109 resultados para Hemorrhagic Fever with Renal Syndrome, Risk Factors, Time-series Poisson Regression


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The aim of this study was to assess the coronary heart disease risk factors in the Asian Indian community living in a large city in Australia. A cross-sectional survey was conducted at the Australia India Friendship Fair in 2010. All people of Asian Indian descent who attended the Fair and visited the health promotion stall were eligible to participate in the study if they self-identified as of Asian Indian origin, were aged between 18 and 80 years, and were able to speak English. Blood pressure, blood glucose, waist circumference, height, and weight were measured by a health professional. Smoking, cholesterol levels, and physical activity status were obtained through self-reports. Data were analyzed for 169 participants. More than a third of the participants under the age of 65 years had high blood pressure. Prevalence of diabetes (16%) and obesity (61%) was significantly higher compared with the national average. Ten women identified themselves as smokers. Physical activity patterns were similar to that of the wider Australian population. The study has provided a platform for raising awareness among nurses and promoting advocacy on the cardiovascular risk among Asian Indians. Strategies involving Asian Indian nurses and other Asian Indian health professionals as well as support from the private and public sectors can assist in the reduction of the coronary heart disease risk factors among this extremely susceptible population.

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In this study, we report the epidemiology and risk factors for humeral fractures (proximal humerus and shaft) among men and women residing in south-eastern Australia. Incident fractures during 2006 and 2007 were identified using X-ray reports (Geelong Osteoporosis Study Fracture Grid). Risk factors were identified using data from case-control studies conducted as part of the Geelong Osteoporosis Study. Median age of fracture was lower in males than females for proximal humerus (33.0 vs 71.2 years), but not for humeral shaft (8.9 vs 8.5 years). For females, proximal humerus fractures occurred mainly in the 70-79 and 80+ years age groups, whereas humeral shaft fractures followed a U-shaped pattern. Males showed a U-shaped pattern for both proximal humerus and humeral shaft fractures. Overall age-standardised incidence rates for proximal humerus fractures in males and females were 40.6 (95 % CI 32.7, 48.5) and 73.2 (95 % CI 62.2, 84.1) per 100,000 person years, respectively. For humeral shaft fractures, the age-standardised rate was 69.3 (95 % CI 59.0, 79.6) for males and 61.5 (95 % CI 51.9, 71.0) for females. There was an increase in risk of proximal humerus fractures in men with a lower femoral neck BMD, younger age, prior fracture and higher milk consumption. In pre-menopausal women, increased height and falls were both risk factors for proximal humerus fractures. For post-menopausal women, risk factors associated with proximal humerus fractures included a lower non-milk dairy consumption and sustaining a prior fracture. Humeral shaft fractures in both sexes were sustained mainly in childhood, while proximal humerus fractures were sustained in older adulthood. The overall age-standardised rates of proximal humerus fractures were nearly twice as high in females compared to males, whereas the incidence rates of humeral shaft fractures were similar.

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Recent years have seen a consensus emerge regarding the dynamic risk factors that are associated with future violence. These risk factors are now routinely assessed in structured violence risk assessment instruments. They provide a focus for treatment in structured group programmes. However, relatively little attention has been paid to risk-related theoretical issues, whether these dynamic risk factors are causally related or simply correlates of violent offending, or the extent to which they change as a consequence of treatment. More challenging is the lack of evidence to suggest that changes in these dynamic risk factors actually result in reductions in violent offending. In this paper we consider the meaning of the term dynamic risk, arguing that only those factors that, when changed, reduce the likelihood of violent recidivism, can be considered to be truly dynamic. We conclude that few of the violence risk factors commonly regarded as dynamic fulfil this requirement. There is a need to think more critically about assessment findings and treatment recommendations relating to dynamic risk, and conduct research that establishes, rather than assumes, that certain dynamic risk factors are directly related to violence. Some suggestions for advancing knowledge and practice are provided.

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Background

Previous reviews on risk and protective factors for violence in psychosis have produced contrasting findings. There is therefore a need to clarify the direction and strength of association of risk and protective factors for violent outcomes in individuals with psychosis.

