Associations for birth weight were stronger in boys for FEV1  0.24 to 0.38, girls: 0.18 L, 95% CI 0.12 to 0.25), FVC  and FEF25–75%  adjusted for age, socioeconomic position and infant and maternal characteristics. Similarly adjusted, preterm birth (compared to full-term birth) was associated with lower FEV1/FVC and FEF25–75%. Thus, associations of lower birth weight, especially in boys, and prematurity with poorer lung function at 17.5 years were found. Identifying underlying mechanism might contribute to the improvement of pulmonary health and the prevention of adult respiratory illness.We aimed to determine if prematurity and lower birth weight are associated with poorer lung function in a non-western developed setting with less marked confounding by socioeconomic position. Using multivariable linear regression in Hong Kong’s “Children of 1997” birth cohort, adjusted associations of prematurity and birth weight with forced expiratory volume in 1 second (FEV Observationally poorer intrauterine experiences, proxied by birth weight or premature birth, are adversely associated with many aspects of adult health, including poorer lung function6. Lung function contributes both directly to chronic diseases via lung diseases and indirectly as a cardiovascular-related risk factor8, with potentially a causal role of forced expiratory volume9.The developmental origins of health and diseases (DOHaD) hypothesis emphasizes the role of poorer early growth, particularly in the first 1000 days, in non-communicable diseases (NCDs)10. On the other hand, there have been occasions when observational evidence has not been such a reliable guide, for example as regards the effects of hormone replacement therapy or vitamins12, likely because of residual confounding. Observational studies of birth attributes are open to confounding by maternal smoking, maternal overweight and lower socioeconomic position, which are also associated with worse birth outcomes and many health-conditions, including poorer lung function16. Birth weight also depends on gestational age which may not always be accurate, particularly in studies from before the routine use of ultrasound dating scans, when prematurity may be related to lower lung function20. The DOHaD hypothesis that early life is the critical period for respiratory health also does not consider evolutionary biology life history trade-offs, where early survival to reproductive age could trade-off against adult health including respiratory function. Lung function tracks throughout life21. Observationally, birth weight is inversely associated with indicators of restrictive lung function ) but evidence is weaker for the association of indicators of obstructive patterns (lower FEV1/FVC) in adults5. Previous studies have shown airway obstruction ) in extreme preterm births while fewer studies have focused on lung function in late preterm births26.The DOHaD hypothesis has major implications for the care of mothers and babies. The DOHaD hypothesis largely rests on observational evidence from Western settings, which can be a very effective guide to action, for example as regards the harms of smoking1) and FVC29. More generally, Mendelian randomization studies of birth weight are difficult to interpret because of confounding by infant and/or maternal genetics31, but a study of monozygotic twins suggested little effect of birth weight on ischemic heart disease32. However, randomized controlled trials concerning the long-term effects of interventions targeting birth weight on lung function, are difficult and expensive to implement, and few such trials exist34. To our knowledge no Mendelian randomization studies have assessed whether birth weight is a causal factor for lung function, despite the relation between lung function and cardiovascular disease9. Hong Kong is a developed non-Western city, with social infrastructure and economic development similar to Western countries, where few women smoke, maternal overweight is less common than elsewhere35, and gestational age and birth weight are less confounded by socio-economic position36. Assessing the role of birth weight in lung function in this setting is less open to confounding possibly because of the less evident association of parental height with socioeconomic position in this population mainly formed by migrants from southern China in the mid-20th century37. In this unique non-Western setting we examined the relations of birth weight and prematurity with lung function at ~17.5 years in a Hong Kong Chinese birth cohort: “Children of 1997”. We also considered whether the associations varied by sex, because of the shorter life expectancy in men than women.Evidence from twin studies, which are less open to confounding by family socio-economic position, is limited, but suggests lower birth weight is associated with poorer lung function, i.e. lower expiry in the first second of forced expiration . Informed written consent was obtained from the parents/guardians, or from the participant if 18 years or older, before participation in the Biobank Clinical Follow-up. All methods were performed in accordance with the relevant guidelines and regulations.38. At the infant’s first visit for free vaccinations and postnatal preventive care at all Maternal and Child Health Centers (MCHCs) in Hong Kong, 8237 mother-infant pairs were enrolled in an 18-month study to examine the association of environmental smoking with infant health39. Maternal characteristics , family characteristics (education and residency status) and infant characteristics  were parent-or-career reported using a self-administered questionnaire in Chinese. Socioeconomic characteristics, such as parental occupation, household size and monthly household income were also reported. The study was resurrected as a birth cohort in 2005, with record linkage to Maternal and Child Health Center (MCHC) clinical records of growth and development including weight from birth to 5 years, and height from 3 months . In 2008–2012, active follow-up via three postal and/or telephone surveys was conducted. In 2013–2016, a Biobank clinical follow-up was conducted including anthropometrics, and a health check. Lung function was measured by spirometry (SpiroBank G Spirometer with WinspiroPRO software) and cleaned according to the American Thoracic Society/European Respiratory Society (ATS/ERS) criteria40. All lung function measurements were performed in a standing position with normal breath at rest before each test. Forceful slow inhalation and quick exhalation were performed not more than six times for at least three acceptable blows according to the ATS/ERS criteria, and the flow-volume curves with data were recorded. Any blow with a curve that did not resemble the ATS/ERS criteria predicted graph was considered as unacceptable and discarded. The spirometric curves with the maximum sum of FVC and FEV1 were selected.The current study utilizes a population-representative Chinese birth cohort from Hong Kong, “Children of 1997”, covering 88% of all births between April 1 and May 31, 1997, as described elsewhere42. Gestational age was calculated from the interval between expected and actual date of delivery. Preterm birth was defined as birth before 37 completed gestational weeks. Using the most commonly used cutoffs (10th and 90th percentile in singletons), we categorized sex- and gestational age-specific z-score for birth weight into small-for-gestational age (SGA), appropriate-for-gestational age (AGA) and large-for-gestational age (LGA)43.Given the birth weight in our population representative cohort is lower than the WHO standard, the WHO standard is not suitable for measuring the body size at birth in our study, hence we considered birth weight as internal sex- and gestational age-specific z-scores (standard deviation score) for singletons in this population-representative birth cohort1, FEF25–75% and FEV1/FVC, measured at ~17.5 years. Z-scores of these spirometric indices were based on the Global Lung Function Initiative (GLI) reference 44, which has specific age-, height- and sex- equations for South East Asians based on data from Hong Kong, southwest China, Taiwan and Thailand (collected in 1996–2002) and the Hong Kong reference 45.The outcomes were lung function as FVC, FEVw and Cohen’s d effect size, for categorical variables and continuous variables, where <0.1 and <0.2, respectively, indicate small differences between groups46. Analysis of variance (ANOVA) was used to compare birth weight, birth weight z-score and gestational age by potential confounders. Locally weighted scatterplot smoothing (LOWESS) curves were used to visualize the associations of birth weight and prematurity with lung function. Multivariable linear regression was used to examine adjusted associations of exposures and outcomes. Differences by sex were assessed from the significance of the relevant interaction term adjusted for confounding interactions. Potential confounders considered, i.e., common causes of birth weight or gestational age and lung function at ~17.5 years, included birth order, maternal birthplace, maternal smoking, maternal age at delivery, and parental socioeconomic position . Potential mediators, such as breastfeeding, age of puberty, respiratory infections, weight and smoking, which might mediate the