Association of maternal, obstetric, fetal, and neonatal mortality outcomes with Lady Health Worker coverage from a cross-sectional survey of >10,000 households in Gilgit-Baltistan, Pakistan.

Pakistan has among the highest rates of maternal, perinatal, and neonatal mortality globally. Many of these deaths are potentially preventable with low-cost, scalable interventions delivered through community-based health worker programs to the most remote communities. We conducted a cross-sectional survey of 10,264 households during the baseline phase of a cluster randomized controlled trial (cRCT) in Gilgit-Baltistan, Pakistan from June-August 2021. The survey was conducted through a stratified, two-stage sampling design with the objective of estimating the neonatal mortality rate (NMR) within the study catchment area, and informing implementation of the cRCT. Study outcomes were self-reported and included neonatal death, stillbirth, health facility delivery, maternal death, postpartum hemorrhage (PPH), and Lady Health Worker (LHW) coverage. Summary statistics (proportions and rates) were weighted according to the sampling design, and mixed-effects Poisson regression was conducted to explore the relationship between LHW coverage and maternal/newborn outcomes. We identified 7,600 women who gave birth in the past five years, among whom 13% reported experiencing PPH. The maternal mortality ratio was 225 maternal deaths per 100,000 live births (95% confidence interval [CI] 137-369). Among 12,376 total births, the stillbirth rate was 41.4 per 1,000 births (95% CI 36.8-46.7) and the perinatal mortality rate was 53.0 per 1,000 births (95% CI 47.6-59.0). Among 11,863 live births, NMR was 16.2 per 1,000 live births (95% CI 13.6-19.3) and 65% were delivered at a health facility. LHW home visits were associated with declines in PPH (risk ratio [RR] 0.89 per each additional visit, 95% CI 0.83-0.96) and late neonatal mortality (RR 0.80, 95% CI 0.67-0.97). Intracluster correlation coefficients were also estimated to inform the planning of future trials. The high rates of maternal, perinatal, and neonatal death in Gilgit-Baltistan continue to fall behind targets of the 2030 Sustainable Development Goals.

Trajectory of maternal depression and parasomnias.

Maternal depressive symptoms are associated with poorer sleep quality in their children. Although parasomnias can occur at any age, this group of sleep disorders is more common in children. The aim of this study was to assess whether maternal depression trajectories predict parasomnias at the age of 11 years. Data were from a Birth Cohort of 4231 individuals followed in the city of Pelotas, Brazil. Maternal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) at 12, 24, and 48 months, and 6 and 11 years postpartum. Maternal depression trajectories were calculated using a group-based modelling approach. Information on any parasomnias (confused arousals, sleepwalking, night terrors, and nightmares) was provided by the mother. Five trajectories of maternal depressive symptoms were identified: chronic-low (34.9%), chronic-moderate (41.4%), increasing (10.3%), decreasing (8.9%), and chronic-high (4.4%). The prevalence of any parasomnia at the age of 11 years was 16.8% (95% confidence interval [CI] 15.6%-18.1%). Confusional arousal was the most prevalent type of parasomnia (14.5%) and varied from 8.7% to 14.7%, 22.9%, 20.3%, and 27.5% among children of mothers at chronic-low, moderate-low, increasing, decreasing, and chronic-high trajectories, respectively (p < 0.001). Compared to children from mothers in the chronic-low trajectory, the adjusted prevalence ratio for any parasomnia was 1.58 (95% CI 1.29-1.94), 2.34 (95% CI 1.83-2.98), 2.15 (95% CI 1.65-2.81), and 3.07 (95% CI 2.31-4.07) among those from mothers in the moderate-low, increasing, decreasing, and chronic-high trajectory groups, respectively (p < 0.001). In conclusion, parasomnias were more prevalent among children of mothers with chronic symptoms of depression.

An integrated newborn care kit (iNCK) to save newborn lives and improve health outcomes in Gilgit Baltistan (GB), Pakistan: study protocol for a cluster randomized controlled trial.

