We analyze the impact of birth seasonality  on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However, as the mean birth rate increases, both birth amplitude and phase play an important role in driving the dynamics of the epidemic. There are stronger effects at higher birth rates. The incidence of influenza and many other respiratory infections increases during cold winter months; cholera and malaria incidence increase during the rainy season; even the incidence of sexually transmitted disease such as gonorrhea increases during the summer months A range of mechanisms with the potential to drive seasonal and multiannual fluctuations in the incidence of infectious diseases have been identified. They include factors that impact transmission, such as ability of the pathogen to survive outside a host, and seasonal changes in host behavior; factors that impact host susceptibility, such as seasonal changes in immune function; and factors that impact host birth rate, such as seasonal fluctuations in the birth rate Most human disease ecologists have focused on identifying drivers leading to seasonal fluctuations in the transmission parameter, because of its large impact on infectious disease dynamics in the presence of transmission seasonality Almost all human populations exhibit seasonal variation in reproduction, which typically account of a large source of variation in birth rates This paper is an extension of the work of He and Other studies looking at the effect of intra-annual fluctuations in birth rates comes from studies of wildlife diseases In this paper, we analyze the impact of seasonal fluctuations in human birth rates  on measles disease incidence and dynamics. Not all infectious disease dynamics will be sensitive to seasonal forcing in the birth rates. Diseases of interest have the following properties–acute, immunizing infections, with a low mean age of infection We focus on the effect of changes in birth amplitude given a wide range of baseline birth rates that corresponds to empirical data from sub-Saharan Africa, while He and Earn model a relatively low baseline birth rate  that corresponds to developed countries Furthermore, we model the effect of birth seasonality on one disease, measles, so mean duration of the infectious period is constant and Specifically, we try to answer the following question: what are the impacts of changing the parameters of the seasonal birth forcing function  Demographic and Health Surveys (DHS). The DHS use nationally representative samples of women of reproductive age. The DHS contains retrospective birth histories, which have been widely used to estimate birth rates and recently seasonal birth amplitude. Although it had long been known that seasonal fluctuations in births are ubiquitous in human populations, there were very few estimates of birth seasonality in SSA, in part due to lack of vital registration data. Fortunately the DHS data can also be used to calculate birth seasonality. Following the method described by He and Earn , we obtain estimates of average monthly amplitude.On average, SSA birth rates range from 22.1 in South Africa in 1998, to 51.7 per 1000 in Niger in 1998. We documented birth amplitude levels ranging from 5 to 65 percent at the national level. At the sub-national level, higher levels of birth amplitude have been documented, in SSA some in excess of 100 percent In addition to having an estimate for the strength of seasonality, we also need information on the shape of the seasonal forcing function If the goal is to fit a disease model with birth seasonality, to observed data, we may choose to use actual monthly fluctuations in birth rates or birth amplitudes as parameters. Nevertheless, for the rest of this paper, a simple cosine function is used, as the shape of the seasonal recruitment function does not qualitatively affect whether bifurcations will take place Measles is a highly infectious virus transmitted by aerosol particles The rates of change in the compartments is defined by the following differential equations:Here, the seasonal forcing functions–birth seasonality  per capita natural death rate  integration method from the GNU Scientific library. Starting with a population where the proportion of susceptible individuals are six percent of the population, exposed and infectious individuals are each 0.1 percent of the population, and recovered individuals represent 93.8 percent of the population and parameter values , increasing transmission amplitude above the threshold shifts the epidemic towards the beginning of the year while increasing birth amplitude shifts the timing of the epidemic peaks towards the end of the year. When birth and transmission seasonality are out of phase, above the aforementioned threshold, increasing both transmission and birth amplitudes shift the timing of the epidemic peak to the beginning of the year  and 9c. In this paper we extend previous work to show that at high birth rates, amplitude can be important, especially coupled to seasonality in transmission. We also highlight an important source of data, the Demographic and Health Surveys, for estimating seasonal birth patterns for many SSA countries. Having an estimate of the birth seasonality function, allows us to separate seasonal forcing in births from other seasonal forcers such as those in transmission.Models of acute immunizing childhood infections in SSA should take into account birth seasonality. The presence of birth seasonality alone can lead to spatial and temporal variation in the periodicity, magnitude, and timing of epidemics in SSA. The interaction between baseline birth rate and birth amplitude are important. Biennial epidemics occur only at high levels of birth amplitude and intermediate levels of baseline birth rates. In the regime of annual epidemics, as baseline birth rate increases the effect of increasing birth amplitude on peak incidence also increased.We also explored the interactions between transmission and birth seasonality. As He and Earn There are some limitations to this study. We did not use an age-structured model; however, the SEIR model without age structure still captures the dynamical essence of the system Candidate SSA countries where birth seasonality may play an important role include Sierra Leone, Guinea, Democratic Republic of Congo, and Nigeria. These countries have strong birth seasonality (maximum amplitude between 30 to 65 percent), low proportions of fully immunized population (20 to 40 percent), and high birth rates (30/100 to 44/1000)] Birth amplitude tends to decline over time, as a result of increased development Figure S1Effects of changing the parameters ((TIFF)Click here for additional data file.Figure S2This bifurcation diagram illustrates the impact of changing magnitude of  Two trajectories are for (TIFF)Click here for additional data file.Figure S3Bifurcation diagram at the Poincaré section showing the impact of varying birth amplitude  increasing the amplitude leads to larger annual epidemics. At intermediate birth rates (30/1000) increasing amplitude first leads to larger annual epidemics but at amplitudes greater than 65 percent increasing amplitudes lead to biennial epidemics with increasing peak sizes. At very high birth rates (40/1000) changes in amplitude lead to increasingly large annual epidemics. ((TIFF)Click here for additional data file.Figure S4Spectral analysis and relative size of peak incidence in model with demographic stochasticity. The peaks (black dots) are not of the same magnitude from year to year but a general pattern emerges as we increase amplitude and birth rates. We use heat colors to indicate the power spectral density, therefore the highest peaks are in red.(TIFF)Click here for additional data file.File S1Analysis of a Stochastic SEIR model with seasonality in the birth rate. The periodicity and relative changes in peak incidence are plotted for varying levels of birth amplitude and baseline birth rates in (PDF)Click here for additional data file.


Epidemiological studies suggest that prenatal exposure to different types of viral or bacterial infections may be associated with similar outcomes; i.e., an increased risk of mental illness disorders in the offspring. Infections arising from various causes have similar debilitating effects in later life, suggesting that the exact pathogen may not be the critical factor in determining the neurological and cognitive outcome in the offspring. Instead, it is thought that response of the innate immune system, specifically the increased production of inflammatory cytokines, may be the critical mediator in altering fetal brain development pre-disposing the offspring to mental illness disorders later in life. Inflammatory cytokines are essential for normal brain development. Factors such as the site of cytokine production, a change in balance between anti- and pro- inflammatory cytokines, placental transfer of cytokines, the effects of cytokines on glial cells, and the effects of glucocorticoids are important when evaluating the impact of maternal infection on fetal brain development. Although it is clear that cytokines are altered in the fetal brain following maternal infection, further evidence is required to determine if cytokines are the critical factor that alters the trajectory of brain development, subsequently leading to postnatal behavioral and neurological abnormalities. Genetic background and environmental factors can predispose an individual to neuropsychiatric disorders, although the prevalence of conditions such as schizophrenia and autism cannot be accounted for by these factors alone   glial cells and 2) the hypothalamic-pituitary- adrenal axis.The suggestion that an increase of particular cytokines or a change in the critical balance between classes of cytokines caused by a prenatal infection may detrimentally alter normal fetal brain development, also assumes that glial cells are likely to be involved or at least affected as these cells are shown to not only produce cytokines but respond to them in the fetal brain Hanisch, .Glial cells, such as astrocytes and microglia, are essential for normal brain development. Astrocytes are critical for the development of neurons and synapse formation during brain development and support neuronal repair and synapse formation  axis, responsible for generalized stress responses, are inextricably linked (Franchimont et al., Although glucocorticoids are essential for normal brain development, exposure of the fetal brain to excess glucocorticoids can also modify fetal brain development and permanently alter the function of the HPA axis in postnatal life (Matthews, The involvement of the HPA axis on cytokine changes in the fetal brain is dependent on the ability of the fetus to produce an appropriate stress response involving the HPA axis, and therefore, the time of the infection during pregnancy can be expected to modify the impact on the fetal brain development. Particularly as HPA axis development is strongly linked to the development of specific regions of the brain (Matthews, It is well known that changes during fetal development can permanently programme the HPA axis, to have a long lasting impact on neuroendocrine function in postnatal life [reviewed in Matthews ; Bale etWhile mental illnesses such as schizophrenia and autism have been associated with prenatal infection, the variety of infections producing similar outcomes suggest that a response by the immune system common to all infections may be the important factor in the etiology of mental illness disorders. The common pathway may include induction of cytokines, triggered by activation of TLRs to assist in the resolution of disease but which then produce a pro-inflammatory environment that has downstream effects that are detrimental to fetal brain development. It is not entirely clear if significant amounts of cytokines enter the fetal circulation by placental transfer, or if placental and fetal production of cytokines is also important. However, the evidence is convincing that cytokines produced in response to infection during pregnancy have detrimental and long-lasting effects on the brain.Inflammatory cytokines can affect the function of glia in the developing brain. Early deregulation of glial cells, such as microglia, may set in motion a cascade of events that lead to permanent alterations in these cells. There is substantial evidence for microglial activation in the post-mortem brains of patients that suffered a mental illness (Bayer et al., It is possible to conclude that exposure to prenatal infection via the actions of cytokines can predispose or increase the susceptibility of an individual to future inflammatory events or postnatal stressors, as the function of the systems that act to resolve these insults have been permanently altered. Therefore, we believe it is important for future research to investigate two-hit models of mental illness disorders i.e., a first hit during fetal life—a prenatal viral or bacterial infection that drives an early susceptibility to mental illness via the activation of inflammatory pathways, such as the persistent activation of microglia, or changes in HPA axis function- in combination with a second hit during postnatal life—an immune activator or environmental factors such as chronic stressors or trauma. The development of these models may provide a unique period of time, prior to the “second hit,” to develop and target potential interventions or treatments to prevent the “full-blown” onset of a mental illness disorder.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.


