Associations of parental reproductive age and elevated blood pressure in offspring: An observational study

BackgroundIncreased parental reproductive age has been a social trend around the world, and elevated blood pressure in children leads to an approximately two-fold increased risk of hypertension in adulthood. Aim of this study is to assess the associations of parental reproductive age with the risk of elevated blood pressure in offspring, and to explore the influence of offspring lifestyle on the associations.MethodsData was obtained from a national school program conducted in 7 Chinese provinces, and the final sample was 39,190 students aged 7–18 years. Anthropometric measurements and questionnaires were designed to collect data of children blood pressure and information respectively.ResultsIn this study, 26.7% of children were defined as elevated blood pressure. A U-shaped pattern was observed in the relationship between maternal age and risk of elevated blood pressure, while risk of elevated blood pressure decreased continuously with paternal age increased. After adjustment, offspring of paternal age ≤27 & maternal age ≤26 years and those of paternal age >30 & maternal age >32 years were related to great risk of elevated blood pressure (OR = 1.18, 95% CI: 1.08–1.29, P < 0.001; OR = 1.18, 95% CI: 1.01–1.38, P < 0.05). When stratified by lifestyle status, significant associations between maternal/paternal age and risk of elevated blood pressure were only observed in those with worse lifestyle behaviors, but not in offspring with healthier lifestyle.ConclusionOur findings demonstrate that risk of elevated blood pressure in children is independently related to parental reproductive age, and children maintaining a healthy lifestyle may mitigate the adverse effect

Assimilation of surface weather observations in complex terrain

Present computing power allows fine-resolution numerical weather prediction models to resolve meso-gamma flows within individual valleys. Such resolution is critical for mountainous British Columbia, because the valleys contain most of the population centers, industries, and transportation routes. Accurate high-resolution forecasts depend on accurate initial fields from which to start. To this end, dense local surface weather observations should be utilized to supplement the existing coarse-resolution Eta model analysis, while keeping computational costs of data assimilation reasonable for local mesoscale modeling. This dissertation develops a technique that allows the creation of a new anisotropic background-error correlation model for complex terrain, which horizontally spreads surface weather observations along circuitous valleys. The technique, called the mother-daughter approach, is based on first-order boundary-layer characteristics in mountainous terrain. The approach is further refined to account for land-sea anisotropy, and to treat mountaintop observations differently from valley observations. The resulting improved analysis from combining the detailed surface analysis with pseudo upper-air data from the Eta model analysis is used to initialize a high-resolution forecast model. The mother-daughter approaches are tested and compared with two existing methods, using virtual and real observations over different domains in mountainous British Columbia. It is found that the mother-daughter approaches outperform the other methods. The coastline refinement adds value to the original mother-daughter approach in maintaining thermal contrast across coastlines. Numerical experiments are performed to assess the impacts of assimilating surface observations in complex terrain on subsequent forecasts of near-surface parameters. Better skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the whole boundary layer instead of at only one model level. Experimental results show improvement on subsequent near-surface forecasts of the variables (e.g., temperature and humidity) that are directly assimilated into the model. However, the assimilation forecast run tends to worsen the forecasts of near-surface winds, which were not assimilated. These findings are confirmed by operational runs, and only minor differences are found. In summary, a method is devised to bring local surface weather observations in complex terrain into a high-resolution forecast model. Suggestions are made to also assimilate surface-wind data.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofGraduat

Mesoscale Analysis Method for Surface Potential Temperature in Mountainous and Coastal Terrain

A technique is developed to anisotropically spread surface observations in steep valleys. The goal is to create an improved objective analysis for the lowest, terrain-following numerical weather prediction (NWP) model level in mountainous terrain. The method is a mother–daughter (MD) approach, where the amount of information transferred from one grid point (the mother) to all neighboring grid points (the daughters) depends on elevation differences. The daughters become mothers and further share information with their neighboring grid points. This iterative method allows information to follow valleys around ridges, while reducing spread over the ridge top. The method is further refined to account for land–sea anisotropy. This approach is tested in the objective analyses of surface potential temperatures over the steep mountainous and coastal terrain of southwestern British Columbia, Canada. Analysis results are compared with other existing schemes using the Advanced Regional Prediction System Data Assimilation System (ADAS). It is found that the MD approach outperforms the other schemes over mountainous and coastal terrain. Copyright 2005 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected], Faculty ofEarth and Ocean Sciences, Department ofReviewedFacult

Assimilating Surface Weather Observations from Complex Terrain into a High-Resolution Numerical Weather Prediction Model.