Method

We conducted a systematic review and meta-analysis using 6 electronic databases (CINAHL, EBSCO, EMBASE, Global Health, PsycINFO, PUBMED) and Google Scholar. Studies were identified that reported factors associated with violence in adults diagnosed, using DSM or ICD criteria, with schizophrenia and other psychoses. We considered non-English language studies and dissertations. Risk and protective factors were meta-analysed if reported in three or more primary studies. Meta-regression examined sources of heterogeneity. A novel meta-epidemiological approach was used to group similar risk factors into one of 10 domains. Sub-group analyses were then used to investigate whether risk domains differed for studies reporting severe violence (rather than aggression or hostility) and studies based in inpatient (rather than outpatient) settings.

Findings

There were 110 eligible studies reporting on 45,533 individuals, 8,439 (18.5%) of whom were violent. A total of 39,995 (87.8%) were diagnosed with schizophrenia, 209 (0.4%) were diagnosed with bipolar disorder, and 5,329 (11.8%) were diagnosed with other psychoses. Dynamic (or modifiable) risk factors included hostile behaviour, recent drug misuse, non-adherence with psychological therapies (p values<0.001), higher poor impulse control scores, recent substance misuse, recent alcohol misuse (p values<0.01), and non-adherence with medication (p value <0.05). We also examined a number of static factors, the strongest of which were criminal history factors. When restricting outcomes to severe violence, these associations did not change materially. In studies investigating inpatient violence, associations differed in strength but not direction.

Conclusion

Certain dynamic risk factors are strongly associated with increased violence risk in individuals with psychosis and their role in risk assessment and management warrants further examination.

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AIM: To determine whether the risk of stillbirth is associated with male fetal sex, fetal growth and maternal factors in an Australian population. METHODS: A retrospective secondary data analysis of 16 445 singleton births was performed using a tertiary referral centre obstetric database (1995-1999). Univariate and multiple logistic regression analyses were performed. RESULTS: Stillbirth complicated 1% of the pregnancies in the study population, and 59% of stillbirths were associated with a male fetus. Significant characteristics associated with stillbirth were intrauterine growth restriction (IUGR), birth defects, gestational age, Aboriginal ethnicity, previous stillbirth, parity greater than three and placental abruption. Male stillbirths were more likely to occur at a later gestation (median gestation 30.5 weeks, range 20-43 weeks) compared to females (median 25 weeks, range 20-40 weeks), P = 0.01. Sixty per cent of IUGR fetuses were female (P < 0.001). Male sex (odds ratio (OR) 1.5, confidence interval (CI) 1.01, 2.17, P = 0.04) and maternal type 1 diabetes (OR 4.7, CI 1.58, 14.19, P = 0.006) were independently associated with stillbirth. CONCLUSION: Male fetal sex and pre-existing diabetes are independent risk factors for stillbirth. Diabetes remains a significant risk for stillbirth even with contemporary monitoring and clinical management. Those diabetic pregnancies where the fetus is male require appropriate monitoring and timely interventions to achieve an optimal outcome.

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AIM: Infertility is a concern for young survivors of colorectal cancer (CRC), but this risk is not well quantified. Carriers of mismatch repair (MMR) mutations are a useful cohort for studying fertility after CRC as they commonly develop CRC when young, and unaffected family members provide demographically similar controls. The aim of this study was to determine the effect of CRC on fertility in a large cohort of MMR mutation carriers. METHOD: Mismatch repair mutation carriers identified from the Australasian Colorectal Cancer Family Registry were included. For each year of life within the fertile age range (15-49), the number of living individuals and the number of children born to them were determined. Individuals were grouped by whether or not they had had a diagnosis of CRC by that age. Age-specific and total fertility rates were calculated. RESULTS: We identified 1068 subjects (611 women and 457 men), of whom 467 were diagnosed with CRC. There were 1192 births during 18 674 person-years of follow-up to the women and 814 births during 14 013 person-years of follow-up to the men. The total fertility rate was decreased in women after a diagnosis of CRC compared with those who did not have CRC (1.3 vs 2.2; P = 0.0011), but age-specific fertility was only reduced in the 20-24-year age group. In men the total fertility rate was similar for both groups (2.0 vs 1.8; P = 0.27). CONCLUSION: Age-specific fertility was decreased in female CRC survivors with Lynch syndrome aged 20-24, but not in older women or in men.

