Cytokines and chemokines are key signaling molecules of the immune system. Recent technological advances enable measurement of multiplexed cytokine profiles in biological samples. These profiles can then be used to identify potential biomarkers of a variety of clinical phenotypes. However, testing for such associations for each cytokine separately ignores the highly context-dependent covariation in cytokine secretion and decreases statistical power to detect associations due to multiple hypothesis testing. Here we present CytoMod—a novel data-driven approach for analysis of cytokine profiles that uses unsupervised clustering and regression to identify putative functional modules of co-signaling cytokines. Each module represents a biosignature of co-signaling cytokines. We applied this approach to three independent clinical cohorts of subjects naturally infected with influenza in which cytokine profiles and clinical phenotypes were collected. We found that in two out of three cohorts, cytokine modules were significantly associated with clinical phenotypes, and in many cases these associations were stronger than the associations of the individual cytokines within them. By comparing cytokine modules across datasets, we identified cytokine “cores”—specific subsets of co-expressed cytokines that clustered together across the three cohorts. Cytokine cores were also associated with clinical phenotypes. Interestingly, most of these cores were also co-expressed in a cohort of healthy controls, suggesting that in part, patterns of cytokine co-signaling may be generalizable. CytoMod can be readily applied to any cytokine profile dataset regardless of measurement technology, increases the statistical power to detect associations with clinical phenotypes and may help shed light on the complex co-signaling networks of cytokines in both health and infection. Cytokines and chemokines are key signaling molecules of the immune system, mediating a complex network of interacting cells that govern the immune response , 2. ThesStaphylococcus aureus.Influenza is a respiratory virus that accounts for significant rates of hospitalizations and deaths, especially among very young or old individuals . Due to Cytokine expression in response to influenza infection has been studied using human blood and nasal samples, immune cell cultures and animal models , 24. NumDespite our partial understanding of cytokine biology there are a variety of therapeutic treatments that target specific cytokines, which are in wide clinical use to treat autoimmune diseases and cancer. There are a variety of licensed monoclonal antibody (Ab) treatments that target cytokines or their receptors. Examples include: anti TNF-α Abs , 35, an Since cytokines and chemokines (hereafter referred to as cytokines) reflect the local or systemic immune state, they have the potential to serve as indicators of various clinical conditions. Various studies suggested the use of measurements of circulating cytokines as biomarkers in order to aid clinicians in patient prognosis and care –46. FurtWhile numerous studies have reported associations between cytokine levels and various clinical phenotypes, the analysis of cytokine profiles is often statistically underpowered to detect such associations, due to the large number of cytokines and the requirement for multiplicity adjustment. Furthermore, the relatively high-cost of cytokine profiles limits the sizes of cohorts for which they are measured. A typical cytokine profile dataset can have measurements obtained from tens to hundreds of subjects. These opposing trends make it increasingly important to develop new computational tools for analyzing cytokine profiles that are statistically efficient and provide interpretable results.One possible solution for preserving statistical power, is to select a small subset of cytokines for a primary analysis with phenotypes, with a secondary/exploratory analysis that includes all remaining cytokines. For example, in previous work on cytokine profiles following influenza natural infection we pre-selected a subset of 11 cytokines for the primary analyses based on published studies . MultiplAnother important property of cytokine signaling is its inherent redundancy , 50. ManPython code or an interactive Jupyter Notebook.Motivated by previous work, and the growing abundance of cytokine profile datasets, we developed CytoMod: a novel method for the analysis of cytokine profiles based on identifying cytokine modules. The modular-based approach is partly inspired by similar approaches used for analyzing gene expression data –57. Our We analyzed cytokine profiles of 611 subjects collected from three independent studies , 51, 58 PICFLU - The PICFLU study was a prospective multi-center study of severe influenza infections in children aged 0.06–18.19 years (median 6.97)  were influenza type A positive, while the remaining cases  were influenza type B positive. Eighty-one subjects (36.6%) had a bacterial coinfection, predominantly with Staphylococcus aureus, Streptococcus pneumoniae and Streptococcus pyogenes. Additional information regarding the design, sampling, and subjects in PICFLU cohort can be found in an 6.97) . Blood sFLU09 - The FLU09 study was a prospective study of children and their household members. It included samples of blood plasma and nasal swab/lavage from influenza infected subjects as well as their asymptomatic Influenza-positive household contacts. Three hundred and three subjects aged 0.05–69.53 years (median 17.23) were enrolled during 2009–2014 and included 142 healthy household members. A preliminary analysis of cytokine profiles (profiles  includedSHIVERS - The Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS) study included 87 Influenza infected subjects recruited from 16 sentinel general practices and 4 hospitals .Cytokinej, such that the vector of the means is used as a predictor for Cytokinej's level in the sample, defined as the response variable:Construct a regression model for Cytokinej level using the regression model defined in II. Calculate the residue of the regression as:For each sample compute the expected As shown in Fiore-Gartland et al.  and abovWe note that the CytoMod adjustment procedure utilizes the values of all cytokines in a given dataset and may therefore be sensitive to the specific cytokines that were measured. To quantify the sensitivity of the adjustment procedure to cytokine selection, we conducted the following analysis: Subsets of cytokines were randomly selected from the original set of 37 cytokines in the PICFLU dataset; their size ranged between 2 and 36 cytokines. For the size of 36 cytokines, 37 subsets of cytokines were drawn, each containing the entire set of cytokines except for a single cytokine that was left out in each. For each subset size between 2 and 35, 50 different subsets of cytokines were randomly drawn. For each subset the adjustment procedure was conducted over the selected subset and the Spearman correlation was computed between the adjusted cytokine values of this subset, and their corresponding adjusted values over the entire set of 37 cytokines. CytoMod is a modular approach for cytokine analysis that clusters cytokines based on pairwise correlations, to both amplify the signal they share and aid in interpretation by grouping putatively co-signaling molecules. Cytokines are grouped using a hierarchical clustering technique which iteratively pairs cytokines (and groups of cytokines) with similar behavior to generate a series of nested clusters. The clustering hierarchy can be represented by a tree-like graph (dendrogram) in which branches indicate the similarity between the formed subgroups of cytokines. By slicing the tree at a certain level we can obtain a set of distinct clusters. The dendrogram allows to graphically portray the clusters hierarchy and visualize the structure and data distribution in a manner that is intuitive for both computational and non-computational practitioners , 56, 60.In this study, cytokine measurements from each dataset were clustered independently of the others. Measurements of different compartment samples in the same study were clustered independently due to notable differences in signaling patterns as shown in two different studies , 51. ImpThe number of clusters (K) for each dataset was determined using the Tibshirani “gap statistic” heuristic method , which cIn our implementation we chose to test K values between 1 and 11 and generate a reference dataset by shuffling each feature (cytokine) independently of the others with 200 repetitions. For both real and null data distances between cytokines were defined using Pearson's correlation coefficient. For the real dataset bootstrapped clustering was performed as described above. To constrain the number of modules to be smaller than 6, and at least 2, in cases where the estimated best K found was not in these bounds or the condition was not satisfied for all K between 1 and 11, we chose K between 2 and 6 for whichp-values will decrease accordingly.We chose to limit the number of clusters to 6 in order to reduce the formation of small (and possibly singleton) clusters. This threshold also affects the increase in statistical power for detecting associations, since as the number of clusters grows, more hypotheses will be tested and the adjusted Finally, each cluster was used to calculate module scores for each subject in each dataset. Module scores were computed as the mean value of all cytokines that belong to the module after standardizing cytokine values to mean zero and unit variance.P-values for the coefficients describing the associations of cytokines and symptom scores were adjusted for multiple hypothesis tests within each cohort, compartment and adjustment method. P-values for the coefficients between module scores and symptom scores were also adjusted, separately from the cytokine coefficients. We report associations using two types of multiplicity adjustment methods: (1) false-discovery rate (FDR) using the Benjamini Hochberg procedure . Regression models controlled for the effects of variables that were previously used in each of the studies , 51, 58,rocedure ; (2) Famrocedure . Only asCytokine measurements from each dataset were clustered into modules as described in section 