Sub-Saharan Africa has the highest rates of maternal and neonatal mortality worldwide. Young maternal age at delivery has been proposed as risk factor for adverse pregnancy outcome, yet there is insufficient data from Sub-Saharan Africa. The present study aimed to investigate the influence of maternal adolescence on pregnancy outcomes in the Central African country Gabon.Plasmodium falciparum infection, use of bednets, and intake of intermittent preventive treatment of malaria in pregnancy were collected in a cross-sectional survey in 775 women giving birth in three mother-child health centers in Gabon. Adolescent women (≤16 years of age) had a significantly increased risk to deliver a baby with low birth weight in univariable analysis  and young maternal age showed a statistically significant association with the risk for low birth weight in multivariable regression analysis after correction for established risk factors . In further analysis adolescent women were shown to attend significantly less antenatal care visits than adult mothers  and this difference accounted at least for part of the excess risk for low birth weight in adolescents.Data on maternal age, parity, birth weight, gestational age, maternal Our data demonstrate the importance of adolescent age as risk factor for adverse pregnancy outcome. Antenatal care programs specifically tailored for the needs of adolescents may be necessary to improve the frequency of antenatal care visits and pregnancy outcomes in this risk group in Central Africa. Sub-Saharan Africa accounts for half of the world's burden of maternal, newborn and child death with over 13,000 mothers, newborns and children dying every day In Africa high rates of maternal and neonatal morbidity and mortality are a consequence of multiple causes including endemic infectious diseases , malnutrition and micronutrient deficiencies, child-birth complications, newborn illness and inadequate antenatal and perinatal care due to financial and logistic constraints in these resource poor regions Adolescent pregnancy is defined as gestation of women before having reached the full somatic development The study protocol was approved by the Ethics Committee of the International Foundation for the Albert Schweitzer Hospital in Lambaréné. Written informed consent was sought from the mother and the guardian accompanying the patient to the hospital.Plasmodium falciparum malaria From May 2005 to September 2006 a cross-sectional study in women delivering at the obstetric departments of local hospitals in the cities of Libreville  and Lambaréné  was conducted in the Central African country Gabon. The region is characterized by perennial high transmission of Women in labour attending the hospital for delivery were eligible for participation in this survey. Information on maternal age, last date of menstruation, parity, number of antenatal consultations, use of bednets during pregnancy and intake of sulfadoxine-pyrimethamine for intermittent preventive treatment of malaria were collected in structured interviews and from mother-child health booklets. A thick blood smear for the diagnosis of malaria was performed as well as maternal haemoglobin measurements .All newborns were weighed immediately after birth and birth outcome was evaluated by the midwife in charge of the delivering women. Only women giving birth to live singletons were considered for analysis. Data were captured on paper record forms and reviewed manually before analysis.The aim of the statistical analysis was to evaluate differences in pregnancy characteristics and birth outcomes of adolescent versus adult women. Adolescent status was defined as an age of or below 16 years at delivery. The number of antenatal consultations, use of bednet during pregnancy, intake of sulfadoxine-pyrimethamine for intermittent preventive treatment of malaria, maternal haemoglobin at delivery, and peripheral parasitaemia at delivery were specified as main pregnancy characteristics. Continuous and categorical measures of birth weight and gestational age at delivery were defined as main birth outcome variables. Gestational age was calculated based on the last date of menses as reported by the pregnant women. Birth weight below 2500g was defined as low birth weight and deliveries before 37 weeks of gestation were classified as preterm deliveries. Univariable analysis of epidemiological data for the two groups (adolescent and adult pregnant women) was performed by Student's t-test at a two-sided significance level of α = 0.05 for continuous variables and odds ratios for categorical variables.Since parity is a known risk factor for low birth weight an analysis of nulliparous adolescent and adult mothers was performed to correct for differences in parity between the two groups. In addition a separate analysis of differences in birth weight was carried out in the subset of term-newborns in order to account for the strong influence of preterm delivery on the occurrence of low birth weight. Finally, a comparative graphical analysis of birth weight for each completed week of gestation was performed in the subset of term-newborns to appreciate potential differences of growth retardation in adolescent and adult mothers over time.To further analyse the impact of adolescent pregnancy on low birth weight multivariable logistic regression analysis was performed. For this purpose statistical significance of variables associated with low birth weight was computed. Known risk factors for low birth weight and variables showing a statistically significant association with low birth weight in our study population were included as dichotomized variables in the logistic regression analysis. Data are displayed as mean (±standard deviation) or median (±interquartile range). Statistical analysis was performed using JMP .A total of 775 pregnant women delivering at the Centre Hospitalier de Libreville (n = 591) or at one of the two hospitals in Lambaréné (n = 184) were included in this epidemiological survey. Pregnant women participating in the study had a mean age of 24 years. The age ranged from 13 to 45 years. Parity ranged from 0 to 15 and 275 (37%) women had not given birth before. The number of pregnant women with an age of or below 15, 16, 17, and 18 years was 29 (4%), 57 (7%), 90 (12%) and 142 (18%), respectively. Intake of at least one or two doses of intermittent preventive treatment of malaria in pregnancy was recorded in 607 (86%) and 414 (60%) women, respectively. Bednet use was reported by 329 (50%) mothers.Peripheral parasitaemia at delivery was detected in 13 (2%) women. Newborns had a mean birth weight of 3077±500 g and 80 (10%) children were classified as presenting with low birth weight. Reliable information on last date of menses could be obtained in 661 cases and preterm birth was recorded in 126 (19%) children. Out of the 69 children with low birth weight for whom information on gestational age was available, 38 (55%) were classified as preterm newborns. Information on the number of antenatal care visits was obtained in 356 cases and a median (IQR) of 4 P. falciparum was significantly higher in adolescent mothers than in mothers older than 16 years (7% (4/57) vs. 1% (9/718), OR 5.9, 95%CI: 1.7–19.9, n = 775).The proportion of infants with low birth weight was 23% (13/57) in adolescent women compared to 9% (67/718) in women older than 16 years . Accordingly, children born to adolescents had an average birth weight which was 304g lower than those born to adults . The mean gestational age at delivery was comparable between both groups  and there was no statistically significant difference in the occurrence of preterm birth . The prevalence of a peripheral blood smear positive for P. falciparum (7% (4/56) vs. 2% (4/219), OR 4.1, 95%CI: 1.1–17.1). Since adolescent women are more likely to give birth to a first child and primiparity is an established risk factor for adverse birth outcome the same statistical analysis was performed for nulliparous women only (n = 275). In this analysis differences between the two groups were statistically significant for mean birth weight  and the prevalence of a peripheral blood smear positive for As preterm delivery is the most important risk factor for low birth weight, a separate analysis of differences in birth weight between adolescent and adult mothers was carried out in the subset of term newborns (n = 535). Among these, the proportion of infants with low birth weight was 16% (6/37) in adolescents compared to 5% (25/498) in adults . Accordingly, term newborns born to adolescent women had an average birth weight which was 315g lower than newborns born to adult women . Furthermore, mean birth weight was lower in newborns of adolescent than of adult mothers for each completed week of gestation .P. falciparum infection at delivery (y/n).The impact of young maternal age on the probability of low birth weight was further analyzed in multivariable logistic regression analysis. The following dichotomized variables were used for logistic regression analysis with the occurrence of low birth weight as dependent variable: gestational age (preterm <37 vs. term ≥37 weeks of gestation), maternal age (≤16 or >16), parity status (nulliparity vs. multiparity), intake of intermittent preventive treatment of malaria during pregnancy (<2 vs. ≥2 doses), use of bednets (y/n) and P. falciparum infection at delivery had no significant impact on the probability of low birth weight in this model. The model showed an acceptable fit  and preterm delivery , young maternal age ≤16  and parity  showed a statistically significant influence on the probability to deliver an infant with low birth weight. Use of bednet, intake of intermittent preventive treatment of malaria, and Information on the number of antenatal care visits was available only in a subset of mothers (n = 356) and a separate analysis was therefore performed. Patient characteristics  in this subset did not differ significantly from the main study population (data not shown).Adolescent mothers had attended significantly less antenatal care visits than adult mothers  and the difference in the frequency of consultations remained statistically significant after restriction to nulliparous women only .Multivariable regression analysis of the probability to deliver a low birth weight infant was performed in this subset of mothers using the same logistic regression model as for the main study population. In addition, the number of antenatal consultations  was entered as further variable into this analysis. This modified model again showed an acceptable fit , and prematurity  and less than 3 antenatal care visits  were the only variables significantly associated with the occurrence of low birth weight .Due to conflicting results from previous epidemiologic studies and a lack of data from Sub-Saharan Africa, we aimed to analyze the risk of adolescent pregnant women to give birth to a low birth weight infant in the Central African country of Gabon. Our data indicate that the probability to deliver an infant with low birth weight was more than doubled for adolescent women compared to mothers older than 16 years. In multivariable analysis the probability of giving birth to a low birth weight infant remained significantly higher for adolescent than for adult mothers after correction for preterm delivery, parity and other established risk factors. Our data are in line with a previous report from neighboring Congo – a region with comparable prevalence of early pregnancy – showing an even higher proportion of low birth weight infants (37%) in young women Several reasons for the high risk of delivering a low birth weight infant by adolescent mothers have been discussed in scientific literature. Anatomic immaturity and continued maternal growth may represent biologic growth barriers for the fetus P. falciparum did not play a major role for adverse birth outcome in our study population. This finding may be explained by the low rate of P. falciparum infections in peripheral blood samples in our study population. Although placental sampling may have improved the detection of pregnancy associated malaria these results are in line with a recent epidemiologic survey on the