Parental stress increases body mass index trajectory in pre-adolescents.

What is already known about this subjectRates of childhood obesity have increased since the mid-1970s. Research into behavioural determinants has focused on physical inactivity and unhealthy diets. Cross-sectional studies indicate an association between psychological stress experienced by parents and obesity in pre-adolescents.What this study addsWe provide evidence of a prospective association between parental psychological stress and increased weight gain in pre-adolescents. Family-level support for those experiencing chronic stress might help promote healthy diet and exercise behaviours in children.ObjectiveWe examined the impact of parental psychological stress on body mass index (BMI) in pre-adolescent children over 4 years of follow-up.MethodsWe included 4078 children aged 5-10 years (90% were between 5.5 and 7.5 years) at study entry (2002-2003) in the Children's Health Study, a prospective cohort study in southern California. A multi-level linear model simultaneously examined the effect of parental stress at study entry on the attained BMI at age 10 and the slope of change across annual measures of BMI during follow-up, controlled for the child's age and sex. BMI was calculated based on objective measurements of height and weight by trained technicians following a standardized procedure.ResultsA two standard deviation increase in parental stress at study entry was associated with an increase in predicted BMI attained by age 10 of 0.287 kg m(-2) (95% confidence interval 0.016-0.558; a 2% increase at this age for a participant of average attained BMI). The same increase in parental stress was also associated with an increased trajectory of weight gain over follow-up, with the slope of change in BMI increased by 0.054 kg m(-2) (95% confidence interval 0.007-0.100; a 7% increase in the slope of change for a participant of average BMI trajectory).ConclusionsWe prospectively demonstrated a small effect of parental stress on BMI at age 10 and weight gain earlier in life than reported previously. Interventions to address the burden of childhood obesity should address the role of parental stress in children

Banning Commercial Foresting: What are the Costs?

The Philippines' forest cover has suffered from massive denudation through the years due to uncontrolled and indiscriminate commercial logging. Because of this, calls for a total logging ban had been raised in various fora, including in the legislature where bills that consider the possibility of a ban are being studied. However, the possible economic costs of such ban as espoused in some studies has delayed the passage of these bills. This Policy Notes provides some economic costing based on computations that may help in firming up decisions regarding the proposed ban.forestry sector, environmental issues, environmental management

Sedimentology and microfacies of a mud-rich slope succession: in the Carboniferous Bowland Basin, NW England (UK)

A paucity of studies on mud-rich basin slope successions has resulted in a significant gap in our sedimentological understanding in these settings. Here, macro- and micro-scale analysis of mudstone composition, texture and organic matter was undertaken on a continuous core through a mud-dominated slope succession from the Marl Hill area in the Carboniferous Bowland Basin. Six lithofacies, all dominated by turbidites and debrites, combine into three basin slope facies associations: sediment-starved slope, slope dominated by low-density turbidites and slope dominated by debrites. Variation in slope sedimentation was a function of relative sea-level change, with the sediment-starved slope occurring during maximum flooding of the contemporaneous shelf, and the transition towards a slope dominated by turbidites and then debrites occurring during normal or forced shoreline progradation towards the shelf margin. The sediment-starved slope succession is dominated by Type II kerogen, whereas the slope dominated by low-density turbidites is dominated by Type III kerogen. This study suggests that mud-dominated lower slope settings are largely active depositional sites, with consistent evidence for sediment traction. Additionally, the composition and texture of basin slope mudstones, as well as organic content, vary predictably as a function of shelf processes linked to relative sea-level change

Exposure to Traffic-related Air Pollution During Pregnancy and Term Low Birth Weight: Estimation of Causal Associations in a Semiparametric Model

Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000-2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants

Air Pollution Exposure Assessment for Epidemiologic Studies of Pregnant Women and Children: Lessons Learned from the Centers for Children’s Environmental Health and Disease Prevention Research

The National Children’s Study is considering a wide spectrum of airborne pollutants that are hypothesized to potentially influence pregnancy outcomes, neurodevelopment, asthma, atopy, immune development, obesity, and pubertal development. In this article we summarize six applicable exposure assessment lessons learned from the Centers for Children’s Environmental Health and Disease Prevention Research that may enhance the National Children’s Study: a) Selecting individual study subjects with a wide range of pollution exposure profiles maximizes spatial-scale exposure contrasts for key pollutants of study interest. b) In studies with large sample sizes, long duration, and diverse outcomes and exposures, exposure assessment efforts should rely on modeling to provide estimates for the entire cohort, supported by subject-derived questionnaire data. c) Assessment of some exposures of interest requires individual measurements of exposures using snapshots of personal and microenvironmental exposures over short periods and/or in selected microenvironments. d) Understanding issues of spatial–temporal correlations of air pollutants, the surrogacy of specific pollutants for components of the complex mixture, and the exposure misclassification inherent in exposure estimates is critical in analysis and interpretation. e) “Usual” temporal, spatial, and physical patterns of activity can be used as modifiers of the exposure/outcome relationships. f) Biomarkers of exposure are useful for evaluation of specific exposures that have multiple routes of exposure. If these lessons are applied, the National Children’s Study offers a unique opportunity to assess the adverse effects of air pollution on interrelated health outcomes during the critical early life period