2.3. Since airway samples were available only for two out of three studies, clustering comparison was only performed for the blood samples results. Comparison was performed for the absolute and adjusted clusters separately. For each we recorded the number of times each pair of cytokines clustered together in all three blood datasets. Cytokine cores were defined as groups of cytokines that clustered together across all three datasets. It should be noted that these cores may be refined when additional cytokine profile datasets are available.P-values for the coefficients describing the associations of cytokines and phenotype scores were adjusted for multiple hypothesis tests within each presented dataset separately. P-values for the regression coefficients calculated for the core scores were adjusted separately than the coefficients calculated for individual cytokines. Individual cytokine p-values were adjusted across all cytokines and not only for the cytokines included in the core cytokine set.Cytokine cores associations with phenotypes were calculated as described in section 2.4. A subject's score for each core was calculated based on the mean cytokine concentration of cytokines within the core, after standardizing each cytokine to mean zero and unit variance. P-values for the correlation coefficients were adjusted for multiple hypothesis tests within each dataset. The correlations were presented alongside each other in order to highlight trends across all datasets.Finally, we calculated pairwise Pearson correlations between cytokine cores within each blood dataset, i.e., PICFLU, SHIVERS, FLU09 and FLU09-healthy. We applied CytoMod to cytokine profiles of three independent cohorts (see section 2.1 for details) of consented subjects naturally infected with influenza virus: (1) PICFLU—a prospective multi-center study of children admitted to intensive care units with severe influenza virus infection ; (2) FLUTo allow a direct comparison between the different cohorts, we limited our analysis to 37 cytokines that were measured from the blood of subjects in all three studies. These cytokines were also used to profile nasal wash from FLU09 subjects and endotracheal aspirates of PICFLU subjects. Cytokine concentrations (pg/mL) and subject ages were log-transformed for all analyses. Cytokine measurements from each study were analyzed independently of the others due to differences in subject characteristics and measurement methods. Measurements from different compartments  were also analyzed separately due to notable differences in signaling patterns, as shown previously , 51. In K) for each dataset was determined using the Tibshirani “gap statistic” method  was also reflected in the significant positive correlations between each cytokine and the mean cytokine level within each subject  Figure . Thus, sP-values for the coefficients describing the associations of modules and cytokines with clinical phenotypes were adjusted for multiple hypothesis tests within each figure presented . The P-values for the module and cytokine coefficients were adjusted independently. Family-wise error rate (FWER)-adjusted p-values using the Bonferroni-Holm method . Regression models controlled for the effects of age and other variables, as previously chosen for each of the three cohorts , 51, 58.m method  were calrocedure ]. HoweveFLU09 - The associations with clinical phenotypes in influenza-positive FLU09 absolute datasets were calculated using linear regression adjusted for age . Individual cytokines within these modules were also significantly associated as follows: BS3 cytokines EGF, GRO and IP-10 positively associated with total symptoms and IP-10 also associated with systemic symptoms; the BS4 cytokine Fractalkine (FKN) was positively associated with lower RT symptoms. While most of the regression coefficients of these cytokines were slightly higher than those of their modules, the statistical significance of the absolute associations after FWER adjustment was stronger for the modules than the individual cytokines in 4 of 5 (significant) cases; only the significance of the Fractalkine association was stronger than that of the BS4 module to which it belongs. In addition, IL-10 was significantly associated with both upper and lower RT, while the BS2 module to which it belonged was not significantly associated with any symptoms. This increase in statistical significance is directly attributable to the reduction in the number of statistical tests across which multiplicity adjustment is applied. In the absolute-module set analysis of the nasal wash samples, the majority of cytokines clustered together into one module (NW2), perhaps due to high immune activation at the site of infection. Absolute NW2 was significantly positively associated with upper RT symptoms , however, NW2 cytokine IL-6 had a stronger significant positive association with the same phenotypes. It should be noted that all of the previously reported cytokine associations with symptom scores identified using data from years 1 to 2 of the FLU09 study (using an FDR threshold of 0.2) ( for age . Modules of 0.2) , were re of 0.2) , and addPICFLU - Positive significant correlations were also observed in the absolute PICFLU serum associations with clinical phenotypes portrayed in p-values 0.00002, 0.0286, respectively). The BS3 cytokines IL-6 and IP-10 had an association with shock, while IL-8 and MCP-1 had an association with both shock and pneumonia-ARDS. The BS3 association with ECMO or death was significant while none of the individual cytokines in the module were significantly associated. The strength of the association with shock for all individual BS3 cytokines was weaker than for the module as a whole. On the contrary, absolute IL-8 and MCP-1 had a significant association with pneumonia-ARDS, while the absolute BS3 module did not. The PICFLU absolute endotracheal samples did not have any significant associations with outcomes . Logistic Regression models included adjustment for age, ethnicity and sampling time. No significant associations were detected among absolute individual serum cytokines, with severe acute respiratory illness (SARI) (s (SARI) . Howevers (SARI) , which ws (SARI) .While none of the absolute concentrations of cytokines or their modules were negatively associated with clinical phenotypes, we found several significant negative associations using cytokines and cytokine modules that had been adjusted for the mean cytokine concentration. Interestingly, some, but not all of the significant positive associations that were identified using absolute cytokine concentrations were also significant after adjustment for the mean.FLU09 - as seen in p-values 0.0011, 0.008, respectively, as detailed in PICFLU - The adjusted BS4 module containing EGF, Eotaxin, FGF-2, Fractalkine (FKN), GRO, IFN-α2, IL-12-P70, IL-7, MDC, and sCD40-L was negatively associated with shock, pneumonia-ARDS and ECMO or death . The BS3 adjusted cytokines IL-6 and IP-10 were associated with shock, while IL-8 and MCP-1 were associated with both shock and pneumonia-ARDS. As with the absolute cytokine analysis, adjusted BS3 was associated with ECMO or death, while none of its constituents were associated on their own. The significance of all adjusted BS3 member cytokines with shock was weaker than the module's; the significance of the adjusted IL-8 association with pneumonia-ARDS was also weaker than that of BS3. However, the significance of the association of adjusted MCP-1 with pneumonia-ARDS was stronger than that of its module BS3.SHIVERS - While no significant associations were detected among adjusted individual serum cytokines, we found that the adjusted BS6 module was positively associated with severe acute respiratory illness (SARI) (s (SARI) . Furthers (SARI) .We next asked whether cytokine modules were consistent across datasets, i.e., were there cytokine “cores”—clusters of cytokines that were consistently correlated during influenza infection. Since airway samples were available only for two out of three cohorts, this analysis was only performed using blood sample (serum or plasma) modules. To identify cytokine cores, we tallied the number of times that each pair of cytokines clustered together across the three blood datasets . CytokinTo determine whether the cytokine cores were unique to influenza infected subjects, we constructed modules of adjusted and absolute plasma samples provided by 142 healthy volunteers in the FLU09 study. We found that overall, cytokine cores were consistent across influenza-infected and healthy controls with two exceptions: in the absolute cores, GCSF did not cluster together with other core-6 cytokines and cores-4 and -6 were not identified in the adjusted modules of healthy controls.Each absolute or adjusted core was composed of cytokines that clustered together into the same module in all three cohorts , 4. For P-values for the coefficients describing the associations of cytokines and symptom scores were adjusted for multiple hypothesis tests within each presented dataset separately. P-values for the regression coefficients calculated for the core scores were adjusted independently of the coefficients calculated for individual cytokines. Individual cytokine p-values were adjusted across all cytokines and not only for the cytokines included in the core cytokine set.We then tested for associations between the cytokine cores and clinical phenotypes, using the same methodology described above. A subject's score for each core was calculated based on the mean cytokine concentration of cytokines within the core, after standardizing each cytokine to mean zero and unit variance. FLU09 - None of the adjusted plasma FLU09 cores were significantly associated with clinical symptoms, but trends were in agreement with the module associations .We computed correlations between cores within each of the blood cytokine profile datasets, including the FLU09 healthy controls (see section 2.5 for details). Overall we found mostly positive significant correlations between absolute cores that were consistent across all datasets, with a few notable exceptions: cores-1 and -7 and cores-3 and -4 .We also computed pairwise correlations for the adjusted cores . SimilarHere we presented CytoMod—a data driven approach for