Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting.

Small newborns are vulnerable to mortality and lifelong loss of human capital. Measures of vulnerability previously focused on liveborn low-birthweight (LBW) babies, yet LBW reduction targets are off-track. There are two pathways to LBW, preterm birth and fetal growth restriction (FGR), with the FGR pathway resulting in the baby being small for gestational age (SGA). Data on LBW babies are available from 158 (81%) of 194 WHO member states and the occupied Palestinian territory, including east Jerusalem, with 113 (58%) having national administrative data, whereas data on preterm births are available from 103 (53%) of 195 countries and areas, with only 64 (33%) providing national administrative data. National administrative data on SGA are available for only eight countries. Global estimates for 2020 suggest 13·4 million livebirths were preterm, with rates over the past decade remaining static, and 23·4 million were SGA. In this Series paper, we estimated prevalence in 2020 for three mutually exclusive types of small vulnerable newborns (SVNs; preterm non-SGA, term SGA, and preterm SGA) using individual-level data (2010-20) from 23 national datasets (∼110 million livebirths) and 31 studies in 18 countries (∼0·4 million livebirths). We found 11·9 million (50% credible interval [Crl] 9·1-12·2 million; 8·8%, 50% Crl 6·8-9·0%) of global livebirths were preterm non-SGA, 21·9 million (50% Crl 20·1-25·5 million; 16·3%, 14·9-18·9%) were term SGA, and 1·5 million (50% Crl 1·2-4·2 million; 1·1%, 50% Crl 0·9-3·1%) were preterm SGA. Over half (55·3%) of the 2·4 million neonatal deaths worldwide in 2020 were attributed to one of the SVN types, of which 73·4% were preterm and the remainder were term SGA. Analyses from 12 of the 23 countries with national data (0·6 million stillbirths at ≥22 weeks gestation) showed around 74% of stillbirths were preterm, including 16·0% preterm SGA and approximately one-fifth of term stillbirths were SGA. There are an estimated 1·9 million stillbirths per year associated with similar vulnerability pathways; hence integrating stillbirths to burden assessments and relevant indicators is crucial. Data can be improved by counting, weighing, and assessing the gestational age of every newborn, whether liveborn or stillborn, and classifying small newborns by the three vulnerability types. The use of these more specific types could accelerate prevention and help target care for the most vulnerable babies.

Neonatal mortality risk of vulnerable newborns by fine stratum of gestational age and birthweight for 230 679 live births in nine low- and middle-income countries, 2000-2017.

OBJECTIVE: To describe the mortality risks by fine strata of gestational age and birthweight among 230 679 live births in nine low- and middle-income countries (LMICs) from 2000 to 2017. DESIGN: Descriptive multi-country secondary data analysis. SETTING: Nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION: Liveborn infants from 15 population-based cohorts. METHODS: Subnational, population-based studies with high-quality birth outcome data were invited to join the Vulnerable Newborn Measurement Collaboration. All studies included birthweight, gestational age measured by ultrasound or last menstrual period, infant sex and neonatal survival. We defined adequate birthweight as 2500-3999 g (reference category), macrosomia as ≥4000 g, moderate low as 1500-2499 g and very low birthweight as <1500 g. We analysed fine strata classifications of preterm, term and post-term: ≥42+0 , 39+0 -41+6 (reference category), 37+0 -38+6 , 34+0 -36+6 ,34+0 -36+6 ,32+0 -33+6 , 30+0 -31+6 , 28+0 -29+6 and less than 28 weeks. MAIN OUTCOME MEASURES: Median and interquartile ranges by study for neonatal mortality rates (NMR) and relative risks (RR). We also performed meta-analysis for the relative mortality risks with 95% confidence intervals (CIs) by the fine categories, stratified by regional study setting (sub-Saharan Africa and Southern Asia) and study-level NMR (≤25 versus >25 neonatal deaths per 1000 live births). RESULTS: We found a dose-response relationship between lower gestational ages and birthweights with increasing neonatal mortality risks. The highest NMR and RR were among preterm babies born at <28 weeks (median NMR 359.2 per 1000 live births; RR 18.0, 95% CI 8.6-37.6) and very low birthweight (462.8 per 1000 live births; RR 43.4, 95% CI 29.5-63.9). We found no statistically significant neonatal mortality risk for macrosomia (RR 1.1, 95% CI 0.6-3.0) but a statistically significant risk for all preterm babies, post-term babies (RR 1.3, 95% CI 1.1-1.5) and babies born at 370 -386 weeks (RR 1.2, 95% CI 1.0-1.4). There were no statistically significant differences by region or underlying neonatal mortality. CONCLUSIONS: In addition to tracking vulnerable newborn types, monitoring finer categories of birthweight and gestational age will allow for better understanding of the predictors, interventions and health outcomes for vulnerable newborns. It is imperative that all newborns from live births and stillbirths have an accurate recorded weight and gestational age to track maternal and neonatal health and optimise prevention and care of vulnerable newborns.

