144 resultados para Attributable Mortality


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Background Studies of mid-aged adults provide evidence of a relationship between sitting-time and all-cause mortality, but evidence in older adults is limited. The aim is to examine the relationship between total sitting-time and all-cause mortality in older women. Methods The prospective cohort design involved 6656 participants in the Australian Longitudinal Study on Women's Health who were followed for up to 9 years (2002, age 76–81, to 2011, age 85–90). Self-reported total sitting-time was linked to all-cause mortality data from the National Death Index from 2002 to 2011. Cox proportional hazard models were used to examine the relationship between sitting-time and all-cause mortality, with adjustment for potential sociodemographic, behavioural and health confounders. Results There were 2003 (30.1%) deaths during a median follow-up of 6 years. Compared with participants who sat <4 h/day, those who sat 8–11 h/day had a 1.45 times higher risk of death and those who sat ≥11 h/day had a 1.65 times higher risk of death. These risks remained after adding sociodemographic and behavioural covariates, but were attenuated after adjustment for health covariates. A significant interaction (p=0.02) was found between sitting-time and physical activity (PA), with increased mortality risk for prolonged sitting only among participants not meeting PA guidelines (HR for sitting ≥8 h/day: 1.31, 95% CI 1.07 to 1.61); HR for sitting ≥11 h/day: 1.47, CI 1.15 to 1.93). Conclusions Prolonged sitting-time was positively associated with all-cause mortality. Women who reported sitting for more than 8 h/day and did not meet PA guidelines had an increased risk of dying within the next 9 years.

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Background Recent estimates suggest that high body mass index (BMI), smoking, high blood pressure (BP) and physical inactivity are leading risk factors for the overall burden of disease in Australia. The aim was to examine the population attributable risk (PAR) of heart disease for each of these risk factors, across the adult lifespan in Australian women. Methods PARs were estimated using relative risks (RRs) for each of the four risk factors, as used in the Global Burden of Disease Study, and prevalence estimates from the Australian Longitudinal Study on Women's Health, in 15 age groups from 22–27 (N=9608) to 85–90 (N=3901). Results RRs and prevalence estimates varied across the lifespan. RRs ranged from 6.15 for smoking in the younger women to 1.20 for high BMI and high BP in the older women. Prevalence of risk exposure ranged from 2% for high BP in the younger women to 79% for high BMI in mid-age women. In young adult women up to age 30, the highest population risk was attributed to smoking. From age 31 to 90, PARs were highest for physical inactivity. Conclusions From about age 30, the population risk of heart disease attributable to inactivity outweighs that of other risk factors, including high BMI. Programmes for the promotion and maintenance of physical activity deserve to be a much higher public health priority for women than they are now, across the adult lifespan.

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Background Studies investigating the relationship between malnutrition and post-discharge mortality following acute hip fracture yield conflicting results. This study aimed to determine whether malnutrition independently predicted 12-month post-fracture mortality after adjusting for clinically relevant covariates. Methods An ethics approved, prospective, consecutive audit was undertaken for all surgically treated hip fracture inpatients admitted to a dedicated orthogeriatric unit (November 2010–October 2011). The 12-month mortality data were obtained by a dual search of the mortality registry and Queensland Health database. Malnutrition was evaluated using the Subjective Global Assessment. Demographic (age, gender, admission residence) and clinical covariates included fracture type, time to surgery, anaesthesia type, type of surgery, post-surgery time to mobilize and post-operative complications (delirium, pulmonary and deep vein thrombosis, cardiac complications, infections). The Charlson Comorbidity Index was retrospectively applied. All diagnoses were confirmed by the treating orthogeriatrician. Results A total of 322 of 346 patients were available for audit. Increased age (P = 0.004), admission from residential care (P < 0.001), Charlson Comorbidity Index (P = 0.007), malnutrition (P < 0.001), time to mobilize >48 h (P < 0.001), delirium (P = 0.003), pulmonary embolism (P = 0.029) and cardiovascular complication (P = 0.04) were associated with 12-month mortality. Logistic regression analysis demonstrated that malnutrition (odds ratio (OR) 2.4 (95% confidence interval (CI) 1.3–4.7, P = 0.007)), in addition to admission from residential care (OR 2.6 (95% CI 1.3–5.3, P = 0.005)) and pulmonary embolism (OR 11.0 (95% CI 1.5–78.7, P = 0.017)), independently predicted 12-month mortality. Conclusions Findings substantiate malnutrition as an independent predictor of 12-month mortality in a representative sample of hip fracture inpatients. Effective strategies to identify and treat malnutrition in hip fracture should be prioritized.

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OBJECTIVE: Lower limb amputation is often associated with a high risk of early post-operative mortality. Mortality rates are also increasingly being put forward as a possible benchmark for surgical performance. The primary aim of this systematic review is to investigate early post-operative mortality following a major lower limb amputation in population/regional based studies, and reported factors that might influence these mortality outcomes. METHODS: Embase, PubMed, Cinahl and Psycinfo were searched for publications in any language on 30 day or in hospital mortality after major lower limb amputation in population/regional based studies. PRISMA guidelines were followed. A self developed checklist was used to assess quality and susceptibility to bias. Summary data were extracted for the percentage of the population who died; pooling of quantitative results was not possible because of methodological differences between studies. RESULTS: Of the 9,082 publications identified, results were included from 21. The percentage of the population undergoing amputation who died within 30 days ranged from 7% to 22%, the in hospital equivalent was 4-20%. Transfemoral amputation and older age were found to have a higher proportion of early post-operative mortality, compared with transtibial and younger age, respectively. Other patient factors or surgical treatment choices related to increased early post-operative mortality varied between studies. CONCLUSIONS: Early post-operative mortality rates vary from 4% to 22%. There are very limited data presented for patient related factors (age, comorbidities) that influence mortality. Even less is known about factors related to surgical treatment choices, being limited to amputation level. More information is needed to allow comparison across studies or for any benchmarking of acceptable mortality rates. Agreement is needed on key factors to be reported.

