CHD) survival estimates are important to understand prognosis and evaluate health and social care needs. Few studies have reported CHD survival estimates according to maternal and fetal characteristics. This study aimed to identify predictors of CHD survival and report conditional survival estimates.Congenital heart disease (CHD (n=5070) born during 1985–2003 and notified to the Northern Congenital Abnormality Survey (NorCAS) were matched to national mortality information in 2008. Royston–Parmar regression was performed to identify predictors of survival. Five‐year survival estimates conditional on gestational age at delivery, birth weight, and year of birth were produced for isolated CHD . Year of birth, gestational age, birth weight, and extracardiac anomalies were independently associated with mortality . Five‐year survival for children born at term (37–41 weeks) in 2003 with average birth weight (within 1 SD of the mean) was 96.3% . Survival was most optimistic for high‐birth‐weight children (>1 SD from the mean) born post‐term  and least optimistic for very preterm (<32 weeks) low‐birth‐weight (<1 SD from mean) children .Cases of CHD survival is highly influenced by gestational age and birth weight. For prenatal counseling, conditional survival estimates provide best‐ and worst‐case scenarios, depending on final gestational age and birth weight. For postnatal diagnoses, they can provide parents with more‐accurate predictions based on their baby's birth weight and gestational age.Five‐year  Congenital heart disease (CHD) is a range of structural anomalies of the heart, which affect around 1% of births.The aim of this study is to estimate long‐term survival of individuals with CHD, born in the North of England during 1985–2003, conditioned on important determinants.The Northern Congenital Abnormality Survey (NorCAS) is a population‐based register that collects data on cases of congenital anomalies delivered to women residing in the North of England . Cases dCases with CHD  live born between January 1, 1985 and December 31, 2003 were included. Cases with a single minor CHD, for example, patent ductus arteriosus born <37 weeks' gestation, were excluded as per European Surveillance of Congenital Anomalies guidelines.Deaths before age 1 year were identified from the region's Perinatal Mortality Survey, which is linked to the NorCAS through the mother's details. The Perinatal Mortality Survey collects data on infant deaths from statutory death registrations for infants whose mothers reside in the North of England . Deaths The NorCAS has approval from the Confidentiality Advisory Group of the Health Research Authority (PIAG 2‐08(e)/2002) to hold data without consent and, at the time of study, ethics approval (09/H0405/48) to undertake research involving the data. This study was given a favorable ethical opinion by the South Tees Local Research Ethics Committee.Using a fetal growth formula, birth weight at 40 weeks gestational age was predicted for all cases .From mothers' residential postcode at delivery, the Index of Multiple Deprivation 2004 was calculated. Index of Multiple Deprivation is a measure of area‐level socioeconomic deprivation calculated from income, employment, health, education, access to services, social environment, housing stress, living environment, and crime.The following were investigated as risk factors of mortality: year of birth (continuous); maternal age at birth (continuous); extracardiac anomalies ; standardized birth weight ; gestational age at birth ; socioeconomic deprivation , infant sex ; and plurality (singleton or twin). CHD severity was coded into 4 groups , using a slightly adapted version of Khoshnood et al's coding system., averageUnadjusted and adjusted HRs were estimated using proportional hazards Royston–Parmar models, with 1 knot. Parametric models such as Royston–Parmar models differ from the traditionally used semiparametric Cox model because they directly model the baseline hazard.P<0.05 was considered statistically significant and analyses were performed in Stata software .The proportional hazards assumption was checked using log‐log plots and by comparing HRs for different categorizations of survival time. Martingale residuals were plotted against continuous variables to check that the functional form was linear. Of 5093 cases of CHD, 5070 (99.5%) had known survival status. Of these, 87.1%  survived to age 5 years, 86.7%  to age 10 years and 85.2%  to age 20 years. Of cases with isolated CHD, 91.2%  survived to age 5 years, 90.9%  to age 10 years, and 89.7%  to age 20 years.P<0.001), gestational age at birth (P<0.001), birth weight (P<0.001), extracardiac anomalies (P<0.001), CHD severity (P<0.001), maternal age (P=0.04), and plurality of pregnancy (P=0.009) were all crudely associated with survival (Table P<0.001) and 2.09  times more likely to result in mortality than term cases. Cases born post‐term were 27% less likely to result in mortality , although this was not statistically significant (P=0.22). Compared with average birth‐weight cases, low birth weight cases were at increased risk of mortality  and high birth weight cases were at decreased risk of mortality, although this did not reach statistical significance in the univariable model . For each year increase in maternal age, the risk of mortality increased by 1% . The risk of mortality was 18% lower in cases resident in the region's third least deprived areas compared with the third most deprived , although the total effect of socioeconomic deprivation was not statistically significant (P=0.11). Cases from multiple pregnancies were 1.62 times more likely to result in mortality than singletons . Cases with structural and chromosomal anomalies were at quadrupled risks of mortality .Year of birth P<0.00, gestatiP<0.001), gestational age at birth (P<0.001), birth weight (P=0.001), CHD severity (P<0.001), and extracardiac anomalies (P<0.001) remained significant in the multivariable model, although the HRs were all attenuated compared with univariable analyses (Table P=0.22), with the effect changing direction . The small increased risk of mortality associated with increasing maternal age was similar, but no longer statistically significant (P=0.10).Year of birth P<0.00, gestatiMost children with CHD were born at term with average birth weight  and only very few were both low birth weight and very preterm .Five‐year survival for a child with isolated CHD, born at term in 2003 with average birth weight, was estimated as 96.3% . This dropped to 83.1%  for very preterm births and 93.4%  for moderately preterm births, but increased to 97.3%  for post‐term births. Five‐year survival for a child with isolated CHD, born at term in 2003 with low birth weight, was estimated as 95.2%  and with high birth weight was estimated as 97.2% . Children with low birth weight born very preterm had the worst prognosis  and children with high birth weight born post‐term had the best prognosis  for a severity I CHD, 89.2%  for severity II, 99.3%  for severity III, and 98.1%  for unclassified. Survival for selected CHD subtypes conditional on birth weight and gestational age are shown in Table Year of birth, gestational age at birth, birth weight, and extracardiac anomalies were independently associated with mortality in individuals with CHD. Most children (53.7%) with isolated CHD were born at term with average birth weight. An estimated 96.3% of isolated cases born at term in 2003, with average birth weight, were alive at age 5 years. This ranged from 58.8% for children with the most severe CHD subtypes to 99.3% for the least severe. Five‐year survival was most optimistic (97.9%) for children born with high birth weight post‐term and was least optimistic (78.8%) for children born very preterm with a low birth weight.This study's main strength is the use of data from a high‐quality, population‐based register, which is notified from multiple sources to maximize ascertainment. The NorCAS is annually cross‐validated with a pediatric cardiac database at the local tertiary center. Complex cases are reviewed by pediatric pathologists and clinical geneticists, and, where relevant, diagnoses are confirmed by postmortem. NorCAS cases may be diagnosed at any age up to 16 years 12 after 2001), meaning that difficult and late diagnoses are included. However, cases born to mothers resident in the North of England that move out of the UK before diagnosis may not be picked up by the NorCAS. Given that the North of England is a very stable population with little migration, this is likely to apply to a very few cases.01, meaniWe uniquely present adjusted 5‐year survival estimates, overall, by CHD severity and by selected CHD subtypes. Existing studies typically report survival for all CHD combined, not accounting for modifying factors such as extracardiac anomalies or preterm birth. We show that these factors substantially influence survival . Adjusted survival estimates are important for health and social care planning. For prenatal counselling, they can provide best‐ and worst‐case scenarios, depending on the final gestational age and birth weight. For postnatal diagnoses, they can provide parents with more‐accurate predictions based on their baby's birth weight and gestational age.Although one of the largest studies to examine the influences of CHD survival, we still lacked power to assess uncommon features  or factors with modest effect sizes . Nonsignificant associations should therefore be interpreted with care.Simulation studies suggest that survival analysis requires a minimum of 5 to 10 events per variable for adequate statistical power.Ethnicity and parity have previously been associated with CHD mortality.Without information on cause of death, we cannot confirm whether a cardiac event was the cause of death. Mortality among cases with extracardiac anomalies may result from the coincident anomaly, rather than the CHD. However, for severe subtypes, the contribution of any additional anomalies is diminished by the CHD lethality. To provide the most widely relevant figures, we presented our adjusted survival estimates for isolated CHD only.We found that CHD survival improved over time during 1985–2003. We therefore fixed our survival estimates to the latest year of study. Survival prospects are likely to have improved since 2003, and this should be considered when interpreting our estimates. Assuming trends increased at the same rate until 2016, survival for cases born at term, with average birth weight and isolated CHD, would have increased form 96.3% to 98.7%. Similarly, survival for cases born very preterm with low birth weight would have increased from 78.8% in 2003 to 91.9% in 2016. Survival for cases born post‐term with high birth weight would have increased from 97.9% in 2003 to 99.3% in 2016.Our Kaplan–Meier survival estimate of 87.8% at age 5 years is comparable to the pooled estimate of 85% reported in our recent systematic reviewIn our study, cases with extracardiac anomalies experienced ≈4‐fold increased risk of mortality. Knowles et al and Olsen et al similarly reported that children with extracardiac anomalies were at increased risk of mortality, but with smaller effect sizes.We found that CHD survival improved over time, reflecting the findings of several other population‐based studies.We found that greater gestational age at birth was associated with improved survival. Knowles et al also reported an increased risk of mortality in preterm compared with term cases HR=1.43).3.4 We foWe found some evidence of an association between maternal age at delivery and mortality. Wang et al and Oster et al reported significantly decreased mortality in cases born to mothers respectively aged >35 years compared with 30 to 34 years HR=0.88)88 and agWe found lower survival in cases from multiple pregnancies. However, after accounting for other variables, this association was no longer significant. In our data, cases from multiple births were 10 times more likely to be preterm, 1.5 times more likely to have low birth weight, and 2.5 times more likely to have structural extracardiac anomalies. Therefore, although twins on average have poorer prognoses, a term, average‐weight twin with isolated CHD should have the same survival prospects as an equivalent singleton.We found poorer survival of children with CHD born in the most compared with the least deprived areas in the North of England. Miller et al did not find a significant association between socioeconomic position and atrioventricular septal defect survival in the USA; however, survival decreased linearly with decreasing level of deprivation.Twenty‐year survival associated with CHD was 85.2%. Year of birth, gestational age at birth, standardized birth weight, and the presence of extracardiac anomalies were associated with mortality in individuals with CHD. This information is important for health and social care planning.This work was supported by a British Heart Foundation studentship (FS/12/23/29511 to Best). NorCAS is currently funded by Public Health England.None.


