Hasil untuk "Demography. Population. Vital events"

Catherine E. Slavik, Daniel A. Chapman, Stephanie E. Cleland et al.

Wildfire smoke poses a serious and growing health threat to communities in the United States (US), Canada, and beyond. Some populations—including children—are especially susceptible. Air Quality Indexes (AQIs) can inform parents about local air quality during smoke events and offer guidance on actions that protect children. In July–August 2023, parents from Oregon, Washington, California, and British Columbia (BC) (n = 2100) participated in an online cross-sectional study. Binary and ordinal logistic regression models were used to examine geographic, demographic, and psychosocial predictors of three dependent variables: knowledge of where to check AQI information, frequent checking of AQI information during wildfire seasons, and adherence to AQI health messages around reducing/rescheduling outdoor physical activity. Smoke-exposure analysis indicated widespread potential exposures to wildfire smoke across all four jurisdictions. Nonetheless, parents in BC, on average, were less likely to report knowing where to check AQI information, checked less frequently, and were less likely to adhere to AQI guidance than parents in the three US states. Adherence to AQI health messages did not differ by jurisdiction in the presence of other covariates, suggesting parents are equally likely to follow AQI guidance when they know where to find it and check it. Other consistent predictors of the three dependent variables included experience with prior smoke-related health impacts, smoke risk perceptions, and use of internet/mobile applications as sources of smoke information. These findings indicate that increased promotion of AQIs may benefit parents in some regions during wildfires. Future evaluations of smoke education initiatives could help health agencies share effective practices across jurisdictions and target interventions to increase AQI adoption.

Vrinda Ravi Kumar, Shyamsunder Buddh, Shivansh Singhal et al.

Evolutionary rescue helps populations survive environmental change, but the phenotypic and demographic factors associated with rescue dynamics and its long-term effects remain unclear. We experimentally evolved 10 wild-collected populations of flour beetles from across India in a suboptimal corn resource for 70 generations (>5 years), collecting >10,000 population census points book-ended by measurements of fitness-related traits for 30 experimental lines. Despite clear ancestral trait differences, all lines showed highly parallel evolutionary rescue within 20 generations. Long-term average population size varied across source populations and was positively correlated with ancestral development rate, which increased convergently across populations and emerged as the single best predictor of population performance during and after evolutionary rescue. Notably, specific demographic events during rescue (such as the rate of population decline and recovery) were uncorrelated both with ancestral trait distributions and post-rescue adaptation. Our results support prior work showing founder traits as key predictors of adaptation, and highlight their role in long-term adaptation and trait evolution following evolutionary rescue. SIGNIFICANCE STATEMENT Understanding how populations adapt to sudden environmental change is vital given accelerating biodiversity declines, the rise of antimicrobial resistance and climate change. We chart evolutionary rescue — where rapid adaptation prevents extinction — in flour beetles across 70 generations. Using >10,000 census points and measuring fitness in ancestors, their offspring and in evolved lines, we show that larval development rate is the strongest correlate of long-term population success across diverse wild-collected populations. The effect of ancestral variation is dynamic and disassociated from finer-grained details of the rescue. All populations show highly parallel evolutionary rescue, with convergent evolution in key traits. These findings have direct implications for predicting species’ survival after environmental change, ranging from conservation to pest and pathogen management.

Ryo Yamaguchi, Hidaka Kubo, Tokuya Ogawa et al.

Speciation—the process by which new species arise—is fundamentally influenced by population‐level factors, such as population size and demographic dynamics. Here, we review how population size and its dynamics shape speciation mechanisms and the generation of biodiversity across evolutionary scales. Small populations can undergo rapid genetic changes via drift and founder events, potentially promoting speciation, whereas large populations harbor greater genetic diversity and adaptive potential, influencing divergence in different ways. We examine how genetic drift and gene flow interact to facilitate or impede speciation under various scenarios and how extinction risk during adaptation affects the development of reproductive isolation. Finally, we explore how speciation rates and the persistence of populations/species over time are related in theoretical models. We highlight insights from mathematical models—especially those explicitly incorporating population size—and identify open questions for future research.

