Approximately three billion individuals are exposed to household air pollution (HAP) from the burning of biomass fuels worldwide. Household air pollution is responsible for 2.9 million annual deaths and causes significant health, economic and social consequences, particularly in low- and middle-income countries. Although there is biological plausibility to draw an association between HAP exposure and respiratory diseases, existing evidence is either lacking or conflicting. We abstracted systematic reviews and meta-analyses for summaries available for common respiratory diseases in any age group and performed a literature search to complement these reviews with newly published studies. Based on the literature summarized in this review, HAP exposure has been associated with acute respiratory infections, tuberculosis, asthma, chronic obstructive pulmonary disease, pneumoconiosis, head and neck cancers, and lung cancer. No study, however, has established a causal link between HAP exposure and respiratory disease. Furthermore, few studies have controlled for tobacco smoke exposure and outdoor air pollution. More studies with consistent diagnostic criteria and exposure monitoring are needed to accurately document the association between household air pollution exposure and respiratory disease. Better environmental exposure monitoring is critical to better separate the contributions of household air pollution from that of other exposures, including ambient air pollution and tobacco smoking. Clinicians should be aware that patients with current or past HAP exposure are at increased risk for respiratory diseases or malignancies and may want to consider earlier screening in this population.

Rationale: Management of pulmonary nodules depends critically on the probability of malignancy. Models to estimate probability have been developed and validated, but most clinicians rely on judgment.Objectives: The aim of this study was to compare the accuracy of clinical judgment with that of two prediction models.Methods: Physician participants reviewed up to five clinical vignettes, selected at random from a larger pool of 35 vignettes, all based on actual patients with lung nodules of known final diagnosis. Vignettes included clinical information and a representative slice from computed tomography. Clinicians estimated the probability of malignancy for each vignette. To examine agreement with models, we calculated intraclass correlation coefficients (ICC) and kappa statistics. To examine accuracy, we compared areas under the receiver operator characteristic curve (AUC).Measurements and Main Results: Thirty-six participants completed 179 vignettes, 47% of which described patients with malignant nodules...

Interventions implementing clean fuels to mitigate household air pollution in low- and middle-income countries have focused on environmental and health outcomes, but few have evaluated time savings. We performed a systematic review, searching for studies of clean fuel interventions that measured time use. A total of 868 manuscripts were identified that met the search criteria, but only 2 met the inclusion criteria. Both were cross-sectional and were conducted in rural India. The first surveyed the female head of household (141 using biogas and 58 using biomass) and reported 1.2 h saved per day collecting fuel and 0.7 h saved cooking, resulting in a combined 28.9 days saved over an entire year. The second surveyed the head of household (37 using biogas and 68 using biomass, 13% female) and reported 1.5 h saved per day collecting fuel, or 22.8 days saved over a year. Based on these time savings, we estimated that clean fuel use could result in a 3.8% or 4.7% increase in daily income, respectively, not including time or costs for fuel procurement. Clean fuel interventions could save users time and money. Few studies have evaluated this potential benefit, suggesting that prospective studies or randomized controlled trials are needed to adequately measure gains.

In resource-limited settings, pneumonia diagnosis and management are based on thresholds for respiratory rate (RR) and oxyhaemoglobin saturation (SpO2) recommended by WHO. However, as RR increases and SpO2 decreases with elevation, these thresholds might not be applicable at all altitudes. We sought to determine upper thresholds for RR and lower thresholds for SpO2 by age and altitude at four sites, with altitudes ranging from sea level to 4348 m. In 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 SpO2 with the Rad-97. Trained staff measured RR in duplicate and SpO2 in triplicate in children who had no respiratory symptoms or signs in the past 2 weeks. We estimated smooth percentiles for RR and SpO2 that varied by age and site using generalised additive models for location, shape, and scale. We compared these data with WHO RR and SpO2 thresholds for tachypnoea and hypoxaemia to determine agreement. Between Nov 24, 2017, and Oct 10, 2018, we screened 2027 children for eligibility. 335 were ineligible, leaving 1692 eligible participants. 30 children were excluded because of missing values and 92 were excluded because of measurement or data entry errors, leaving 1570 children in the final analysis. 404 participants were from India (altitude 1-919 m), 389 were from Guatemala (1036-2017 m), 341 from Rwanda (1449-1644 m), and 436 from Peru (3827-4348 m). Mean age was 7·2 months (SD 7·2) and 796 (50·7%) of 1570 participants were female. Although average age was mostly similar between settings, the average participant age in Rwanda was noticeably younger, at 5·5 months (5·9). In the 1570 children included in the analysis, mean RR was 31·9 breaths per min (SD 7·1) in India, 41·5 breaths per min in Guatemala (8·4), 44·0 breaths per min in Rwanda (10·8), and 48·0 breaths per min in Peru (9·4). Mean SpO2 was 98·3% in India (SD 1·5), 97·3% in Guatemala (2·4), 96·2% in Rwanda (2·6), and 89·7% in Peru (3·5). Compared to India, mean RR was 9·6 breaths per min higher in Guatemala, 12·1 breaths per min higher in Rwanda, and 16·1 breaths per min higher in Peru (likelihood ratio test p<0·0001). Smooth percentiles for RR and SpO2 varied by site and age. When we compared age-specific and site-specific 95th percentiles for RR and 5th percentiles for SpO2 against the WHO cutoffs, we found that the proportion of false positives for tachypnoea increased with altitude: 0% in India (95% CI 0-0), 7·3% in Guatemala (4·1-10·4), 16·8% in Rwanda (12·9-21·1), and 28·9% in Peru (23·7-33·0). We also found a high proportion of false positives for hypoxaemia in Peru (11·6%, 95% CI 7·0-14·7). WHO cutoffs for fast breathing and hypoxaemia overlap with RR and SpO2 values that are normal for children in different altitudes. Use of WHO definitions for fast breathing could result in misclassification of pneumonia in many children who live at moderate to high altitudes and show acute respiratory signs. The 5th percentile for SpO2 was in reasonable agreement with the WHO definition of hypoxaemia in all regions except for Peru (the highest altitude site). Misclassifications could result in inappropriate management of paediatric respiratory illness and misdirection of potentially scarce resources such as antibiotics and supplemental oxygen. Future studies at various altitudes are needed to validate our findings and recommend a revision to current guidelines. Substantiating research in sick children is still needed. US National Institutes of Health, Bill & Melinda Gates Foundation.