BACKGROUND: Ongoing high neonatal mortality rates (NMRs) represent a global challenge. In 2021, of the 5 million deaths reported worldwide for children under five years of age, 47% were newborns. Pakistan has one of the five highest national NMRs in the world, with an estimated 39 neonatal deaths per 1,000 live births. Reducing newborn deaths requires sustainable, evidence-based, and cost-effective interventions that can be integrated within existing community healthcare infrastructure across regions with high NMR. METHODS: This pragmatic, community-based, parallel-arm, open-label, cluster randomized controlled trial aims to estimate the effect of Lady Health Workers (LHWs) providing an integrated newborn care kit (iNCK) with educational instructions to pregnant women in their third trimester, compared to the local standard of care in Gilgit-Baltistan, Pakistan, on neonatal mortality and other newborn and maternal health outcomes. The iNCK contains a clean birth kit, 4% chlorhexidine topical gel, sunflower oil emollient, a ThermoSpot™ temperature monitoring sticker, a fleece blanket, a click-to-heat reusable warmer, three 200 µg misoprostol tablets, and a pictorial instruction guide and diary. LHWs are also provided with a handheld scale to weigh the newborn. The primary study outcome is neonatal mortality, defined as a newborn death in the first 28 days of life. DISCUSSION: This study will generate policy-relevant knowledge on the effectiveness of integrating evidence-based maternal and newborn interventions and delivering them directly to pregnant women via existing community health infrastructure, for reducing neonatal mortality and morbidity, in a remote, mountainous area with a high NMR. TRIAL REGISTRATION: NCT04798833, March 15, 2021.

Associations between human milk oligosaccharides and infant growth in a Bangladeshi mother-infant cohort.

BACKGROUND: We aimed to estimate associations between human milk oligosaccharides (HMOs) and infant growth (length-for-age (LAZ) and weight-for-length (WLZ) z-scores) at 12 months postnatal age. METHODS: In this secondary analysis of data from a maternal vitamin D trial in Dhaka, Bangladesh (N = 192), absolute concentrations of HMOs were measured in 13 ± 1 week(s) postpartum milk samples, infant anthropometric measurements were obtained soon after birth and at 12 months postpartum, and infant feeding was classified during 6 months postpartum. Associations between individual HMOs or HMO groups and LAZ or WLZ were estimated by multivariable linear regression adjusting for infant feeding pattern, maternal secretor status, and other potential confounders. RESULTS: The concentrations of 6'sialyllactose, lacto-N-neotetraose, and the non-fucosylated non-sialylated HMOs were inversely associated with LAZ at 12 months of age, whereas the fucosylated non-sialylated HMO concentration was positively associated with LAZ at 12 months. These associations were robust in analyses restricted to infants who were primarily exclusively/predominantly fed human milk during the first 3 (or 6) months. CONCLUSIONS: Since HMOs are both positively and negatively associated with postnatal growth, there is a need for randomized trials to estimate the causal benefits and risks of exogenously administered HMOs on infant growth and other health outcomes. IMPACT: 6'sialyllactose, lacto-N-neotetraose, and the non-fucosylated non-sialylated human milk oligosaccharides (HMOs) were inversely associated with length-for-age z-scores (LAZ) at 12 months, whereas the fucosylated non-sialylated HMO concentration was positively associated with LAZ at 12 months among Bangladeshi infants. Associations between individual and grouped HMOs with infant length growth at 12 months were as strong or stronger in analyses restricted to infants who were exclusively or predominantly fed human milk up to 3 (or 6) months. Randomized trials are needed to characterize the effects of specific HMOs on infant growth, particularly in countries where postnatal linear growth faltering is common.

A novel systematic pipeline for increased predictability and explainability of growth patterns in children using trajectory features.

OBJECTIVE: Longitudinal patterns of growth in early childhood are associated with health conditions throughout life. Knowledge of such patterns and the ability to predict them can lead to better prevention and improved health promotion in adulthood. However, growth analyses are characterized by significant variability, and pattern detection is affected by the method applied. Moreover, pattern labelling is typically performed based on ad hoc methods, such as visualizations or clinical experience. Here, we propose a novel pipeline using features extracted from growth trajectories using mathematical, statistical and machine-learning approaches to predict growth patterns and label them in a systematic and unequivocal manner. METHODS: We extracted mathematical and clinical features from 9577 children growth trajectories embedded with machine-learning predictions of the growth patterns. We experimented with two sets of features (CAnonical Time-series Characteristics and trajectory features specific to growth), developmental periods and six machine-learning classifiers. Clinical experts provided labels for the detected patterns and decision rules were created to associate the features with the labelled patterns. The predictive capacity of the extracted features was validated on two heterogenous populations (The Applied Research Group for Kids and the 2004 Pelotas Birth Cohort, based in Canada and Brazil, respectively). RESULTS: Features predictive ability measured by accuracy and F1 score was ≥ 80% and ≥ 0.76 respectively in both cohorts. A small number of features (n = 74) was sufficient to distinguish between growth patterns in both cohorts. Slope, intercept of the trajectory, age at peak value, start value and change of the growth measure were among the top identified features. CONCLUSION: Growth features can be reliably used as predictors of growth patterns and provide an unbiased understanding of growth patterns. They can be used as tool to reduce the effort to repeat analysis and variability concerning anthropometric measures, time points and analytical methods, in the context of the same or similar populations.

