Abnormal structural covariance networks in young adults with recent cannabis use.

BACKGROUND: Recent cannabis use (RCU) exerts adverse effects on the brain. However, the effect of RCU on structural covariance networks (SCNs) is still unclear. This retrospective cross-sectional study aimed to explore the effects of RCU on SCNs in young adults in terms of whole cerebral cortical thickness (CT) and cortical surface area (CSA). METHODS: A total of 117 participants taking tetrahydrocannabinol (RCU group) and 896 participants not using cannabis (control group) were included in this study. All participants underwent MRI scanning following urinalysis screening, after which FreeSurfer 5.3 was used to calculate the CT and CSA, and SCNs matrices were constructed by Brain Connectivity Toolbox. Subsequently, the global and nodal network measures of the SCNs were computed based on these matrices. A nonparametric permutation test was used to investigate the group differences by Matlab. RESULTS: Regarding global network measures of CT, young adults with RCU exhibited altered small-worldness (P = 0.020) and clustering coefficient (P = 0.031) compared to controls, whereas there were no significant group differences in terms of SCNs constructed with CSA. Additionally, SCNs based on CT and CSA displayed abnormal nodal degree, nodal efficiency, and nodal betweenness centrality in vital brain regions of the triple network, including the dorsolateral and ventrolateral prefrontal cortex, and anterior cingulate cortex. CONCLUSION: The effects of RCU on brain structure in young adults can be detected by SCNs, in which structural abnormalities in the triple network are dominant, indicating that RCU can be detrimental to brain function.

Clinical landscape of citrin deficiency: A global perspective on a multifaceted condition.

Citrin deficiency is an autosomal recessive disorder caused by a defect of citrin resulting from mutations in SLC25A13. The clinical manifestation is very variable and comprises three types: neonatal intrahepatic cholestasis caused by citrin deficiency (NICCD: OMIM 605814), post-NICCD including failure to thrive and dyslipidemia caused by citrin deficiency, and adult-onset type II citrullinemia (CTLN2: OMIM 603471). Frequently, NICCD can run with a mild clinical course and manifestations may resolve in the post-NICCD. However, a subset of patients may develop CTLN2 when they become more than 18 years old, and this condition is potentially life-threatening. Since a combination of diet with low-carbohydrate and high-fat content supplemented with medium-chain triglycerides is expected to ameliorate most manifestations and to prevent the progression to CTLN2, early detection and intervention are important and may improve long-term outcome in patients. Moreover, infusion of high sugar solution and/or glycerol may be life-threatening in patients with citrin deficiency, particularly CTLN2. The disease is highly prevalent in East Asian countries but is more and more recognized as a global entity. Since newborn screening for citrin deficiency has only been introduced in a few countries, the diagnosis still mainly relies on clinical suspicion followed by genetic testing or selective metabolic screening. This paper aims at describing (1) the different stages of the disease focusing on clinical aspects; (2) the current published clinical situation in East Asia, Europe, and North America; (3) current efforts in increasing awareness by establishing management guidelines and patient registries, hereby illustrating the ongoing development of a global network for this rare disease.

RNet: a network strategy to predict RNA binding preferences.

Determining the RNA binding preferences remains challenging because of the bottleneck of the binding interactions accompanied by subtle RNA flexibility. Typically, designing RNA inhibitors involves screening thousands of potential candidates for binding. Accurate binding site information can increase the number of successful hits even with few candidates. There are two main issues regarding RNA binding preference: binding site prediction and binding dynamical behavior prediction. Here, we propose one interpretable network-based approach, RNet, to acquire precise binding site and binding dynamical behavior information. RNetsite employs a machine learning-based network decomposition algorithm to predict RNA binding sites by analyzing the local and global network properties. Our research focuses on large RNAs with 3D structures without considering smaller regulatory RNAs, which are too small and dynamic. Our study shows that RNetsite outperforms existing methods, achieving precision values as high as 0.701 on TE18 and 0.788 on RB9 tests. In addition, RNetsite demonstrates remarkable robustness regarding perturbations in RNA structures. We also developed RNetdyn, a distance-based dynamical graph algorithm, to characterize the interface dynamical behavior consequences upon inhibitor binding. The simulation testing of competitive inhibitors indicates that RNetdyn outperforms the traditional method by 30%. The benchmark testing results demonstrate that RNet is highly accurate and robust. Our interpretable network algorithms can assist in predicting RNA binding preferences and accelerating RNA inhibitor design, providing valuable insights to the RNA research community.

