Burning biomass fuels indoors for cooking is associated with high concentrations of particulate matter (PM) and carbon monoxide (CO). More efficient biomass-burning stoves and chimneys for ventilation have been proposed as solutions to reduce indoor pollution. We sought to quantify indoor PM and CO exposures in urban and rural households and determine factors associated with higher exposures. A secondary objective was to identify chronic vs. acute changes in cardiopulmonary biomarkers associated with exposure to biomass smoke.

Background: Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. Methods: We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Results: Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Conclusions: Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Background: Socioeconomic status is associated with cesarean section (CS). Maternal height, however, may be another related factor to CS. In Guatemala, a quarter of women between 15 and 49 years of age are shorter than 145 cm. Therefore, this study aims to examine the association of maternal height with cesarean section in Guatemala. Methods: We carried out a secondary analysis study using data from the 2014–15 Guatemalan national maternal and child health survey—9542 mothers aged 15–49 and 12,426 live births were analyzed. We obtained the prevalence ratio of the association between maternal height and CS based on three Poisson regression models. One model included all live births, another the first live birth, and a third model the last live birth. For each model, we accounted for covariates and sampling design. Results: The national prevalence of CS was 26.3% (95%CI: 25.0, 27.7). The adjusted prevalence ratio of CS, including all live births, was 1.63 (95%CI: 1.37, 1.94) more likely in mothers shorter than 145 cm compared with those equal or greater than 170 cm. This figure was 1.45 (95%CI: 1.19, 1.76) in the model with the first live birth. In the model with the last birth, maternal height was not associated with CS after accounting for previous CS as one of the covariates. Conclusions: Prevalence of CS in this setting was high and above international recommendations. Further, very short mothers were more likely to experience CS compared to taller mothers after accounting for covariates, except when a previous CS was present. Maternal height should be included in clinical assessments during prenatal care.

Widespread availability of antibiotics without prescription potentially facilitates overuse and contributes to selection pressure for antimicrobial resistant bacteria. Prior to this study, anecdotal observations in Guatemala identified corner stores as primary antibiotic dispensaries, where people purchase antibiotics without prescriptions. We carried out a cross sectional study to document the number and types of antibiotics available in corner stores, in four study areas in Guatemala. A total of 443 corner stores were surveyed, of which 295 (67%) sold antibiotics. The most commonly available antibiotics were amoxicillin, found in 246/295 (83%) stores, and tetracycline, found in 195/295 (66%) stores. Over the counter sales result from laissez-faire enforcement of antibiotic dispensing regulations in Guatemala combined with patient demand. This study serves as a baseline to document changes in the availability of antibiotics in informal establishments in light of new pharmacy regulations for antibiotic dispensing, which were adopted after this study was completed.

Household air pollution (HAP) due to solid fuel use during pregnancy is associated with adverse birth outcomes. The real-life effectiveness of clean cooking interventions has been disappointing overall yet variable, but the sociodemographic determinants are not well described. We measured personal 24-h PM_2.5 (particulate matter <2.5 µm in aerodynamic diameter) thrice in pregnant women (n = 218) gravimetrically with Teflon filter, impactor, and personal pump setups. To estimate the effectiveness of owning chimney and liquefied petroleum gas (LPG) stoves (i.e., proportion of PM_2.5 exposure that would be prevented) and to predict subject-specific typical exposures, we used linear mixed-effects models with log (PM_2.5) as dependent variable and random intercept for subject. Median (IQR) personal PM_2.5 in µg/m³ was 148 (90–249) for open fire, 78 (51–125) for chimney stove, and 55 (34–79) for LPG stoves. Adjusted effectiveness of LPG stoves was greater in women with ≥6 years of education (49% (95% CI: 34, 60)) versus <6 years (26% (95% CI: 5, 42)). In contrast, chimney stove adjusted effectiveness was greater in women with <6 years of education (50% (95% CI: 38, 60)), rural residence (46% (95% CI: 34, 55)) and lowest SES (socio-economic status) quartile (59% (95% CI: 45, 70)) than ≥6 years education (16% (95% CI: 22, 43)), urban (23% (95% CI: −164, 42)) and highest SES quartile (−44% (95% CI: −183, 27)), respectively. A minority of LPG stove owners (12%) and no chimney owner had typical exposure below World Health Organization Air Quality guidelines (35 μg/m³). Although having a cleaner stove alone typically does not lower exposure enough to protect health, understanding sociodemographic determinants of effectiveness may lead to better targeting, implementation, and adoption of interventions.

Objectives: The spread of extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE) and carbapenemresistant Enterobacterales (CRE) has resulted in increased morbidity, mortality, and health care costs worldwide. To identify the factors associated with ESCrE and CRE colonization within hospitals, we enrolled hospitalized patients at a regional hospital located in Guatemala. Methods: Stool samples were collected from randomly selected patients using a cross-sectional study design (March-September, 2021), and samples were tested for the presence of ESCrE and CRE. Hospital-based and household variables were examined for associations with ESCrE and CRE colonization using lasso regression models, clustered by ward (n = 21). Results: A total of 641 patients were enrolled, of whom complete data sets were available for 593. Colonization with ESCrE (72.3%, n = 429/593) was negatively associated with carbapenem administration (odds ratio [OR] 0.21, 95% confidence interval [CI] 0.11-0.42) and positively associated with ceftriaxone administration (OR 1.61, 95% CI 1.02-2.53), as was reported hospital admission within 30 days of the current hospitalization (OR 2.84, 95% CI 1.19-6.80). Colonization with CRE (34.6%, n = 205 of 593) was associated with carbapenem administration (OR 2.62, 95% CI 1.39-4.97), reported previous hospital admission within 30 days of current hospitalization (OR 2.58, 95% CI 1.17-5.72), hospitalization in wards with more patients (OR 1.05, 95% CI 1.02-1.08), hospitalization for >= 4 days (OR 3.07, 95% CI 1.72-5.46), and intubation (OR 2.51, 95% CI 1.13-5.59). No household-based variables were associated with ESCrE or CRE colonization in hospitalized patients. Conclusion: The hospital-based risk factors identified in this study are similar to what has been reported for risk of health care-associated infections, consistent with colonization being driven by hospital settings rather than community factors. This also suggests that colonization with ESCrE and CRE could be a useful metric to evaluate the efficacy of infection and prevention control programs in clinics and hospitals.