effectiveness of intermittent preventive treatment of malaria in pregnancy in our study region Interestingly other well-established risk factors for low birth weight including the use of insecticide-treated bednets, adherence to intermittent preventive treatment of malaria in pregnancy, and infection with To better appreciate potential differences of intrauterine growth retardation during gestation and to better understand the interplay between preterm delivery and low birth weight, several sub-analyses have been performed including restriction of the study population to term deliveries and graphical depiction of birth weight for each week of gestation. All these analyses conclusively showed consistently lower birth weights for newborns of adolescent mothers compared to adults. This finding strongly indicates that low birth weight is not explained by the more frequent occurrence of preterm delivery in adolescent mothers and similarly that intrauterine growth retardation is a consistent phenomenon in adolescent pregnancies for all gestational ages.Based on our data adolescent women constitute a special risk group of pregnant women. Since young pregnant women differ in many aspects from adults, routine antenatal health care programs may be insufficient for their needs. In a recent study from Zimbabwe, transport costs and costs for prenatal services have been characterized as major factors influencing adolescents' late or non-utilization of prenatal services The frequency of pregnancy during adolescence is highly variable in Africa Possible limitations of our study include the fact that low birth weight – our primary outcome measure – is a surrogate marker for adverse pregnancy outcome. Although widely accepted and used as validated endpoint in clinical trials evaluating public health interventions in Africa, its significance as causal factor for disease has been discussed controversially The analysis focuses on women delivering live infants in health facilities and does therefore neither account for early abortions nor for home deliveries. Since home deliveries are estimated to occur in approximately 10% in our study area it is however not anticipated that this constitutes an important bias in this study Our results convincingly demonstrate the importance of adolescent age and antenatal care for the improvement of pregnancy outcomes in Central Africa. Large prospective interventional studies are needed to further characterize adolescent pregnancy as risk factor for low birth weight, to evaluate potential strategies for the prevention of low birth weight in adolescent women, and to better appreciate the importance of adolescent pregnancy in different epidemiologic and demographic settings in Africa.


Since cell membranes are weak sources of electrostatic fields, this ECG interpretation relies on the analogy between cells and electrets. It is here assumed that cell-bound electric fields unite, reach the body surface and the surrounding space and form the thoracic electric field that consists from two concentric structures: the thoracic wall and the heart. If ECG leads measure differences in electric potentials between skin electrodes, they give scalar values that define position of the electric field center along each lead.Repolarised heart muscle acts as a stable positive electric source, while depolarized heart muscle produces much weaker negative electric field. During T-P, P-R and S-T segments electric field is stable, only subtle changes are detectable by skin electrodes.Diastolic electric field forms after ventricular depolarization (T-P segments in the ECG recording). Telediastolic electric field forms after the atria have been depolarized (P-Q segments in the ECG recording). Systolic electric field forms after the ventricular depolarization (S-T segments in the ECG recording).The three ECG waves  can then be described as unbalanced transitions of the heart electric field from one stable configuration to the next and in that process the electric field center is temporarily displaced. In the initial phase of QRS, the rapidly diminishing septal electric field makes measured potentials dependent only on positive charges of the corresponding parts of the left and the right heart that lie within the lead axes. If more positive charges are near the "DOWN" electrode than near the "UP" electrode, a Q wave will be seen, otherwise an R wave is expected. Repolarization of the ventricular muscle is dampened by the early septal muscle repolarization that reduces deflection of T waves. Since the "UP" electrode of most leads is near the usually larger left ventricle muscle, T waves are in these leads positive, although of smaller amplitude and longer duration than the QRS wave in the same lead.The proposed interpretation is applied to bundle branch blocks, fascicular (hemi-) blocks and changes during heart muscle ischemia. Before describing here presented interpretation of the heart electric activity, some introductory remarks seem appropriate. Contemporary physiological and internal medicine textbooks use very similar interpretations of ECG -4. They Although this vector-based interpretation has been successfully used in teaching ECG basics for decades, the clinical practice remained focused on the ECG morphology and characteristic wave patterns instead on vectors. This discrepance between the basic ECG interpretation and clinical medicine is well described by a short statement by W. Jonathan Lederer :“Because the movement of charge  has both a three-dimensional direction and a magnitude, the signal measured on an ECG is a vector. The system that clinicians use to measure the heart's three-dimensional, time-dependent electrical vector is simple to understand and easy to implement, but it can be challenging to interpret.”Listing several clinically relevant topics not quite suited to the vector interpretation is not difficult. Here are just few examples:•Textbooks often mention direction of depolarization of the spreading wave: if it is perpendicular to the ECG lead, no voltage is recorded, if it is “approaching” the “positive” (+) electrode, the voltage will be positive, if it is “moving” toward the “negative” (-) electrode, the voltage will be negative.∘ An example of this interpretation can be found in Boron : “…we ca•ECG of patients with myocard ischemia show a very peculiar evolution of changes that include S-T elevation, T wave inversion, emergence of Q waves etc. -4, most •QRS morphology is characteristically altered and prolonged in bundle branch blocks, while in patients with a fascicular block of the left bundle branch (often referred as “hemiblocks”) only the heart electric axis is deviated, while the QRS is not prolonged .•QRS amplitude is routinely used to detect ventricle hypertrophy in our patients, although direct reciprocity of electric amplitude and the heart muscle mass is not clearly present. Explaining higher and prolonged voltage surges recorded during some ventricular premature beats, even in person with normally sized hearts is not easy.During 25 years of teaching the Guyton’s preclinical ECG interpretation to medical students and other profiles of health professionals and working as a clinician, these listed “vector resistant” ECG topics have often made me wander whether the vector interpretation of ECG is fully valid. The turning point was the paper by Harland CJ et al. ]. Be]. BeHear -90 mV ]. Th]. Be]. B.... studies of the precordial leads are reported which were designed to determine whether these deflections are principally measurements of the electrical field of the heart as a whole or are dominated by the forces from the region of the heart immediately beneath the electrode. It was found that the former was the case, which leads to a simpler and more rational method for interpreting the electrocardiogram than has been available heretofore.”During T-P, P-R and S-T segments electric field is stable and only subtle changes can be detected by skin electrodes. These small changes of electric fields can electromagnetically induce only very weak magnetic activity, detectable by MCG . OverallIt is important that any electrostatic field is by definition irrotational, conservative vector field analogous to gravity, possible to be described as the gradient of electrostatic potential, a scalar function. This approach gives us the opportunity to abandon the vector concept when discussing these three “isoelectric” ECG segments.On the other hand, moving charges produce both magnetic and electric forces, united in the electromagnetic field. Then the three ECG waves  can be described as electrodynamic bursts while the heart electric field shifts from one stable configuration to the next. These shifts have already been considered analogous to the waves achieved in a packed football stadium, often referred as "the Mexican wave" , that haOne might argue that electrostatic field could not be maintained since body tissues and fluids are electrically conductive. Keeping in mind that only continuous ion pumping and ion leakages make our cells “pseudoelectrets” is important. Although redistribution of the surrounding ions probably dampens the pericellular electric field, some fraction of the field spreads further due to electrostatic induction of remote structures. The result is that skin electrodes detect brain or heart activity. This means that despite free ion fluxes in body fluids, all cells act as small sources of electric positive charges and these sources fuse and form unified electric fields that surround brain, heart and other organs. Electric fields that emanate around animal bodies are important for prey detection by electroreception found in various aquatic or amphibious predators .Then the heart cycle electric activity can be described as changes in the electric field magnitude and shape during ECG waves, while the field remains nearly stable during the three isoelectric segments of the ECG line.The presented interpretation is based on several assumptions:•The fact that electric potential sensors can record the heart electric activity, even from distance , suggest∘ If we put two electrodes on the opposite sides of the body, as in Frank and other triaxial ECG recordings, each pair of electrodes will measure potential difference even if there is no electric activity since the distribution of electric charges between the electrodes form sources of electric fields that unite into the thoracic electric field.– This means that any bipolar lead measures the momentary electric field distribution along its axis with temporary negative or positive displacements during ECG waves from the “isoelectric line”. Conventionally, ECG electrodes are labeled as “positive” or “negative”, but in Table ▪ Bipolar ECG leads: in lead I, the “UP” deflection directs to the left side and “DOWN” to the right side. For leads II and III, the “UP” deflection is toward the heart apex and “DOWN” toward the heart base.▪ Unipolar ECG leads:∗ For aVL, aVR and aVF, the “UP” deflection points in the direction of the particular extremity, while the “DOWN” deflection points somewhere in the middle of other two extremities.∗ In precordial lads, V1 to V6, the “UP” deflection points more peripherally, to the chest wall, to the chest electrode, while the “DOWN” deflection points toward the central terminal, the referent value that simulates electric potential in the heart center [t center . In otheThe basic idea of the presented interpretation is that ECG continuously measures position of the thoracic electric field center. This field changes its shape, position and strength due to heart electric and pumping electricity, but at any moment, the measured potential difference necessarily reflects only momentary distribution of mainly positive charges in tissues lying between the electrodes.