (GA) (OR 2.43 per 1 week of age, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004) were associated with proteinuria, while male sex was a protective factor (OR 0.16, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0203).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere was a high prevalence of CVD RFs in 5-year-old LBW children. SGA status at birth, maternal anemia, female sex, and higher GA were associated with proteinuria. The role of GV in the etiopathogenesis of CVD remains controversial.\u003c/p\u003e","manuscriptTitle":"Risk factors for the development of cardiovascular diseases among 5-year-old low birth weight children","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-29 18:30:36","doi":"10.21203/rs.3.rs-4164128/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b4eedbf5-acea-4fba-987f-59d7ecca13c9","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-11T22:16:26+00:00","versionOfRecord":{"articleIdentity":"rs-4164128","link":"https://doi.org/10.1007/s44411-026-00556-8","journal":{"identity":"bratislava-medical-journal","isVorOnly":false,"title":"Bratislava Medical Journal"},"publishedOn":"2026-03-04 00:00:00","publishedOnDateReadable":"March 4th, 2026"},"versionCreatedAt":"2024-03-29 18:30:36","video":"","vorDoi":"10.1007/s44411-026-00556-8","vorDoiUrl":"https://doi.org/10.1007/s44411-026-00556-8","workflowStages":[]},"version":"v1","identity":"rs-4164128","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4164128","identity":"rs-4164128","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}