Complementary and alternative metrics for tracking population-level trends in child linear growth.

Stunting prevalence is commonly used to track population-level child nutritional status. However, other metrics derived from anthropometric datasets may be used as alternatives to stunting or provide complementary perspectives on the status of linear growth faltering in low- and middle-income countries (LMICs). Data from 156 Demographic and Health Surveys in 63 LMICs (years 2000 to 2020) were used to generate 2 types of linear growth metrics: (i) measures of location of height distributions (including stunting) for under-5 years (<5y) and 2 to 5 years (2-5y); (ii) model-derived metrics including predicted mean height-for-age z-score (HAZ) at 0, 2, and 5 years; interval slopes of HAZ, height-for-age difference (HAD), and growth delay (GD) from 1 month to 2 years (1mo-2y) and 2-5y; and the SITAR intensity parameter (SITAR-IP) for <5y. Using Spearman's rank correlation coefficient (r), metrics were considered alternatives to stunting if very strongly correlated with stunting (|r|≥0.95) and at least as strongly correlated as stunting with selected population indicators (under 5y mortality, gross domestic product, maternal education). Metrics were considered complementary if less strongly correlated with stunting (|r|<0.95) yet correlated with population indicators. We identified 6 of 15 candidate metrics (stunting 2-5y, mean HAZ <5y and 2-5y, p25 HAZ <5y and 2-5y, predicted HAZ at 2y) as potential alternatives to stunting and 6 as complementary metrics (SITAR-IP, predicted HAZ at 5y, HAZ slope 1m-2y, HAD slope 1m-2y, GD slopes 1m-2y and 2-5y). Three metrics (HAZ slope 2-5y, HAD slope 2-5y years and predicted HAZ at birth) had weak correlations with population indicators (|r| ≤ 0.43). In conclusion, several linear growth metrics could serve as alternatives to stunting prevalence and others may be complementary to stunting in tracking global progress in child health and nutrition. Further research is needed to explore the real-world utility of these alternative and complementary metrics.

A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age.

Child growth patterns assessment is critical to design public health interventions. However, current analytical approaches may overlook population heterogeneity. To overcome this limitation, we developed a growth trajectories clustering pipeline that incorporates a shape-respecting distance, baseline centering (i.e., birth-size normalized trajectories) and Gestational Age (GA)-correction to characterize shape-based child growth patterns. We used data from 3945 children (461 preterm) in the 2004 Pelotas Birth Cohort with at least 3 measurements between birth (included) and 11 years of age. Sex-adjusted weight-, length/height- and body mass index-for-age z-scores were derived at birth, 3 months, and at 1, 2, 4, 6 and 11 years of age (INTERGROWTH-21st and WHO growth standards). Growth trajectories clustering was conducted for each anthropometric index using k-means and a shape-respecting distance, accounting or not for birth size and/or GA-correction. We identified 3 trajectory patterns for each anthropometric index: increasing (High), stable (Middle) and decreasing (Low). Baseline centering resulted in pattern classification that considered early life growth traits. GA-correction increased the intercepts of preterm-born children trajectories, impacting their pattern classification. Incorporating shape-based clustering, baseline centering and GA-correction in growth patterns analysis improves the identification of subgroups meaningful for public health interventions.

Construction and validation of the Oxford Neurodevelopment Assessment (OX-NDA) in 1-year-old Brazilian children.