An anisotropic surface analysis method based on the mother–daughter (MD) approach has been developed to spread valley station observations to grid points in circuitous steep valleys. In this paper, the MD approach is further refined to allow spreading the mountain-top observations to grid points near neighboring high ridges across valleys. Starting with a 3D first guess from a high-resolution mesoscale model forecast, surface weather observations are assimilated into the boundary layer, and pseudo-upper-air data (interpolated from the coarser-resolution analyses from major operational centers) are assimilated into the free atmosphere. Incremental analysis updating is then used to incorporate the final analysis increments (the difference between the final analysis and the first guess) into a high-resolution numerical weather prediction model. The MD approaches (including one with shoreline refinement) are compared with other objective analysis methods using case examples and daily mesoscale real-time forecast runs during November and December 2004. This study further confirms that the MD approaches outperform the other methods, and that the shoreline refinement achieves better analysis quality than the basic MD approach. The improvement of mountain-top refinement over the basic MD approach increases with the percentage of mountaintop stations, which is usually low. Higher skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the boundary layer instead of at only the bottom model level. The results show improved near-surface forecasts of temperature and humidity that are directly assimilated into the model, but poorer forecasts of near-surface winds and precipitation, which are not assimilated into the model. Copyright 2007 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected], Faculty ofEarth and Ocean Sciences, Department ofReviewedFacult

Ozone ensemble forecasts: 1. A new ensemble design

A new Ozone Ensemble Forecast System (OEFS) is tested as a technique to improve the accuracy of real-time photochemical air quality modeling. The performance of 12 different forecasts along with their ensemble mean is tested against the observations during 11–15 August 2004, over five monitoring stations in the Lower Fraser Valley, British Columbia, Canada, a population center in a complex coastal mountain setting. The 12 ensemble members are obtained by driving the U.S. Environmental Protection Agency (EPA) Models-3/Community Multiscale Air Quality Model (CMAQ) with two mesoscale meteorological models, each run at two resolutions (12- and 4-km): the Mesoscale Compressible Community (MC2) model and the Penn State/NCAR mesoscale (MM5) model. Moreover, CMAQ is run for three emission scenarios: a control run, a run with 50% more NOx emissions, and a run with 50% fewer. For the locations and days used to test this new OEFS, the ensemble mean is the best forecast if ranked using correlation, gross error, and root mean square error and has average performance when evaluated with the unpaired peak prediction accuracy. Ensemble averaging removes part of the unpredictable components of the physical and chemical processes involved in the ozone fate, resulting in a more skilful forecast when compared to any deterministic ensemble member. There is not one of the 12 individual forecasts that clearly outperforms the others on the basis of the four statistical parameters considered here. A lagged-averaged OEFS is also tested as follows. The 12-member OEFS is expanded to an 18-member OEFS by adding the second day from the six 12-km “yesterday” forecasts to the “today” ensemble forecast. The 18-member ensemble does not improve the ensemble mean forecast skill. Neither correlation nor a relationship between ensemble spread and forecast error is evident. An edited version of this paper was published by AGU. Copyright 2006 American Geophysical Union.Science, Faculty ofEarth and Ocean Sciences, Department ofReviewedFacult