Data collection systems for active safety surveillance of vaccines during pregnancy in low- and middle-income countries: developing and piloting an assessment tool (VPASS).

BACKGROUND: There is an urgent need for active safety surveillance to monitor vaccine exposure during pregnancy in low- and middle-income countries (LMICs). Existing maternal, newborn, and child health (MNCH) data collection systems could serve as platforms for post-marketing active surveillance of maternal immunization safety. To identify sites using existing systems, a thorough assessment should be conducted. Therefore, this study had the objectives to first develop an assessment tool and then to pilot this tool in sites using MNCH data collection systems through virtual informant interviews. METHODS: We conducted a rapid review of the literature to identify frameworks on population health or post-marketing drug surveillance. Four frameworks that met the eligibility criteria were identified and served to develop an assessment tool capable of evaluating sites that could support active monitoring of vaccine safety during pregnancy. We conducted semi-structured interviews in six geographical sites using MNCH data collection systems (DHIS2, INDEPTH, and GNMNHR) to pilot domains included in the assessment tool. RESULTS: We developed and piloted the "VPASS (Vaccines during Pregnancy - sites supporting Active Safety Surveillance) assessment tool" through interviews with nine stakeholders, including central-level systems key informants and site-level managers from DHIS2 and GNMNHR; DHIS2 in Kampala (Uganda) and Kigali (Rwanda); GNMNHR from Belagavi (India) and Lusaka (Zambia); and INDEPTH from Nanoro (Burkina Faso) and Manhica (Mozambique). The tool includes different domains such as the system's purpose, the scale of implementation, data capture and confidentiality, type of data collected, the capability of integration with other platforms, data management policies and data quality monitoring. Similarities among sites were found regarding some domains, such as data confidentiality, data management policies, and data quality monitoring. Four of the six sites met some domains to be eligible as potential sites for active surveillance of vaccinations during pregnancy, such as a routine collection of MNCH individual data and the capability of electronically integrating individual MNCH outcomes with information related to vaccine exposure during pregnancy. Those sites were: Rwanda (DHIS2), Manhica (IN-DEPTH), Lusaka (GNMNHR), and Belagavi (GNMNHR). CONCLUSION: This study's findings should inform the successful implementation of active safety surveillance of vaccines during pregnancy by identifying and using active individual MNCH data collection systems in LMICs.

Corrigendum: Different frequency bands in various regions of the brain play different roles in the onset and wake-sleep stages of infantile spasms.

[This corrects the article DOI: 10.3389/fped.2022.878099.].

Global or local: The future of biotech.

Biotech start-ups often begin as domestic companies relying on local resources and talent, but this approach might not be effective in achieving rapid growth and long-term success, particularly for developing new therapeutics that require significant resources and extensive commitment. Here, we argue that born-global biotechs are better equipped to tackle major industry challenges, such as innovation, resource constraints, and limited talent diversity, especially in current challenging times. We also highlight the importance of capital efficiency in maximizing the benefits of being a born-global biotech, and provide an operational framework, based on the FlyWheel concept, for becoming a successful born-global biotech.

Different Frequency Bands in Various Regions of the Brain Play Different Roles in the Onset and Wake-Sleep Stages of Infantile Spasms.

Objective: The study aimed to identify the signatures of brain networks using electroencephalogram (EEG) in patients with infantile spasms (IS). Methods: Scalp EEGs of subjects with IS were prospectively collected in the first year of life (n = 8; age range 4-8 months; 3 males, 5 females). Ten minutes of ictal and interictal EEGs were clipped and filtered into different EEG frequency bands. The values of each pair of EEG channels were directly compared between ictal with interictal onsets and the sleep-wake phase to calculate IS brain network attributes: characteristic path length (CPL), node degree (ND), clustering coefficient (CC), and betweenness centrality (BC). Results: CPL, ND, and CC of the fast waves decreased while BC increased. CPL and BC of the slow waves decreased, while ND and CC increased during the IS ictal onset (P < 0.05). CPL of the alpha decreased, and BC increased during the waking time (P < 0.05). Conclusion: The transmission capability of the fast waves, the local connectivity, and the defense capability of the slow waves during the IS ictal onset were enhanced. The alpha band played the most important role in both the global and local networks during the waking time. These may represent the brain network signatures of IS.

