Health & Place

Greenspace has been associated with a wide range of health outcomes and conditions related to functional limitation and disability. Yet less is known about how the spatial morphology of greenspace relates to disability prevalence across different stages of the life course. This study examines associations between greenspace morphology and disability prevalence among children, working-age adults, and older adults in urban census tracts across the contiguous United States. Using national land-cover data, we quantified morphological metrics at the census-tract level, including greenspace percentage, density, mean size, connectedness, shape complexity, inter-greenspace distance, and diversity. These indicators were linked with age-specific disability prevalence obtained from the American Community Survey. Spatial lag regression models were used to account for spatial dependence while adjusting for socio-demographic and contextual characteristics. Across age groups, higher greenspace percentage was consistently associated with lower disability prevalence (children: {beta} = -0.081, 95% CI: -0.096 to -0.066; adults: {beta} = -0.804, -0.858 to -0.750; older adults: {beta} = -1.132, -1.250 to -1.013). Among children, patch density ({beta} = -0.045, -0.061 to -0.029), mean patch area ({beta} = -0.029, -0.040 to -0.018), connectedness ({beta} = -0.051, -0.069 to -0.032), diversity ({beta} = -0.036, -0.051 to -0.020), and inter-greenspace distance ({beta} = 0.056, 0.039 to 0.073) were all associated with disability prevalence, whereas shape complexity was not ({beta} = 0.004, -0.010 to 0.018). Among working-age adults, associations were observed for mean area ({beta} = -0.023, -0.090 to -0.002), connectedness ({beta} = -0.127, -0.243 to -0.011), shape complexity ({beta} = -0.123, -0.174 to -0.072), diversity ({beta} = -0.146, -0.201 to -0.091), and inter-greenspace distance ({beta} = 0.151, 0.059 to 0.242), whereas patch density was not significantly associated with disability prevalence ({beta} = -0.013, -0.048 to 0.022). In older adults, all examined greenspace morphology metrics showed significant associations with disability prevalence, including patch density ({beta} = -0.445, -0.842 to -0.049), diversity ({beta} = -0.126, -0.188 to -0.065), and inter-greenspace distance ({beta} = 0.455, 0.409 to 0.501). Overall, the findings suggest that higher greenspace percentage, larger patch size, greater connectedness, greater diversity, and more spatially clustered greenspace distributions are associated with lower disability prevalence across the life course, although the strength and consistency of these associations varied across age groups. The study provides national-scale evidence for incorporating greenspace morphology into urban planning and public health strategies to support more inclusive and health-supportive urban environments.

Ambient temperature is emerging as an environmental factor that may influence cognitive performance in ageing populations. This is particularly relevant in Australia, where people live across diverse climatic regions spanning alpine to tropical conditions. We examined daily temperatures and cognitive performance in 1,873 midlife and older adults (1,297 women, mean age 61.0 years) who completed the Creyos online battery (formerly Cambridge Brain Sciences). Twelve tasks assessed memory, visuospatial processing, language, attention, and executive function. Task scores were linked to postcode-level contemporaneous weather data. The scores were analysed in relation to maximum and minimum air and wet-bulb temperatures and postcode- and month-relative temperature percentiles. Regression models adjusted for age, sex, education, socioeconomic status, and climate zone, with season included for air and wet-bulb measures. Higher minimum, but not maximum, temperature was associated with poorer performance on Paired Associates, a task assessing associative memory. This pattern was observed for air temperature, wet-bulb temperature, and temperature percentile, suggesting poorer memory performance after warmer nights, both in absolute terms and relative to local seasonal norms. Temperature was not significantly associated with performance on any other task, including measures of short-term/working memory, visuospatial processing, language, attention, or executive function. These findings suggest a task-specific association between higher overnight temperature and poorer associative memory performance, rather than a general reduction in cognition. Further studies incorporating personal exposure and sleep measures are needed to clarify whether night-time thermal conditions affect cognitive health in midlife and older populations.