Delivery and postnatal care among women in 71 low- and middle-income countries: analyzing coverage gaps using household surveys.

BACKGROUND: High levels of maternal morbidity and mortality persist in low- and middle-income countries, despite increases in coverage of facility delivery and skilled assistance at delivery. We compared levels of facility birth to a summary delivery care measure and quantified gaps. METHODS: We approximated a delivery care score from type of delivery (home, lower-level facility, or hospital), skilled attendant at delivery, a stay of 24-or-more-hours after delivery, and a health check within 48-h after delivery. Data were obtained from 333,316 women aged 15-49 who had a live birth in the previous 2 years, and from 71 countries with nationally representative surveys between 2013 and 2020. We computed facility delivery and delivery care coverage estimates to assess the gap. We stratified the analysis by country characteristics, including the national maternal mortality ratio (MMR), to assess the size of coverage gaps, and we assessed missed opportunities through coverage cascades. We looked at the association between MMR and delivery care coverage. RESULTS: Delivery care coverage varied by country, ranging from 24% in Sudan to 100% in Cuba. Median coverage was 70% with an interquartile range of 30 percentage points (55% and 85%). The cascade showed that while 76% of women delivered in a facility, only 41% received all four interventions. Coverage gaps exist across all MMR levels. Gaps between highest and lowest wealth quintiles were greatest in countries with MMR levels of 100 or higher, and the gap narrowed in countries with MMR levels below 100. The delivery care indicator had a negative association with MMR. CONCLUSIONS: In addition to providing high-quality evidenced-based care to women during birth and the postpartum period, there is also a need to address gaps in delivery care, which occur within and between countries, wealth quintiles, and MMR phases.

Climate shocks and nutrition: The role of food security policies and programs in enhancing maternal and neonatal survival in Niger.

Niger is afflicted with high rates of poverty, high fertility rates, frequent environmental crises, and climate change. Recurrent droughts and floods have led to chronic food insecurity linked to poor maternal and neonatal nutrition outcomes in vulnerable regions. We analyzed maternal and neonatal nutrition trends and subnational variability between 2000 and 2021 with a focus on the implementation of policies and programs surrounding two acute climate shocks in 2005 and 2010. We used four sources of data: (a) national household surveys for maternal and newborn nutritional indicators allowing computation of trends and differences at national and regional levels; (b) document review of food security reports; (c) 30 key informant interviews and; (d) one focus group discussion. Many food security policies and nutrition programs were enacted from 2000 to 2020. Gains in maternal and neonatal nutrition indicators were more significant in targeted vulnerable regions of Maradi, Zinder, Tahoua and Tillabéri, from 2006 to 2021. However, poor access to financial resources for policy execution and suboptimal implementation of plans have hindered progress. In response to the chronic climate crisis over the last 20 years, the Nigerien government and program implementers have demonstrated their commitment to reducing food insecurity and enhancing resilience to climate shocks by adopting a deliberate multisectoral effort. However, there is more that can be achieved with a continued focus on vulnerable regions to build resilience, targeting high risk populations, and investing in infrastructure to improve health systems, food systems, agriculture systems, education systems, and social protection.

Neonatal mortality risk of large-for-gestational-age and macrosomic live births in 15 countries, including 115.6 million nationwide linked records, 2000-2020.

