Human growth, biological maturation, motor performance and contextual factors in Madeira children

The central aims of this study were: (1) to construct age- and gender-specific percentiles for motor coordination (MC), (2) to analyze the change, stability, and prediction of MC, (3) to investigate the relationship between motor performance and body fatness, and (4) to evaluate the relationships between skeletal maturation and fundamental motor skills (FMS) and MC. The data collected was from the ‘Healthy Growth of Madeira Children Study’ and from the ‘Madeira Child Growth Study’. In these studies, MC, FMS, skeletal age, growth characteristics, motor performance, physical activity, socioeconomic status, and geographical area were assessed/measured. Generalized additive models for location, scale and shape, mixed between-within subjects ANOVA, multilevel models, and hierarchical regression (blocks) were some of the statistical procedures used in the analyses. Scores on walking backwards and moving sideways improved with age. It was also found that boys performed better than girls on moving sideways. Normal-weight children outperformed obese peers in almost all gross MC tests. Inter-age correlations were calculated to be between 0.15 and 0.60. Age was associated with a better performance in catching, scramble, speed run, standing long jump, balance, and tennis ball throwing. Body mass index was positively associated with scramble and speed run, and negatively related to the standing long jump. Physical activity was negatively associated with scramble. Semi-urban children displayed better catching skills relative to their urban peers. The standardized residual of skeletal age on chronological age (SAsr) and its interaction with stature and/or body mass accounted for the maximum of 7.0% of variance in FMS and MC over that attributed to body size per se. SAsr alone accounted for a maximum of 9.0% variance in FMS and MC over that attributed to body size per se and interactions between SAsr and body size. This study demonstrates the need to promote FMS, MC, motor performance, and physical activity in children.

Abiotic modulators of Podocnemis unifilis (Testudines: Podocnemididae) abundances in the Peruvian Amazon

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Associação de polimorfismos nos genes TLR2 e TLR4 com risco de câncer colorretal esporádico e influência na expressão gênica

Pós-graduação em Genética - IBILCE

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumare, State of Sao Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

TLR2 and TLR4 polymorphisms influence mRNA and protein expression in colorectal cancer

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Habitat use of migrating dwarf minke whales (Balaenoptera acutorostrata subspecies) in Tasmanian waters

The Great Barrier Reef hosts the only known reliable aggregation of dwarf minke whale (Balaenoptera acutorostrata subspecies) in Australian waters. While this short seasonal aggregation is quite predictable, the distribution and movements of the whales during the rest of their annual cycle are poorly understood. In particular, feeding and resting areas on their southward migration which are likely to be important have not been described. Using satellite telemetry data, I modelled the habitat use of seven whales during their southward migration through waters surrounding Tasmania. The whales were tagged with LIMPET satellite tags in the GBR in July 2013 (2 individuals) and 2014 (5 individuals). The study area around Tasmania was divided into 10km² cells and the time spent by each individual in each cell was calculated and averaged based on the number of animals using the cell. Two areas of high residency time were highlighted: south-western Bass Strait and Storm Bay (SE Tasmania). Remotely sensed ocean data were extracted for each cell and averaged temporally during the entire period of residency. Using Generalised Additive Models I explored the influence of key environmental characteristics. Nine predictors (bathymetry, distance from coast, distance from shore, gradient of sea surface temperature, sea surface height (absolute and variance), gradient of current speed, wind speed and chlorophyll-a concentration) were retained in the final model which explained 68% of the total variance. Regions of higher time-spent values were characterised by shallow waters, proximity to the coast (but not to the shelf break), high winds and sea surface height but low gradient of sea surface temperature. Given that the two high residency areas corresponded with regions where other marine predators also forage in Bass Strait and Storm Bay, I suggest the whales were probably feeding, rather than resting in these areas.

