The global burden attributable to low bone mineral density

Introduction The Global Burden of Disease Study 2010 estimated the worldwide health burden of 291 diseases and injuries and 67 risk factors by calculating disability-adjusted life years (DALYs). Osteoporosis was not considered as a disease, and bone mineral density (BMD) was analysed as a risk factor for fractures, which formed part of the health burden due to falls. Objectives To calculate (1) the global distribution of BMD, (2) its population attributable fraction (PAF) for fractures and subsequently for falls, and (3) the number of DALYs due to BMD. Methods A systematic review was performed seeking population-based studies in which BMD was measured by dual-energy X-ray absorptiometry at the femoral neck in people aged 50 years and over. Age- and sex-specific mean ± SD BMD values (g/cm2) were extracted from eligible studies. Comparative risk assessment methodology was used to calculate PAFs of BMD for fractures. The theoretical minimum risk exposure distribution was estimated as the age- and sex-specific 90th centile from the Third National Health and Nutrition Examination Survey (NHANES III). Relative risks of fractures were obtained from a previous meta-analysis. Hospital data were used to calculate the fraction of the health burden of falls that was due to fractures. Results Global deaths and DALYs attributable to low BMD increased from 103 000 and 3 125 000 in 1990 to 188 000 and 5 216 000 in 2010, respectively. The percentage of low BMD in the total global burden almost doubled from 1990 (0.12%) to 2010 (0.21%). Around one-third of falls-related deaths were attributable to low BMD. Conclusions Low BMD is responsible for a growing global health burden, only partially representative of the real burden of osteoporosis.

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study

Investigative trends in understanding penalty-kick performance in association football: An ecological dynamics perspective

There have been different approaches to studying penalty-kick performance in association football. In this paper, the authors synthesize key findings within an ecological dynamics theoretical framework. According to this theoretical perspective, information is the cornerstone for understanding the dynamics of action regulation in penalty-kick performance. Research suggests that investigators need to identify the information sources that are most relevant to penalty-kick performance. An important task is to understand how constraints can channel (i.e. change, emphasize or mask) information sources used to regulate upcoming actions and how the influence of these constraints is expressed in players' behavioural dynamics. Due to the broad range of constraints influencing penalty-kick performance, it is recommended that future research adopts an interdisciplinary focus on performance assessment to overcome the current lack of representativeness in penalty-kick experimental designs. Such an approach would serve to capture the information-based control of action of both players as components of this dyadic system in competitive sport.

The contribution of three components of nutrition knowledge to socio-economic differences in food purchasing choices

Objectives: To assess socio-economic differences in three components of nutrition knowledge, i.e. knowledge of (i) the relationship between diet and disease, (ii) the nutrient content of foods and (iii) dietary guideline recommendations; furthermore, to determine if socio-economic differences in nutrition knowledge contribute to inequalities in food purchasing choices. Design: The cross-sectional study considered household food purchasing,nutrition knowledge, socio-economic and demographic information. Household food purchasing choices were summarised by three indices, based on self-reported purchasing of sixteen groceries, nineteen fruits and twenty-one vegetables. Socio-economic position (SEP) was measured by household income and education. Associations between SEP, nutrition knowledge and food purchasing were examined using general linear models adjusted for age, gender, household type and household size. Setting: Brisbane, Australia in 2000. Subjects: Main household food shoppers (n 1003, response rate 66?4 %), located in fifty small areas (Census Collectors Districts). Results: Shoppers in households of low SEP made food purchasing choices that were less consistent with dietary guideline recommendations: they were more likely to purchase grocery foods comparatively higher in salt, sugar and fat, and lower in fibre, and they purchased a narrower range of fruits and vegetables. Those of higher SEP had greater nutrition knowledge and this factor attenuated most associations between SEP and food purchasing choices. Among nutrition knowledge factors, knowledge of the relationship between diet and disease made the greatest and most consistent contribution to explaining socio-economic differences in food purchasing. Conclusions: Addressing inequalities in nutrition knowledge is likely to reduce socio-economic differences in compliance with dietary guidelines. Improving knowledge of the relationship between diet and disease appears to be a particularly relevant focus for health promotion aimed to reduce socio-economic differences in diet and related health inequalities.

Assessment of the molecular structure of an intermediate member of the triplite-zwieselite mineral series: A raman and infrared study

The mineral series triplite-zwieselite with theoretical formula (Mn2+)2(PO4)(F)-(Fe2+)2(PO4)(F) from the El Criolo granitic pegmatite, located in the Eastern Pampean Ranges of Córdoba Province, was studied using electron microprobe, thermogravimetry, and Raman and infrared spectroscopy. The analysis of the mineral provided a formula of (Fe1.00, Mn0.85, Ca0.08, Mg0.06)∑2.00(PO4)1.00(F0.80, OH0.20)∑1.00. An intense Raman band at 981 cm−1 with a shoulder at 977 cm−1 is assigned to the ν1 symmetric stretching mode. The observation of two bands for the phosphate symmetric stretching mode offers support for the concept that the phosphate units in the structure of triplite-zwieselite are not equivalent. Low-intensity Raman bands at 1012, 1036, 1071, 1087, and 1127 cm−1 are assigned to the ν3 antisymmetric stretching modes. A set of Raman bands at 572, 604, 639, and 684 cm−1 are attributed to the ν4 out-of-plane bending modes. A single intense Raman band is found at 3508 cm−1 and is assigned to the stretching vibration of hydroxyl units. Infrared bands are observed at 3018, 3125, and 3358 cm−1 and are attributed to water stretching vibrations. Supplemental materials are available for this article. Go to the publisher's online edition of Spectroscopy Letters to view the supplemental file.