Ozone ensemble forecasts: 2. A Kalman filter predictor bias correction

The Kalman filter (KF) is a recursive algorithm to estimate a signal from noisy measurements. In this study it is tested in predictor mode, to postprocess ozone forecasts to remove systematic errors. The recent past forecasts and observations are used by the KF to estimate the future bias. This bias correction is calculated separately for, and applied to, 12 different air quality (AQ) forecasts for the period 11–15 August 2004, over five monitoring stations in the Lower Fraser Valley, British Columbia, Canada, a population center in a complex coastal mountain setting. The 12 AQ forecasts are obtained by driving an AQ Model (CMAQ) with two mesoscale meteorological models (each run at two resolutions) and for three emission scenarios (Delle Monache et al., 2006). From the 12 KF AQ forecasts an ensemble mean is calculated (EK). This ensemble mean is also KF bias corrected, resulting in a high-quality estimate (KEK) of the short-term (1- to 2-day) ozone forecast. The Kalman filter predictor bias-corrected ensemble forecasts have better forecast skill than the raw forecasts for the locations and days used here. The corrected forecasts are improved for correlation, gross error, root mean square error, and unpaired peak prediction accuracy. KEK is the best and EK is the second best forecast overall when compared with the other 12 forecasts. The reason for the success of EK and KEK is that both the systematic and unsystematic errors are reduced, the first by Kalman filtering and the second by ensemble averaging. An edited version of this paper was published by AGU. Copyright 2006 American Geophysical Union.Science, Faculty ofEarth and Ocean Sciences, Department ofReviewedFacult

Verification of Mesoscale Numerical Weather Forecasts in Mountainous Terrain for Application to Avalanche Prediction.

Two high-resolution, real-time, numerical weather prediction (NWP) models are verified against case study observations to quantify their accuracy and skill in the mountainous terrain of western Canada. These models, run daily at the University of British Columbia (UBC), are the Mesoscale Compressible Community (MC2) Model and the University of Wisconsin Nonhydrostatic Modeling System (NMS). The main motivations of this work are: 1) to extend the lead time of avalanche forecasts by using NWP-projected meteorological variables as input to statistical avalanche threat models; and 2) to create another tool to help avalanche forecasters in their daily decision-making process. Observation data from the Whistler/Blackcomb ski area in the British Columbia (BC) Coast Mountains and from Kootenay Pass in the Columbia Mountains of southeast BC are used to verify the forecasts. The two models are run with grid spacings of 3.3 km (MC2) and 10 km (NMS) over Whistler/Blackcomb, and with 2, 10 (MC2), and 30 km (NMS) over Kootenay Pass. The quality of the forecasts is measured using standard statistical methods for those variables that are important for avalanche forecasting. It is found that the raw model output has biases that can be easily removed using Kalman filter predictor postprocessing. The resulting automatically corrected forecasts have quite small absolute errors in temperature (0.78C). It is also found that the coarser-resolution NMS model produces comparable results to the finer-resolution MC2 model for precipitation at Kootenay Pass. These objective forecast errors are of the same order of magnitude as the meteorological observation (sampling/representativeness) errors in the snowy, windy mountainous terrain, resulting in forecasts that have value in extending the range of avalanche forecasts for locations such as Kootenay Pass, as discussed in a recent study by Roeger et al. Copyright 2003 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected], Faculty ofEarth and Ocean Sciences, Department ofReviewedFacult

Exploring the Associations between Single-Child Status and Childhood High Blood Pressure and the Mediation Effect of Lifestyle Behaviors

Background: This study aimed to assess the association between single-child status and childhood high blood pressure (HBP) and to explore the role of lifestyle behaviors in this relationship. Methods: This study used data from a cross-sectional survey of 50,691 children aged 7~18 years in China. Linear and logistic regression models were used to assess the relationship between single-child status and HBP, and interactions between single-child status and lifestyle behaviors were also evaluated. Mediation analysis was conducted to detect the mediation effect of lifestyle behaviors. Results: Of the participants enrolled, 67.2% were single children and 49.4% were girls. Non-single children were associated with a greater risk of HBP, especially in girls (OR = 1.11, 95%CI: 1.03~1.19). Meat consumption and sedentary behavior mediated 58.9% of the association between single-child status and HBP (p < 0.01). When stratified by sleeping duration, non-single girls of insufficient sleep and hypersomnia showed a higher risk of HBP (p < 0.05) than single-child peers, but not in those with adequate sleep. Conclusion: Findings suggest that non-single children had an increased risk of HBP, and keeping healthy lifestyle behaviors could help to mitigate the adverse impact in non-single children