Infant birth weight, which is classified into low birth weight, normal birth weight and macrosomia, is associated with short and long-term health consequences, such as neonatal mortality and chronic disease in life. Macrosomia and low birth weight are double burden problems in developing counties, such as Ethiopia, but the paucity of evidence has made it difficult to assess the extent of this situation. As a result there has been inconsistency in the reported prevalence of low birth weight and macrosomia in Ethiopia. This study aimed to determine the incidence and predictors of low birth weight and macrosomia in Tigray, Northern Ethiopia.We conducted a cross-sectional survey among a cohort of 1152 neonates delivered in Tigray Region at randomly selected hospitals between April and July 2014. We used the birth weight category described previously as an outcome variable. Data were collected using structured questionnaire by midwives. We entered and analyzed data using STATA™ Version 11.0. Data were described using a frequency, percentage, relative risk ratio, and 95% confidence interval. Multinomial logistic regression was conducted to identify independent predictors of low birth weight and macrosomia.In this study, we found a 10.5% and 6.68% incidence of low birth weight and macrosomia, respectively. Seventy (57.8%) of all low birth weight neonates were term births. The predictors for low birth weight were: early marriage (<18 year) ; rural residence ; prematurity ; no antenatal follow-up ; and female sex . Predictors for macrosomia were: female gender ; high body mass index ; post-maturity ; and no maternal complication .In this study, we found gestational age and gender of the neonate to be common risk factors for both low birth weight and macrosomia. Strengthening antenatal follow up, prevention of pre and post maturity, controlling body mass index, and improving socioeconomic status of mothers are recommendations to prevent the double burden (low birth weight and macrosomia) and associated short and long-term consequences. Birth weight is an important indicator in the prediction of short- and long-term health outcomes . Based oStudies also showed macrosomia to be associated with long-term consequences including obesity, diabetes, and heart disease –15. LBW Several maternal characteristics, such as prior history of diabetes, prolonged gestation, multiparty, older maternal age, short height, high body mass index, and significant weight gain during pregnancy are associated with an increased risk of macrosomia , 17–19. There is evidence that the risk factors for LBW, such as high risk pregnancy, extremes of age at time of pregnancy, anemia, pregnancy-induced hypertension, and poor nutritional status, are widely reported in Sub-Saharan Africa including Ethiopia , 20, 21.Findings from recent studies in Ethiopia have shown that despite the decline in infant and child mortality, neonatal mortality remains unacceptably high , 23. DesThe present study aims to measure the levels of LBW and macrosomia among women in Tigray region. In addition, the study identifies maternal and obstetric characteristics associated with the risk of LBW, and macrosomia in this setting in an effort to identify potentially modifiable factors in order to mitigate their short and long-term consequences.This study is a part of a large prospective observational study undertaken in one of the nine administrative regions of Ethiopia to investigate pregnancy outcome and neonatal survival. The current study is a cross-sectional survey of 1162 neonates-maternal dyads delivered in select hospitals between April and July 2014 in Tigray, Ethiopia. Details of sample size calculation and sampling procedure have been published previously .This study was conducted in seven randomly selected public hospitals in Tigray region, northern Ethiopia. Tigray Region is one of the 11 administrative states in Ethiopia with a total population of 5,055,999 . The Ethiopian health system is structured into a three-tier system with the primary care level comprised of health posts, health centers and primary hospitals, the secondary care level including general hospitals, and the tertiary care level of specialized hospitals. In Tigray region there are 15 public general hospitals, 1 specialized referral hospital and 20 primary hospitals, 204 health centers and 712 health posts. All general hospitals and specialized referral hospital provide comprehensive maternal and newborn services, emergency and elective caesarean sections. This study was conducted in the specialized referral hospital, and six general hospitals which were randomly selected from the 16 hospitals of the region by lottery method .Data were collected using a pre-tested structured questionnaire on 5% of the sample size to improve clarity and modify the data collection instruments and a checklist adapted from the WHO standard verbal neonatal autopsy questionnaires . The queWomen, who experienced live births in the study hospitals from April –July, 2014 were included in the study. Mothers who were unable to speak and mothers with psychiatric illnesses were excluded from the study.Considering previous evidence and the nature of our study, which includes both clinical and sociodemographic characteristics, the independent variables were broadly categorized as distal, intermediate, and proximal. Distal variables included socioeconomic and demographic factors such as: reported income ; residence [urban and rural]; age at first marriage . Intermediate factors related to maternal, neonatal, and health services included: maternal factors, such as body mass index (BMI) ; fertility (number of live children) ; antenatal follow up is defined as care or supervision given to a pregnant, parturient, peurperal woman so as to enable her to pass through the dangers of pregnancy with least possible risk. It was categorized into ; neonatal factors such as birth weight [measured using a standard beam balance within one hour of delivery], gender [female/male], gestational age  of LBW neonates and of macrosomia neonates [16(20.6%)] were delivered in Ayder  and Suhl  hospitals, respectively. Maternal residence indicated 755(65.5%) resided in the urban settings and the remaining numbers resided in the rural areas. Of these, the highest proportion of 62 mothers (51.2%) of LBW neonates were delivered by rural mothers, while 54 mothers (70.1%) of macrosomic neonates were from urban mothers (Table (Table One in every 10 live births (10.5%) was underweight 121/1152), and 6.7% (77/1152) were macrosomic, while the remainder (954/1152) were within the normal range of birth weight. Considerable LBW babies [40% (49/121)] were pre-term births 1/1152, a(Table ).Regarding maternal complication, 19.2% of the mothers had complications, of which 15% related to macrosomic births and 10.4% to LBW deliveries. With regard to mode of delivery, 241(20.92%) babies were delivered by Caesarean section and, of these, 29(12%) were macrosomic neonates and 27(11.2%) preterm. Neonates showed a 1:1.12 male to female ratio. Nearly 60% (71) of LBW babies were at term On bivariable analysis, using multinomial regression, multiparty (≥5) was associated with LBW but not with macrosomia . Four in ten LBW births (40%) was preterm, which was associated with LBW  and post-term birth was significantly associated with macrosomia  ). Regarding gestational age, the risk of macrosomia was twice as high in post-term neonates compared to term babies ) and risk of LBW was fifteen times higher in pre-term neonates than in term neonates . Female neonate were found 42% less at risk of becoming macrosomic than their counterpart male neonates , but 1.77 times  more likely to experience low birth weight than their male counterparts. Similarly, mothers who had no complication around birth had a 54% lower risk of delivering macrosomia  than these mothers who had complications. Delivery complications were not significantly associated with LBW . Concerning antenatal follow-up, with relative to normal birth weight neonates mothers who never had antenatal follow-up were 6.78 times at increased risk of delivering LBW neonates compared to those who attended antenatal care .From the sociodemographic characteristics, mothers who resided in the urban area were at 47% lower risk of delivering LBW neonates than their rural counterparts .).From the intermediate factors, first marriage was significantly associated with LBW for mothers who married after 18 years and above. Specifically, they were 41% less likely to deliver LBW neonate than mothers married before the age of 18 , but marital age was not significantly associated with macrosomic birth  (Table In this study, we determined the incidence of LBW and macrosomia. We also identified the independent predictors of LBW and macrosomia on the same model.Accordingly, we found the incidence of macrosomia to be 6.7%. The rate of macrosomia is within the worldwide and range of African studies , 30. In The incidence of LBW found was 10.5% which is higher than the reported rates in developed countries and lower than the rate of some sub-Saharan African studies , 31. It Gestational age was one of the independent predictors of macrosomia and LBW. Post-maturity was significantly associated with macrosomia, which is similar to previous findings , 17. ThiMale neonates are also associated with increased risk of being macrosomic, which aligns with a previous meta-analysis conducted in 23 countries and a study in China , 18. TheMaternal complications were associated with macrosomia. This finding is supported with previous study for macrosomia , 17. In Rural residence and early marriage were also associated with delivering LBW babies, which is a similar finding to previous studies , 36–38. Having no antenatal follow up is significant predictors of LBW, which mirrors prior findings , 36, 38.The strength of this data is that it is a prospective study. In addition, our study covers the entire range of hospitals in the study region so that it will be generalizable to all Ethiopian hospitals. This study concurrently considered both LBW and macrosomia and identified the common factors, such as gestational age and gender. It is favorable to tackle both of these problems at the same time.The limitations of this study are that did not specifically study mothers with diabetes, or term births yielding low birth weight neonates, nor fully consider maternal complications owing to nature of our study. Further, this study was also conducted cross-sectionally and only in hospitals, whereby, in the study region, only 27% of mothers deliver in hospitals or another health care facility . ConsequOur study revealed that mothers with early marriage, delivery of premature neonates, lacking antenatal follow-up, bearing female neonates, and/or who had pregnancy related complications are at higher risk to deliver low birth weight neonates. In addition, mothers who delivered male neonates, had pregnancy related complications, post-maturity, and high BMI are at risk of delivering macrosomic neonates. Therefore, strengthening antenatal follow-up, improving socioeconomic status and lifestyle, promoting early detection and management of complications, enhancing early detection of prematurity and post-maturity are recommended to prevent or mitigate both low birth weight and macrosomia and their long term consequences. We also recommend longitudinal studies on the long-term consequences of low birth weight and macrosomia throughout Ethiopia.


In the United States, major structural or genetic birth defects affect approximately 3% of live births  codes 740.00–759.9. CDC did not consider the following conditions to be birth defects: 1) persistent fetal circulation (747.83) or balanced autosomal translocation in a normal person (758.4), if they were the only codes in this range recorded for the discharge; and 2) patent ductus arteriosus (747.0) or ostium secundum type atrial septal defect  if they were the only birth defect codes for preterm infants or term infants aged <28 days. For infants aged <1 year, CDC classified acquired pyloric stenosis (537.0) as a birth defect; for persons aged ≥1 year, this was not considered a birth defect. Hospitalizations that included at least one discharge diagnosis with a birth defect ICD-9-CM code meeting these definitions were considered “birth defect–associated” hospitalizations. Eligible birth defect codes found in any diagnosis field  were analyzed for all birth defects combined, for categories of birth defects broadly defined by organ system  and the payment received by hospitals (cost). CDC used the HCUP hospital-specific all-payer inpatient cost-to-charge ratio when available, or the weighted group average all-payer inpatient cost-to-charge ratio otherwise , accounting for 1.1% of total hospital costs and 22.0% of birth defect–associated hospitalization costs when all discharge diagnoses were included. Among the birth defect types examined using only the primary birth defect ICD-9-CM codes, hypoplastic left heart syndrome had the highest mean cost  and interrupted aortic arch had the highest median cost .After excluding discharges with ICD-9-CM or Diagnosis Related Group codes indicating preterm birth, the total estimated cost for birth defect–associated hospitalizations was $18,884,865,845  or 82.3% of total costs of all birth defect–associated discharges.CDC’s analysis of NIS data indicates that the annual cost of hospitalizations that included a birth defect discharge diagnosis code in 2013 was $22.9 billion. Although birth defect–associated hospitalizations accounted for 3.0% of all hospitalizations, they accounted for 5.2% of total hospital costs, highlighting the disproportionately high costs of treating patients with these conditions. The share of costs was especially high for infants, accounting for 35.0% of total hospitalization costs for children aged <1 year. Across all ages, costs were particularly high for hospitalizations associated with cardiovascular defects, which accounted for approximately 14.0% of birth defect–associated hospitalizations but 26.6% of birth defect–associated costs.In a previous analysis of 2004 HCUP data, the total cost of birth defect–associated hospitalizations was estimated at $2.6 billion (The findings in this report are subject to at least five limitations. First, use of all diagnosis codes might have overestimated costs because the coded birth defect might have been incidental to the reason for the hospitalization. Conversely, birth defects that influence conditions leading to hospitalization might be less likely to be coded as a person ages. Second, the primary analysis included preterm infants, who have higher associated hospitalization costs (By estimating the cost of birth defect–associated hospitalizations, both researchers and policy makers can be more informed of the impact of birth defects on the health care system and can use this knowledge to motivate change through prevention, early detection, and care throughout the lifespan of affected persons.Major structural or genetic birth defects affect approximately 3% of live births and are responsible for 20% of infant deaths.Analysis of 2013 hospital discharge data found that birth defect–associated hospitalizations accounted for 3.0% of all hospitalizations and 5.2% of total hospital costs. The estimated annual cost of U.S. hospitalizations that included a birth defect code among any discharge diagnosis was $22.9 billion, whereas the estimated cost based on having a primary birth defect discharge diagnosis code was $5.0 billion. When birth defects among any diagnosis code were included, but preterm delivery codes were excluded, the total estimated cost was $18.9 billion.Estimates of the cost of birth defect–associated hospitalizations offer important information on the impact of birth defects on the overall health care system and can be used to prioritize prevention measures.