+ ions diffuse from the cell and this surplus of cations on the outer and deficit on the inner membrane side together generate the membrane electric potential. This means that cells from most organs and tissues act as small sources of POSITIVE electric charge (the negative charges remain hidden within each cell).In most cells some KThe highest outwardly positive membrane potentials reach 80 to 90 mV in neurons, skeletal and heart muscle cells ,2, makinThe heart muscle electric activity is different ,2. The sThis all means that the electric potential of a certain point on the body surface or near it is a scalar value, a situation analogous to the temperature distribution through space, or to the pressure distribution in a fluid.The presented interpretation is based on the idea that thoracic tissues produce a positive electric field that emanates from two concentric structures: the thoracic wall and the heart itself. This means that the center of the thoracic electric field changes its position during systole and diastole mainly due to changes in heart muscle polarization, since the outer envelope of electric charges comes from resting thoracic skeletal muscles, sources of an almost unaltered positive electrostatic field.The term attractor is here used to describe a setting toward which the thoracic electric field tends to evolve, but without the necessity that the process of changing the thoracic field center position is periodic or chaotic. Perhaps the best description might be that the ECG data from consecutive heart cycles virtually obey an almost periodic function. This means that ECG data appear to retrace their space trajectories within a given accuracy.Better to illustrate this point, high resolution (1 KHz sampling rate) a triaxial ECG was recorded from a healthy 50 years old male (the author’s own ECG recording). Six isoelectric segments of 50 ms were isolated from 100 consecutive heart cycles . The field consists of the thoracic wall and completely repolarised heart muscle . These transitions are not smooth, symmetric or homogenous, so the electric field center becomes momentarily displaced and this offset causes the three characteristic ECG waves.In normal individuals, the described attractors are expected to be so near each other in space that in all leads the three correspondent ECG segments form a virtually single “isoelectric line”. In here presented interpretation, the three isoelectric segments are near each other due to concentric anatomical structures and the anchoring effect of the repolarised septal muscle that will be later described in details.Several conditions that compromise tissue distribution within thorax and/or myocard capacity to depolarize or repolarize can normally offset the systolic attractor from the diastolic and telediastolic attractors. This is evident in the ECG recording as the ST elevation -4,16  wall, the septal muscle as the next, more remote source and lastly the right ventricular (RV) wall, it is understandable that for the “UP” electrode, the RV wall is the weakest electric source. The opposite “DOWN” electrode “sees” the sources in the opposite sequence: proximal is the RV wall, then septum and finally the remote LV wall Table .∘ In individuals with normal anatomy, the “UP” electrode measures higher potential than the “DOWN” electrode and the diastolic potential difference will be slightly higher at the “UP” electrode.•In the moment of the initial QRS, the septal muscle is depolarized , while both LV and RV walls are still repolarised. This means that the septal muscle electrically speaking “vanishes” from the thoracic electric field and then field potential will become relatively more positive (UP) than was the P-R potential, if the LV wall is healthy, thicker and closer to the “UP” electrode than is the RV wall to the “DOWN” electrode. This will result in an R wave, but if the LV wall is damaged, or there is more electric activity in the hypertrophic RV wall, a Q wave will appear.This interpretation postulates that presence of positively charged septal heart muscle during T-P and P-R segments makes the entire heart electric field more homogenous. Depolarized septal muscle during the initial QRS allows Q to be visible if the repolarised nonseptal heart muscle near the “DOWN” electrode prevails over the similar muscle near the “UP” electrode. Since in our leads almost all “UP” electrodes are monitoring the normally stronger LV wall, any Q usually means that the LV wall electric function is somehow altered and the opposite heart structures prevail in the early phase of QRS.Repolarization of the ventricular muscle is not initiated through the conductive system so it takes place when muscle cells become ready for depolarization. This process is dampened by the early septal muscle repolarization that reduces amplitude of T waves. The consequence is that since the “UP” electrode of most leads is near the usually larger left ventricle muscle, T waves are in these leads positive, although of smaller amplitude and longer duration than the QRS wave in the same lead.As it is already mentioned in the introductory section of this paper, the challenge of the proposed interpretation is to apply it to clinical entities that are not clearly explained by the conventional vectorial description. Tables Although we often attribute at least the P and QRS waves to the conductive tissue activity, here presented interpretation is based on the idea that almost no electric activity in the conductive tissue is directly evident in the skin surface ECG. Instead of that, ECG traces changes in the position of the thoracic electric field center, so only polarization changes of the large portions of the working heart muscle are detectable.Although P waves are simultaneous with atrial depolarization, a plausible explanation is that the initial P wave stroke is caused by the displacement of the electric field center toward the heart apex, due to weak negative potential of the atrial muscle. The other part of the P wave can be explained as a hemodynamic change, ventricles are further enlarged due to atrial systole and this moves the electric field center near the initial position, so P-R remains near the T-P segment.rd heart sound.The similar logic is applicable to other ECG waves. Even H wave  and U waStarting clinical examples with the bundle branch blocks seems appropriate. From the AV node the electrical impulse travels down the Bundle of His and divides into the right and left bundle branches, so bundle branch blocks occur when one branch is interrupted. In leads that show the bundle branch block, T waves are usually deflected opposite the terminal deflection of the QRS complex.The right bundle branch block is characterized by the widened QRS complex that also shows an extra deflection in the right precordial leads the V1 lead) [ lead 1-. The conIf we consider bundle branch fascicles, the situation becomes more complex -4. SinceIf only one fascicle is interrupted, the left ventricle can still be quickly depolarized from the remaining fascicle. The QRS complex is not widened but the QRS electric axis shows the active fascicle. Left anterior fascicular block causes left axis deviation, while posterior fascicular block causes right deviation.In the anterior fascicle block, the QRS complex in the lead aVF becomes overall negative (often described as the left deviation of the heart electric axes) and small Q waves can also be seen in leads I and aVL. In the posterior fascicle block, the QRS complexes in the lead I become overall negative (the right axes deviation) while qR complexes are found in leads II, III and aVF -4.Here presented interpretation of fascicular left bundle branch blocks is that we are dealing with an almost normal ventricle depolarization during which the left ventricle depolarization is unidirectional. Due to unidirectional left ventricle depolarization through only one fascicle, the initial part of QRS shows displacement of the electric field center toward the blocked fascicle since this part of the LV remains positive, while the normally stimulated part depolarizes.In the anterior fascicle block, the electric field center moves dorsally, then left and returns through the anteroseptal segment , In the posterior fascicle block, the electric field center moves in the opposite direction: from anteroseptal to the left and to the dorsal segment . These depolarization routes deviate the electric axis from the intermediary position .The origin of small q-waves due to anterior hemiblock in leads I and aVL can be explained by the reduced quantity of positive charges near the “UP” electrode of the leads I and aVL moves the electric field center toward the “DOWN” electrode on the right arm. Similar interpretation is for the posterior hemiblock. The left ventricle depolarization through the anterior fascicle in the initial part of QRS reduces quantity of positive charges near the “UP” electrode of the II, III aVF leads that is on the left leg. This moves the electric field center toward the “DOWN” electrodes . These changes are visible as small Q wave in these three leads.It must be noted that when both fascicles are active, their simultaneous actions make the left ventricle depolarization more balanced and any Q wave is normally not visible in the mentioned leads, since depolarization of the septal muscle is not followed by the electric center displacement toward the “DOWN” electrode. Instead of that, the center moves toward the remaining polarized muscle, closer to the “UP” electrode, resulting in the initially “up” deflection, or an R wave in the mentioned leads.Electrocardiographic changes in patients with acute coronary syndrome show specific evolution. Tables Often the first change is the emergence of hyperacute T waves that can be interpreted as altered repolarization of the involved left ventricle area that is out of phase with the still normal repolarization of the right ventricle and septal muscle, making the left ventricle repolarization more prominent.The characteristic ST-segment elevation is interpreted as altered systolic and diastolic distributions of ventricular charges. Any asymmetry in the systolic or in the diastolic ventricular electric field changes the position of the thoracic field center in that heart cycle phase and this offset is visible as the ST-segment elevation. A similar situation of ST elevations often found in cases of left ventricle aneurysm that would make the diastolic distribution asymmetric and different from the systolic distribution.Pathologic Q wave appearances are conventionally attributed to necrosis of the heart muscle. In the presented interpretation the Q wave mechanism is the same for ischemic and other Q waves. In the early systole, the septal muscle positive electric field disappears due to depolarization and this leaves charges in peripheral ventricular walls to struggle for electric balance. This short phase of imbalanced thoracic electric field is ECG evident as the QRS complex and if positive charges of the right heart side temporary prevail over the reduced positive charges of the corresponding part of the left heart muscle, a Q wave will occur.This can happen in all three bipolar leads and aVL, aVR and aVF leads. For unipolar precordial leads, if central tissues (mainly the right ventricle) have more positive charges than the peripheral tissue  Q will emerge in precordial V3 to V6 leads. For the “coronary” Q wave it is proposed that immediately after the septal muscle is depolarized, ischemia of the left ventricle wall reduces quantity of positive charges near the "UP" electrode and thus allows the heart muscle near the “DOWN” electrode to prevail during depolarization.Similar interpretation is found for the inverted T waves. Left ventricle wall ischemia reduces quantity of tissue able to repolarise near the "UP" electrode. This deficit allows the septal and right ventricle muscles near the “DOWN” electrode to prevail and thus inverse T waves.Combination of pathologic Q waves and upright T waves is usually attributed to fibrosis. Here proposed interpretation is that the remaining left ventricle muscle tissue recovers and starts repolarization (positive T waves), although remaining unable to prevail over the right ventricle muscle near the “DOWN” electrode during early depolarization.Q waves may get smaller or disappear with time. This can be interpreted consequently of cicatrisation that physically reduces the electrically "dead" area, so the surrounding muscle can better oppose the still prevailing right ventricle muscle, leading to smaller Q waves.The author declares that he has no competing interests.