OBJECTIVE: We aimed to compare the prevalence and neonatal mortality associated with large for gestational age (LGA) and macrosomia among 115.6 million live births in 15 countries, between 2000 and 2020. DESIGN: Population-based, multi-country study. SETTING: National healthcare systems. POPULATION: Liveborn infants. METHODS: We used individual-level data identified for the Vulnerable Newborn Measurement Collaboration. We calculated the prevalence and relative risk (RR) of neonatal mortality among live births born at term + LGA (>90th centile, and also >95th and >97th centiles when the data were available) versus term + appropriate for gestational age (AGA, 10th-90th centiles) and macrosomic (≥4000, ≥4500 and ≥5000 g, regardless of gestational age) versus 2500-3999 g. INTERGROWTH 21st served as the reference population. MAIN OUTCOME MEASURES: Prevalence and neonatal mortality risks. RESULTS: Large for gestational age was common (median prevalence 18.2%; interquartile range, IQR, 13.5%-22.0%), and overall was associated with a lower neonatal mortality risk compared with AGA (RR 0.83, 95% CI 0.77-0.89). Around one in ten babies were ≥4000 g (median prevalence 9.6% (IQR 6.4%-13.3%), with 1.2% (IQR 0.7%-2.0%) ≥4500 g and with 0.2% (IQR 0.1%-0.2%) ≥5000 g). Overall, macrosomia of ≥4000 g was not associated with increased neonatal mortality risk (RR 0.80, 95% CI 0.69-0.94); however, a higher risk was observed for birthweights of ≥4500 g (RR 1.52, 95% CI 1.10-2.11) and ≥5000 g (RR 4.54, 95% CI 2.58-7.99), compared with birthweights of 2500-3999 g, with the highest risk observed in the first 7 days of life. CONCLUSIONS: In this population, birthweight of ≥4500 g was the most useful marker for early mortality risk in big babies and could be used to guide clinical management decisions.

Neonatal mortality risk of vulnerable newborns: A descriptive analysis of subnational, population-based birth cohorts for 238 203 live births in low- and middle-income settings from 2000 to 2017.

OBJECTIVE: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low- and middle-income countries (LMICs). DESIGN: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000. SETTING: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION: Live birth neonates. METHODS: We categorically defined five vulnerable newborn types based on size (large- or appropriate- or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies. MAIN OUTCOME MEASURES: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. RESULTS: There were 238 203 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.6, interquartile range [IQR] 2.0-2.9), PT + LGA (median RR 7.3, IQR 2.3-10.4), PT + AGA (median RR 6.0, IQR 4.4-13.2) and PT + SGA (median RR 10.4, IQR 8.6-13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies. CONCLUSIONS: Small and/or preterm babies in LIMCs have a considerably increased mortality risk compared with babies born at term and larger. This classification system may advance the understanding of the social determinants and biomedical risk factors along with improved treatment that is critical for newborn health.

Psychosocial Assessment Tools for Youth with Type 1 Diabetes: a 10-Year Review.

PURPOSE OF REVIEW: There is a notable lack of consistency in the measurement of psychosocial factors affecting youth with type 1 diabetes, resulting in a need for increased measurement standardization and establishment of measures tailored to capture unique experiences faced by youth. This review sought to assess 10 years of extant literature (2011 to 2020) to identify which established measurement tools are commonly used and to evaluate new measurement tools that were introduced during this period. RECENT FINDINGS: There are a variety of psychosocial factors affecting youth, and assessment of these measures has shown substantial variability. Our review found that most frequently cited scales were those pertaining to self-efficacy, diabetes distress, family conflict, autonomy, and fear of hypoglycemia. During our review period, experts developed and validated 21 new scales, the majority of which sought to evaluate areas pertaining to diabetes distress. Of the common scales and newly developed scales identified in this review, psychometric properties showcase high reliability and validity, and items are becoming increasingly specific to youth but still lack assessment of how youth perceive technology's impact on diabetes management. The field would benefit from measures employing more nuanced age specificity and addressing technology usage.

Demographic, socio-economic, obstetric, and behavioral factors associated with small-and large-for-gestational-age from a prospective, population-based pregnancy cohort in rural Nepal: a secondary data analysis.