BACKGROUND: Over 250 million children under 5 years, globally, are at risk of developmental delay. Interventions during the first 2 years of life have enduring positive effects if children at risk are identified, using standardized assessments, within this window. However, identifying developmental delay during infancy is challenging and there are limited infant development assessments suitable for use in low- and middle-income (LMIC) settings. Here, we describe a new tool, the Oxford Neurodevelopment Assessment (OX-NDA), measuring cognition, language, motor, and behaviour, outcomes in 1-year-old children. We present the results of its evaluation against the Bayley Scales of Infant Development IIIrd edition (BSID-III) and its psychometric properties. METHODS: Sixteen international tools measuring infant development were analysed to inform the OX-NDA's construction. Its agreement with the BSID-III, for cognitive, motor and language domains, was evaluated using intra-class correlations (ICCs, for absolute agreement), Bland-Altman analyses (for bias and limits of agreement), and sensitivity and specificity analyses (for accuracy) in 104 Brazilian children, aged 12 months (SD 8.4 days), recruited from the 2015 Pelotas Birth Cohort Study. Behaviour was not evaluated, as the BSID-III's adaptive behaviour scale was not included in the cohort's protocol. Cohen's kappas and Cronbach's alphas were calculated to determine the OX-NDA's reliability and internal consistency respectively. RESULTS: Agreement was moderate for cognition and motor outcomes (ICCs 0.63 and 0.68, p < 0.001) and low for language outcomes (ICC 0.30, p < 0.04). Bland-Altman analysis showed little to no bias between measures across domains. The OX-NDA's sensitivity and specificity for predicting moderate-to-severe delay on the BSID-III was 76, 73 and 43% and 75, 80 and 33% for cognition, motor and language outcomes, respectively. Inter-rater (k = 0.80-0.96) and test-rest (k = 0.85-0.94) reliability was high for all domains. Administration time was < 20 minutes. CONCLUSION: The OX-NDA shows moderate agreement with the BSID-III for identifying infants at risk of cognitive and motor delay; agreement was low for language delay. It is a rapid, low-cost assessment constructed specifically for use in LMIC populations. Further work is needed to evaluate its use (i) across domains in populations beyond Brazil and (ii) to identify language delays in Brazilian children.

A Bayesian adaptive design for clinical trials of rare efficacy outcomes with multiple definitions.

INTRODUCTION: Bayesian adaptive designs for clinical trials have gained popularity in the recent years due to the flexibility and efficiency that they offer. We consider the scenario where the outcome of interest comprises events with relatively low risk of occurrence and different case definitions resulting in varying control group risk assumptions. This is a scenario that occurs frequently for infectious diseases in global health research. METHODS: We propose a Bayesian adaptive design that incorporates different case definitions of the outcome of interest that vary in stringency. A set of stopping rules are proposed where superiority and futility may be concluded with respect to different outcome definitions and therefore maintain a realistic probability of stopping in trials with low event rates. Through a simulation study, a variety of stopping rules and design configurations are compared. RESULTS: The simulation results are provided in an interactive web application that allows the user to explore and compare the design operating characteristics for a variety of assumptions and design parameters with respect to different outcome definitions. The results for select simulation scenarios are provided in the article. DISCUSSION: Bayesian adaptive designs offer the potential for maximizing the information learned from the data collected through clinical trials. The proposed design enables monitoring and utilizing multiple composite outcomes based on rare events to optimize the trial design operating characteristics.

Growth delay: an alternative measure of population health based on child height distributions.

BACKGROUND: Indicators of child height, such as mean height-for-age Z-scores (HAZ), height-for-age difference (HAD) and stunting prevalence, do not account for differences in population-average bone developmental stage. AIM: Propose a measure of child height that conveys the dependency of linear growth on stage rather than chronological age. SUBJECTS AND METHODS: Using Demographic and Health Surveys (2000-2018; 64 countries), we generated: (1) predicted HAZ at specific ages (HAZ regressed on age); (2) height-age (age at which mean height matches the WHO Growth Standards median); (3) Growth delay (GD), the difference between chronological age and height-age; (4) HAD; and (5) stunting prevalence. Metrics were compared based on secular trends within countries and age-related trajectories within surveys. RESULTS: In the most recent surveys (N = 64), GDs ranged from 1.9 to 19.1 months at 60 months chronological age. Cross-sectionally, HAZ, HAD and GD were perfectly correlated, and showed similar secular trends. However, age-related trajectories differed across metrics. Accumulating GD with age demonstrated growth faltering as slower than expected growth for children of the same height-age. Resumption of growth at the median for height-age was rarely observed. CONCLUSION: GD is a population-level measure of child health that reflects the role of delayed skeletal development in linear growth faltering.