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Background
This paper examines the opportunity and need for lifestyle interventions for patients attending generalist community nursing services in Australia. This will help determine the scope for risk factor management within community health care by generalist community nurses (GCNs).

Methods
This was a quasi-experimental study conducted in four generalist community nursing services in NSW, Australia. Prior to service contacts, clients were offered a computer-assisted telephone interview to collect baseline data on socio-demographics, health conditions, smoking status, physical activity levels, alcohol consumption, height and weight, fruit and vegetable intake and 'readiness-to-change' for lifestyle risk factors.

Results

804 clients participated (a response rate of 34.1%). Participants had higher rates of obesity (40.5% vs 32.1%) and higher prevalence of multiple risk factors (40.4% vs 29.5%) than in the general population. Few with a SNAPW (S moking-N utrition-A lcohol-P hysical-Activity-Weight) risk factor had received advice or referral in the previous 3 months. The proportion of clients identified as at risk and who were open to change (i.e. contemplative, in preparation or in action phase) were 65.0% for obese/overweight; 73.8% for smokers; 48.2% for individuals with high alcohol intake; 83.5% for the physically inactive and 59.0% for those with poor nutrition.

Conclusions

There was high prevalence of lifestyle risk factors. Although most were ready to change, few clients recalled having received any recent lifestyle advice. This suggests that there is considerable scope for intervention by GCNs. The results of this trial will shed light on how best to implement the lifestyle risk factor management in routine practice.

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Objectives

To examine relationships between body mass index (BMI), prevalence of physician-recorded cardiovascular disease (CVD) risk factors in primary care, and changes in risk with 10% weight change.

Methods

The Counterweight Project conducted a baseline cross-sectional survey of medical records of 6150 obese (BMI ≥ 30 kg/m2), 1150 age- and sex-matched overweight (BMI 25 to <30 kg/m2), and 1150 age- and sex-matched normal weight (BMI 18.5 to <25 kg/m2) controls, in primary care. Data were collected for the previous 18 months to examine BMI and disease prevalence, and then modelled to show the potential effect of 10% weight loss or gain on risk.

Results

Obese patients develop more CVD risk factors than normal weight controls. BMI ≥ 40 kg/m2 exhibits increased prevalence of type 2 diabetes mellitus (DM), odds ratio (OR) men: 6.16 (p < 0.001); women: 7.82 (p < 0.001) and hypertension OR men: 5.51 (p < 0.001); women: 4.16 (p < 0.001). Dyslipidaemia peaked around BMI 35 to <37.5 kg/m2, OR men: 3.26 (p < 0.001); women 3.76 (p < 0.001) and CVD at BMI 37.5 to <40 kg/m2 in men, OR 4.48 (p < 0.001) and BMI ≥ 40 kg/m2 in women, OR 3.98 (p < 0.001).

A 10% weight loss from the sample mean of 32.5 kg/m2 reduced the OR for type 2 DM by 30% and CVD by 20%, while 10% weight gain increased type 2 DM risk by more than 35% and CVD by 20%.

Conclusion

Obesity plays a fundamental role in CVD risk, which is reduced with weight loss. Weight management intervention strategies should be a public health priority to reduce the burden of disease in the population.

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Background

Despite evidence for the effectiveness of interventions to modify lifestyle behaviours in the primary health care (PHC) setting, assessment and intervention for these behaviours remains low in routine practice. Little is known about the relative importance of various determinants of practice.

This study aimed to examine the relative importance of provider characteristics and attitudes, patient characteristics and consultation factors in determining the rate of assessment and intervention for lifestyle risk factors in PHC.

Methods

A prospective audit of assessment and intervention for lifestyle risk factors was undertaken by PHC nurses and allied health providers (n = 57) for all patients seen (n = 732) over a two week period. Providers completed a survey to assess key attitudes related to addressing lifestyle issues. Multi-level logistic regression analysis of patient audit records was undertaken. Associations between variables from both data sources were examined, together with the variance explained by patient and consultation (level 1) and provider (level 2) factors.