Abnormalities in birth weight and gestational age cause several adverse maternal and infant out-comes. Our study aims to determine the potential factors that affect birth weight and gestational age, and theirassociation.We conducted this cross-sectional study of 4415 pregnant women in Tehran, Iran, from July6-21, 2015. Joint multilevel multiple logistic regression was used in the analysis with demographic and obstetricalvariables at the first level, and the hospitals at the second level.We observed the following prevalence rates: preterm (5.5%), term (94%), and postterm (0.5%). Lowbirth weight (LBW) had a prevalence rate of 4.8%, whereas the prevalence rate for normal weight was 92.4, and2.8% for macrosomia. Compared to term, older mother’s age , preeclampsia , multiple pregnancy , and use of assisted reproductive technology (ART)  were associated withpreterm birth. Better socioeconomic status (SES) was responsible for decreased odds for postterm birth com-pared to term birth . Cases with higher maternal body mass index (BMI) were 1.02times more likely for macrosomia (95% CI: 1.01-1.04), and male infant sex . LBWwas related to multiparity , multiple pregnancy ,and preeclampsia .Maternal age, SES, preeclampsia, multiple pregnancy, ART, higher maternal BMI, parity, and male infantsex were determined to be predictive variables for birth weight and gestational age after taking into consideration theirassociation by using a joint multilevel multiple logistic regression model World Health Organization definitions on gestational age state that a baby is preterm if born before 37 weeks of gestation, full term if born between 37 through 42 weeks, and late or postterm if born after 42 weeks from the first day of the women’s last menstrual period , 2. PretPreterm birth may result from risk factors that include multiple pregnancy, infection, advanced maternal age, short interval between pregnancies, low maternal bodymass index (BMI), poor maternal nutrition, the use of assisted reproductive technology (ART), maternal psychological health, and lifestyle . The preCurrently, abnormal gestational age is more common due to the increased rate of multiple births, use of ART, and higher numbers of obstetric interventions , 8. In Birth weight, or the first weight of a newborn baby, can be categorized as normal (=2.5 to < 4.0 kg), low (<2.5 kg), and macrosomia (=4.0 kg) . In addiMacrosomia is associated with an increased risk of cesarean delivery, prolonged labor, perinatal trauma, maternal diabetes and obesity, excessive weight gain, male infant sex, prolonged gestation, high maternal age, multiparity, and postpartum hemorrhage. Adverse outcomes of macrosomia for the infant include dystocia, birth injury, or death. In addition, these children will be at risk for diabetes and obesity later in life , 15. LBCluster data are widely recorded in medical and clinical areas where the cases are nested in clusters. For instance, students may be clustered in schools. In contrast to the traditional statistical approaches, multilevel models take the correlation among subjects in the same cluster into account , 19. RecThe detrimental outcomes after abnormalities in birth weight and gestational age are well discussed in the literature. However, regarding the association between these two variables, it is very important to predict the classes of birth weight and gestational age using their potential risk factors. Hence, the current study aims to model birth weight and gestational age jointly for the data from maternity clinic centers in Tehran province by applying a joint multilevel multiple logistic regression model.We conducted this cross-sectional study on 4415 fertile women who referred to maternity clinic centers in Tehran Province, Iran, from July 6-21, 2015. These centers are supervised by the following universities located in Tehran, Iran: Tehran University of Medical Sciences, Shahid Beheshti University of Medical Sciences, Iran University of Medical Science, and Islamic Azad University School of Medicine.The Ethical Committee of Royan Institute approved our study. Patients received a clear explanation of the study goals as well as assurances for data confidentiality. The participants were assured that their choice to participate in the study would not affect their treatment procedures. Voluntary completion of the questionnaire was considered to be written informed consent.2), baby’s head circumference (cm), parity (1 and≥ 2), education of mother (undergraduate and graduate), mother’s occupation (housewife or employed), type of pregnancy , history of abortion (yes or no), history of stillbirth (yes or no), preeclampsia (yes or no), multiple pregnancy (yes or no), and ART (yes or no).The instrument used in this survey was based on a checklist that consisted of the mothers’ demographics and information about midwifery and the infant. We completed the checklist by interviewing the mother; medical files in the delivery room were checked by a midwife and well-trained nurse. The checklist contained information about the maternal and paternal age (years), socioeconomic status (SES), mother’s BMI (kg/mi. Birth weight (g): LBW (<2500 g), normal birthweight (2500-4000 g) and macrosomia (≥4000 g) and ii. Gestational age (weeks) at birth: preterm birth (<37 weeks), term birth (37-42 weeks) and postterm birth (≥42 weeks of gestation). We performed a joint multilevel multiple logistic regression model , 20. “JoIn the model, y1iJ and y2iJ are the gestational age and birth weight for subject j at hospital I, respectively. Both x and z are predictor variables of the response variables. â and á are the estimated coefficient vectors that correspond to the predictors. The terms u1i and u2i are the random intercepts . ù and è are the thresholds of each response variable category (c). The reference level for gestational age was “term” as well as “normal weight” for birth weight. According to the logit link function, eâ (eá) indicates the OR of LBW (preterm)/macrosomia (postterm) to normal weight (term) for X=x+1 compared to X=x. A 95% confidence interval (CI) that contained 1 indicated a P>0.05 and a non-significant effect size. Simple univariate multilevel nominal logistic regression models were separately applied for predictors. Those variables with P<0.20 were used in the joint multilevel multiple logistic regression model.The data analysis was carried out recruiting the PROC NLMIXED in SAS software version 9.2 . A P<0.05 was considered significant. Two-sided tests were run for the statistical hypothesis.We observed the following prevalence rates for preterm (5.5%), term (94%), and postterm (0.5%). LBW had a prevalence rate of 4.8%. The prevalence rate for normal weight was 92.4 and 2.8% for macrosomia. The independent chi-square test exposed a strong association between gestational age and weight at birth .The distribution of cases’ characteristics in three groups of gestational age and weight at birth are illustrated Tables, 2. PatiThe joint multilevel multiple logistic regression model analysis adjusted the association between gestational age and birth weight as well as the interaction among several predictors . Based We assessed infant weight at birth, mother’s age, mother’s BMI, mother’s education, parity, history of stillbirth, multiple pregnancy, preeclampsia, and infant sex as the candidate affective predictors by the univariate models. According to 95% CI, parity, multiple pregnancy, and preeclampsia had a statistical association with LBW. Macrosomia showed a significant association with mother’s BMI and infant sex. Mothers with more than two pregnancies were less likely to deliver a child with LBW . The patients with multiple pregnancy were 17.35 (95% CI: 9.73-30.94) times more prone for LBW than normal weight. Children from mothers with preeclampsia were 3.36 (95% CI: 2.15-5.24) times more likely to experience LBW compared to normal mothers. The OR of macrosomia to normal weight for a mother with a higher BMI was 1.02 (95% CI: 1.01-1.04). Macrosomia was more common among male infants compared to females .Numerous studies reported a direct, positive correlation between weight at birth and gestational age , 22, 23A systematic review Flenady et al.  has sougKistka et al.  assessedWe showed that the presence of preeclampsia increased the odds for preterm and LBW. However, our study showed that the odds for postterm delivery and macrosomia were higher among those with preeclampsia. These ratios were not significant. Davies et al.  investigDunietz et al.  assessedBased on the results from our study, macrosomia was affected by mother’s BMI. Rockhill et al.  reportedThe strength of this study was the association between two ordinal outcomes of pregnancy and determining their potential risk factors by using an advanced statistical joint modeling approach. Ignoring the strong association between the two response variables, weight at birth and gestational age, reduced the statistical power to find their significant risk factors. In contrast to univariate models and traditional approaches, jointly modeling several response variables increases the statistical power of data analysis. In a study by Santos et al. , multivaKassahun et al. used a joint model for hierarchical continuous and zero-inflated overdispersed count data to assess the diarrhoeal disease burden. To do so, the combined infant body weight and number of days of diarrhoeal illness using a longitudinal design . MoreoveThese types of data are widely used in medical and clinical areas; ignoring its’ natural variance causes misleading estimations . NkansahThe study results showed an association between preterm and postterm births to maternal age and SES. In contrast to postterm births, preeclampsia, multiple pregnancy, and ART affected preterm births. Macrosomia was caused by higher maternal BMI. Macrosomia was more common among male infants. We observed an association between LBW and parity, preeclampsia, and multiple pregnancy. We have determined that the joint multilevel multiple logistic regression model is a proper statistical tool for these types of data.