BACKGROUND: In South Asia, a third of babies are born small-for-gestational age (SGA). The risk factors are well described in the literature, but many studies are in high-and-middle income countries or measure SGA on facility births only. There are fewer studies that describe the prevalence of risk factors for large-for-gestational age (LGA) in low-income countries. We aim to describe the factors associated with SGA and LGA in a population-based cohort of pregnant women in rural Nepal. METHODS: This is a secondary data analysis of community-based trial on neonatal oil massage (22,545 women contributing 39,479 pregnancies). Demographic, socio-economic status (SES), medical/obstetric history, and timing of last menstruation were collected at enrollment. Vital signs, illness symptoms, and antenatal care (ANC) attendance were collected throughout the pregnancy and neonatal weight was measured for live births. We conducted multivariate analysis using multinomial, multilevel logistic regression, reporting the odds ratio (OR) with 95% confidence intervals (CIs). Outcomes were SGA, LGA compared to appropriate-for-gestational age (AGA) and were multiply imputed using birthweight recalibrated to time at delivery. RESULTS: SGA was associated with nulligravida (OR: 2.12 95% CI: 1.93-2.34), gravida/nulliparous (OR: 1.86, 95% CI: 1.26-2.74), interpregnancy intervals less than 18 months (OR: 1.16, 95% CI: 1.07-1.27), and poor appetite/vomiting in the second trimester, (OR: 1.27, 95% CI: 1.19-1.35). Greater wealth (OR: 0.78, 95% CI: 0.69-0.88), swelling of hands/face in the third trimester (OR: 0.81, 95% CI: 0.69-0.94) parity greater than five (OR: 0.77, 95% CI: 0.65-0.92), male fetal sex (OR: 0.91, 95% CI: 0.86-0.98), and increased weight gain (OR: 0.93 per weight kilogram difference between 2nd and 3rd trimester, 95% CI: 0.92-0.95) were protective for SGA. Four or more ANC visits (OR: 0.53, 95% CI: 0.41-0.68) and respiratory symptoms in the third trimester (OR: 0.67, 95% CI: 0.54-0.84) were negatively associated with LGA, and maternal age < 18 years (OR: 1.39, 95% CI: 1.03-1.87) and respiratory symptoms in the second trimester (OR: 1.27, 95% CI: 1.07-1.51) were positively associated with LGA. CONCLUSIONS: Our findings are in line with known risk factors for SGA. Because the prevalence and mortality risk of LGA babies is low in this population, it is likely LGA status does not indicate underlaying illness. Improved and equitable access to high quality antenatal care, monitoring for appropriate gestational weight gain and increased monitoring of women with high-risk pregnancies may reduce prevalence and improve outcomes of SGA babies. TRIAL REGISTRATION: The study used in this secondary data analysis was registered at Clinicaltrials.gov NCT01177111.

Barriers and facilitators to influenza and pneumococcal vaccine hesitancy in rheumatoid arthritis: a qualitative study.

OBJECTIVES: Immunization is an essential component of RA care. Nevertheless, vaccine coverage in RA is suboptimal. Contextual, individual and vaccine-related factors influence vaccine acceptance. However, barriers and facilitators of vaccination in RA are not well defined. The aim of this study was to assess perspectives of RA patients and healthcare professionals (HCPs) involved in RA care of barriers and facilitators regarding influenza and pneumococcal vaccines. METHODS: Eight focus groups (four with RA patients and four with HCPs) and eight semi-structured open-ended individual interviews with vaccine-hesitant RA patients were conducted. Data were audio recorded, transcribed verbatim and imported to MAXQDA software. Analysis using the framework of vaccine hesitancy proposed by the Strategic Advisory Group of Experts on Immunization was conducted. RESULTS: RA patients and HCPs reported common and specific barriers and facilitators to influenza vaccination that included contextual, individual and/or group and vaccine- and/or vaccination-specific factors. A key contextual influence on vaccination was patients' perception of the media, pharmaceutical industry, authorities, scientists and the medical community at large. Among the individual-related influences, experiences with vaccination, knowledge/awareness and beliefs about health and disease prevention were considered to impact vaccine acceptance. Vaccine-related factors including concerns about vaccine side effects such as RA flares, the safety of new formulations, the mechanism of action, access to vaccines and costs associated with vaccination were identified as actionable barriers. CONCLUSION: Acknowledging RA patients' perceived barriers to influenza and pneumococcal vaccination and implementing specific strategies to address them might increase vaccination coverage in this population.

Estimating population-based coverage of reproductive, maternal, newborn, and child health (RMNCH) interventions from health management information systems: a comprehensive review.

BACKGROUND: Routinely collected health facility data usually captured and stored in Health Management Information Systems (HMIS) are potential sources of data for frequent and local disaggregated estimation of the coverage of reproductive, maternal, newborn, and child health interventions (RMNCH), but have been under-utilized due to concerns over data quality. We reviewed methods for estimation of national or subnational coverage of RMNCH interventions using HMIS data exclusively or in conjunction with survey data from low- and middle-income countries (LMICs). METHODS: We conducted a comprehensive review of studies indexed in PubMed and Scopus to identify potential papers based on predefined search terms. Two reviewers screened the papers using defined inclusion and exclusion criteria. Following sequences of title, abstract and full paper reviews, we retained 18 relevant papers. RESULTS: 12 papers used only HMIS data and 6 used both HMIS and survey data. There is enormous lack of standards in the existing methods for estimating RMNCH intervention coverage; all appearing to be highly author dependent. The denominators for coverage measures were estimated using census, non-census and combined projection-based methods. No satisfactory methods were found for treatment-based coverage indicators for which the estimation of target population requires the population prevalence of underlying conditions. The estimates of numerators for the coverage measures were obtained from the count of users or visits and in some cases correction for completeness of reporting in the HMIS following an assessment of data quality. CONCLUSIONS: Standard methods for correcting numerators from HMIS data for accurate estimation of coverage of RMNCH interventions are needed to expand the use of these data. More research and investments are required to improve denominators for health facility-derived statistics. Improvement in routine data quality and analytical methods would allow for timely estimation of RMNCH intervention coverage at the national and subnational levels.

