scholarly journals The impact of smoking and obesity on disability-free life expectancy in older Australians

2020 ◽  
Author(s):  
Andrew Kingston ◽  
Julie Byles ◽  
Kim Kiely ◽  
Kaarin Anstey ◽  
Carol Jagger
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Life Expectancy ◽  
Mortality Data ◽  
Obese Women ◽  
Mobility Disability ◽  
Total Life Expectancy ◽  
Disability Free Life Expectancy ◽  
Adl Disability ◽  
The Impact

Abstract Background Smoking and obesity are two modifiable risk factors for disability. We examine the impact of smoking and obesity on disability-free life expectancy (DFLE) at older ages, using two levels of disability. Methods We used the DYNOPTA dataset, derived by harmonizing and pooling risk factors and disability outcomes from five Australian longitudinal ageing studies. We defined mobility disability as inability to walk one kilometre, and more severe (ADL) disability by the inability to dress or bathe. Mortality data for the analytic sample (N=20,401; 81.2% women) were obtained from Government Records via data linkage. We estimated sex-specific total life expectancy, DFLE, and years spent with disability by Interpolated Markov Chain (IMaCh) software for each combination of smoking (never vs ever), obesity (Body Mass Index ≥30 vs 18.5-<30), and education (left school age 14 or younger vs age 15 or older). Results Compared to those without either risk factor, high educated non-obese smokers at age 65 lived shorter lives (men and women: 2.5 years) and fewer years free of mobility disability (men: 2.1 years; women: 2.0 years), with similar results for ADL disability. Obesity had the largest effect on mobility disability in women; high educated obese non-smoking women lived 1.3 years less than non-smoking, not obese women but had 5.1 years fewer free of mobility disability and 3.2 fewer free of ADL disability. Differences between risk factor groups were similar for the low educated. Conclusions Our findings suggest eliminating obesity would lead to an absolute reduction of disability, particularly in women.

scholarly journals A patient-level model to estimate lifetime health outcomes of patients with type 1 diabetes

2020 ◽  
Author(s):  
An Tran-Duy ◽  
Josh Knight ◽  
Andrew J Palmer ◽  
Dennis Petrie ◽  
Tom WC Lung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 1 Diabetes ◽  
Risk Factor ◽  
Life Expectancy ◽  
Health Outcomes ◽  
Economic Evaluations ◽  
Internal Validation ◽  
Patient Level ◽  
The Impact

<b>OBJECTIVE </b> <p>To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>Data for model development were obtained from the <a>Swedish National Diabetes Register</a>. We derived parametric proportional hazards models predicting absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.</p> <p><b>RESULTS </b></p> <p>The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was approximately 13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for approximately 40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycaemia and hyperglycaemia, and lowering HbA1c in reducing the risk of complications and death.</p> <p><b>CONCLUSIONS </b></p> Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes, and project events occurring over patients’ lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.

scholarly journals A patient-level model to estimate lifetime health outcomes of patients with type 1 diabetes

2020 ◽  
Author(s):  
An Tran-Duy ◽  
Josh Knight ◽  
Andrew J Palmer ◽  
Dennis Petrie ◽  
Tom WC Lung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 1 Diabetes ◽  
Risk Factor ◽  
Life Expectancy ◽  
Health Outcomes ◽  
Economic Evaluations ◽  
Internal Validation ◽  
Patient Level ◽  
The Impact

<b>OBJECTIVE </b> <p>To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>Data for model development were obtained from the <a>Swedish National Diabetes Register</a>. We derived parametric proportional hazards models predicting absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.</p> <p><b>RESULTS </b></p> <p>The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was approximately 13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for approximately 40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycaemia and hyperglycaemia, and lowering HbA1c in reducing the risk of complications and death.</p> <p><b>CONCLUSIONS </b></p> Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes, and project events occurring over patients’ lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.

scholarly journals Estimating the burden of cardiovascular risk in community dwellers over 40 years old in South Africa, Kenya, Burkina Faso and Ghana

2021 ◽  
Vol 6 (1) ◽  
pp. e003499
Author(s):  
Ryan G Wagner ◽  
Nigel J Crowther ◽  
Lisa K Micklesfield ◽  
Palwende Romauld Boua ◽  
Engelbert A Nonterah ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
South African ◽  
Sub Saharan Africa ◽  
African Countries ◽  
Cvd Risk ◽  
Genomic Studies ◽  
Sub Saharan ◽  
Context Specific ◽  
The Impact

