Environmental Determinants Research Articles

Tailored Multifaceted Strategy for Implementing Fundamental Evidence-Based Nursing Care: An Evaluation Study

Background/Objectives: Extensive research has emphasised the persistent challenges and failures in providing hospitalised patients with fundamental evidence-based nursing care, often resulting in grave consequences for patient safety. Recommendations from implementation research indicate that a tailored theory- and research-based implementation strategy targeting contextual determinants can optimise the implementation of evidence-based clinical practice for the benefit of patients. This study evaluated the feasibility of an implementation strategy designed to improve the quality of nursing care by targeting behavioural and environmental barriers in a hospital setting. Methods: Proctor’s conceptual model for implementation was applied to evaluate the strategy based on eight outcomes: adoption, acceptability, appropriateness, fidelity, feasibility, penetration, sustainability, and costs. Data collection methods included field observations, informal and focus group interviews, registrations, and audits of electronic patient records. Results: The strategy was adoptive, acceptable, appropriate, and feasible in targeting complex environmental and behavioural determinants (at the individual, team, and management level), enabling successful implementation of fundamental evidence-based nursing care. However, fidelity, feasibility, and sustainability were challenged by competing organisational demands and time constraints. Conclusions: The tailored, multifaceted strategy proved effective in addressing complex environmental and behavioural determinants across multiple levels, facilitating the implementation of fundamental evidence-based nursing care in a clinical practice. Further testing and larger-scale studies is needed to assess the strategy’s transferability and its impact on nursing-sensitive patient outcomes in different clinical settings.

DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data

BackgroundMetabolomics is a high-throughput technology that measures small molecule metabolites in cells, tissues or biofluids. Analysis of metabolomics data is a multi-step process that involves data processing, quality control and normalization, followed by statistical and bioinformatics analysis. The latter step often involves pathway analysis to aid biological interpretation of the data. This approach is limited to endogenous metabolites that can be readily mapped to metabolic pathways. An alternative to pathway analysis that can be used for any classes of metabolites, including unknown compounds that are ubiquitous in untargeted metabolomics data, involves defining metabolite-metabolite interactions using experimental data. Our group has developed several network-based methods that use partial correlations of experimentally determined metabolite measurements. These were implemented in CorrelationCalculator and Filigree, two software tools for the analysis of metabolomics data we developed previously. The latter tool implements the Differential Network Enrichment Analysis (DNEA) algorithm. This analysis is useful for building differential networks from metabolomics data containing two experimental groups and identifying differentially enriched metabolic modules. While Filigree is a user-friendly tool, it has certain limitations when used for the analysis of large-scale metabolomics datasets.ResultsWe developed the DNEA R package for the data-driven network analysis of metabolomics data. We present the DNEA workflow and functionality, algorithm enhancements implemented with respect to the package’s predecessor, Filigree, and discuss best practices for analyses. We tested the performance of the DNEA R package and illustrated its features using publicly available metabolomics data from the environmental determinants of diabetes in the young. To our knowledge, this package is the only publicly available tool designed for the construction of biological networks and subsequent enrichment testing for datasets containing exogenous, secondary, and unknown compounds. This greatly expands the scope of traditional enrichment analysis tools that can be used to analyze a relatively small set of well-annotated metabolites.ConclusionsThe DNEA R package is a more flexible and powerful implementation of our previously published software tool, Filigree. The modular structure of the package, along with the parallel processing framework built into the most computationally extensive steps of the algorithm, make it a powerful tool for the analysis of large and complex metabolomics datasets.

Environmental determinants of the incidence of stunting in the working area of the Tempino Health Centre, Mestong District, Muaro Jambi Regency, 2024

Stunting is a condition where a child's body size is not appropriate for their age. The consequences of malnutrition, infection, and poor social life can have long-term impacts, such as depression, loss of cognitive and mental functions. The prevalence of stunting in the Tempino Health Center Working Area in 2023 was 2.63%. This study aims to determine the relationship between environmental sanitation and the incidence of stunting in the Tempino Community Health Center Working Area, Mestong District, Muaro Jambi Regency This type of quantitative research with a case control design. The population was 100 and the sample size was 66 respondents with a ratio of 1: 1 taken with the Total Sampling technique. There is a significant relationship between the physical quality of clean water (P-Value = 0.000; (OR) = 12.880), household wastewater disposal system (P-Value = 0.003; (OR) = 5.714), latrine building (P-Value = 0.003; (OR) = 5.333) with the incidence of stunting. There was no association between household waste bins (P-Value = 0.573 (OR) = 0.619 (0.203-1.892), hand washing with soap (P-Value = 0.240; OR) = 0.411) with the incidence of stunting among children under five.