Effective immunomodulatory therapies for children with life-threatening “cytokine storm” triggered by acute influenza infection are lacking. Understanding the immune profiles of children progressing to severe lung injury and/or septic shock could provide insight into pathogenesis.To compare the endotracheal and serum cytokine profiles of children with influenza-related critical illness and to identify their associations with severe influenza-associated complications.N = 171) and validation (N = 73) cohorts (December 2008 through May 2016). Concentrations of 42 cytokines were measured in serum and endotracheal samples and clustered into modules of covarying cytokines. Relative concentrations of cytokines and cytokine modules were tested for associations with acute lung injury (ALI), shock requiring vasopressors, and death/ECMO.Children with influenza-related critical illness were enrolled across 32 hospitals in development , were both associated with ALI, shock, and death-ECMO independent of age and bacterial coinfection. Both of these associations were confirmed in the validation cohort. Endotracheal and serum cytokine associations differed markedly and were differentially associated with clinical outcomes.Modules of covarying cytokines were more significantly associated with disease severity than individual cytokines. In the development cohort, increased levels of a serum module containing IL6, IL8, IL10, IP10, GCSF, MCP1, and MIP1α [shock odds ratio (OR) = 3.37, family-wise error rate (FWER) We identified strong positive and negative associations of cytokine modules with the most severe influenza-related complications in children, providing new insights into the pathogenesis of influenza-related critical illness in children. Effective therapies may need to target mediators of both inflammation and repair. Staphylococcus aureus  and avian H7N9 and H5N1, have yielded important insights into the proinflammatory factors involved in host response and pathogenesis –16. UnfoPrevious work by our group and others tested for associations of individual cytokines with illness severity –19, howeWe enrolled children with suspected influenza critical illness at 35 hospitals . Children with underlying medical conditions predisposing to severe influenza infection  were excSamples of blood and endotracheal aspirates (if intubated) were provided; BSL2 and universal precautions were taken with all samples. Samples were provided at enrollment (mostly within 24 h of intensive care unit admission). The pediatric risk of mortality (PRISM) III score was used for admission severity. ALI was defined by American-European Consensus Conference criteria . We quanCytokine concentrations (pg/mL) were log-transformed for all analyses. Pearson’s correlation was used to assess cytokine covariation. To adjust for high correlation among cytokines, relative concentrations were computed from the absolute concentrations by adjusting for the mean cytokine level within each sample; the effect was that all downstream analyses of relative concentrations were independent of the mean cytokine concentrations of each sample . Briefly, each cytokine variable was regressed on a vector of mean concentrations in each sample, and the residuals were taken as cytokine concentration adjusted for the mean. Cytokine modules were constructed with ET and blood stream (BS) samples separately, using hierarchical clustering on a correlation-based similarity metric; patient-level bootstrapping was employed to improve cluster reliability . Modulesp < 0.05 accounting for 182 comparisons (including modules based on relative and absolute cytokine concentrations). False-discovery rate (FDR) adjusted q-values are also reported. Significant modules of relative cytokines in the development cohort were tested for associations in the validation cohort, using unadjusted p < 0.05 as criteria for successful validation. Except where indicated, figures and text describe analyses of relative as opposed to absolute cytokine concentrations. Python code for all statistical analyses is publicly available on github: https://github.com/agartland/cycluster.The prespecified primary analysis included evaluation of each BS and ET modules for associations with clinical complications using logistic regression, with and without adjustment for age and bacterial coinfection. An exploratory analysis followed to evaluate the associations of individual cytokines with the clinical complications. Associations of individual cytokines and modules are reported using an odds ratio (OR) and a fold-difference in concentration or module score between patients with and without the respective complication. For the primary analysis significance was based on a conservative family-wise error rate (FWER) adjusted 2/FiO2 < 300 mmHg) with the majority having its more severe form ARDS (PaO2/FiO2 ≤ 200 mmHg). In the development cohort, the 2009 pandemic H1NI was the most common strain identified, whereas influenza A H3N2 was commonly identified in the validation cohort.Characteristics of the 171 children with influenza critical illness in the development cohort were overall similar to those of the 76 children in the validation cohort . Detailed comparisons of demographic characteristics, clinical outcomes, and infections for these outcome subgroups are shown in Tables S1 and S2 in Supplementary Material.In the development cohort, there were 70 (40.9%) with no shock or ALI, 22 with ALI only (12.9%), 20 with shock only (11.7%), and 59 with both (34.5%). In children with both ALI and shock, 32% received ECMO and 17% died versus 0 and 1% of children without either ALI or shock; survivors of both also had significantly longer PICU length of stay. Children with ALI and shock were older . Influenza B and bacterial superinfection with methicillin-resistant Serum samples from the BS were provided at enrollment (mostly within 24 h) by 165 of 171 influenza-positive children in the development cohort, with endotracheal samples (ET) available from 93 patients on mechanical ventilator support . We measured the concentrations of 42 cytokines, chemokines, and other immune signaling analytes (referred to hereafter as cytokines) in BS and ET samples .p < 0.05) with a median correlation coefficient of 0.26 [IQR ]. Correlations were also high among ET cytokines with a median correlation coefficient of 0.37 . Therefore, within a compartment, children with a high concentration of one cytokine were relatively likely to have high concentrations of all other cytokines. With the exception of one BS cytokine and one ET cytokine, the levels of all cytokines were correlated with the mean cytokine level within each compartment ; the difference was also significant for intercompartment correlations and ET cytokines (p < 0.001). For example, the correlation coefficient of IP10 measured in BS and ET  was 0.15 while the median correlation of ET IP10 with all other ET cytokines was 0.27 [IQR ] .Most cytokines in BS samples were positively correlated. We quantified this by computing the Pearson’s correlation coefficient between all pairs of BS cytokines Figure A. Eviden6 .6 .relative to the all of the other cytokines in the sample . Overall, the percentage of significantly correlated cytokine pairs (unadjusted p < 0.05) dropped from 70 to 42% in the blood and from 79 to 38% in the lung after adjusting for mean cytokine concentration.We hypothesized that the high levels of intrasample correlation reflected generalized inflammation or possibly sampling artifacts , both of which could obscure important immunological signals. Therefore, from the absolute cytokine concentrations we derived relative concentrations that compensated for the mean concentration of cytokines in each sample; a high relative concentration reflected that the cytokine was high p < 10−4) and ALI/ARDS , with a trend for association with ECMO-death  and ECMO-death ; all cytokines were lower in patients with septic shock, including EGF, GRO, IL12-P70, sCD40L, eotaxin, FGF2, and PAI-1. Notably, even the most strongly associated cytokine, EGF (OR 0.11), was not significantly associated after FWER-adjustment, demonstrating the increased sensitivity of a modular approach. A module of endotracheal cytokines, ET2, was significantly associated with ECMO-death  and ECMO-death ; it did not reach significance for ALI/ARDS  . AbsBS1 containing IFNβ, FLT3L, neutrophil elastase, and HMGB1 was also positively associated with ECMO-death . No AbsBS or AbET modules were inversely associated with clinical outcomes. No absolute individual BS or ET cytokines or ET cytokine modules were significantly associated with outcomes after multiplicity adjustment .Analyses were conducted in parallel using absolute cytokine concentrations and their modules (denoted AbsBSX). Twelve of 42 cytokines (28.6%) were in the same BS modules and 16 of 42 (38.1%) were in the same ET modules . The cytokines in BS3 were identical to those in AbsBS3 and the module was also positively associated with shock  as well as the inverse associations of BS4 with shock (p = 0.04) and ECMO-death (p = 0.0003). We also found that additional associations in the development cohort with FDR-q < 0.2 were replicated in the validation cohort. There were insufficient ET validation samples to validate ET module results.In the validation cohort, we evaluated each of the significant associations that were identified between the BS3 and BS4 cytokine modules and clinical complications. Despite the smaller cohort, all findings were replicated , including both the direct associations of BS3 with ALI, shock, and ECMO-death  logistic regression with L1-regularization (LASSO), 2) support vector machine classifier with L2-regularization (SVC), and (3) gradient boosting machine classifier. Both relative and absolute cytokine concentrations were considered in two independent analyses. Classification performance was evaluated in 10-fold nested cross-validation using the area under the receiver operator curve (AUC), sensitivity , and specificity . The classifiers based on absolute cytokine concentration performed well Figure ; Table 2 support The cytokine-based classifiers were compared to a logistic regression model using each patient’s age and admission day illness severity score (PRISM III score) measuring degree of organ dysfunction based on patient physiology and excluding level of support. The score was developed as a mortality risk assessment tool in the PICU . NotablyChildren who develop the most severe complications of influenza infection, including ALI/ARDS and septic shock, are the focus of critical care management and could potentially benefit from targeted immunomodulatory therapy. However, a major hurdle will be to dissect the pathways that can be targeted to reduce pathogenesis while maintaining the ability of host cells to mount an antiviral response . Althougin vitro alveolar human type 2 epithelial function and increase survival in H5N1 influenza infection , which included IL6, IL8, IL10, IP10, GCSF, and MCP1, was elevated in patients with septic shock, ALI, and ECMO-death, in two independent cohorts. In a previous study of influenza-infected PICU patients, all but GCSF and IL10 were previously associated with mortality . StudiesBy analyzing cytokines in the blood as well as the lung, at the site of infection, we were able to distinguish unique patterns of immune signaling in the two immune compartments. Cytokines were moderately correlated within compartments and weakly correlated between compartments, consistent with a previous study by our group of a cohort with less severe influenza infection . The twoCurrently, there is no standard method to adjust absolute cytokine concentrations for sampling effects or for overall cytokine secretion, particularly for respiratory