analyzing cytokine profiles and their association with clinical phenotypes. Our approach leverages the inherent redundancy of cytokines to form modules—clusters of cytokines whose signals correlate across a cohort of individuals. CytoMod is an unsupervised method—i.e., it does not use any information about clinical phenotypes or outcomes to identify cytokine modules. Using cytokine modules increases the statistical power to detect associations with clinical phenotypes, by amplifying the signal within a module relative to the noise, as well as reducing the number of tests subject to multiplicity adjustment. It also allows for the identification of data-specific co-signaling cytokines, which may provide clues about the underlying immunological pathways. A preliminary version of CytoMod was applied in the analysis of the PICFLU cohort . ImportaTo our knowledge CytoMod is the first method for the analysis of cytokine profiles and clinical phenotypes that utilizes modules identified within cytokine expression data. In the age of multi-omics approaches, novel strategies for the integration of multiplex data with clinical outcome information can assist in the identification of complex pathological alterations of physiological networks. CytoMod only requires a dataset of cytokine measurements and  clinical phenotypes. Importantly, it does not assume that modules necessarily capture biological function.CytoMod is based on unsupervised clustering which can help uncover inherent structures within a given dataset. Our work is related to previous work on methods for cluster analysis of variables –67, whicWe applied CytoMod to three independent cohorts of influenza-infected subjects. The analyses of SHIVERS and FLU09 datasets presented here included previously unpublished data from additional study years, as well as data from healthy volunteers. To allow comparisons between the cohorts, we limited the number of cytokines analyzed to a subset of 37 cytokines that were quantified in all three cohorts. We found that in two of these cohorts, modules were significantly associated with clinical phenotypes, and in most cases the associations were stronger than those of individual cytokines within the module. Specifically, we found that across all modules in these two datasets, the association of the module with outcomes was more significant than that of an individual cytokine in 14 out of 22 cases in which the cytokine's association was significant. Furthermore, in 6 cases, a module had a significant association with a phenotype while non of its cytokines had any significant association.n = 52), and sampling variability . We identified novel associations between modules and clinical phenotypes. Specifically, the adjusted BS1 module containing FLT3L, IL-13, IL-1β, IL-4, IL-5, IL-7, IL-9, and TNF-β was found to be significantly negatively associated with total and systemic symptoms. Out of these cytokines, only IL-1β was included in the previous analysis. In addition, we found novel associations of the absolute EGF, GRO, FKN levels that were not previously reported. In the analysis of the PICFLU study, which only included children admitted to the ICU with influenza infection, we found that the serum module BS3 is significantly associated with Shock and ECMO/death outcomes. Interestingly, this module contains IL-6, IL-8, and MCP-1, which have been previously reported to be hyperactivated in subjects with severe influenza infection . No signiability  which fuiability , which wq-values ≤ 0.2 may also be worth further exploration  adjusted core-3 which includes IL-1β, IL-4, and IL-13 contribute to epithelial repair mechanisms , 77.While we found that the cytokine cores were significantly associated with clinical phenotypes, the associations of the cytokine modules that were defined separately for each dataset were overall stronger. This is not surprising for two reasons: (1) using the strict definition of cores used here , cores are typically smaller than data-driven modules and are more sensitive to measurement noise; (2) Data driven modules of a specific cohort may also be affected by other covariates which may be specific to that cohort, and are not captured by the cytokine “cores” which are created using multiple datasets.We analyzed correlations between cytokine cores, and compared these across datasets in both the absolute and adjusted datasets. We found that overall, the correlations between different cytokine cores were consistent across the three datasets, as well as in a cohort of healthy controls. However, we found one notable exception: adjusted core-1 and core-5 were negatively associated only in the PICFLU dataset. This is also reflected in the fact that core-1  was weakly positively associated with outcome in a cohort of mild influenza infection (FLU09) and was negatively associated with outcome of severe influenza infection (PICFLU).The existence of cytokine cores, and their association with clinical phenotypes despite a variety of differences between the cohorts suggest that these cores may represent stable underlying cytokine modules that consistently co-signal during influenza infection, and in some cases also in a healthy state. Cytokine cores may relate to specific functions and underlying biological processes that govern the complex cytokine signaling network. Nonetheless, defining robust cytokine cores requires large scale analysis of multiple cytokine datasets. As additional cytokine profile datasets are generated and made publicly available, cores can be dynamically re-defined, including defining “softer” probabilistic cores based on frequency of co-occurrence across many datasets and conditions. Identification of consistent cytokine subsets may provide a basis for the selection of biomarkers and the development of targeted immune assays, as part of a novel approach for developing future point-of-care diagnostic tests based on cytokine measurements that may be used for many different infections.CytoMod groups cytokines into modules so that each cytokine belongs to a single module. We hypothesize that similar to genes, each cytokine may play several functional roles under different immune contexts. This would be best captured by “soft” modules, in which each cytokine may belong to more than one module. Once a sufficiently large number of cytokine datasets are analyzed such softer modules may be identified and annotated, similar to annotations of gene modules , 57. OurCytoMod can be applied to any cytokine profile dataset and does not make any assumptions regarding the specific technology that was used to quantify cytokines. Furthermore, the modular approach allows identification of co-signaling cytokines across study years, even if the specific kit used to quantify cytokines was changed during the study, or other changes to the study were implemented. This is due to the fact that correlations are computed between cytokines across study subjects. Indeed despite significant differences between the cytokine measurements in years 1 and 2 of the SHIVERS study, we used both years to generate cytokine modules for this dataset.https://github.com/liel-cohen/CytoMod as well as in an interactive Jupyter Notebook available at https://nbviewer.jupyter.org/github/liel-cohen/CytoMod/blob/master/cytomod_notebook.ipynb.In summary, using a modular approach to analyze cytokine profile datasets provides two major advantages: (1) It increases statistical power to detect associations with clinical phenotypes; and (2) By comparing modules obtained from different independently sampled datasets, we can identify cytokine cores - sets of consistently co-signaling cytokines. By aggregating cytokine information across datasets, this approach may help identify inherent, and condition-specific groupings of cytokines, providing the basis for future mechanistic molecular studies. A Python implementation code of CytoMod can be found at All datasets generated for this study are included in the AF-G, LC, and TH developed the computational method. AF-G and LC analyzed data. TH designed the study. AR, AP-M, S-SW, JR, TW, RS, QH, RW, and PT enrolled the clinical cohorts, and generated data. LC and TH wrote the paper. AF-G, AR, S-SW, and PT commented and edited the paper.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.


Objective: A matched, case–control study was conducted to examine the association between development of low birth weight (LBW) and maternal factors, including dietary intake, comorbidities, and socioeconomic factors, among women in Cap Haitien, Haiti.Design: Mothers who delivered LBW babies; defined as ≤2.5 kg, were identified by review of the medical record and matched to mothers of similar age, parity, with normal birth weight (NBW) babies. A survey was administered consisting of Women's Dietary Diversity Score (WDDS), maternal reporting of comorbidities, income, and educational level.Subjects: Women were eligible if they delivered and had newborns weighed within the last 2 years. Total study participants consisted of 32 cases and 34 controls matched for age, parity, and month of delivery.Results: Mothers who consume eggs were 78% less likely to have given birth to a LBW infant (OR 0.22 (95% CI: 0.05–0.87). Mothers with NBW babies had a nonsignificant trend towards higher WDDS. The prevalence of hypertension in mothers who were seen in the clinic at least once over the past 2 years was found to be 27%, and 78% of mothers were not aware of their diagnosis.Conclusion: Enhancing maternal nutrition during pregnancy has broad implications for reducing LBW, improving fetal health and reducing fetal predilection for chronic diseases in adulthood. Longitudinal prospective studies are needed to evaluate the selective benefit of eggs and other high-quality foods in protecting fetal growth. Efforts to improve knowledge and awareness of hypertension in Haiti should be undertaken. In Haiti, it is estimated that 21% of children are born LBW, defined as weighing at or below 2.5 kg.9 Among the factors contributing to LBW, lack of dietary diversity with few fruits, vegetables, and animal sources of food has been noted in low and middle-income countries.10 Maternal hypertension was also noted to be a significant risk factor for LBW infants in recent Haitian immigrants to the United