The Nutrition Society Satellite Symposium, Nutrition Congress: Workplace diet and health.

The workplace is a key environmental determinant of health and wellbeing. Food choices can be influenced by several workplace related factors including, but not limited to, working hours, the workplace food environment, job roles and workplace culture. Therefore, the workplace is increasingly viewed as an important place for public health nutrition interventions. However, research in this area is fragmented and heterogeneous due to the wide range of workplace settings and occupational groups. This editorial summarises the research presented at The Nutrition Society Workplace Diet and Health Special Interest Group Satellite Symposium in July 2024 as part of the inaugural Nutrition Society congress.

Geographic disparities and determinants of full utilization of the continuum of maternal and newborn healthcare services in rural India

BackgroundTo further reduce maternal and neonatal mortality, it is essential for mothers and newborns to fully utilize all essential services within the continuum of maternal and newborn care. However, research on maternal and child health services in India has not sufficiently examined geographical disparities in the full utilization of these services and the factors influencing the full utilization, particularly in rural areas. This study aims to address this critical gap.MethodsUtilizing data from 130,312 mothers collected in the National Family Health Survey-5 (2019–21), this study employed spatial analysis to uncover geographical disparities in the full utilization of the continuum of maternal and newborn healthcare services in rural India. Additionally, binary logistic regression was used to identify the factors associated with this utilization.ResultsIn rural India, 54.3% mothers recieved four or more antenatal care visits, 88.6% received skilled birth attendance, and 75.5% of mothers and 79.8% of newborns received postnatal care within 48 hours of birth. However, only 43.5% mothers-newborn dyads in rural India utilized all four services of the continuum of maternal and newborn healthcare. There were significant geographical disparities in the full utilization of the continuum of maternal and newborn healthcare services. Hotspots were primarily identified in districts of southern states, western Maharashtra, and central Odisha, while cold spots were evident in the northeastern states of Arunachal Pradesh, Meghalaya, Assam, and Nagaland, as well as in the Empowered Action Group states of Bihar, Uttar Pradesh, and Jharkhand. Key determinants influencing the full utilization of the continuum of care in rural India included maternal education, household wealth, parity, health insurance coverage, and exposure to mass media. Specifically, the odds of fully utilizing the continuum of care were significantly lower among women without formal education (adjusted odds ratio = 0.60, 95% CI = 0.56–0.65), those from the poorest wealth quintile (0.65, 0.61–0.69), and mothers with six or more children (0.42, 0.37–0.47), compared to mothers with higher education, those in the richest wealth quintile, and mothers with a single child, respectively. Additionally, mothers from the southern region were more than twice as likely (2.11, 1.99–2.20) to fully utilize the continuum of healthcare services compared to mothers from the northern region.ConclusionThe significant geographical disparities in the full utilization of maternal and newborn healthcare services in rural India highlight the necessity for tailored, region-specific interventions. Future programs should focus on addressing the barriers to care by prioritizing vulnerable groups, including those who are poor, uninsured, less educated, adolescents, and women with high parity.

Influence of climatic variables on biome transitions in the COLOMBIAN and PANAMANIAN Caribbean region

Disentangling the environmental determinants of tropical biomes is crucial for understanding their response to climate change. This study investigated the effect of climate and soil-related variables on biome transitions in the Caribbean region of Colombia and Panama, focusing on xerophytic forest (XF), tropical dry forest (TDF), and tropical rainforest (TRF). We analyzed the climatic variables at different time scales (daily, seasonal, and annual) and their interaction with soil properties. We performed an ordinal logistic regression to assess the combined effect of the most important variables in biome transitions. Our results showed that climate variables are major discriminators in our study region, particularly precipitation at a seasonal and annual scale. The ordinal logistic regression highlighted the significance of annual precipitation and dry-season length in biome transitions, with maximum temperature impacting TDF-TRF transitions. Soil differences, although present (e.g., higher sand content in XF), played a marginal role. Overall, our findings emphasize the dominance of climate over soil in shaping tropical biome distributions in the northern Caribbean part of South America. These findings contribute to a deeper understanding of tropical biome responses to climate change.

