Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100728
Fridolin Haugg MS , Grace Lee MD , John He BS , Justin Johnson MS , Anna Zapaishchykova MS , Danielle S Bitterman MD , Benjamin H Kann MD , Prof Hugo J W L Aerts PhD , Raymond H Mak MD
Chronological age, although commonly used in clinical practice, fails to capture individual variations in rates of ageing and physiological decline. Recent advances in artificial intelligence (AI) have transformed the estimation of biological age using various imaging techniques. This Review consolidates AI developments in age prediction across brain, chest, abdominal, bone, and facial imaging using diverse methods, including MRI, CT, x-ray, and photographs. The difference between predicted and chronological age—often referred to as age deviation—is a promising biomarker for assessing health status and predicting disease risk. In this Review, we highlight consistent associations between age deviation and various health outcomes, including mortality risk, cognitive decline, and cardiovascular prognosis. We also discuss the technical challenges in developing unbiased models and ethical considerations for clinical application. This Review highlights the potential of AI-based age estimation in personalised medicine as it offers a non-invasive, interpretable biomarker that could transform health risk assessment and guide preventive interventions.
{"title":"Imaging biomarkers of ageing: a review of artificial intelligence-based approaches for age estimation","authors":"Fridolin Haugg MS , Grace Lee MD , John He BS , Justin Johnson MS , Anna Zapaishchykova MS , Danielle S Bitterman MD , Benjamin H Kann MD , Prof Hugo J W L Aerts PhD , Raymond H Mak MD","doi":"10.1016/j.lanhl.2025.100728","DOIUrl":"10.1016/j.lanhl.2025.100728","url":null,"abstract":"<div><div>Chronological age, although commonly used in clinical practice, fails to capture individual variations in rates of ageing and physiological decline. Recent advances in artificial intelligence (AI) have transformed the estimation of biological age using various imaging techniques. This Review consolidates AI developments in age prediction across brain, chest, abdominal, bone, and facial imaging using diverse methods, including MRI, CT, x-ray, and photographs. The difference between predicted and chronological age—often referred to as age deviation—is a promising biomarker for assessing health status and predicting disease risk. In this Review, we highlight consistent associations between age deviation and various health outcomes, including mortality risk, cognitive decline, and cardiovascular prognosis. We also discuss the technical challenges in developing unbiased models and ethical considerations for clinical application. This Review highlights the potential of AI-based age estimation in personalised medicine as it offers a non-invasive, interpretable biomarker that could transform health risk assessment and guide preventive interventions.</div></div>","PeriodicalId":34394,"journal":{"name":"Lancet Healthy Longevity","volume":"6 7","pages":"Article 100728"},"PeriodicalIF":14.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144683303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100731
Jasmine Ming Gan MBBS , Emily Louise Boucher BHSc , Nicola Georgia Lovett MD , Sophie Roche BM BCh , Sarah Catherine Smith MBBS , Sarah Tamsin Pendlebury DPhil
Background
Reliable estimates of delirium occurrence and outcomes are necessary to inform hospital services, research, and policy, but inclusive cohorts with long-term follow-up are scarce. We aimed to assess the age-specific occurrence of delirium in acute general (internal) medicine, associated factors, and 10-year outcomes stratified by age and comorbid dementia status.
Methods
This longitudinal, observational study was done at the John Radcliffe Hospital (Oxford, UK). We included consecutive adult patients aged 16 years and older in an acute general (internal) medicine service over six 8-week periods (between Sept 4, 2010, and Nov 15, 2018). Delirium was diagnosed prospectively using the Confusion Assessment Method and Diagnostic and Statistical Manual of Mental Disorders, fourth edition, criteria and subcategorised as prevalent (≤48 h of admission) or incident (>48 h postadmission). Odds ratios adjusted (adjORs) for demographics, comorbidity, frailty, and illness severity were calculated for binarised outcomes and adjusted hazard ratios (adjHRs) were calculated for time to death.
