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1.
Popul Health Metr ; 22(1): 4, 2024 Mar 09.
Article in English | MEDLINE | ID: mdl-38461232

ABSTRACT

BACKGROUND: Studying long-term trends in educational inequalities in health is important for monitoring and policy evaluation. Data issues regarding the allocation of people to educational groups hamper the study and international comparison of educational inequalities in mortality. For the UK, this has been acknowledged, but no satisfactory solution has been proposed. OBJECTIVE: To enable the examination of long-term mortality trends by educational level for England and Wales (E&W) in a time-consistent and internationally comparable manner, we propose and implement an approach to deal with the data issues regarding mortality data by educational level. METHODS: We employed 10-year follow-ups of individuals aged 20+ from the Office for National Statistics Longitudinal Study (ONS-LS), which include education information from each decennial census (1971-2011) linked to individual death records, for a 1% representative sample of the E&W population. We assigned the individual cohort data to single ages and calendar years, and subsequently obtained aggregate all-cause mortality data by education, sex, age (30+), and year (1972-2017). Our data adjustment approach optimised the available education information at the individual level, and adjusts-at the aggregate level-for trend discontinuities related to the identified data issues, and for differences with country-level mortality data for the total population. RESULTS: The approach resulted in (1) a time-consistent and internationally comparable categorisation of educational attainment into the low, middle, and high educated; (2) the adjustment of identified data-quality related discontinuities in the trends over time in the share of personyears and deaths by educational level, and in the crude and the age-standardised death rate by and across educational levels; (3) complete mortality data by education for ONS-LS members aged 30+ in 1972-2017 which aligns with country-level mortality data for the total population; and (4) the estimation of inequality measures using established methods. For those aged 30+ , both absolute and relative educational inequalities in mortality first increased and subsequently decreased. CONCLUSION: We obtained additional insights into long-term trends in educational inequalities in mortality in E&W, and illustrated the potential effects of different data issues. We recommend the use of (part of) the proposed approach in other contexts.


Subject(s)
Mortality , Humans , Wales/epidemiology , Longitudinal Studies , Educational Status , England/epidemiology , Socioeconomic Factors
2.
J Epidemiol Community Health ; 77(7): 421-429, 2023 Jul.
Article in English | MEDLINE | ID: mdl-37173136

ABSTRACT

BACKGROUND: Across Europe, socioeconomic inequalities in mortality are large and persistent. To better understand the drivers of past trends in socioeconomic mortality inequalities, we identified phases and potential reversals in long-term trends in educational inequalities in remaining life expectancy at age 30 (e30), and assessed the contributions of mortality changes among the low-educated and the high-educated at different ages. METHODS: We used individually linked annual mortality data by educational level (low, middle and high), sex and single age (30+) from 1971/1972 onwards for England and Wales, Finland and Italy (Turin). We applied segmented regression to trends in educational inequalities in e30 (e30 high-educated minus e30 low-educated) and employed a novel demographic decomposition technique. RESULTS: We identified several phases and breakpoints in the trends in educational inequalities in e30. The long-term increases (Finnish men, 1982-2008; Finnish women, 1985-2017; and Italian men, 1976-1999) were driven by faster mortality declines among the high-educated aged 65-84, and by mortality increases among the low-educated aged 30-59. The long-term decreases (British men, 1976-2008, and Italian women, 1972-2003) were driven by faster mortality improvements among the low-educated than among the high-educated at age 65+. The recent stagnation of increasing inequality (Italian men, 1999) and reversals from increasing to decreasing inequality (Finnish men, 2008) and from decreasing to increasing inequality (British men, 2008) were driven by mortality trend changes among the low-educated aged 30-54. CONCLUSION: Educational inequalities are plastic. Mortality improvements among the low-educated at young ages are imperative for achieving long-term decreases in educational inequalities in e30.


Subject(s)
Life Expectancy , Male , Humans , Female , Adult , Aged , Socioeconomic Factors , Educational Status , Europe/epidemiology , Italy
3.
BMJ Open ; 9(4): e024404, 2019 04 24.
Article in English | MEDLINE | ID: mdl-31023749

ABSTRACT

OBJECTIVES: The life course determinants of midlife and later life cognitive function have been studied using longitudinal population-based cohort data, but far less is known about whether the pattern of these pathways is similar or distinct for clinically relevant cognitive state. We investigated this for Addenbrooke's Cognitive Examination third edition (ACE-III), used in clinical settings to screen for cognitive impairment and dementia. DESIGN: Longitudinal birth cohort study. SETTING: Residential addresses in England, Wales and Scotland. PARTICIPANTS: 1762 community-dwelling men and women of European heritage, enrolled since birth in the Medical Research Council (MRC) National Survey of Health and Development (the British 1946 birth cohort). PRIMARY OUTCOME: ACE-III. RESULTS: Path modelling estimated direct and indirect associations between apolipoprotein E (APOE) status, father's social class, childhood cognition, education, midlife occupational complexity, midlife verbal ability (National Adult Reading Test; NART), and the total ACE-III score. Controlling for sex, there was a direct negative association between APOE ε4 and the ACE-III score (ß=-0.04 [-0.08 to -0.002], p=0.04), but not between APOE ε4 and childhood cognition (ß=0.03 [-0.006 to 0.069], p=0.10) or the NART (ß=0.0005 [-0.03 to 0.03], p=0.97). The strongest influences on the ACE-III were from childhood cognition (ß=0.20 [0.14 to 0.26], p<0.001) and the NART (ß=0.35 [0.29 to 0.41], p<0.001); educational attainment and occupational complexity were modestly and independently associated with the ACE-III (ß=0.08 [0.03 to 0.14], p=0.002 and ß=0.05 [0.01 to 0.10], p=0.02, respectively). CONCLUSIONS: The ACE-III in the general population shows a pattern of life course antecedents that is similar to neuropsychological measures of cognitive function, and may be used to represent normal cognitive ageing as well as a screen for cognitive impairment and dementia.


Subject(s)
Aging , Child Development , Cognition Disorders/epidemiology , Cognition , Dementia/epidemiology , Language Arts , Social Class , Adolescent , Adult , Aged , Apolipoprotein E4/metabolism , Child , Cognition Disorders/etiology , Cognition Disorders/metabolism , Cohort Studies , Dementia/etiology , Dementia/metabolism , Educational Status , England , Female , Follow-Up Studies , Health Surveys , Humans , Longitudinal Studies , Male , Memory , Middle Aged , Occupations , Scotland , Wales , Wechsler Scales , White People , Young Adult
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