BackgroundThe presence of skilled birth attendants (SBAs) is crucial in childbirth to reduce the maternal mortality ratio (MMR) and to achieve the maternal mortality target of the United Nations’ Sustainable Development Goals (SDGs). The aim of this study was to investigate the factors related to childbirths attended by SBAs in Bangladesh.MethodsData from the Bangladesh Demographic and Health Survey (2014 BDHS) were analyzed. Logistic regression was applied to calculate crude odds ratios (CORs), adjusted odds ratios (AORs), 95% confidence intervals (CIs), and p-values.ResultsIn Bangladesh, 35.9% of deliveries were attended by SBAs, and 44.2% of those women received at least one antenatal check-up by a skilled provider. The deliveries by SBAs were less than 50% of the total deliveries in all divisions, excluding Khulna. Known pregnancy complications (AOR: 1.2; 95% CI: 1.1–1.4), higher level of education in both women (AOR: 1.7; 95% CI: 1.2–2.3) and their husbands (AOR: 1.8; 95% CI: 1.3–2.4), receiving antenatal care (ANC) by a skilled provider during the pregnancy period (AOR: 1.5; 95% CI: 1.1–2.1), and higher wealth quintiles (AOR: 3.4; 95% CI: 2.5–4.7) were all significantly associated with an increased likelihood of a delivery by SBAs (p <0.05). In contrast, women living in rural areas (AOR: 0.7; 95% CI: 0.6–0.8) and the Sylhet Division (AOR: 0.4; 95% CI: 0.3–0.5) were less likely to be delivered by SBAs.ConclusionsTo achieve the target of the Government of Bangladesh - 50% of deliveries to be attended by SBAs - it is important to increase ANC services and awareness programs in all seven divisions of Bangladesh. Special focus in rural areas is also required to meet this target. A new study should be conducted to explore the unexamined factors associated with the presence of SBAs during childbirth.

IMPORTANCEMost of the global morbidity and mortality in chronic obstructive pulmonary disease (COPD) occurs in low-and middle-income countries (LMICs), with significant economic effects.OBJECTIVE To assess the discriminative accuracy of 3 instruments using questionnaires and peak expiratory flow (PEF) to screen for COPD in 3 LMIC settings. DESIGN, SETTING, AND PARTICIPANTSA cross-sectional analysis of discriminative accuracy, conducted between January 2018 and March 2020 in semiurban Bhaktapur, Nepal; urban Lima, Peru; and rural Nakaseke, Uganda, using a random age-and sex-stratified sample of the population 40 years or older.EXPOSURES Three screening tools, the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE; range, 0-6; high risk indicated by a score of 5 or more or score 2-5 with low PEF [<250 L/min for females and <350 L/min for males]), the COPD in LMICs Assessment questionnaire (COLA-6; range, 0-5; high risk indicated by a score of 4 or more), and the Lung Function Questionnaire (LFQ; range, 0-25; high risk indicated by a score of 18 or less) were assessed against a reference standard diagnosis of COPD using quality-assured postbronchodilator spirometry. CAPTURE and COLA-6 include a measure of PEF. MAIN OUTCOMES AND MEASURESThe primary outcome was discriminative accuracy of the tools in identifying COPD as measured by area under receiver operating characteristic curves (AUCs) with 95% CIs. Secondary outcomes included sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS Among 10 709 adults who consented to participate in the study (mean age, 56.3 years (SD, 11.7); 50% female), 35% had ever smoked, and 30% were currently exposed to biomass smoke. The unweighted prevalence of COPD at the 3 sites was 18.2% (642/3534 participants) in Nepal, 2.7% (97/3550) in Peru, and 7.4% (264/3580) in Uganda. Among 1000 COPD cases, 49.3% had clinically important disease (Global Initiative for Chronic Obstructive Lung Disease classification B-D), 16.4% had severe or very severe airflow obstruction (forced expiratory volume in 1 second <50% predicted), and 95.3% of cases were previously undiagnosed. The AUC for the screening instruments ranged from 0.717 (95% CI, 0.677-0.774) for LFQ in Peru to 0.791 (95% CI, 0.770-0.809) for COLA-6 in Nepal. The sensitivity ranged from 34.8% (95% CI, 25.3%-45.2%) for COLA-6 in Nepal to 64.2% (95% CI, 60.3%-67.9%) for CAPTURE in Nepal. The mean time to administer the instruments was 7.6 minutes (SD 1.11), and data completeness was 99.5%. CONCLUSIONS AND RELEVANCEThis study demonstrated that screening instruments for COPD were feasible to administer in 3 low-and middle-income settings. Further research is needed to assess instrument performance in other low-and middle-income settings and to determine whether implementation is associated with improved clinical outcomes.