Background. Prevalence of the metabolic syndrome is increasing in pediatric age groups worldwide. Meeting the criteria for the metabolic syndrome puts children at risk for later cardiovascular and metabolic disease. Methods. Using linear regression, we examined the association between infant weight gain from birth to 3 months and risk for the metabolic syndrome among 16- to 17-year-old Chilean adolescents (n = 357), accounting for the extent of breastfeeding in infancy and known covariates including gender, birth weight, and socioeconomic status. Results. Participants were approximately half male (51%), born at 40 weeks of gestation weighing 3.5 kg, and 48% were exclusively breastfed for ≥90 days. Factors independently associated with increased risk of metabolic syndrome in adolescence were faster weight gain in the first 3 months of life  and male gender . Breastfeeding as the sole source of milk for ≥90 days was associated with significantly decreased risk of metabolic syndrome (B = −0.16). Conclusion. This study adds to current knowledge about early infant growth and breastfeeding and their long-term health effects. As the prevalence of obesity in children and adolescents has escalated worldwide, signs of the metabolic syndrome (MetS) are increasingly observed in the pediatric age range . MetS reA large body of evidence suggests that metabolic programming can occur early in life –8. EarlyMuch of the work on fetal origins of disease has been done in developed countries beginning with Barker's work in England . ResearcP < 0.05). The longitudinal study has been approved by the institutional review boards of the University of Michigan, Ann Arbor USA; Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile for each wave of study; by the University of California, San Diego, for the 16-year study of obesity and cardiovascular risk.This is an observational cohort study involving adolescents who were enrolled as infants in a randomized controlled trial of iron supplementation to prevent iron deficiency anemia. Infants were enrolled from 1991–1996 in Santiago, Chile; 1657 infants completed the preventive trial at 1 year. The inclusion criteria for the preventive trial were infant birth weight of 3 kg or more, with no birth complications, major congenital abnormalities, or prior iron therapy. Due to a highly successful national breastfeeding campaign, all but 8 infants in the cohort were initially breastfed. Infants were randomly assigned to low or high iron supplementation, or usual nutrition (no added iron). A more detailed description of randomization techniques, sampling, and entrance and exclusion criteria is published elsewhere . The parWe included the following infancy measures: gender, weight measured at birth and at 3 months, and date of the first supplemental bottle. Maternal education was used as a proxy for SES. Mother's prepregnancy BMI was calculated from measured height and self-report of prepregnancy weight. Data on pre-pregnancy weight was not collected for the infancy study. During the 10-year wave of data collection, mothers reported their pre-pregnancy weight; it was highly correlated with their actual weight 10 years later. Adolescents were assessed between 16 and 17 years during the fourth wave of the longitudinal research study . Height (cm), weight (kg), waist and hip circumference (cm), and blood pressure (mm Hg) were measured by a physician-investigator at the nutrition research center. Standardized procedures  were usez-score according to the work of Brage and colleagues  at 3-month birth weight [kg])/(age at 3-month measurement ∗ 91.3 days). Extent of breastfeeding was assessed as a dichotomous variable representing breastfeeding without bottle supplementation for less than 90 days, compared to 90 days or more. Data was not available on introduction of complementary foods. Maternal education was assessed as a continuous measure (median for sample = 10 years). We constructed a metabolic syndrome risk lleagues . The folFor descriptive statistics, continuous variables were expressed as median and interquartile ranges and categorical variables as frequencies. We evaluated cardio/metabolic risk factors and overall prevalence of the MetS according to International Diabetes Federation definition : waist cP value of <0.05 denoted statistical significance. Multiple linear regression models were used to determine the relationship between change in weight (kg) in the first 3 months and metabolic syndrome risk z-score, adjusting for extent of breastfeeding and the following covariates: birth weight, gender, SES, age, mother's age at birth of infant, mother's pre-pregnancy BMI, and family history of type 2 diabetes, dyslipidemia, and heart attack. We tested the full model and then, using backward elimination, removed each variable that was not significantly related to the outcome in the model based on a significant P value of <0.05. As the sample came from an iron-deficient anemia prevention trial, we tested whether iron-deficient anemia during the first year of life or iron supplementation were significant covariates in our models. Neither variable showed significant relationship in the models and were thus removed from the final models. We used SPSS for Windows version 18.0 , a z-scores than females. There were no significant differences between males and females in gestational age, birth weight, maternal education, exclusive breastfeeding for ≥90 days, and prevalence of the MetS. Participants were assessed at a mean age of 16.6 years. Males and females represented about 51% and 49% of the sample, respectively. Participants had been born at 40 weeks of gestation weighing 3.5 kg, on average, and 48% were exclusively breastfed for ≥90 days. The median BMI percentile was 68.7 with 15.2% in the obese range and 10.4% met criteria for MetS. B = 0.16, 95%  CI = 0.04, 0.27, P < 0.05). Introduction of the first bottle at 90 days or after was related to a lower MetS risk score in adolescence , taking into account other covariates. Additionally, being male was associated with an increased MetS risk score in the model . The final model explained 9% of the variance in MetS risk.The multiple variable linear regression models  are shown in We examined weight gain in the first 3 months of life and timing of bottle supplementation related to MetS risk at 16 years. In both sexes, adolescents who had more rapid weight gain during the first 3 months of infancy had higher adolescent MetS risk scores compared to those who gained less weight in early infancy. The association of weight gain with MetS risk is consistent with findings from a study addressing the same question, in a Scandinavian country . InfancyThere is accumulating evidence that breastfeeding offers some protection related to the development of obesity, and that the effect may be “dose-dependent” , 29. BecWe do not know why males had higher MetS risk scores compared to females, but they had marginally significant higher birth weights and gained more weight in the first 3 months. Nonetheless, the effect of gender on MetS was independent of birth weight and infancy weight gain. This finding is consistent with higher prevalence rates of MetS in men compared to women in Chile . In US aOur study has several limitations. The cohort was enrolled from a low- to middle-income community in Santiago, Chile, during a period of economic and nutritional transition. The setting and the fact that children with birth weights under 3 kg were not included limits generalizability. The study also has many strengths. The context of economic growth, high rates of breastfeeding, and nutritional support for infants allowed us to assess a sample where malnutrition was not a confounding factor. The longitudinal study took place at a nutrition research center allowing for detailed anthropometric measurement during infancy and the adolescent wave of data collection. Other strengths of the study include prospective data collection including monthly anthropometry in infancy and breastfeeding data collected from 4 to 12 months. In addition, the adolescent data collection included family history of diabetes, hypertension, elevated cholesterol, and heart attack.In conclusion, this study adds to the current knowledge about early infant growth and breastfeeding and their long-term health effects. Higher infant weight gain was associated with increased MetS risk, whereas longer duration of exclusive breastfeeding was protective in healthy adolescents living in a rapidly developing country. Considering the increasing prevalence of the MetS in younger age groups and associations between the MetS and later disease, the replication and validation of these findings in different contexts is warranted.


