849 resultados para Risk factor.
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Introduction: Self-image is important in the behaviour and lifestyle of children and adolescents. Analysing the self-image they have and the factors that might influence their distortion, can be used to prevent problems of obesity and anorexia. The main objective of present publication was to analyse the risk factors that may contribute to self-image distortion. Material and Methods: A descriptive survey study was conducted among 659 children and adolescents in two social classes (low and medium-high), measuring height and weight, calculating BMI percentile for age and gender. Body image and self-perception were registered. Results: The percentage of overweight-obesity is higher in scholars (41.8% boys, 28.7% girls) than in adolescents (30.1% and 22.2% respectively), with no difference between socioeconomic classes. The multinomial logistic regression analysis gives a risk of believing thinner higher (p=0.000) among boys OR=2.9(95%CI:1.43-3.37), school (p=0.000) OR=2.42(95%CI:1.56-3.76) and much lower (p=0.000) between normally nourished OR=0.08(95%CI:0.05-0.13), with no differences according to socioeconomic status. The risk of believing fatter is lower (p=0.000) between boys OR=0.28(95%CI:0.14-0.57), school(p=0.072) OR=0.54(95%CI:0.27-1.6), and much higher among underweight (p=0.000) OR=9x108(95% CI:4x108-19x108). Conclusions: Are risk factors of believing thinner: males, being in a group of schoolchildren and overweight-obesity. Conversely, are risk factors of believing fatter: females, teen and above all, be thin.
The development of an improved railroad-highway grade crossing risk factor. Executive summry report.
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Ohio Department of Transportation, Columbus
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Ohio Department of Transportation, Columbus
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"November 1986."
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The Low-Density Lipoprotein Receptor (LDLR) gene is a cell surface receptor that plays an important role in cholesterol homeostasis. We investigated the (TA)n polymorphism in exon 18 of the LDLR gene on chromosome 19p13.2 performing an association analysis in 244 typical migraine-affected patients, 151 suffering from migraine with aura (MA), 96 with migraine without aura (MO) and 244 unaffected controls. The populations consisted of Caucasians only, and controls were age- and sex-matched. The results showed no significant difference between groups for allele frequency distributions of the (TA)n polymorphism even after separation of the migraine-affected individuals into subgroups of MA and MO affected patients. This is in contradiction to Mochi et al. [Mochi M, Cevoli S, Cortelli P, Pierangeli G, Scapoli C, Soriani S, Montagna P. Investigation of an LDLR gene polymorphism (19p13.2) in susceptibility to migrane without aura. J Neurol Sci 2003; 213 (1-2): 7-10.] who found a positive association of this variant with MO. Our study discusses possible differences between the two studies and extends this research by investigating circulating cholesterol levels in a migraine-affected population. (C) 2004 Elsevier B.V. All rights reserved.
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It remains unclear whether genetic variants in SNCA (the alpha-synuclein gene) alter risk for sporadic Parkinson's disease (PD). The polymorphic mixed sequence repeat (NACP-Rep I) in the promoter region of SNCA has been previously examined as a potential susceptibility factor for PD with conflicting results. We report genotype and allele distributions at this locus from 369 PD cases and 370 control subjects of European Australian ancestry, with alleles designated as -1, 0, +1, +2, and +3 as previously described. Allele frequencies designated (0) were less common in Australian cases compared to controls (OR = 0.80, 95% CI 0.62-1.03). Combined analysis including all previously published ancestral European Rep1 data yielded a highly significant association between the 0 allele and a reduced risk for PD (OR = 0.79, 95% CI 0.70-0.89, p = 0.0001). Further study must now proceed to examine in detail this interesting and biologically plausible genetic association. (C) 2004 Elsevier Ireland Ltd. All rights reserved.
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Reliable, comparable information about the main causes of disease and injury in populations, and how these are changing, is a critical input for debates about priorities in the health sector. Traditional sources of information about the descriptive epidemiology of diseases, injuries and risk factors are generally incomplete, fragmented and of uncertain reliability and comparability. Lack of a standardized measurement framework to permit comparisons across diseases and injuries, as well as risk factors, and failure to systematically evaluate data quality have impeded comparative analyses of the true public health importance of various conditions and risk factors. As a consequence the impact of major conditions and hazards on population health has been poorly appreciated, often leading to a lack of public health investment. Global disease and risk factor quantification improved dramatically in the early 1990s with the completion of the first Global Burden of Disease Study. For the first time, the comparative importance of over 100 diseases and injuries, and ten major risk factors, for global and regional health status could be assessed using a common metric (Disability-Adjusted Life Years) which simultaneously accounted for both premature mortality and the prevalence, duration and severity of the non-fatal consequences of disease and injury. As a consequence, mental health conditions and injuries, for which non-fatal outcomes are of particular significance, were identified as being among the leading causes of disease/injury burden worldwide, with clear implications for policy, particularly prevention. A major achievement of the Study was the complete global descriptive epidemiology, including incidence, prevalence and mortality, by age, sex and Region, of over 100 diseases and injuries. National applications, further methodological research and an increase in data availability have led to improved national, regional and global estimates for 2000, but substantial uncertainty around the disease burden caused by major conditions, including, HIV, remains. The rapid implementation of cost-effective data collection systems in developing countries is a key priority if global public policy to promote health is to be more effectively informed.