Gavin Long, Evgeniya Lukinova, John Harvey et al.

Introduction & Background Climate change represents one of the most pressing challenges of our time. Within this context, the food sector is a critical domain for intervention, accounting for approximately one-third of global greenhouse gas emissions. While consumers increasingly express concern about environmental issues, they often lack access to transparent, actionable information about the environmental footprint of their food choices. Objectives & Approach This study integrates environmental impact data of grocery products with digital footprint data from a major UK retailer to analyse sustainable food purchasing patterns. Through advanced text processing techniques including natural language processing (NLP) algorithms and machine learning classification models, we established comprehensive product mappings across retailers using product name similarity matching and category classification. Environmental impact scores were calculated based on life cycle assessment (LCA) data encompassing carbon footprint, water usage, and land use metrics, weighted by product-specific environmental intensity factors. These scores were merged with transactional shopping data for over 4 million loyalty card holders covering the period from July 2019 to December 2021. The analysis examines spatio-temporal variations in food-related environmental impacts across British neighbourhoods, at the Lower and Middle Super Output Area levels, incorporating area-level socioeconomic status (SES) data, such as the 2019 Indices of Deprivation, to explore demographic patterns in consumption behaviours and their associated environmental impact. Relevance to Digital Footprints Analysis of grocery transactions by loyalty card members demonstrates the ability of digital footprint data to be an effective method for visualising variations in the environmental footprint of food purchases at the local level and highlighting seasonal variations in environmental impacts. Results Mapping the normalised results shows wide divergences of environmental impact across neighbourhoods and seasons. Areas with above-average levels of animal-based products have higher environmental footprints, with a notable correlation between higher socio-economic status areas and increased consumption of environmentally intensive products per pound spent. Despite red meat having a significantly higher impact than other foods, it is often foods with lower environmental impact, like dairy products, that are responsible for much of the environmental footprint due to their higher levels of overall consumption. Seasonal analysis reveals distinct patterns: environmental impacts peak during winter months (December-February), potentially due to increased consumption of imported produce and processed foods, while summer months show reduced impacts likely coinciding with greater consumption of locally-sourced fresh produce. Conclusions & Implications The development of cross-retailer product datasets through text-based matching and machine learning techniques enables broader application of retailer-specific environmental impact data. This methodology mitigates single-source bias and enhances the generalizability of research findings. Our spatiotemporal analysis reveals that environmental footprints are primarily driven by consumption volume, with significant seasonal variations observed at the neighbourhood level and notable socio-economic disparities in consumption patterns of high-impact animal-based foods like red meat and dairy products.

Raquel Zanatta Coutinho, Fabiana Ferreira Guimarães, Michelle Elaine Siqueira Ferreira

Este estudo analisa dados da pesquisa “Percepção das mulheres sobre a assistência obstétrica e suas consequências para a saúde da mulher e da criança em Belo Horizonte”, que coletou depoimentos de 100 mulheres (20 a 47 anos) em processo de abortamento, atendidas em hospitais de Belo Horizonte (Brasil) entre janeiro de 2018 e abril de 2021. Investigou-se a ocorrência de violência obstétrica utilizando a tipificação de Bohren et al. (2015). No Brasil, há garantia de direito à assistência humanizada em todas as etapas do abortamento (diagnóstico, manejo e pós-evento). Contudo, foram encontradas violações categorizadas como: abuso físico; abuso sexual; abuso verbal; estigma e discriminação; falhas no padrão do cuidado profissional; comunicação deficiente entre mulher e prestador do serviço; e restrição de serviços. Os resultados podem subsidiar ações de saúde para promover informações corretas, reduzir desigualdades no acesso e melhorar a qualidade do atendimento.