Direct financial assistance for improved maternal and child health data: a pilot study supporting the health management information system in Malawi.

BACKGROUND: The health management information system (HMIS) is an integral component of a strong health care system. Despite its importance for decision-making, the quality of HMIS data remains of concern in low- and middle-income countries. To address challenges with the quality of maternal and child health (MCH) data gathered within Malawi's HMIS, we conducted a pilot study evaluating different support modalities to district-level HMIS offices. We hypothesized that providing regular, direct financial assistance to HMIS offices would enable staff to establish strategies and priorities based on local context, resulting in more accurate, timely, and complete MCH data. METHODS: The pilot intervention was implemented in Mwanza district, while Chikwawa, Neno, and Ntchisi districts served as control sites given support received from other institutions. The intervention consisted of providing direct financial assistance to Mwanza's HMIS office following the submission of detailed budgets and lists of planned activities. In the control districts, we performed interviews with the HMIS officers to track the HMIS-related activities. We evaluated the intervention by comparing data quality between the post- and pre-intervention periods in the intervention and control districts. Additionally, we conducted interviews with Mwanza's HMIS office staff to determine the acceptability and appropriateness of the intervention. RESULTS: Following the 10-month intervention period, we observed improvements in MCH data quality in Mwanza. The availability and completeness of MCH data collected in the registers increased by 22 and 18 percentage points, respectively. The consistency of MCH data between summary reports and electronic HMIS also improved. In contrast, 2/3 control districts noted minimal changes or reductions in data quality after 10 months. The qualitative interviews confirmed that, despite some challenges, the intervention was well received by the participating HMIS office. HMIS staff preferred our strategy to other conventional strategies that fail to give them the independence to make decisions. CONCLUSIONS: This pilot intervention demonstrated an alternative approach to support HMIS offices in their daily efforts to improve data quality. Given the Ministry of Health's (MoH) interest in strengthening its HMIS, our intervention provides a strategy that the MoH and local and international partners could consider to rapidly improve HMIS data with minimal oversight.

Influence of maternal excess weight before pregnancy on breast-feeding and weaning: pooled analyses of four population-based cohorts born between 1982 and 2015.

To investigate the associations of maternal excess weight before pregnancy with (1) weaning at 3 months of age, (2) duration of exclusive breast-feeding at 6 months of age, (3) duration of any breast-feeding at 12 months of age and (4) to compare the magnitude of these associations over four decades. Data were from participants in the Pelotas (Brazil) Birth Cohorts born in 1982 (n 5334), 1993 (n 1442), 2004 (n 4092) and 2015 (n 4102). Maternal pre-pregnancy weight was collected after the delivery and breast-feeding status was assessed when children were 3 and 12 months old. Only in the most recent cohort (2015), women with excess weight (BMI ≥ 25 kg/m2) before pregnancy had higher risk of discontinuing exclusive breast-feeding within the first 6 months postpartum than women with normal weight (hazard ratio = 1·22 (95 % CI 1·15, 1·30)). Duration of any type of breast-feeding until 12 months of age was not affected by pre-pregnancy weight. Excess weight before pregnancy is associated with exclusive breast-feeding only in the most recent birth cohort coinciding with increases in excess weight and breast-feeding over time.

Combined Clinical Audits and Low-Dose, High-frequency, In-service Training of Health Care Providers and Community Health Workers to Improve Maternal and Newborn Health in Mali: Protocol for a Pragmatic Cluster Randomized Trial.