Pneumonia is a leading killer of children younger than 5 years despite high vaccination coverage, improved nutrition, and widespread implementation of the Integrated Management of Childhood Illnesses algorithm. Assessing the effect of interventions on childhood pneumonia is challenging because the choice of case definition and surveillance approach can affect the identification of pneumonia substantially. In anticipation of an intervention trial aimed to reduce childhood pneumonia by lowering household air pollution, we created a working group to provide recommendations regarding study design and implementation. We suggest to, first, select a standard case definition that combines acute (≤14 days) respiratory symptoms and signs and general danger signs with ancillary tests (such as chest imaging and pulse oximetry) to improve pneumonia identification; second, to prioritise active hospital-based pneumonia surveillance over passive case finding or home-based surveillance to reduce the risk of non-differential misclassification of pneumonia and, as a result, a reduced effect size in a randomised trial; and, lastly, to consider longitudinal follow-up of children younger than 1 year, as this age group has the highest incidence of severe pneumonia.

Background In resource-limited settings, pneumonia diagnosis and management are based on thresholds for respiratory rate (RR) and oxyhaemoglobin saturation (SpO 2 ) recommended by WHO. However, as RR increases and SpO 2 decreases with elevation, these thresholds might not be applicable at all altitudes. We sought to determine upper thresholds for RR and lower thresholds for SpO 2 by age and altitude at four sites, with altitudes ranging from sea level to 4348 m. MethodsIn this cross-sectional study, we enrolled healthy children aged 0-23 months who lived within the study areas in India, Guatemala, Rwanda, and Peru. Participants were excluded if they had been born prematurely (<37 weeks gestation); had a congenital heart defect; had history in the past 2 weeks of overnight admission to a health facility, diagnosis of pneumonia, antibiotic use, or respiratory or gastrointestinal signs; history in the past 24 h of difficulty breathing, fast breathing, runny nose, or nasal congestion; and current runny nose, nasal congestion, fever, chest indrawing, or cyanosis. We measured RR either automatically with the Masimo Rad-97, manually, or both, and measured SpO 2 with the Rad-97. Trained staff measured RR in duplicate and SpO 2 in triplicate in children who had no respiratory symptoms or signs in the past 2 weeks. We estimated smooth percentiles for RR and SpO 2 that varied by age and site using generalised additive models for location, shape, and scale. We compared these data with WHO RR and SpO 2 thresholds for tachypnoea and hypoxaemia to determine agreement.

Background Low- and middle-income countries (LMICs) account for >90% of deaths and illness episodes related to COPD; however, this condition is commonly underdiagnosed in these settings. Case-finding instruments for COPD may improve diagnosis and identify individuals that need treatment, but few have been validated in resource-limited settings. Methods We conducted a population-based cross-sectional study in Uganda to assess the diagnostic accuracy of a respiratory symptom, exposure and functional questionnaire in combination with peak expiratory flow for COPD diagnosis using post-bronchodilator FEV 1 /FVC z-score below the 5th percentile as the gold standard. We included locally relevant exposure questions and statistical learning techniques to identify the most important risk factors for COPD. We used 80% of the data to develop the case-finding instrument and validated it in the remaining 20%. We evaluated for calibration and discrimination using standard approaches. The final score, COLA (COPD in LMICs Assessment), included seven questions, age and pre-bronchodilator peak expiratory flow. Results We analyzed data from 1,173 participants (average age 47 years, 46.9% male, 4.5% with COPD) with acceptable and reproducible spirometry. The seven questions yielded a cross-validated area-under-the-curve [AUC] of 0.68 (95% CI 0.61–0.75) with higher scores conferring greater odds of COPD. The inclusion of peak expiratory flow and age improved prediction in a validation sample (AUC=0.83, 95% CI 0.78–0.88) with a positive predictive value of 50% and a negative predictive value of 96%. The final instrument (COLA) included seven questions, age and pre-bronchodilator peak expiratory flow. Conclusion COLA predicted COPD in urban and rural settings in Uganda has high calibration and discrimination, and could serve as a simple, low-cost screening tool in resource-limited settings.