SummaryBackgroundLittle is known about how the proportions of dependency states have changed between generational cohorts of older people. We aimed to estimate years lived in different dependency states at age 65 years in 1991 and 2011, and new projections of future demand for care.MethodsIn this population-based study, we compared two Cognitive Function and Ageing Studies (CFAS I and CFAS II) of older people (aged ≥65 years) who were permanently registered with a general practice in three defined geographical areas (Cambridgeshire, Newcastle, and Nottingham; UK). These studies were done two decades apart (1991 and 2011). General practices provided lists of individuals to be contacted and were asked to exclude those who had died or might die over the next month. Baseline interviews were done in the community and care homes. Participants were stratified by age, and interviews occurred only after written informed consent was obtained. Information collected included basic sociodemographics, cognitive status, urinary incontinence, and self-reported ability to do activities of daily living. CFAS I was assigned as the 1991 cohort and CFAS II as the 2011 cohort, and both studies provided prevalence estimates of dependency in four states: high dependency (24-h care), medium dependency (daily care), low dependency (less than daily), and independent. Years in each dependency state were calculated by Sullivan's method. To project future demands for social care, the proportions in each dependency state (by age group and sex) were applied to the 2014 England population projections.FindingsBetween 1991 and 2011, there were significant increases in years lived from age 65 years with low dependency (1·7 years [95% CI 1·0–2·4] for men and 2·4 years [1·8–3·1] for women) and increases with high dependency (0·9 years [0·2–1·7] for men and 1·3 years [0·5–2·1] for women). The majority of men's extra years of life were spent independent (36·3%) or with low dependency (36·3%) whereas for women the majority were spent with low dependency (58·0%), and only 4·8% were independent. There were substantial reductions in the proportions with medium and high dependency who lived in care homes, although, if these dependency and care home proportions remain constant in the future, further population ageing will require an extra 71 215 care home places by 2025.InterpretationOn average older men now spend 2·4 years and women 3·0 years with substantial care needs, and most will live in the community. These findings have considerable implications for families of older people who provide the majority of unpaid care, but the findings also provide valuable new information for governments and care providers planning the resources and funding required for the care of their future ageing populations.FundingMedical Research Council (G9901400) and (G06010220), with support from the National Institute for Health Research Comprehensive Local research networks in West Anglia and Trent, UK, and Neurodegenerative Disease Research Network in Newcastle, UK.

SummaryBackgroundWhether rises in life expectancy are increases in good-quality years is of profound importance worldwide, with population ageing. We investigate how various health expectancies have changed in England between 1991 and 2011, with identical study design and methods in each decade.MethodsBaseline data from the Cognitive Function and Ageing Studies in populations aged 65 years or older in three geographically defined centres in England (Cambridgeshire, Newcastle, and Nottingham) provided prevalence estimates for three health measures: self-perceived health (defined as excellent–good, fair, or poor); cognitive impairment (defined as moderate–severe, mild, or none, as assessed by Mini-Mental State Examination score); and disability in activities of daily living (defined as none, mild, or moderate–severe). Health expectancies for the three regions combined were calculated by the Sullivan method, which applies the age-specific and sex-specific prevalence of the health measure to a standard life table for the same period.FindingsBetween 1991 and 2011, gains in life expectancy at age 65 years (4·5 years for men and 3·6 years for women) were accompanied by equivalent gains in years free of any cognitive impairment (4·2 years [95% CI 4·2–4·3] for men and 4·4 years [4·3–4·5] for women) and decreased years with mild or moderate–severe cognitive impairment. Gains were also identified in years in excellent or good self-perceived health (3·8 years [95% CI 3·5–4·1] for men and 3·1 years [2·7–3·4] for women). Gains in disability-free years were much smaller than those in excellent–good self-perceived health or those free from cognitive impairment, especially for women (0·5 years [0·2–0·9] compared with 2·6 years [2·3–2·9] for men), mostly because of increased mild disability.InterpretationDuring the past two decades in England, we report an absolute compression (ie, reduction) of cognitive impairment, a relative compression of self-perceived health (ie, proportion of life spent healthy is increasing), and dynamic equilibrium of disability (ie, less severe disability is increasing but more severe disability is not). Reasons for these patterns are unknown but might include increasing obesity during previous decades. Our findings have wide-ranging implications for health services and for extension of working life.FundingUK Medical Research Council.

Our results suggest that inequalities in HLY50 across Europe are large, increasing and partly explained by levels of material deprivation. Moreover long-term unemployment has become more influential in explaining variation in HLY50 between 2005 and 2010.

This paper reports on projections of the United Kingdom's ethnic group populations for 2001-2051. For the years 2001-2007 we estimate fertility rates, survival probabilities, internal migration probabilities and international migration flows for 16 ethnic groups and 355 UK areas.We make assumptions about future component rates, probabilities and flows and feed these into our projection model. This model is a cohort-component model specified for single years of age to 100?. To handle this large state space, we employed a bi-regional model. We implement four projections: (1) a benchmark projection that uses the component inputs for 2001; (2) a trend projection where assumptions beyond 2007 are adjusted to those in the UK 2008-based National Population Projections (NPP); (3) a projection that modifies the NPP assumptions and (4) a projection that uses a different emigration assumption. The projected UK population ranges between a low of 63 millions in 2051 under the first projection to a high of 79 million in the third projection. Under all projections ethnic composition continues to change: the White British, White Irish and Black Caribbean groups experience the slowest growth and lose population share; the Other White and Mixed groups to experience relative increases in share; South Asian groups grow strongly as do the Chinese and Other Ethnic groups. The ethnic minority share of the population increases from 13% (2001) to 25% in the trend projection but to only 20% under our modified emigration projection. However, what is certain is that the UK can look forward to be becoming a more diverse nation by mid-century.