samples that could be influenced by dilution from capillary leak or use of saline. Our novel use of relative cytokine levels, adjusted for the overall mean concentration of all cytokines in a sample, revealed potentially important inverse associations, evidenced by BS4 whose association with shock was not detected using absolute concentrations. There was one module based on absolute concentrations, containing IFNβ, FLT3L, neutrophil elastase, and HMGB1, that was associated with ECMO or death, but did not have an analogous module of relative cytokines with similar associations. Therefore, to fully reveal immune signaling, it may be important to evaluate absolute and relative concentrations; insights from one or the other may differ by context.Application of a module-based analysis approach appeared overall to increase statistical power, presumably by aggregating covarying signals prior to testing. Although modular analysis has been applied to gene expression studies , it has Modules were not used for development of a cytokine biomarker since interpretability and power for statistical inference were not a requirement. The concordance among three machine-learning algorithms suggested that there was a robust signal in the data. The comparable performance of relative and absolute cytokine concentrations is not surprising as relative concentrations are derived from absolute concentrations. Though the biomarker would need further development and validation before use in the PICU, the LASSO classifier would be most practical as it decreased the number of cytokines required from 42 to 19. The high performance of the PRISM classifier on the development cohort was expected as it is aggregated from several measures of symptom severity, some of which directly inform the diagnosis of shock and ALI. The substantial drop in performance on the validation cohort suggests that the model may be inflexible and overly sensitive at the decision boundary. The validation also showed that a cytokine-based classifier performs comparably to a PRISM-based classifier despite that the latter benefits from direct influence of patient severity. A question for future studies is whether a cytokine-based biomarker could be used earlier, perhaps prior to PICU admission, to identify high risk patients. In this study, we have characterized the state of the immune system in the later stages of infection, when the patient is critically ill. The findings provide new insights into the immune signaling underlying disease pathogenesis and offer potential targets for future investigation.This study was carried out in accordance with the recommendations of the Institutional Review Boards at each study site with written informed consent from at least one parent or guardian of each subject. The parent or guardian of each subject gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Institutional Review Boards at each study site.Study design: AR, AP-M, and PALISI. Clinical data collection and management: AA, AP-M, PALISI, and AR. Cytokine data generation: AP-M, AM, and AR. Statistical analysis: AF-G and TH. Synthesis and manuscript writing: AF-G, AP-M, AA, AM, MM, PT, TH, and AR.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.DOI:http://dx.doi.org/10.7554/eLife.23804.001 What is evolution? The common definition is that evolution is the temporal dynamics of gene frequencies or phenotype distributions, or generally the change over time of important characteristics of populations of organisms. Such dynamics are thought to occur if there is heritable variation in these characteristics, and if individuals with different characteristics survive and reproduce at different rates, i.e., have different ”fitness" . This viIn this essay, we advocate a mechanistic approach to evolutionary dynamics that is based on individual organisms undergoing the fundamental events of birth and death. In this approach, the long-term dynamics of genotype or phenotype distributions become an emergent property of the underlying birth-death process. While this line of thought might appear to be straightforward, it leads us to question a number of evolutionary concepts that are held dearly by many. After presenting a general description of evolution as a birth-death process, we discuss some implications of this approach for the concepts of fitness and optimality, for the relationship between ecology and evolution, for social evolution and multi-level selection, and for cultural evolution. Even though in full generality, evolutionary birth-death processes are mathematically intractable, in all these areas a mechanistic model of evolution generates unified perspectives that will be useful for clarifying empirical questions, as well as for future developments in evolutionary theory.Every model, whether verbal or mathematical, starts with simplifications. From a simplified, yet general perspective, the fundamental processes that give rise to evolution in the biosphere are that individual organisms give birth and die at certain rates . Individuals have properties, such as genotypes or phenotypes, or age and physiological state, and their birth and death rates depend on these properties. However, in general an individual’s birth and death rates also depend on many other things, such as the number and properties of other individuals in the evolving population, properties of individuals in other populations, and the external environment. As a consequence, birth and death rates typically vary in time as populations and the environment change. To obtain a general model of evolution, consider a population of individuals We denote by Here The stochastic process leading to evolution unfolds through birth and death events that occur with probabilities that are proportional to the birth and death rates. Such processes are examples of Markov processes, which are of central importance in the mathematical theory of stochastic processes . One canThe result is a stochastic process in which the type composition of the evolving population changes as individuals die, in which case their type is removed from the population, or give birth, in which case an individual is added to the population. In the latter case, the type of the newborn individuals is determined by the various processes involved in the production of offspring, such as mate choice, recombination, and mutation. Formally, these processes can be subsumed in an ”offspring function" In this way, the functions In reality, the rate functions endence, . In addiEven though the description of evolution as a birth-death process is conceptually very simple, the potential for complexity should not really come as a surprise. After all, it seems intuitively obvious that, generally speaking, the biosphere is a complex system , and that its composition undergoes complicated temporal changes. It is important to keep in mind that in principle, this complexity of evolutionary dynamics not only comes from novelties generated by mutational processes  by assuming that the functions Even though births and deaths of reproducing units are a natural starting point for describing evolution as the dynamics of the abundance of different kinds of individuals, the definition of reproductive unit may not always be straightforward. In some fungi or plants, for example, biomass growth may be a reasonable substitute for reproduction, in which case the birth and death rate functions would take on a slightly different meaning and include growth and decline of biomass. The meaning of the offspring function It is also worth pointing out that in the evolutionary birth-death process described, any form of genetic heritability is incorporated in the offspring function An important, though admittedly self-evident aspect of the perspective of evolution as a birth-death process is that evolution explicitly becomes a forward-propagating process. What happens next in an evolving system is entirely determined by the current state of the system, and not by any sort of ”teleological" quantity. In particular, a priori there is no fitness function that ”drives" evolution. Of course, an immediate counterargument to this statement would be that one could define fitness as the difference between birth and death rates. Then the quantity For example, the variance across replicates of an evolving system depends on the sum of This seems obvious, but is worth being emphasized. To this day, mainstream evolutionary thinking is dominated by imagining evolution as a process that maximizes ”fitness". This is true both for the theoretical (e.g. population genetic) and the empirical literature, as well as in popular accounts of evolution . A common metaphor in evolutionary biology is the fitness landscape . FormallIn terms of the stochastic birth-death process described above, assuming that evolution is determined by a constant fitness landscape corresponds exactly to assuming that there is a global fitness function We have recently argued that in some sense, most evolutionary dynamics should be expected to be complicated if they unfold in a type space that is itself sufficiently complicated . This iIn some, and perhaps even in many situations it may be possible to derive such a function from the given birth-death process. In fact, as we argue in the next section, considering certain precisely defined variants of the growth rate Incidentally, this also applies to evolutionary game theory  and its Given the rate functions see e.g. . A form see e.g. , 2008 haOne interesting result is that the type of analytical approximation one obtains depends very much on the type of limits one takes . Thus, dHere Invasion fitness can be derived from evolutionary birth-death processes not only for particular cases, but as a general principle , and adaBirth-death processes are fundamentally ecological, because they result in temporal fluctuations in the number of individuals in the population. What makes birth-death processes evolutionary is the offspring function In practice, the offspring function duction" , e.g. ofSocial evolution, and in particular the evolution of cooperation, is one of the fundamental problems in evolutionary biology. There has been much discussion in recent years about how to model social evolution, and about what the correct ”fitness measures" are that should be employed in such models , such processes do not in general admit a global fitness function from which their dynamics can be derived. In existing models of social evolution, inclusive fitness is almost never derived from an underlying birth-death process, and deriving an inclusive fitness function capturing the dynamics of the underlying process would only be possible under special assumptions.In a birth-death process for social evolution, individuals obviously do not ”know" anything about maximizing inclusive fitness. Instead, individuals characterized by certain social traits simply give birth and die at certain rates, which are determined independently for each individual. Birth rates (and death rates) of different individuals may of course be correlated, e.g. due to a shared environment, but birth and death rates of each individual are calculated independently, and, in particular, independently of the degree of relatedness of other individuals. Social evolution is then an emergent property of this process. For example, for the classical problem of the evolution of cooperation it is typically assumed that individuals differ in their contributions to some ”public good" that benefits others but whose production is costly. One could e.g. assume that individuals making larger contributions to the public good have a lower birth rate, a higher death rate, or both, and that the presence of the public good in the vicinity of an individual increases that individual’s