IntroductionCardiovascular disease (CVD) risk factors are increasing in sub-Saharan Africa. The impact of these risk factors on future CVD outcomes and burden is poorly understood. We examined the magnitude of modifiable risk factors, estimated future CVD risk and compared results between three commonly used 10-year CVD risk factor algorithms and their variants in four African countries.MethodsIn the Africa-Wits-INDEPTH partnership for Genomic studies (the AWI-Gen Study), 10 349 randomly sampled individuals aged 40–60 years from six sites participated in a survey, with blood pressure, blood glucose and lipid levels measured. Using these data, 10-year CVD risk estimates using Framingham, Globorisk and WHO-CVD and their office-based variants were generated. Differences in future CVD risk and results by algorithm are described using kappa and coefficients to examine agreement and correlations, respectively.ResultsThe 10-year CVD risk across all participants in all sites varied from 2.6% (95% CI: 1.6% to 4.1%) using the WHO-CVD lab algorithm to 6.5% (95% CI: 3.7% to 11.4%) using the Framingham office algorithm, with substantial differences in risk between sites. The highest risk was in South African settings (in urban Soweto: 8.9% (IQR: 5.3–15.3)). Agreement between algorithms was low to moderate (kappa from 0.03 to 0.55) and correlations ranged between 0.28 and 0.70. Depending on the algorithm used, those at high risk (defined as risk of 10-year CVD event >20%) who were under treatment for a modifiable risk factor ranged from 19.2% to 33.9%, with substantial variation by both sex and site.ConclusionThe African sites in this study are at different stages of an ongoing epidemiological transition as evidenced by both risk factor levels and estimated 10-year CVD risk. There is low correlation and disparate levels of population risk, predicted by different risk algorithms, within sites. Validating existing risk algorithms or designing context-specific 10-year CVD risk algorithms is essential for accurately defining population risk and targeting national policies and individual CVD treatment on the African continent.

scholarly journals The decomposition of life expectancy for age and cause of death in Tuscany, Italy

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
N Nante ◽  
L Kundisova ◽  
F Gori ◽  
A Martini ◽  
F Battisti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Causes Of Death ◽  
National Level ◽  
Age Groups ◽  
Resistant Bacteria ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Icd 10 ◽  
Reduction Of Mortality ◽  
The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, &lt;1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

Abstract T P136: Potential Contributors to the Declining Impact of Stroke Risk Factors with Age: Implications for Stroke Epidemiology in the Elderly

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
George Howard ◽  
Mary Cushman ◽  
Maciej Banach ◽  
Brett M Kissela ◽  
David C Goff ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Stroke Risk ◽  
Multivariable Analysis ◽  
The Elderly ◽  
Stroke Risk Factors ◽  
Age Related ◽  
Increased Risk ◽  
The Impact ◽  
Age Related Changes

Purpose: The importance of stroke research in the elderly is increasing as America is “graying.” For most risk factors for most diseases (including stroke), the magnitude of association with incident events decreases at older ages. Potential changes in the impact of risk factors could be a “true” effect, or could be due to methodological issues such as age-related changes in residual confounding. Methods: REGARDS followed 27,748 stroke-free participants age 45 and over for an average of 5.3 years, during which 715 incident strokes occurred. The association of the “Framingham” risk factors (hypertension [HTN], diabetes, smoking, AFib, LVH and heart disease) with incident stroke risk was assessed in age strata of 45-64 (Young), 65-74 (Middle), and 75+ (Old). For those with and without an “index” risk factor (e.g., HTN), the average number of “other” risk factors was calculated. Results: With the exception of AFib, there was a monotonic decrease in the magnitude of the impact across the age strata, with HTN, diabetes, smoking and LVH even becoming non-significant in the elderly (Figure 1). However, for most factors, the increasing prevalence of other risk factors with age impacts primarily those with the index risk factor absent (Figure 2, example HTN as the “index” risk factor). Discussion: The impact of stroke risk factors substantially declined at older ages. However, this decrease is partially attributable to increases in the prevalence of other risk factors among those without the index risk factor, as there was little change in the prevalence of other risk factors in those with the index risk factor. Hence, the impact of the index risk factor is attenuated by increased risk in the comparison group. If this phenomenon is active with latent risk factors, estimates from multivariable analysis will also decrease with age. A deeper understanding of age-related changes in the impact of risk factors is needed.