139 mySkin: a co-designed self-report longitudinal cohort study to understand environmental determinants of psoriasis onset and progression

139 mySkin: a co-designed self-report longitudinal cohort study to understand environmental determinants of psoriasis onset and progression

Spirulina platensis: Unveiling Phenotypic Plasticity impact on its Metabolic Profile and Bioactivity Via Chemometric Analysis

Spirulina platensis, a blue-green microalgae, is commonly cultivated for its nutritional benefits. it exhibits remarkable phenotypic plasticity. This study investigated the impact of environmental factors on the morphological features, phytochemical constituents, and bioactivity of two spirulina strains, SP1 and SPM2, cultivated under different climates in Egypt: Bilbeis (Nile Delta) and Alexandria (North Coast), respectively. Despite sharing 95% similarity in genetic profile using ISSR-PCR, these strains manifested distinct microscopic variations. Their phytochemical profiles, analysed using HPLC-PDA, revealed high amino acids and carotenoid content. Moreover, comprehensive metabolic profiling for both strains via UPLC-ESI-MS/MS exhibited substantial similarities and differences in their chemical profiles. The in vitro antioxidant and anti-inflammatory activities characterized this functional biochemical variation, where SP1 was superior to SPM2. Further, a positive correlation exists between the detected bioactive metabolites and the observed biological activities. Such findings underscore the substantial impact of environmental determinants on spirulina bioactivity, regardless of its genotype. Also, it highlights the selection strategies to optimize the health-promoting potential of spirulina for functional food applications. Notably, it is the first approach to compare metabolic profiling for both strains cultivated in different climates correlated to their biological activity via chemometric analysis.

Population trends of insect pollinators in a species-rich tropical rainforest: stable trends but contrasting patterns across taxa.

Recent reports of insect decline have raised concerns regarding population responses of ecologically important groups, such as insect pollinators. Additionally, how population trends vary across pollinator taxonomic groups and degree of specialization is unclear. Here, we analyse 14 years of abundance data (2009-2022) for 38 species of native insect pollinators, including a range of Coleoptera, Lepidoptera and Hymenoptera specialists and generalists from the tropical rainforest of Barro Colorado Island, Panama. We estimated population trends across taxonomic groups to determine whether specialist species with a narrower range of interacting mutualistic partners are experiencing steeper population declines under environmental change. We also examined the relationship between climate variables and pollinator abundance over time to determine whether differences in sensitivity to climate predict differences in population trends among pollinator species. Our analyses indicated that most pollinator populations were stable or increasing, with few species showing evidence of decline, regardless of their degree of specialization. Differences in climate sensitivity varied among pollinator species but were not associated with population trends, suggesting other environmental factors at play for tropical insect pollinators. These results highlight the need for long-term population data from diverse tropical taxa to better assess the environmental determinants of insect pollinator trends.

Application of Isotope Ratio Mass Spectrometry (IRMS) in The Geographical Determination of Selected Herbs: A Review

Application of Isotope Ratio Mass Spectrometry (IRMS) in The Geographical Determination of Selected Herbs: A Review

Geographic Determinants and Spatial Epidemiology of Prescription Drug Abuse: A Comprehensive Analysis of Distribution Patterns, Treatment Accessibility and Intervention Strategies

This study examines the complex spatial patterns and geographic variations in prescription drug abuse, analyzing their impact on treatment outcomes and public health interventions. Through comprehensive spatial epidemiological analysis, we investigate how geographic factors influence abuse patterns across urban, suburban, and rural landscapes. The research synthesizes data on healthcare accessibility, socioeconomic conditions, and regional policy frameworks to understand their collective impact on prescription drug misuse. Our findings reveal significant geographic disparities in treatment accessibility, with rural areas facing substantial barriers to addiction services compared to urban centers. Analysis of prescription drug monitoring programs demonstrates varying effectiveness across regions, highlighting the need for spatially-tailored interventions. The study identifies distinct regional profiles of drug misuse, influenced by factors including healthcare infrastructure, cultural norms, and local regulatory environments. Advanced spatial analysis techniques, including geospatial mapping and hotspot analysis, revealed significant correlations between geographic determinants and abuse patterns. Results indicate that proximity to healthcare facilities, pharmaceutical distribution networks, and demographic characteristics contribute to localized risk profiles. The integration of multiple data sources, including prescription records and treatment admissions, provided insights into space-time clustering of abuse patterns. This research emphasizes the importance of developing geographically-informed approaches to combat prescription drug abuse, suggesting that intervention strategies should be tailored to specific regional contexts while addressing broader systemic issues. The findings have significant implications for public health policy, healthcare resource allocation, and the development of targeted prevention strategies.