effect of birth weight on lung function but not cause birth weight were not included as confounders to avoid over adjustment47. To illustrate the potential effect of height, we present 2 models with different adjustment. Model 1 adjusted for confounders. Model 2 additionally adjusted for height in the sensitivity analysis using lung function in original units (Table Baseline characteristics of the participants included and excluded were compared using Cohen’s ts Table . We only48. The single estimated β coefficients (mean difference) and 95% CI were summarized from 10 imputed datasets using Rubin’s rules and the inverse probability weights. Statistical analyses were conducted using R version 3.3.1 .To predict missing values for gestational age (0.48% missing) and potential confounders (0.48% to 12.6% missing), multiple imputation based on additive regression and predictive mean matching was used. The regression model for multiple imputation incorporated exposures, outcomes and potential confounders, and interaction terms. To account for the probability of exclusion, inverse probability weighting was used to minimize possible selection bias induced by participants without valid lung function measurements. The inverse probability weights were calculated based on a logistic regression model with predictor variables including the exposures and the measured potential confounders after multiple imputationAs of January, 2017, 29 of the original 8327 cohort participants had permanently withdrawn and were excluded. Of the remaining 8298 participants, 6850 were considered potentially contactable for the Biobank clinical follow-up in 2013–2016. Of these, 3460 attended and completed the lung function test. Lung function curves for 415 participants failed the lung function acceptibility criteria and were excluded, leaving 3030 with valid lung function. Among these 3030, mean birth weight was 3156 grams for girls and 3234 grams for boys. Gestational age was 39.0 weeks on average, 136 (4.5%) were preterm with an average gestational age of 34.8 weeks, of whom 99 (72.8%) were born after 34 gestational weeks. Birth weight and gestational age in the participants with and without valid lung function data did not differ  and FVC  differed by sex, with stronger positive associations in boys than girls, adjusted for age, socioeconomic position and maternal and infant characteristics  was associated with higher FEV1, FVC and FEF25–75% and SGA was associated with lower FEV1, FVC and FEF25–75% but not with FEV1/FVC ratio. These associations were more evident in boys. This pattern remained after additionally adjusting for height, with the estimate slightly attenuated towards the null  at birth, which may result in long-term lung functional abnormalities in later life58. Late preterm births are born at the late saccular stage of lung development when the lung volume and surface area is developing rapidly. Delivery during this period may also result in a less mature lung at birth and dysregulate alveolar development. Infants with immature lungs and poor airway function may be more susceptible to respiratory diseases after birth, which are also linked to worse lung function in late adolescence and early adulthood59. Other exposures that might lead to preterm birth, such as adverse maternal nutritional status, hypertensive disorders and overweight during pregnancy, might also affect airway development in utero60. Finally, poorer maternal lung function, for whatever reason, could result in both poorer birth outcomes and poorer offspring lung function. Apart from the negative exposure causing preterm birth, preterm births are more likely to receive neonatal intensive care, among which some interventions such as mechanical ventilation and oxygen therapy were associated with adverse respiratory health, abnormal lung growth and development61.In animal experiments, sheep and lambs with intrauterine growth restriction (IUGR) have structurally and functionally impaired lung development, suggesting that insults which cause IUGR may detrimentally affect the lungs resulting in persistent alternation in structure and function in later life63 Boys are more vulnerable to respiratory diseases than girls65, but why this should affect particularly lower birth weight boys is unclear. Alternatively, androgens may adversely affect surfactant production coupled with the later start of pulmonary surfactant production in male fetuses66, which might make lighter boys more vulnerable. Finally lower birth weight may reduce muscle mass more in men than women67, possibly with corresponding effects on respiratory function via the respiratory muscles. Mechanistic studies are needed to distinguish between these possibilities so as to identify the best interventions to protect lung function in lower birth weight boys.Stronger associations of birth weight with poor lung function in boys than girls have been observed before68. Nevertheless, key confounders including maternal smoking and socioeconomic position were adjusted for in this study and hence our associations are unlikely to be explained by socioeconomic position or related attributes. Third, poorly reported gestational age without information from ultrasound scans might result in misclassification, which is likely to be small and non-differential because the information was reported by the main caregivers shortly after birth when gestational age looms large. Fourth, we did not assess potential mediators, such as diet and physical activity, and some potential parental confounders, such as maternal nutrition status. Fifth, the internal sex and gestational age specific z-scores for birth weight in the extremely preterm children (≤28 weeks) might be less accurate due to the small sample size of the very preterm births. Replication in other settings with birth weight and gestational age little confounded by socioeconomic factors, or re-examination using Mendelian Randomization accounting for maternal genetics is warranted to confirm the causal effects.Although our study was conducted in a non-western setting with less obvious social patterning of birth weight and prematurity, several limitations exist. First, selection bias may exist, however, those with and without lung function had similar baseline characteristics Table . Additio1, FVC and FEF25–75%, particularly among boys, indicating lower birth weight may reduce lung function mainly in the airway capacity at 17.5 years. In contrast, prematurity was associated with lower FEV1/FVC and FEF25–75%, indicating preterm birth may impair airway development, which suggests increasing vulnerability to obstructive lung diseases. As such, our study suggests that both lower birth weight and prematurity may have long-lasting effects on lung function, which may be particularly detrimental for men.In a population with minimal confounding by socioeconomic position, birth weight was inversely associated with FEVTable S1-S2


Women's basic beliefs about birth as a natural and as a medical process are associated with childbirth choices and experience. These beliefs have only recently been quantified and not much is known about their development. In the current study, we assessed the differential effects of the objective and the subjective birth experience on changes in these beliefs. Using self-report questionnaires, we evaluated prenatal to postpartum changes among 342 Israeli first-time mothers. Participants were recruited during pregnancy, between February 2016 and January 2017, mostly in clinical settings, and followed-up two months postpartum. On average, women's beliefs about birth being natural weakened following childbirth and their belief about birth being medical strengthened. In regression models, it was either the objective or the subjective experience that was related to change in the basic birth beliefs: A more medicalized birth was associated with strengthening of the medical belief while greater birth satisfaction was related to strengthening of the natural belief. A mediation effect was observed, which indicated that the beliefs are strengthened when the lived experience fulfilled women's expectation about birth being satisfying, natural or medical. This study adds to the growing body of knowledge regarding the development and evolution of the birth beliefs. It highlights the need to view the beliefs separately and to distinctively assess the objective and subjective birth experience. It supports the need to empower mothers, especially those who had more medicalized births or unsatisfactory ones, which would help conserve their belief in their body and in the normal physiological course of birth. People's decision-making regarding health-related issues is heavily based on their beliefs and perceptions . The belThe basic birth beliefs refer to the way women view the physical aspects of birth. They are composed of a medical birth belief and a natural birth belief and women may have varying views regarding each belief. The medical and natural beliefs are (negatively) correlated but only moderately, so they do not form a dichotomous continuum. The two beliefs are independent concepts and are not mutually exclusive ,6. BelieQualitative studies have shown that perceiving birth to be natural and safe or medical and risky were related to more medicalized birth