Urban mobility may provide insight into population health by capturing how residents connect to services, resources, and urban systems. This is relevant for communities facing higher disease burden and limited resources, where reduced connectivity may signal barriers to care, healthy environments, and participation. Mobility patterns are furthermore shaped by socioeconomic position, housing, environmental quality, facilities access, lifestyle patterns, and population composition. Mobility-health associations may therefore reflect underlying social and environmental disadvantage rather than mobility itself, risking misdirected public-health policy responses. This ecological cross-sectional study examined associations between aggregated mobile phone-based mobility and health outcomes in The Hague, Netherlands, from January-July 2019. Mobile phone mobility was measured as mean outgoing mobility distance across eight regions. Contextual and health indicators were available at neighbourhood-level and were aggregated or linked to regions where required. Health outcomes were operationalised as indicators of disease burden, including cardiometabolic medication prescriptions, polypharmacy, and a syndemic-based measure of interacting health conditions. Contextual domains were selected using spatial clustering and ordinary least squares models, after which residual mobility-health associations were assessed. Outgoing mobility varied across regions and was strongly patterned by contextual factors. Lifestyle, housing, physical environment, and income accounted for 73.2% of variance in outgoing mobility. After adjustment, residual mobility showed weak, non-significant associations with cardiometabolic medication prescription, polypharmacy, and the syndemic-based measure. Sensitivity analyses supported these findings. Aggregated mobility should not be interpreted as a straightforward independent determinant of health. Instead, it appears to function as an integrative marker of urban context, spatial structure, and population composition.

Residential greenness has been associated with reduced heat-related illness, yet the specific role of greenspace morphology at the neighborhood scale remains insufficiently understood. This study quantified the relationship between heat-related illness and multiple dimensions of greenspace morphology using an eight year (2016-2023) unbalanced panel dataset comprising 19,021 block group year observations across 2,427 census block groups in Arizona, USA. One meter high resolution National Agricultural Imagery Program aerial imagery was classified to calculate greenspace percentage, number of greenspaces, average size, shape complexity, connectedness, and distantness, at the block group level. We applied conditional spatial autoregressive models with a negative binomial distribution to estimate associations between each morphology metric and yearly heat-related illness counts, adjusting for sociodemographic and geographic covariates. We found higher greenspace percentage, aggregation, shape complexity, connectedness, and density were consistently associated with lower heat-related illness risk. A one standard deviation increases in shape complexity corresponded to a 12.4% decrease in expected heat-related illness counts (IRR=0.876, 95% CI: 0.834-0.921). Similarly, increases in greenspace percentage (14.6% decrease; IRR=0.855, 95% CI: 0.827-0.885), number of greenspace patches (3.7% decrease; IRR=0.963, 95% CI: 0.937-0.990), average size (4.5% decrease; IRR=0.955, 95% CI: 0.923-0.989), and connectedness (5.5% decrease; IRR=0.945, 95% CI: 0.918-0.972) were all protective. In contrast, larger inter greenspace distances were associated with increased heat-related illness risk (6.1% increase; IRR=1.061, 95% CI: 1.033-1.091). Our findings highlight the critical importance of multiple dimensions of greenspace morphology in mitigating heat-related health risks. These results suggest that heat reduction planning with greening initiatives should consider not only the amount of greenspace but also its spatial configuration to maximize cooling and result in health benefits.