birth rate .The question then is whether the frequency or abundance of individuals making larger contributions will increase or decrease over evolutionary time. The answer emerges as the birth-death process unfolds, and of course the expectation is that the frequency of cooperative individuals can only increase if on average, their loss (in birth/death rates) due to production of the public good is compensated by gain (in birth/death rates) from the presence of the public good in their vicinity. In some scenarios it may be possible to subsume and describe the emergent dynamics using an inclusive fitness measure, but such a fitness measure would not be a basic ingredient of the underlying birth-death process, and instead could at best be a quantity that is derived from that process. Moreover, if it is possible to derive this quantity, then it is also possible to derive other fitness measures that would describe the dynamics of the process, such as the direct fitness measures used in evolutionary game theory. Direct fitness measures simply calculate the average number of offspring per unit time of the different cooperative types, taking into account the expected cooperative environment of each type, i.e., the degree of positive assortment between cooperating individuals .In reality, many processes of social evolution, e.g. in the microbial world, may be too complicated to readily admit any sort of fitness measure from which their dynamics could be derived. Instead, one would have to resort to determine birth and death rates of individuals as a function of their social traits and their environment, and then simulate the stochastic process . Thus, the perspective of evolutionary birth-death processes reveals that there is no fitness concept that would be fundamentally necessary for understanding social evolution.It has been argued that it is often useful to investigate social evolution in the context of group selection, i.e., of multi-level selection scenarios in which fitness accrues to both individuals and groups of individuals . SomewhaWe think that the perspective of evolutionary birth-death processes can shed light on the issue of group selection, and of multi-level selection in general. If a population of individuals is undergoing an evolutionary birth-death process, and if in this process type A prevails over type B, one could describe this as selection having favoured type A. Further, because individual organisms are the units giving birth and dying in this scenario, one would describe this as selection occurring at the individual level. In other words, in the perspective of evolutionary birth-death processes, individual-level selection requires individual-level events, i.e., individuals undergoing a birth-death process. Generalizing from this, processes of group selection require group level events. For example, groups could fission into smaller groups at certain rates, and groups could go extinct, which would define a birth-death process at the the level of groups. More generally, multi-level selection requires a birth-death process at multiple levels of biological organization.In Cultural evolution refers to the waxing and waning of ideas and cultural practices throughout the history of human societies. Cultural evolution is a powerful alternative to genetic evolution that shapes a myriad of aspects of human life, from tool making to music and religion . CulturaAn alternative way to model cultural evolution consists of considering cultural ideas as reproductive units themselves, so that the evolutionary birth-death process is defined at the level of cultural content. The initial problem with this approach is to define what exactly a cultural reproductive unit is, but a similar problem of course also exists in traditional models with humans as reproductive units carrying cultural content. Possible examples of cultural units are blueprints for tool making, levels of cooperation, forms of religion, etc. For a representation in the material world, one could identify cultural units with the patterns of neuron firing or memory storage to which they correspond. Once the units are defined, one can envisage them as colonizing human brains, much like microbes colonize and inhabit the human gut. Thus, cultural units live in human habitats (brains), in which they may accumulate or vanish, corresponding to birth and death. For example, an individual brain might acquire a strong belief and later become agnostic again, corresponding to the waxing and waning of a population of cultural units within that brain. Also, cultural units may be transmitted between habitats (brains) through various mechanisms such as conversations, reading, or social media. These transmission events can also be interpreted as birth events, with the offspring function The process unfolds in collections of human brains, and would be analogous to evolutionary birth-death processes for microbiota inhabiting human bodies. One advantage of such a perspective is that cultural evolution would unfold based on what properties of cultural content are good or bad for the propagation of culture itself, rather than based on what is good or bad for humans exhibiting cultural traits. For example, this might give insights into the mechanisms for the spread of cultural practices that are detrimental to humans, such as certain forms of religion, which may spread not because of their effect on humans, but because of their properties as cultural content. For example, a religion may spread because it prescribes its followers to convince at least The approach of considering culture as the reproductive units in an evolutionary process has for example been used in Organismic evolution in the biosphere is ultimately the consequence of some organisms dying and others giving birth to new organisms. Therefore, evolutionary birth-death processes are a natural starting point for both verbal and mathematical descriptions of evolution. For understanding the evolution of a type or a set of types, one should start by asking how those types affect birth and death rates, and how those effects depend on the state of the evolving population and its biotic and abiotic environment. The state space of an evolving system is generally complicated and includes not only the space of all possible types (e.g. genotypes or phenotypes), but also all possible states of evolving populations , as well as environmental states. Because birth and death rates in an evolutionary birth-death process are functions of the state of the evolving system, which in turn changes due to to birth and death events, the dynamics of such processes can be very complicated  and three reviewers, one of whom, Wenying Shou (Reviewer 1), is a member of our Board of Reviewing Editors. The following individuals involved in review of your submission have agreed to reveal their identity: Paul Rainey (Reviewer 2) and Jeff Gore (Reviewer 3).Thank you for submitting your article "Some perspectives on evolutionary theory" to The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:All three reviewers support the publication of this opinion piece. Revisions are recommended as detailed below.Reviewer #1:Doebeli et al. challenges the usefulness of the concept "fitness", and instead advocates a more mechanistic approach based on individual birth and death processes. I share much of authors' views of deriving understanding from first principles (birth and death in this context), although like many others, I also believe that multiple concepts can coexist to shed insights in different ways.Authors argue that because dynamics of an evolving system are intrinsically complex, the classic analogy of an evolving population "climbing" fitness peaks is often invalid and that the appropriate fitness function may not even exist. Trading "fitness" with an alternative such as "invasion fitness" where changing fitness landscape is considered, we can explain for example evolutionary branching, a phenomenon that does not emerge with constant fitness landscape. Their paper serves as a useful reminder that the suitable degree of abstraction in any model depends on the phenomenon one studies. I do feel however that fitness-related concepts and analogies are still useful in some cases . This should be mentioned in the text.With respect to authors' view on the Price's equation, I feel that the Price's equation is a clever and useful tool for conceptualizing social evolution. A phenomenon can often be viewed through different perspectives, as nicely argued in Ben Kerr's chapter "theoretical and experimental approaches to the evolution of altruism and the levels of selection". The usefulness of one perspective does not preclude the usefulness of another perspective. On the other hand, I agree with the authors that multilevel selection can mean different things to different people (e.g. whether there are group-level birth and death processes), and should be clarified.Reviewer #2:eLife opinion piece. For far too long evolutionary biology has been held back by comforting, but often misleading, representations of underlying process. In advocating a shift away from fitness as a basal descriptor of evolution and toward a birth-death descriptor, Doebeli and colleagues help fuel new ideas and a more complete understanding of the processes by which evolution actually works. Personally, I find the idea that fitness is – at best – an emergent property highly compelling. It makes sense.This is an important paper that is highly appropriate for an Two issues tangential to the authors' main thesis that they may wish to consider. Firstly, a seemingly trivial matter, but one that is not often appreciated and that is the importance of the coupling of death and birth: this coupling ensures that selection works on fecundity and not just on viability. Eliminate the possibility of birth, and selection works purely on viability (and is largely impotent). Add the possibility of birth, and thus the selection works on fecundity, and evolution is potent. It wouldn't take much to make this link.Secondly, an important shift that comes from considering the primary currency of evolution as birth/death comes from the fact that the focus moves from growth rate. The standard adaptive landscape metaphor, combined with evolution experiments in simple environments, means that fitness is almost always considered a function of growth rate. But in nature this is probably rarely the case. Once consideration is given to criteria for avoidance of death (and thus the possibility of birth) it becomes apparent that selection can work on many properties  and in so doing the range of phenotypic states open to evolution vastly increases.A related issue is that of timescale. Possibly it is beyond the current manuscript – although the authors touch upon this (I think) around section titled 'Some remarks', second paragraph – but time at which death comes about – whether it is with each cell division, or at some other ecologically or evolutionarily defined (or arbitrarily defined) time interval is hugely important. It is when selection comes to work over a time frame that is longer than the doubling time of individual cells that things get interesting.A further issue warranting comment is the order of birth/death vs. death/birth. At least in models of evolution on graphs involving a birth/death process, the outcome is different depending upon which event comes first. I think it matters. It is the difference between selection rewarding persistence (avoidance of death) vs. selection rewarding growth rate.In the section on application to multi-level selection the authors might like to consider the work of Hammerschmidt et al. (Nature) 2014 who incorporated into their experimental design an explicit death-birth process precisely