choices, such as cesarean delivery (CD) or using analgesia during labor, or more natural birth choices, such as home birth, giving birth at free-standing birth centers or delivering without epidural analgesia –10. The The beliefs have only recently been quantified and there is a dearth of empirical knowledge regarding their development. Nonetheless, there is evidence that women who had a more medicalized obstetric history (such as pregnancy loss) have a stronger belief that birth is a medical process and a weaker belief that it is a natural process . In addiIn the current study we wished to assess the effects of actual and subjective birth experiences on first-time mothers' basic birth beliefs. To our knowledge, an investigation studying changes in the beliefs following birth has not been documented. Gaining deeper insight into the mechanisms related to the beliefs will propel theoretical knowledge regarding birth and could also have clinical implications. Prenatally, understanding women's beliefs and their correlates can help instigate open discussion with women about their expectations regarding childbirth and promote patient-centered care and shared-decision making regarding birth choices. Postpartum, understanding how the lived birth experience affects women's beliefs could help practitioners relate to women's experiences and ameliorate perceptual consequences that a negative birth experience might have. Since perceptions about birth are known to develop even before the first pregnancy , we expeM = 31.7±5.2 weeks gestation) and two months postpartum (T2 M = 9.2±3.6 weeks postpartum). Eligibility criteria included a singleton pregnancy ≥ 24 weeks gestation, with VD medically possible (for example no placenta previa). Exclusion criteria were being in labor pain (VAS > 3) or having a medical emergency and non-Hebrew speaking.The current report focuses on 342 primiparae who completed questionnaires prenatally . Recruitment of women for the study took place between February 2016 and January 2017 at three settings: (1) At four different Women’s Health Centers of Clalit Health Care Services in the center of Israel while waiting for prenatal check-up; (2) At Rabin Medical Center,  when coming for a prenatal class, hospital tour, check-up or birth; (3) Purposeful sampling of women who preferred to birth in alternative modes of birth  through specific, natural/home birth Facebook groups, home midwives, or personal acquaintances.Recruitment was mostly done by trained social work graduate students  with a small part conducted by midwives . Women who were recruited at the clinical settings received an explanation about the study from a member of the study team and were asked for their written consent. Participants were also asked for their contact information for follow-up. Thereafter, they completed the baseline questionnaire (T1). Women recruited in the purposeful, alternative fashion, were offered a paper questionnaire or an identical online version. Before completing the questionnaire, these women were also asked to indicate their consent and provide their contact information.Overall, 976 primiparae and multiparae women completed the baseline questionnaire: Sixty-six percent were recruited at Women's Health Centers, 22% in the alternative sampling and 12% at the hospital. Out of 1,059 women who were approached at the clinical settings and were eligible to participate in the study, 764 agreed to participate and filled out the first questionnaire (72.6% recruitment rate). Main reasons for not participating were disinterest, dislike of surveys, concerns about anonymity and lack of time. Two of the recruited women were later excluded because of perinatal infant mortality. Another 214 women were recruited in the alternative sampling. Since the invitation to the survey in the alternative sample was mostly online, we were unable to determine recruitment rates. Of all women participating at T1, 413 (42.3%) were primiparae.n = 342, 82.8%).Follow-up was conducted by the study team approximately two months postpartum (T2). Women who provided an email address were sent a unique link to the questionnaire two months after their due-date using Qualtrics survey software. Women who did not complete the survey were followed up by text message, a reminder email and a phone call. Women who did not use email were mailed a paper questionnaire with a return envelope. These women were contacted by phone prior to the mailing of the questionnaire and two weeks after to ensure it was received and filled out. Return rates of the second survey were high for the whole sample (80%) and even higher for the primiparae  [le (BBS)  which inActual Birth was assessed at T2. Women were asked where and how they birthed, with the following options: Emergency CD; Planned CD; Instrumental VD; VD with epidural analgesia; VD without epidural analgesia in a regular delivery room; VD in a natural birth center; Home birth. A panel of three obstetricians and four midwives assessed these options for face validity and rated them on a medical to natural continuum. There ratings had an almost perfect agreement [greement . TherefoBirth Satisfaction was assessed at T2 using the Childbirth Satisfaction Scale [on Scale . The scat-test for prenatal to postpartum changes. Hierarchical linear regression and the PROCESS macro [Analyses were performed using SPSS 24  on the dSS macro  were useParticipants were on average 30.0±4.5 years old at recruitment (T1). They were mostly Jewish (98.5%) and married or cohabiting (95.3%). Additional socio-demographic characteristics can be found in n = 142, 41%), followed by instrumental birth , emergency CD , and VD without epidural in a regular delivery room . Fewer women had an elective CD , home birth  or birth in a natural birth center .Descriptive statistics for the study variables are presented in Intercorrelation between study variables are presented in r = 0.63 and r = 0.78, respectively for the Natural and the Medical beliefs). Yet, when conducting a Students' t-test for paired variables, on average, women's postpartum BBS-Natural (M = 3.94±0.64) was weaker compared to the prenatal measurement (M = 4.10±0.58) (t(322) = 5.72, p < 0.001). Correspondingly, postpartum BBS-Medical (M = 3.39±0.83) was stronger compared to the prenatal measurement (M = 3.27±0.83) (t(323) = -4.01, p < 0.001). In other words, following birth, on average, the beliefs became more medical and less natural.As can be seen, the associations between prenatal and comparable postpartum beliefs were strong  predicted an increase in postpartum BBS-Natural. In contrast, when predicting postpartum BBS-Medical, after controlling for the prenatal BBS-Medical, Actual Birth (but not Birth Satisfaction) predicted an increase in BBS-Medical.Hierarchical linear regression models were used to predict the effects of the birth experience on prenatal to postpartum changes in both the beliefs . The depSince there were correlations between the prenatal BBS-Natural and Birth Satisfaction and BBS-Medical and Actual Birth, there was reason to examine whether the birth experiences mediated the association between the prenatal and postpartum beliefs. Mediation tests conducted with the PROCESS macro indicated significant partial mediation : signifiWomen approaching their first birth mostly agreed that birth is a natural process yet were more varied regarding the belief that it is a medical process. These findings are in line with those from qualitative studies showing that although women in Western, medicalized birth cultures  are ofteThe mediation model indicated that women who tended to view birth as medical and dangerous also tended to have more medicalized births , which in turn perpetuated and even strengthened their medicalized beliefs. Modern birth culture emphasizes the inherent faultiness of the female body  and in aBeliefs about birth as a natural process were associated with birth satisfaction in a reciprocal manner. Women who prenatally had stronger beliefs that birth is a natural process, were more satisfied with their births, which led to even stronger beliefs that it is a natural process. It is possible that the natural beliefs affected their expectations and experience of birth ,13,14. WThe knowledge gained from this study could help practitioners who provide perinatal care to women, better relate to women's birth expectations and experiences. As obstetrics shifts to more patient-centered care, there is increasing interest in women's perceptions and needs . Birth aOne of the strengths of our study was that it was prospective, measuring beliefs both before and after women's first birth. Thus, we could estimate change in our outcome measures related to the birth experience, though causality could not be conclusively determined. Additional strengths included the sample size, focusing on first-time mothers, and the heterogeneity of birth modes. However, despite the rigor of the sampling method and the large sample size, it was not representative of the general Israeli population and generalization should be made with caution.Our conclusion is in line with the recent World Health Organization guidelines regarding encouraging intrapartum care practice which contributes to a positive birth experience : SupportS1 File(XLSX)Click here for additional data file.