NSCGRN: a network structure control method for gene regulatory network inference.

Accurate inference of gene regulatory networks (GRNs) is an essential premise for understanding pathogenesis and curing diseases. Various computational methods have been developed for GRN inference, but the identification of redundant regulation remains a challenge faced by researchers. Although combining global and local topology can identify and reduce redundant regulations, the topologies' specific forms and cooperation modes are unclear and real regulations may be sacrificed. Here, we propose a network structure control method [network-structure-controlling-based GRN inference method (NSCGRN)] that stipulates the global and local topology's specific forms and cooperation mode. The method is carried out in a cooperative mode of 'global topology dominates and local topology refines'. Global topology requires layering and sparseness of the network, and local topology requires consistency of the subgraph association pattern with the network motifs (fan-in, fan-out, cascade and feedforward loop). Specifically, an ordered gene list is obtained by network topology centrality sorting. A Bernaola-Galvan mutation detection algorithm applied to the list gives the hierarchy of GRNs to control the upstream and downstream regulations within the global scope. Finally, four network motifs are integrated into the hierarchy to optimize local complex regulations and form a cooperative mode where global and local topologies play the dominant and refined roles, respectively. NSCGRN is compared with state-of-the-art methods on three different datasets (six networks in total), and it achieves the highest F1 and Matthews correlation coefficient. Experimental results show its unique advantages in GRN inference.

Health care in pregnancy during the COVID-19 pandemic and pregnancy outcomes in six low- and-middle-income countries: Evidence from a prospective, observational registry of the Global Network for Women's and Children's Health.

OBJECTIVE: To assess, on a population basis, the medical care for pregnant women in specific geographic regions of six countries before and during the first year of the coronavirus disease 2019 (COVID-19) pandemic in relationship to pregnancy outcomes. DESIGN: Prospective, population-based study. SETTING: Communities in Kenya, Zambia, the Democratic Republic of the Congo, Pakistan, India and Guatemala. POPULATION: Pregnant women enrolled in the Global Network for Women's and Children's Health's Maternal and Newborn Health Registry. METHODS: Pregnancy/delivery care services and pregnancy outcomes in the pre-COVID-19 time-period (March 2019-February 2020) were compared with the COVID-19 time-period (March 2020-February 2021). MAIN OUTCOME MEASURES: Stillbirth, neonatal mortality, preterm birth, low birthweight and maternal mortality. RESULTS: Across all sites, a small but statistically significant increase in home births occurred between the pre-COVID-19 and COVID-19 periods (18.9% versus 20.3%, adjusted relative risk [aRR] 1.12, 95% CI 1.05-1.19). A small but significant decrease in the mean number of antenatal care visits (from 4.1 to 4.0, p = <0.0001) was seen during the COVID-19 period. Of outcomes evaluated, overall, a small but significant decrease in low-birthweight infants in the COVID-19 period occurred (15.7% versus 14.6%, aRR 0.94, 95% CI 0.89-0.99), but we did not observe any significant differences in other outcomes. There was no change observed in maternal mortality or antenatal haemorrhage overall or at any of the sites. CONCLUSIONS: Small but significant increases in home births and decreases in the antenatal care services were observed during the initial COVID-19 period; however, there was not an increase in the stillbirth, neonatal mortality, maternal mortality, low birthweight, or preterm birth rates during the COVID-19 period compared with the previous year. Further research should help to elucidate the relationship between access to and use of pregnancy-related medical services and birth outcomes over an extended period.

Factors associated with home delivery in rural Sindh, Pakistan: results from the global network birth registry.