Background: The traditional wealth index, based on principal component analysis (PCA), used in the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), suffers from urban bias, distorting estimates of health inequality. We compared the traditional index (PEAR1) with an alternative two-component polychoric PCA index (POLY2) using annual expenditure from 12 LSMS surveys as the gold standard to determine which provides more accurate SEP measures for equitable policy targeting. Methods: We compared the traditional wealth index (PEAR1) with a two-component polychoric PCA approach (POLY2) using 12 LSMS (Living Standards Measurement Study) surveys (2015-2022) from 12 African countries. Annual household consumption expenditure was the gold standard. We assessed agreement using weighted Cohen's kappa and validated against education (proportion of households with secondary or higher education) using the concentration index (CIX) and slope index of inequality (SII). Results: The POLY2 index showed higher agreement with expenditure quintiles (average national weighted kappa = 43.3%) than the PEAR1 index (35.1%), with notable improvements in urban (43.5% vs. 27.5%) and rural (35.3% vs. 22.4%) areas. POLY2 also attenuated extreme household distributions observed in PEAR1. Education validation showed that POLY2 produced intermediate inequality gradients between the flatter expenditure-based gradient and the steeper PEAR1-based gradient. Conclusion: The POLY2 wealth index is superior to the traditional index, reducing urban-rural bias and providing more accurate socioeconomic classifications. Its adoption in large-scale surveys such as DHS and MICS is recommended to improve equitable monitoring of health inequalities in low- and middle-income countries.

Summary Background: Spatial variation in heat-related mortality remains poorly understood, particularly at fine geographical scales. We conducted a nationwide small-area study to examine the association between spatial variation in heat-related mortality and environmental, demographic, health, and socio-economic factors. Methods: We obtained daily all-cause mortality data for people aged [≥] 65 years during the summers of 2011-2023 and linked them with municipality-level daily temperature estimates from the ERA5-Land reanalysis dataset. We applied a two-stage Bayesian hierarchical model to estimate small-area heat-related mortality and assess the contribution of community characteristics to spatial variability. Findings: Heat-related mortality showed marked geographical differences, with the highest rates in southern and southeastern Italy. Across municipalities, the relative risk at the 90th temperature percentile, relative to the minimum mortality temperature, ranged from 1.06 to 1.33. The heat-attributable fraction exceeded 6% in several southern municipalities, while excess mortality surpassed 8 deaths per 1,000 inhabitants in parts of the Po Valley, Tuscany, Apulia, and Sicily. National heat-attributable mortality peaked in 2022, with an estimated 17,828 deaths (95% credible intervals: 17,339, 18,285) among older adults. Municipalities with higher average temperatures, less green space, higher obesity prevalence, and more residents aged [≥] 85 years had higher heat-related mortality. Educational attainment and employment were among the strongest modifiers of spatial variation. Interpretation: Our findings highlight substantial small-area differences in heat-related mortality across Italy and identify socio-economic deprivation as a key determinant of vulnerability. Heat is likely to disproportionately affect disadvantaged communities, reinforcing the need for adaptation strategies addressing social inequality. Funding: Imperial College Research Fellowship; Italian Ministry of Health PNC (CUP J55I22004450001); NIHR Imperial Biomedical Research Center (BRC NIHR203323).

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

Maternal depressive symptoms are a major public health concern in low- and middle-income countries (LMICs), yet evidence on their relationship with early childhood development (ECD) remains mixed. This study examined the association between maternal depressive symptoms and ECD outcomes during infancy and toddlerhood, and whether household composition moderated these associations. Additionally, we examined whether child stimulation activities were associated with ECD outcomes across both timepoints. We analysed data from 769 mother-child dyads drawn from a cluster-randomised controlled trial conducted in the Cajamarca region of Peru. Maternal depressive symptoms were assessed during infancy (approximately 5 months) using the DASS-21 depression subscale. Child development was assessed during infancy (mean age 5.2 months) using the CREDI and during toddlerhood (mean age 28.7 months) using the GSED Long Form. Associations were examined using linear regression models, adjusting for demographic, household, social, and caregiving covariates. Effect modification by number of siblings under 6 years and number of adults in the household was assessed. Approximately one in six mothers (17.4%) reported any depressive symptoms. Maternal depressive symptoms were neither associated with child development outcomes in infancy (adjusted {beta} = 0.01, 95% CI [-0.01, 0.01]) nor in toddlerhood (adjusted {beta} = -0.01, 95% CI [-0.07, 0.05]). No significant moderation was observed for either household composition variable. Among the covariates examined in the adjusted models, child stimulation activities showed the strongest independent association with child development at both timepoints, regardless of maternal depressive symptom status. We found no evidence that maternal depressive symptoms were associated with child development during infancy or toddlerhood, and household composition did not moderate these associations. These findings suggest that the relationship between maternal depressive symptoms and early child development may be more complex than previously assumed in this rural Andean context. However, the absence of an association in this study should not be interpreted as evidence that maternal depressive symptoms are unimportant, as previous research has documented important effects on maternal wellbeing, family functioning, and child outcomes.