Disrespectful care in family planning services among youth and adult simulated clients in public sector facilities in Malawi.

BACKGROUND: Provision of high-quality family planning (FP) services improves access to contraceptives. Negative experiences in maternal health have been documented worldwide and likely occur in other services including FP. This study aims to quantify disrespectful care for adult and adolescent women accessing FP in Malawi. METHODS: We used simulated clients (SCs) to measure disrespectful care in a census of public facilities in six districts of Malawi in 2018. SCs visited one provider in each of the 112 facilities: two SCs visits (one adult and one adolescent case scenario) or 224 SC visits total. We measured disrespectful care using a quantitative tool and field notes and report the prevalence and 95% confidence intervals for the indicators and by SC case scenarios contextualized with quotes from the field notes. RESULTS: Some SCs (12%) were refused care mostly because they did not agree to receive a HIV test or vaccination, or less commonly because the clinic was closed during operating hours. Over half (59%) of the visits did not have privacy. The SCs were not asked their contraceptive preference in 57% of the visits, 28% reported they were not greeted respectfully, and 20% reported interruptions. In 18% of the visits the SCs reported humiliation such as verbal abuse. Adults SCs received poorer counseling compared to the adolescent SCs with no other differences found. CONCLUSIONS: We documented instances of refusal of care, lack of privacy, poor client centered care and humiliating treatment by providers. We recommend continued effort to improve quality of care with an emphasis on client treatment, regular quality assessments that include measurement of disrespectful care, and more research on practices to reduce it.

Comparability of family planning quality of care measurement tools in low-and-middle income country settings: a systematic review.

BACKGROUND: In low-and-middle income countries (LMICs), accurate measures of the elements of quality care provided by a health worker through family planning services (also known as process quality) are required to ensure family's contraceptives needs are being met. There are many tools used to assess family planning process quality of care (QoC) but no one standardized method. Those measuring QoC in LMICs should select an appropriate tool based the program context and financial/logistical parameters, but they require data on how well each tool measures routine clinical care. We aim to synthesize the literature on validity/comparability of family planning process QoC measurement tools through a quantitative systematic review with no meta-analysis. METHODS: We searched six literature databases for studies that compared quality measurements from different tools using quantitative statistics such as sensitivity/specificity, kappa statistic or absolute difference. We extracted the comparative measure along with other relevant study information, organized by quality indicator domain (e.g. counseling and privacy), and then classified the measure by low, medium, and high agreement. RESULTS: We screened 8172 articles and identified eight for analysis. Studies comparing quality measurements from simulated clients, direct observation, client exit interview, provider knowledge quizzes, and medical record review were included. These eight studies were heterogenous in their methods and the measurements compared. There was insufficient data to estimate overall summary measures of validity for the tools. Client exit interviews compared to direct observation or simulated client protocols had the most data and they were a poor proxy of the actual quality care received for many measurements. CONCLUSION: To measure QoC consistently and accurately in LMICs, standardized tools and measures are needed along with an established method of combining them for a comprehensive picture of quality care. Data on how different tools proxy quality client care will inform these guidelines. Despite the small number of studies found during the review, we described important differences on how tools measure quality of care.

Accurate measures of process quality of care­or how well clinicians deliver services according to standards of care­are important to monitor, evaluate and improve service quality. Periodic surveys of health facilities or provider are the main source of national or regional quality of care data in many low- and middle-income countries. Many tools are used for these surveys: exit interviews with patients, observations of the visits by a clinician-assessor, simulated or mystery patients, and others. Implementers must select the appropriate and feasible tools for their program, context and setting but there is little information on how well different tools measure the same quality of care indicators.This review summarizes the current literature on the validity of measurements from different family planning quality of care tools. We found only eight studies, but we were able to see some differences important to consider when selecting the most appropriate tool. For instance, patients reported different events through an exit interview than what was documented by the assessor during the same visit. Exit interviews may be more appropriate to measure client experience or satisfaction rather than specifics of the care received. Knowing these differences will help implementers choose an appropriate tool depending on the focus of the quality assessment. This review contributes to the body of knowledge on improving quality of care measurements, resulting in better data to improve family planning services for patients.

Obtaining district-level health estimates using geographically masked location from Demographic and Health Survey data.