Customized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth. It is unknown whether customized birth weight charts better identify newborns at risk of long-term adverse outcomes than population birth weight charts. We aimed to examine whether birth weight classification according to customized charts is superior to population charts at identification of newborns at risk of adverse cardio-metabolic and respiratory health outcomes.In a population-based prospective cohort study among 6052 pregnant women and their children, we measured infant catch-up growth, overweight, high blood pressure, hyperlipidemia, liver steatosis, clustering of cardio-metabolic risk factors, and asthma at age 10. Small size and large size for gestational age at birth was defined as birth weight in the lowest or highest decile, respectively, of population or customized charts. Association with birth weight classification was assessed using logistic regression models.Of the total of 605 newborns classified as small size for gestational age by population charts, 150 (24.8%) were reclassified as appropriate size for gestational age by customized charts, whereas of the total of 605 newborns classified as large size for gestational age by population charts, 129 (21.3%) cases were reclassified as appropriate size for gestational age by customized charts. Compared to newborns born appropriate size for gestational age, newborns born small size for gestational age according to customized charts had increased risks of infant catch-up growth (odds ratio (OR) 5.15  4.22 to 6.29)), high blood pressure (OR 2.05 (95% CI 1.55 to 2.72)), and clustering of cardio-metabolic risk factors at 10 years (OR 1.66 (95% CI 1.18 to 2.34)). No associations were observed for overweight, hyperlipidemia, liver steatosis, or asthma. Newborns born large-size for gestational age according to customized charts had higher risk of catch-down-growth only (OR 3.84 (95% CI 3.22 to 4.59)). The direction and strength of the observed associations were largely similar when we used classification according to population charts.Small-size-for-gestational-age newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of the use of customized or population birth weight charts. Small size for gestational age (SGA) and large size for gestational age (LGA) are important risk factors for adverse perinatal outcomes and death . ChildreWe hypothesized that compared to population charts, customized charts can better identify newborns at risk of long-term adverse health outcomes. We examined in a population-based prospective cohort study among 6052 newborns the associations of SGA and LGA based on both customized and population charts for identification of newborns at risk of adverse growth patterns, cardio-metabolic, and respiratory risk factors in childhood.n = 246), participants without information on weight and gestational age at birth or maternal characteristics needed to generate customized charts (n = 2004), and children without long-term outcomes available (n = 577). The population for analysis comprised 6052 mothers and their children  participants. Catch-up and catch-down growth for weight was defined as an increase or decrease of > 0.67 SD of weight from birth to 12 months of age . This ch2. Children were scanned using a 3.0 Tesla MRI  using standard protocols [2 from the central portion of the hepatic volume. Liver steatosis was defined as liver fat fraction ≥ 5.0%. Blood pressure was measured four times in supine position, with 1-min intervals at the right brachial artery using the automatic sphygmomanometer Datascope Accutor Plus  [At the age of 10 years, children were invited for detailed measurements. We measured height and weight without shoes and heavy clothing. We calculated sex- and age-adjusted childhood BMI SDS based on Dutch reference growth charts  and categorized BMI into normal, overweight, and obesity using the definition of Cole et al. , 19. Totrotocols . Visceramus, NK) . The meamus, NK) . Non-fasmus, NK) . For clumus, NK) .1), forced vital capacity (FVC), FEV1:FVC, and forced expiratory flow after expiring 75% of FVC (FEF75) were measured by spirometry  CareFusion Netherlands) [Forced expiratory volume in the first second (FEVerlands) . Measureerlands) . Asthma First, each newborn was classified into birth weight categories using both customized and population classifications. Descriptive data of birth weight categories were compared. Second, the percentages of newborns reclassified as SGA or LGA by customized charts only or population charts only were assessed and population characteristics were compared using one-way ANOVA for continuous and chi-square test for categorical variables. Third, we assessed the associations of SGA and LGA at birth according to both customized and population charts with adverse outcomes using linear and logistic regression models for continuous and categorical outcomes, respectively. Non-normally distributed variables were log-transformed, and SDS were calculated. For categorical outcomes, we calculated prevalences of adverse outcomes among SGA, AGA, and LGA newborns, by dividing the number of cases by the number of newborns in each birth weight category. Finally, we assessed the predictive performance of both classifications for the prediction of the risk of long-term adverse health outcomes among SGA and LGA newborns by calculating receiver operating characteristic (ROC) curves, the corresponding area under the curve, and sensitivity at a 90% specificity. We did not adjust our analyses for potentially confounding maternal characteristics, as customized classification already considers maternal characteristics and we were interested in comparing the classifications. All analyses were performed using the Statistical Package of Social Sciences version 24.0 for Windows .Table Table Based on customized charts, newborns classified as SGA had a higher risk of infant catch-up-growth compared to newborns classified as AGA (odds ratio (OR) 5.15  4.22 to 6.29), Fig. Compared to newborns classified as AGA, newborns classified as SGA using customized charts had higher risks of high childhood blood pressure (OR 2.05 (95% CI 1.55 to 2.72)) and clustering of cardio-metabolic risk factors (OR 1.66 (95% CI 1.18 to 2.34)). They also tended to have higher risk of childhood overweight (OR 1.24 (95% CI 0.95 to 1.60)), hyperlipidemia (OR 1.25 (95% CI 0.88 to 1.79)), and liver steatosis (OR 1.77 (95% CI 0.88 to 3.54)), but these findings did not reach statistical significance (Fig. Results presented in the supplementary materials show associations of birth weight using both customized and population classifications with continuously measured blood pressure, lipid, glucose and insulin concentrations, and lung function (Additional file Our findings suggest that newborns born SGA have increased risks of an adverse cardio-metabolic profile at school age. Newborns born LGA have an increased risk of catch-down growth. Similar associations were present for classifications using customized charts and population charts, which suggests that customized charts are not superior to population charts at identification of SGA newborns at increased risk of adverse cardio-metabolic and respiratory outcomes at later age.Birth weight is a strong determinant of neonatal health and health in later life . Both exPrevious studies mainly focused on the effects of customization on selecting newborns at risk for adverse perinatal outcomes. A meta-analysis including 20 studies comparing the effectiveness of customized versus population charts for prediction of adverse perinatal outcomes has shown similar effect estimates for associations of abnormal size at birth with intra-uterine fetal demise, neonatal intensive care unit admission, and neonatal and perinatal death . A recenThere are several reasons why we might not observe strong differences in risks of long-term adverse outcomes between birth weights classified using customized or population charts. First, current customized birth weight charts have been criticized as they might not yet capture growth potential well enough to truly differentiate between pathologically and constitutionally SGA and LGA newborns , 31. ThiBased on the findings in our study and the fact that population charts are easier to use and widely implemented, we would not recommend implementation of customized birth weight charts for identification of newborns at risk of long-term adverse health outcomes.. Blood sample collection was performed in a non-fasting state at different time points in the day. Since glucose and insulin levels are sensitive towards carbohydrate intake and vary during the day, this may have led to non-differential misclassification and an underestimation of the observed effect estimates.We had a prospective data collection from early pregnancy onwards and a large sample of 6052 newborns available with detailed childhood growth, cardio-metabolic, and respiratory measurements. Loss to follow-up could have reduced statistical power and led to biased effect estimates if associations differ between children included and not included in the analysis. We do not think this poses a problem within our study, as the aim of our study was to compare two classification methods. The non-response at baseline might have led to selection of a healthier population, which might affect the generalizability of our results to higher-risk populations. In clinical practice, often sex-specific population charts are used to classify abnormal size at birth weight. Given the aim of our study to specifically assess the effect of customization by major determinants of fetal growth, we constructed a population chart which included gestational age only to enable the most optimal comparison. By including fetal sex in the population chart, we could underestimate the effect of customized charts, as fetal sex is one of the major physiological determinants of fetal growth. If we had included fetal sex in our population charts, we expect similar or even weaker differences between the associations of abnormal size at birth with the risk of long-term adverse outcomes according to customized charts and population charts. Which maternal factors should be included in the customized charts also remains debatable. We included the pathological variable maternal smoking in the construction of the model to obtain a better fitted model. For the construction of a customized growth chart, the term for smoking was set to zero, whether the pregnant woman smoked or not, and thereby, non-smoking was used as reference category within our customized model for all women. This approach still allowed us to detect pathological fetal growth restriction due to maternal smoking during pregnancy. A similar approach may also be used for other pathological variables and further improve customized charts. Further studies are needed to explore whether customized charts which consider more maternal factors improve the classification of size at birthSGA newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of use of customized or population birth weight charts. Our results suggest that customized charts are not superior to population charts at selecting newborns at risk of adverse childhood growth, cardio-metabolic, and respiratory outcomes. Based on these findings, we do not recommend implementation of customized charts for selection of newborns at risk of long-term adverse outcomes.Additional file 1: Figure S1. Population for analysis. Table S1. Maternal and birth characteristics of SGA and LGA newborns by population charts only compared to newborns classified SGA or LGA by both classifications. Table S2. Predictive power of customized and population charts for long-term adverse outcomes. Table S3. Body composition and blood pressure at 10 years among newborns classified SGA or LGA by customized and population charts. Table S4. Cholesterol, triglycerides, insulin and glucose at 10 years among newborns classified SGA or LGA by customized and population charts. Table S5. Measures of lung function at 10 years among newborns classified SGA or LGA by customized and population charts.Additional file 2. STROBE statement.


