Physical Activity, Sedentary Behavior, and Long-Term Changes in Aortic Stiffness: The Whitehall II Study

BACKGROUND: Physical activity is associated with reduced cardiovascular disease risk, mainly through effects on atherosclerosis. Aortic stiffness may be an alternative mechanism. We examined whether patterns of physical activity and sedentary behavior are associated with rate of aortic stiffening. METHODS AND RESULTS: Carotid-femoral pulse wave velocity (PWV) was measured twice using applanation tonometry at mean ages 65 (in 2008/2009) and 70 (in 2012/2013) years in the Whitehall-II study (N=5196). Physical activity was self-reported at PWV baseline (2008/2009) and twice before (in 1997/1999 and 2002/2003). Sedentary time was defined as sitting time watching television or at work/commute. Linear mixed models adjusted for metabolic and lifestyle risk factors were used to analyze PWV change. Mean (SD) PWV (m/s) was 8.4 (2.4) at baseline and 9.2 (2.7) at follow-up, representing a 5-year increase of 0.76 m/s (95% CI 0.69, 0.83). A smaller 5-year increase in PWV was observed for each additional hour/week spent in sports activity (-0.02 m/s [95% CI -0.03, -0.001]) or cycling (-0.02 m/s [-0.03, -0.008]). Walking, housework, gardening, or do-it-yourself activities were not significantly associated with aortic stiffening. Each additional hour/week spent sitting was associated with faster PWV progression in models adjusted for physical activity (0.007 m/s [95% CI 0.001, 0.013]). Increasing physical activity over time was associated with a smaller subsequent increase in PWV (-0.16 m/s [-0.32, -0.002]) compared with not changing activity levels. CONCLUSIONS: Higher levels of moderate-to-vigorous physical activity and avoidance of sedentary behavior were each associated with a slower age-related progression of aortic stiffness independent of conventional vascular risk factors

Physical Activity, Sedentary Behavior, and Long-Term Changes in Aortic Stiffness: The Whitehall II Study

BACKGROUND: Physical activity is associated with reduced cardiovascular disease risk, mainly through effects on atherosclerosis. Aortic stiffness may be an alternative mechanism. We examined whether patterns of physical activity and sedentary behavior are associated with rate of aortic stiffening. METHODS AND RESULTS: Carotid-femoral pulse wave velocity (PWV) was measured twice using applanation tonometry at mean ages 65 (in 2008/2009) and 70 (in 2012/2013) years in the Whitehall-II study (N=5196). Physical activity was self-reported at PWV baseline (2008/2009) and twice before (in 1997/1999 and 2002/2003). Sedentary time was defined as sitting time watching television or at work/commute. Linear mixed models adjusted for metabolic and lifestyle risk factors were used to analyze PWV change. Mean (SD) PWV (m/s) was 8.4 (2.4) at baseline and 9.2 (2.7) at follow-up, representing a 5-year increase of 0.76 m/s (95% CI 0.69, 0.83). A smaller 5-year increase in PWV was observed for each additional hour/week spent in sports activity (-0.02 m/s [95% CI -0.03, -0.001]) or cycling (-0.02 m/s [-0.03, -0.008]). Walking, housework, gardening, or do-it-yourself activities were not significantly associated with aortic stiffening. Each additional hour/week spent sitting was associated with faster PWV progression in models adjusted for physical activity (0.007 m/s [95% CI 0.001, 0.013]). Increasing physical activity over time was associated with a smaller subsequent increase in PWV (-0.16 m/s [-0.32, -0.002]) compared with not changing activity levels. CONCLUSIONS: Higher levels of moderate-to-vigorous physical activity and avoidance of sedentary behavior were each associated with a slower age-related progression of aortic stiffness independent of conventional vascular risk factors

Adiposity, obesity, and arterial aging: longitudinal study of aortic stiffness in the Whitehall II cohort

