scholarly journals Socio-economic inequalities in life expectancy of older adults with and without multimorbidity: a record linkage study of 1.1 million people in England

2019 ◽  
Vol 48 (4) ◽  
pp. 1340-1351 ◽  
Author(s):  
Mei Sum Chan ◽  
Ardo van den Hout ◽  
Mar Pujades-Rodriguez ◽  
Melvyn Mark Jones ◽  
Fiona E Matthews ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Smoking Prevalence ◽  
Age Of Onset ◽  
Smoking Status ◽  
Linkage Study ◽  
Area Deprivation ◽  
Healthy Life ◽  
Unequal Rates ◽  
State Models ◽  
Never Smokers

Abstract Background Age of onset of multimorbidity and its prevalence are well documented. However, its contribution to inequalities in life expectancy has yet to be quantified. Methods A cohort of 1.1 million English people aged 45 and older were followed up from 2001 to 2010. Multimorbidity was defined as having 2 or more of 30 major chronic diseases. Multi-state models were used to estimate years spent healthy and with multimorbidity, stratified by sex, smoking status and quintiles of small-area deprivation. Results Unequal rates of multimorbidity onset and subsequent survival contributed to higher life expectancy at age 65 for the least (Q1) compared with most (Q5) deprived: there was a 2-year gap in healthy life expectancy for men [Q1: 7.7 years (95% confidence interval: 6.4–8.5) vs Q5: 5.4 (4.4–6.0)] and a 3-year gap for women [Q1: 8.6 (7.5–9.4) vs Q5: 5.9 (4.8–6.4)]; a 1-year gap in life expectancy with multimorbidity for men [Q1: 10.4 (9.9–11.2) vs Q5: 9.1 (8.7–9.6)] but none for women [Q1: 11.6 (11.1–12.4) vs Q5: 11.5 (11.1–12.2)]. Inequalities were attenuated but not fully attributable to socio-economic differences in smoking prevalence: multimorbidity onset was latest for never smokers and subsequent survival was longer for never and ex smokers. Conclusions The association between social disadvantage and multimorbidity is complex. By quantifying socio-demographic and smoking-related contributions to multimorbidity onset and subsequent survival, we provide evidence for more equitable allocation of prevention and health-care resources to meet local needs.

scholarly journals 377Smoking, blood pressure, and body mass index to estimate healthy life expectancy: NIPPON DATA90

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Rumi Tsukinoki ◽  
Takehito Hayakawa ◽  
Aya Kadota ◽  
Yoshitaka Murakami ◽  
Katsuyuki Miura ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Life Expectancy ◽  
Life Table ◽  
Body Mass ◽  
Smoking Status ◽  
Healthy Life Expectancy ◽  
Ageing Society ◽  
Healthy Life ◽  
Multistate Life Table

Abstract Background Healthy life expectancy (HLE) is an important measure of an ageing society. We estimated HLE based on combinations of smoking, blood pressure (BP), and body mass index (BMI) in the Japanese population using a multistate life table. Methods A nationwide cohort study of Japan was performed using NIPPON DATA90 (N = 6,676) with the Katz Activities of Daily Living Index as the HLE endpoint. Combinations of smoking (non-smokers and smokers), BP (2018 ESC/ESH Guidelines classification), and BMI (underweight, normal, and overweight) were developed, and the group-specific HLEs were calculated using a multistate life table. Results At age 65, smokers had shorter HLE than non-smokers for all BMI and BP groups. The HLE of men who were overweight, hypertensive (Grade 2 or 3), and smokers was 14.05 years (95% confidence interval: 15.77-21.36); in contrast, the HLE of men who were normal weight, normotensive, and non-smokers was 19.04 years (16.46-21.61). Among all BMI and smoking status groups, HLE decreased linearly as BP increased regardless of sex. The HLE distribution showed a slight inverted U-shape as BMI increased in both sexes. Conclusions This study showed that HLE at age 65 was considerably shorter in smokers and individuals with higher BP. Furthermore, both underweight and overweight had modest effects on HLE at age 65. Key messages HLE was considerably shorter in smokers and individuals with higher BP. In addition, both underweight and overweight had modest effects on HLE.

scholarly journals Cigarette Smoking Status, Cigarette Exposure, and Duration of Abstinence Predicting Incident Dementia and Death: A Multistate Model Approach

2021 ◽  
Vol 80 (3) ◽  
pp. 1013-1023
Author(s):  
Adrienne L. Johnson ◽  
Naomi C. Nystrom ◽  
Megan E. Piper ◽  
Jessica Cook ◽  
Derek L. Norton ◽  
...  
Keyword(s):  
Cigarette Smoking ◽  
Competing Risks ◽  
Smoking Status ◽  
Risk Of Death ◽  
Incident Dementia ◽  
Smoking Exposure ◽  
Increased Risk ◽  
State Models ◽  
Never Smokers ◽  
The Impact