Balamuthia amoebic encephalitis (BAE) is a serious human disease almost always leading to death. An important step in BAE is amoebae invasion of the bloodstream, followed by their haematogenous spread. Balamuthia mandrillaris entry into the central nervous system (CNS) most likely occurs at the blood–brain barrier (BBB) sites. Macrophages are thought to be the first line of defense in many infectious diseases and are present in high numbers during infections. The objective of the present study was to determine the impact of cytokines and macrophages on the virulence characteristics of B. mandrillaris in vitro.In vitro, B. mandrillaris were used to demonstrate the effects of cytokines and macrophages on the physiological and morphological characteristics of amoeba. Using human brain microvascular endothelial cells (HBMEC), which constitutes the BBB, adhesion and cytotoxicity assays were performed. To investigate the engulfing property and proteolytic activity of the amoeba, phagocytosis and zymography assays were conducted respectively.B. mandrillaris exhibited >90 % binding and >70 % cytotoxicity to HBMEC which was further enhanced in the presence of cytokines and macrophages. It has also been observed that cytokines TNF-α and TGF-β significantly increased the B. mandrillaris numbers in the presence of macrophages. It is important to note that amoebic numbers were more than doubled in the presence of cytokines and macrophages within 24h. We have shown in the past the bacteria uptake by B. mandrillaris is limited which is further significantly inhibited in the presence of cytokines during phagocytosis assays. Zymography assays revealed that cytokines and macrophages have no inhibitory effect on proteolytic activity of B. mandrillaris. In addition the activated macrophages did not show any vital effects on amoebic virulence properties.It was observed B. mandrillaris in vitro.Overall we described for the first time that cytokines and macrophages has no inhibitory effects on the virulence properties of


In a systematic review and meta-analysis, Jasper Been and colleagues investigate the association between preterm birth and the development of wheezing disorders in childhood.Please see later in the article for the Editors' Summary Accumulating evidence implicates early life factors in the aetiology of non-communicable diseases, including asthma/wheezing disorders. We undertook a systematic review investigating risks of asthma/wheezing disorders in children born preterm, including the increasing numbers who, as a result of advances in neonatal care, now survive very preterm birth.Two reviewers independently searched seven online databases for contemporaneous (1 January 1995–23 September 2013) epidemiological studies investigating the association between preterm birth and asthma/wheezing disorders. Additional studies were identified through reference and citation searches, and contacting international experts. Quality appraisal was undertaken using the Effective Public Health Practice Project instrument. We pooled unadjusted and adjusted effect estimates using random-effects meta-analysis, investigated “dose–response” associations, and undertook subgroup, sensitivity, and meta-regression analyses to assess the robustness of associations. We identified 42 eligible studies from six continents. Twelve were excluded for population overlap, leaving 30 unique studies involving 1,543,639 children. Preterm birth was associated with an increased risk of wheezing disorders in unadjusted  and adjusted analyses . The risk was particularly high among children born very preterm . Findings were most pronounced for studies with low risk of bias and were consistent across sensitivity analyses. The estimated population-attributable risk of preterm birth for childhood wheezing disorders was ≥3.1%.Key limitations related to the paucity of data from low- and middle-income countries, and risk of residual confounding.There is compelling evidence that preterm birth—particularly very preterm birth—increases the risk of asthma. Given the projected global increases in children surviving preterm births, research now needs to focus on understanding underlying mechanisms, and then to translate these insights into the development of preventive interventions.CRD42013004965PROSPERO Please see later in the article for the Editors' Summary Most pregnancies last around 40 weeks, but worldwide, more than 11% of babies are born before 37 weeks of gestation (the period during which a baby develops in its mother's womb). Preterm birth is a major cause of infant death—more than 1 million babies die annually from preterm birth complications—and the number of preterm births is increasing globally. Multiple pregnancies, infections, and chronic (long-term) maternal conditions such as diabetes can all cause premature birth, but the cause of many preterm births is unknown. The most obvious immediate complication that is associated with preterm birth is respiratory distress syndrome. This breathing problem, which is more common in early preterm babies than in near-term babies, occurs because the lungs of premature babies are structurally immature and lack pulmonary surfactant, a unique mixture of lipids and proteins that coats the inner lining of the lungs and helps to prevent the collapse of the small air sacs in the lungs that absorb oxygen from the air. Consequently, preterm babies often need help with their breathing and oxygen supplementation.Improvements in the management of prematurity mean that more preterm babies survive today than in the past. However, accumulating evidence suggests that early life events are involved in the subsequent development of non-communicable diseases (non-infectious chronic diseases). Given the increasing burden of preterm birth, a better understanding of the long-term effects of preterm birth is essential. Here, the researchers investigate the risks of asthma and wheezing disorders in children who are born preterm by undertaking a systematic review  and a meta-analysis . Asthma is a chronic condition that is caused by inflammation of the airways. In people with asthma, the airways can react very strongly to allergens such as animal fur and to irritants such as cigarette smoke. Exercise, cold air, and infections can also trigger asthma attacks, which can sometimes be fatal. The symptoms of asthma include wheezing (a high-pitched whistling sound during breathing), coughing, chest tightness, and shortness of breath. Asthma cannot be cured, but drugs can relieve its symptoms and prevent acute asthma attacks.The researchers identified 30 studies undertaken between 1995 and the present  that investigated the association between preterm birth and asthma/wheezing disorders in more than 1.5 million children. Across the studies, 13.7% of preterm babies developed asthma/wheezing disorders during childhood, compared to only 8.3% of babies born at term. Thus, the risk of preterm babies developing asthma or a wheezing disorder during childhood was 1.71 times higher than the risk of term babies developing these conditions (an unadjusted odds ratio [OR] of 1.71). In analyses that allowed for confounding factors—other factors that affect the risk of developing asthma/wheezing disorders such as maternal smoking—the risk of preterm babies developing asthma or a wheezing disorder during childhood was 1.46 times higher than that of babies born at term (an adjusted OR of 1.46). Notably, compared to children born at term, children born very early (before 32 weeks of gestation) had about three times the risk of developing asthma/wheezing disorders in unadjusted and adjusted analyses. Finally, the population-attributable risk of preterm birth for childhood wheezing disorders was more than 3.1%. That is, if no preterm births had occurred, there would have been more than a 3.1% reduction in childhood wheezing disorders.These findings strongly suggest that preterm birth increases the risk of asthma and wheezing disorders during childhood and that the risk of asthma/wheezing disorders increases as the degree of prematurity increases. The accuracy of these findings may be affected, however, by residual confounding. That is, preterm children may share other, unknown characteristics that increase their risk of developing asthma/wheezing disorders. Moreover, the generalizability of these findings is limited by the lack of data from low- and middle-income countries. However, given the projected global increases in children surviving preterm births, these findings highlight the need to undertake research into the mechanisms underlying the association between preterm birth and asthma/wheezing disorders and the need to develop appropriate preventative and therapeutic measures.http://dx.doi.org/10.1371/journal.pmed.1001596.Please access these websites via the online version of this summary at preterm birth (in English and Spanish)The March of Dimes, a nonprofit organization for pregnancy and baby health, provides information on premature babies and on asthma Nemours, another nonprofit organization for child health, also provides information (in English and Spanish) on premature labor and birth and a real story about having a preterm baby; it provides information about asthma in children The UK National Health Service Choices website provides information about preterm birth, asthma, asthma in children, and wheezing (in English and Spanish); MedlinePlus provides links to further information on premature birth, asthma, and asthma in children (in English and Spanish)The MedlinePlus Encyclopedia has pages on  The impact of early life exposures on subsequent health and disease is increasingly recognised Respiratory distress syndrome is the most obvious direct manifestation of immaturity in preterm newborns. The combination of structural lung immaturity and pulmonary surfactant deficiency results in regional atelectasis and a varying degree of respiratory compromise Accumulating evidence now implicates preterm birth in the development of respiratory disease in later life. Small airway obstruction is evident through decreased forced expiratory volume in 1 s (FEV1) in children and adults born preterm We aimed to investigate the association between preterm birth and childhood wheezing disorders through a systematic review and meta-analysis of studies with populations born from the 1990s onwards. We focused on wheezing disorders in general rather than just asthma, given the difficulty in differentiating between the two, particularly among young children This review was performed following the methods detailed in a systematic review protocol registered with PROSPERO  and asthma or wheezing in children (aged 0.5 to 18 y). Studies reporting on populations that included children born before 1995 were eligible for inclusion only when at least 50% of the cohort was born from 1995 onwards and none of the children was born before 1990, so as to primarily include studies conducted in the period following the important changes in neonatal practice outlined earlier. When studies with overlapping data were identified, the most informative study was selected for inclusion in this report; the determination of which study was considered most informative was based on consensus, study size being an important determinant. Final study selection was based on a consensus decision between reviewers, with arbitration by a third reviewer in case of disagreement.Data were independently extracted from eligible studies by two reviewers (J. V. B. and M. J. L.); disagreements were resolved through discussion, with arbitration by a third reviewer if necessary (A. S.). The following study characteristics were extracted: authors, full reference, study design, location, sample size, inclusion and exclusion criteria, age range and birth year of study participants, method of ascertainment of exposure and outcomes, and outcome measure.Post-term (>42 wk gestation) births were excluded from the analyses, if possible. If studies reported follow-up at different time points, the most recent was selected. Similarly to previous work Absolute patient counts were extracted to compose 2×2 tables according to preterm birth and wheezing disorder status, and these were used to calculate univariate odds ratios (ORs); in instances where relevant crude data were missing, we approached authors to request these. If needed, count data were calculated from provided percentages, and these were then rounded off to the nearest integer. Adjusted association measures were extracted from the most adjusted model presented.Study quality was assessed independently by two investigators using the Effective Public Health Practice Project quality assessment tool for quantitative studies Univariate association measures were pooled using Mantel-Haenszel analysis. Random-effects models were applied because of anticipated heterogeneity given between-country variation in clinical practice and differences in inclusion and exclusion criteria, outcome specification, and ascertainment level of exposure and outcome. Adjusted association measures were pooled via random-effects generic inverse variance analysis. Standard errors for study point estimates were calculated from the respective 95% confidence intervals as described in the Cochrane Handbook Q-statistic and I2-test were used to assess heterogeneity among studies. Small-study effects were assessed using funnel plots and Harbord's modified regression test for unadjusted data and Egger's regression test for adjusted association measures.For studies reporting adjusted association measures according to multiple gestational age strata, the least preterm stratum was selected to obtain the most conservative estimate. In a separate analysis, a linear association between gestational age at birth and wheezing disorder risk was investigated, pooling individual studies by random-effects generic inverse