BACKGROUND: According to global estimates for 2017, nearly 295,000 maternal deaths occurred worldwide. Thus, approximately 810 women die every day due to pregnancy-related complications. This burden of maternal deaths in LMICs is primarily due to poor healthcare service utilization, as indicated by relatively low rates of institutional deliveries and skilled-birth attendance (SBA). We conducted this study with an aim to assess the factors associated with home delivery and its subsequent effect on the pregnancy outcome in rural Sindh, Pakistan. METHODS: Data for this study were taken from The Global Network's Maternal Newborn Health Registry (MNHR), which is a prospective, population-based observational cohort study. Registry data for 2018-2019 for District Thatta, Pakistan was retrieved for the analysis. Multivariable logistic regression models were used to determine the effect of each independent variable on the place of delivery by including all predictors and covariates. Results of the regression analyses are presented with crude odds ratios (OR) and adjusted odds ratios (aOR) with 95% confidence intervals (CIs). RESULTS: A total of 4649 women were included in the study, of these, 1286 (27.7%) women had delivered at home. Of those who delivered at home, a larger proportion was illiterate (90%), had a BMI of less than 18.5 kg/m2 (26.0%), had parity of 3 or more (48.1%), and had a history of pregnancy loss as compared to women who had institutional delivery. In addition, two-thirds of women (63.4%) who had delivered at home had less than 4 ANC visits, whereas 15.6% did not receive any ANC. On multivariable logistic regression we found that home delivery was significantly associated with being illiterate (aOR = 1.60; [95% CI: 1.34, 2.04]), having high parity (aOR = 1.91; [95% CI: 1.58, 2.32]), and no ANC visit (aOR = 14.8; [95% CI: 10.2, 21.5]). CONCLUSIONS: More than a quarter of our study sample women delivered at home. These women were illiterate, multiparous, and did not receive antenatal care during pregnancy. It is essential to conduct extensive educational interventions for the women and their family members regarding the potential benefits of delivering in a safe and skilled environment. Moreover, the provision of comprehensive and quality antenatal care should be ensured as it improves the mothers' health-seeking behavior and helps them make informed decisions about their health and well-being.

Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder.

Background: The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD. Methods: High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups. Results: Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs. Conclusion: Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

Microbial Composition and Co-occurrence Patterns in the Gut Microbial Community of Normal and Obese Mice in Response to Astaxanthin.

The changes and interaction of gut microbiota, which respond to dietary supplements, play critical roles on improving human health. The modulating effect of astaxanthin on gut microbiota has been reported. However, little is known about the co-occurrence patterns among microbial taxa in response to astaxanthin. In this study, the gut microbial composition, co-occurrence patterns, and microbial correlations with physiological parameters in astaxanthin-fed normal and obese mice were studied. Astaxanthin altered the microbial composition and co-occurrence patterns in normal and obese mice. Furthermore, astaxanthin gave more profound impacts on microbiota in obesity when compared with normal mice. In group A (normal or obese mice supplemented with astaxanthin), the abundance of Acinetobacter was decreased, and Alistipes was increased by astaxanthin, which also occurred in the MA group (obese mice supplemented with astaxanthin). An operational taxonomic unit (OTU) (GreenGeneID# 4029632) assigned to the genus Bacteroides acted as a connector in the global network of A and MA groups. It may play critical roles in bridging intimate interactions between the host and other bacteria intervened by astaxanthin. Several modules correlated with physiological parameters were detected. For example, modules A12 and MA10 were significantly and negatively correlated with lipopolysaccharide (LPS) and fasting blood glucose (FBG) levels, respectively. A positive correlation was found between the node connectivity of the OTUs belonging to Clostridiaceae with LPS in obese mice, which indicated the role of Clostridiales as a potential pathological marker. Our findings provided a new interpretation of the role of astaxanthin in health and may contribute to further research on microbial community engineering.

Global Network Organization of the Fetal Functional Connectome.

Recent advances in brain imaging have enabled non-invasive in vivo assessment of the fetal brain. Characterizing brain development in healthy fetuses provides baseline measures for identifying deviations in brain function in high-risk clinical groups. We examined 110 resting state MRI data sets from fetuses at 19 to 40 weeks' gestation. Using graph-theoretic techniques, we characterized global organizational features of the fetal functional connectome and their prenatal trajectories. Topological features related to network integration (i.e., global efficiency) and segregation (i.e., clustering) were assessed. Fetal networks exhibited small-world topology, showing high clustering and short average path length relative to reference networks. Likewise, fetal networks' quantitative small world indices met criteria for small-worldness (σ > 1, ω = [-0.5 0.5]). Along with this, fetal networks demonstrated global and local efficiency, economy, and modularity. A right-tailed degree distribution, suggesting the presence of central areas that are more highly connected to other regions, was also observed. Metrics, however, were not static during gestation; measures associated with segregation-local efficiency and modularity-decreased with advancing gestational age. Altogether, these suggest that the neural circuitry underpinning the brain's ability to segregate and integrate information exists as early as the late 2nd trimester of pregnancy and reorganizes during the prenatal period. Significance statement. Mounting evidence for the fetal origins of some neurodevelopmental disorders underscores the importance of identifying features of healthy fetal brain functional development. Alterations in prenatal brain connectomics may serve as early markers for identifying fetal-onset neurodevelopmental disorders, which in turn provide improved surveillance of at-risk fetuses and support the initiation of early interventions.