Josep Grau-Bové, Mara Cruz, Pakhee Kumar

The National Covid Memorial Wall in London, featuring over 240,000 hand-painted red hearts, faces significant conservation challenges due to the rapid fading of the paint. This study evaluates the transition to a better-quality paint and its implications for the wall's long-term preservation. The rapid fading of the initial materials required an unsustainable repainting rate, burdening volunteers. Lifetime simulations based on a collections demography framework suggest that repainting efforts must continue at a rate of some hundreds of hearts per week to maintain a stable percentage of hearts in good condition. This finding highlights the need for a sustainable management strategy that includes regular maintenance or further reduction of the fading rate. Methodologically, this study demonstrates the feasibility of using a collections demography approach, supported by citizen science and social media data, to inform heritage management decisions. An agent-based simulation is used to propagate the multiple uncertainties measured. The methodology provides a robust basis for modeling and decision-making, even in a case like this, where reliance on publicly available images and volunteer-collected data introduces variability. Future studies could improve data within a citizen science framework by inviting public submissions, using on-site calibration charts, and increasing volunteer involvement for longitudinal data collection. This research illustrates the flexibility of the collections demography framework, firstly by showing its applicability to an outdoor monument, which is very different from the published case studies, and secondly by demonstrating how it can work even with low-quality data.

Johanna Hartke

Planetary nebulae (PNe) are valuable spatial and kinematic tracers of nearby galaxies. In this mini-review, I focus on their role in tracing the halo and intra-cluster/intra-group light assembly in groups and clusters of galaxies within 100~Mpc and, in particular, the link between characteristic PN metrics such as the $α$-parameter and the PN luminosity function and changes from the underlying in-situ to ex-situ stellar populations. These results from nearby groups and clusters are placed into context with integral-field spectroscopic surveys of galaxies, which allow the co-spatial measurement of PN and stellar population properties. I provide an outlook on upcoming instrumentation that will provide new opportunities for the study of extragalactic PN populations. I address the challenges of reconciling observations of extragalactic PN populations with predictions from stellar evolution models and how revised late-stellar-evolution models have alleviated some of the tensions between observations and theory.

C. Nanayakkara, Peter Christen, Chris Dibben et al.

ObjectivesReconstructing populations by linking vital event records can facilitate a variety of studies including the analysis of hereditary illnesses and socioeconomic changes. We present a record linkage framework to identify siblings, which is a first step in population reconstruction, applied on a Scottish database spanning nearly 120 years. MethodsPairwise comparison of records to identify matches (siblings) and non-matches (non-siblings) is not scalable to large population databases containing millions of records. We therefore apply a novel blocking approach based on Locality Sensitive Hashing to reduce the comparison space, and employ multiprocessing techniques to further improve scalability. In addition to calculating attribute similarities to determine whether a record pair is a match or not, to improve linkage quality we also incorporate temporal constraints (such as siblings born three months apart being not feasible). The final linkage results are stored in a Neo4j graph database to facilitate querying and visualisation. ResultsWe apply our record linkage framework on vital event records (around 14 million birth, 8 million death, and 4 million marriage certificates) from Scotland to identify records that correspond to sibling groups. We generate a similarity graph, with nodes representing records and edges corresponding to similarities, by comparing over 150 million record pairs using attributes that are expected to be similar for siblings (such as mother's name and parents' marriage place). Using graph-clustering techniques we then group records such that each cluster represents a sibling group. We independently link birth, death, and marriage certificates for sibling group generation to create complementary results, which we then use to identify high confidence links. We also employ unsupervised evaluation techniques to assess the quality of our linkage results. ConclusionLarge-scale population record linkage is non-trivial due to quality and scalability challenges. We propose a scalable and effective population linkage framework for identifying siblings by linking and clustering vital event records. We store our linkage outcomes in a graph database to facilitate visualisation and research based on reconstructed populations.