Background: To fully characterize the risk for dementia associated with cigarette smoking, studies must consider competing risks that hinder the observation of dementia or modify the chance that dementia occurs (i.e., death). Extant research examining the competing risks fails to account for the occurrence of death following dementia, limiting our understanding of the relation between smoking and dementia. Objective: Examine the impact of smoking status, lifetime smoking exposure, and duration of abstinence on incident dementia, death following dementia, and death without dementia. Methods: Multi-state models estimated hazard ratios (HR) for 95% confidence interval (CI) of 10,681 cognitively healthy adults for transition from baseline to dementia, baseline to death, and dementia to death based on smoking status, lifetime cigarette exposure, and abstinence duration. Results: Compared to never smokers, current smokers had increased risk of dementia (HR = 1.66; 95% CI 1.18– 2.32; p = 0.004), and death from baseline (HR = 2.98; 95% CI 2.24– 3.98; p < 0.001) and incident dementia (HR = 1.88; 95% CI 1.08– 3.27; p = 0.03). Pack years increased risk of death from baseline (HR = 1.01; 95% CI 1.00– 1.01; p < 0.001), but not dementia risk (HR = 1.00; 95% CI 1.00– 1.00; p = 0.78) or death following dementia (HR = 1.01; 95% CI 1.00– 1.01; p = 0.05). Recent quitters (quit < 10 years), compared to never smokers, had increased risk of death after baseline (HR = 2.31; 95% CI 1.55– 3.43; p < 0.001), but not dementia (HR = 1.17; 95% CI 0.73– 1.88; p = 0.52) or death following dementia (HR = 1.01; 95% CI 0.42– 2.41; p = 0.99). Conclusion: Current smoking increases the risk for dementia and death, but dementia is better attributed to smoking recency than lifetime exposure. Smoking cessation at any age might reduce these risks for cognitively healthy individuals.

scholarly journals Transitions in Smoking among Adults Newly Purchasing the JUUL System

2021 ◽  
Vol 45 (3) ◽  
pp. 546-562
Author(s):  
Shivaani Prakash ◽  
Yingying Xu ◽  
Nicholas I. Goldenson ◽  
Rasmus Wissmann ◽  
Robyn Gougelet ◽  
...  
Keyword(s):  
Smoking Prevalence ◽  
Smoking Status ◽  
Health Impact ◽  
Adult Age ◽  
Sample Composition ◽  
Former Smokers ◽  
Never Smokers ◽  
One Year ◽  
First Time

Objectives: In this study, we prospectively assessed changes in smoking a year after US adults' first-time purchase of a JUUL Starter Kit (JSK). Methods: Descriptive analyses assessed transitions in smoking status at 12 months among adult (age ≥21) JSK purchasers providing baseline and 12-month follow-up data (N = 27,164 [49.0% of baseline]), stratified by baseline smoking status. Baseline regular use of other ENDS was also considered. Results: Purchasers included baseline past 30-day smokers (65.2%), former smokers (12.0%), and never smokers (9.7%); over 90% were ever-smokers. One year later, the majority (58%) of those smoking at baseline reported no longer smoking. Former smokers or never smokers who were smoking at 12 months represented less than 2% of respondents. Former and current smokers who were regularly using other ENDS at baseline were less likely to report smoking at 12 months. Conclusions: Past 30-day smoking prevalence in a large longitudinal study of first-time JSK purchasers fell by more than half over 12 months. Analyzing the sample composition at purchase and transitions within subgroups defined by smoking status allows for a detailed understanding to help inform assessments of the population health impact of ENDS.

scholarly journals Evidencing the gap between health expectancy and life expectancy for ethnic groups in Scotland.

2020 ◽  
Vol 7 (1) ◽  
pp. 135-162 ◽  
Author(s):  
Genevieve I Cezard
Keyword(s):  
Life Expectancy ◽  
Ethnic Minorities ◽  
Linkage Study ◽  
Health Expectancy ◽  
Future Research ◽  
Healthy Life ◽  
Majority Population ◽  
Two Measures ◽  
Self Assessed Health ◽  
Sullivan Method