BACKGROUND: Demographic and Health Survey (DHS) data are an important source of maternal, newborn, and child health as well as nutrition information for low- and middle-income countries. However, DHSs are often unavailable at the administrative unit that is most interesting or useful for program planning. In addition, the location of DHS survey clusters are geomasked within 10 km, and prior to 2009, may have crossed district boundaries. We aim to use DHS surveyed information with these geomasked coordinates to estimate district assignments for use in health program planning and evaluation. METHODS: We developed three methods to assign a district to a geomasked survey cluster in two DHS surveys from Malawi: 2000 and 2004. Method A assigns districts of origin in proportion to the likelihood that results from repeated simulated geomasking, allowing more than one possible district of origin. Method B assigns a single district of origin which contains the greatest proportion of simulated geomasked survey clusters. Method C maps the geomasked survey cluster's location to a district polygon. We used these method assignments to estimate a selection of commonly used coverage indicators for each district. We compared the district coverage estimates, confidence intervals, and concordance correlation coefficients, by each of the methods, to those which used validated district assignments in 2004, and we looked at coverage change from 2000 to 2004. RESULTS: The methods we tested each approximated the validated estimates in 2004 by confidence interval comparison and concordance correlation coefficient. Estimated agreement for method A was between .14 and .98, for method B the estimated agreement was between .97 and .99, and for method C the agreement ranged from .93 to .99 when compared with the validated district assignments. Therefore, we recommend the protocol which is the simplest to implement-method C-overlaying geomasked survey cluster within district polygon. CONCLUSIONS: Using geomasked survey clusters from DHSs to assign districts provided district level coverage rates similar to those using the validated surveyed locations. This method may be applied to data sources where survey cluster centroids are available and where district level estimates are needed for program implementation and evaluation in low- and middle-income settings. This method is of special interest to those using DHSs to study spatiotemporal trends as it allows for the utilization of historic DHS data where geomasking hinders the generation of reliable subnational estimates of health in areas smaller than the first-order administrative unit (ADM1).

Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival.

Conceived in 2003 and born in 2005 with the launch of its first report and country profiles, the Countdown to 2015 for Maternal, Newborn, and Child Survival has reached its originally proposed lifespan. Major reductions in the deaths of mothers and children have occurred since Countdown's inception, even though most of the 75 priority countries failed to achieve Millennium Development Goals 4 and 5. The coverage of life-saving interventions tracked in Countdown increased steadily over time, but wide inequalities persist between and within countries. Key drivers of coverage such as financing, human resources, commodities, and conducive health policies also showed important, yet insufficient increases. As a multistakeholder initiative of more than 40 academic, international, bilateral, and civil society institutions, Countdown was successful in monitoring progress and raising the visibility of the health of mothers, newborns, and children. Lessons learned from this initiative have direct bearing on monitoring progress during the Sustainable Development Goals era.

Modeling potential reduction of child mortality after national scale-up of community-based treatment of childhood illnesses in Ethiopia.

BACKGROUND: Since 2010, 28,000 female health extension workers (IEWs) received training and support to provide integrated community based case management (iCCM) of childhood pneumonia, diarrhea, malaria, and se- vere malnutrition in Ethiopia. OBJECTIVE: We conducted a modeling exercise using two scenarios to project the potential reduction of the under five mortality, riate due io the iCCM program in the four agrarian regions of Ethiopia. METHODS. We created three projections: (1) baseline projection without iCCM; (2) a "moderate" projection using 2012 coverage data scaled up to 30% by 2015 and (3) a "best case" scenario scaled up to 80% with 50% of newborns with sepsis receiving effective treatment by 2015. RESULTS. If the 2012 coverage gains (moderate projection) were applied to the four agrarian regions, we project that the iCCM program could have saved over 10,000 additional lives per year among children age 1-59 months. If iCCM coverage reaches the, "best case" scenario, nearly 80,000 additional lives among children 1-59 months of age would be saved between 2012 and 2015. CONCLUSION. High quality iCCM, delivered and used at scale, is an important contributor to the reduction of under five mortality in rural Ethiopia. Continued investments in iCCM are critical to sustaining and improving recent declines in child mortality.

Assessment of the monitoring and evaluation system for integrated community case management (ICCM) in Ethiopia: a comparison against global benchmark indicators.

