Age at menarche in relation to prenatal rainy season exposure and altitude of residence: results from a nationally representative survey in a tropical country.

Intrauterine exposure to the rainy season in the tropics may be accompanied by high rates of infection and nutritional deficiencies. It is unknown whether this exposure is related to the extrauterine timing of development. Our aim was to evaluate the relations of prenatal exposure to the rainy season and altitude of residence with age at menarche. The study included 15,370 girls 10 to <18 years old who participated in Colombia's 2010 National Nutrition Survey. Primary exposures included the number of days exposed to the rainy season during the 40 weeks preceding birth, and altitude of residence at the time of the survey. We estimated median menarcheal ages and hazard ratios with 95% confidence interval (CI) according to exposure categories using Kaplan-Meier cumulative probabilities and Cox proportional hazards models, respectively. All tests incorporated the complex survey design. Girls in the highest quintile of gestation days exposed to the rainy season had an earlier age at menarche compared with those in the lowest (adjusted hazard ratios (HR)=1.08; 95% CI 1.00-1.18, P-trend=0.03). Girls living at altitudes ⩾2000 m had a later age at menarche compared with those living <1000 m (adjusted HR=0.88; 95% CI 0.82-0.94, P-trend <0.001). The inverse association between gestation days during the rainy season and menarche was most apparent among girls living at altitudes ⩾2000 m (P, interaction=0.04). Gestation days exposed to the rainy season and altitude of residence were associated with the timing of sexual maturation among Colombian girls independent of socioeconomic status and ethnicity.

The epidemiology of falling-through-the-ice in Alaska, 1990-2010.

BACKGROUND: Climate change has contributed to increasing temperatures, earlier snowmelts and thinning ice packs in the Arctic, where crossing frozen bodies of water is essential for transportation and subsistence living. In some Arctic communities, anecdotal reports indicate a growing belief that falling-through-the-ice (FTI) are increasing. The objective of this study was to describe the morbidity and mortality associated with unintentional FTIs in Alaska. METHODS: We searched newspaper reports to identify FTI events from 1990 to 2010. We also used data from a trauma registry, occupational health and law enforcement registries and vital statistics to supplement the newspaper reports. Morbidity and mortality rates were calculated for Alaska Native (AN) people and all Alaskans. RESULTS: During the 21-year period, we identified 307 events, affecting at least 449 people. Events ranged from no morbidity to fatalities of five people. More than half of the events involved transportation by snow machine. Mortality rates were markedly higher for AN people than that for all Alaskans. CONCLUSIONS: We provide a numeric estimate of the importance of FTI events in Alaska. FTIs may represent an adverse health outcome related to climate changes in the Arctic, and may be particularly critical for vulnerable populations such as AN people.

Estimating the potential impacts of intervention from observational data: methods for estimating causal attributable risk in a cross-sectional analysis of depressive symptoms in Latin America.

BACKGROUND: The field of epidemiology struggles both with enhancing causal inference in observational studies and providing useful information for policy makers and public health workers focusing on interventions. Population intervention models, analogous to population attributable fractions, estimate the causal impact of interventions in a population, and are one option for understanding the relative importance of various risk factors. With population intervention parameters, risk factors are effectively standardised, allowing one to compare their values directly and determine which potential intervention may have the greatest impact on the outcome. METHODS: The difference between total effects and population intervention parameters was examined using naïve, G-computation and inverse probability of treatment weighting approaches. The differences between these parameters and the intuitions they provide were explored using data from a 2003 cross-sectional study in rural Mexico. RESULTS: The assumptions, specific analytic steps, limitations and interpretations of the total effects and population intervention parameters are discussed, and code is provided in Stata. CONCLUSION: Population intervention parameters are a valuable and straightforward approach in epidemiological studies for making causal inference from the data while also supplying information that is relevant for researchers, public health practitioners and policy makers.

Using directed acyclic graphs to guide analyses of neighbourhood health effects: an introduction.

BACKGROUND: Directed acyclic graphs, or DAGs, are a useful graphical tool in epidemiologic research that can help identify appropriate analytical strategies in addition to potential unintended consequences of commonly used methods such as conditioning on mediators. The use of DAGs can be particularly informative in the study of the causal effects of social factors on health. METHODS: The authors consider four specific scenarios in which DAGs may be useful to neighbourhood health effects researchers: (1) identifying variables that need to be adjusted for in estimating neighbourhood health effects, (2) identifying the unintended consequences of estimating "direct" effects by conditioning on a mediator, (3) using DAGs to understand possible sources and consequences of selection bias in neighbourhood health effects research, and (4) using DAGs to identify the consequences of adjustment for variables affected by prior exposure. CONCLUSIONS: The authors present simplified sample DAGs for each scenario and discuss the insights that can be gleaned from the DAGs in each case and the implications these have for analytical approaches.