BACKGROUND: Although most births in Mali occur in health facilities, a substantial number of newborns still die during delivery and within the first 7 days of life, mainly because of existing training deficiencies and the challenges of maintaining intrapartum and postpartum care skills. OBJECTIVE: This trial aims to assess the effectiveness and cost-effectiveness of an intervention combining clinical audits and low-dose, high-frequency (LDHF) in-service training of health care providers and community health workers to reduce perinatal mortality. METHODS: The study is a three-arm cluster randomized controlled trial in the Koulikoro region in Mali. The units of randomization are each of 84 primary care facilities. Each trial arm will include 28 facilities. The facilities in the first intervention arm will receive support in implementing mortality and morbidity audits, followed by one-day LDHF training biweekly, for 6 months. The health workers in the second intervention arm (28 facilities) will receive a refresher course in maternal neonatal and child health (MNCH) for 10 days in a classroom setting, in addition to mortality and morbidity audits and LDHF hands-on training for 6 months. The control arm, also with 28 facilities, will consist solely of the standard MNCH refresher training delivered in a classroom setting. The main outcomes are perinatal deaths in the intervention arms compared with those in the control arm. A final sample of approximately 600 deliveries per cluster was expected for a total of 30,000 newborns over 14 months. Data sources included both routine health records and follow-up household surveys of all women who recently gave birth in the study facility 7 days postdelivery. Data collection tools will capture perinatal deaths, complications, and adverse events, as well as the status of the newborn during the perinatal period. A full economic evaluation will be conducted to determine the incremental cost-effectiveness of each of the case-based focused LDHF hands-on training strategies in comparison to MNCH refresher training in a classroom setting. RESULTS: The trial is complete. The recruitment began on July 15, 2019, and data collection began on July 23, 2019, and was completed in November 2020. Data cleaning or analyses began at the time of submission of the protocol. CONCLUSIONS: The results will provide policy makers and practitioners with crucial information on the impact of different health care provider training modalities on maternal and newborn health outcomes and how to successfully implement these strategies in resource-limited settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT03656237; https://clinicaltrials.gov/ct2/show/NCT03656237. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28644.

Adolescents' experiences with group antenatal care: Insights from a mixed-methods study in Senegal.

OBJECTIVES: Group antenatal care (G-ANC) is an innovative model in which antenatal care is delivered to a group of 8-12 women of similar gestational age. Evidence from high-income countries suggests G-ANC is particularly effective for women from marginalised populations, including adolescents. The objective of this study was to examine the experiences of Senegalese adolescents engaged in group antenatal care. METHODS: This convergent parallel mixed-methods study is derived from a larger effectiveness-implementation hybrid pilot study conducted in Kaolack district, Senegal. Quantitative data for adolescent participants were collected through baseline and postnatal surveys and descriptively analysed. One-on-one interviews and focus-group discussions were conducted with adolescent participants, and qualitative data were analysed using qualitative descriptive analysis. RESULTS: Forty-five adolescents aged 15-19 participated in G-ANC, with a median age of 18 years. The majority (93.3%) were married, and 64.4% were nulliparous. Findings indicated similar levels of G-ANC participation for adolescent and adult women. The majority (93.1%) of participants who had previously attended individual ANC indicated they would prefer G-ANC to individual care for a future pregnancy. Qualitative findings indicated key facets of consideration relevant to G-ANC for adolescents include social connectedness, the influence of social norms and the opportunity for engagement in healthcare. CONCLUSIONS: This study suggests that G-ANC has the potential to be an adolescent-responsive and culturally appropriate method of delivering antenatal care in Senegal.

Tools for measuring gender equality and women's empowerment (GEWE) indicators in humanitarian settings.

BACKGROUND: Effective measurement of Gender Equality and Women's Empowerment (GEWE) is challenging in low and middle-income countries (LMICs), and even more so in humanitarian settings. Conflict, natural disasters, and epidemics may increase gender inequities, but also present an opportunity to address them. This scoping review describes and identifies gaps in the measurement tools, methods, and indicators used to measure GEWE in humanitarian settings, and presents a dashboard that can be used by researchers, organizations and governments to identify GEWE measurement tools. METHODS: Scientific articles published between January 2004 and November 2019 were identified using Embase, Medline, PsycInfo, CINAHL, Scopus, and PAIS index. Relevant non peer-reviewed literature was downloaded from the websites of humanitarian organizations. Publications on women and/or girls impacted by a humanitarian crisis in a LMIC, within 5 years of data collection, were included. Publications were double-screened in the title/abstract and full-text stages. We used a machine learning software during the title/abstract screening to increase the efficiency of the process. Measurement tools, sampling and data collection methods, gap areas (geographical, topical and contextual), and indicators were catalogued for easy access in an interactive Tableau dashboard. RESULTS: Our search yielded 27,197 publications and 2396 non peer-reviewed literature reports. One hundred and seventy publications were included in the final review. Extracted indicators were categorized into seven domains: economic, health, human development, leadership, psychological, security and justice, and sociocultural. The vast majority of studies were observational, and over 70% utilized a cross-sectional study design. Thirty-eight toolkits and questionnaires were identified in this review, of which 19 (50%) were designed specifically for humanitarian settings. Sociocultural was the largest domain in number of studies and indicators in this review, with gender-based violence indicators reported in 66% of studies. Indicators of economic, human development and leadership were uncommon in the peer-reviewed literature. DISCUSSION: While there has been some effort to measure GEWE in conflict-affected and other humanitarian settings, measurement has largely focused on violence and security issues. A more comprehensive framework for measuring GEWE in these settings is needed; objective measurement of women's empowerment and gender equality should be prioritized by organizations providing humanitarian aid.