Findings
1846 patients were admitted to acute general (internal) medicine (mean age 68·2 years [SD 20·0], age range 16–102 years), 426 (23% [95% CI 21–25]) of whom had delirium (prevalent n=290 [68%], incident n=73 [17%], both prevalent and incident n=63 [15%]), of whom 134 (31·5%) had dementia. 950 (51·5%) patients were female, 895 (48·5%) were male, and sex data were missing for one patient. Delirium increased with age, from six (2% [95% CI 1–4]) of 340 patients younger than 50 years and 31 (9% [6–13]) of 333 patients at age 50–64 years to 57 (20% [16–25]) of 281 at age 65–74 years, 245 (35% [31–38]) of 704 at age 75–89 years, and 87 (46% [39–54]) of 188 at age 90 years and older. Of the 37 patients younger than 65 years who had delirium, 28 (76%) had an underlying neurological or neuropsychiatric disorder. In those aged 65 years or older, delirium was overall associated (all p<0·001, age and sex adjusted) with dementia (adjOR 3·63 [95% CI 2·65–4·98]), pre-admission dependency (2·63 [2·02–3·43]), comorbidity burden (1·04 [1·02–1·05]), and frailty (moderate vs low risk 3·62 [2·70–4·85] and high vs low risk 11·85 [7·24–19·42]), with stronger associations in patients without comorbid dementia than in those with comorbid dementia. Delirium predicted inpatient stay longer than 7 days (adjOR 2·48 [1·84–3·35]), discharge care needs (2·41 [1·70–3·40]), and mortality during admission (2·45 [1·52–3·94]). The increased risk of death in the delirium group was highest in the immediate postadmission period and attenuated thereafter, but was maintained for up to 10 years of follow-up (adjHR 2·03 [95% CI 1·40–2·97] for 30-day mortality vs 1·52 [1·30–1·77] for 10-year mortality). Excess inpatient mortality was highest i
{"title":"Occurrence, associated factors, and outcomes of delirium in patients in an adult acute general medicine service in England: a 10-year longitudinal, observational study","authors":"Jasmine Ming Gan MBBS , Emily Louise Boucher BHSc , Nicola Georgia Lovett MD , Sophie Roche BM BCh , Sarah Catherine Smith MBBS , Sarah Tamsin Pendlebury DPhil","doi":"10.1016/j.lanhl.2025.100731","DOIUrl":"10.1016/j.lanhl.2025.100731","url":null,"abstract":"<div><h3>Background</h3><div>Reliable estimates of delirium occurrence and outcomes are necessary to inform hospital services, research, and policy, but inclusive cohorts with long-term follow-up are scarce. We aimed to assess the age-specific occurrence of delirium in acute general (internal) medicine, associated factors, and 10-year outcomes stratified by age and comorbid dementia status.</div></div><div><h3>Methods</h3><div>This longitudinal, observational study was done at the John Radcliffe Hospital (Oxford, UK). We included consecutive adult patients aged 16 years and older in an acute general (internal) medicine service over six 8-week periods (between Sept 4, 2010, and Nov 15, 2018). Delirium was diagnosed prospectively using the Confusion Assessment Method and Diagnostic and Statistical Manual of Mental Disorders, fourth edition, criteria and subcategorised as prevalent (≤48 h of admission) or incident (>48 h postadmission). Odds ratios adjusted (<sub>adj</sub>ORs) for demographics, comorbidity, frailty, and illness severity were calculated for binarised outcomes and adjusted hazard ratios (<sub>adj</sub>HRs) were calculated for time to death.</div></div><div><h3>Findings</h3><div>1846 patients were admitted to acute general (internal) medicine (mean age 68·2 years [SD 20·0], age range 16–102 years), 426 (23% [95% CI 21–25]) of whom had delirium (prevalent n=290 [68%], incident n=73 [17%], both prevalent and incident n=63 [15%]), of whom 134 (31·5%) had dementia. 950 (51·5%) patients were female, 895 (48·5%) were male, and sex data were missing for one patient. Delirium increased with age, from six (2% [95% CI 1–4]) of 340 patients younger than 50 years and 31 (9% [6–13]) of 333 patients at age 50–64 years to 57 (20% [16–25]) of 281 at age 65–74 years, 245 (35% [31–38]) of 704 at age 75–89 years, and 87 (46% [39–54]) of 188 at age 90 years and older. Of the 37 patients younger than 65 years who had delirium, 28 (76%) had an underlying neurological or neuropsychiatric disorder. In those aged 65 years or older, delirium was overall associated (all p<0·001, age and sex adjusted) with dementia (<sub>adj</sub>OR 3·63 [95% CI 2·65–4·98]), pre-admission dependency (2·63 [2·02–3·43]), comorbidity burden (1·04 [1·02–1·05]), and frailty (moderate <em>vs</em> low risk 3·62 [2·70–4·85] and high <em>vs</em> low risk 11·85 [7·24–19·42]), with stronger associations in patients without comorbid dementia than in those with comorbid dementia. Delirium predicted inpatient stay longer than 7 days (<sub>adj</sub>OR 2·48 [1·84–3·35]), discharge care needs (2·41 [1·70–3·40]), and mortality during admission (2·45 [1·52–3·94]). The increased risk of death in the delirium group was highest in the immediate postadmission period and attenuated thereafter, but was maintained for up to 10 years of follow-up (<sub>adj</sub>HR 2·03 [95% CI 1·40–2·97] for 30-day mortality <em>vs</em> 1·52 [1·30–1·77] for 10-year mortality). Excess inpatient mortality was highest i","PeriodicalId":34394,"journal":{"name":"Lancet Healthy Longevity","volume":"6 7","pages":"Article 100731"},"PeriodicalIF":14.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evidence shows that violence in childhood affects health in adulthood, and violence in adulthood is associated with worse health. However, the extent to which violence-related health disparities persist into later life and whether the gap between victims and non-victims narrows, remains stable, or widens over time are unclear. This study aimed to examine the long-term effects of childhood and lifetime violence on health trajectories in older age.
