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Introduction: Pollution and climate have an impact on pediatric respiratory diseases; few studies have assessed this in the Autonomous City of Buenos Aires., Objective: To assess the impact of the interaction between air pollutants and climate on the Emergency Department visits for acute lower respiratory tract infection (ALRTI) in a children's hospital., Methods: Ecological, time-series study with generalized additive models that included total visits and visits for ALRTI to the Emergency Department between 2012 and 2016. A series with 7-day moving averages for ALRTI visits was founded as a bias control measure. Predictors were daily levels of air pollutants (carbon monoxide, nitrous dioxide, particulate matter < 10 μ) and meteorological variables (temperature, humidity). Pollutants were measured at three monitoring stations. Temporal variables (day of the week, warm/cold semester) were controlled., Results: There were 455 256 total visits; 17 298 accounted for visits for ALRTI. A correlation was established only between total visits and day of the week (Mondays and Saturdays, more visits; Thursdays, less visits). Less visits for ALRTI were recorded in the warm semester compared to the cold semester (relative risk = 0.23; 95 % confidence interval: 0.29-0.18; p < 0.001). One monitoring station did not show any correlation; the other two stations showed a weak correlation between carbon monoxide and particulate matter < 10 μ and visits for ALRTI., Conclusion: The season accurately accounts for the increased number of total visits and visits for ALRTI. Although there was a correlation between the level of certain pollutants and the number of visits, its impact was irrelevant., Competing Interests: The authors report no conflicts of interest in this work., (Sociedad Argentina de Pediatría.)

Background: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature., Objectives: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset., Methods: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques., Results: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1-3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly., Discussion: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.