BACKGROUND: Program managers require feasible, timely, reliable, and valid measures of iCCM implementation to identify problems and assess progress. The global iCCM Task Force developed benchmark indicators to guide implementers to develop or improve monitoring and evaluation (M&E) systems. OBJECTIVE: To assesses Ethiopia's iCCM M&E system by determining the availability and feasibility of the iCCM benchmark indicators. METHODS: We conducted a desk review of iCCM policy documents, monitoring tools, survey reports, and other rele- vant documents; and key informant interviews with government and implementing partners involved in iCCM scale-up and M&E. RESULTS: Currently, Ethiopia collects data to inform most (70% [33/47]) iCCM benchmark indicators, and modest extra effort could boost this to 83% (39/47). Eight (17%) are not available given the current system. Most benchmark indicators that track coordination and policy, human resources, service delivery and referral, supervision, and quality assurance are available through the routine monitoring systems or periodic surveys. Indicators for supply chain management are less available due to limited consumption data and a weak link with treatment data. Little information is available on iCCM costs. CONCLUSION: Benchmark indicators can detail the status of iCCM implementation; however, some indicators may not fit country priorities, and others may be difficult to collect. The government of Ethiopia and partners should review and prioritize the benchmark indicators to determine which should be included in the routine M&E system, especially since iCCMdata are being reviewed for addition to the HMIS. Moreover, the Health Extension Worker's reporting burden can be minimized by an integrated reporting approach.

Coverage and equitability of interventions to prevent child mortality in rural Jimma and West Hararghe Zones, Oromia Region, Ethiopia.

BACKGROUND: Interventions to prevent childhood illnesses are important components of the Ethiopian Health Extension Program (HEP). Although the HEP was designed to reduce inequities in access to health care, there is little evidence on equitability of preventive interventions in Ethiopia. PURPOSE: This article describes coverage of preventive interventions and how many interventions individual children received We also examined which factors were associated with the number of preventive interventions received, and assessed the extent to which interventions were equitably distributed. METHODS: We conducted a cross-sectional survey in 3,200 randomly selected households in the rural Jimma and West Hararghe Zones of Ethiopia's Oromia Region. We calculated coverage of 10 preventive interventions and a composite of eight interventions (co-coverage) representing the number of interventions received by children. Mul- tiple linear regressions were used to assess associations between co-coverage and explanatory variables. Finally, we assessed the equitability of preventive interventions by comparing coverage among children in the poorest and the least poor wealth quintiles. RESULTS: Coverage was less than 50% for six of the 10 interventions. Children received on average only three of the eight interventions included in the co-coverage calculation. Zone, gender, caretaker age, religion, and household wealth were all significantly associated with co-coverage, controlling for key covariates. Exclusive breastfeeding, vaccine uptake, and vitamin A supplementation were all relatively equitable. On the other hand, coverage of insecticide-treated nets or indoor residual spraying (ITN/IRS) and access to safe water were significantly higher among the least poor children compared to children in the poorest quintile. CONCLUSION: Coverage of key interventions to prevent childhood illnesses is generally low in Jimma and West Hararghe. Although a number of interventions were equitably distributed, there were marked wealth-based inequities for interventions that are possessed at the household level, even among relatively homogeneous rural communities.

Psychometric properties of the Mini-Balance Evaluation Systems Test and physical function measures in patients with Ehlers-Danlos syndrome/hypermobility spectrum disorders.

PURPOSE: Ehlers-Danlos syndrome (EDS) and hypermobility spectrum disorders (HSD) are associated with impairments in balance and physical function. However, the psychometric properties of relevant outcome measures remain largely unexplored. The objectives of this study were to evaluate the construct validity of the Mini-Balance Evaluation Systems Test (Mini-BESTest) alongside the test-retest reliability of the Mini-BESTest, Six Minute Walk Test (6MWT), and Lower Extremity Functional Scale (LEFS) in patients with the hypermobility subtype of EDS (hEDS) and HSD. MATERIALS AND METHODS: Participants with hEDS/HSD (n = 20) attended two visits scheduled one to two weeks apart. The construct validity of the Mini-BESTest was determined through Pearson correlations between force plate balance measures, 6MWT, and LEFS. Test-retest reliability of the measures was evaluated through intraclass correlation coefficients (ICC). Minimal detectable change values with 95% confidence (MDC95) were also calculated. RESULTS: Mini-BESTest demonstrated significant correlations with force plate measures, 6MWT, and LEFS (r = -0.41 to 0.66). Test-retest reliability was excellent for the Mini-BESTest, 6MWT, and LEFS (ICC = 0.91 to 0.96). MDC95 was 4 for the Mini-BESTest, 77 m for the 6MWT, and 11 for the LEFS. CONCLUSION: The Mini-BESTest is valid and reliable for assessing balance and mobility in patients with hEDS/HSD.IMPLICATIONS FOR REHABILITATIONThe Mini Balance Evaluation Systems Test (Mini-BESTest) is valid in capturing aspects of balance and physical function in patients with hypermobile Ehlers-Danlos syndrome or hypermobility spectrum disorders.However, the Mini-BESTest may show a potential ceiling effect for high functioning patients in this population.The Mini-BESTest, 6 Minute Walk Test, and the Lower Extremity Functional Scale also show excellent test-retest reliability in this population.The Minimal Detectable Change with 95% confidence intervals is 4 for the Mini-BESTest, 77 m for the 6 Minute Walk Test, and 11 for the Lower Extremity Functional Scale in this population.