Abstract 141: Impact of an Aggressive Medical Management Protocol on Early Risk Factor Measures in the Stenting and Aggressive Medical Management for Preventing Recurrent stroke in Intracranial Stenosis (SAMMPRIS) Trial

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Tanya N Turan ◽  
Azhar Nizam ◽  
Michael J Lynn ◽  
Colin P Derdeyn ◽  
David Fiorella ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Medical Management ◽  
Intracranial Stenosis ◽  
Patient Specific ◽  
Early Risk ◽  
Aggressive Medical Management ◽  
The Impact ◽  
Early Risk Factor

Purpose: SAMMPRIS is the first stroke prevention trial to include protocol-driven aggressive management of multiple vascular risk factors. We sought to determine the impact of this protocol on early risk factor control in the trial. Materials and Methods: SAMMPRIS randomized 451 patients with symptomatic 70%-99% intracranial stenosis to aggressive medical management or stenting plus aggressive medical management at 50 USA sites. For the primary risk factor targets (SBP < 140 mm/Hg (<130 if diabetic) and LDL < 70 mg/dL), the study neurologists follow medication titration algorithms and risk factor medications are provided to the patients. Secondary risk factors (diabetes, non-HDL, weight, exercise, and smoking cessation) are managed with assistance from the patient’s primary care physician and a lifestyle modification program (provided). Sites receive patient-specific recommendations and feedback to improve performance. Follow-up continues, but the 30-day data are final. We compared baseline to 30-day risk factor measures using paired t-tests for means and McNemar tests for percentages. Results: The differences in risk factor measures between baseline and 30 days are shown in Table 1. Conclusions: The SAMMPRIS protocol resulted in major improvements in controlling most risk factors within 30 days of enrollment, which may have contributed to the lower than expected 30 day stroke rate in the medical group (5.8%). However, the durability of this approach over time will be determined by additional follow-up.

Abstract 183: Depressive Symptoms and Incident Stroke in Black and White Participants in the REGARDS Study

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Audrey L Austin ◽  
Michael G Crowe ◽  
Martha R Crowther ◽  
Virginia J Howard ◽  
Abraham J Letter ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Depressive Symptoms ◽  
Racial Differences ◽  
Stroke Risk ◽  
Depression Scale ◽  
Stroke Incidence ◽  
Blacks And Whites ◽  
The Impact

Background and Purpose: Research suggests that depression may contribute to stroke risk independent of other known risk factors. Most studies examining the impact of depression on stroke have been conducted with predominantly white cohorts, though blacks are known to have higher stroke incidence than whites. The purpose of this study was to examine depressive symptoms as a risk factor for incident stroke in blacks and whites, and determine whether depressive symptomatology was differentially predictive of stroke among blacks and whites. Methods: The REasons for Geographic and Racial Differences in Stroke (REGARDS), is a national, population-based longitudinal study designed to examine risk factors associated with black-white and regional disparities in stroke incidence. Among 30,239 participants (42% black) accrued from 2003-2007, excluding those lacking follow-up or data on depressive symptoms, 27,557 were stroke-free at baseline. As of the January 2011 data closure, over an average follow-up of 4.6 years, 548 incident stroke cases were verified by study physicians based on medical records review. The association between baseline depressive symptoms (assessed via the Center for Epidemiological Studies Depression scale, 4-item version) and incident stroke was analyzed with Cox proportional hazards models adjusted for demographic factors (age, race, and sex), stroke risk factors (hypertension, diabetes, smoking, atrial fibrillation, and history of heart disease), and social factors (education, income, and social network). Results: For the total sample, depressive symptoms were predictive of incident stroke. The association between depressive symptoms and stroke did not differ significantly based on race (Wald X 2 = 2.38, p = .1229). However, race-stratified analyses indicated that the association between depressive symptoms and stroke was stronger among whites and non-significant among blacks. Conclusions: Depressive symptoms were an independent risk factor for incident stroke among a national sample of blacks and whites. These findings suggest that assessment of depressive symptoms may warrant inclusion in stroke risk scales. The potential for a stronger association in whites than blacks requires further study.

scholarly journals Trends in Avoidable Mortality in Lithuania During 2001–2008 and Their Impact on Life Expectancy

Medicina ◽  
2011 ◽  
Vol 47 (9) ◽  
pp. 504 ◽  
Author(s):  
Vilius Grabauskas ◽  
Aldona Gaižauskienė ◽  
Skirmantė Sauliūnė ◽  
Rasa Mišeikytė
Keyword(s):  
Life Expectancy ◽  
Mortality Data ◽  
Avoidable Mortality ◽  
Average Life Expectancy ◽  
Mortality Trends ◽  
Annual Percent Change ◽  
Increasing Trend ◽  
Causes Of Deaths ◽  
Changes Over Time ◽  
The Impact