Results

There was significant variance between providers in the assessment and intervention for lifestyle risk factors. The consultation type and reason for the visit were the most important in explaining the variation in assessment practices, however these factors along with patient and provider variables accounted for less than 20% of the variance. In contrast, multi-level models showed that provider factors were most important in explaining the variance in intervention practices, in particular, the location of the team in which providers worked (urban or rural) and provider perceptions of their effectiveness and accessibility of support services. After controlling for provider variables, patients' socio-economic status, the reason for the visit and providers' perceptions of the 'appropriateness' of addressing risk factors in the consultation were all significantly associated with providing optimal intervention. Together, measured patient consultation and provider variables accounted for most (80%) of the variation in intervention practices between providers.

Conclusion

The findings highlight the importance of provider factors such as beliefs and attitudes, team location and work context in understanding variations in the provision of lifestyle intervention in PHC. Further studies of this type are required to identify variables that improve the proportion of variance explained in assessment practices.

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Background
Primary health care (PHC) clinicians have an important role to play in addressing lifestyle risk factors for chronic diseases. However they intervene only rarely, despite the opportunities that arise within their routine clinical practice. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about this for PHC clinicians working outside general practice. The aim of this study was to explore the beliefs and attitudes of PHC clinicians about incorporating lifestyle risk factor management into their routine care and to examine whether these varied according to their self reported level of risk factor management.

Methods

A cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians' beliefs and attitudes were also explored through qualitative interviews with a purposeful sample of 22 clinicians from the teams. Mixed methods analysis was used to compare beliefs and attitudes for those with high and low levels of self reported risk factor management.

Results
Role congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians' own lifestyle were key themes related to risk factor management practices. Those reporting high levels of risk factor screening and intervention had different beliefs and attitudes to those PHC clinicians who reported lower levels.

Conclusion

PHC clinicians' level of involvement in risk factor management reflects their beliefs and attitudes about it. This provides insights into ways of intervening to improve the integration of behavioural risk factor management into routine practice.

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BACKGROUND: Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. METHODS: We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. RESULTS: Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. CONCLUSIONS: These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

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BACKGROUND: Workplace health programs have demonstrated improvements in a number of risk factors for chronic disease. However, there has been little investigation of participant characteristics that may be associated with change in risk factors during such programs. The aim of this paper is to identify participant characteristics associated with improved waist circumference (WC) following participation in a four-month, pedometer-based, physical activity, workplace health program.

METHODS: 762 adults employed in primarily sedentary occupations and voluntarily enrolled in a four-month workplace program aimed at increasing physical activity were recruited from ten Australian worksites in 2008. Seventy-nine percent returned at the end of the health program. Data included demographic, behavioural, anthropometric and biomedical measurements. WC change (before versus after) was assessed by multivariable linear and logistic regression analyses. Seven groupings of potential associated variables from baseline were sequentially added to build progressively larger regression models.

RESULTS: Greater improvement in WC during the program was associated with having completed tertiary education, consuming two or less standard alcoholic beverages in one occasion in the twelve months prior to baseline, undertaking less baseline weekend sitting time and lower baseline total cholesterol. A greater WC at baseline was strongly associated with a greater improvement in WC. A sub-analysis in participants with a 'high-risk' baseline WC revealed that younger age, enrolling for reasons other than appearance, undertaking less weekend sitting time at baseline, eating two or more pieces of fruit per day at baseline, higher baseline physical functioning and lower baseline body mass index were associated with greater odds of moving to 'low risk' WC at the end of the program.

CONCLUSIONS: While employees with 'high-risk' WC at baseline experienced the greatest improvements in WC, the other variables associated with greater WC improvement were generally indicators of better baseline health. These results indicate that employees who started with better health, potentially due to lifestyle or recent behavioural changes, were more likely to respond positively to the program. Future health program initiators should think innovatively to encourage all enrolees along the health spectrum to achieve a successful outcome.