Factors Predicting Completion of Four or More Antenatal Care Visits in Sarlahi District, Nepal.

Background: A significant number of women die from pregnancy and childbirth complications globally, particularly in low- and middle-income countries (LMICs). Receiving at least four antenatal care (ANC) visits may be important in reducing maternal and perinatal deaths. This study investigates factors associated with attending ≥ 4 ANC visits in Sarlahi district of southern Nepal. Methods: A secondary analysis was conducted on data from the Nepal Oil Massage Study (NOMS), a cluster-randomized, community-based longitudinal pregnancy cohort study encompassing 34 Village Development Committees. We quantified the association between receipt/attendance of ≥ 4 ANC visits and socioeconomic, demographic, morbidity, and pregnancy history factors using logistic regression; Generalized Estimating Equations were used to account for multiple pregnancies per woman. Results: All pregnancies resulting in a live birth (n=31,867) were included in the model and 31.4% of those pregnancies received 4+ ANC visits. Significant positive associations include socioeconomic factors such as participation in non-farming occupations for women (OR=1.52, 95% CI: 1.19, 1.93), higher education (OR=1.79, 95% CI: 1.66, 1.93) and wealth quintile OR=1.44, 95% CI: 1.31, 1.59), nutritional status such as non-short stature (OR=1.17, 95% CI: 1.07, 1.27), obstetric history such as adequate interpregnancy interval (OR=1.31, 95% CI: 1.19, 1.45) and prior pregnancy but no live birth (OR=2.14, 95% CI: 1.57, 2.92), symptoms such as vaginal bleeding (OR=1.35, 95% CI:1.11, 1.65) and awareness of the government's conditional cash transfer ANC program (OR=2.26, 95% CI: 2.01, 2.54). Conversely, belonging to the lower Shudra caste (OR=0.56, 95% CI: 0.47, 0.67), maternal age below 18 or above 35 (OR=0.81, 95% CI:0.74, 0.88; OR=0.77, 95% CI: 0.62, 0.96)), preterm birth (OR=0.41, 95% CI: 0.35, 0.49), parity ≥ 1 (OR=0.66, 95% CI: 0.61, 0.72), and the presence of hypertension during pregnancy (OR=0.79, 95% CI: 0.69, 0.90) were associated with decreased likelihood of attending ≥ 4 ANC visits. Conclusions: These findings underscore the importance of continuing and promoting the government's program and increasing awareness among women. Moreover, understanding these factors can guide interventions aimed at encouraging ANC uptake in the most vulnerable groups, subsequently reducing maternal-related adverse outcomes in LMICs. Trial registration: The clinicaltrial.gov trial registration number for NOMS was #NCT01177111. Registration date was August 6th, 2010.

Quality adjusted coverage of family planning services in low- and middle-income countries: Analysis of 33 countries using Demographic and Health Survey data.

Background: Monitoring service quality for family planning programmes in low- and middle-income countries (LMICs) has been challenging due to data availability. Self-reported service quality from Demographic and Health Surveys (DHS) can provide additional information on quality beyond simple service contact. Methods: The DHS collects need, use and counselling for contraceptives. We used this data from 33 LMICs to develop quality-adjusted demand for modern family planning satisfied indicator (DFPSq). We compared it with the crude indicator (demand for family planning satisfied (DFPS)) and performed an equity analysis. Median, interquartile ranges (IQR) and the absolute and relative gap by country were used to describe the findings. Results: The median DFPS was 49% (IQR = 41-57%) and the median DPFSq was 19% (IQR = 14-27%). We found similar relative differences in the gap stratified by SES indicating quality was universally low. One exception is that adolescents had a higher relative gap (70%, IQR = 57-79%) compared to adults (54%, IQR = 46-68%), indicating lower quality access. Conclusions: Severe and pervasive quality gaps exist in family planning services across most LMICs. Our novel DFPSq indicator is one additional tool for monitoring access and quality of service that is critical to meet the family planning needs of women.