MH 1.53 (95% CI: 1.01–2.34) and 2.43 (95% CI: 1.27–4.66). Our study suggested that the longer duration of FA supplementation before pregnancy might increase the risk of GDM, but decrease the risk of SGA birth. Longer duration of FA supplementation during pregnancy had beneficial effects on birth outcomes in women with GDM. Further studies should consider a larger sample size to confirm these findings.This study aimed to examine the associations between the duration of folic acid (FA) supplementation, gestational diabetes mellitus (GDM), and adverse birth outcomes. A total of 950 mother-offspring pairs participated in the cohort study during 2015 in Changsha, China. The data were collected through home visits and perfected by maternal and child healthcare handbooks. Generalized linear models and stratified analyses were used for statistical analyses. The incidence of GDM in our cohort was 10.2%. FA supplementation for ≥3 months before pregnancy was associated with an increased risk of GDM (adjusted relative risk (aRR): 1.72; 95% CI: 1.17–2.53) and decreased risk of small-for-gestational-age (SGA) birth . In the group of FA supplementation for ≥3 months during pregnancy, GDM was associated with an increased risk of cesarean delivery  and macrosomia , but the aRRs were lower than the RR Folic acid (FA) is a water-soluble B vitamin. During pregnancy, FA supplementation is required to increase the expansion of maternal blood volume and growth of the fetus . In addin = 3474), daily FA supplementation, during early pregnancy, increased the risk of GDM [n = 326) showed that women who did not take FA and took FA for > 90 days had a higher incidence of GDM compared with those who took FA for ≤60 days [n = 4353) showed that FA supplement use ≥800 µg/day from pre-conceptional ≥4 weeks until ≥16 weeks during pregnancy was associated with higher GDM risk compared with non-users [However, recent evidence has revealed the associations between FA supplementation and gestational diabetes mellitus (GDM) among pregnant women. In a Chinese cohort study . These mother-offspring pairs were recruited for the cohort. The cohort study was approved by the Independent Ethics Committee of Clinical Pharmacology Institute, Central South University, Changsha, China (Project number: CTXY-130041-3-2). Additional details of the cohort study were published previously . The incTrained investigators used a self-designed questionnaire with 60-items to interview mothers by means of home visits. Information about sociodemographic, maternal nutritional, lifestyle, medical factors, and neonatal anthropometric measures were collected through home visits at 1 month postpartum. The records from CHMIS, and maternal and child healthcare handbooks, which recorded the results of the antenatal examination and neonatal birth information, were used for checking and supplementing. The calculation of the sample size was based on the requirements for the cohort studies of disease . AccordiInformation on the use of FA supplements was provided by questioning during the interview, including the initiation and ending time of FA supplementation , dose, frequency of use, and supplements brand name. Here FA supplementation included taking exclusive FA supplements and FA-containing multivitamins. The duration of FA supplementation was classified into two groups: <3 months and ≥3 months ,17. Not Pregnant women underwent a fasting blood glucose test or 75 g oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups criteria , if pregThe adverse birth outcomes included cesarean delivery, pre-term birth, early term birth, macrosomia, LBW birth, LGA birth, and SGA birth. Pre-term birth was defined as delivery before 37 gestational weeks, and early term birth as delivery before 39 gestational weeks. The gestational week was calculated from the first day of the last normal menstrual period. Macrosomia was defined as birth weight ≥4000 g and LBW birth as <2500 g. LGA birth was determined as birth weight above the 90th percentile for a specific gestational age, and SGA birth as below the 10th percentile, based on a global reference for fetal-weight and birthweight percentiles, published in 2011 . Birth w2), parity (primiparous or multiparous), iron supplementation (yes or no), multivitamin supplementation (yes or no), gestational dietary intake (≥3 times a week or <3 times a week), passive smoking (yes or no), alcohol use (yes or no), gestational hypertension (yes or no), and gestational anemia (yes or no). BMI was categorized into four levels: <18.5 kg/m2 (underweight), 18.5–23.9 kg/m2 , 24–27.9 kg/m2 (overweight), and 28 kg/m2 (obese), which was based on the recommendations from the Working Group on Obesity in China [The potential confounding variables were identified from previous studies ,6,7,12. in China . BMI wasThe data were presented as frequency and percentage, since all variables and outcomes were categorical variables. The differences in maternal characteristics between two groups of the duration of FA supplementation (<3 months and ≥3 months) were compared using the chi-square test. The differences in infant characteristics between GDM and non-GDM group were also compared using the chi-square test.Generalized linear models were used to assess the risk of FA supplementation for ≥3 months on GDM, compared with FA supplementation for <3 months. The distribution was specified as “binomial” and the link function as “log”. Relative risk (RR) and corresponding 95% confidence intervals (CIs) quantified the extent of risks. The potential confounders included maternal age, education, average monthly household income, postpartum BMI, parity, passive smoking, family history of diabetes, iron supplementation, multivitamin supplementation, gestational dietary intake, and alcohol use. We assessed the interaction between the duration of FA supplementation and multivitamin supplementation on GDM . GeneralThe stratified analyses were conducted to identify whether the duration of FA supplementation was a confounder, or an effect modifier in the associations between GDM and adverse birth outcomes. The Breslow-Day test was used to assess the homogeneity of the RRs in the two duration groups of FA supplementation. The Mantel-Haenszel chi-square test was used to estimate the associations between GDM and adverse birth outcomes, after adjusting for the duration of FA supplementation. It can compute a weighted average of the RRs across the two duration groups of FA supplementation.p-value < 0.05 was regarded as statistically significant. All statistical analyses were performed using IBM SPSS Statistics, version 22.0 .The missing values were estimated by the multiple imputation methods, which can reduce bias and increase precision and is recommended as a routine practice . A two-tOur study included 950 mother-offspring pairs, after excluding 265 infants who did not have health care records in the CHMIS, 45 mothers who refused to participate, 25 multiple births, and 1 mother who had diabetes before pregnancy.p = 0.008) and took iron supplements (p = 0.008 and p = 0.003) were more likely to take FA supplements for ≥3 months both before, and during, pregnancy. In addition, women who had a higher monthly income (p = 0.005) were more likely to take FA supplements for ≥3 months during pregnancy. Women who used multivitamin supplements (p = 0.004) were more likely to take FA supplements for ≥3 months before pregnancy. The sample with missing data and those estimated by multiple imputations had similar maternal characteristics according to the duration of FA supplementation (see tion see .p = 0.045) and macrosomia (p = 0.006). The rates of infant gender, pre-term birth, early term birth, LBW birth, LGA birth, and SGA birth, were similar between GDM and non-GDM group.MH 1.53 (95% CI: 1.01–2.34), which was higher than the cRR . In the group of FA supplementation for ≥3 months during pregnancy, GDM was associated with an increased risk of cesarean delivery with aRR 1.36 (95% CI: 1.06–1.75), which was lower than RRMH.MH 2.46 (95% CI: 1.28–4.73) and 2.43 (95% CI: 1.27–4.66), which were both higher than the cRR 2.24 (95% CI: 1.27–3.97). In the group of FA supplementation for ≥3 months before pregnancy, GDM was associated with an increased risk of macrosomia with cRR 2.56 (95% CI: 1.04–6.29). But the association was not statistically significant in the adjusted analysis. Likewise, in the group of FA supplementation for ≥3 months during pregnancy, GDM was associated with an increased risk of macrosomia with aRR 2.11 , which was lower than RRMH. In the analyses stratified by duration of FA supplementation, we did not observe that GDM was significantly associated with pre-term birth, early term birth, LBW birth, LGA birth, or SGA birth.In the analyses stratified by duration of FA supplementation before pregnancy and during pregnancy, GDM was associated with an increased risk of macrosomia with RROur study suggested that FA supplementation for ≥3 months before pregnancy was associated with a higher risk of GDM and lower risk of SGA birth, but during pregnancy was not. FA supplementation for ≥3 months, during pregnancy, might decrease the effect of GDM on cesarean delivery and macrosomia. These associations remained statistically significant after adjusting for potential confounders.In our cohort, the FA supplementation rate was 98.6%. A high FA supplementation rate