States.11According to the Developmental Origins of Health and Disease Hypothesis, maternal micronutrient insufficiency leads to fetal undernutrition, causing maladaptive changes and increased risk of chronic diseases in adulthood.12 In Haiti, 14% of school age children are stunted at baseline, another 14.5% are underweight, while 65% of children aged 6–59 months are anemic.14 Low socioeconomic status and poverty play a role in limiting food in pregnant women.16 Poor gestational nutrition, low prepregnancy weight, short maternal stature, general morbidity, and general episodic illness are known major determinants of intrauterine growth restriction and subsequent LBW.17 In contrast, increased intake of green leafy vegetables, fruits, and milk products have been associated with increase in birth weight.18Haiti is one of the poorest countries globally, ranking 168 out of 187 countries on the Human Development Index.10 As a response, a WDDS consisting of nine food groups was adopted by the Food and Agriculture Organization of the United Nations (FAO). A score of 4 or more has been shown to be associated with lower risk of maternal anemia and giving birth to LBW infants.19 The use of dietary recall to reflect the dietary habits of a previous pregnancy has been validated in a previous study.20 At the time of submission, to the best of our knowledge, there have been no clinical studies addressing dietary diversity, hypertension awareness, and birth outcomes in Haiti.We examined the association between maternal dietary diversity, anemia, blood pressure, and reporting of comorbidities such as diabetes, hypertension, and socioeconomic status on the development of LBW infants in a matched, case–control study conducted in Cap-Haïtien, Haiti. To determine the potential for future medical interventions, we also examined knowledge and awareness of hypertension by administered a questionnaire. Dietary diversity was used as a proxy for nutrient adequacy by tabulating a Women's Dietary Diversity Score (WDDS). The Women's Dietary Diversity Project validated WDDS as an instrument to predict micronutrient adequacy in females of reproductive age in a number of diverse settings.This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects/patients were approved by the Institutional Review Board (IRB) at Washington University in St. Louis as well as Haitian IRB through the Ministry of Health of Haiti. Written informed consent was obtained from all subjects/patient with the assistance of an interpreter. The study was conducted in Cap-Haitien, Haiti from March to April 2016. All records were obtained from Hospital Fort St. Michel, a public clinic in an urban community in Cap Haitien. Medical records were selected at random from all patients at the hospital who were seen between September 2014 and February 2016. Records were screened for obstetric visits where a birth weight was recorded. Over 90% of the mothers of LBW infants were called using telephone numbers in the hospital records. The affiliation of the authors, an outline of the study, and a small remuneration for participation ($5 USD) was communicated to potential participants. Each mother of a LBW infant who agreed to participate was then matched by age at delivery, parity, date of infant's birth, and gestational age to 1–2 mothers of infants with normal birth weight (NBW). These mothers were contacted using the same process outlined above.All study components were conducted in Haitian Creole by local nurses who were hired and trained by the study authors. The study was conducted in a dedicated room within Hospital Fort St. Michel. Patient consent was obtained upon arrival, after which the survey was administered, and finally anthropometric data were collected.Information on food consumption was collected by a qualitative dietary recall over the previous 24 h, based on the WDDS. The women were asked to recall all the dishes, sauces, snacks, drinks, and other foods they had consumed the previous day. The women were then prompted for any additional foods and asked to describe all the ingredients in the food they had eaten. The ingredients were subsequently translated into English and coded into a predefined list of 10 food groups: starchy staples ; dark green leafy vegetables; vitamin-A-rich fruits and vegetables; other fruits and vegetables; organ meat; flesh meat and fish; eggs; milk and dairy products; legumes and nuts; and oils and fats. This information allowed the construction of WDDS. They were then asked to complete a multiple-choice survey containing questions about hypertension.Hemoglobin concentrations were measured using the HemoCue system and reported in grams per 100 milliliters (g/dL). The HemoCue system was cleaned and calibrated each morning before sample collection. Blood was collected with a fingerstick and a microcuvette in one continuous process and tested in the HemoCue system. For anthropometry, the Seca Model 874  440 lb×0.1 lb resolution scale and the ShorrBoard height measuring board were used to collect weight (to the nearest 0.1 kg) and height measures (to the nearest 1 mm), respectively, using international protocols. We also recorded the vital signs, including blood pressure with a manual sphygmomanometer, for all the participants.t test for continuous variables. A p value of ≤0.05 was accepted as significant. Odds ratios were calculated with each food group being the exposure variable and LBW the outcome variable. All analyses were performed using the statistical software package SPSS (Version 23).Characteristics of mothers with and without LBW infants were compared using the chi-square test for categorical variables and Student's unpaired Records of more than 15,000 clinic visits between September 2014 and February 2016 were reviewed. Of these, 1046 were records of deliveries where a birth weight was documented. There appeared to be no seasonal variation in birth weight (data not shown). Of all the birth records reviewed, 172 (16%) of these births were of infants ≤2.5 kg. Fifty-six (33%) of the infants gestational ages were not documented in the chart, but of those that were documented, 94 were full term (≥37 weeks). One hundred fifty-three mothers of LBW infants were called to participate in the study. Majority of study participant's telephone numbers obtained from the chart were disconnected and could not be reached. However, of those whose numbers were still in service, greater than 90% were able to partake in the study. A total of 32 mothers of LBW infants and 34 mothers of NBW infants completed the survey and anthropometric data collection.p<0.001). There was no significant difference in WDDS between the cases and controls when measured as a mean  or as a dichotomous variable for presence of a diverse diet, meaning ≥5 food groups   . Subgrou p=0.31) .21 Only 22% reported having high blood pressure, and only 33% had been told by their doctor that their blood pressure needed to be controlled. Out of the entire sample, less than half (41%) believed that they could afford medications to treat hypertension.In a subanalysis of hypertension knowledge and awareness among mothers screened during the study, none of the 66 were able to correctly define hypertension . Only 21In this matched case–control study, we aimed to characterize LBW in Haiti by looking at a number of factors known to contribute to the development of LBW infants. Mothers who consumed eggs were significantly less likely to have given birth to a LBW baby. Comparison of the dietary habits, socioeconomic standing, hemoglobin concentration, blood pressure, BMI, and maternal reporting of comorbidities between mothers with and without LBW babies did not reveal any significant difference. A separate questionnaire assessing knowledge of hypertension and awareness found profound poor comprehension and lack of awareness. The majority of study participants did not know the impact of untreated hypertension or have the financial means to afford prescription medications to treat high blood pressure.22–24 In a randomized control trial conducted in Ecuador,22 children ages 6–9 months were assigned to an intervention of one egg per day for 6 months. The investigators noted a reduced prevalence of stunting by 47%  and underweight by 74%  in the children who consumed eggs. Eggs are commonly available, relatively inexpensive, and contain nutrients that may be of benefit during pregnancy as well as during weaning, including vitamin D, folate, iodine, selenium, and long-chain n-3 polyunsaturated fatty acids (omega-3 fatty acids).There is emerging literature supporting the benefits of egg consumption during pregnancy.Several limitations are noted in this case–control study. Our data set was drawn from patients who delivered at the clinic; subsequently there is selection bias due to the missing home births. We were unable to collect diet and morbidity data during pregnancy. Given that participants were months to years out of pregnancy, the physiologic and socioeconomic environment of our study participants might have changed, impacting our findings. Lack of inclusion of rural study participants also limits the applicability of the study outside an urban setting similar to Cap-Haïtien, Haiti. Erratic phone services limited reaching potential study participants. In addition, the study had a small sample size and thus lacked study power; future studies with larger sample sizes would be beneficial.25 More research is needed to examine the effects of improving dietary diversity more broadly, and the use of affordable animal source foods such as eggs as sustainable alternatives to addressing LBW.Our study offers preliminary insight into nutrition-related factors influencing birthweight outcomes and the prevalence of hypertension among women in a low-resource setting. More research is needed to examine the multifaceted problem of LBW and potential types of nutrition and interventions to improve birth outcomes. These studies will also require consideration of births that occur outside the healthcare system, such as in rural villages. Identifying the most effective nutritional intervention to reduce LBW is even more critical, with recent findings from the International Lipid-Based Nutrient Supplement trials showing only limited effects on reducing birth outcomes.