The process of the restructuring of health care system in Lithuania demonstrates the need to continue the monitoring of changes in avoidable mortality. Objective. To assess the level of avoidable mortality as well as its changes over time in Lithuania during 2001–2008 and to define the impact of avoidable mortality on life expectancy. Material and Methods. The mortality data were taken from the Lithuanian Department of Statistics. Twelve avoidable causes of deaths (treatable and preventable) were analyzed. Mortality trends were assessed by computing the average annual percent change (AAPC). The shortening of average life expectancy was computed from survival tables. Results. During the period 2001–2008, the avoidable mortality was increasing more significantly (AAPC 3.0%, P<0.05) than the overall mortality (AAPC 1.7%, P<0.05) in the population aged 5–64 years. The increasing trend was mainly determined by mortality from preventable diseases (AAPC 4.6%, P<0.05). The avoidable causes of death reduced the life expectancy by 1.77 years (preventable by 1.12 and treatable by 0.63 years). Diversity in trends in mortality of different avoidable causes was disclosed. A declining trend in mortality caused by chronic rheumatic heart disease and lung cancer was observed for males (AAPC –22.6% and –2.1%, respectively; P<0.05). However, the mortality caused by liver cirrhosis was increasing for both genders (AAPC 16.1% for males and 17.6% for females, P<0.01) and that caused by tuberculosis – only for females (AAPC 7.8%, P<0.05). Conclusions. An increasing trend in avoidable mortality was observed. Deaths caused by the diseases that could have been prevented had the greatest impact on the increasing mortality and decreasing life expectancy.

Increased pitch velocity and workload are common risk factors for ulnar collateral ligament injury in baseball players: a systematic review

2018 ◽  
Vol 4 (1) ◽  
pp. 41-47
Author(s):  
Ryan P Coughlin ◽  
Yung Lee ◽  
Nolan S Horner ◽  
Nicole Simunovic ◽  
Edwin R Cadet ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Injury Prevention ◽  
Ulnar Collateral Ligament ◽  
Quality Data ◽  
Sufficient Evidence ◽  
Collateral Ligament ◽  
Level Of Evidence ◽  
Baseball Players ◽  
The Impact

ImportanceUlnar collateral ligament (UCL) injuries commonly occur in baseball players. Strategies for injury prevention have long been accepted without clinical data informing which risk factors lead to serious injury.ObjectiveThe objective of this study was to systematically review the impact of various pitching-related risk factors for UCL injury in baseball players from all levels of play.Evidence reviewThe electronic databases MEDLINE, EMBASE and PubMed were systematically searched until 4 March 2018, and pertinent data were abstracted by two independent reviewers. Search terms included ‘ulnar collateral ligament’, ‘medial ulnar collateral ligament’, ‘Tommy John’, ‘risk’ and ‘association’. Inclusion criteria were English-language studies, level of evidence I–IV and studies reporting risk factors for UCL injury of the elbow in baseball players. Study quality was assessed using the methodological index for non-randomised studies (MINORS) criteria. The results are presented in a narrative summary.FindingsPitching practices (workload and pitch characteristics) were reported in 9/15 studies. Specifically, three of four studies (n=1810) reported increased pitch workload as a risk factor for native UCL injury (p<0.001 to 0.02). The most common pitch characteristic reported was pitch velocity with four of five studies showing increased velocity being significantly associated with native UCL injury (p<0.01 to 0.02). Biomechanical risk factors reported were increased humeral retrotorsion (two studies; n=324), poor lower extremity and trunk balance (one study; n=42) and loss of total arc of shoulder motion (two studies; n=118), all significantly associated with UCL injury (p<0.0001 to 0.05). One of three studies assessing pitch workload as a risk factor for re-rupture of UCL reconstruction found a significant association (p<0.01).Conclusions and relevancePitching practices, reflected by increased pitch workload and velocity, were most commonly associated with UCL injury; however, the definition of workload (number of pitches per game, inning or season) was inconsistently reported. Biomechanical risk factors were less commonly reported and lack sufficient evidence to recommend preventative strategies. More quality data is needed to refine the current recommendations for injury prevention in baseball players.Level of evidenceIII.

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