A novel development indicator based on population-average height trajectories of children aged 0-5 years modelled using 145 surveys in 64 countries, 2000-2018.

INTRODUCTION: Children's growth status is an important measure commonly used as a proxy indicator of advancements in a country's health, human capital and economic development. We aimed to assess the feasibility of using Super-Imposition by Translation And Rotation (SITAR) models for summarising population-based cross-sectional height-by-age data of children under 5 years across 64 countries. METHODS: Using 145 publicly available Demographic and Health Surveys of children under 5 years across 64 low-income and middle-income countries from 2000 to 2018, we created a multicountry pseudo-longitudinal dataset of children's heights. RESULTS: SITAR models including two parameters (size and intensity) explained 81% of the between-survey variation in mean boys' height and 80% in mean girls' height. Size parameters for boys and girls (relative to the WHO child growth standards) were distributed non-normally around a mean of -5.2 cm for boys (range: -7.9 cm to -1.6 cm) and -4.9 cm for girls (range: -7.7 cm to -1.2 cm). Boys exhibited 10% slower linear growth compared with the WHO (range: 19.7% slower to 1.6% faster) and girls 11% slower linear growth compared with the WHO (range: 21.4% slower to 1.0% faster). Variation in the SITAR size parameter was ≥90% explained by the combination of average length within the first 60 days of birth (as a proxy for fetal growth) and intensity, regardless of sex, with much greater contribution by postnatal intensity (r≥0.89 between size and intensity). CONCLUSIONS: SITAR models with two random effects can be used to model child linear growth using multicountry pseudo-longitudinal data, and thereby provide a feasible alternative approach to summarising early childhood height trajectories based on survey data. The SITAR intensity parameter may be a novel indicator for specifically tracking progress in the determinants of postnatal growth in low-income and middle-income countries.

Maternal perinatal depression and infant sleep problems at 1 year of age: Subjective and actigraphy data from a population-based birth cohort study.

This study used data from 2,222 mothers and infants participating in a population-based birth cohort to verify whether maternal depression in the perinatal period was associated with poor infant sleep. Mothers who scored ≥13 points on the Edinburgh Postnatal Depression Scale at 16-24 weeks of gestation and/or 3 months after delivery were considered perinatally depressed. The main outcome variable was poor infant sleep at 12 months of age, defined as >3 night wakings, nocturnal wakefulness >1 hr or total sleep duration <9 hr. Infant sleep data were obtained with the Brief Infant Sleep Questionnaire (BISQ) and 24-hr actigraphy monitoring. Prevalence of perinatal depression in the sample was 22.3% (95% confidence interval [CI], 20.5-24.0). After Poisson regression, infants of depressed mothers showed an adjusted relative risk (RR) of 1.44 (95% CI, 1.00-2.08; p = .04) for >3 night wakings with questionnaire-derived data. When actigraphy data were analysed, no association was found between perinatal depression and poor infant sleep (adjusted RR, 1.20; 95% CI, 0.82-1.74; p = .35). In conclusion, although mothers in the depressed group were more likely to report more night wakings, objective data from actigraphy did not replicate this finding. Dysfunctional cognition, maternal behavioural factors and sleep impairment associated with perinatal depression may affect the mother's impression of her infant's sleep.

Relationship of Patent Ductus Arteriosus Echocardiographic Markers With Descending Aorta Diastolic Flow.

