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INTRODUCTION: Protective associations of greenspace with Parkinsons disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization). METHODS: We created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007-2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization. RESULTS: There were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density. CONCLUSION: Increasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas.

Urbanization has altered land surface properties driving changes in micro-climates. Urban form influences peoples activities, environmental exposures, and health. Developing detailed and unified longitudinal measures of urban form is essential to quantify these relationships. Local Climate Zones [LCZ] are a culturally-neutral urban form classification scheme. To date, longitudinal LCZ maps at large scales (i.e., national, continental, or global) are not available. We developed an approach to map LCZs for the continental US from 1986 to 2020 at 100 m spatial resolution. We developed lightweight contextual random forest models using a hybrid model development pipeline that leveraged crowdsourced and expert labeling and cloud-enabled modeling - an approach that could be generalized to other countries and continents. Our model achieved good performance: 0.76 overall accuracy (0.55-0.96 class-wise F1 scores). To our knowledge, this is the first high-resolution, longitudinal LCZ map for the continental US. Our work may be useful for a variety of fields including earth system science, urban planning, and public health.

Abstract Background Polypharmacy and inappropriate drug use are associated with adverse health outcomes in older people. Collaborative interventions between geriatricians and general practitioners have demonstrated effectiveness in improving clinical outcomes for complex medication regimens in home-dwelling patients. Since 2012, Norwegian municipalities have established municipal in-patient acute care (MipAC) units, designed to contribute towards reducing the number of hospital admissions. These units predominantly serve older people who typically benefit from multidisciplinary approaches. The primary objective of this study is to evaluate the effect of cooperative medication reviews conducted by MipAC physicians, supervised by geriatricians, and in collaboration with general practitioners, on health-related quality of life and clinical outcomes in MipAC patients ≥ 70 years with polypharmacy. Additionally, the study aims to assess the carbon footprint of the intervention. Methods This is a randomized, single-blind, controlled superiority trial with 16 weeks follow-up. Participants will be randomly assigned to either the control group, receiving usual care at the MipAC unit, or to the intervention group which in addition receive clinical medication reviews that go beyond what is considered usual care. The medication reviews will evaluate medication appropriateness using a structured but individualized framework, and the physicians will receive supervision from geriatricians. Following the clinical medication reviews, the MipAC physicians will arrange telephone meetings with the participants’ general practitioners to combine their assessments in a joint medication review. The primary outcome is health-related quality of life as measured by the 15D instrument. Secondary outcomes include physical and cognitive functioning, oral health, falls, admissions to healthcare facilities, and mortality. Discussion This study aims to identify potential clinical benefits of collaborative, clinical medication reviews within community-level MipAC units for older patients with polypharmacy. The results may offer valuable insights into optimizing patient care in comparable municipal healthcare settings. Trial registration The study was registered prospectively on ClinicalTrials.gov 30.08.2023 with identifier NCT06020391.

IntroductionOlder adults with higher needs are ideal candidates for social prescribing interventions, given the complex and intersectoral nature of their needs. This article describes findings from a developmental evaluation of 19 social prescribing programs for older adults at risk of frailty. MethodsAn evaluation of the programs was conducted from 2020 to 2023. We used data from three components of the evaluation: (1) initial evaluation data collected in 2020 and 2021; (2) program profiles developed in 2022; and (3) co-creation sessions conducted in 2023. ResultsFrom startup until March 2023, the programs served a total of 2544 older adults. The community connectors identified factors at the individual, interpersonal, institutional, community and policy levels that contributed to the successful implementation and delivery of their programs (e.g. physician champions, communities of practice, strong pre-existing relationships with the health care system), as well as challenges (e.g. limited capacity of family physicians, lack of community resources). There was strong agreement among community connectors that successful social prescribing programs should include the following core elements: (1) making connections to needed community resources; (2) co-creation of a wellness plan with long-term clients or clients who require intensive supports; (3) ongoing follow-up and check-ins for clients with wellness plans; and (4) an assessment and triaging process for the prioritization of clients. ConclusionTo leverage the full potential of social prescribing interventions, it is essential that programs engage with a range of health and social care providers, that community connectors are skilled and well supported, and that adequate investments are made in the nonprofit and voluntary sector.