Public Initiatives to Combat Health Disinformation in Argentina and Spain: A Gender, Social, and Environmental Analysis

Introduction: Public health disinformation is a significant problem as demonstrated by the recent scientific literature on the COVID-19 pandemic. However, further studies that analyse disinformation in public health initiatives within specific contexts and which contains a multidimensional approach (gender, social and environmental) are required. Evidence shows that disinformation, information overload, misinformation or fake news on health issues are also influenced by these issues. Objective: To analyse health disinformation in national public initiatives implemented by the governments of Argentina and Spain before, during and after the COVID-19 pandemic. Additionally, this paper incorporated a gender-based approach and social and environmental determinants in order to identify the limitations of these initiatives and offer certain recommendations. We conducted a descriptive, qualitative and quantitative study, as well as content analysis. We focused on documents from the websites of the national health ministries of Argentina and Spain, and digital repositories of regulations at the national level. Various strategies for systematic searches on government websites were designed and implemented. This included manual searches on Google. The first step involved a general analysis of all documents found by the searches, followed by a qualitative analysis of the documents that were related to health issues. Based on this work, a comprehensive and flexible framework of (pre-established and emerging) dimensions and categories of health disinformation and infodemics was generated. Results. The work was based on a total of 202 documents (both downloadable information and information included in websites); 117 for Argentina and 85 for Spain. Of the total, 60.9% were published during the COVID-19 pandemic. In the second stage of the analysis, 55 texts were selected for Argentina and 47 for Spain. In both countries, the central communications approach used was disinformation and/or infodemics (although definitions such as fake news were also used). They were mainly linked to the COVID-19 pandemic, but other emerging health problems were also detected to a lesser degree. However, disinformation (or a related concept) was prominently present in only 17 documents in Argentina and 3 documents in Spain. In terms of document type, working materials were foremost in Argentina (44.4%) and Spain (37.6%), with little presence of policy, regulatory and evaluation documents (only 5). Gender binary language was predominantly used in these texts. Vulnerable groups and social determinants were poorly included. Environmental determinants were mentioned in conjunction with health disinformation in only one paper on the use of plastics and its impact on human health in Argentina, and in another paper from the Global Summit on Climate and Health in Spain. Conclusions: Based on the document analysis, the inclusion of health disinformation within public actions in both countries before, during and after the COVID-19 pandemic, was detected. However, different limitations were observed: it was clear that the problem was strongly linked to the health emergency and did not extend much beyond that. Health disinformation was secondary and did not play a key role in public policy nor did it have greater institutional importance. Limitations were also detected in terms of gender perspectives, vulnerable groups and social and environmental determinants linked to health disinformation, displaying a reductionist approach. Based on these results, this paper makes certain policy recommendations.

Intervention Mapping for Refining a Sport-Based Public Health Intervention in Rural Schools

Sport-based youth development programs, delivered through campus–community partnerships, can create impactful experiences for college students, meet university objectives, and improve the health of children in under-resourced rural communities. This study aimed to pilot test intervention mapping (IM), a systematic approach to intervention development and implementation, to refine the Hoosier Sport intervention, which is a local public health initiative that utilizes the Obesity-Related Behavioral Intervention Trials (ORBITs) model to improve physical activity in middle school children. The IM process, which included a diverse IM planning and advisory group of university representatives and local schools, was guided by self-determination theory (SDT) and social cognitive theory (SCT) and followed four steps: Logic Model of the Problem, Logic Model of Change, Program Design, and Program Production. Using SDT and SCT, we identified our personal determinants as autonomy, competence, and relatedness, while our environmental determinants were role-modeling and sports equipment access. We then created change methods and practical applications for refining and implementing our intervention and gathered pilot test data to assess the feasibility of the intervention. The IM process provided a more robust and evidence-based approach to intervention design and production, while involving stakeholders to foster meaningful collaboration and increase program success. By using IM in program development, public health interventions that promote youth development through sport will likely be more easily scaled up.