Climate change draws attention to the planetary health perspective in sport and exercise sciences, that is, to physical activity that supports both human wellbeing and environmental sustainability. Active commuting is a sustainable form of physical activity with well-established somatic health benefits. However, more knowledge is needed on its relationship with mental health. We examined dose-response associations between active commuting, anxiety symptoms, and mental wellbeing among Finnish adults, and whether green commuting environment moderates these relationships. We used data from the cross-sectional Environment and Health Survey collected in June-September 2023 in the ten largest cities in Finland. Employed participants with data on anxiety symptoms (Generalized Anxiety Disorder-7, GAD-7), mental wellbeing (World Health Organization-Five Well-Being Index, WHO-5), commuting profile over a year (mode, frequency, distance, and perceived greenness along the commute route), and sociodemographic and lifestyle factors were included (n=1,672; mean age 45.3 years; 53.8% women). Active commuting was defined as travelling the entire commute by walking or cycling (including e-biking) that was converted into approximated annual km/week and MET-h/week. We used linear and logistic regression with restricted cubic splines to evaluate dose-response associations, adjusted for key covariates. The role of perceived greenness was tested using an active commuting x commute greenness interaction term. We found no dose-response relationships between active commuting and anxiety symptoms or mental wellbeing in any of the models. No effect modification by commute greenness was observed. More research on how active commuting may support planetary health from a mental health perspective is needed.

Aim: Neighbourhood food outlet availability influences dietary behaviours and nutrition related health outcomes. However, food environment research across Europe remains limited by inconsistent spatial data, heterogenous food outlet classifications, and the lack of publicly available high-resolution retail food data. We developed and evaluated a scalable framework to acquire, classify, validate, and analyse food-related points of interest (POIs) from Google Maps across 39 countries in Europe and Turkey. We also developed a method for characterizing the joint co-occurrence of multiple outlet types as neighbourhood-level food environment exposures. Methods: We harmonized ~3.26 million food-related POIs. Outlets were classified into five main categories (cafes and bakeries, restaurants, fast-food and snack outlets, groceries and food retail, and bars and pubs) and 25 subcategories. We assessed data quality against official registers in five regions (the Netherlands, United Kingdom, Denmark, Madrid (Spain), and Brno (Czech Republic)), testing agreement in positional accuracy, completeness, spatial clustering (Nearest Neighbour Index), and spatial density (kernel density estimation (KDE)). To enable cross-country comparisons, POIs were aggregated to national and city scales, with food outlet density calculated as outlets per 1,000 residents and standardised using z-scores. To characterize neighbourhood-level co-exposures, we applied Principal Component Analysis (PCA) followed by Latent Class Analysis (LCA) to z-standardized outlet densities across 500 m hexagonal grid cells in eight major European cities. Results: Google Maps data showed high positional accuracy, with 91% of outlets located within 30m of registry records. Completeness varied by region, while KDE comparisons showed moderate-to-strong spatial agreement with city-specific variation. PCA identified two components explaining 68.4% of the variance (PC1: 51.3%, PC2: 17.1%), with PC2 differing between cafe/bar and fast-food/supermarket densities. LCA identified four neighbourhood classes: low-access, moderate-mixed, dining-out, and high-density-mixed. Conclusion: Our harmonized high-resolution framework supports cross-national monitoring of retail food environments and spatial epidemiological research across European settings.