variance analysis. For this purpose, adjusted association measures for multiple gestational age strata were aggregated within studies using a fixed-effects log-linear dose–response regression model Subgroup analyses were performed according to age group (<5 y versus ≥5 y) and degree of prematurity (<32 wk versus 32–36 wk). When studies reported the association between preterm birth and wheezing disorders for both subgroups , the corresponding association measures were included in both sides of the comparison.n<10,000 versus n≥10,000), and outcome definition (asthma versus wheezing) and ascertainment (clinician diagnosis and/or medication use versus parent-reported outcomes).Sensitivity analyses were performed according to risk of bias , study size , diagnosis ascertainment, and publication year on the association between preterm birth and wheezing disorders.Pe is the exposure prevalence and RRe is the relative risk due to exposure e was calculated as follows:PAR was calculated using the following formula:Analyses were performed using Stata 12 (StataCorp).The funders had no role in study design, collection, analysis, interpretation of the data, writing of the report, or decision to submit the work for publication.n = 4) n = 3) n = 2) n = 2) Forty-two eligible studies were identified Four studies were deemed to have low risk of bias, 12 had moderate risk of bias, and 14 had high risk of bias . Studiesp<0.001; Crude data were provided by authors of five studies p<0.001; Seventeen studies provided adjusted association measures that could be pooled in a meta-analysis . Although the variables for which individual studies adjusted varied , the majp<0.001) indicated a 6% (95% CI 4%–8%) decrease in wheezing disorder risk for every week increase in gestation length up to 40 wk.In order to investigate a possible “dose–response” relationship between gestational age at birth and wheezing disorder risk, we aggregated corresponding adjusted association measures from 17 studies . Aggregate ORs did not differ much between subgroups according to study size , diagnosis ascertainment , S12, orI2 values suggested that additional unmeasured factors contributed to between-study heterogeneity.To further investigate the independent effects of study size, population age, diagnosis ascertainment, wheezing type, and publication year, meta-regression analysis was performed. None of these factors had an independent effect on the strength of association between preterm birth and wheezing disorders . The modp = 0.55; unadjusted association measures) and Egger's test  revealed no important small-study effects potentially indicative of publication bias.Funnel plot asymmetry was minimal for both unadjusted and adjusted association measures . AccordiBased on unadjusted association measures, the PAR for childhood wheezing disorders associated with preterm birth was estimated at 4.0% overall, comprising 1.6% (95% CI 1.3%–1.9%) for very preterm birth and 2.4% (95% CI 1.7%–3.1%) for moderately preterm birth. PAR based on adjusted association measures was 3.1%: 1.2% (95% CI 1.1%–1.3%) for very preterm birth and an additional 1.9% (95% CI 1.0%–2.7%) for moderately preterm birth.In this meta-analysis of observational studies, using data from over 1.5 million children from across six continents, preterm birth was found to be associated with a 1.71 (95% CI 1.57–1.87) times increased risk of childhood wheezing disorders. The association was slightly attenuated by adjustment for potential confounding within individual studies . Additional analyses strongly support a dose–response relationship between length of gestation and wheezing disorders , with children born very preterm having three times the risk of that of children born at term . Consistency across sensitivity analyses further supports the robustness of the findings. Moderate preterm birth accounted for the majority of the explained variation in childhood wheezing disorders by preterm birth. Together, these findings are in line with the increasing recognition of the impact that early life influences have on subsequent health and disease, including pulmonary outcomes As with any systematic review we cannot exclude the possibility that potentially relevant studies were missed by our search strategy, although it included the primary online databases for medical research and the most rational search terms relevant to the research question. Identification of additional studies was performed through screening of reference lists and citations, and contacting an international panel of experts. Absence of important small-study effects suggests that bias resulting from selective study inclusion is likely to be minor.I2 values suggested that considerable heterogeneity was present among the studies included in the meta-analysis, although these values may be inflated by the inclusion of some very large studies I2 values in subgroup analyses according to age group suggest that between-study population age differences may contribute. Variation furthermore exists among doctors and parents, and between doctors and parents regarding the definition and perception of wheeze, as well as asthma. We therefore performed sensitivity analyses separating wheezing from asthma, and physician diagnoses from parental reports. The results suggest that, although perceptions may differ, this did not affect the estimation of the association between preterm birth and childhood wheezing disorders. Indeed, residual heterogeneity remained after adjustment for these and other factors via meta-regression analysis. Although study quality may be another responsible factor, the observation that aggregated association measures were most pronounced in studies with low risk of bias supports the validity of the conclusions.Several factors potentially confound the association between preterm birth and wheezing disorders Different methods for gestational age estimation exist. Although most studies failed to report their approach, first trimester ultrasound is increasingly used in higher income countries. Alternative estimation is usually based on the last menstrual period, which is known to overestimate the numbers of preterm and post-term births In a previous meta-analysis, preterm birth was associated with a 1.37 (95% CI 1.30–1.43) times increased risk of asthma The current findings do not support prior suggestions that the association between preterm birth and wheezing disorders becomes less prominent with increasing age The processes underlying preterm birth are poorly understood The magnitude of the problem having been established, there is now a pressing need to address several knowledge gaps. Epidemiological studies should concentrate on temporal tracking of respiratory status into adulthood following preterm birth, with particular focus on different wheezing phenotypes, and estimating the relative impact of distinct early life factors on these patterns. Recent accomplishments in combining European birth cohorts can help provide the required numbers This work provides compelling evidence that preterm birth is an important early life risk factor for wheezing disorders in childhood. Given the increasing incidence of both entities and their potentially lifelong consequences, there is an urgent need to identify the underlying mechanisms and explore the potential for preventive and therapeutic approaches.Checklist S1PRISMA checklist.(DOC)Click here for additional data file.Figure S1Meta-analysis of unadjusted association between preterm birth and childhood wheezing disorders according to age group. Since estimates from Boyle I2 (<5 y) = 56% (95% CI 0%–76%); I2 (≥5 y) = 48% (95% CI 0%–72%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S2Meta-analysis of adjusted association between preterm birth and childhood wheezing disorders according to age group. Since estimates from Boyle I2 (<5 y) = 31% (95% CI 0%–77%); I2 (≥5 y) = 41% (95% CI 0%–69%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S3Meta-analysis of adjusted dose–response association between gestational age (per week increase) and childhood wheezing disorders according to age group. Since estimates from Boyle I2 (<5 y) = 0% (95% CI 0%–68%); I2 (≥5 y) = 37% (95% CI 0%–69%). WD, wheezing disorders.(TIF)Click here for additional data file.Figure S4Meta-analysis of unadjusted association between preterm birth and childhood wheezing disorders according to risk of bias. Heterogeneity: I2 (high risk of bias) = 60% (95% CI 10%–77%); I2 (moderate risk of bias) = 63% (95% CI 0%–80%); I2 (low risk of bias) = 0% (95% CI 0%–68%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S5Meta-analysis of adjusted association between preterm birth and childhood wheezing disorders according to risk of bias. Subgroups taken from individual studies noted in parentheses. Confounders adjusted for in individual studies are outlined in I2 (high risk of bias) = 56% (95% CI 0%–82%); I2 (moderate risk of bias) = 46% (95% CI 0%–73%); I2 (low risk of bias) = 0% (95% CI 0%–68%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S6Meta-analysis of adjusted dose–response association between gestational age (per week increase) and childhood wheezing disorders according to risk of bias. Confounders adjusted for in individual studies are outlined in I2 (high risk of bias) = 39% (95% CI 0%–76%); I2 (moderate risk of bias) = 63% (95% CI 0%–81%); I2 (low risk of bias) = 8% (95% CI 2%–90%). WD, wheezing disorders.(TIF)Click here for additional data file.Figure S7Meta-analysis of unadjusted association between preterm birth and childhood wheezing disorders according to study size. Heterogeneity: I2  = 47% (95% CI 0%–67%); I2  = 95% (95% CI 93%–97%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S8Meta-analysis of adjusted association between preterm birth and childhood wheezing disorders according to study size. Subgroups taken from individual studies noted in parentheses. Confounders adjusted for in individual studies are outlined in I2  = 42% (95% CI 0%–68%); I2  = 94% (95% CI 89%–96%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S9Meta-analysis of adjusted dose–response association between gestational age (per week increase) and childhood wheezing disorders according to study size. Confounders adjusted for in individual studies are outlined in I2  = 39% (95% CI 0%–68%); I2  = 97% (95% CI 95%–98%). WD, wheezing disorders.(TIF)Click here for additional data file.Figure S10Meta-analysis of unadjusted association between preterm birth and childhood wheezing disorders according to diagnosis ascertainment. Heterogeneity: I2 (parent reported) = 19% (95% CI 0%–55%); I2 (doctor diagnosed) = 93% (95% CI 89%–95%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S11Meta-analysis of adjusted association between preterm birth and childhood wheezing disorders according to diagnosis ascertainment. Subgroups taken from individual studies noted in parentheses. Confounders adjusted for in individual studies are outlined in I2 (parent reported) = 43% (95% CI 0%–71%); I2 (doctor diagnosed) = 90% (95% CI 82%–93%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S12Meta-analysis of adjusted dose–response association between gestational age (per week increase) and childhood wheezing disorders according to diagnosis ascertainment. Confounders adjusted for in individual studies are outlined in I2 (parent reported) = 54% (95% CI 0%–76%); I2 (doctor diagnosed) = 95% (95% CI 92%–96%). WD, wheezing disorders.(TIF)Click here for additional data file.Figure S13Meta-analysis of unadjusted association between preterm birth and childhood wheezing disorders according to wheezing type. Heterogeneity: I2 (wheezing) = 52% (95% CI 0%–76%); I2 (asthma) = 86% (95% CI 79%–90%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S14Meta-analysis of adjusted association between preterm birth and childhood wheezing disorders according to wheezing type. Subgroups taken from individual studies noted in parentheses. Confounders adjusted for in individual studies are outlined in I2 (wheezing) = 41% (95% CI 0%–74%); I2 (asthma) = 86% (95% CI 76%–90%). PTB, preterm birth; WD, wheezing disorders.(TIF)Click here for additional data file.Figure S15Meta-analysis of adjusted dose–response association between gestational age (per week increase) and childhood wheezing disorders according to wheezing type. Confounders adjusted for in individual studies are outlined in I2 (wheezing) = 52% (95% CI 0%–78%); I2 (asthma) = 92% (95% CI 87%–94%). WD, wheezing disorders.(TIF)Click here for additional data file.Table S1Characteristics of studies excluded because of population overlap. *Selected inhaled or systemic adrenergics, anticholinergics, xantines, antiallergics, leukotriene receptor antagonists, and/or steroids; ** as compared to preterm babies without BPD. GA, gestational age; KFHP, Kaiser Foundation Health Plan; KPMCP, Kaiser Permanente Medical Care Program; N/R, not reported; LMP, last menstrual period; SD, standard deviation.(DOCX)Click here for additional data file.Table S2Assessment of study quality. Scoring according to the Effective Public Health Practice Project quality assessment tool for quantitative studies. For study design “7” indicates cross-sectional design in all cases. N/A, not applicable.(DOCX)Click here for additional data file.Table S3Covariates in multivariate models of individual studies associating preterm birth with wheezing disorders.amonth of conception, maternal urinary tract infection, pre-labour rupture of membranes, prostaglandin induction, neonatal jaundice, neonatal sepsis; bthreatened miscarriage, infections, asphyxia, birth trauma, premature rupture of membranes, umbilical cord knots, placenta problems; cCC10 G+38A polymorphisms, cord blood IgE.(DOCX)Click here for additional data file.Text S1PROSPERO-registered review protocol.(PDF)Click here for additional data file.Text S2Expert panel.(DOCX)Click here for additional data file.