We sought to determine whether adiposity in later midlife is an independent predictor of accelerated stiffening of the aorta. Whitehall II study participants (3789 men; 1383 women) underwent carotid-femoral applanation tonometry at the mean age of 66 and again 4 years later. General adiposity by body mass index, central adiposity by waist circumference and waist:hip ratio, and fat mass percent by body impedance were assessed 5 years before and at baseline. In linear mixed models adjusted for age, sex, ethnicity, and mean arterial pressure, all adiposity measures were associated with aortic stiffening measured as increase in pulse wave velocity (PWV) between baseline and follow-up. The associations were similar in the metabolically healthy and unhealthy, according to Adult Treatment Panel-III criteria excluding waist circumference. C-reactive protein and interleukin-6 levels accounted for part of the longitudinal association between adiposity and PWV change. Adjusting for chronic disease, antihypertensive medication and risk factors, standardized effects of general and central adiposity and fat mass percent on PWV increase (m/s) were similar (0.14, 95% confidence interval: 0.05-0.24, P=0.003; 0.17, 0.08-0.27, P<0.001; 0.14, 0.05-0.22, P=0.002, respectively). Previous adiposity was associated with aortic stiffening independent of change in adiposity, glycaemia, and lipid levels across PWV assessments. We estimated that the body mass index-linked PWV increase will account for 12% of the projected increase in cardiovascular risk because of high body mass index. General and central adiposity in later midlife were strong independent predictors of aortic stiffening. Our findings suggest that adiposity is an important and potentially modifiable determinant of arterial aging

Forecasted trends in disability and life expectancy in England and Wales up to 2025: a modelling study

Background Reliable estimation of future trends in life expectancy and the burden of disability is crucial for ageing societies. Previous forecasts have not considered the potential impact of trends in disease incidence. The present prediction model combines population trends in cardiovascular disease, dementia, disability, and mortality to forecast trends in life expectancy and the burden of disability in England and Wales up to 2025. Methods We developed and validated the IMPACT-Better Ageing Model—a probabilistic model that tracks the population aged 35–100 years through ten health states characterised by the presence or absence of cardiovascular disease, dementia, disability (difficulty with one or more activities of daily living) or death up to 2025, by use of evidence-based age-specific, sex-specific, and year-specific transition probabilities. As shown in the English Longitudinal Study of Ageing, we projected continuing declines in dementia incidence (2·7% per annum), cardiovascular incidence, and mortality. The model estimates disability prevalence and disabled and disability-free life expectancy by year. Findings Between 2015 and 2025, the number of people aged 65 years and older will increase by 19·4% (95% uncertainty interval [UI] 17·7–20·9), from 10·4 million (10·37–10·41 million) to 12·4 million (12·23–12·57 million). The number living with disability will increase by 25·0% (95% UI 21·3–28·2), from 2·25 million (2·24–2·27 million) to 2·81 million (2·72–2·89 million). The age-standardised prevalence of disability among this population will remain constant, at 21·7% (95% UI 21·5–21·8) in 2015 and 21·6% (21·3–21·8) in 2025. Total life expectancy at age 65 years will increase by 1·7 years (95% UI 0·1–3·6), from 20·1 years (19·9–20·3) to 21·8 years (20·2–23·6). Disability-free life expectancy at age 65 years will increase by 1·0 years (95% UI 0·1–1·9), from 15·4 years (15·3–15·5) to 16·4 years (15·5–17·3). However, life expectancy with disability will increase more in relative terms, with an increase of roughly 15% from 2015 (4·7 years, 95% UI 4·6–4·8) to 2025 (5·4 years, 4·7–6·4). Interpretation The number of older people with care needs will expand by 25% by 2025, mainly reflecting population ageing rather than an increase in prevalence of disability. Lifespans will increase further in the next decade, but a quarter of life expectancy at age 65 years will involve disability. Funding British Heart Foundation

Veterinarski obilazak mliječnih farmi s povećanim brojem somatskih stanica i bakterija iznad zakonom dozvoljenih vrijednosti