Background Recent evidence has shown that ethnic minorities live longer than the majority population in Scotland. This mortality advantage in ethnic minorities is not unique to Scotland. However, whether morbidity patterns by ethnicity align with mortality patterns by ethnicity is unknown. Thus, this study explores ethnic differences in health expectancies (HE) in Scotland and contrasts HE with life expectancy (LE) findings. Methods The Scottish Health and Ethnicity Linkage study anonymously links the Scottish Census 2001 for 4.6 million people to mortality records. The Scottish Census 2001 collected two measures of self-assessed health, self-declared ethnicity, age, and sex. Utilising the life tables used to calculate life expectancy by ethnicity and sex in Scotland, the Sullivan method was employed to calculate two measures of health expectancy (healthy life expectancy and disability-free life expectancy) by ethnicity and sex. 95% confidence intervals were calculated to detect significant differences compared to the majority White Scottish population, taken as reference. Results Longer health expectancies were found in males and females of Other White British, Other White, and Chinese origins as well as in Indian males compared to White Scottish populations. Any Mixed Background and Pakistani populations had the shortest healthy life expectancies. Patterns of health expectancy by ethnicity mostly aligned with patterns of life expectancy by ethnicity with the clear exception of the Pakistani population who showed among the longest life expectancies with the shortest health expectancies. Contrasting HE with LE findings, the number of years in an unhealthy state was greater in females than in males for each ethnic group. In relation to ethnicity, Pakistani and Indian populations had the highest number of years in an unhealthy state in Scotland. Pakistani females showed the strong-est disadvantage in this respect. Conclusion Pakistani populations had the shortest health expectancies contrasting with the longest life expectancies in Scotland. Future research should aim to understand why such a discrepancy occurs while policy makers ensure that fair and adapt-ed care is provided to offer better quality of life for the most vulnerable.

Smoking and treatment outcomes of neovascular age-related macular degeneration over 12 months

2019 ◽  
Vol 104 (7) ◽  
pp. 893-898
Author(s):  
Harshil Dharamdasani Detaram ◽  
Nichole Joachim ◽  
Gerald Liew ◽  
Kim Van Vu ◽  
George Burlutsky ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Treatment Outcomes ◽  
Age Of Onset ◽  
Smoking Status ◽  
Subretinal Fluid ◽  
Age Related Macular Degeneration ◽  
Age Related ◽  
Younger Age ◽  
Never Smokers ◽  
Endothelial Growth Factor

BackgroundTo assess the association of smoking with age of onset of neovascular age-related macular degeneration (nAMD), visual acuity (VA), central macular thickness (CMT) and the presence of fluid in patients with nAMD.Methods547 patients with nAMD were recruited from a tertiary eye clinic during 2012–2015; of these, 490 patients were followed up 12 months later. Clinical diagnosis of nAMD was confirmed by a retinal specialist. Smoking was determined from self-reported history as never, past or current. Age of onset was defined as date of first recorded diagnosis of nAMD in either eye or date of first anti-vascular endothelial growth factor injection. CMT and presence of fluid were recorded from spectral-domain optical coherence tomography images. VA was recorded as number of letters read at 3 m.ResultsAfter multivariable adjustment, current smokers developed nAMD at an average 5.5 years younger age than never smokers and 4.4 years younger age than past smokers (p<0.0001 and p=0.0008, respectively). At baseline, adjusted mean CMT was significantly higher in current compared with past smokers (259.2 µm vs 231.9 µm, respectively, p=0.04). Current smokers versus never smokers had greater odds of presence of subretinal fluid at 12-month follow-up: multivariable-adjusted OR 1.99 (95% CI 1.09 to 3.67). Smoking status was not significantly associated with VA over 12 months.ConclusionsCurrent smoking was associated with a younger age of nAMD onset and key treatment outcomes such as higher mean CMT and greater odds of subretinal fluid presence. These findings suggest that smoking cessation may benefit patients being treated for nAMD.

scholarly journals BMI and healthy life expectancy in old and very old women

2016 ◽  
Vol 116 (4) ◽  
pp. 692-699 ◽  
Author(s):  
L. Leigh ◽  
J. E. Byles ◽  
C. Jagger
Keyword(s):  
Weight Loss ◽  
Life Expectancy ◽  
Good Health ◽  
Normal Weight ◽  
Healthy Life Expectancy ◽  
Obese Women ◽  
Healthy Life ◽  
Conflicting Evidence ◽  
Total Life Expectancy ◽  
State Models