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Background COVID-19 is an emergent infectious disease that has spread geographically to become a global pandemic. While much research focuses on the epidemiological and virological aspects of COVID-19 transmission, there remains an important gap in knowledge regarding the drivers of geographical diffusion between places, in particular at the global scale. Here, we use quantile regression to model the roles of globalisation, human settlement and population characteristics as socio-spatial determinants of reported COVID-19 diffusion over a six-week period in March and April 2020. Our exploratory analysis is based on reported COVID-19 data published by Johns Hopkins University which, despite its limitations, serves as the best repository of reported COVID-19 cases across nations. Results The quantile regression model suggests that globalisation, settlement, and population characteristics related to high human mobility and interaction predict reported disease diffusion. Human development level (HDI) and total population predict COVID-19 diffusion in countries with a high number of total reported cases (per million) whereas larger household size, older populations, and globalisation tied to human interaction predict COVID-19 diffusion in countries with a low number of total reported cases (per million). Population density, and population characteristics such as total population, older populations, and household size are strong predictors in early weeks but have a muted impact over time on reported COVID-19 diffusion. In contrast, the impacts of interpersonal and trade globalisation are enhanced over time, indicating that human mobility may best explain sustained disease diffusion. Conclusions Model results confirm that globalisation, settlement and population characteristics, and variables tied to high human mobility lead to greater reported disease diffusion. These outcomes serve to inform suppression strategies, particularly as they are related to anticipated relocation diffusion from more- to less-developed countries and regions, and hierarchical diffusion from countries with higher population and density. It is likely that many of these processes are replicated at smaller geographical scales both within countries and within regions. Epidemiological strategies must therefore be tailored according to human mobility patterns, as well as countries’ settlement and population characteristics. We suggest that limiting human mobility to the greatest extent practical will best restrain COVID-19 diffusion, which in the absence of widespread vaccination may be one of the best lines of epidemiological defense.

Objectives. We aim to develop robust estimates of disability-free life expectancy (DFLE) and healthy life expectancy (HLE) for ethnic groups in England and Wales in 2001 and to examine observed variations across ethnic groups. Design. DFLE and HLE by age and gender for five-year age groups were computed for 16 ethnic groups by combining the 2001 Census data on ethnicity, self-reported limiting long-term illness and self-rated health using mortality by ethnic group estimated by two methods: the Standardised Illness Ratio (SIR) method and the Geographically Weighted Method (GWM). Results. The SIR and GWM methods differed somewhat in their estimates of life expectancy (LE) at birth but produced very similar estimates of DFLE and HLE by ethnic group. For the more conservative method (GWM), the range in DFLE at birth was 10.5 years for men and 11.9 years for women, double that in LE. DFLE at birth was highest for Chinese men (64.7 years, 95% CI 64.0–65.3) and women (67.0 years, 95% CI 66.4–67.6). Over half of the ethnic minority groups (men: 10; women: 9) had significantly lower DFLE at birth than White British men (61.7 years, 95% CI 61.7–61.7) or women (64.1 years, 95% CI 64.1–64.2), mostly the Black, Asian and mixed ethnic groups. The lowest DFLE observed was for Bangladeshi men (54.3 years, 95% CI 53.7–54.8) and Pakistani women (55.1 years, 95% CI 54.8–55.4). Notable were Indian women whose LE was similar to White British women but who had 4.3 years less disability-free (95% CI 4.0–4.6). Conclusions. Inequalities in DFLE between ethnic groups are large and exceed those in LE. Moreover, certain ethnic groups have a larger burden of disability that does not seem to be associated with shorter LE. With the increasing population of the non-White British community, it is essential to be able to identify the ethnic groups at higher risk of disability, in order to target appropriate interventions.

Projections of the UK's ethnic populations from 2001 to 2051 show significant future change. Groups outside the White British majority will increase in size and share, not only in core areas but throughout the country. Ethnic minorities will shift out of deprived local authorities and into less deprived ones, while the White distribution remains stable. The share of the Mixed group population in the most deprived quintile (Q5) of local authorities reduces from 26 to 19%, while its share in the least deprived quintile (Q1) increases from 22 to 29%. The corresponding shifts for Asian groups are from 25 to 18% for Q5 and from 9 to 20% for the Q1. For Black groups the Q5 quintile sees a decrease from 54 to 39% while the Q1 sees an increase from 7 to 19%. There are shifts to local authorities with lower ethnic minority concentrations by Mixed, Asian and Black populations from local authorities with high ethnic concentrations, while the White, Chinese and Other group distributions remain in 2051 as they were in 2001. So, ethnic minority groups will be less segregated from the rest of the population in 2051 than in 2001. Indices of Dissimilarity between each group and the rest of the population fall by a third over the projection period. The UK in 2051 will be a more ethnically diverse society than in 2001.