N. Jones, David S. Gilliam

The size structure of stony coral populations can reveal underlying demographic barriers to population growth or recovery. Recent declines in coral cover from acute disturbances are well documented, but few studies have assessed size structure and the demographic processes that determine population growth. Vital rates, such as recruitment and survival, vary spatially and temporally in response to environmental conditions, in turn influencing assemblage composition. The Southeast Florida Coral Reef Ecosystem Conservation Area (Coral ECA) is a high-latitude reef system offshore of a heavily urbanized coastline. Consecutive heat stress events, stony coral tissue loss disease (SCTLD), and Hurricane Irma caused significant declines in stony coral cover and density from 2014 to 2018. The recovery potential of stony coral assemblages is influenced by their composition, the size structure of the remnant populations, and population growth during inter-disturbance periods. To assess the viability of the remaining stony coral assemblages in the Coral ECA, we quantified variation in stony coral recruit density, abundance, size structure, and assemblage composition across depth and latitude at permanent sites over 3 years (2019–2022) when no disturbances occurred. We found spatial decoupling in recruit density, adult colony density, and cover that maintains a preponderance of small colonies and skewed size structure. At sites close to shore where recruit density was higher, there was limited evidence of survival and growth of recruits, while at sites where large colonies were sampled or cover was relatively high, there was limited recruitment. The majority (>75%) of recruits sampled were Siderastrea siderea, but size frequency distributions were positively skewed and the coefficient of variation was high, suggesting high recruit/juvenile colony mortality and little growth into larger size classes. Porites astreoides size structure was generally lognormal and mesokurtic, particularly closer to shore, suggesting a transition between size classes. Skewness decreased moving offshore in Montastraea cavernosa and S. siderea, suggesting a transition between size classes. Recruit and adult diversity also increased moving offshore, but recruits of most species were uncommon throughout the study area. We suggest that low recruitment and high mortality, particularly in small colonies and inshore, even during inter-disturbance periods, limit the population growth of stony coral assemblages in southeast Florida.

Martin Andrzejak, Tiffany M Knight, Carolin Plos et al.

Abstract Climate change is one of the largest threats to grassland plant species, which can be modified by land management. Although climate change and land management are expected to separately and interactively influence plant demography, this has been rarely considered in climate change experiments. We used a large‐scale experiment in central Germany to quantify the effects of grassland management, climate change, and their joint effect on the demography and population growth rate of 11 plant species all native to this temperate grassland ecosystem. We parameterized integral projection models with five years of demographic data to project population growth rate. We hypothesized that plant populations perform better in the ambient than in the future climate treatment that creates hotter and drier summer conditions. Further, we hypothesized that plant performance interactively responds to climate and land management in a species‐specific manner based on the drought, mowing, and grazing tolerances as well as the flowering phenology of each species. Due to extreme drought events, over half of our study species went quasi extinct, which highlights how extreme climate events can influence long‐term experimental results. We found no consistent support for our expectation that plants perform better in ambient compared with future climate conditions. However, several species showed interactive responses to the treatments, indicating that optimal management strategies for plant performance are expected to shift with climate change. Changes in population growth rates of these species across treatments were mostly due to changes in plant reproduction. Experiments combined with measuring plant demographic responses provide a way to isolate the effects of different drivers on the long‐term persistence of species and to identify the demographic vital rates that are critical to manage in the future. Our study suggests that it will become increasingly difficult to maintain species with preferences for moister soil conditions, and that climate and land use can interactively alter demographic responses of the remaining grassland species.

T. Kłosiewicz, Sandra Śmigasiewicz, Hanna Cholerzyńska et al.

Background Cardiac arrest constitutes a critical medical emergency necessitating swift intervention to reinstate normal heart rhythm and prevent harm to vital organs. The pivotal role of bystander cardiopulmonary resuscitation (CPR) in influencing survival rates is well recognized. With older adults being the most common group to witness such events, it’s curcial to understand their attitudes and knowledge about performing CPR. Additionally, understanding if health status has an influence can help in tailoring education for specific seniors needs. Methods A cross-sectional survey was sent to University of the Third Age (UTA) students. The survey comprised sections focusing on demographic data, CPR knowledge, automated external defibrillator (AED) knowledge, first aid training, and readiness to perform CPR and use AEDs. Participants’ health conditions were also assessed through multiple-choice options. Results We received 456 responses. Significant awareness of emergency numbers and cardiac arrest recognition was revealed. However, knowledge gaps persisted, particularly in compression rates. Most participants comprehended AED usage, yet training primarily relied on theoretical approaches. Health conditions notably affected CPR readiness, with associations between specific chronic diseases and willingness to perform CPR. Conclusions Addressing knowledge gaps and tailoring education for elderly needs are crucial for improving survival rates. Future research should explore barriers to bystander CPR during out-of-hospital cardiac arrests to further enhance survival prospects.

Elizabeth Nelson

Over the last decade there has been an increasing focus on utilising government-held data for large-scale data linkage research projects, with an emphasis on public benefit. Most, if not all, administrative data research initiatives will recognise public involvement and engagement (PI&E) as a cornerstone of research and emphasise that administrative data is essentially public data, and, therefore, that publics must have a say in how it is used. Much of this focuses on engaging with communities and their representative organisations. What is less explicitly discussed is the role that data-driven research plays within a broader public realm that is increasingly driven by data, or datafied. This paper will examine the ways in which PI&E both challenges and contributes to the datafication of society, through the work of the Administrative Data Research Centre Northern Ireland (ADRC NI), part of ADR UK. It will explore if – and how  – PI&E in administrative data research can play a role in democratising this datafied society. The paper will use the Northern Ireland Public Data Panel (NIPDP) and the Voices of Young People in Care (VOYPIC) initiative as case studies to explore the ways in which ADRC NI successfully or unsuccessfully create sites of democratisation within the data ecosystem. Finally, the paper will consider how to amplify the democratic benefits of PI&E in data-driven research while minimising any potential harms, in the form of a potential framework for data justice within PI&E in data-driven research.

Aude Bernard, Jing Wu, Tom Wilson et al.

BACKGROUND: To enhance its data capability, Australia recently set up a longitudinal administrative micro-dataset, the Person Level Integrated Data Asset (PLIDA). OBJECTIVE: To ensure that users in both scholarly and applied settings understand how PLIDA can be reliably used, we assess its Combined Location Module, which provides place of residence by combining three administrative datasets since 2006. METHODS: Using descriptive statistics and regression analysis, we compare the population coverage of PLIDA to the census, estimate the incidence of missing values at various spatial scales, quantify spatial mismatch between PLIDA and the census, and compare the intensity, selectivity, and spatial patterns of internal migration between the two datasets. RESULTS: The PLIDA population is higher than the census population, but very remote populations and recently arrived and temporary migrants are under-represented. We uncover a high mismatch rate between PLIDA and the census for small spatial units, particularly among highly mobile groups. As a result, PLIDA overestimates the level of internal migration and slightly distorts migration age patterns at young ages. Migration patterns are broadly comparable at large spatial scales, except for rapidly growing peri-urban regions, inner cities with short-term residents, and regions with a seasonal or temporary workforce. CONCLUSIONS: PLIDA can be used in some applied settings outside demography if the spatial scale of analysis is aggregated, the analysis is restricted to census respondents, or the analysis is limited to well-represented groups. However, in its current form PLIDA is not suitable for demographic applications such as internal migration estimates, and we discourage its use for population projections. CONTRIBUTION: Researchers need to be aware of the pitfalls of administrative data to knowingly decide on appropriate use. We recommend researchers to keep abreast of developments by the Australia Bureau of Statistics, which is continuously improving PLIDA.

Ellie Johnson, Nevil Pierse, Chisholm Chisholm

Objectives It is estimated that around 30,000 New Zealand (NZ) children are hospitalised each year for preventable conditions related to poor-quality housing. To combat the high levels of housing-related illness in NZ, the Healthy Homes Initiative (HHI) was established. The HHI is a government-funded, multicomponent housing intervention programme operating with the aim of reducing the incidence of housing-related illness in children. The objective of this study was to evaluate the impact of the HHI programme on health outcomes of participating families. Approach The Integrated Data Infrastructure (IDI) is a database of linked microdata maintained by Statistics NZ. Deidentified HHI referral data were linked to the IDI, and we used government administrative data to explore the impact of the HHI on health outcomes. Results The HHI dataset linked to the IDI provided referral information for over 21,000 participants of the programme. Characteristics of the cohort included a higher proportion of participants who identified as Māori or Pacific Islander and lower socio-economic status than the general NZ population. Odds ratios were calculated for all variables in the model and showed lower odds of hospitalisation associated with participation in the HHI programme. Conclusion This study demonstrates how housing-intervention programmes can improve health outcomes for those at risk of illness related to housing. These programmes are imperative for addressing the burden of disease and significant health inequities driven by exposure to substandard housing in NZ. This study shows how data linkage methods and administrative data can be used to evaluate large-scale government housing programmes.