Bayesian hierarchical modeling and analysis for physical activity trajectories using actigraph data

Rapid developments in streaming data technologies are continuing to generate increased interest in monitoring human activity. Wearable devices, such as wrist-worn sensors that monitor gross motor activity (actigraphy), have become prevalent. An actigraph unit continually records the activity level of an individual, producing a very large amount of data at a high-resolution that can be immediately downloaded and analyzed. While this kind of \textit{big data} includes both spatial and temporal information, the variation in such data seems to be more appropriately modeled by considering stochastic evolution through time while accounting for spatial information separately. We propose a comprehensive Bayesian hierarchical modeling and inferential framework for actigraphy data reckoning with the massive sizes of such databases while attempting to offer full inference. Building upon recent developments in this field, we construct Nearest Neighbour Gaussian Processes (NNGPs) for actigraphy data to compute at large temporal scales. More specifically, we construct a temporal NNGP and we focus on the optimized implementation of the collapsed algorithm in this specific context. This approach permits improved model scaling while also offering full inference. We test and validate our methods on simulated data and subsequently apply and verify their predictive ability on an original dataset concerning a health study conducted by the Fielding School of Public Health of the University of California, Los Angeles

Confounding and exposure measurement error in air pollution epidemiology

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains

Long-term exposure to outdoor air pollution and the incidence of chronic obstructive pulmonary disease in a national English cohort.

OBJECTIVES: The role of outdoor air pollution in the incidence of chronic obstructive pulmonary disease (COPD) remains unclear. We investigated this question using a large, nationally representative cohort based on primary care records linked to hospital admissions. METHODS: A cohort of 812 063 patients aged 40-89 years registered with 205 English general practices in 2002 without a COPD diagnosis was followed from 2003 to 2007. First COPD diagnoses recorded either by a general practitioner (GP) or on admission to hospital were identified. Annual average concentrations in 2002 for particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5), nitrogen dioxide (NO2), ozone and sulfur dioxide (SO2) at 1 km(2) resolution were estimated from emission-based dispersion models. Hazard ratios (HRs) per interquartile range change were estimated from Cox models adjusting for age, sex, smoking, body mass index and area-level deprivation. RESULTS: 16 034 participants (1.92%) received a COPD diagnosis from their GP and 2910 participants (0.35%) were admitted to hospital for COPD. After adjustment, HRs for GP recorded COPD and PM10, PM2.5 and NO2 were close to unity, positive for SO2 (HR=1.07 (95% CI 1.03 to 1.11) per 2.2 µg/m(3)) and negative for ozone (HR=0.94 (0.89 to 1.00) per 3 µg/m(3)). For admissions HRs for PM2.5 and NO2 remained positive (HRs=1.05 (0.98 to 1.13) and 1.06 (0.98 to 1.15) per 1.9 µg/m(3) and 10.7 µg/m(3), respectively). CONCLUSIONS: This large population-based cohort study found limited, inconclusive evidence for associations between air pollution and COPD incidence. Further work, utilising improved estimates of air pollution over time and enhanced socioeconomic indicators, is required to clarify the association between air pollution and COPD incidence

The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.Methods: A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes ( birth weight, small for gestational age and preterm births), in a two-level hierarchical model.Results: We found effects of both individual ( education, race, prenatal care index) and area-based ( median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.Conclusion: Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.This work is supported by the Harvard Environmental Protection Agency (EPA) Center, Grants R827353 and R-832416, and National Institute for Environmental Health Science (NIEHS) ES-0002

Green spaces and cognitive development in primary schoolchildren

© 2015, National Academy of Sciences. All rights reserved. Exposure to green space has been associated with better physical and mental health. Although this exposure could also influence cognitive development in children, available epidemiological evidence on such an impact is scarce. This study aimed to assess the association between exposure to green space and measures of cognitive development in primary schoolchildren. This study was based on 2,593 schoolchildren in the second to fourth grades (7-10 y) of 36 primary schools in Barcelona, Spain (2012-2013). Cognitive development was assessed as 12-mo change in developmental trajectory of working memory, superior working memory, and inattentiveness by using four repeated (every 3 mo) computerized cognitive tests for each outcome. We assessed exposure to green space by characterizing outdoor surrounding greenness at home and school and during commuting by using high-resolution (5 m x5 m) satellite data on greenness (normalized difference vegetation index). Multilevel modeling was used to estimate the associations between green spaces and cognitive development. We observed an enhanced 12-mo progress in working memory and superior working memory and a greater 12-mo reduction in inattentiveness associated with greenness within and surrounding school boundaries and with total surrounding greenness index (including greenness surrounding home, commuting route, and school). Adding a traffic-related air pollutant (elemental carbon) to models explained 20-65% of our estimated associations between school greenness and 12-mo cognitive development. Our study showed a beneficial association between exposure to green space and cognitive development among schoolchildren that was partly mediated by reduction in exposure to air pollution