DE-PASS Best Evidence Statement (BESt): Determinants of self-report physical activity and sedentary behaviours in children in settings: A systematic review and meta-analyses.

Previous physical activity interventions for children (5-12yrs) have aimed to change determinants associated with self-report physical activity behaviour (PAB) and/or sedentary behaviour (SB), however, the associations between these determinants and PAB/SB in different settings are uncertain. The present study aimed to identify modifiable determinants targeted in previous PAB/SB interventions for children. Intervention effects on the determinants and their associations with self-report PAB/SB were assessed across settings. Search of relevant interventions from pre-defined databases was conducted up to July 2023. Randomized and non-randomized controlled trials with modifiable determinants were included. Data extraction and risk of bias assessments were conducted by two independent researchers. Where data could be pooled, we performed Robust Bayesian meta-analyses. Heterogeneity, publication bias and certainty of evidence were assessed. Fifteen studies were deemed eligible to be included. Thirty-seven unique determinants within four settings were identified-school, family, school with family/home, and community with(out) other settings. Ninety-eight percent of determinants belonged to individual/interpersonal determinant categories. Narratively, intervention effects on student perception of teachers' behaviour (school), self-management, perceived barriers, external motivation, exercise intention, parental modeling on SB (school with family/home) and MVPA expectations (community) were weak to strong, however, corresponding PAB/SB change was not evident. There were negligible effects for all other determinants and the corresponding PAB/SB. Meta-analyses on self-efficacy, attitude, subjective norm and parental practice and PAB/SB in two settings showed weak to strong evidence against intervention effect, while the effect on knowledge could not be determined. Similarly, publication bias and heterogeneity for most analyses could not be ascertained. We found no concrete evidence of association between the modifiable determinants and self-report PAB/SB in any settings. This is presumably due to intervention ineffectiveness. Design of future interventions should consider to follow the systems-based approach and identify determinants unique to the context of a setting, including policy and environmental determinants.

The Prevalence of Stunting in Indonesia: An Examination of the Health, Socioeconomic Status, and Environmental Determinants

Background: Stunting is a significant public health concern in Indonesia. It represents a form of chronic malnutrition that manifests not only as a short stature for one’s age, but also as a profound challenge affecting children’s physical and cognitive development. This study aims to provide more research basis for the government to formulate stunting policies by exploring the ecological factors associated with stunting, consistent with the goal of reducing stunting according to Sustainable Development Goals (SDGs) targets by 2030. Methods: Data were collected on stunting and ecological factors from 34 provinces in Indonesia from 2015-18, sourced from Statistics Indonesia and the Ministry of Health. A framework of ecological factors that influence stunting, consisting of health, socioeconomic status, and the environment was developed. A panel data model to test the influence of each ecological factor on stunting was created. Results: Among the 27 independent variables of health, economic status, and environment, the results of this study show that malnutrition, diarrhea, dependency ratio, and hygiene significantly affect the risk of stunting. Meanwhile, antenatal care, nurses, and sanitation have an effect on reducing the risk of stunting. Conclusion: To achieve the SDGs targets associated with malnutrition by 2030, addressing stunting in Indonesia requires a comprehensive and multisectoral approach that addresses the fundamental causes of stunting, including health, socioeconomic status, and environmental factors. Addressing stunting is crucial for Indonesia, not only to improve the health and well-being of its children, but also for the long-term benefits of enhancing educational outcomes and economic productivity.

Protocol of the Nutritional, Psychosocial, and Environmental Determinants of Neurodevelopment and Child Mental Health (COINCIDE) study