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Objective To determine mortality rates after a first lower limb amputation and explore the rates for different subpopulations. Methods Retrospective cohort study of all people who underwent a first amputation at or proximal to transtibial level, in an area of 1.7 million people. Analysis with Kaplan-Meier curves and Log Rank tests for univariate associations of psycho-social and health variables. Logistic regression for odds of death at 30-days, 1-year and 5-years. Results 299 people were included. Median time to death was 20.3 months (95%CI: 13.1; 27.5). 30-day mortality = 22%; odds of death 2.3 times higher in people with history of cerebrovascular disease (95%CI: 1.2; 4.7, P = 0.016). 1 year mortality = 44%; odds of death 3.5 times higher for people with renal disease (95%CI: 1.8; 7.0, P < 0.001). 5-years mortality = 77%; odds of death 5.4 times higher for people with renal disease (95%CI: 1.8; 16.0,P = 0.003). Variation in mortality rates was most apparent in different age groups; people 75–84 years having better short term outcomes than those younger and older. Conclusions Mortality rates demonstrated the frailty of this population, with almost one quarter of people dying within 30-days, and almost half at 1 year. People with cerebrovascular had higher odds of death at 30 days, and those with renal disease and 1 and 5 years, respectively.

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Background The Global Burden of Diseases (GBD), Injuries, and Risk Factors study used the disability-adjusted life year (DALY) to quantify the burden of diseases, injuries, and risk factors. This paper provides an overview of injury estimates from the 2013 update of GBD, with detailed information on incidence, mortality, DALYs and rates of change from 1990 to 2013 for 26 causes of injury, globally, by region and by country. Methods Injury mortality was estimated using the extensive GBD mortality database, corrections for ill-defined cause of death and the cause of death ensemble modelling tool. Morbidity estimation was based on inpatient and outpatient data sets, 26 cause-of-injury and 47 nature-of-injury categories, and seven follow-up studies with patient-reported long-term outcome measures. Results In 2013, 973 million (uncertainty interval (UI) 942 to 993) people sustained injuries that warranted some type of healthcare and 4.8 million (UI 4.5 to 5.1) people died from injuries. Between 1990 and 2013 the global age-standardised injury DALY rate decreased by 31% (UI 26% to 35%). The rate of decline in DALY rates was significant for 22 cause-of-injury categories, including all the major injuries. Conclusions Injuries continue to be an important cause of morbidity and mortality in the developed and developing world. The decline in rates for almost all injuries is so prominent that it warrants a general statement that the world is becoming a safer place to live in. However, the patterns vary widely by cause, age, sex, region and time and there are still large improvements that need to be made.

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Background Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. Methods We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. Results The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). Conclusions We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.

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Globally, the main contributors to morbidity and mortality are chronic conditions, including cardiovascular disease and diabetes. Chronic disease is costly and partially avoidable, with around 60% of deaths and nearly 50% of the global disease burden attributable to these conditions. By 2020, chronic illnesses will likely be the leading cause of disability worldwide. Existing healthcare systems that focus on acute episodic health conditions, both national and international, cannot address the worldwide transition to chronic illness; nor are they appropriate for the ongoing care and management of those already dealing with chronic diseases. As such, chronic disease management requires integrated approaches that incorporate interventions targeted at both individuals and populations, and emphasise the shared risk factors of different conditions. International and Australian strategic planning documents articulate similar elements to manage chronic disease, including the need for aligning sectoral policies for health, forming partnerships, and engaging communities in decision-making. Infectious diseases are also a common and significant contributor to ill health throughout the world. In many countries, this impact has been minimised by the combined efforts of preventative health measures and improved treatment methods. However, in low-income countries, infectious diseases remain the dominant cause of death and disability. The World Health Organization (WHO) estimates that infectious diseases (including respiratory infections) still account for around 23% (or around 14 million) of all deaths each year, and result in over 4.6 billion episodes of diarrhoeal disease and 243 million cases of malaria each year (Lozano et al. 2012, WHO 2009). In addition to the high level of mortality, infectious diseases disable many hundreds of millions of people each year, mainly in developing countries, with the global burden of disease from infectious diseases estimated to be around 300 million DALYs (disability-adjusted life years) (WHO 2012). The aim of this chapter is to outline the impact that infectious diseases and chronic diseases have on the health of the community, describe the public health strategies used to reduce the burden of those diseases, and discuss the historic and emerging disease risks to public health. This chapter examines the comprehensive approaches implemented to prevent both chronic and infectious diseases, and to manage and care for communities with these conditions.

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Context Evidence from prospective cohort studies has suggested that high volumes of reported daily sitting time is associated with mortality.1 ,2 However, not all have observed the same association.3 Fidgeting (small movements associated with nervousness or impatience), could provide additional energy expenditure when sitting, although the relationship with sitting and health outcomes had yet to be examined. Hagger-Johnson et al examined data from nearly 13 000 women to determine whether fidgeting modified the association between sitting time and mortality. Methods This study featured prospective data from 12 778 participants (aged 37–78 years) in the Women's Cohort Study (UK). Average daily sitting time was reported for weekdays and weekend days, and combined …