among Chinese women has previously been reported. In 2015, approximately 93.1% of 1,921 pregnancy women used FA supplementation in Tianjin, China . Our stuOur results showed that FA supplementation for ≥3 months before pregnancy increased the risk of GDM, compared with FA supplementation for <3 months. In another Chinese study , women wIn our study, we found that FA supplementation for ≥3 months before pregnancy decreased the risk of SGA birth. Two cohort studies and one literature review both showed that pre-conceptional FA supplementation was significantly associated with a reduced risk of SGA birth, compared with no FA supplementation ,12,38. AOur results showed that FA supplementation for ≥3 months during pregnancy might decrease the effect of GDM on cesarean delivery. The reviewed literature suggested that multiple-micronutrient supplementation, with iron and FA, was not associated with cesarean delivery . So far,In our study, we found that FA supplementation for ≥3 months during pregnancy might decrease the effect of GDM on macrosomia. In a birth cohort study, the continued FA supplementation with 400 µg/day, in the second and third trimesters of pregnancy, significantly increased the risk of LGA birth, compared with FA supplementation only in the first trimester . But it The biological mechanism by which FA supplementation for ≥3 months during pregnancy may decrease the effect of GDM on cesarean delivery and macrosomia is unclear. The main explanation focuses on the relationship of FA supplementation and GDM on birth weight. We make the following two hypotheses. First, continuing FA after the first trimester of pregnancy can increase maternal and cord blood folate status and lead to a lower homocysteine concentration , which iIn our study, we did not observe that FA supplementation for ≥3 months before pregnancy significantly decreased the effects of GDM on any adverse birth outcomes after adjusting for potential confounders. There are two possible explanations in this case. Firstly, the sample size and the number of positive results in our study is not large enough to reveal the true effects of GDM on adverse birth outcomes, stratified by the duration of FA supplementation. Secondly, the duration of FA supplementation before pregnancy did not actually affect the relationships between GDM and adverse birth outcomes. At present, little is known about the effects of duration of FA supplementation before pregnancy on GDM and infant birth outcomes. In a prospective cohort study, pre-conceptional FA supplementation was inversely associated with the risk of pre-term birth and SGA birth . A cohorOur study has several strengths. First, the study was a prospective birth cohort, which decreased the influence of selection or recall bias. We excluded mothers with mental illnesses or brain diseases and infants with multiple births, avoiding information bias. We used maternal and child healthcare handbooks to check and supplement the collected data, minimizing the risks of recall bias. Second, we collected enough data, including all kinds of confounding factors in the adjusted analyses, obtaining the real effect of duration of FA supplementation on GDM and adverse birth outcomes. Third, the incidences of FA supplementation, GDM, cesarean delivery, and macrosomia in our study were almost consistent with other regions in China ,32,33,34Several limitations are present in this study. First, the known associations between GDM and other adverse birth outcomes, such as pre-term birth and LGA birth, cannot be assessed possibly due to smaller sample size and insufficient power in our study. Second, we did not measure the serum concentration of FA before pregnancy or early in pregnancy. Higher FA level in serum was associated with a higher risk of GDM and lower risks of adverse birth outcomes ,52. ThirThe study clarified the potential risk of longer duration of FA supplementation, which is significance for pregnant women and fetuses. The longer duration of FA supplementation before pregnancy might increase the risk of GDM, but decrease the risk of SGA birth. Longer duration of FA supplementation during pregnancy had beneficial effects on birth outcomes in women with GDM. Further studies should consider a larger sample size to confirm these findings.


Preterm birth has previously been linked with cardiovascular disease (CVD) in adulthood. However, associations with lipid disorders , which are major risk factors for CVD, have seldom been examined and are conflicting. Clinicians will increasingly encounter adult survivors of preterm birth and will need to understand the long-term health sequelae. We conducted the first large population-based study to determine whether preterm birth is associated with an increased risk of lipid disorders.P < 0.001). Relative to full-term birth , the adjusted HR associated with preterm birth (<37 weeks) was 1.23 , and further stratified was 2.00  for extremely preterm (22–27 weeks), 1.33  for very preterm (28–33 weeks), and 1.19  for late preterm (34–36 weeks). These findings were similar in men and women . Co-sibling analyses suggested that they were substantially though not completely explained by shared genetic or environmental factors in families. The main study limitation was the unavailability of laboratory data to assess specific types or severity of lipid disorders.A retrospective national cohort study was conducted of all 2,235,012 persons born as singletons in Sweden during 1973 to 1995 (48.6% women), who were followed up for lipid disorders identified from nationwide inpatient, outpatient, and pharmacy data through 2016 (maximum age 44 years). Cox regression was used to adjust for other perinatal and maternal factors, and co-sibling analyses assessed the potential influence of unmeasured shared familial  factors. A total of 25,050 (1.1%) persons were identified with lipid disorders in 30.3 million person-years of follow-up. Each additional 5 weeks of gestation were associated with a 14% reduction in risk of lipid disorders  in adulthood, but associations with lipid disorders (major risk factors for CVD) have been conflicting.Clinicians will increasingly encounter adult survivors of preterm birth and will need to understand the long-term health sequelae.In a cohort study of 2.1 million adults, preterm birth  and extremely preterm birth (22–27 weeks) were associated with 1.2- and 2.0-fold risks of lipid disorders in early- to midadulthood, compared with full-term birth (39–41 weeks).These findings were substantially but not completely explained by shared genetic or environmental factors in families.Persons born prematurely may need early preventive evaluation and long-term monitoring for lipid disorders to reduce their future CVD risks. Preterm birth  affects 11% of all births worldwide , 3, and The few prior studies of preterm birth in relation to lipid disorders have yielded discrepant findings. The largest study to date assessed plasma lipid levels in a British cohort of 7,847 adults aged 44 to 45 years and reported a modest inverse linear association between gestational age at birth and total cholesterol levels among women only . HoweverTo address these knowledge gaps, we conducted a national cohort study of more than 2 million adults in Sweden. The goals of this study were to examine associations between gestational age at birth and risk of lipid disorders at ages 18 to 44 years, the maximum follow-up currently possible in this large cohort, to assess whether these associations differ according to sex or fetal growth, and to explore for potential confounding by shared familial  factors using co-sibling analyses.The Swedish Birth Registry contains prenatal and birth information for nearly all births nationwide since 1973 . Using tGestational age at birth was identified from the Swedish Birth Registry based on maternal report of last menstrual period in the 1970s and ultrasonography estimation starting in the 1980s and onward. This was analyzed alternatively as a continuous variable or categorical variable with 6 groups: extremely preterm 22–27 weeks), very preterm (28–33 weeks), late preterm (34–36 weeks), early term (37–38 weeks), full term , and post term (≥42 weeks). Early-term birth was examined as a separate category because it has previously been associated with increased cardiovascular- and endocrine-related mortality relative to later-term birth , 22. In –27 weeksThe study cohort was followed up for lipid disorders from age 18 years through the end of follow-up in 2016 (maximum age 44 years). Lipid disorders were defined based on either of the following: (1) International Classification of Diseases (ICD) codes for lipid disorders ; or (2) prescription of lipid-modifying medications  without a concurrent diagnosis of IHD . ICD codes were identified from all primary and secondary diagnoses in the Swedish Hospital and Outpatient Registries. The Swedish Hospital Registry contains all primary and secondary hospital discharge diagnoses from 6 populous counties in southern Sweden starting in 1964, and with nationwide coverage starting in 1987; these diagnoses are currently >99% complete, and their positive predictive value for most chronic disorders has been reported to be 85% to 95% . The SweOther perinatal and maternal characteristics that may be associated with gestational age at birth and lipid disorders were identified using the