Survey estimation and marginal effects in Stata

Stata is a general purpose software package that has become popular among various disciplines such as epidemiology, economics, or social sciences. Users like Stata for its scientific approach, its robustness and reliability, and the ease with which its functionality can be extended by user written programs. In this talk I will first give a brief overview of the functionality of Stata and then discuss two specific features: survey estimation and predictive margins/marginal effects. Most surveys are based on complex samples that contain multiple sampling stages, are stratified or clustered, and feature unequal selection probabilities. Standard estimators can produce misleading results in such samples unless the peculiarities of the sampling plan are taken into account. Stata offers survey statistics for complex samples for a wide variety of estimators and supports several variance estimation procedures such as linearization, jackknife, and balanced repeated replication (see Kreuter and Valliant, 2007, Stata Journal 7: 1-21). In the talk I will illustrate these features using applied examples and I will also show how user written commands can be adapted to support complex samples. Complex can also be the models we fit to our data, making it difficult to interpret them, especially in case of nonlinear or non-additive models (Mood, 2010, European Sociological Review 26: 67-82). Stata provides a number of highly useful commands to make results of such models accessible by computing and displaying predictive margins and marginal effects. In my talk I will discuss these commands provide various examples demonstrating their use.

Effects of air pollution on asthma hospitalization rates in different age groups in metropolitan cities of Korea

Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

A STUDY ON THE EPIDEMIOLOGY OF POSITIVE PHYSICAL HEALTH (NHANES I)

HANES 1 detailed sample data were used to operationalize a definition of health in the absence of disease and to describe and compare the characteristics of the normal (healthy) group versus an abnormal (unhealthy) group.^ Parallel screening gave a 3.8 percent prevalence proportion of physical health, with a female:male ratio of 2:1 and younger ages in the healthy group. Statistically significant Mantel-Haenszel gender-age-adjusted odds ratios (MHOR) were estimated among abnormal non-migrants (1.53), skilled workers/unemployed (1.76), annual family incomes of less than $10,000 (1.56), having ever smoked (1.58), and started smoking before 18 years of age (1.58). Significant MHOR were also found for abnormals for health promoting measures: non-iodized salt use (1.94), needed dental care (1.91); and for fair to poor perceived health (4.28), perceiving health problems (2.52), and low energy level (1.68). Significant protective effects for much to moderate recreational exercise (MHOR 0.42) and very active to moderate non-recreational activity (MHOR 0.49) were also obtained. Covariance analysis additive models detected statistically significant higher mean values for abnormals than normals for serum magnesium, hemoglobin, hematocrit, urinary creatinine, and systolic and diastolic blood pressures, and lower values for abnormals than normals for serum iron. No difference was detected for serum cholesterol. Significant non-additive joint effects were found for body mass index.^ The results suggest positive physical health can be measured with cross-sectional survey data. Gender differentials, and associations between ecologic, socioeconomic, hazardous risk factors, health promoting activities and physical health are in general agreement with published findings on studies of morbidity. Longitudinal prospective studies are suggested to establish the direction of the associations and to enhance present knowledge of health and its promoting factors. ^

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Factores determinantes de la variabilidad espacial de anchoveta peruana (Engraulis ringens) en el Pacífico Sudoriental