Socioeconomic inequality in exposure to air pollution possess a significant public health challenge, yet little is known about how the disparities vary across the various economic status areas in Nairobi. Globally, studies have shown that exposure to air pollution is unequal across communities hence disparities in harm to human health. This study examined the association between socioeconomic characteristics and perceived air quality among residents of low- and high-socioeconomic status areas in Nairobi, Kenya. Two regions within Nairobi County were selected for this study: Mukuru kwa Njenga (representing the Low Socioeconomic Status) and Langata (representing the High Socioeconomic Status) with a sample size of 384 in HSES areas and 368 in LSES areas. A cross-sectional study was conducted among 752 respondents residing in selected LSES and HSES areas of Nairobi. Data was collected using a structured questionnaire assessing sociodemographic characteristics, income, education, employment, perceived air quality, and self-reported health outcomes associated with air pollution exposure. Descriptive statistics were used to summarize participant characteristics and perceived air quality. Chi-square tests were used to examine associations between residential area and categorical health outcomes, while ordinal logistic regression was used to assess the association between socioeconomic characteristics and perceived air-quality ratings. Perceived air quality differed significantly between residential socioeconomic groups. Respondents in LSES areas were more likely to rate air quality as poor or very poor, with 45.4% rating it as very poor, compared with only 1.6% of respondents in HSES areas. In contrast, 12.2% of HSES respondents rated air quality as good compared with 0.3% in LSES areas. The association between area of residence and perceived air-quality rating was statistically significant, {chi}2(3) = 282.672, p < 0.001. In the ordinal logistic regression model, HSES residence was associated with significantly lower odds of reporting poorer perceived air quality compared with LSES residence (OR = 0.135, 95% CI: 0.095-0.190, p < 0.001). Income was also significantly associated with perceived air quality, while respondents with no formal education had higher odds of reporting poorer perceived air quality compared with those with secondary education (OR = 3.254, 95% CI: 1.388-7.638, p = 0.007). Significant differences were also observed for several self-reported health outcomes. Respiratory problems were more prevalent among respondents in LSES areas than HSES areas (72.7% versus 50.4%; {chi}2(1) = 29.081, p < 0.001; Cramer's V = 0.224). However, allergies, eye irritation, and headaches were reported more frequently in HSES areas than in LSES areas, with significant associations observed for allergies ({chi}2(1) = 106.479, p < 0.001; Cramer's V = 0.429), eye irritation ({chi}2(1) = 136.577, p < 0.001; Cramer's V = 0.486), and headaches ({chi}2(1) = 149.180, p < 0.001; Cramer's V = 0.508). No statistically significant association was observed for cardiovascular problems, likely reflecting the very low number of reported cases. Substantial socioeconomic disparities in perceived air quality and self-reported respiratory health outcomes were observed. Residents of low-socioeconomic status areas consistently perceived poorer air quality and reported a higher burden of respiratory problems, highlighting the need for targeted interventions to reduce environmental health inequalities.

Early life adversity is a recognised risk factor for poor health in later life, but its relationship with allostatic load (AL; a measure of cumulative physiological stress) remains underexplored across populations around the world. This study builds evidence to test a life course approach to AL using harmonised data from six longitudinal ageing cohorts: Health and Retirement Study (US, N=2,427), English Longitudinal Study of Ageing (England, N=2,038), The Irish Longitudinal Study on Ageing (Ireland, N=8,184), Survey of Health Ageing and Retirement in Europe (Europe, N=4,079), China Health and Retirement Longitudinal Study (China, N=5,220), and Indonesia Family Life Survey (Indonesia, N=1,243). Childhood information at aged ten to sixteen was collected retrospectively from adults aged 65 on average. An AL score is constructed using biomarker data and a latent construct of early life adversity constructed to address recall bias. Results show that early life poverty is significantly associated with raised AL in Ireland, China, and Indonesia, supporting the impact of early life experiences on older adulthood. However, studies from other countries do not confirm statistical significance. These findings document that experiencing poverty during development phase in some settings is associated with higher AL in later life, however further analyses are required to explore possible variations across different populations and their social and economic context. These results add further evidence that social determinants of health, including child poverty, in some settings, contribute to cumulative physiological stress across the life course, and that policies and actions to reduce child poverty can have beneficial effects not only as children, but also as older adults.