IntroductionLes aînés ayant des besoins accrus sont des candidats idéaux pour les interventions de prescription sociale, compte tenu de la nature complexe et intersectorielle de leurs besoins. Cet article présente les résultats d’une évaluation de l’élaboration de 19 programmes de prescription sociale destinés aux aînés à risque de fragilité. MéthodologieNous avons effectué une évaluation des programmes pour la période 2020-2023. Nous avons utilisé les données de trois composantes de l’évaluation : 1) les données de l’évaluation initiale, recueillies en 2020 et en 2021, 2) les profils des programmes élaborés en 2022 et 3) les séances de cocréation tenues en 2023. RésultatsDe leur lancement jusqu’au mois de mars 2023, les programmes ont servi 2 544 aînés. Les agents de liaison communautaire ont cerné les facteurs au niveau individuel, au niveau interpersonnel, au niveau des établissements, au niveau de la collectivité et au niveau des politiques qui ont contribué à la mise en oeuvre et à la prestation de leurs programmes (médecins champions, communautés de pratique, solides relations préexistantes avec le système de santé, etc.), de même que les difficultés qui ont été rencontrées (capacité limitée des médecins de famille, manque de ressources communautaires, etc.). Les agents de liaison communautaire ont convenu qu’un programme de prescription sociale efficace devrait comprendre les éléments essentiels suivants : 1) établir des liens avec les ressources communautaires nécessaires, 2) prévoir la cocréation d’un plan de mieux-être avec les clients ayant besoin d’un soutien de longue durée ou intensif, 3) assurer un suivi et des vérifications de façon continuelle dans le cas des clients ayant des plans de mieux-être et 4) prévoir un processus d’évaluation et de triage pour la priorisation des clients. ConclusionPour tirer pleinement parti des possibilités offertes par les interventions de prescription sociale, il est essentiel que les programmes mobilisent un éventail de fournisseurs de soins de santé et de services sociaux, que les agents de liaison communautaire soient qualifiés et bien appuyés et que des investissements adéquats soient faits dans le secteur des organismes à but non lucratif et du bénévolat.

Abstract Background A concentrated transdiagnostic and micro choice-based group treatment for patients with depression and anxiety has previously shown to yield significant reduction in symptoms and increased level of functioning from pre to 3-month follow-up. In the present study, we report the results after 12 months follow-up. Methods This was a non-randomized clinical intervention pilot study, conducted in line with a published protocol. Sixty-seven consecutively referred patients, aged 19–47 (mean age 32.5, SD = 8.0) were included and completed treatment. All had a severity of their problems that entitled them to care in the specialist public mental health care. Self-reported age at onset of symptoms was 17.6 (SD = 7.9) years. Mean number of prior treatment courses was 3.5 (SD = 3.3; range 0–20). The main objective was to assess the treatment effectiveness by questionnaires measuring relevant symptoms at pre-treatment, 7 days-, 3 months-, 6 months- and at 12-months follow-up. Results Validated measures of functional impairment (WSAS), depression (PHQ9), anxiety (GAD7), worry (PSWQ), fatigue (CFQ), insomnia (BIS) and illness perception (BIPQ) improved significantly (p