Giving childbirth is a natural reward for human beings to replace themselves to exist in the world. Despite all the efforts made to improve maternal health, maternal morbidity and mortality continue during childbirth. Hence, this study aimed to determine the proportion of maternal birth outcomes and identify their predictors among mothers who gave birth in hospitals. p value ≤0.05.  A hospital-based cross-sectional study was conducted from April 9 to June 7, 2016, among 384 postnatal mothers in Debre Tabor Hospital. Randomly selected mothers were interviewed by trained data collectors. Data were checked for completeness, entered using Epi Info version 7, and analyzed using STATA 14 software. A multivariate logistic regression model was used to control confounders and identify predictors of maternal birth outcomes. Statistical significance was declared by adjusted odds ratio with a 95% confidence interval and a  About 77%  of the mothers had good maternal birth outcomes. Antenatal care utilization ; BPCR practice ; self-preference of health institution ; and mode of delivery: caesarean , assisted breech , and instrumental  were associated with good maternal birth outcome.  In this study, the maternal birth outcome among postnatal mothers was good in more than three-fourth of the cases. Hence, encouraging mothers to utilize health-care services and counseling and supporting them on BPCR practice are recommended. In the year 2015, an estimated rate of 303,000 maternal mortality had occurred globally [Developing countries, as reported in 2015, are suffering from the high burden of maternal mortality with about 99% of global estimates [Maternal mortality trends in Ethiopia demonstrated a decreasing MMR from 871 in 2000 to 412 in 2016 . The lifWorld strived to cope with maternal health problems and developed different strategies. The World Health Organization (WHO) developed a manual and suggested recommendations for maternal and neonatal health , 5, partPresence of a skilled attendant at birth is as well among key strategies to improve maternal and neonatal health . The levA systematic review and meta-analysis result revealed that disclosure to BPCR interventions resulted in a statistically significant fall of neonatal mortality risk by 18% and a nonsignificant reduction of maternal mortality risk by 28% . A subgrAlthough all possible efforts to improve maternal health care are in place, maternal morbidity and mortality remain a challenge. Hence, this study was intended to determine the proportion and determinants of maternal birth outcomes among postnatal mothers who gave birth in Debre Tabor Hospital.This hospital-based cross-sectional study was conducted among mothers who gave birth in Debre Tabor Hospital and admitted to the postnatal unit.Debre Tabor is the capital of South Gondar administration zone and is 98 km northwest to Bahir Dar city. The hospital is situated in the middle of the zone and serves for an estimated 2,445,826 population of the zone. Besides all other services, the hospital provides an estimated rate of 500 delivery services per month.The data were collected for a period of 2 months from April 9 to June 7, 2016. Mothers were approached within 24 hours of delivery and before discharge when stayed longer. All mothers who were admitted to the postnatal unit were considered as study population, and those who might develop some iatrogenic complications were treated under exclusion criteria.The sample size was calculated based on the following assumptions: Mothers who were expected to give birth in a period of two months were estimated to be 1000. Proportions of mothers who were supposed to have good birth outcome were assumed to be 50% since previous studies which reported similar findings were lacking. Taking 5% margin of error, 95% confidence level, and single population proportion formula, the maximum sample size was turned to 384.st mother was randomly selected; and thereafter, every third client was interviewed until the estimated sample size was obtained in a period of two months.Systematic random sampling technique was used to select study participants. A skip interval of 3 was calculated; among the first three postnatal admissions, the 1A pretested structured questionnaire was developed in English and translated to Amharic then back to English to maintain its consistency. Training on the aim of the study, data collection tool, and procedure was given for the data collectors and supervisor. A pretest was then conducted in a nearby health center among 20 postnatal mothers, and a minor correction was made on the questionnaire before actual data collection.Three midwives, BSc, conducted a face-to-face interview, observation, and chart review. One midwife, BSc, supervised the data collection process. Data collectors interviewed participants on their sociodemographic, reproductive and obstetric, and BPCR-related data, whereas birth outcome data were collected through direct patient observation and chart review.The maternal birth outcome was measured as “good” if mothers were clinically assessed normal and discharged within the recommended time, whereas those who developed postpartum hemorrhage and postpartum sepsis and sustained injury to the perineum, cervix, and bladder were categorized as having “bad” outcome.Birth preparedness and complication readiness was measured based on the following five areas: identifying health institution for labor and delivery, saving money for labor- and delivery-related reasons, identifying skilled health-care provider(s) for labor and delivery, identifying means of transportation to place of childbirth or in case of emergency, and arranging blood donor in case if needed. Mothers who followed three and more steps of the above five components were considered prepared in this study which was also considered in previous studies –17.Mothers who came to the current place of delivery by their own or their families' preference were considered as “self-referred/self-preference,” and those who were referred by the community or other lower-level health facilities were considered as “referred”.p value ≤0.2 under bivariate analysis in order to control the confounding variable and identify factors associated with the outcome variable. The strength of association was determined by the adjusted odds ratio (AOR) with its 95% confidence interval (CI) and a p value ≤0.05.The collected data were first manually checked for completeness and coded and then entered into Epi Info version 7 and then transported to STATA software version 14 for analysis. Descriptive analysis was done and presented using tables, figure, and text. Bivariate logistic regression analysis was done to identify the association of sociodemographic and reproductive and obstetric variables with the maternal birth outcome. Then, multivariate logistic regression was done by running all variables with a Written ethical clearance was obtained from the research and ethical committee of the Department of Midwifery, College of Medicine and Health Sciences, University of Gondar. Debre Tabor hospital was then communicated through a formal support letter and permission gained. Informed consent was obtained from participants, and they were assured about the privacy and confidentiality of their responses.Three hundred eighty-four mothers participated in the study, and their age ranged from 16 to 46 years (median age (interquartile) was 28 (8.5) years). The majority were married and Orthodox Christians. More than half of the participants were rural residents, and nearly three-fourth were housewives. About one-third of the mothers had not attended formal education, and one-fifth had education beyond secondary school .About nine-tenths of the participants in this study had ANC during their index pregnancy, but only about one-third attended 4 visits. More than half of the mothers gave birth in the hospital because they were referred from other facilities. The majority gave vaginal birth, and spontaneous vaginal delivery occurred among three-fourth of the participants .In about 77% of the mothers, the maternal birth outcome was normal, and they were discharged without having complications. The common complication (11%) in this study was postpartum hemorrhage (PPH), and about 4.2% developed postpartum sepsis. The remaining 7.5% sustained genital and urinary tract injuries .In multivariate logistic regression analysis, attending ANC during index pregnancy is significantly associated with maternal birth outcome . Well preparedness for birth and its complication and self-preference of health facility for labor and delivery were also associated with good maternal birth outcome. On the contrary, modes of delivery other than a spontaneous vaginal mode of delivery were protective with good maternal birth outcome .This research has shown birth outcome proportions among postnatal mothers. In addition, it identified factors associated with good birth outcomes. Accordingly, nearly three-fourth of the mothers experienced good birth outcome. Antenatal care utilization, preparedness for birth and its complication, self-preference of health facility for labor and delivery, and mode of delivery were predictors of birth outcome in this study.In this study, among hospital births, 77% of the mothers experienced normal birth outcome. The remaining nearly 23% of the mothers developed complications such as postpartum hemorrhage (PPH) (11%), postpartum sepsis (4.2%), and genital and urinary tract tear/injury (7.5%). During the study period and among studied mother, no maternal mortality was reported.Postpartum hemorrhage (PPH) found to be more common in this study. Other studies reported the proportion as 24% in Italy , 12.5% iInfection in general, postpartum infection (sepsis) in particular, is also a commonly reported type of cause of maternal morbidity. This study determined about 4% of cases of postpartum sepsis. Studies in Nigeria  and UganAntenatal care is a commonly provided service for pregnant mothers in Ethiopia . This stThis study in addition identified that mothers who were well prepared for birth and complications were two times more likely to have good outcomes than those who were less prepared. Studies also supported that birth preparedness and complication readiness interventions besides contributing to maternal well-being were identified to contribute to reducing maternal and neonatal mortality in developing countries . The assThe current study further identified that mode of delivery is associated with maternal birth outcomes. Compared to those who gave spontaneous vaginal delivery, mothers who delivered by caesarean section were 54% more likely to develop complications. Also, assisted breech and instrumental delivery, respectively, hold 83% and 73% more likely risk of complication than spontaneous vaginal delivery. Studies , 29 as wAlthough this study is limited to a single institution, the data quality is better since it was collected through interviewer-administered questionnaire and observation and the study tried to identify actionable factors to poor maternal birth outcomes. However, it would have been better if such studies became a multicenter and incorporated quality of delivery-care services.In this study, maternal birth outcome among postnatal mothers was good in more than three-fourth of the cases. However, nearly a quarter of the mothers developed postpartum hemorrhage and postnatal sepsis and sustained genital tract injury. Antenatal care utilization, BPCR practice, self-preference of a hospital for labor and delivery service, and mode of delivery were statistically significant factors for good maternal birth outcomes. Hence, providing individual-, couple-, and community-level interventions in encouraging mothers to utilize health-care services and health facilities as well as counseling and supporting them on BPCR practice is recommended.