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Although there is increasing concern about both the prevalence of, and harms associated with the abuse of older adults, progress in the development of interventions to prevent its occurrence has been slow. This paper reports the findings of a systematic review of the published literature that identified studies in which the outcomes of preventative interventions are described. A total of eight different intervention trials, published since 2004, are described across the primary, secondary and tertiary levels of prevention and in terms of the types of risk factor that they target. The current evidence to support the effectiveness of these interventions is not only limited by the small number of outcome studies but also the poor quality of evaluation designs and the focus of many interventions on single risk factors. It is concluded that work is needed to strengthen the evidence base that supports the delivery of interventions to prevent elder abuse.

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This project measured population salt intake in Samoa by integrating urinary sodium analysis into the World Health Organization's (WHO's) STEPwise approach to surveillance of noncommunicable disease risk factors (STEPS). A subsample of the Samoan Ministry of Health's 2013 STEPS Survey collected 24-hour and spot urine samples and completed questions on salt-related behaviors. Complete urine samples were available for 293 participants. Overall, weighted mean population 24-hour urine excretion of salt was 7.09 g (standard error 0.19) to 7.63 g (standard error 0.27) for men and 6.39 g (standard error 0.14) for women (P=.0014). Salt intake increased with body mass index (P=.0004), and people who added salt at the table had 1.5 g higher salt intakes than those who did not add salt (P=.0422). A total of 70% of the population had urinary excretion values above the 5 g/d cutoff recommended by the WHO. A reduction of 30% (2 g) would reduce average population salt intake to 5 g/d, in line with WHO recommendations. While challenging, integration of salt monitoring into STEPS provides clear logistical and cost benefits and the lessons communicated here can help inform future programs.

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Many parts of the world in which common infectious diseases are endemic also have the highest prevalence of trace metal deficiencies or rising rates of trace metal pollution. Infectious diseases can increase human susceptibility to adverse effects of metal exposure (at suboptimal or toxic levels), and metal excess or deficiency can increase the incidence or severity of infectious diseases. The co-clustering of major infectious diseases with trace metal deficiency or toxicity has created a complex web of interactions with serious but poorly understood health repercussions, yet has been largely overlooked in animal and human studies. This book focuses on the distribution, trafficking, fate, and effects of trace metals in biological systems. Its goal is to enhance our understanding of the relationships between homeostatic mechanisms of trace metals and the pathogenesis of infectious diseases. Drawing on expertise from a range of fields, the book offers a comprehensive review of current knowledge on vertebrate metal-withholding mechanisms and the strategies employed by different microbes to avoid starvation (or poisoning). Chapters summarize current, state-of-the-art techniques for investigating pathogen-metal interactions and highlight open question to guide future research. The book makes clear that improving knowledge in this area will be instrumental to the development of novel therapeutic measures against infectious diseases. ContributorsM. Leigh Ackland, Vahid Fa Andisi, Angele L. Arrieta, Michael A. Bachman, J. Sabine Becker, Robert E. Black, Julia Bornhorst, Sascha Brunke, Joseph A. Caruso, Jennifer S. Cavet, Anson C. K. Chan, Christopher H. Contag, Heran Darwin, George V. Dedoussis, Rodney R. Dietert, Victor J. DiRita, Carol A. Fierke, Tamara Garcia-Barrera, David P. Giedroc, Peter-Leon Hagedoorn, James A. Imlay, Marek J. Kobylarz, Joseph Lemire, Wenwen Liu, Slade A. Loutet, Wolfgang Maret, Andreas Matusch, Trevor F. Moraes, Michael E. P. Murphy, Maribel Navarro, Jerome O. Nriagu, Ana-Maria Oros-Peusquens, Elisabeth G. Pacyna, Jozef M. Pacyna, Robert D. Perry, John M. Pettifor, Stephanie Pfaffen, Dieter Rehder, Lothar Rink, Anthony B. Schryvers, Ellen K. Silbergeld, Eric P. Skaar, Miguel C. P. Soares, Kyrre Sundseth, Dennis J. Thiele, Richard B. Thompson, Meghan M. Verstraete, Gonzalo Visbal, Fudi Wang, Mian Wang, Thomas J. Webster, Jeffrey N. Weiser, Günter Weiss, Inga Wessels, Bin Ye, Judith T. Zelikoff, Lihong Zhang