Swedish Birth Registry and national census data, which were linked using an anonymous personal identification number. The following were included as adjustment variables: birth year , sex, birth order , maternal age at delivery (continuous), maternal education level , maternal birth country or region , maternal body mass index , and maternal history of lipid disorders . In a secondary analysis, further adjustment was made for fetal growth , to assess the association between gestational age at birth and lipid disorders independently of fetal growth.Maternal BMI was assessed at the beginning of prenatal care starting in 1982 and was available for 38.8% of women. Data were >99% complete for all other variables. Missing data for each covariate were imputed using a standard multiple imputation procedure based on the variable’s relationship with all other covariates and lipid disorders . The anan = 131,492; 5.9%) or death as identified in the Swedish Death Registry . Analyses were conducted both unadjusted and adjusted for covariates (as above).Cox proportional hazards regression was used to compute hazard ratios (HRs) and 95% CIs for associations between gestational age at birth and lipid disorders at ages 18 to 44 years. Attained age was used as the Cox model time axis. Individuals were censored at emigration as determined by absence of a Swedish residential address in census data . This approach can help further elucidate whether associations observed in the primary analyses are related to direct effects of preterm birth as opposed to shared genetic or environmental factors that may predispose to both preterm birth and lipid disorders. These analyses used stratified Cox regression with a separate stratum for each family as identified by the mother’s anonymous identification number. In the stratified Cox model, each set of siblings had its own baseline hazard function that reflects the family’s shared genetic and environmental factors, and thus associations between gestational age at birth and time to diagnosis of lipid disorders were examined within families, controlling for their shared factors. In addition, these analyses were further adjusted for the same covariates as in the primary analyses.Co-sibling analyses were performed to assess for potential confounding by unmeasured shared familial  factors among individuals who had at least one sibling  or those without . In a post hoc meta-analysis, risk estimates from a standard analysis of persons without siblings and from the co-sibling analysis were pooled using the inverse-variance method In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers. http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. 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Please see our author guidelines for more information: "was associated" at line 303; "need" seems too strong at lines 41 and 309remove page numbers from STROBE checklist – this should be sections and paragraphs, as they can change during page layout. Causal language – Line 274 – “have several clinical implications” as this is not a trial and an observational study, please tone down causal, overheated language – for example, ‘may have’; also Line 275 “should” replace with ‘may’ and again “should be recognized as a risk factor”…’may be taken into account when considering’ ….Please adjust throughout where such language occurs. Comments from the reviewers:Reviewer #1: See attachmentMichael DeweyReviewer #2: The authors examined longitudinal associations of preterm birth with a risk of developing lipid disorders in young adulthood (age 18-44). This study is unique and highlighting the potential of shaping a national database into a birth cohort for research on adult-onset diseases. However, the strength of clinical implications was challenging to judge, and there are several concerns. The reviewer is providing main and minor comments hereafter.Major comments: 1. The authors defined "lipid disorders" using ICD codes. The codes included ICD-8/9: 272 and ICD-10: E66. The latter includes the followings:E66 Overweight and obesity- E66.0 Obesity due to excess calories - E66.1 Drug-induced obesity- E66.2 Morbid (severe) obesity with alveolar hypoventilation- E66.3 Overweight- E66.8 Other obesity- E66.9 Obesity, unspecifiedICD-10 E66 is for obesity or overweight, not for lipid disorders. It may be uncommon for adults <44 years go to a clinic just because they are overweight or obese. So, the observed low risk of being recorded with "E66" would make sense. The authors should check back what information the authors extracted. If the authors had used E66 literally, the authors should revise it to study lipid disorders as the authors aimed and redo all the analysis.1. The validity of the longitudinal analysis is unclear or not identifiable. The authors evaluated lipid disorders at ages 18-44 years as "lipid disorders in adulthood". Therefore, the authors should not count any lipid disorders before participants became 18 years old. Also, there is a possibility that a lipid disorder occurred during a fetal period and caused a preterm delivery. It is not clear how the authors treated those individuals who developed such a fetal, infantile, or juvenile lipid disorder. The authors are describing that one of the inclusion criteria for this cohort was "still living in Sweden at age 18 years". This description did not rule out the possibility that entry of adolescents with a lipid disorder into the cohort.The authors should confirm and clarify that the authors had evaluated participants who were free from a lipid disorder at the age of 18 years. If the authors were not sure, the authors should do additional analyses, for example, excluding those who were treated at least once with lipid-lowering drugs during 18-20 years of age. Sipola-Leppanen et al. reported the association of preterm delivery with unfavourable lipid profiles in adolescents :e1072-81). Other studies exist sufficiently to raise the concern about censoring and the risk set in this study.2. The clinical relevance may be much weaker than the extent which the authors are describing. This point may be crucial and should not be discussed just as a limitation or weakness in the Discussion. Analysis should deal with it.We should note that lipid disorders in this manuscript were those developed before the age of 44 years as the primary outcome. The average incidence rate was approximately 0.1% (100/100000) (Table 2). The clinical implications for such a rare event may require the focus on many possible rare conditions in childhood.The concern is about secondary dyslipidemia. Many children or young adults may have experienced an onset of respiratory disease, dermatological disease, an endocrine disorder, or another. They might receive medications which influence lipid homeostasis and induce secondary dyslipidemia :961-968). For participants treated with other medications for their primary disease, lipid profiles are subject to monitoring and treatment. For clinicians who often face secondary dyslipidemia anyhow, this paper may not be informative, and the authors may not need to highlight the importance. This point partly relates to the comment above about a lipid disorder or any other diseases arising before aged 18 years. The authors should account for this plausibility over the course from the analysis stage (see the other comments) to the interpretation and discussion. The authors discuss clinical implications on Page 13. This part may represent what paediatricians already know. Birth outcomes, including preterm delivery, may influence a child-onset disease that requires a particular medication and the medical condition further influences lipid profiles and further cardiovascular health in later life. If that is a causal pathway, the authors' implication would require revision.In addition to secondary dyslipidemia, preterm birth may relate to a growth spurt and later obesity or overweight. Concerning the obesity issue, physicians commonly pay attention to preterm birth and childhood obesity. Then, lipid disorders and other cardiometabolic outcomes may get concerning reasonably. Regarding many correlated issues and causal pathways, clinicians may have already recognised the importance of preterm delivery for cardiovascular risk factors, not only lipid disorders. From this broad view, again, the clinical implication of this study seems to be weak. The authors need to account for related, well-known issues which pediatricians have already know.3. The authors state the availability of primary and secondary diagnoses (Line 94-108). The authors seem to be able to identify different types of medications, not only lipid-lowering medications.Therefore, the authors should address the concern of secondary dyslipidemia above raised. Note that some observational studies using an extensive medical database have incorporated as much information as possible, including different types of medications and clinical diagnoses . The similar effort would be crucial.4.Co-sibling analyses are unique and informative for readers. Future readers will be careful of the potential of using a national database containing similar types of information.The authors described that the sample size of the co-sibling analysis was approximately 80% of the total number of participants. The authors should explain or revise those participants fully contributed to the