Spillover Effect of the Internet on Trade Performance Based on a Vision of the Public's Sleep Health: A Spatial Study of the Global Network.

This is the first study to analyze the spatial spillover effect of the internet on trade performance based on a vision of the public's sleep health. The internet's effect on trade performance has been enhanced in a new economy consisting of larger global markets. An overall improvement in health gradually impacts economic development. In this study, hierarchical modeling is applied to reveal the effect of the internet on trade performance at a fundamental level, and the effect of sleep health on trade performance at general level. The global network is structured by a spatial weight matrix based on the Mahalanobis distance of the internet and sleep health. Furthermore, spatial autoregressive modeling is applied to study the effect of the spatial weight matrix based on the Mahalanobis distance matrix of the internet and sleep health on trade performance. The spatial Durbin modeling is applied to further analyze the interaction effect of the spatial weight matrix and countries' factors on trade performance. It was found that the internet has a positive effect on trade performance, and good sleep health can be helpful to the spillover effect of the internet on trade performance. The interaction of the spatial weight matrix and gross domestic product (GDP) can further enhance the effect. This research can assist global managers to further understand the spatial spillover effect of the internet on trade performance based on a vision of the public's sleep health.

Maternal near miss: reaching the last mile.

Maternal mortality misses the morbidity associated with pregnancy and delivery. Maternal Near Miss is an alternate measure that reflects maternal morbidity and in areas with low maternal mortality improves comparability. Maternal Near Miss is a proxy indicator of the quality of healthcare services and helps in understanding health system failures with relation to obstetric care and addressing them. But regional variations in availability of resources have led to a dozen different adapted versions of WHO Maternal Near Miss criteria. This creates confusion and reduces comparability, nationally and internationally. A review of articles defining maternal near miss was conducted using a PubMed search to compare and assess the various definitions of MNM. The present article summarises the available criteria and discusses the advantages and drawbacks of WHO MNM criteria as compared to others. The objective is to impress the need to have comprehensive criteria that can be applied in different settings and ensure comparability.Impact statementWhat is already known on this subject? Many different definitions and criteria to diagnose Maternal Near Miss are available. They are diverse, thereby reducing comparability both nationally and internationally.What do the results of this study add? This article summarises the differences in the available definitions and classifying criteria. It also highlights the difficulty in usage of the criteria in different settings.What are the implications of these findings for clinical practice and/or further research? This calls for researchers working in areas of maternal health to further simplify the definitions and criteria used for identification of Maternal Near Miss to improve comparability and uniformity.

Developing Age-Friendly Cities and Communities: Eleven Case Studies from around the World.

Developing age-friendly cities and communities has become a key part of policies aimed at improving the quality of life of older people in urban areas. The World Health Organization has been especially important in driving the 'age-friendly' agenda, notably through its Global Network of Age-Friendly Cities and Communities, connecting 1114 (2020 figure) cities and communities worldwide. Despite the expansion and achievements of the Network over the last decade, little is known about the progress made by cities developing this work around the world. This article addresses this research gap by comparing the experience of eleven cities located in eleven countries. Using a multiple case study approach, the study explores the key goals, achievements, and challenges faced by local age-friendly programs and identifies four priorities the age-friendly movement should consider to further its development: (1) changing the perception of older age; (2) involving key actors in age-friendly efforts; (3) responding to the (diverse) needs of older people; and (4) improving the planning and delivery of age-friendly programs. The article concludes by discussing the research and policy implications of these findings for the age-friendly movement.

Why are the Pakistani maternal, fetal and newborn outcomes so poor compared to other low and middle-income countries?