The EU Directives 92/46 and 92/47 (D.P.R. 54/97 under national legislation) fix the agreed levels of somatic cell counts and total bacterial counts allowed in milk. Over a one year period, a total of 165farms which did not comply with one or more such legal requirements were visited and monitored. This was in order to check and, where necessary, correct the hygienic and sanitary management of the farm. A comparison of the bulk tank milk somatic cell count (BTMSCC) before and after the veterinary visit, shows improvements in all the farms which were tested. In a relatively short time, visited dairy farms with a somatic cell content between 401.000 and 500.000 cells/ml managed to comply with the parameters set down by law, achieving a mean of 304.000 cells/ml. However, those farms with a somatic cell counts between 501.000 and 800.000 cells/ml required further technical action. In fact, despite considerable improvements (mean somatic cell count decreasing from 638.000 cells/ml to 403.000 cells/ml), it was not possible to meet the required levels so rapidly. On these farms, a second veterinary visit was needed as well as more specific milk sampling for bacteriological assay and therapeutic guidelines in order to meet the specified requirements.Smjernicama 92/46. i 92/47. (D.P.R. 54/97). Europska unija je utvrdila maksimalno dozvoljene vrijednosti ukupnog broja bakterija i somatskih stanica u mlijeku. Unutar godine dana posjećeno je 165 farmi koje nisu zadovoljavale svim uvjetima. Posjet je obavljen s ciljem da se snimi postojeća situacija, i, ukoliko je neophodno, da se provedu adekvatne korekcije u higijenskom i sanitarnom vođenju farmi. Usporedbom broja somatskih stanica (BTMSCC) u dobavnim tankovima za mlijeko, prije i poslije veterinarske posjete, uočena su poboljšanja na svim ispitanim farmama. Ispitane mliječne farme s brojem somatskih stanica između 401000 i 500.000 stanica/mL u relativno kratkom vremenu uspjele su smanjiti taj broj na prosječnih 304.000 stanica/mL, što udovoljava propisanim vrijednostima. Međutim, na farmama s brojem somatskih stanica između 501.000 i 800.000 Stanica/mL potrebno je provesti dodatne tehničke mjere. Usprkos značajnom poboljšanju (prosječni broj somatskih stanica smanjene je sa 638.000 stanica/mL na 403.000 stanica/mL), nisu dobivene vrijednosti unutar zakonski propisanih. Ovim farmama bio je potreban dodatni veterinarski posjet kao i specifično bakteriološko ispitivanje te terapeutski naputci s ciljem da se postigne usuglašenost sa specifičnim zahtjevima

C-Reactive Protein Identifies Low-Risk Metabolically Healthy Obese Persons: The European Prospective Investigation of Cancer-Norfolk Prospective Population Study.

BACKGROUND: Conflicting data exist about the cardiovascular risk of metabolically healthy obese persons. The prognostic value of C-reactive protein (CRP) in this intriguing group is unknown. We assessed the association between CRP levels and the risk of coronary heart disease (CHD) in metabolically healthy persons with abdominal obesity. METHODS AND RESULTS: In the European Prospective Investigation of Cancer-Norfolk prospective cohort, CRP levels and information on metabolic syndrome criteria were available for 7279 participants, of whom 825 (11%) developed CHD during a follow-up period of 10.9±1.8 years. There was a trend toward a higher multivariable-adjusted hazard ratio for CHD in metabolically healthy obese participants with CRP levels >2 mg/L compared with <2 mg/L (hazard ratio 1.59, 95% CI 0.97-2.62, P=0.066). Metabolically unhealthy obese participants had significantly higher CHD risk compared with metabolically healthy obese participants with CRP levels <2 mg/L (hazard ratio 1.88, 95% CI 1.20-2.94, P=0.006). Most important, we found that the risk of CHD among metabolically healthy obese persons with CRP levels <2 mg/L was comparable to that of metabolically healthy nonobese persons (hazard ratio 0.91, 95% CI 0.60-1.39, P=0.674). CONCLUSIONS: Among metabolically healthy obese persons, low CRP levels were associated with a CHD risk comparable to that of metabolically healthy nonobese persons. CRP appears to be an easy and widely available method for identifying a low-risk subpopulation among metabolically healthy obese persons.EPIC‐Norfolk is supported by program grants from the Medical Research Council UK and Cancer Research UK. The CRP measurements in the full cohort were supported by a grant from the Medical Research Council to the Medical Research Council Epidemiology Unit, Cambridge, United Kingdom (MRC G0701863). The funding sources had no role in the study design, the conduct of the analysis, or the decision to submit the manuscript for publication