as articulated by the authors. The "higher" level, defined by capacity to proceed through a life cycle involving two different ecological stages, being prone to failure (based on the properties of the cells) allowing the possibility that extant types (that avoided extinction) had opportunity to export their reproductive success. Groups competed with groups with the evolutionary process being driven by death/birth events.Finally, the authors may also want to consider more fully the discomfort that arises from trying to reconcile the stochasticity inherent in death/birth processes with evolution by natural selection. I don't think that are difficult to reconcile, but doing so requires recognition that what we would consider as adaptive phenotypes are underpinned by much more chance (drift) that we are typically comfortable with.Reviewer #3:I very much like the approach suggested by the authors, as birth/death events are clear and unambiguous. We are all aware that "fitness" is a tricky thing to define, and the approach taken by the authors makes it clear why this is. I especially like the birth/death approach because it greatly clarifies the links between evolution and ecology. In addition, I believe that eco-evolutionary feedback loops will be easier to spot using this approach. I believe that this perspective will be very helpful for the community, and I believe that it could/should be published essentially as is.I am not familiar with the concept of invasion fitness, and I can't say that the description here was sufficient for me to understand it. For example, how do we average over an infinite time horizon if the invasion fitness is a function of time? . Reviewer #1:Doebeli et al. challenges the usefulness of the concept "fitness", and instead advocates a more mechanistic approach based on individual birth and death processes. I share much of authors' views of deriving understanding from first principles (birth and death in this context), although like many others, I also believe that multiple concepts can coexist to shed insights in different ways.Authors argue that because dynamics of an evolving system are intrinsically complex, the classic analogy of an evolving population "climbing" fitness peaks is often invalid and that the appropriate fitness function may not even exist. Trading "fitness" with an alternative such as "invasion fitness" where changing fitness landscape is considered, we can explain for example evolutionary branching, a phenomenon that does not emerge with constant fitness landscape. Their paper serves as a useful reminder that the suitable degree of abstraction in any model depends on the phenomenon one studies. I do feel however that fitness-related concepts and analogies are still useful in some cases . This should be mentioned in the text.We agree that fitness-related concepts can be useful, but only if they are justified “ecologically”, i.e., based on birth and death events. Otherwise, we think that such concepts are mainly misleading, exactly because they seem useful based on intuitive grounds, but really aren’t if they can’t be derived from underlying mechanisms. We have inserted the following sentence in the (newly named) “Concluding remarks” section:“The concept of fitness has of course played a major role in the development of evolutionary theory, and as such has been very useful, and very widely used, albeit often without empirical or ‘microscopic’ justification.”With respect to authors' view on the Price's equation, I feel that the Price's equation is a clever and useful tool for conceptualizing social evolution. A phenomenon can often be viewed through different perspectives, as nicely argued in Ben Kerr's chapter "theoretical and experimental approaches to the evolution of altruism and the levels of selection". The usefulness of one perspective does not preclude the usefulness of another perspective. On the other hand, I agree with the authors that multilevel selection can mean different things to different people (e.g. whether there are group-level birth and death processes), and should be clarified.We have inserted the word “useful” in the corresponding sentence . We would maintain that the Price equation is not a model, but a particular way of arranging the data coming out of a specified model (or from an experiment). Data visualization can suggest mechanism, but can never prove mechanism. Moreover, to us the Price equation does not seem useful to study group selection, since the number of groups is typically held constant in formulations based on the Price equation, hence there is no birth-death process at the level of groups. Other than that, this reviewer comment did not seem to be an “actionable item”, as we give quite a lot of information about what we would call group selection (based on birth-death process at the level of groups). Please let us know if you would like to see more clarification on how we view group selection (or the Price equation).Reviewer #2:This is an important paper that is highly appropriate for an eLife opinion piece. For far too long evolutionary biology has been held back by comforting, but often misleading, representations of underlying process. In advocating a shift away from fitness as a basal descriptor of evolution and toward a birth-death descriptor, Doebeli and colleagues help fuel new ideas and a more complete understanding of the processes by which evolution actually works. Personally, I find the idea that fitness is – at best – an emergent property highly compelling. It makes sense.Two issues tangential to the authors' main thesis that they may wish to consider. Firstly, a seemingly trivial matter, but one that is not often appreciated and that is the importance of the coupling of death and birth: this coupling ensures that selection works on fecundity and not just on viability. Eliminate the possibility of birth, and selection works purely on viability (and is largely impotent). Add the possibility of birth, and thus the selection works on fecundity, and evolution is potent. It wouldn't take much to make this link.Secondly, an important shift that comes from considering the primary currency of evolution as birth/death comes from the fact that the focus moves from growth rate. The standard adaptive landscape metaphor, combined with evolution experiments in simple environments, means that fitness is almost always considered a function of growth rate. But in nature this is probably rarely the case. Once consideration is given to criteria for avoidance of death (and thus the possibility of birth) it becomes apparent that selection can work on many properties  and in so doing the range of phenotypic states open to evolution vastly increases.A related issue is that of timescale. Possibly it is beyond the current manuscript – although the authors touch upon this (I think) around section titled'Some remarks', second paragraph – but time at which death comes about – whether it is with each cell division, or at some other ecologically or evolutionarily defined (or arbitrarily defined) time interval is hugely important. It is when selection comes to work over a time frame that is longer than the doubling time of individual cells that things get interesting.In response to first two points raised, we have inserted the following passage:“Also, an explicit distinction between birth and death events allows for separate descriptions of the effects of genotypes or phenotypes on fecundity and viability, which gives more flexibility compared to describing these effects based on compound properties such as growth rates.”Regarding the time scale issue, we are not entirely sure what the reviewer means, but we think that these concerns are addressed in our approach, at least implicitly: since evolution occurs by propagating a birth-death process, there is no particular time scale any more at which “selection acts”: rather, one can simply chose any time scale of interest and then observe the dynamics of the process over that time scale. A further issue warranting comment is the order of birth/death vs. death/birth. At least in models of evolution on graphs involving a birth/death process, the outcome is different depending upon which event comes first. I think it matters. It is the difference between selection rewarding persistence (avoidance of death) vs. selection rewarding growth rate.This is a rather technical issue (on which we have previously published) that arises in evolutionary models of Moran processes in populations of a fixed, finite size. Such models are not discussed in our paper, and we would prefer to refrain from addressing this technical issue, because we think it does not fit into the present context.In the section on application to multi-level selection the authors might like to consider the work of Hammerschmidt et al. (Nature) 2014 who incorporated into their experimental design an explicit death-birth process precisely as articulated by the authors. The "higher" level, defined by capacity to proceed through a life cycle involving two different ecological stages, being prone to failure (based on the properties of the cells) allowing the possibility that extant types (that avoided extinction) had opportunity to export their reproductive success. Groups competed with groups with the evolutionary process being driven by death/birth events.Thanks for pointing this out. We have inserted the following sentence:“Group level birth and death events, and hence group selection, may also be very important for the evolution of multicellularity from aggregations of single-celled organisms.”Finally, the authors may also want to consider more fully the discomfort that arises from trying to reconcile the stochasticity inherent in death/birth processes with evolution by natural selection. I don't think that are difficult to reconcile, but doing so requires recognition that what we would consider as adaptive phenotypes are underpinned by much more chance (drift) that we are typically comfortable with.Again, this is a valid point, but since we are throughout talking about stochastic processes anyway, we don’t really see how to incorporate this remark. What the reviewer refers to as “natural selection” appears to be based on some sort of deterministic fitness measure, which we argue should not be used unconditionally anyway. In our view, it’s not that one has something deterministic to start with, and then adds stochasticity and asks how the deterministic thing would be affected by that. Rather, to begin with all we have is the stochastic process, from which one can perhaps derive a deterministic theory, which would then have to reflect the effects of stochasticity at least to some extent.Reviewer #3:I very much like the approach suggested by the authors, as birth/death events are clear and unambiguous. We are all aware that "fitness" is a tricky thing to define, and the approach taken by the authors makes it clear why this is. I especially like the birth/death approach because it greatly clarifies the links between evolution and ecology. In addition, I believe that eco-evolutionary feedback loops will be easier to spot using this approach. I believe that this perspective will be very helpful for the community, and I believe that it could/should be published essentially as is.I am not familiar with the concept of invasion fitness, and I can't say that the description here was sufficient for me to understand it. For example, how do we average over an infinite time horizon if the invasion fitness is a function of time? .Due to the nature of our piece, we can’t really go into any technical details, but we have tried to clarify this issue, at least to some extent, in the last paragraph of section titled 'Towards an analytical theory of evolutionary birth-death processes'.