BackgroundPatients with advanced cancer are prone to develop different opportunistic oral infection due to anti-cancer treatment or the malignancies themselves. Studies of oral fungal samples show an increased prevalence of non-Candida albicans species in mixed oral infections with Candida albicans. Non-C. albicans and C. albicans are associated with varying degrees of resistance to azoles, which may have implications for treatment. This study aimed to assess the diversity and antifungal susceptibility of Candida species detected in the oral cavity.MethodsAn observational study with microbiological analysis was conducted. Clinical fungal isolates were collected from patients in a hospice unit in 2014-2016. Isolates were re-grown on chromID® Candida plates in 2020. Single colony of each species was re-cultivated and prepared for biochemical identification with a VITEK2® system and verified by gene sequencing. Etest was performed on RPMI agar, and the antifungals fluconazole, amphotericin B, anidulafungin and nystatin were applied.ResultsFifty-six isolates from 45 patients were identified. Seven different Candida species and one Saccharomyces species were detected. The results of biochemical identification were confirmed with sequencing analysis. Thirty-six patients had mono infection, and nine out of 45 patients had 2-3 different species detected. Of C. albicans strains, 39 out of 40 were susceptible to fluconazole. Two non-C. albicans species were resistant to fluconazole, one to amphotericin B and three to anidulafungin.ConclusionC. albicans was the predominant species, with a high susceptibility to antifungal agents. Different Candida species occur in both mono and mixed infections. Identification and susceptibility testing may therefore lead to more effective treatment and may prevent the development of resistance among patients with advanced cancer.Trail registrationThe study Oral Health in Advanced Cancer was registered at ClinicalTrials.gov (#NCT02067572) in 20/02/2014.

Background: Exposure to ambient air pollution is associated with a significant number of deaths. Much of the evidence associating air pollution with adverse effects is from North American and Europe, partially due to incomplete data in other regions limiting location specific examinations. The aim of the current paper is to leverage satellite derived air quality data to examine the relationship between ambient particulate matter and all-cause and cause-specific mortality in Asia. Methods: Six cohorts from the Asia Cohort Consortium provided residential information for participants, recruited between 1991 and 2008, across six countries (Bangladesh, India, Iran, Japan, South Korea, and Taiwan). Ambient particulate material (PM2·5) levels for the year of enrolment (or 1998 if enrolled earlier) were assigned utilizing satellite and sensor-based maps. Cox proportional models were used to examine the association between ambient air pollution and all-cause and cause-specific mortality (all cancer, lung cancer, cardiovascular and lung disease). Models were additionally adjusted for urbanicity (representing urban and built characteristics) and stratified by smoking status in secondary analyses. Country-specific findings were pooled via random-effects meta-analysis. Findings: More than 300,000 participants across six cohorts were included, representing more than 4-million-person years. A positive relationship was observed between a 5 µg/m (Dockery et al., 1993) increase in PM2·5 and cardiovascular mortality (HR: 1·06, 95 % CI: 0.99, 1·13). The additional adjustment for urbanicity resulted in increased associations between PM2.5 and mortality outcomes, including all-cause mortality (1·04, 95 % CI: 0·97, 1·11). Results were generally similar regardless of whether one was a current, never, or ex-smoker. Interpretation: Using satellite and remote sensing technology we showed that associations between PM2.5 and all-cause and cause-specific Hazard Ratios estimated are similar to those reported for U.S. and European cohorts. Funding: This project was supported by the Health Effects Institute. Grant number #4963-RFA/18–5. Specific funding support for individual cohorts is described in the Acknowledgements.

Introduction: Protective associations of greenspace with Parkinson’s disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization). Methods: We created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007–2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization. Results: There were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density. Conclusion: Increasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas.

