145 resultados para Risk Factors
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PURPOSE: We sought to examine cancer diagnosis, cancer treatment, and related risk factors among Australian, middle-aged, exclusively heterosexual women compared with sexual minority women (SMW; mainly heterosexual, bisexual, mainly lesbian, and lesbian). METHODS: Secondary data analysis of the Australian Longitudinal Study of Women's Health for women born in 1946 through 1951 (n = 10,451) included bivariate tests (i.e., contingency table analyses, independent t tests). RESULTS: SMW did not have significantly higher cancer diagnoses compared with exclusively heterosexual women, although they were more likely to report never having had a mammogram or pap smear. SMW were also significantly more likely to be high-risk drinkers (11.1% vs. 6.8%; p < .05), current smokers (15.1% vs. 8.3%; p < .001), report significantly higher rates of depression (mean ± SD; 6.4 ± 5.5 vs. 5.4 ± 5.1; p < .01.), have experienced physical abuse (10.2% vs. 5.1%; p < .001), and been in a violent relationship (27.2% vs. 12.8%; p < .001). CONCLUSION: SMW had higher rates of several known cancer risk factors, ostensibly placing them at higher risk of cancer as well as chronic health conditions. Further research is needed to determine whether increased risk results in increased cancer as these women age, and to inform the development of interventions to reduce the risk of disease for SMW.
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BACKGROUND: Adequate nutrition is needed to ensure optimum growth and development of infants and young children. Understanding of the risk factors for stunting and severe stunting among children aged less than five years in North Maluku province is important to guide Indonesian government public health planners to develop nutrition programs and interventions in a post conflict area. The purpose of the current study was to assess the prevalence of and the risk factors associated with stunting and severe stunting among children aged less than five years in North Maluku province of Indonesia. METHODS: The health and nutritional status of children aged less than five years was assessed in North Maluku province of Indonesia in 2004 using a cross-sectional multi-stage survey conducted on 750 households from each of the four island groups in North Maluku province. A total of 2168 children aged 0-59 months were used in the analysis. RESULTS: Prevalence of stunting and severe stunting were 29% (95%CI: 26.0-32.2) and 14.1% (95%CI: 11.7-17.0) for children aged 0-23 months and 38.4% (95%CI: 35.9-41.0) and 18.4% (95%CI: 16.1-20.9) for children aged 0-59 months, respectively. After controlling for potential confounders, multivariate analysis revealed that the risk factors for stunted children were child's age in months, male sex and number of family meals per day (
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AIMS: Few studies have examined the role of gender and both area-level and individual socio-economic status (SES) as independent predictors of alcohol-related aggression (ARA) in and around licensed venues. METHODS: The aim of the present study was to investigate the relationship between gender, area-level SES and individual SES (operationalised as occupational category) and ARA in and around licensed venues. The sample comprised 697 men and 649 women aged 16-47, who completed a patron intercept survey as part of a larger study assessing trends in harm and stakeholders' views surrounding local community level interventions in dealing with alcohol-related problems in the night-time economy. RESULTS: Binary logistic regression analyses showed that age, gender, occupational category, area-level SES and level of intoxication at time of interview were all significant predictors of involvement in ARA. Being male doubled the odds of involvement in ARA, while age was a protective factor. Blue collar workers had more than double the odds of ARA involvement of professionals, while those living in the most socio-economically disadvantaged areas were over twice as likely to report experiencing ARA compared to those living in the most advantaged areas. However, assessment of the predictive model by gender revealed that effects of age, occupational category and area-level SES were restricted to male participants, with greater intoxication no longer predictive. CONCLUSIONS: ARA among patrons was significantly more likely to occur among men, those in blue collar occupations, and individuals living in low SES areas, suggesting both individual and area-level disadvantage may play a role in ARA.
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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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Increasing age is a risk factor for diabetes; consequently, diabetes is prevalent in older people. Older people with diabetes are at high risk of cardiovascular disease (CVD) and cardiovascular events, such as myocardial infarction and heart failure.Multiple pathological processes underlie CVD, including inflammation, oxidative stress, endothelial dysfunction, thrombosis and angiogenesis. These pathological processes are influenced by age, ethnicity, genetic makeup, obesity, hyperglycaemia,insulin resistance, dyslipidaemia, hypertension, renal disease, inappropriate diet and inactivity, which are components of the metabolic syndrome and CVD risk factors. The more risk factors present, the higher the risk of CVD. Significantly, vascular damage occurs slowly; therefore, it is essential to undertake a comprehensive vascular risk assessment and manage the risk early in life to improve the individual’soutcomes. Management strategies must be negotiated with the individual and appropriately tailored to their CVD risk and functional status, life expectancy and safety.
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OBJECTIVE: To determine whether the amount of time spent in screen-based behaviors (SBBs; television viewing, computer use, and playing electronic games) is independently associated with individual and clustered cardiovascular disease (CVD) risk factors among elementary school children. STUDY DESIGN: Baseline data were used from 264 children (age 7-10 years) participating in the Transform-Us! cluster-randomized controlled trial. Time (h/d) spent in SBBs was obtained using a parent proxy-report questionnaire. Anthropometrics, blood pressure (BP), and lipids were measured using standard techniques. A clustered CVD risk score was calculated as the average of the standardized values of the subcomponents (waist circumference [WC], systolic BP, diastolic BP, and lipids). RESULTS: After adjusting for sex, parent education, physical activity (accelerometry), diet, and WC (when adiposity was not the outcome), television viewing time was positively associated with body mass index z-score (P = .002), WC (P = .02), and systolic BP (P = .05). Electronic games was positively associated with low density lipoprotein levels (P = .05), and total screen-time was positively associated with body mass index (P = .02). CONCLUSIONS: Differential associations were observed between types of SBBs and CVD risk factors, indicating that not all SBBs are adversely associated with obesity and CVD risk. There is a need to differentiate between types of SBBs when evaluating the CVD risk associated with screen behaviors in children. TRIAL REGISTRATION: International Standard Randomized Controlled Trial: ISRCTN83725066; Australian New Zealand Clinical Trials Registry: ACTRN12609000715279.
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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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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.