It remains unclear whether it is more detrimental to be born too early or too small in relation to symptoms of attention deficit/hyperactivity disorder (ADHD). Thus, we tested whether preterm birth and small body size at birth adjusted for gestational age are independently associated with symptoms of ADHD in children.A longitudinal regional birth cohort study comprising 1535 live-born infants between 03/15/1985 and 03/14/1986 admitted to the neonatal wards and 658 randomly recruited non-admitted infants, in Finland. The present study sample comprised 828 children followed up to 56 months. The association between birth status and parent-rated ADHD symptoms of the child was analysed with multiple linear and logistic regression analyses.Neither prematurity (birth < 37 weeks of gestation) nor lower gestational age was associated with ADHD symptoms. However, small for gestational age (SGA < -2 standard deviations [SD] below the mean for weight at birth) status and lower birth weight SD score were significantly, and independently of gestational age, associated with higher ADHD symptoms. Those born SGA, relative to those born AGA, were also 3.60-times more likely to have ADHD symptoms scores above the clinical cut-off. The associations were not confounded by factors implicated as risks for pregnancy and/or ADHD.per se, may increase risk for symptoms of ADHD in young children.Intrauterine growth restriction, reflected in SGA status and lower birth weight, rather than prematurity or lower gestational age  This The study cohort comprised a subsample of 2193 infants participating in the Arvo Ylppö Longitudinal Study (AYLS) ,13. FiguP's < 0.02). Whereas, those lost to follow-up due to lack of parent rated ADHD symptoms had mothers who smoked more during pregnancy (P = 0.003).The study participants (n = 828) did not differ from those who were lost to follow-up due to lack of information on birth weight, gestational age or pre- and neonatal control variables (N = 88), and/or additionally due to lack of parent rated symptoms of ADHD (n = 941) in sex, multiple pregnancy, mother's age, height, BMI at the end of pregnancy or change in weight during pregnancy, in parental education or in admission to neonatal ward . Further, those lost to follow-up due to lack of parent rated ADHD symptoms did not differ from the participants in the current study in gestational age/preterm status or in birth weight standard deviations [SD]/SGA status . However, those lost to follow-up due to lack of information on pre- and neonatal variables were more likely to have been admitted to a neonatal ward, to come from less educated families, and their mothers smoked more during pregnancy ; for the remaining 157 (19.0%), gestational age was calculated from the date of the mother's last menstrual period. In addition, all infants were given a Dubowitz assessment of gestational age . When thData on the newborns' weight (g) were extracted from birth records. Birth weight was transformed into gestational age -adjusted standard deviation (SD) scores according to Finnish growth charts. Children born < -2 SDs of the mean for weight at birth  were classified as SGA . The remAt the 56-month follow-up the parents evaluated the child's behavioural symptoms of ADHD with the Conners' Hyperactivity Index-parent version . This inversus term birth, and of SGA versus AGA status on ADHD symptoms were confounded by the child's sex, multiple pregnancy (singleton vs. multiple), mother's smoking during pregnancy , parental education , maternal age (yrs), maternal height (cm), maternal body mass index (kg/m2) at the end of pregnancy and change in weight (kg) during the pregnancy. In addition, as symptoms of ADHD and cognitive performance are associated [We tested if the effects of preterm sociated  we analysociated ,19. The sociated  and it hsociated ,20.As the primary data analytical tools, we used multiple linear regression analysis (symptoms of ADHD as continuous measure) and logistic regression analysis  . We examTo test whether any potential differences in ADHD symptoms of children born preterm and term, and SGA and AGA were independent of each other, both these dichotomous variables were entered simultaneously into the regression equation. To test for interactional effects, an interaction term 'preterm/term status × SGA/AGA status' was entered into regression equation in addition to the main effects of these two dichotomous variables.Further, to test whether associations differed between boys and girls an interaction term 'sex × preterm/term', and 'sex × SGA/AGA-status' was entered into regression equation in addition to the main effects of these variables.All analyses were also run using gestational age and birth weight SD scores as continuous variables.versus term birth and SGA versus AGA status are presented in Tables Characteristics of the sample according to preterm Table Table There were no significant 'preterm/term- × SGA/AGA-status' or 'gestational age × birth weight SD score' - interactions . Neither were there any significant sex-specific associations .Finally, the analyses were re-run excluding children from multiple pregnancies (n = 44). The results remained virtually identical .per se, may pose a risk for symptoms of ADHD in young children.The present study showed that preterm birth (before 37+0 weeks of gestation) was not associated with higher parent-rated behavioural symptoms scores of ADHD at 56 months of age. However, being born SGA (< -2 SD) was associated with higher ADHD symptoms scores. Those born SGA, relative to those born AGA, were also over three times more likely to have ADHD symptoms scores above a cut-off indicative of a clinically significant level of symptoms. The findings were similar when gestational age and birth weight SD score were used as continuous variables: gestational age was not, while lower birth weight SD was associated with higher ADHD symptoms scores and with scores that were above the clinical cut-off. The effects of SGA status and birth weight SD score were independent of prematurity and gestational age. The effects were also not confounded by parent- or child-related characteristics that may pose a risk for pregnancy and/or ADHD or its symptoms. Our findings, thus, suggest that intrauterine growth restriction, as reflected in the SGA status and lower birth weight SD score, rather than prematurity or lower gestational age The current results are in line with previous findings suggesting that the children born SGA rather than those born AGA, may be the most vulnerable for displaying symptoms of ADHD later in life ,5-7. HowThe major strength of this study was the inclusion of well-defined gestational age and birth weight SD scores as dichotomous and continuous variables. Further, a number of parental- and child- related variables have been implicated as risks for pregnancy and/or symptoms of ADHD of the child. In the current study we could control for several of those factors. We also had extensive clinical data and thus could exclude children with severe neonatal or childhood conditions that could have potentially confounded the findings.There are some limitations to the study. For practical constraints several parents did not receive questionnaire of the child's ADHD symptoms at the 56 months follow-up or failed to fill it in . However, the participants in the present study did not differ from those lost to follow-up due to lack of information on ADHD symptoms, except that their mothers smoked less during pregnancy. Yet, there might be other unmeasured or unknown social factors that might have affected the five year outcome. In the light of the current confounders the found results may be more characteristic of children developing in more affluent prenatal environments.http://www.sotkanet.fi and school does not start before age of seven. Finally, we did not have any information on the parental behavioural symptoms of ADHD and were thus unable to adjust for the possible genetic susceptibility.Further, behavioural symptoms of ADHD were evaluated only by the parent and we did not have any information of the child's behaviour in different settings e.g., in day care. However, in Finland only approximately half of the children aged 3-5 were in a full-time day care in the nineties The underlying mechanisms explaining the association might be either biological or psychosocial, or both. Causes of both preterm birth and intrauterine growth restriction (IUGR) are multiple. Preterm labour/birth may be initiated by infection or inflammation, uteroplacental ischaemia or haemorrhage, uterine overdistension, stress, and other immunologically mediated processes . Even thEvidence exists also that brain structure differs in growth restricted infants. It has been shown for example that term-SGA children have a reduced total brain volume , and preMothers with low birth weight children are faced with challenges that impact their parenting and perceptions of their child . Mothersper se, may increase risk for symptoms of ADHD in young children. Future studies are needed to replicate these findings and clarify mechanisms underlying the found associations.Our study extends the existing literature by showing that intrauterine growth restriction, reflected in SGA status and lower birth weight SD score, rather than prematurity or lower gestational age The authors declare that they have no competing interests.KH and KR made substantial contributions to analysis and interpretation of data and have been involved in drafting the manuscript and revising it critically for important intellectual content. A-KP, SA, EK, EGJ have contributed to analysis and interpretation of data, and have been involved in revising manuscript critically for important intellectual content; DW has made substantial contributions to conception and design, and acquisition of data as well as to interpretation of data, and has revised manuscript critically for important intellectual content. AL has made substantial contributions acquisition of data and has been involved in revising manuscript critically for important intellectual content. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/10/91/prepub