co-sibling analysis. For example, if one family has two siblings, and if both did not develop lipid disorders, the within-family matched analysis would not use them. With the rarity of the events, effective sample sizes of the co-sibling analyses might be much smaller than those presented. The authors should verify and clarify it. (note: the continuous estimate in Table 3 had nearly five times greater variance than that in Table 2.)The authors' interpretation from the co-sibling analyses seems to be valid, but at the same time, the authors may want to describe the nature of the uncertainty as well.Minor comments: Table 2 and Table 3 do not need to show the results after sex-stratification. The results by sex were unremarkable. There is no clear, strong rationale or hypothesis to indicate the effect modification by sex. Also, equivalent and additional pieces of information are available in the supplementary materials. In both Table 2 and Table 3, the authors should include hazard ratios  from different regression models. Unadjusted HRs are worth presenting. Changes in HRs via different adjustments could be meaningful to present . "Preterm or not" showed unadjusted HR=1.32 and adjusted HR=1.23. The shift is informative about mechanisms of the complex association of early-life environment with lipid disorders recorded in later life.For the analysis treating gestational age as a continuous variable, the authors may better use hazard ratio per 5 weeks. One week is of a too narrow range given the distribution of the gestational ages, and the point estimates were not informative. The point estimates and 95% CIs in Table 2 and Table 3 were informative enough for some readers to calculate p-values. The authors may better avoid inconsistent presentation between Table 2 and Table 3 .Methods:The reviewer wonders if the information on C-section was available.Results:Some text, Page 10 in particular, was hard to read. Readers expect to read results, not descriptions of the methods, rationales, and interpretations. Those should be in Methods or Discussion. The authors should document what results were from which analysis.The results of the co-sibling analyses should include information on the number of families, not only individual adults.Line 201-204: The text seems that the authors are obsessed with statistical significance. "slightly lower" is just fine with p for interaction = 0.41. Not wrong. The next sentence should be in the Discussion section.Line 206-213: The authors should note the analysis of within-family carryover effects in Methods. Then, the sample size should be clarified. This analysis must have included families with discordant outcomes in their siblings only. The authors should not use the phrase "case-crossover" as it is confusing and should correspond to a particular study design which the authors did not adopt.In the Discussion, the authors cited information on genetic factors influencing both timing of delivery and lipid disorder in an offspring. The authors bind this to the finding just once in the Discussion. Figures/Tables:Figure 1 should not include the label of 0.00 as 0.00 is not possible. Also, the authors should provide each point estimate and 95% CI on the right of the panel. The horizontal axis covers a too wide range of HRs, and then uncertainty (CIs) give a false impression of narrow ones. Present the range up to 2.5 rather than 3.0 and use an arrow to the right. The reviewer reserves other minor comments at this moment.Reviewer #3: This work reveal important associations between how gestational lengths may effect serious complications later in life, lipid disorders, which is the underlying cause of cardiovascular diseases in adults. This knowledge is important for understanding how diseases arise and but could also be important for clinicians to recognize early risk factors in patients and encourage life style changes in reducing the risk of diseases to improve public health. The paper is well written. The research presented in the paper is of good quality and is scientifically sound. I have only some minor comments:1. In the abstract line 2, it would be interesting to know what type of disorders you are referring too, if word counts accept this. 2. Line 26, comment on type of cohort study, a retrospective design?3. Line 27, why did you choose this time period? Many cases are still young. Would it be easier to see associations in older age groups? Later in the manuscript I did understand that you choose this period because of the registry and no data was accessible before this time period. If you had access to data from older age groups, how do you think this would have affected the results? 4. Line 34, why did you use full-term birth only gestational week 39-41?5. Line 50, again a short introduction about what type of lipid disorders you are referring to. 6. Line 86, gestational length is collected from both last menstruation period and ultrasound. How do you this this affects the results in the study?7. Line 114. Some covariates are missing e.g. smoking, physical activity and diet. How do you think this would impact the results if they were available? 8. In the discussion part you are presenting some studies that has looked at specific lipids as for example triglycerides. Triglycerides are more of a risk factor for CVD in women. Was it not possible to analyze from the Registry? 9. Why did you choose Cox regression model?Overall, the paper is presenting convincing research results and I believe it is a good candidate for being published in PLOS Medicine.Any attachments provided with reviews can be seen via the following link:[LINK]Attachmentcrump.pdfSubmitted filename: Click here for additional data file. 12 Aug 2019AttachmentCrump_Response_to_Reviewers_PLOS_Med.docxSubmitted filename: Click here for additional data file. 29 Aug 2019Dear Dr. Crump,Thank you very much for submitting your manuscript "Preterm Birth and Risk of Lipid Disorders in Early Adulthood: A Swedish Cohort Study" (PMEDICINE-D-19-01959R1) for consideration at PLOS Medicine. Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:[LINK]In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers. http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. 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For instructions see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it. Please ensure that the paper adheres to the PLOS Data Availability Policy  involved bias because the authors assumed that all the observations were independent while those within the same families were not independent.The reviewer suggests the authors do the followings:1) conduct the co-sibling analysis .2) do the standard analysis of participants without any siblings , and3) meta-analyze the two estimates. Each output from these three analyses  is worth presenting. The authors may do after stating that it is post hoc.Minor comments:In the description of the co-siblings data, the reviewer suggests that the authors clarify that they examined the association of gestational ages at birth with time to events within the family. It would be difficult to understand what the authors stated, "comparisons of different gestational ages at birth are made within the family." The reviewer suggests the authors not to state "fully adjusted" . Observational studies cannot make "full" adjustment without perfect randomization. The authors should rephrase it to mean that they did the best effort over the availability of their data, saying "most adjusted" or something similar.Line 241-245: the authors should move this part to Methods. If the authors want to re-emphasize what the analysis would mean, the authors may state it in a phrase. Then, the sentence could be: "In co-sibling analyses controlling for unmeasured shared genetic or environmental factors within families, all risk estimates were substantially attenuated (Table 3) in comparison to the primary results."Line 249-251: The authors should move this interpretation to Discussion.Likewise, redundant information across Methods, Results, and Discussion is subject to minor revisions to make the manuscript succinct.Line 372-382: The authors may better highlight that the findings were likely to be independent of secondary dyslipidemia and so on. The reviewer is now supportive of the clinical implication of this study. On the other hand, the reviewer suggests the authors acknowledge dyslipidemia in the pediatrics field or drug-induced dyspilidemia. This approach will be better, considering readers who have already been working on dyslipidemia in youths and young adults.Any attachments provided with reviews can be seen via the following link:[LINK] 6 Sep 2019Dear Dr. Crump,Thank you very much for re-submitting your manuscript "Preterm Birth and Risk of Lipid Disorders in Early Adulthood: A Swedish Cohort Study" (PMEDICINE-D-19-01959R2) for review by PLOS Medicine.I have discussed the paper with my colleagues and the academic editor and it was also seen again by reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. 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PROFILE INFORMATIONhttps://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.Now that your manuscript has been accepted, please log into EM and update your profile. Go to Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it. Best wishes, Gordon Smith, Obstetrics & Gynaecology PLOS Medicineplosmedicine.org