AbstractThere is conflicting evidence for the effect of BMI on mortality at older ages, and little information on its effect on healthy life expectancy (HLE). Longitudinal data were from the 1921–1926 cohort of the Australian Longitudinal Study on Women’s Health (n 11 119), over 18 years of follow-up. Self-rated health status was measured at each survey, and BMI was measured at baseline. Multi-state models were fitted to estimate the effect of BMI on total life expectancy (TLE) and HLE. Compared with women of normal weight, overweight women at the age of 75 years had similar TLE but fewer years healthy (−0·79; 95 % CI −1·21, −0·37) and more years unhealthy (0·99; 95 % CI 0·56, 1·42). Obese women at the age of 75 years lived fewer years in total than normal-weight women (−1·09; 95 % CI −1·77, −0·41), and had more unhealthy years (1·46; 95 % CI 0·97, 1·95 years). Underweight women had the lowest TLE and the fewest years of healthy life. Women should aim to enter old age at a normal weight and in good health, as the slight benefit on mortality of being overweight is offset by spending fewer years healthy. All outcomes were better for those who began in good health. The relationship between weight and HLE has important implications for nutrition for older people, particularly maintenance of lean body mass and prevention of obesity. The benefit of weight loss in obese older women remains unclear, but we support the recommendation that weight-loss advice be individualised, as any benefits may not outweigh the risks in healthy obese older adults.

scholarly journals The effect of smoking on cumulative damage in systemic lupus erythematosus: An incident cohort study

Lupus ◽  
2021 ◽  
pp. 096120332098860
Author(s):  
Trevor McKown ◽  
Maria Schletzbaum ◽  
Rachna Unnithan ◽  
Xing Wang ◽  
Nnenna Ezeh ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Median Time ◽  
Lupus Erythematosus ◽  
Smoking Status ◽  
Damage Index ◽  
Smoking History ◽  
Area Deprivation ◽  
Systemic Lupus ◽  
Never Smokers ◽  
Incident Cohort

Objectives To investigate the relationship between smoking history and pack-year exposure on the rate of end-organ damage in systemic lupus erythematosus (SLE). Methods The SLE incident cohort included patients who met American College of Rheumatology (ACR) 1997 or SLE International Collaborating Clinics (SLICC) 2012 SLE criteria and had rheumatology encounters at a US academic institution (2008–16). The primary outcome was median time to SLICC/ACR damage index (SLICC/ACR-DI) increase or death. Main explanatory variables were smoking status and pack-years. Covariates included age, sex, race, ethnicity, receipt of Medicaid, neighborhood area deprivation index, and baseline SLE damage. Damage increase-free survival was evaluated by smoking status and pack-years using Kaplan-Meier and Cox proportional hazards methods. Results Patients of Black race and Medicaid recipients were more commonly current smokers ( p’s < 0.05). Former smokers were older and more likely to have late-onset SLE (54% versus 33% of never and 29% of current smokers, p = 0.001). Median time to SLICC/ACR-DI increase or death was earlier in current or former compared to never smokers (4.5 and 3.4 versus 9.0 yrs; p = 0.002). In multivariable models, the rate of damage accumulation was twice as fast in current smokers (HR 2.18; 1.33, 3.57) and smokers with a >10 pack-year history (HR 2.35; 1.15, 3.64) versus never smokers. Conclusions In this incident SLE cohort, past or current smoking predicted new SLE damage 4-5 years earlier. After adjustment, current smokers and patients with a pack-year history of >10 years accumulated damage at twice the rate of never smokers.

DIAGNOSTICS OF THE CURRENT STATE OF HEALTHCARE IN RUSSIA

2020 ◽  
Vol 15 (5) ◽  
pp. 35-55
Author(s):  
N.P. STARYKH ◽  
◽  
A.V. EGOROVA ◽  
Keyword(s):  
Health Care ◽  
Life Expectancy ◽  
Statistical Data ◽  
Secondary Analysis ◽  
World Health ◽  
Healthy Life Expectancy ◽  
Federal State ◽  
Sociological Research ◽  
Healthy Life ◽  
Current State

The purpose of the article is to analyze the current state of healthcare in Russia. Scientific novelty of the study: the authors suggest that the efficiency of the health care system depends on the state of such indicators of public health as life expectancy and healthy life expectancy. Life expectancy is an integrated demographic indicator that characterizes the number of years that a person would live on average, provided that the age-specific mortality rate of a generation would be at the level for which the indicator was calculated throughout life. The indicator ‘healthy life expectancy’ is formed by subtracting the number of years of unhealthy life (due to chronic diseases, disabilities, mental and behavioral disorders, etc.) from the life expectancy indicator. Results: the article presents an analysis of the current state of Russian healthcare based on statistical data provided by the Federal State Statistics Service, the World Health Organization, and world rankings. Attention is focused on the perceptions of Russians about the quality of medical services and Russian healthcare. Conclusions about the current state of health care in Russia are formulated by the authors, based on a secondary analysis of statistical data, as well as data from sociological research presented by leading Russian sociological centers.

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