Methods
The English Longitudinal Study of Ageing is one of the only cohort studies to cover violence across the lifespan alongside health trajectories in later life. Data were collected every 2 years between 2006 and 2019 and experiences of violence and limiting long-standing illness or disability (LLSID) were self-reported. We used logistic multilevel regressions and growth curve modelling to examine associations between parental physical abuse in childhood, lifetime physical or sexual violence, and any violence across the life course, with subsequent change in LLSID and depressive symptoms in later life, adjusted for demographic (age, gender, marital status, and region), socioeconomic (education, occupational class, tenure, and financial hardship), and social (household size and caregiving) attributes. Depressive symptoms were measured with the Centre for Epidemiological Studies Depression scale.
Findings
Of the 9771 participants who responded to the questionnaire, 6171 answered all three questions about experiences of violence and were included in this cohort. Any experience of violence was consistently associated with worse health in older age, including depression scale score of at least 4 (men: adjusted odds ratio 1·99, 95% CI 1·34–2·94; women: 1·38, 1·02–1·86) and LLSID (men: 1·74, 1·08–2·81; women: 2·15, 1·45–3·17). The patterns were evident in men and women.
Interpretation
Physical and mental health disadvantages associated with experiencing violence in childhood and adulthood are sustained throughout later life. There was little evidence that health disparities between victims and non-victims reduce over time. Preventing violence in both childhood and adulthood could promote healthy ageing.
{"title":"Violence across the life course and physical and mental health trajectories in later life: a 13-year population-based cohort study in England","authors":"Anastasia Fadeeva PhD , Polina Obolenskaya PhD , Estela Capelas Barbosa PhD , Prof Gene Feder MD , Prof Sally McManus MSc","doi":"10.1016/j.lanhl.2025.100738","DOIUrl":"10.1016/j.lanhl.2025.100738","url":null,"abstract":"<div><h3>Background</h3><div>Evidence shows that violence in childhood affects health in adulthood, and violence in adulthood is associated with worse health. However, the extent to which violence-related health disparities persist into later life and whether the gap between victims and non-victims narrows, remains stable, or widens over time are unclear. This study aimed to examine the long-term effects of childhood and lifetime violence on health trajectories in older age.</div></div><div><h3>Methods</h3><div>The English Longitudinal Study of Ageing is one of the only cohort studies to cover violence across the lifespan alongside health trajectories in later life. Data were collected every 2 years between 2006 and 2019 and experiences of violence and limiting long-standing illness or disability (LLSID) were self-reported. We used logistic multilevel regressions and growth curve modelling to examine associations between parental physical abuse in childhood, lifetime physical or sexual violence, and any violence across the life course, with subsequent change in LLSID and depressive symptoms in later life, adjusted for demographic (age, gender, marital status, and region), socioeconomic (education, occupational class, tenure, and financial hardship), and social (household size and caregiving) attributes. Depressive symptoms were measured with the Centre for Epidemiological Studies Depression scale.</div></div><div><h3>Findings</h3><div>Of the 9771 participants who responded to the questionnaire, 6171 answered all three questions about experiences of violence and were included in this cohort. Any experience of violence was consistently associated with worse health in older age, including depression scale score of at least 4 (men: adjusted odds ratio 1·99, 95% CI 1·34–2·94; women: 1·38, 1·02–1·86) and LLSID (men: 1·74, 1·08–2·81; women: 2·15, 1·45–3·17). The patterns were evident in men and women.</div></div><div><h3>Interpretation</h3><div>Physical and mental health disadvantages associated with experiencing violence in childhood and adulthood are sustained throughout later life. There was little evidence that health disparities between victims and non-victims reduce over time. Preventing violence in both childhood and adulthood could promote healthy ageing.</div></div><div><h3>Funding</h3><div>UK Prevention Research Partnership.</div></div>","PeriodicalId":34394,"journal":{"name":"Lancet Healthy Longevity","volume":"6 7","pages":"Article 100738"},"PeriodicalIF":14.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100724
Thomas Canning MSc , Jorge Arias-de la Torre PhD , Helen L Fisher Prof , John Gulliver Prof , Anna L Hansell Prof , Rebecca Hardy Prof , Stephani L Hatch Prof , Ian S Mudway PhD , Amy Ronaldson PhD , Molly Cartlidge MSc , Sarah-Naomi James PhD , Sarah E Keuss PhD , Jonathan M Schott FMedSci , Marcus Richards PhD , Ioannis Bakolis Prof
<div><h3>Background</h3><div>Previous research has linked higher exposure to air pollution to increased cognitive impairment at older ages. We aimed to extend the existing evidence in this area by incorporating exposures across the life course in addition to measures of cognition and brain structural imaging in participants at midlife to older age.</div></div><div><h3>Methods</h3><div>For this population-based study, we used data from the Medical Research Council National Survey of Health and Development (NSHD; also known as the 1946 British Birth Cohort) and a neuroimaging substudy of the NSHD known as Insight 46. Participants were recruited after birth in a single week during March, 1946. Our objectives were to assess whether exposure to air pollutants in midlife (age 45–64 years) was associated with poorer processing speed and poorer verbal memory between the ages of 43 years and 69 years, and whether exposures were associated with poorer cognitive state and brain structure outcomes at age 69–71 years. Air pollution exposure data were available for nitrogen dioxide (NO<sub>2</sub>; ages 45–64 years); particulate matter with diameter less than 10 μm (PM<sub>10</sub>; ages 55–64 years); and nitrogen oxides (NO<sub>x</sub>) and particulate matter with diameters less than 2·5 μm (PM<sub>2·5</sub>) and between 2·5 μm and less than 10 μm (PM<sub>coarse</sub>) and particulate matter absorbance (PM<sub>2·5</sub>abs) as a measure of black carbon absorption (ages 60–64 years), with adjustments for early-life exposures to black smoke and sulphur dioxide. Verbal memory was tested with a 15-item recall task and processing speed with a visual search task at ages 43, 53, 60–64, and 69 years. The Addenbrooke’s Cognitive Examination III (ACE-III), a measure of cognitive state, was conducted at age 69 years. Whole-brain, ventricular, hippocampal, and white matter hyperintensity volumes were assessed by MRI at age 69–71 years. Generalised linear models and generalised mixed linear models were used to explore associations between pollution exposure, cognitive measures, and brain structural outcomes, adjusted for sociodemographic factors including smoking status and neighbourhood deprivation.</div></div><div><h3>Findings</h3><div>Between the ages of 43 years and 69 years, we included 1534 NSHD participants in the verbal memory and processing speed analysis. Of 2148 participants who underwent testing during the wave of follow-up in 2015–16, at age 69 years, 1761 were included in the ACE-III analysis. Of the 502 NSHD participants recruited into the Insight 46 substudy, 453 were included in the analysis. Higher exposure to NO<sub>2</sub> and PM<sub>10</sub> was associated with slower processing speed between the ages of 43 years and 69 years (NO<sub>2</sub> β −8·121 [95% CI −10·338 to −5·905 per IQR increase in exposure]; PM<sub>10</sub> β −4·518 [−6·680 to −2·357]). Higher exposure to all tested pollutants was associated with lower ACE-III score at age 69 years (eg,
{"title":"Associations between life course exposure to ambient air pollution with cognition and later-life brain structure: a population-based study of the 1946 British Birth Cohort","authors":"Thomas Canning MSc , Jorge Arias-de la Torre PhD , Helen L Fisher Prof , John Gulliver Prof , Anna L Hansell Prof , Rebecca Hardy Prof , Stephani L Hatch Prof , Ian S Mudway PhD , Amy Ronaldson PhD , Molly Cartlidge MSc , Sarah-Naomi James PhD , Sarah E Keuss PhD , Jonathan M Schott FMedSci , Marcus Richards PhD , Ioannis Bakolis Prof","doi":"10.1016/j.lanhl.2025.100724","DOIUrl":"10.1016/j.lanhl.2025.100724","url":null,"abstract":"<div><h3>Background</h3><div>Previous research has linked higher exposure to air pollution to increased cognitive impairment at older ages. We aimed to extend the existing evidence in this area by incorporating exposures across the life course in addition to measures of cognition and brain structural imaging in participants at midlife to older age.</div></div><div><h3>Methods</h3><div>For this population-based study, we used data from the Medical Research Council National Survey of Health and Development (NSHD; also known as the 1946 British Birth Cohort) and a neuroimaging substudy of the NSHD known as Insight 46. Participants were recruited after birth in a single week during March, 1946. Our objectives were to assess whether exposure to air pollutants in midlife (age 45–64 years) was associated with poorer processing speed and poorer verbal memory between the ages of 43 years and 69 years, and whether exposures were associated with poorer cognitive state and brain structure outcomes at age 69–71 years. Air pollution exposure data were available for nitrogen dioxide (NO<sub>2</sub>; ages 45–64 years); particulate matter with diameter less than 10 μm (PM<sub>10</sub>; ages 55–64 years); and nitrogen oxides (NO<sub>x</sub>) and particulate matter with diameters less than 2·5 μm (PM<sub>2·5</sub>) and between 2·5 μm and less than 10 μm (PM<sub>coarse</sub>) and particulate matter absorbance (PM<sub>2·5</sub>abs) as a measure of black carbon absorption (ages 60–64 years), with adjustments for early-life exposures to black smoke and sulphur dioxide. Verbal memory was tested with a 15-item recall task and processing speed with a visual search task at ages 43, 53, 60–64, and 69 years. The Addenbrooke’s Cognitive Examination III (ACE-III), a measure of cognitive state, was conducted at age 69 years. Whole-brain, ventricular, hippocampal, and white matter hyperintensity volumes were assessed by MRI at age 69–71 years. Generalised linear models and generalised mixed linear models were used to explore associations between pollution exposure, cognitive measures, and brain structural outcomes, adjusted for sociodemographic factors including smoking status and neighbourhood deprivation.</div></div><div><h3>Findings</h3><div>Between the ages of 43 years and 69 years, we included 1534 NSHD participants in the verbal memory and processing speed analysis. Of 2148 participants who underwent testing during the wave of follow-up in 2015–16, at age 69 years, 1761 were included in the ACE-III analysis. Of the 502 NSHD participants recruited into the Insight 46 substudy, 453 were included in the analysis. Higher exposure to NO<sub>2</sub> and PM<sub>10</sub> was associated with slower processing speed between the ages of 43 years and 69 years (NO<sub>2</sub> β −8·121 [95% CI −10·338 to −5·905 per IQR increase in exposure]; PM<sub>10</sub> β −4·518 [−6·680 to −2·357]). Higher exposure to all tested pollutants was associated with lower ACE-III score at age 69 years (eg,","PeriodicalId":34394,"journal":{"name":"Lancet Healthy Longevity","volume":"6 7","pages":"Article 100724"},"PeriodicalIF":14.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144675949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100729
Yana Vinogradova PhD , Barbara Iyen PhD , Prof Tahir Masud MRCP , Lauren Taylor BMBS , Prof Joe Kai MD
<div><h3>Background</h3><div>Women benefit from reduced fracture risk while using menopausal hormone therapy. However, information on risks after stopping menopausal hormone therapy is scarce and inconsistent, with no information on longer-term fracture risk as women age. We aimed to produce robust estimates of fracture risk among past users for the longest possible period after discontinuing therapy.</div></div><div><h3>Methods</h3><div>We did a nested case–control study using UK primary and secondary care data from the Clinical Practice Research Datalink, with the underlying cohorts CPRD GOLD and Aurum. Women, aged 40 years and older, registered with a primary care practice between Jan 1, 1998, and Feb 28, 2023, and with a first record for any fracture, were matched at the fracture index date with up to five female controls with no fracture history, who were of the same age and registered at the same general practice. Menopausal hormone therapy-related fracture risks were assessed using conditional logistic regression adjusted for demographics, family history, menopausal symptoms, comorbidities, and other medications.</div></div><div><h3>Findings</h3><div>In total, 648 747 women (500 692 from Aurum and 148 055 from GOLD databases) with a first fracture record during the study period were matched to 2 357 125 women with no previous or contemporaneous fracture record. Age of average fracture cases was 68·5 years (SD 14·0), 3·2% were recorded as being from minority ethnic populations, and about a quarter of patients were older than 80 years. 140 410 (21·6%) cases used menopausal hormone therapy for a median of 3·6 years (IQR 1·3–6·8) and 515 917 (21·9%) controls used it for a median of 3·9 years (1·4–7·3). Compared with never-use, overall fracture risk was reduced for current use (oestrogen-only odds ratio [OR] 0·76 [95% CI 0·74–0·78], oestrogen–progestogen OR 0·75 [0·73–0·76]), became higher 1–10 years after discontinuation (oestrogen-only OR 0·99 [0·98–1·01], oestrogen–progestogen OR 1·06 [1·05–1·08]), but was again lower for more than 10 years post-cessation (oestrogen-only OR 0·93 [0·91–0·94], oestrogen–progestogen OR 0·95 [0·94–0·96]). Risk levels varied by menopausal hormone therapy type and by duration of treatment. Estimated extra fracture cases per 10 000 women-years 1–10 years after oestrogen–progestogen treatment were equivalent to 14 cases for less than 5 years menopausal hormone therapy exposure and five cases for 5 or more years of exposure. However, for more than 10 years after discontinuation, we estimated three fewer fracture cases for those on oestrogen–progestogen therapy for less than 5 years exposure and 13 fewer fracture cases for those with 5 or more years of exposure.</div></div><div><h3>Interpretation</h3><div>We have observed an attenuation of fracture risk after discontinuing menopausal hormone therapy, which manifests after an initial sharp rise. Fracture risk generally increases with age, but after discontinuation of m
{"title":"Discontinuation of menopausal hormone therapy and risk of fracture: nested case–control studies using routinely collected primary care data","authors":"Yana Vinogradova PhD , Barbara Iyen PhD , Prof Tahir Masud MRCP , Lauren Taylor BMBS , Prof Joe Kai MD","doi":"10.1016/j.lanhl.2025.100729","DOIUrl":"10.1016/j.lanhl.2025.100729","url":null,"abstract":"<div><h3>Background</h3><div>Women benefit from reduced fracture risk while using menopausal hormone therapy. However, information on risks after stopping menopausal hormone therapy is scarce and inconsistent, with no information on longer-term fracture risk as women age. We aimed to produce robust estimates of fracture risk among past users for the longest possible period after discontinuing therapy.</div></div><div><h3>Methods</h3><div>We did a nested case–control study using UK primary and secondary care data from the Clinical Practice Research Datalink, with the underlying cohorts CPRD GOLD and Aurum. Women, aged 40 years and older, registered with a primary care practice between Jan 1, 1998, and Feb 28, 2023, and with a first record for any fracture, were matched at the fracture index date with up to five female controls with no fracture history, who were of the same age and registered at the same general practice. Menopausal hormone therapy-related fracture risks were assessed using conditional logistic regression adjusted for demographics, family history, menopausal symptoms, comorbidities, and other medications.</div></div><div><h3>Findings</h3><div>In total, 648 747 women (500 692 from Aurum and 148 055 from GOLD databases) with a first fracture record during the study period were matched to 2 357 125 women with no previous or contemporaneous fracture record. Age of average fracture cases was 68·5 years (SD 14·0), 3·2% were recorded as being from minority ethnic populations, and about a quarter of patients were older than 80 years. 140 410 (21·6%) cases used menopausal hormone therapy for a median of 3·6 years (IQR 1·3–6·8) and 515 917 (21·9%) controls used it for a median of 3·9 years (1·4–7·3). Compared with never-use, overall fracture risk was reduced for current use (oestrogen-only odds ratio [OR] 0·76 [95% CI 0·74–0·78], oestrogen–progestogen OR 0·75 [0·73–0·76]), became higher 1–10 years after discontinuation (oestrogen-only OR 0·99 [0·98–1·01], oestrogen–progestogen OR 1·06 [1·05–1·08]), but was again lower for more than 10 years post-cessation (oestrogen-only OR 0·93 [0·91–0·94], oestrogen–progestogen OR 0·95 [0·94–0·96]). Risk levels varied by menopausal hormone therapy type and by duration of treatment. Estimated extra fracture cases per 10 000 women-years 1–10 years after oestrogen–progestogen treatment were equivalent to 14 cases for less than 5 years menopausal hormone therapy exposure and five cases for 5 or more years of exposure. However, for more than 10 years after discontinuation, we estimated three fewer fracture cases for those on oestrogen–progestogen therapy for less than 5 years exposure and 13 fewer fracture cases for those with 5 or more years of exposure.</div></div><div><h3>Interpretation</h3><div>We have observed an attenuation of fracture risk after discontinuing menopausal hormone therapy, which manifests after an initial sharp rise. Fracture risk generally increases with age, but after discontinuation of m","PeriodicalId":34394,"journal":{"name":"Lancet Healthy Longevity","volume":"6 7","pages":"Article 100729"},"PeriodicalIF":14.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144718798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100719
Hanseul Cho MD , Soeun Kim MSc , Yejun Son MSc , Wonwoo Jang MD , Hyeon Jin Kim PhD , Hayeon Lee PhD , Sooji Lee MD , Jiyeon Oh MD , Prof Jiseung Kang PhD , Alexander C Tsai MD , Ann K Shinn MD , Prof Guillaume Fond MD , Prof Laurent Boyer MD , Prof Marco Solmi MD , Prof Selin Woo PhD , Prof Dong Keon Yon MD , Prof Paolo Fusar-Poli MD
<div><h3>Background</h3><div>Suicide rates are highest among older adults, yet comprehensive global studies are limited. This study aimed to estimate suicide mortality rates among older adults aged 65 years and older across 47 countries and territories from 1996 to 2021, including analyses by suicide method, project future rates to 2050, and identify associated factors.</div></div><div><h3>Methods</h3><div>The study adhered to the Guidelines for Accurate and Transparent Health Estimates Reporting. We extracted suicide mortality data of older adults (≥65 years) across 47 countries and territories from the WHO Mortality Database for the period 1996–2021. We first estimated suicide mortality rates using a locally estimated scatterplot smoothing curve from 1996 to 2021, conducting subanalyses by sex, age subgroup, and suicide method. We then estimated future projections of suicide mortality rates to 2050 via Bayesian age-period-cohort (BAPC) modelling. We also performed a decomposition analysis using the Das Gupta method to identify factors contributing to changes in suicide death numbers between 1996 and 2021. Finally, we examined associations between suicide mortality rates in 2021 or the most recent available year and country-level indicators (poverty rate, disability-adjusted life-year [DALY] rates for alcohol use disorders and mental disorders, civilian firearm ownership, and pesticide use per cropland).</div></div><div><h3>Findings</h3><div>A total of 687 443 older adults who died by suicide (75·2% men, 24·8% women) were included in the analysis. The suicide mortality rate among adults aged 65 years and older was 15·99 deaths per 100 000 (95% CI 14·19–17·80) in 2021, significantly higher than the all-age suicide mortality rate of 10·87 deaths per 100 000 (9·86–11·87) in 2021 (p<0·0001). Firearms were more frequently used by older adults who died by suicide, compared with the total population (14·91% <em>vs</em> 9·88%, respectively; p<0·0001). The firearm-related suicide mortality rate among older adults was 2·44 per 100 000 (95% CI 2·00–2·89) in 2021, approximately twice that of individuals of all ages (1·09 per 100 000; 0·88–1·31; p<0·0001). There was an overall decline in suicide mortality rates among older adults from 1996 to 2021 (average annual percentage change [AAPC] –1·51 per 100 000; 95% CI –1·52 to –1·50), which was more pronounced among women (AAPC –2·24 per 100 000; –2·28 to –2·21) than in men (AAPC –1·45 per 100 000; –1·48 to –1·42; p<0·0001). Older age subgroups had smaller AAPCs (p<0·0001 for comparisons across all age subgroups). Notably, among adults aged 80 years and older, the suicide mortality rate by firearm showed no statistically significant change between 1996 and 2021. BAPC model projections suggest a slowing in the decline of suicide mortality rates among older adults to 2050. Decomposition analysis indicated that compared with 1996, the total number of suicides in 2021 increased by 7781 deaths primarily
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Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100755
The Lancet Healthy Longevity
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Pub Date : 2025-07-01DOI: 10.1016/j.lanhl.2025.100730
Paula Etayo-Urtasun MSc , Mikel Izquierdo PhD , Mikel L Sáez de Asteasu PhD
Background
Acute hospitalisation is a recognised risk factor for adverse outcomes in older adults, including hospital-associated disability. Post-discharge exercise interventions might mitigate physical and cognitive decline, although the few meta-analyses performed previously present limitations. This systematic review and meta-analysis aimed to evaluate the effect of post-discharge exercise interventions on health-related outcomes in older adults.