Background Over 250 million children are developing sub-optimally due to their exposure to early life adversities. While previous studies have examined the independent effects of nutritional status, psychosocial adversities, and environmental pollutants on children’s outcomes, little is known about their interaction and cumulative effects. Objectives This study aims to investigate the independent, interaction, and cumulative effects of nutritional, psychosocial, and environmental factors on children’s cognitive development and mental health in urban and rural India. It also seeks to explain pathways leading to inequities in child outcomes at the individual, household, and neighbourhood levels. Methods A mixed-methods prospective cohort study will be conducted on 1600 caregiver-child dyads (child age 3–10 years) in urban and rural India. Nutritional status, psychosocial adversities, environmental pollutants, and child mental health outcomes will be assessed using parent-report questionnaires. Performance-based measures will be used to assess cognitive outcomes. Venous blood and urine samples will be used to measure nutritional and pesticide biomarkers in 500 children. Indoor air pollution will be monitored in 200 households twice, during two seasons. Multilevel regression, weighted quantile sum regression, and Bayesian kernel machine regression will assess the individual and combined effects of exposures on child outcomes. Thematic analysis of in-depth interviews and focus group discussions will explore pathways to middle-and late childhood development inequities. Discussion The data will be used to formulate a Theory of Change (ToC) to explain the biological, psychosocial, and environmental origins of children’s cognitive and mental health outcomes across the first decade of life in diverse Indian settings, which can inform interventions targets for promoting children’s outcomes beyond the first 1000 days, potentially generalizable to similar under-resourced global settings. The COINCIDE research infrastructure will comprise a valuable global health resource, including prospective cohort data, validated study tools, and stored biological and environmental samples for future studies.

Mapping urban health policies: A scoping review of environmental, behavioural and socioeconomic determinants of health

Researchers have consistently shown that determinants of health—factors beyond healthcare, including the built environment and socioeconomic conditions— significantly impact health outcomes. This understanding has led to a growing trend in recent decades towards policy discourse that links determinants of health with health outcomes. However, the scientific community's access to these policies in a structured and systematised manner remains limited. The importance of this gap cannot be overstated, as information about which determinants of health are discussed and prioritised in policy agendas is spread across various documents from different organisations, making it difficult to address relevant policy questions promptly. A scoping review of urban health policies was conducted following JBI guidelines to bridge this gap. The aim was to create a structured framework that outlines the environmental, behavioural, and socioeconomic determinants of health included in policy agendas, as well as how they are understood and prioritised, their relationships with each other and with health outcomes, and how they vary across different geographic and governance levels. Using content analysis methods, 128 policy documents from intergovernmental, national, regional, and local governance levels were analysed, covering the World and European region and the cities of London, Lisbon, and Copenhagen from 2010 to 2022. The review identified 83 determinants of health employed in policy discourse, categorising them into nine priority themes: healthy diet; drug, alcohol, and tobacco; social cohesion; physical activity; safety; active travel; natural and open spaces; environmental exposures; and basic services. These determinants of health were organised in a structured framework to illustrate their perceived relationships with each other, the priority themes, and health outcomes, as well as their prioritisation in policy discourse based on their frequency of use in urban health policy. This review represents the first comprehensive scope of how determinants of health are employed in policy discourse. The resulting conceptual framework offers a remarkably comprehensive mapping of the systemic relations between determinants of health and health outcomes, which forms a valuable tool for guiding research and practice on the policy-suggested complex multivariate causal pathways between variables. This framework provides a foundation for systematically exploring previously challenging questions, such as how research evidence is being translated into policy discourse and which aspects of this discourse are being implemented into action. Moreover, the scoping review and content analysis protocol can be replicated in other geographic regions, providing insights into potential outcome variations.

Unlocking data: Decision-maker perspectives on cross-sectoral data sharing and linkage as part of a whole-systems approach to public health policy and practice.