Many urban health outcomes are shaped by environmental stressors that occur together rather than in isolation, yet methods for measuring such co-occurrence at the neighbourhood scale remain underdeveloped. We developed a multi-metric framework for joint co-exposure assessment and applied it to characterise the joint spatial distribution of summer surface heat and fine particulate matter (PM2.5) across 42,304 census tracts in 48 large US metropolitan areas during summers 2015 to 2020, covering approximately 174.6 million residents. The framework combines a composite co-exposure index, a joint exceedance indicator, a conditional exceedance ratio that compares observed joint occurrence to within-group statistical independence, and an upper tail dependence parameter estimated using both the non-parametric Caperaa-Fougeres-Genest estimator and a Gumbel copula, with bias-corrected and accelerated (BCa) confidence intervals obtained from a 5,000-replicate metropolitan-area block bootstrap. Among residents of predominantly Black tracts, 13.21% lived in neighbourhoods that simultaneously exceeded the within-metropolitan-area 80th percentile for both heat and PM2.5, compared with 3.33% of residents of predominantly White tracts; the corresponding heat-only and PM2.5-only ratios were 2.88 and 2.48. Residents of Home Owners Loan Corporation grade D tracts had 3.97 times the odds (95% confidence interval 2.79 to 5.66) of joint hotspot residence compared with grade A residents after adjustment for contemporary tract racial composition, poverty, renter-occupancy, and pre-1960 housing. The within-group conditional exceedance ratio at the 80th percentile was 2.29 in predominantly White tracts (95% BCa CI 1.81 to 2.78), 1.27 in predominantly Black tracts (0.71 to 1.56), and 1.13 in predominantly Hispanic tracts (0.70 to 1.41); the White interval excluded one while the Black and Hispanic intervals included one, which we interpret as power-limited given fewer contributing CBSAs. Magnitudes attenuated under near-surface air temperature surfaces but the direction and statistical significance of the primary findings were preserved. The framework is portable to other compound-exposure questions and supports cumulative-impact assessment.

Homicide is a leading cause of preventable death in the United States and disproportionately affects Black and Indigenous communities. Structural racism and neighborhood disinvestment are central drivers of these disparities, yet national evidence on whether the association between neighborhood opportunity and homicide risk varies by race/ethnicity remains limited. Using 2020 data from the restricted-use National Violent Death Reporting System linked to Child Opportunity Index (COI 3.0) scores and Census population denominators across 30,077 ZIP codes in 48 states, we estimated age-adjusted log-linked generalized linear models to examine racial/ethnic disparities in homicide rates and their interaction with neighborhood opportunity. Black men experienced homicide rates nearly 20 times those of White men; Indigenous men experienced rates approximately 6 times higher. Higher neighborhood opportunity was independently associated with lower homicide risk across all groups and explained 43-59% of excess risk for Black and Indigenous individuals. Crucially, the association between neighborhood opportunity and homicide was nonlinear and significantly heterogeneous by race/ethnicity, with the steepest rate reductions occurring at the lowest opportunity levels for Black and Indigenous men. These findings suggest that place-based investments in severely deprived communities may yield the greatest reductions in homicide and racial/ethnic health inequities.