The impacts of social restrictions during the COVID-19 pandemic on the physical activity levels of over 50-year olds: the CHARIOT COVID-19 Rapid Response (CCRR) cohort study

Objectives To quantify the associations between shielding status and loneliness at the start of the COVID-19 pandemic, and physical activity (PA) levels throughout the pandemic. Methods Demographic, health and lifestyle characteristics of 7748 cognitively healthy adults aged >50, and living in London, were surveyed from April 2020 to March 2021. The International Physical Activity Questionnaire (IPAQ) short-form assessed PA before COVID-19 restrictions, and up to 6 times over 11 months. Linear mixed models investigated associations between baseline shielding status, loneliness, and time-varying PA. Results Participants who felt ‘often lonely’ at the outset of the pandemic completed an average of 522 and 547 fewer Metabolic Equivalent of Task (MET) minutes/week (95% CI: -809, -236, pConclusions Those shielding or lonely at pandemic onset were likely to have completed low levels of PA during the pandemic. These associations are influenced by co-morbidities and health status

What will the cardiovascular disease slowdown cost? Modelling the impact of CVD trends on dementia, disability, and economic costs in England and Wales from 2020-2029.

To model the health impact and economic costs of the recent slowing of the historical decline in cardiovascular disease (CVD) incidence

Midlife contributors to socioeconomic differences in frailty during later life: a prospective cohort study

BACKGROUND: Health inequalities persist into old age. We aimed to investigate risk factors for socioeconomic differences in frailty that could potentially be modified through policy measures. METHODS: In this multi-wave longitudinal cohort study (Whitehall II study), we assessed participants' socioeconomic status, behavioural and biomedical risk factors, and disease status at age 45-55 years, and frailty (defined according to the Fried phenotype) at baseline and at one or more of three clinic visits about 18 years later (mean age 69 years [SD 5·9]). We used logistic mixed models to examine the associations between socioeconomic status and risk factors at age 50 years and subsequent prevalence of frailty (adjusted for sex, ethnic origin, and age), with sensitivity analyses and multiple imputation for missing data. FINDINGS: Between Sept 9, 2007, and Dec 8, 2016, 6233 middle-aged adults were measured for frailty. Frailty was present in 562 (3%) of 16 164 person-observations, and varied by socioeconomic status: 145 (2%) person-observations had high socioeconomic status, 241 (4%) had intermediate status, and 176 (7%) had low socioeconomic status, adjusting for sex and age. Risk factors for frailty included cardiovascular disease, depression, smoking, high or abstinent alcohol consumption, low fruit and vegetable consumption, physical inactivity, poor lung function, hypertension, and overweight or obesity. Cardiometabolic markers for future frailty were high ratio of total to high-density lipoprotein cholesterol, and raised interleukin-6 and C-reactive protein concentrations. The five most important factors contributing to the frailty gradient, assessed by percent attenuation of the association between socioeconomic status and frailty, were physical activity (13%), interleukin-6 (13%), body-mass index category (11%), C-reactive protein (11%), and poor lung function (10%). Overall, socioeconomic differences in frailty were reduced by 40% in the maximally-adjusted model compared with the minimally-adjusted model. INTERPRETATION: Behavioural and cardiometabolic risk factors in midlife account for more than a third of socioeconomic differences in frailty. Our findings suggest that interventions targeting physical activity, obesity, smoking, and low-grade inflammation in middle age might reduce socioeconomic differences in later-life frailty. FUNDING: British Heart Foundation and British Medical Research Council

Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study

BACKGROUND: Evaluation of cardiovascular disease risk in primary care, which is recommended every 5 years in middle-aged and older adults (typical age range 40-75 years), is based on risk scores, such as the European Society of Cardiology Systematic Coronary Risk Evaluation (SCORE) and American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease (ASCVD) algorithms. This evaluation currently uses only the most recent risk factor assessment. We aimed to examine whether 5-year changes in SCORE and ASCVD risk scores are associated with future cardiovascular disease risk. METHODS: We analysed data from the Whitehall II longitudinal, prospective cohort study for individuals with no history of stroke, myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, definite angina, heart failure, or peripheral artery disease. Participants underwent clinical examinations in 5-year intervals between Aug 7, 1991, and Dec 6, 2016, and were followed up for incident cardiovascular disease until Oct 2, 2019. Levels of, and 5-year changes in, cardiovascular disease risk were assessed using the SCORE and ASCVD risk scores and were analysed as predictors of cardiovascular disease. Harrell's C index, continuous net reclassification improvement, the Akaike information criterion, and calibration analysis were used to assess whether incorporating change in risk scores into a model including only a single risk score assessment improved the predictive performance. We assessed the levels of, and 5-year changes in, SCORE and ASCVD risk scores as predictors of cardiovascular disease and disease-free life-years using Cox proportional hazards and flexible parametric survival models. FINDINGS: 7574 participants (5233 [69·1%] men, 2341 [30·9%] women) aged 40-75 years were included in analyses of risk score change between April 24, 1997, and Oct 2, 2019. During a mean follow-up of 18·7 years (SD 5·5), 1441 (19·0%; 1042 [72·3%] men and 399 [27·7%] women) participants developed cardiovascular disease. Adding 5-year change in risk score to a model that included only a single risk score assessment improved model performance according to Harrell's C index (from 0·685 to 0·690, change 0·004 [95% CI 0·000 to 0·008] for SCORE; from 0·699 to 0·700, change 0·001 [0·000 to 0·003] for ASCVD), the Akaike information criterion (from 17 255 to 17 200, change -57 [95% CI -97 to -13] for SCORE; from 14 739 to 14 729, change -10 [-28 to 7] for ASCVD), and the continuous net reclassification index (0·353 [95% CI 0·234 to 0·447] for SCORE; 0·232 [0·030 to 0·344] for ASCVD). Both favourable and unfavourable changes in SCORE and ASCVD were associated with cardiovascular disease risk and disease-free life-years. The associations were seen in both sexes and all age groups up to the age of 75 years. At the age of 45 years, each 2-unit improvement in risk scores was associated with an additional 1·3 life-years (95% CI 0·4 to 2·2) free of cardiovascular disease for SCORE and an additional 0·9 life-years (95% CI 0·5 to 1·3) for ASCVD. At age 65 years, this same improvement was associated with an additional 0·4 life-years (95% CI 0·0 to 0·7) free of cardiovascular disease for SCORE and 0·3 life-years (95% CI 0·1 to 0·5) for ASCVD. These models were developed into an interactive calculator, which enables estimation of the number of cardiovascular disease-free life-years for an individual as a function of two risk score measurements. INTERPRETATION: Changes in the SCORE and ASCVD risk scores over time inform cardiovascular disease risk prediction beyond a single risk score assessment. Repeat data might allow more accurate cardiovascular risk stratification and strengthen the evidence base for decisions on preventive interventions. FUNDING: UK Medical Research Council, British Heart Foundation, Wellcome Trust, and US National Institute on Aging