Secondary data from different policy sectors can provide unique insights into the social, environmental, economic and political determinants of health. This is especially pertinent in the context of whole-systems approaches to healthy public policy, which typically combine cross-sectoral collaboration with the application of theoretical insights from systems science. However, the sharing and linkage of data between different sectors are still relatively rare. Previous research has documented the perspectives of researchers and members of the public on data sharing, especially healthcare data, but has not engaged with relevant policy and practice decision-makers. We sought to work collaboratively with decision-makers relevant to healthy public policy and practice in Scotland to identify practical ways that cross-sectoral data sharing and linkage could be used to best effect to improve health and reduce health inequalities. We facilitated three sequential stakeholder workshops with 20 participants from local and central government, public health teams, Health and Social Care Partnerships, the third sector, organisations which support data-intensive research and public representatives from across Scotland. Workshops were informed by two scoping reviews (carried out in June 2021) and three case studies of existing cross-sectoral linkage projects. Workshop activities included brainstorming of factors that would help participants make better decisions in their current role; reflective questions on lessons learnt from the case studies; and identifying and prioritising recommendations for change. Findings were synthesised using thematic analysis. Scotland; public and third sector data. Based on the workshops, and supported by the reviews and case studies, we created a visual representation of the use of evidence, and secondary data in particular, in decision-making for healthy public policy and practice. This covered three key overarching themes: differing understandings of evidence; diverse functions of evidence; and factors affecting use (such as technical, political and institutional, workforce and governance). Building on this, workshop participants identified six guiding principles for cross-sectoral data sharing and linkage: it should be pragmatic; participatory; ambitious; fair; iterative; with holistic and proportionate governance. Participants proposed 21 practical actions to this end, including: a strategic approach to identifying and sharing key data sets; streamlining governance processes (e.g. through standardised data sharing agreements; central data repositories; and a focus on reusable data resources) and building workforce capacity. To make these possible, participants identified a need for strong political and organisational leadership as well as a transparent and inclusive public conversation. Participation from some stakeholders was limited by workload pressures associated with the COVID-19 pandemic. No consensus was reached on the impact, effort, and/or timing of some recommendations. Findings were closely informed by the Scottish context but are nonetheless likely to be relevant to other jurisdictions. There is broad consensus among key stakeholders that linked cross-sectoral data can be used far more extensively for public health decision-making than it is at present. No single change will lead to improved use of such data: a range of technical, organisational and political constraints must be addressed. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number NIHR133585.

Natural variation in timing of egg hatching, response to water agitation, and bidirectional selection of early and late hatching strains of the malaria mosquito Anopheles gambiae sensu lato

BackgroundEggs of anopheline mosquitoes hatch within a few days of laying and require high levels of humidity to survive. Assessing natural variation in egg hatching and its environmental and genetic determinants in sibling species of the malaria vector Anopheles gambiae s.l. is important for understanding their adaptation to variable aquatic habitats. Crucially, it can also inform insectary rearing practices toward the optimization of mosquito production for genetic vector control strategies.MethodsHatching rates and timing of egg hatching in long-established and recently colonized strains of An. gambiae s.s, Anopheles arabiensis, and Anopheles coluzzii, were compared under still water conditions (26 ℃) and with cold (4 ℃) and (15 ℃) water agitation regimes. Next, early and late hatching strains of the recently colonized An. coluzzii VK colony were generated through bidirectional selection for 18–23 generations to detect a genetic component for this trait.ResultsHatching rates differed significantly between species and treatments. The older An. arabiensis Senn and An. gambiae s.s. Kisumu strains had the highest proportion of hatching and preferred the nonagitation treatment at 26 °C. In contrast, the more recently colonized An. coluzzii VK and An. arabiensis Rufisque strains had lower overall hatching success but responded strongly to agitation at 4 °C, while the An. coluzzii Mopti strain did not significantly respond to water agitation. In all strains, eggs hatching started at day 2 and continued till day 5 in the older strains, whilst it was more staggered and extended up to day 6 in the younger strains. Bidirectional selection for early and late hatching over many generations resulted in early hatching selected strains with eggs hatching 2–3 days earlier than in late hatching ones indicating a significant heritable component for these traits.ConclusionsWater agitation and temperature and age of colonization are likely important determinants of egg hatching in natural An. gambiae s.l. populations. Current rearing protocols systematically select for fast hatching and result in the progressive loss of staggered egg hatching in older laboratory strains. The selection of novel slow-hatching strains may prove instrumental to enable the mass production, shipping, and release of Anopheles mosquitoes across Africa as part of genetic vector control programs.Graphical

Understanding the Role of Social Determinants in Shaping Chronic Disease Outcomes: A Comprehensive Review

This review explores the influence of social determinants of health (SDH) on chronic disease outcomes, focusing on the interconnected roles of socioeconomic status, physical environment, community context, education, healthcare access, and behavioral determinants. Chronic diseases—such as cardiovascular disease, diabetes, and respiratory conditions—pose a significant public health challenge, with social determinants increasingly recognized as critical factors in shaping their prevalence, progression, and management. This review synthesizes findings from recent studies to elucidate how SDH create disparities in chronic disease outcomes, particularly among marginalized populations. We examine mechanisms linking SDH to chronic disease, including biopsychosocial and behavioral pathways, and discuss implications for public health interventions and policy-making. Addressing these social determinants through comprehensive public health strategies could help reduce the burden of chronic diseases, improve health equity, and support healthier communities.