Background: The retail food environment is a widely used exposure in behavioural-nutrition and obesity research, on the premise that nearby food retailers shape diet and obesity risk. Over the past quarter-century, grocery stores have declined across rural and small-town America while limited-assortment discount ("dollar") stores have proliferated. Standard food-environment indices classify retailers as healthy or less-healthy but typically exclude dollar stores, now the fastest-growing food-retail format. As a result, a single classification decision may alter how the food environment is measured and the conclusions drawn from it. We develop a dollar-aware index, quantify how counting dollar stores changes the measured exposure, and derive a longitudinal trajectory typology. Methods: Using establishment-level data from Data Axle for all 878 Mississippi census tracts (1997-2024), we classified food retailers into five mutually exclusive categories using a previously validated approach and calculated the modified Retail Food Environment Index (mRFEI) in both its standard and dollar-aware forms, with the latter counting dollar stores as less-healthy outlets. We fitted Nagin-style group-based trajectory models to the tract-level dollar-aware index, related class membership to the Social Vulnerability Index (SVI) and urbanicity with multinomial regression, and characterised spatial clustering (Getis-Ord Gi*, join-counts) and grocery access. Results: Grocery stores fell from 1,616 to 716 while dollar stores rose from 315 to 1,005, intersecting in 2018. Counting dollar stores lowered the index by a margin that widened over time, and a growing number of tracts had only dollar-store retail, undefined under the standard index. Six trajectory classes emerged: stable adequate (5.6% of tracts), steady decline (13.1%), early collapse (11.1%), late collapse (6.7%), persistently constrained (34.1%) and chronic desert (29.3%); only the stable-adequate class (5.2% of children) stayed adequate throughout. Constrained and steady-decline membership rose steeply with vulnerability (RRR 11.7 and 9.9); chronic desert was urban (RRR 5.2, a food-swamp pattern); collapse classes had no cross-sectional social signature. Conclusions: In the US state with the highest adult obesity prevalence, a single retailer-classification decision substantially changes the measured food environment. The dollar-aware index and trajectory typology offer a transferable, time-varying exposure for behavioural-nutrition and obesity research and establish a foundation for future childhood-obesity studies.

Urban air pollution remains a significant public health concern, contributing to premature deaths and adverse health outcomes. However, there is little causal research evaluating the effectiveness of policies designed to improve air quality. This study assesses the impact of all three stages of London's Ultra Low Emission Zone (ULEZ) on air pollution, via PM2.5 levels, and respiratory health, via prescription records for bronchodilator and respiratory corticosteroid medications. Analyses are at general practice level, using a generalised synthetic control method to estimate causal impacts. Stage 1 was associated with a statistically significant but negligible 0.77% reduction in PM2.5 levels, with no corresponding change in prescribing. Stage 2 produced a paradoxical 2.69% increase in PM2.5, alongside a 4.44% decrease in inhaled corticosteroid quantity but a 12.51% increase in average daily quantity (ADQ) usage, suggesting a worsening of disease severity among existing patients. Stage 3 yielded a 2.69% PM2.5 reduction and a modest 2.18% decrease in bronchodilator ADQ usage. Spillover effects beyond the ULEZ boundary were statistically significant, but negligible. We find overall that the ULEZ had minimal effects on both air quality and respiratory prescribing across all three stages. These findings provide new insights into the effectiveness of ULEZ policies in reducing air pollution and its associated health impacts, suggesting the zone's effects are considerably smaller than previously reported, and that integration with broader policy measures may be necessary to achieve meaningful public health gains.