BACKGROUND: Pakistan has among the poorest pregnancy outcomes worldwide, significantly worse than many other low-resource countries. The reasons for these differences are not clear. In this study, we compared pregnancy outcomes in Pakistan to other low-resource countries and explored factors that might help explain these differences. METHODS: The Global Network (GN) Maternal Newborn Health Registry (MNHR) is a prospective, population-based observational study that includes all pregnant women and their pregnancy outcomes in defined geographic communities in six low-middle income countries (India, Pakistan, Democratic Republic of Congo, Guatemala, Kenya, Zambia). Study staff enroll women in early pregnancy and follow-up soon after delivery and at 42 days to ascertain delivery, neonatal, and maternal outcomes. We analyzed the maternal mortality ratios (MMR), neonatal mortality rates (NMR), stillbirth rates, and potential explanatory factors from 2010 to 2018 across the GN sites. RESULTS: From 2010 to 2018, there were 91,076 births in Pakistan and 456,276 births in the other GN sites combined. The MMR in Pakistan was 319 per 100,000 live births compared to an average of 124 in the other sites, while the Pakistan NMR was 49.4 per 1,000 live births compared to 20.4 in the other sites. The stillbirth rate in Pakistan was 53.5 per 1000 births compared to 23.2 for the other sites. Preterm birth and low birthweight rates were also substantially higher than the other sites combined. Within weight ranges, the Pakistani site generally had significantly higher rates of stillbirth and neonatal mortality than the other sites combined, with differences increasing as birthweights increased. By nearly every measure, medical care for pregnant women and their newborns in the Pakistan sites was worse than at the other sites combined. CONCLUSION: The Pakistani pregnancy outcomes are much worse than those in the other GN sites. Reasons for these poorer outcomes likely include that the Pakistani sites' reproductive-aged women are largely poorly educated, undernourished, anemic, and deliver a high percentage of preterm and low-birthweight babies in settings of often inadequate maternal and newborn care. By addressing the issues highlighted in this paper there appears to be substantial room for improvements in Pakistan's pregnancy outcomes.

Institutional deliveries and stillbirth and neonatal mortality in the Global Network's Maternal and Newborn Health Registry.

BACKGROUND: Few studies have shown how the move toward institutional delivery in low and middle-income countries (LMIC) impacts stillbirth and newborn mortality. OBJECTIVES: The study evaluated trends in institutional delivery in research sites in Belagavi and Nagpur India, Guatemala, Kenya, Pakistan, and Zambia from 2010 to 2018 and compared them to changes in the rates of neonatal mortality and stillbirth. METHODS: We analyzed data from a nine-year interval captured in the Global Network (GN) Maternal Newborn Health Registry (MNHR). Mortality rates were estimated from generalized estimating equations controlling for within-cluster correlation. Cluster-level analyses were performed to assess the association between institutional delivery and mortality rates. RESULTS: From 2010 to 2018, a total of 413,377 deliveries in 80 clusters across 6 sites in 5 countries were included in these analyses. An increase in the proportion of institutional deliveries occurred in all sites, with a range in 2018 from 57.7 to 99.8%. In 2010, the stillbirth rates ranged from 19.3 per 1000 births in the Kenyan site to 46.2 per 1000 births in the Pakistani site and by 2018, ranged from 9.7 per 1000 births in the Belagavi, India site to 40.8 per 1000 births in the Pakistani site. The 2010 neonatal mortality rates ranged from 19.0 per 1000 live births in the Kenyan site to 51.3 per 1000 live births in the Pakistani site with the 2018 neonatal mortality rates ranging from 9.2 per 1000 live births in the Zambian site to 50.2 per 1000 live births in the Pakistani site. In multivariate modeling, in some but not all sites, the reductions in stillbirth and neonatal death were significantly associated with an increase in the institutional deliveries. CONCLUSIONS: There was an increase in institutional delivery rates in all sites and a reduction in stillbirth and neonatal mortality rates in some of the GN sites over the past decade. The relationship between institutional delivery and a decrease in mortality was significant in some but not all sites. However, the stillbirth and neonatal mortality rates remain at high levels. Understanding the relationship between institutional delivery and stillbirth and neonatal deaths in resource-limited environments will enable development of targeted interventions for reducing the mortality burden. TRIAL REGISTRATION: The study is registered at clinicaltrials.gov . ClinicalTrial.gov Trial Registration: NCT01073475 .

Maternal mortality in six low and lower-middle income countries from 2010 to 2018: risk factors and trends.