Los modelos de nicho ecológico permiten estudiar el efecto del ambiente sobre la distribución de las especies, relacionando datos de su distribución con información ambiental. El objetivo del presente estudio fue estimar el nicho ecológico y describir la variabilidad en la distribución espacial de la anchoveta (Engraulis ringens) mediante el uso de modelos estadísticos de nicho ecológico. Se trabajó con dos enfoques de análisis: por stocks (norte, centro y sur) en el Pacífico Sudoriental (PSO) y por estadios de desarrollo (pre-reclutas, reclutas y adultos) en la costa peruana. El modelo de nicho ecológico utilizó modelos aditivos generalizados, estimaciones georeferenciadas de presencia y ausencia de anchoveta e información de cuatro variables ambientales (temperatura superficial del mar, salinidad superficial del mar, concentración de clorofila a superficial y la profundidad de la oxiclina) entre los a˜nos 1985 y 2008. Se encontró que no existen diferencias en los nichos ecológicos de los tres stocks de anchoveta siendo los modelos que utilizaron la información de la anchoveta en todo el PSO los que lograron modelar el nicho de manera correcta. Respecto al análisis por estadios, se evidenció que cada estadio de desarrollo tiene distintas tolerancias a las variables ambientales consideradas en este trabajo, siendo los nichos de estadios menos desarrollados los que estuvieron incluidos dentro de los estadios más desarrollados. Se recomienda realizar estudios separados para cada estadio de desarrollo, lo cual permita comprender mejor las relaciones ecológicas encontradas en los resultados del nicho ecológico. Además se recomienda realizar simulaciones con modelos de nicho que incluyan más variables ambientales, las cuales puedan mejorar los mapas de distribución espacial de la anchoveta para los dos enfoques de análisis.

Modelled spatial and seasonal distribution of Blue Whiting (Micromesistius poutassou) larvae in the North-East Atlantic (1951 to 2005)

Blue whiting (Micromesistius poutassou, http://www.marinespecies.org/aphia.php?p=taxdetails&id=126439) is a small mesopelagic planktivorous gadoid found throughout the North-East Atlantic. This data contains the results of a model-based analysis of larvae captured by the Continuous Plankton Recorder (CPR) during the period 1951-2005. The observations are analysed using Generalised Additive Models (GAMs) of the the spatial, seasonal and interannual variation in the occurrence of larvae. The best fitting model is chosen using the Aikaike Information Criteria (AIC). The probability of occurrence in the continous plankton recorder is then normalised and converted to a probability distribution function in space (UTM projection Zone 28) and season (day of year). The best fitting model splits the distribution into two separate spawning grounds north and south of a dividing line at 53 N. The probability distribution is therefore normalised in these two regions (ie the space-time integral over each of the two regions is 1). The modelled outputs are on a UTM Zone 28 grid: however, for convenience, the latitude ("lat") and longitude ("lon") of each of these grid points are also included as a variable in the NetCDF file. The assignment of each grid point to either the Northern or Southern component (defined here as north/south of 53 N), is also included as a further variable ("component"). Finally, the day of year ("doy") is stored as the number of days elapsed from and included January 1 (ie doy=1 on January 1) - the year is thereafter divided into 180 grid points.

Is the association between late-life morbidity and disability attenuated over time? : Exploring the dynamic equilibrium of morbidity hypothesis

Context: There is evidence suggesting that the prevalence of disability in late life has declined over time while the prevalence of disabling chronic diseases has increased. The dynamic equilibrium of morbidity hypothesis suggests that these seemingly contradictory trends are due to the attenuation of the morbidity-disability link over time. The aim of this study was to empirically test this assumption.Methods: Data were drawn from three repeated cross-sections of SWEOLD, a population-based survey among the Swedish men and women ages 77 and older. Logistic regression models were fitted to assess the trends in the prevalence of Activities of Daily Living (ADL) disability, Instrumental ADL (IADL) disability, and selected groups of chronic conditions. The changes in the associations between chronic conditions and disabilities were examined in both multiplicative and additive models.Results: Between 1992 and 2011, the odds of ADL disability significantly declined among women whereas the odds of IADL disability significantly declined among men. During the same period, the prevalence of most chronic morbidities including multimorbidity went up. Significant attenuations of the morbidity-disability associations were found for cardiovascular diseases, metabolic disorders, poor lung function, psychological distress, and multimorbidity.Conclusion: In agreement with the dynamic equilibrium hypothesis, this study concludes that the associations between chronic conditions and disability among the Swedish older adults have largely waned over time.

Ambient ozone pollution and daily mortality in three megacities in China

Thesis (Master's)--University of Washington, 2016-06

(Table 2) Lipid fluxes derived from sediment trap samples

Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods.