This article considers the impact of occupation on mortality using a dataset of over 9,000 male postal workers who can be traced from retirement to death. For each worker, we know their demographic characteristics, occupation, location, and cause of retirement. The article uses these data to model the impact of postal work on survival post-retirement, showing that type of occupation and cause of retirement had significant effects on survival for those pensioners who retired for medical reasons. Different occupations were exposed to varying risks, which led to occupationally distinct patterns of medical causes of retirement. These differing causes of retirement, in turn, led to different survival chances after a worker retired. The article demonstrates how a long-term view can improve our understanding of adult mortality in the United Kingdom in the nineteenth and twentieth centuries.

Clozapine remains the most effective treatment for treatment-resistant schizophrenia and one of the few psychiatric medications consistently associated with reduced suicidal behaviour. Nevertheless, its use remains markedly limited despite advances in pharmacovigilance, haematological monitoring and individualised prescribing strategies. This editorial examines whether psychiatry may continue to evaluate clozapine through historically inherited models of risk perception that emphasise treatment-attributable mortality while insufficiently incorporating the lethality of severe mental illness itself, particularly suicide. Clozapine therefore represents not only a psychopharmacological treatment, but also a revealing case study in how psychiatry conceptualises competing forms of mortality.

This study provides the first comprehensive analysis of morbidity and mortality in Dalmatian Pelican Pelecanus crispus and Great White Pelican P. onocrotalus in Greece. Data were collected over a 24-year period (1998–2021), using specific questionnaires to highlight the temporospatial, age and aetiological causes of morbidity and mortality to advance conservation efforts. Overall, 316 incidents of morbidity/mortality and 23 mass mortality events were recorded while the two species differed significantly in all parameters of morbidity/mortality. Annual rate of mortality was higher in Dalmatian Pelican (44.5 deaths per annum) than the Great White Pelican (2.4 deaths per annum). Dalmatian Pelican mortality tended to occur more during late winter/early spring and late summer/autumn, while Great White Pelican mortality occurred during autumn, matching with the presence of pre-migratory concentrations and migration. Dalmatian Pelican tended to be found dead in areas where pelicans congregated (e.g. colonies, feeding, wintering) while Great White Pelican were equally found in both areas with and without pelican congregations. A total of 30% of Great White Pelican mortality/morbidity happened in south Greece away from pelican areas and along the migration route whilst adult Dalmatian Pelicans and juvenile Great White Pelicans were the prevalent age groups. In Dalmatian Pelicans, 70% of mortality accumulated in the mass mortality events, while the sympatric Great White Pelican was unaffected during these events. Dalmatian Pelican mortality was mostly attributed to environmental (biotoxin) and infectious (viral/avian influenza) causes, while Great White Pelican mostly to anthropogenic (trauma/illegal shooting). Specific causes in Dalmatian Pelican mortality showed significant seasonal variation with viral causes in spring, biotoxin and entrapment in autumn, and illegal shooting and emaciation in winter. In Great White Pelicans, illegal shooting tended to occur in spring. A total of 25% of rescued Dalmatian Pelicans were released. Limitations of this study were that only 1% of the dead pelicans underwent a veterinary post-mortem investigation, in 26% of the dead pelicans the cause was completely unknown, the sex was not determined, and the age remained unidentified in a high percentage (43-46%) of individuals. In future, more veterinary input and a national preparedness plan for mass mortality events are needed.

During the nineteenth century, a notable number of African physicians studied in British medical schools and then served as military surgeons across British West Africa. Despite their importance, the views of this distinguished group about the relationship between data and public health have remained largely unexamined. Focusing on the early career of Dr James Africanus Beale Horton (1835–83), this article explores how his standpoint as a black doctor led him to problematise the way in which large gaps in West African climatological and mortality statistics implicitly contributed to erroneous assumptions about the impact of tropical illness upon African people. It accordingly treats the new evidence he gathered as a form of ‘counter data’ designed to highlight the plight of the black civilian population living in the colony’s diverse topographical regions. Through treating Horton as a counter-data activist, the article offers insight into the larger historical relationship between colonial health and imperial information-gathering strategies, and it establishes Horton as a noteworthy West African public health statistician.

Whether joint eating-timing configurations show comparable mortality associations across chronic diseases is uncertain. We analysed 26 712 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) 2005–2016 who had two reliable 24-h dietary recalls and mortality linkage. Participant-level mean first eating time and eating-window duration were standardised and classified by K-means. Survey-weighted Cox models incorporated strata and primary sampling units within six chronic disease domains; missing covariates were multiply imputed in thirty datasets and prespecified Benjamini–Hochberg false-discovery-rate families addressed multiplicity. Three patterns represented 30·2 % (early-start), 57·2 % (intermediate) and 12·6 % (late-start) of the weighted population. During 224 837·9 person-years, 3279 deaths occurred. None of the six all-cause mortality global tests met the prespecified false-discovery-rate threshold (all q ≥ 0·281). In the cancer domain, the late-start pattern yielded a higher estimated hazard of cancer mortality than early-start (hazard ratio 1·88, 95 % CI 1·15–3·06; P = 0·012), but the global q was 0·052 and pairwise q was 0·073. This association attenuated after exclusion of early deaths and was not reproduced in an independent Day 1 analysis. Proportional hazards were not supported in three models, for which estimates weakened or crossed the null over follow-up. Eating-timing patterns were not universal mortality predictors across chronic diseases. Their nutritional relevance appears context-dependent, and repeated timing assessments with clinical measures of disease severity are needed before these patterns can inform personalised nutritional care.

This study investigates germination transcriptome changes in seeds that aged during cool, dry storage, searching for signals of the alive-to-dead transition. Signals may reflect the activity of uncharacteristic metabolic pathways or the effects of accumulated small injuries that impair recovery from life in the dry state. Cohorts of soybean (Glycine max cv. ‘Williams 82’) seeds were stored for 3, 19 and 22 years, stored in years 1996, 1999 and 2015, respectively. These cohorts showed < 2, 40 and ∼99% mortality, respectively, in response to storage and ageing. Transcriptomes of dry embryonic axes and axes after 24 hours of imbibition were sequenced. Imbibed axes had 19,340 genes significantly differentially expressed (SDE) compared to dry axes. Imbibed axis transcriptomes clustered into three groups, comprised of axes with high, low, or no germination potential (GP). There were 17,360 SDE genes in high-GP axes and 4,892 SDE genes, mostly up-regulated, in no-GP axes. Transcriptomes of no-GP axes imbibed for 24 hours were similar to healthy axes imbibed for 3 hours. Slow transcription, rather than transcription errors or novel expression pathways, signals failure to transition from seed to seedling. We conclude that the death of dry-aged seeds during imbibition arises from metabolism that is ‘too little, too late’.

This paper presents the results of a targeted survey conducted among UK pension consultancies, insurers and reinsurers to explore current actuarial practices and challenges in modelling the impact on mortality and morbidity of climate perils. The responses reveal several recurring themes, including varying degrees of climate risk integration, plus significant data and methodological limitations. This is against a background of growing regulatory and stakeholder pressure to incorporate climate considerations into actuarial models. While a small number of organisations have made substantive progress, many are at a preliminary stage, relying primarily on qualitative or scenario-based approaches. Respondents identified a pressing need for standardised methodologies, improved data sources and practical guidance to support consistent and credible modelling. The findings highlight a clear need for profession-led guidance, improved access to climate-health data and practical frameworks to support the consistent integration of climate-related mortality and morbidity risks into actuarial work. Respondents expressed strong support for collaborative development of standardised scenarios, illustrative modelling approaches and case studies to bridge the gap between public-health research and actuarial application. The paper concludes with practical recommendations for practitioners and identifies priority areas for future research and professional guidance.

Breast cancer represents one of the main causes of mortality among women, and the consumption of bioactive compounds seems to contribute to improving the prognosis of the disease. However, the relationship between polyphenol intake and breast cancer has not yet been fully elucidated. The objective of this study was to investigate the association between polyphenol intake and breast cancer mortality, survival and recurrence. This is an observational study with a prospective sample of ninety-five women, followed up for an average of 11·5 years. Intake of polyphenols was assessed using an FFQ and estimated using the Phenol-Explorer® database. Cox proportional hazard models were used to investigate the associations. Survival curves were calculated using Kaplan–Meier analysis. An inverse association was found between the intake of total polyphenols, phenolic acids and lignans and the risk of breast cancer-specific mortality (hazard ratio (HR) = 0·20, 95 % CI (0·05, 0·80); HR = 0·09, 95 % CI (0·01, 0·50); HR = 0·15, 95 % CI (0·04, 0·63), respectively). Phenolic acids also showed an inverse association with breast cancer recurrence (HR = 0·35, 95 % CI (0·13, 0·98)) and all-cause mortality (HR = 0·23, 95 % CI (0·07, 0·77)). Coffee was the major contributor to total polyphenol, phenolic acid and lignan intake. Total polyphenol intake was associated with longer survival when breast cancer mortality was considered (P = 0·048). In conclusion, higher intake of polyphenols was associated with lower breast cancer-specific mortality. In addition, phenolic acids were associated with lower all-cause mortality and breast cancer recurrence. Further studies are needed to confirm these associations.

Climate change is likely to increase the frequency, severity, and duration of heat waves in many countries. To plan mitigation, adaptation, and resilience strategies, it is necessary to quantify heat wave risk at both the local level and the country level. A new, more granular methodology is proposed in order to integrate the impact of heat waves in hexagonal France on mortality with a short-term stress scenario. Based on open data and reproducible methodology, the approach can be used as a starting point to investigate other effects, such as urban heat islands. The present application is based on in situ observational weather data and environmental vulnerability data to construct adapted geographical clusters without relying on the administrative division of the territory. Excess mortality is modeled as a function of weather using machine learning. Using recent knowledge of climatology, we construct extreme weather scenarios to calculate a shock to mortality. Short-term shocks are compared, and their respective merits are discussed. The methodology has been shown to generate mortality shocks up to five times greater than those estimated by the French regulatory authority.