Charlotte E. Regan, B. Sheldon

Climate models, and empirical observations, suggest that anthropogenic climate change is leading to changes in the occurrence and severity of extreme climatic events (ECEs). Effects of changes in mean climate on phenology, movement, and demography in animal and plant populations are well documented. In contrast, work exploring the impacts of ECEs on natural populations is less common, at least partially due to the challenges of obtaining sufficient data to study such rare events. Here, we assess the effect of changes in ECE patterns in a long‐term study of great tits, near Oxford, over a 56‐year period between 1965 and 2020. We document marked changes in the frequency of temperature ECEs, with cold ECEs being twice as frequent in the 1960s than at present, and hot ECEs being ~three times more frequent between 2010 and 2020 than in the 1960s. While the effect of single ECEs was generally quite small, we show that increased exposure to ECEs often reduces reproductive output, and that in some cases the effect of different types of ECE is synergistic. We further show that long‐term temporal changes in phenology, resulting from phenotypic plasticity, lead to an elevated risk of exposure to low temperature ECEs early in reproduction, and hence suggest that changes in ECE exposure may act as a cost of plasticity. Overall, our analyses reveal a complex set of risks of exposure and effects as ECE patterns change and highlight the importance of considering responses to changes in both mean climate and extreme events. Patterns in exposure and effects of ECEs on natural populations remain underexplored and continued work will be vital to establish the impacts of ECEs on populations in a changing climate.

G. Brooks, Houston C. Chandler, Yan Jiao et al.

Population viability analyses (PVAs) represent a key component of many recovery plans for threatened and endangered species. Demography links the processes that affect individuals to population‐level patterns, and hence projections constructed from demographic data are the most common tools for PVAs. We constructed a size‐structured integral projection model (IPM) for the United States federally endangered Reticulated Flatwoods Salamander, Ambystoma bishopi, to evaluate demographic influences on population growth and predict the efficacy of future management actions. Flatwoods salamanders breed in ephemeral wetlands in the Southeastern United States. The ephemeral nature of breeding sites can result in complete recruitment failure in drought years when wetlands fail to fill, or dry before metamorphosis occurs. As a result, this species exhibits marked temporal variability in vital rates that must be accounted for in projection models. We constructed a stochastic IPM using 13 years of mark‐recapture data (2010–2023) from two breeding wetlands. Variable survival rates exhibited by flatwoods salamanders, coupled with a high probability of recruitment failure, result in a low predicted probability of population persistence. Sensitivity analyses revealed age at maturity and the frequency of recruitment exerted the greatest influence on population growth, and thus managers should prioritize conservation efforts that target these demographic processes. Additional management should consider strategies to dampen temporal variability in larval survival, something that could be achieved through emergency salvage operations, captive rearing efforts, and manipulation of wetland hydroperiods.

Peter Okoth

Civil registration is a fundamental process that captures vital events such as births, deaths, marriages, and divorces, enabling governments to create accurate demographic databases and deliver essential services to their citizens. However, in today's digital age, civil registration systems face numerous security challenges that jeopardize the integrity and confidentiality of vital information. This paper highlights some of the key security challenges encountered in civil registration systems and outlines potential strategies to address them. Firstly, the digitization of civil registration processes has opened new avenues for cyber threats. Malicious actors may attempt to compromise the security of databases, manipulate or steal vital records, or disrupt services through cyberattacks. Robust cybersecurity measures, including encryption, firewalls, intrusion detection systems, and regular security audits, are essential to safeguard sensitive data and ensure the continuity of civil registration operations. Secondly, the issue of identity theft poses a significant challenge to civil registration security. Fraudulent practices, such as the creation of fake identities or the alteration of existing records, can undermine the trustworthiness of the system and lead to the misallocation of resources. The implementation of identity verification mechanisms, such as biometrics or unique identifiers, can enhance the accuracy and integrity of civil registration data while reducing the risk of identity fraud. Thirdly, ensuring the privacy and confidentiality of individuals' personal information is critical in civil registration systems. With the increasing digitization and interconnectedness of data, there is a heightened risk of unauthorized access or data breaches. Strong data protection regulations, robust access controls, and encryption techniques can help mitigate these risks, fostering public trust and confidence in civil registration processes. Moreover, the challenge of inclusivity must be addressed to ensure the effectiveness and reliability of civil registration systems. Marginalized populations, including refugees, migrants, and those residing in remote areas, may face barriers in accessing civil registration services, leaving them vulnerable to identity-related challenges. Deploying mobile registration units, leveraging innovative technologies, and promoting community engagement are strategies that can improve inclusivity and extend the benefits of civil registration to all individuals.