Greenspace may benefit sleep by enhancing physical activity, reducing stress or air pollution exposure. Studies on greenspace and childrens sleep are limited, and most use satellite-derived measures that do not capture ground-level exposures that may be important for sleep. We examined associations of street view imagery (SVI)-based greenspace with sleep in Project Viva, a Massachusetts pre-birth cohort. We used deep learning algorithms to derive novel metrics of greenspace (e.g., %trees, %grass) from SVI within 250m of participant residential addresses during 2007-2010 (mid-childhood, mean age 7.9 years) and 2012-2016 (early adolescence, 13.2y) (N = 533). In early adolescence, participants completed >5 days of wrist actigraphy. Sleep duration, efficiency, and time awake after sleep onset (WASO) were derived from actigraph data. We used linear regression to examine cross-sectional and prospective associations of mid-childhood and early adolescence greenspace exposure with early adolescence sleep, adjusting for confounders. We compared associations with satellite-based greenspace (Normalized Difference Vegetation Index, NDVI). In unadjusted models, mid-childhood SVI-based total greenspace and %trees (per interquartile range) were associated with longer sleep duration at early adolescence (9.4 min/day; 95%CI:3.2,15.7; 8.1; 95%CI:1.7,14.6 respectively). However, in fully adjusted models, only the association between %grass at mid-childhood and WASO was observed (4.1; 95%CI:0.2,7.9). No associations were observed between greenspace and sleep efficiency, nor in cross-sectional early adolescence models. The association between greenspace and sleep differed by racial and socioeconomic subgroups. For example, among Black participants, higher NDVI was associated with better sleep, in neighborhoods with low socio-economic status (SES), higher %grass was associated with worse sleep, and in neighborhoods with high SES, higher total greenspace and %grass were associated with better sleep time. SVI metrics may have the potential to identify specific features of greenspace that affect sleep.

Abstract Urbanization has altered land surface properties driving changes in micro-climates. Urban form influences people’s activities, environmental exposures, and health. Developing detailed and unified longitudinal measures of urban form is essential to quantify these relationships. Local Climate Zones [LCZ] are a culturally-neutral urban form classification scheme. To date, longitudinal LCZ maps at large scales (i.e., national, continental, or global) are not available. We developed an approach to map LCZs for the continental US from 1986 to 2020 at 100 m spatial resolution. We developed lightweight contextual random forest models using a hybrid model development pipeline that leveraged crowdsourced and expert labeling and cloud-enabled modeling – an approach that could be generalized to other countries and continents. Our model achieved good performance: 0.76 overall accuracy (0.55–0.96 class-wise F1 scores). To our knowledge, this is the first high-resolution, longitudinal LCZ map for the continental US. Our work may be useful for a variety of fields including earth system science, urban planning, and public health.

Abstract Background The health care is likely to break down unless we are able to increase the level of functioning for the growing number of patients with complex, chronic illnesses. Hence, novel high-capacity and cost-effective treatments with trans-diagnostic effects are warranted. In accordance with the protocol paper, we aimed to examine the acceptability, satisfaction, and effectiveness of an interdisciplinary micro-choice based concentrated group rehabilitation for patients with chronic low back pain, long COVID, and type 2 diabetes. Methods Patients with low back pain > 4 months sick-leave, long COVID, or type 2 diabetes were included in this clinical trial with pre-post design and 3-month follow-up. The treatment consisted of three phases: (1) preparing for change, (2) the concentrated intervention for 3–4 days, and (3) integrating change into everyday life. Patients were taught and practiced how to monitor and target seemingly insignificant everyday micro-choices, in order to break the patterns where symptoms or habits contributed to decreased levels of functioning or increased health problems. The treatment was delivered to groups (max 10 people) with similar illnesses. Client Satisfaction Questionnaire (CSQ-8)) (1 week), Work and Social Adjustment Scale (WSAS), Brief Illness Perception Questionnaire (BIPQ), and self-rated health status (EQ-5D-5L) were registered at baseline and 3-month follow-up. Results Of the 241 included participants (57% women, mean age 48 years, range 19–84), 99% completed the concentrated treatment. Treatment satisfaction was high with a 28.9 (3.2) mean CSQ-8-score. WSAS improved significantly from baseline to follow-up across diagnoses 20.59 (0.56) to 15.76 (0.56). BIPQ improved from: 22.30 (0.43) to 14.88 (0.47) and EQ-5D-5L: 0.715 (0.01) to 0.779 (0.01)), all P