Adolescents seeking professional help with their gender identity development often present with psychological difficulties. Existing literature on psychological functioning of gender diverse young people is limited and mostly bound to national chart reviews. This study examined the prevalence of psychological functioning and peer relationship problems in adolescents across four European specialist gender services , using the Child Behavioural Checklist (CBCL) and the Youth Self-Report (YSR). Differences in psychological functioning and peer relationships were found in gender diverse adolescents across Europe. Overall, emotional and behavioural problems and peer relationship problems were most prevalent in adolescents from the UK, followed by Switzerland and Belgium. The least behavioural and emotional problems and peer relationship problems were reported by adolescents from The Netherlands. Across the four clinics, a similar pattern of gender differences was found. Birth-assigned girls showed more behavioural problems and externalising problems in the clinical range, as reported by their parents. According to self-report, internalising problems in the clinical range were more prevalent in adolescent birth-assigned boys. More research is needed to gain a better understanding of the difference in clinical presentations in gender diverse adolescents and to investigate what contextual factors that may contribute to this. Growing awareness of specialist gender identity clinics and acceptance of gender diversity by the wider community may have contributed to the increasing number of children and adolescents seeking professional help with their gender identity development . Some yoGender diversity is frequently associated with psychological difficulties. Existing literature on psychological functioning in gender diverse adolescents shows greater prevalence of associated difficulties as compared to the general population. At the specialist gender identity clinic in London, bullying 47%), low mood (42%), and self-harming thoughts and behaviours (39%) were the three most common associated difficulties observed 7%, low m. In The These findings are not solely found in European countries. In the USA, high prevalence of depression, suicidal thoughts and attempts, and substance abuse were reported by several independent gender clinics across the nation –12. In aAs with the studies above, most of the published evidence on gender diverse adolescents has been based on independent clinical chart reviews. The only direct comparison studies in psychological functioning in gender diverse youth was conducted by The Netherlands and North-American specialist gender identity clinics, using standardised parent- and self-report measures such as the Child Behavioural Checklist (CBCL) and the Youth Self-Report (YSR) , 16. In Poor peer relationships were found to be the strongest predictor for emotional and behavioural problem scores in gender diverse youth , 17, 18.Given the high rates of adolescent referrals presenting with co-occurring psychological difficulties, further research in this area is urgently needed. In the cross-continental comparison studies between The Netherlands and North America, differences in psychological functioning in gender diverse youth were largely attributed to differences in peer relationship problems , 17, 18.The Center of Expertise on Gender Dysphoria, VU Medical Center Amsterdam, The Netherlands was established in 1988 at the University Medical Center in Utrecht. It moved to the VU Medical Center in The Netherlands in 2002. It is one of the longest standing gender services in the world. One other adult gender clinic is based in the north of the country. At the time of this study, all child and adolescent referrals were seen by the specialised child and adolescent professionals in the gender service in The Netherlands.The Pediatric Gender Clinic, Ghent University Hospital, Ghent, Belgium, was founded in 2010. There are two other gender services in Liège and Brussels; however, Ghent is the only national clinic for young people.The Department of Child and Adolescent Psychiatry, University Hospital of Psychiatry Zurich, Switzerland. This service was founded in 2009 and during the time of the study covered as catchment area the German speaking part of Switzerland.The Gender Identity Development Service, Tavistock and Portman NHS Foundation Trust, London, United Kingdom, was established in 1989. The GIDS is a national clinic, with a satellite clinic in the north, based on Leeds and a number of other established outreach clinics in the Exeter, Dublin, and Wales.Four specialist gender identity clinics were taking part in this study: The Netherlands, Belgium, Switzerland, and the UK. All clinics were part of the Adolescent Gender Identity Research (AGIR) Group , a collaThe assessment protocol was broadly similar for each of the specialist gender clinics. In line with the international guidelines, the psychosocial assessment across all four clinics comprises of 3–6 appointments with one or two mental health professionals. Assessment appointments were offered around every 4–6 weeks. The mean duration of the diagnostic procedure was approximately 6–8 months. After the diagnostic work was finished, the applicant was discussed by the multidisciplinary team and the team together with the family decides whether the adolescent would benefit from further treatment, involving psychological and physical interventions.n = 1303. We analysed data from all referred adolescents who completed either the CBCL or the YSR at baseline. At the time that this information was gathered, none of the adolescents had started physical interventions. Data for n = 344 adolescents (26.4%) were not available due to not completing or not returning questionnaires. Therefore, they were excluded from the analyses. Therefore, the total number for the included sample was n = 959 . In The Netherlands, a total number of 275 adolescents were referred between 2009 and 2013. Data were available for 252 young people (91.6%). For the UK clinic, 860 adolescents were referred in this time period and data were available for 610 young people (70.9%). For Belgium, 136 adolescents were referred and data for 71 young people were included in this study (52.2%). Switzerland had a total of 32 referrals over this time period, for which 26 were included in the sample (81.3%).For this study, we included all adolescents aged 12–18 who were referred to one of the four European specialist gender clinics between January 2009 and December 2013. The total number of referrals combined was χ2 = 1.8, ρ > 0.05. In this analysis, the excluded data were not available from Belgium or Switzerland. The excluded sample was found to be significantly older compared to the included sample, F = 12.14, ρ < 0.05 .When comparing the included sample with the excluded sample, no significant differences were found with regard to birth-assigned gender, All referred adolescents were compared on several background measures: (1) assigned gender at birth; (2) age at assessment; (3) CBCL gender item 110; and (4) YSR gender item 110. On the CBCL and YSR, item 110 is specifically related to cross-gender identity (wishes to be the other sex). To avoid an artificial inflation in the calculation of behaviour problems on the CBCL and YSR, we set the value to “0” if item 110 was scored as 1 or 2 and the same was done for any other item if the parent identified gender-related issues. By taking this item out of the calculation, we used it as a measure for reporting gender dysphoric feelings.Internalising, Externalising, and the Total Problem Scale. In the present study, four dependent variables from the CBCL and YSR were used: (1) the mean total problem score, i.e., the sum of all items rated 1 or 2; (2) the mean score for internalising problems; (3) the mean score for externalising problems; and (4) and clinical range scores (> 90th percentile) for these three indices , Switzerland , and the UK . No main effect was found for birth-assigned gender. In addition, no interaction effect between gender and clinic was found.On the YSR internalising problem score, a significant main effect was found between clinics, F = 6.54, ρ < 0.01. Adolescents from The Netherlands showed less externalising problems compared to adolescents from the UK, F = 26.41, ρ < 0.01. No main effects were found for Belgium or Switzerland. Between-gender differences were found, F = 4.17, ρ < 0.05, indicating that externalising problem behaviour was more prevalent in birth-assigned girls compared to birth-assigned boys. No interaction effect between birth-assigned gender and clinic was found.For the YSR externalising problem score, between-clinic differences were found, Table χ2 = 11.69, ρ = 0.01. A main effect was found between adolescents from the UK and The Netherlands, χ2 = 10.08, ρ < 0.01, indicating that a greater percentage of the UK adolescents scored in the clinical range compared to The Netherlands adolescents. No main effects were found for Belgium or Switzerland. In addition, differences in birth-assigned gender were found, showing a significantly greater percentage of birth-assigned girls scoring in the clinical range compared to birth-assigned boys (38.7% for birth-assigned boys vs. 53.2% for birth-assigned girls), χ2 = 15.28, ρ < 0.01. No interaction effect between gender and clinic was found.On the CBCL total problem score, between-clinic differences were found, χ2 = 18.24, ρ = 0.01. Significant differences were found between adolescents from Switzerland and The Netherlands, χ2 = 4.40, ρ < 0.05, and the UK and The Netherlands, χ2 = 14.88, ρ < 0.01, indicating that a greater percentage of the adolescents from Switzerland and the UK scored in the clinical range compared to The Netherlands adolescents. No main effect was found for Belgium. In addition, no significant gender differences (50.5% for birth-assigned boys vs. 57.2% for birth-assigned girls) or interaction effects were found.For the CBCL internalising problem score, a significant difference was found between clinics, χ2 = 7.09, ρ < 0.01. No interaction effects between assigned gender at birth or clinic were found.For the CBCL externalising problem score, no significant differences were found between clinics. A significant main effect was found between birth-assigned genders for the CBCL externalising problem score. A greater percentage of birth-assigned girls scored in the clinical range compared to birth-assigned boys (18.9% for birth-assigned boys vs. 27.3% for birth-assigned girls), χ2 = 49.64, ρ < 0.01. Significantly less adolescents referred to The Netherlands had total problem scores in the clinical range compared to Belgium, χ2 = 9.09, ρ < 0.01, and the UK, χ2 = 43.27, ρ < 0.01. Similarly, significantly less adolescents from the Swiss clinic had problem scores in the clinical