OBJECTIVES: To characterize the relationship of echocardiographic markers of left heart overload and flow in peripheral major end-organ vessels (eg, celiac artery) with the presence of reversed holodiastolic flow in the descending aorta, considered a surrogate marker of an increased transductal shunt volume, in preterm patients with a patent ductus arteriosus (PDA). METHODS: This work was a retrospective study of data from echocardiography performed to investigate the hemodynamic significance of a PDA in preterm patients. We studied differences in echocardiographic markers of the PDA shunt volume according to patterns of flow in the postductal descending aorta (no PDA, PDA with antegrade diastolic flow, and PDA with reversed diastolic flow). The strength of the association between each echocardiographic marker and the presence of aortic holodiastolic flow reversal was investigated. RESULTS: We studied 137 patients with a median (interquartile range) birth weight of 850 (694-1030) g and a median gestational age of 25 (24-27) weeks. Among patients with a PDA (113), those with diastolic flow reversal in the descending aorta (44) presented had increased echocardiographic markers representative of the shunt volume (increased left ventricular output, left atrial-to-aortic ratio, pulmonary vein D wave, and shorter isovolumic relaxation time) compared to those with aortic antegrade diastolic flow. A positive, albeit weak, correlation between diastolic flow reversal and shunt volume echocardiographic markers was found. Abnormal diastolic flow in the celiac artery had the strongest correlation (R2  = 0.24). CONCLUSIONS: In preterm patients with a PDA, echocardiographic markers of the shunt volume were more abnormal in patients with reversed diastolic flow in the descending aorta. These data support the assumption that variance in these markers are related to the shunt volume, which needs consideration when adjudicating hemodynamic significance.

Behavioural characteristics and abdominal obesity among Brazilian shift working women.

OBJECTIVE: To explore the association between behavioural characteristics with the prevalence of abdominal obesity (AO) among a population of Southern Brazilian shift working women. DESIGN: A cross-sectional study was conducted. AO was estimated using waist circumference (WC), and it was used to classify women as having AO (WC ≥ 88 cm). Prevalence ratios were estimated using Poisson regression with robust variance. SETTING: A large plastic utensils company in Southern Brazil. PARTICIPANTS: 450 female shift workers. RESULTS: The prevalence of the AO in the women shift workers was 44·5 % (95 % CI 40·0, 49·2 %). In night shift workers, the prevalence of AO was 56·1 % compared with 40·9 % among hybrid shift workers. After adjustments for covariates, women who were current smokers had a decrease in the prevalence of AO compared with those who never smoked. Women who had three or fewer meals per day had a 46 % increase in the AO prevalence compared with those eating more frequent meals. Night shift work was associated with increase in AO prevalence compared with hybrid shift (PR 1·33; 95 % CI: 1·08, 1·64). CONCLUSIONS: Our findings indicate that behavioural characteristics are associated with a high prevalence of AO in female shift workers, thus suggesting that behavioural modifications among women working shifts, such as increase in meal frequency and physical activity, may reduce AO.

Effect of Correcting the Postnatal Age of Preterm-Born Children on Measures of Associations Between Infant Length-for-Age z Scores and Mid-Childhood Outcomes.

Child growth standards are commonly used to derive age- and sex-standardized anthropometric indices but are often inappropriately applied to preterm-born children (<37 weeks of gestational age (GA)) in epidemiology studies. Using the 2004 Pelotas Birth Cohort, we examined the impact of correcting for GA in the application of child growth standards on the magnitude and direction of associations in 2 a priori-selected exposure-outcome scenarios: infant length-for-age z score (LAZ) and mid-childhood body mass index (scenario A), and infant LAZ and mid-childhood intelligence quotient (scenario B). GA was a confounder that had a strong (scenario A) or weak (scenario B) association with the outcome. Compared with uncorrected postnatal age, using GA-corrected postnatal age attenuated the magnitude of associations, particularly in early infancy, and changed inferences for associations at birth. Although differences in the magnitude of associations were small when GA was weakly associated with the outcome, model fit was meaningfully improved using corrected postnatal age. When estimating population-averaged associations with early childhood growth in studies where preterm- and term-born children are included, incorporating heterogeneity in GA at birth in the age scale used to standardize anthropometric indices postnatally provides a useful strategy to reduce standardization errors.