Background: Despite increased literature focusing on the role of the built environment (BE) in health, few cohort studies have quantitatively analyzed neighborhood walkability environment in relation to the risk of death and cardiovascular disease (CVD). This longitudinal study aimed at evaluating the association between perceived BE attributes with mortality and major CVD based on the Prospective Urban Rural Epidemiology study in China (PURE-China). Methods: The PURE-China study recruited 47,931 participants aged 35–70 years from 12 provinces of China between 2005 and 2009. The perceived BE information, including land use, street, aesthetics, and safety, was collected using the neighborhood environment walkability scale (NEWS) questionnaire, with higher scores indicating a more favorable rating. Two primary outcomes are all-cause mortality and major CVD event. The Cox frailty model with random intercepts was used to assess the association between the perceived total BE/subscales score and outcomes. Results: Of 32,163 participants included in this study, 19,253 (59.9 %) were women, and the mean (SD) age was 51.0 (9.5) years. After a median follow-up period of 11.7 years (IQR 9.4 – 12.2), we observed that one standard deviation higher of combined BE scores was related to a lower risk of all-cause mortality (HR = 0.85; 95 %CI, 0.80–0.90), and major CVD events (HR = 0.95; 95 %CI, 0.90–0.99). The subscales of perceived BE were related to a lower risk, although a few were not significant. Land use mix-diversity and safety from crime were the two most significant subscales. Stronger risks were observed among urban and female participants. Conclusion: Favorable perceived BE characteristics were linked with a lower risk of all-cause mortality and major CVD events in Chinese population, especially in urban areas and females. Our findings can be used by policymakers to take action to mitigate the adverse effect of poor community conditions on health, such as improving local amenities and transport connectivity, providing building paths for walking, running and cycling.

BackgroundAnxiety is prevalent among children and adolescents (termed youths), and leads to reduced quality of life, disability, loss of education and reduced life-span. Physical activity has shown promising effects on symptoms of anxiety in adult populations, and an increasing amount of research has also demonstrated some effect in youth. However, physical activity is not widely used in youth mental health care, and research is very limited.Methods/designThis single arm, pre-post study explores the effect of a manualized physical activity-based 14-session intervention termed Confident, Active and Happy Youth. Participants are youth attending specialized mental health care (N=51, M age = 13.4, SD = 2.2). Changes in anxiety symptoms are examined using mixed models with residual maximum likelihood (REML). The potential effect of anxiety subtype differences, participant age, comorbidity, and time spent in out-patient care are explored.ResultsYouths did not report any effect on anxiety symptoms after participation in CAHY, however, their parents report a significant reduction in youth’s anxiety symptoms in general (b = -0.11, 95%, CI: -0.21 to -0.01) and specifically for social phobia (b = -0.19, 95% CI: -0.35 to -0.03). Age and comorbidity showed no significant effect on anxiety symptoms post treatment. Prior treatment time in youth mental health care demonstrated inconclusive results.ConclusionThe study finds initial evidence of symptomatic change in a clinical population of youth’s receiving a physical activity-based intervention. Our research provides preliminary support for physical activity as a supplementary treatment method for mental health disorders among youths.Clinical Trial Registrationclinicaltrials.gov, NCT05049759