Methods
A systematic search of PubMed, Scopus, Web of Science, and ScienceDirect was conducted following PRISMA 2020 guidelines on May 16, 2025. Randomised controlled trials published from Jan 1, 2000, to May 16, 2025, were included. These studies assessed the effectiveness of muscular strength and endurance exercises in older adults (aged 60 years and older) discharged from acute hospitalisation. There were no language filters. Two reviewers independently screened studies using the PICOS framework, extracted data from published reports, and assessed methodological quality using the Physiotherapy Evidence Database scale. Data were pooled using a random-effects model. This systematic review and meta-analysis is registered with PROSPERO, CRD42025630147.
Findings
The search yielded 2868 results, of which 17 articles (1458 participants) met inclusion criteria, with a mean Physiotherapy Evidence Database score of 7·3 (SD 0·9) out of 10, indicating moderate to high quality. Post-discharge exercise significantly improved physical function (standardised mean difference [SMD] 0·78 [95% CI 0·52 to 1·05], p<0·0001). No significant effects were observed for health-related quality of life (SMD 0·23 [−0·04 to 0·51], p=0·098) or readmission risk (risk ratio 0·64 [95% CI 0·39 to 1·05], p=0·076). Exercise effects on functional independence, cognitive function, frailty, and mortality were synthesised descriptively due to insufficient data for meta-analysis. The main sources of heterogeneity were the outcome assessment tools and the exercise protocols. No evidence of risk of bias was found using either selection models (p>0·05) or Egger’s test (p>0·05) for any of the outcomes.
Interpretation
Post-discharge exercise interventions are effective at improving physical function in older adults following acute hospitalisation; however, effects on other health-related outcomes remain inconclusive. Future studies should establish optimal post-discharge exercise modalities, dosages, and delivery strategies tailored to individual patient needs. Advancing these priorities could improve patient outcomes and health-care system efficiency.
Funding
None.
背景：急性住院是老年人不良结局的公认危险因素，包括医院相关残疾。出院后的运动干预可能会减轻身体和认知能力的下降，尽管之前进行的少数荟萃分析存在局限性。本系统综述和荟萃分析旨在评估出院后运动干预对老年人健康相关结局的影响。方法按照PRISMA 2020指南，于2025年5月16日对PubMed、Scopus、Web of Science和ScienceDirect进行系统检索。纳入了2000年1月1日至2025年5月16日发表的随机对照试验。这些研究评估了肌肉力量和耐力锻炼对急性住院出院的老年人（60岁及以上）的有效性。没有语言过滤器。两位审稿人使用PICOS框架独立筛选研究，从已发表的报告中提取数据，并使用物理治疗证据数据库量表评估方法学质量。数据采用随机效应模型汇总。该系统评价和荟萃分析已在PROSPERO注册，编号为CRD42025630147。结果：检索得到2868条结果，其中17篇文献（1458名受试者）符合纳入标准，物理治疗证据数据库的平均评分为7.3分（SD 0.9）（满分为10分），表明质量中等至高。出院后的锻炼显著改善了身体功能（标准化平均差[SMD] 0.78 [95% CI 0.52 ~ 1.05], p< 0.0001）。与健康相关的生活质量（SMD 0.23 [- 0.04 ~ 0.51], p= 0.098）或再入院风险（风险比0.64 [95% CI 0.39 ~ 1.05], p= 0.076）未见显著影响。由于meta分析数据不足，我们对运动对功能独立性、认知功能、虚弱和死亡率的影响进行了描述性综合。异质性的主要来源是结果评估工具和运动方案。使用选择模型（p> 0.05）或Egger检验（p> 0.05）对任何结果均未发现偏倚风险的证据。出院后运动干预对改善老年人急性住院后的身体功能是有效的；然而，对其他健康相关结果的影响仍不确定。未来的研究应该建立最佳的出院后运动方式、剂量和递送策略，以适应个别患者的需要。推进这些优先事项可以改善患者的治疗结果和卫生保健系统的效率。
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