A. Forrester

Vincenzo Iannuzzi, Maria Giulia Bacalini, Claudio Franceschi et al.

Abstract Sex differences in human survival have been extensively investigated in many studies that have in part uncovered the biological determinants that promote a longer life in females with respect to males. Moreover, researches performed in the past years have prompted increased awareness about the biological effects of environmental factors that can modulate the magnitude of the sex gap in survival. Besides the genetic background, epigenetic modifications like DNA methylation, that can modulate cell function, have been particularly studied in this framework. In this review, we aim to summarize the role of the genetic and epigenetic mechanisms in promoting female advantage from the early in life (“INNATE” features), and in influencing the magnitude of the gap in sex differences in survival and ageing (“VARIABLE” features). After briefly discussing the biological bases of sex determination in humans, we will provide much evidence showing that (i) “innate” mechanisms common to all males and to all females (both genetic and epigenetic) play a major role in sex differences in lifespan; (ii) “variable” genetic and epigenetic patterns, that vary according to context, populations and exposures to different environments, can affect the magnitude of the gap in sex differences in survival. Then we will describe recent findings in the use of epigenetic clocks to uncover sex differences in biological age and thus potentially in mortality. In conclusion, we will discuss how environmental factors cannot be kept apart from the biological factors providing evidence from the field of human ecology.

Mauro N. Sanchez, Priscila F.P.S. Pinto, Camila S.S. Teixeira et al.

Objectives Mitigating the socioeconomic determinants of Tuberculosis (TB) and systematic screening of contacts and high-risk groups are targets of The World Health Organization (WHO) End TB Strategy by 2035. Our aim was to link socioeconomic information to TB datasets to inform policy makers in Brazil and contribute to addressing current challenges. Approach Following a signed technical cooperation agreement with the Ministry of Health (MoH), we linked nationwide data on 1.405.682 registries of TB diagnosed between 2004 and 2019 in Brazil to 131.697.800 demographic and socioeconomic registries from the 100 Million Brazilian Cohort (2001-2018) previously linked to nationwide mortality data. We established close links with TB managers to understand the database, clean and deduplicate registries and to analyse the data. We took advantage of the data structure, to set up a cohort of household contacts of TB patients and produce estimates of TB incidence by subgroups of demographic and socioeconomic characteristics. Results The interaction of the MoH was effective and facilitated by a robust TB Programme in the country. 567.999 (40,41%) TB cases were linked to the 100 Million Brazilian Cohort with high specificity (93.6%) and sensitivity (94.6%). Using family identifiers, we established the first TB case within a family unit (i.e., primary case) and followed their household contacts up to 15 years. We found the TB incidence among household contacts to be 427.8/100.000 person-years (95%CI 419.1-436.8). In the first year following the identification of the primary case, there was higher cumulative incidence among household contacts under 5 years of age, which was followed by a plateau of cases in this age group. Cummulative incidence in the other age groups presented a constant increase over time. Conclusion The close collaboration with the MoH, the development of an effective linkage algorithm and the availability of large socioeconomic data allowed for a unique analysis of the high incidence of TB among household contacts. Findings reinforce need for constant dialogue among stakeholders to strengthen case detection by primary health care.