Background We examined whether two key housing quality indicators, energy efficiency and household overcrowding, were associated with lower respiratory tract infection (LRTI) hospital admissions in infants. Methods We used a cohort of all singleton births in Scotland 2010-2012, created through linked vital statistics and health data. LRTI admissions were characterised in hospital records. Overcrowding (defined using the national room standard) and median postcode-level energy efficiency were defined using maternal Census and postcode-level Energy Performance Certificate data linked to the cohort, respectively. We used logistic regression to model the odds of at least one infant LRTI admission. Results The cohort included 136,123 infants of whom 4.0% had at least one LRTI admission. Overcrowding was more common among infants of younger mothers and those in rented housing. Energy efficiency was lower among infants of older mothers, living in owner occupied homes, in less deprived areas. Compared with infants living in homes with excess rooms (under-occupied housing), those whose homes were below, or met, the minimum room standard had higher odds of LRTI admission (adjusted odds ratio 1.07, 95% CI 0.98-1.17; 1.10, 95% CI 1.03-1.17, respectively). Postcode-level energy efficiency was not associated with LRTI admission odds. Conclusion Overcrowding was more common in socioeconomically disadvantaged households and associated with increased risk of LRTI admission in infancy. Lower energy efficiency was associated with factors commonly linked to socioeconomic advantage and was not associated with LRTI admissions. Improving access to housing with adequate living space may reduce the burden of LRTIs in early life.

Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Objectives Increased risk of childhood obesity up to age six years has been linked to higher maternal allostatic load (AL), the physical manifestation of repeated stress exposure. However, associations are less evident when using psychological stress indicators, and data mainly come from higher income countries. Using psychological and physiological stress markers, this study evaluates maternal stress exposures and child risk of obesity in Peruvian women and their children, ages 5 to 15 years, living in a disadvantaged urban area. Methods Maternal stress exposures included mental distress (12-item General Health Questionnaire scores of 5+ for moderate/high and <5 for no/low distress) and AL (lower/moderate/higher AL assessed from Latent Profile Analysis of hair cortisol, BMI, waist circumference, systolic and diastolic blood pressure). Child outcomes included BMI-for-age and waist circumference-for-age z scores (BAZ and WCAZ). Linear regression analyses were conducted, adjusting for confounders and reported as coefficients and 95% confidence intervals (95% CI). Results Versus mothers with no/low distress, those with moderate/high distress had children with 0.40 (95% CI: -0.66,-0.13) and 0.32 lower (-0.53,-0.11) child BAZ and WCAZ respectively. Versus lower AL mothers, moderate AL mothers had children with 1.15 (0.41,1.88) and 0.74 (0.20,1.28) greater BAZ and WCAZ while higher AL mothers had children with 1.43 (0.95,1.92) and 0.91 (0.50,1.32) greater BAZ and WCAZ respectively. Conclusions Children of mothers with higher AL were at greater risk of overweight or obesity, which may add to the rising burdens of non-communicable diseases in resource-constrained settings as well as the related social, economic, and public health costs.

Abstract: Introduction: Community-dwelling seniors in Canada face many challenges, including declining oral function, that may substantiate vulnerabilities associated with aging in place like social isolation, impaired mobility, and greater care needs. This study analyzes the effects of functional mouth problems, namely discomfort while eating and avoiding foods while eating due to mouth problems, and additionally poor/fair perceived oral health, on the vulnerability outcomes of loneliness, fear of falling, and receipt of informal home care associated with aging in place among Canadian Seniors. Methods: Secondary analysis of the Canadian Health Survey on Seniors (CHSS), which included information on oral health, socioeconomic status, and daily habits among over 42,000 respondents, allowed assembly of a 32,756-respondent sample set and survey-weighted population estimate post-exclusion. Primary Analysis, using descriptive and regression methods, examined the effects of experiencing discomfort while eating, whilst secondary analysis examined avoidance of foods and perceived oral health values on senior vulnerability outcomes. Results: Both study analyses revealed that all variables associated with oral function exposure were linked to high loneliness and fear of falling, and to receiving informal home care, with the exception of a weaker association between receipt of informal home care and perceived oral health. Discussion: Other studies of oral function and its effects on the vulnerability of the senior population reported findings comparable to this study, indicating that oral functional problems are associated with generally higher vulnerability outcomes. Conclusion: Discomfort while eating and avoiding foods may be potential indicators of vulnerability associated with aging in place among Canadian seniors.