range compared to both the UK, χ2 = 9,59, ρ < 0.01, and Belgium, χ2 = 5.47, ρ < 0.05. No gender differences were found (38.4% for birth-assigned boys vs. 37.6% for birth-assigned girls). In addition, no interaction effect between birth-assigned gender and clinic was found.For the YSR, between-clinic differences were found on the YSR total problem score, χ2 = 54.24, ρ < 0.01. Significantly less adolescents from The Netherlands clinic had problem scores in the internalising clinical range compared to all other gender clinics; Belgium χ2 = 8.97, ρ < 0.01, Switzerland, χ2 = 8.73, ρ < 0.01, and the UK, χ2 = 53.34, ρ < 0.01. In addition, significant differences were found between birth-assigned gender, indicating that a greater proportion of birth-assigned boys scored in the clinical range compared to birth-assigned girls (57.0% for assigned boys vs. 45.6% for assigned girls), χ2 = 9.78 ρ < 0.01. No interaction effects between birth-assigned gender and clinic were found.For the YSR internalising score, several between-clinic differences were found, χ2 = 18.38, ρ < 0.01. Significantly more adolescents from the UK clinic scored in the externalising clinical range compared to adolescents from The Netherlands, χ2 = 17.62, ρ < 0.01. No gender differences (32.5% for birth-assigned boys vs. 33.3% for birth-assigned girls) or interaction effects between birth-assigned gender and clinic were found.Between-clinic differences were also found for the YSR externalising score, Figures F = 19.44 ρ < 0.01. Adolescents from the UK clinic, F = 49.74, ρ < 0.01, and from the Swiss clinic, F = 17.67, ρ < 0.01, reported significantly more peer relationship problems compared to the adolescents in The Netherlands. No main effect was found for Belgium. In addition, no significant gender differences or interaction effects between birth-assigned gender and clinic were found.For the PRS measured by the CBCL, a significant main effect was found for clinic, F = 35.45, ρ < 0.01. Adolescents from the UK  and Switzerland  reported more peer relationship problems compared to adolescents from The Netherlands. In addition, adolescents from the UK also reported significantly more peer relationship problems compared to the Belgian adolescents, F = 9.04, ρ < 0.01. Again, no gender differences or interaction effects were found.For the PRS measured by the YSR, a main effect for clinic was found, Our study is the first cross-national comparison study examining psychological functioning in gender diverse adolescents across Europe, including four specialist gender identity clinics: The Netherlands, Belgium, Switzerland, and the UK. Standardised measures were used to assess behavioural and emotional functioning and peer relationship problems. Differences in emotional and behavioural problems and peer relationship problems were found across the four clinics. Overall, emotional and behavioural problems and peer relationship problems were most prevalent in adolescents from the UK, followed by Switzerland and Belgium. The least behavioural and emotional problems and peer relationship problems were reported by adolescents from The Netherlands. Across the four clinics, a similar pattern of gender differences was found. Birth-assigned girls showed more total behavioural problems and externalising problems in the clinical range, as reported by their parents. According to self-report, internalising problems in the clinical range were more prevalent in adolescent birth-assigned boys.A rise in number of referrals, particularly in birth-assigned girls, is reported by gender clinics across the world , 8. In lto be of the opposite sex” compared to the birth-assigned boys. Normative sex differences in pubertal onset, in which girls begin puberty on average at an earlier age than boys, may play a role in explaining these differences [Alongside the higher prevalence of total behavioural problems, birth-assigned girls across the four gender clinics also reported a stronger desire “ferences , 30. Duea general pattern of an “inversion” of internalising vs. externalising problems in relation to the sex-typical pattern of more internalising problems in girls and more externalizing problems in boys?” More extensive research is needed to further investigate this phenomenon.Psychological problems and psychiatric comorbidity in gender diverse birth-assigned girls is a subject currently discussed in the literature , 8, 31. Although similarities were found across the four European gender clinics, there were also some differences, particularly in the prevalence of behavioural and emotional problems. On average, adolescents from the UK reported more problems compared to the other three gender services, both measured by parental- and self-report. In The Netherlands, adolescents reported considerably lower total problem scores and internalising problem scores, compared to the other three clinics. Adolescents from Belgium and Switzerland seemed to hold an in-between position.Differences in behavioural and emotional functioning in adolescents across gender clinics were also found in the series of comparison studies between The Netherlands and North America. These studies showed that the Toronto adolescents had, on average, significantly more behavioural and emotional problems than the Amsterdam adolescents, both on the CBCL and on the YSR , 18. It The gender diverse adolescents referred to the European clinics differed in various ways. First, the number of referrals was considerably different across the countries. The UK and The Netherlands received more referrals within the same time period compared to Switzerland and Belgium. The differences in number of referrals could also be related to the time, since treatment, such as puberty suppression and hormones, was offered in the different countries. The gender identity clinics in The Netherlands and the UK represent two of the longest established gender identity clinics in the world , 33, wheSecond, the age at which the adolescents were referred differed between clinics. There is no clear explanation why these differences occurred. The mean age for adolescents from the UK and Switzerland was higher compared to adolescents from The Netherlands and Belgium. In addition, an interaction effect was found, showing that birth-assigned boys in The Netherlands and Switzerland were presenting at younger age compared to the birth-assigned girls from those countries. In UK and Belgium, the opposite was found, showing that assigned girls were presenting at a younger age compared to the birth-assigned boys. From the previous literature, we would expect to see birth-assigned girls being referred at a later age . For botMore broadly, differences in cultural and sociological factors across European countries may also play a role in the different clinical presentations between gender diverse adolescents. Although the four gender clinics are all based in the same continent, there are clear differences in child-well-being between European countries , 35. Facisolation was found to be the strongest predictor for high psychopathology and a “confused” gender identity. This was likely to affect older referred adolescents [It is well-documented in the literature that peer support and psychological well-being are strongly interlinked . Gender lescents .In this study, no gender differences were found in terms of peer relationship problems. However, differences were found between clinics, showing that gender diverse adolescents from UK and Switzerland reported more peer relationship problems compared to adolescents from The Netherlands. Interestingly, there were more similarities between these two countries. First, both reported significantly more internalising problems compared to adolescents from The Netherlands, who reported the least peer relationship problems. Second, gender diverse adolescents from UK and Switzerland were older at referral compared to the other two clinics. Taking all these factors into account, could we hypothesize that older gender diverse adolescents, particularly those experiencing internalising problem behaviours, may be more prone to experience more peer relationship problems? Overall, our findings underline that there is a strong link between peer relationships and behavioural problems across the European countries. Peer relationships are a very important part of general adolescent development . When woA strength of this study was that the population sample included four national samples of specialist gender clinics within Europe. This also makes our sample one of the largest sample sizes on gender diverse adolescents that have been reported in the literature, thus far. One of the limitations of this study was that the population sizes differed considerably between the four countries. Although cross-national differences were found, higher numbers should be warranted for Belgium and Switzerland to make stronger statements about these countries. Second, although we had included several demographic variables, it is possible that other demographic variables that were not included in this study might have contributed to the discrepancies between the European clinics. Factors such as social class or living situation could have given a more nuanced explanation and should be included in future studies. In addition, in this study, we investigated psychological functioning and quality of peer relations separately, while the previous studies have used regression analyses to determine whether peer relationship problems would predict psychological problems. This analysis lacks in this particular study, as its main aim was to focus on the differences found between European clinics. While our findings give further evidence for the link between psychopathology and poor peer relationships, we would emphasize that future research should examine more broadly the impact of other cultural and societal factors, such as experienced stigma and internalised transphobia –44, whicIn conclusion, this is the first cross-national comparison study examining psychological functioning in gender diverse adolescents across Europe. A similar pattern was found across European clinics, showing that the majority of referrals were assigned female at birth. Although there were differences found in psychological functioning across the four clinics, the most notable findings were the different clinical presentations between birth-assigned girls and birth-assigned boys. Future research should focus on gaining a better understanding of the different clinical presentations in gender diverse adolescents and investigating potential contextual factors. These findings should also inform professionals working with this population across centers in Europe, and elsewhere, whether there is a need to develop different clinical pathways for gender diverse birth-assigned boys and birth-assigned girls.