BACKGROUND: Maternal mortality is a public health problem that disproportionately affects low and lower-middle income countries (LMICs). Appropriate data sources are lacking to effectively track maternal mortality and monitor changes in this health indicator over time. METHODS: We analyzed data from women enrolled in the NICHD Global Network for Women's and Children's Health Research Maternal Newborn Health Registry (MNHR) from 2010 through 2018. Women delivering within research sites in the Democratic Republic of Congo, Guatemala, India (Nagpur and Belagavi), Kenya, Pakistan, and Zambia are included. We evaluated maternal and delivery characteristics using log-binomial models and multivariable models to obtain relative risk estimates for mortality. We used running averages to track maternal mortality ratio (MMR, maternal deaths per 100,000 live births) over time. RESULTS: We evaluated 571,321 pregnancies and 842 maternal deaths. We observed an MMR of 157 / 100,000 live births (95% CI 147, 167) across all sites, with a range of MMRs from 97 (76, 118) in the Guatemala site to 327 (293, 361) in the Pakistan site. When adjusted for maternal risk factors, risks of maternal mortality were higher with maternal age > 35 (RR 1.43 (1.06, 1.92)), no maternal education (RR 3.40 (2.08, 5.55)), lower education (RR 2.46 (1.54, 3.94)), nulliparity (RR 1.24 (1.01, 1.52)) and parity > 2 (RR 1.48 (1.15, 1.89)). Increased risk of maternal mortality was also associated with occurrence of obstructed labor (RR 1.58 (1.14, 2.19)), severe antepartum hemorrhage (RR 2.59 (1.83, 3.66)) and hypertensive disorders (RR 6.87 (5.05, 9.34)). Before and after adjusting for other characteristics, physician attendance at delivery, delivery in hospital and Caesarean delivery were associated with increased risk. We observed variable changes over time in the MMR within sites. CONCLUSIONS: The MNHR is a useful tool for tracking MMRs in these LMICs. We identified maternal and delivery characteristics associated with increased risk of death, some might be confounded by indication. Despite declines in MMR in some sites, all sites had an MMR higher than the Sustainable Development Goals target of below 70 per 100,000 live births by 2030. TRIAL REGISTRATION: The MNHR is registered at NCT01073475 .

Rates and risk factors for preterm birth and low birthweight in the global network sites in six low- and low middle-income countries.

BACKGROUND: Preterm birth continues to be a major public health problem contributing to 75% of the neonatal mortality worldwide. Low birth weight (LBW) is an important but imperfect surrogate for prematurity when accurate assessment of gestational age is not possible. While there is overlap between preterm birth and LBW newborns, those that are both premature and LBW are at the highest risk of adverse neonatal outcomes. Understanding the epidemiology of preterm birth and LBW is important for prevention and improved care for at risk newborns, but in many countries, data are sparse and incomplete. METHODS: We conducted data analyses using the Global Network's (GN) population-based registry of pregnant women and their babies in rural communities in six low- and middle-income countries (Democratic Republic of Congo, Kenya, Zambia, Guatemala, India and Pakistan). We analyzed data from January 2014 to December 2018. Trained study staff enrolled all pregnant women in the study catchment area as early as possible during pregnancy and conducted follow-up visits shortly after delivery and at 42 days after delivery. We analyzed the rates of preterm birth, LBW and the combination of preterm birth and LBW and studied risk factors associated with these outcomes across the GN sites. RESULTS: A total of 272,192 live births were included in the analysis. The overall preterm birth rate was 12.6% (ranging from 8.6% in Belagavi, India to 21.8% in the Pakistani site). The overall LBW rate was 13.6% (ranging from 2.7% in the Kenyan site to 21.4% in the Pakistani site). The overall rate of both preterm birth and LBW was 5.5% (ranging from 1.2% in the Kenyan site to 11.0% in the Pakistani site). Risk factors associated with preterm birth, LBW and the combination were similar across sites and included nulliparity [RR - 1.27 (95% CI 1.21-1.33)], maternal age under 20 [RR 1.41 (95% CI 1.32-1.49)] years, severe antenatal hemorrhage [RR 5.18 95% CI 4.44-6.04)], hypertensive disorders [RR 2.74 (95% CI - 1.21-1.33], and 1-3 antenatal visits versus four or more [RR 1.68 (95% CI 1.55-1.83)]. CONCLUSIONS: Preterm birth, LBW and their combination continue to be common public health problems at some of the GN sites, particularly among young, nulliparous women who have received limited antenatal care services. Trial registration The identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475. TRIAL REGISTRATION: The identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475.