Aims. The aims of this study were to quantify the amount of protein intake and to compare growth parameters at hospital discharge (as measured by discharge weight and head circumference percentiles) when using two different methodologies (BW vesrsus current daily weight until BW is regained) for calculating fluid and protein intake in the first two weeks after birth in ELBW infants. Methods. A retrospective review of infants weighing ≤ 1kg at birth was conducted from January 2005 to December 2009  and January 2012 to December 2014  in a tertiary care NICU. At this center, in P1 (2005-09) CW was exclusively used for calculating fluid, calorie, and protein administration till BW was regained. In P2 (2012-14), BW was exclusively used for all calculations. Both P1 and P2 periods were compared and analyzed for differences in demographics, nutritional intake, comorbid conditions, and growth outcomes. Results. We studied 146 infants with 84 and 62 infants in P1 and P2 periods, respectively. The mean gestational age was lower during Phase 1 . However, the birth weights were not different between the two periods. When the multiple-regression analysis was done using a discharge weight of >10th percentile as the dependent variable, protein intake before regaining of BW  and AGA status at birth (OR of 8.37 with 95th CI of 2.67-26.24) remained significant factors. Compared to P1, babies in P2 received 1g/kg/day more protein till BW was regained. In P1, 27% of babies who were appropriate for gestational age (AGA) for head circumference at birth became microcephalic by discharge, compared to 15.6% in P2 (p=0.03). Similarly, 75.3% of the babies who were AGA for weight at birth in P1 became small for gestational age (SGA) by discharge, compared to 16.7% in P2 (p=<0.0001). The number of days it took to regain BW was 9.6 days in P1 vs. 7 days in P2 (p=<0.0001). Conclusions. Basing nutrition calculations in ELBW on birth weight rather than current daily weight until the birth weight is regained resulted in significantly greater protein delivery, a significant decrease in the incidence of failure to thrive and smaller head circumference percentiles at discharge in ELBW infants.Since fluid and nutrition needs and delivery in ELBW infants are calculated based on their body weights, there could be a measurable difference in fluid, nutrition, and protein intake calculations based on birth weight (BW) or current weight of the infant, especially in the first two weeks of life. Theoretically, the use of current daily weight (CW) for calculations may result in decreased fluid, nutrition, and protein delivery as well as a cumulative protein deficit (cPD) over the first two weeks of life until the infant regains birth weight. However, there have been no clinical studies comparing the clinical and nutritional impact of these two strategies is unknown. During the 2nd and early 3rd trimester, fetuses receive about 4+/- 0.5gr/kg/day of protein . A studyIn the premature infant, growth and weight gain do not always occur in the first few days or weeks after birth. An ELBW infant may lose 10-20% of its birth weight (BW) and may take 2 to 3 weeks to regain its BW. Since fluid and nutrition need and delivery in ELBW infants are calculated based on their body weights, there could be a measurable difference in fluid, nutrition, and protein intake calculations based on birth weight or current weight of the infant, especially in the first two weeks of life. The issue is further complicated by the fact that fluid overload in the early newborn period is associated with negative cardiorespiratory outcomes, and most centers pay close attention to the daily fluctuations in weight when managing fluid balance in these infants . TheoretThe aims of this study were to quantify the amount of protein intake and compare growth parameters at hospital discharge (as measured by discharge weight and head circumference percentiles) when using two different methodologies (birth weight versus current daily weight until birth weight is regained) for calculating fluid and protein intake in the first two weeks after birth in ELBW infants.A retrospective review of infants weighing ≤ 1kg at birth was conducted from January 2005 to December 2009  and January 2012 to December 2014  in a tertiary care NICU. All ELBW admissions to the NICU were included except those regaining BW in ≤ 3 days, those who were transferred to another facility, or those who died before reaching discharge. Birth weight, current daily weight, caloric intake , total fluid intake (mL/kg/day), and parenteral protein intake (gm/kg/day) were recorded daily until BW was regained and until discharge. At this center, in P1 (2005-09) CW was exclusively used for calculating fluid, calorie, and protein administration till BW was regained. In P2 (2012-14), BW was exclusively used for all calculations. This study was initiated as a patient care improvement project in 2010, and recommendations were made in 2011. Hence, the follow-up phase of the project was started in 2012.Comorbid conditions that may influence an infant's nutritional needs and growth outcomes were studied. CLD (chronic lung disease) was defined as the requirement for oxygen at 36 weeks of corrected gestational age . PDA , infants were gavage-fed ≤15ml/kg/day for seven days. Soon after birth, protein-based early parenteral nutrition was initiated with infants being given 2g/kg/day within 24 hours of birth. Fluids are initially started at 80-100 ml/kg/day and advanced as needed based on serum sodium levels. Enteral nutrition is calculated based on formula nutrient composition and average breast milk composition. Protein intake was calculated to provide 3-4 g/kg/day in the first week of life based on the current weight. Subsequently, daily administration of a protein of 3-4g/kg/day, calories of 120-130 kcal/kg/day, and fluids of 135-155 ml/kg/day was targeted based on CW, unless an infant's condition warranted a change. Human milk fortifier was used to fortify the breast milk to 24 cal/oz. Average targeted daily weight gain was 15-20 grams/kg/d. No probiotics were administered.P2 (2012-14) infants were gavage-fed ≤15ml/kg/day for five days. Soon after birth, protein-based early parenteral nutrition was initiated with infants being given 2g/kg/day within 24 hours of birth. Protein intake was calculated to provide 3-4g/kg/day after 24 hours of age. Subsequently, daily administration of a protein of 3-4g/kg/day, calories of 120-130 kcal/kg/day, and fluids of 135-155 ml/kg/day was targeted based on BW, unless infant's condition warranted a change. Human milk fortifier was used to fortify the breast milk to 24 cal/oz. Average targeted daily weight gain was 15-20 grams/kg/d. Infants received a daily dose of probiotics .P1 and P2 periods were compared and analyzed for differences in demographics, nutritional intake, comorbid conditions, and growth outcomes.Statistical analysis was completed using SPSS v.18. Descriptive statistics were summarized using frequencies and means. Wilcoxon Signed-rank test and Chi-square analyses were used to determine associations between variables.th percentile as the dependent variable, protein intake before regaining of BW  and AGA status at birth (OR of 8.37 with 95th CI of 2.67-26.24) remained significant factors.We studied 146 infants with 84 and 62 infants in P1 and P2 periods, respectively. The demographics in both periods are given in Nutritional intake comparisons between the two periods of the study are shown in There were better growth outcomes for weight and head circumference in period 2 when current daily weight was used to calculate protein intake. The incidence of small for gestation at discharge irrespective of the birth-weight category was 78.5% in P1 and 43.5% in P2 (P = <0.001). However, In P1, 27% of babies who were appropriate for gestational age (AGA) for head circumference at birth became microcephalic by discharge, compared to 15.6% in P2 (p=0.03). Additionally, 75.3% of those AGA for weight at birth in P1 became small for gestational age (SGA) by discharge, compared to 16.7% in P2 (p=<0.0001). The number of days it took the infants to regain BW was 9.6 days in P1 vs. 7 days in P2 (p=<0.0001).There were no significant differences in other morbidities evaluated, specifically CLD, PDA, IVH, and NEC between the two periods of study .In the regression analysis for the predictors of discharge weight centiles below the 10th percentile for those who were AGA at birth showed that protein received during the first weeks until the regaining of birth weight was very significant with an odds ratio of 4.175 (95% CI 1.886-9.243) and a P value of <0.001. The number of calories delivered before regaining of birth weight (P = 0.995. OR-1. 95% CI = 0.965-1.036), NEC (P = 0.07. OR- 0.119. 95% CI = 0.012-1.165), and PDA  were not significant.The use of birth weight (BW) rather than current daily weight (CW) in calculating fluid and nutritional intakes during the initial part of an infant's stay in the NICU leads to significantly higher protein intake and is associated with higher percentiles achieved for weight and head circumference at the time of discharge. We believe that this simple change in NICU practice may have significant benefits for ELBW infants.It has been shown that, just in the course of routine NICU care, preterm infants of ≤30 weeks could accumulate up to 14+/-3 g/kg of protein deficit in the first week of life . SenterrWhen using CW for nutritional calculations, we found that there was an average of a 2 gm/kg deficit of protein in the first week of life with some infants losing up to a 6.9 gm/kg during P1. It is possible that this protein deficit may not have been adequately compensated for, which led to significantly poorer weight and head circumference growth during P1 compared to P2. This may have an impact on future neurodevelopmental outcomes in these infants. Our findings may be corroborated by a recent study that showed that, for each gram/kg increase in protein delivery in the first week, there was an increase of 8.2 points in MDI  . AnotherAnother aspect of neonatal physiology that impacts this issue is that a fetus in utero receives increasing amounts of protein every day, which accounts for its continuously increasing growth with advancing gestation. In contrast, soon after birth, this increasing protein transfer is not accounted for in the infant's nutrition, and the infant loses weight and may become catabolic. It may take up to a week or longer to regain BW and reverse the catabolic changes. During this period, even in the best circumstances, the infant would receive significantly less protein and other nutrients than it would have in utero. Therefore, there is a need for an additional allowance of nutritional requirements for catch-up growth .The practice of using current daily weight (CW) for nutritional calculations does not appear to have any physiological basis. The concern for fluid overload and poor respiratory outcomes as raised by Van Mater et al.  may not A limitation of our study is that it is retrospective, and, hence, all confounders such as use of antenatal steroids, chorioamnionitis, hemodynamically significant PDA, and probiotics cannot be controlled. However, PDA, NEC, and calories were not significant in the regression analysis for AGA infants developing postnatal growth restriction. Though we did not detect a difference in the incidence of NEC, the study was not, however, powered to detect it. We have not evaluated long-term developmental/neurological outcomes in this cohort. Therefore, it cannot be inferred that our practice change had a long-term positive impact on neurological outcomes. However, the use of birth weight for calculating protein provision in the first few days to a week of life may significantly reduce the postnatal growth restriction and microcephaly in preterm infants weighing ≤ 1kg at birth. Multiple logistic regression analysis confirmed that protein administration before the regain of birth weight could significantly affect discharge weight percentiles.Basing nutrition calculations in ELBW on birth weight rather than current daily weight until the birth weight is regained resulted in significantly higher protein delivery, a significant decrease in the incidence of failure to thrive, and smaller head circumference percentiles at discharge in ELBW infants. The findings from this single-center retrospective study with historical controls need to be corroborated with a larger multicenter population of ELBW infants to confirm the above conclusion.