Introduction: Environmental exposures, such as ambient air pollution and household fuel use affect health and under-5 mortality (U5M) but there is a paucity of data in the Global South. This study examined early-life exposure to ambient particulate matter with a diameter of 2.5 µm or less (PM2.5), alongside household characteristics (including self-reported household fuel use), and their relationship with U5M in the Navrongo Health and Demographic Surveillance Site (HDSS) in northern Ghana. Methods: We employed Satellite-based spatiotemporal models to estimate the annual average PM2.5 concentrations with the Navrongo HDSS area (1998 to 2016). Early-life exposure levels were determined by pollution estimates at birth year. Socio-demographic and household data, including cooking fuel, were gathered during routine surveillance. Cox proportional hazards models were applied to assess the link between early-life PM2.5 exposure and U5M, accounting for child, maternal, and household factors. Findings: We retrospectively studied 48,352 children born between 2007 and 2017, with 1872 recorded deaths, primarily due to malaria, sepsis, and acute respiratory infection. Mean early-life PM2.5 was 39.3 µg/m3, and no significant association with U5M was observed. However, Children from households using “unclean” cooking fuels (wood, charcoal, dung, and agricultural waste) faced a 73 % higher risk of death compared to those using clean fuels (adjusted HR = 1.73; 95 % CI: 1.29, 2.33). Being born female or to mothers aged 20–34 years were linked to increased survival probabilities. Interpretation: The use of “unclean” cooking fuel in the Navrongo HDSS was associated with under-5 mortality, highlighting the need to improve indoor air quality by introducing cleaner fuels.

BackgroundThe tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.MethodsWe used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.ResultsAmong the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 μg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively.InterpretationChronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.

Abstract Background Meeting the oral health needs of the increasing population of older adults presents a major challenge in dental care. Knowledge about the oral health status in the young-elderly age group is essential for the planning of future oral health education and prevention programs. The aims of the present study were therefore to investigate the caries experience among 65-year-olds in Oslo, Norway, and to explore associations between having decayed teeth and sociodemographic, behavioural, and biological factors. Methods A random sample of 65‑year‑olds in Oslo answered a questionnaire and underwent clinical and radiographic examinations (n = 457, 52% men and 48% women) at the Research Clinic, Faculty of Dentistry, University of Oslo, between February and December 2019. Primary- and secondary coronal and root caries lesions, root remnants, and missing and restored teeth were recorded. Decayed teeth (DT) were defined as teeth with coronal- and root caries lesions that had progressed into dentine and root remnants, and the DMFT/S scores were calculated. Results The mean number of teeth was 25 (SD: 4) and the mean DMFT was 19.4 (SD: 4.7). Thirty seven percent of the individuals had at least one decayed tooth (DT > 0), and the mean number of filled teeth (FT) was 16.1 (SD: 5.4). Multivariable logistic regression analysis showed that male gender (OR: 1.8, 95% CI: 1.2–2.8), basic level of education (OR: 1.9, 95% CI: 1.2–2.9), irregular dental attendance (OR: 2.2, 95% CI: 1.0-4.8), and hyposalivation (OR: 2.1, 95% CI: 1.0-4.4) were significant risk indicators for having decayed teeth (DT > 0) (p

BackgroundFew clinical studies evaluate interventions to reduce oral discomfort among patients in palliative care.AimThis study examines the efficacy of a Salvia officinalis (SO) based herbal mouth rinse compared to conventional normal saline (NS) in order to improve oral health.DesignA block-randomized controlled trial. Data were collected before and after a 4-day intervention with either SO (n=44) or NS (n=44). Numerical rating scales (NRS, 0-10) and 12 items from the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Oral Health 17 (EORTC QLQ-OH17) measured patient-reported oral symptoms. An oral examination was performed before and after the intervention.Setting/participantsThis study included adult patients with late-stage cancer in an inpatient hospice unit.ResultsOf the 88 patients included (mean age=63.9 years, SD=10.6), 73 (83%) completed the study. At baseline, 78% reported dry mouth on the EORTC QLQ-OH17, and 80% rated dry mouth ≥4 on the NRS. Total oral health scores based on the 12 EORTC QLQ-OH17 items improved similarly in both groups (p

Background: Although traffic-related air pollution is largely regulated at the federal level, congestion reduction projects may reduce local traffic and air pollution to levels that create positive co-benefits for population health. In recent years, many urban areas have implemented electronic tolling systems to improve traffic conditions. Objective: Quantify associations between implementing electronic tolling and local changes in traffic and infant health. Methods: Using a population-based birth cohort (Texas, 1999–2016), we calculated residential proximity to the nearest tolled road segment within 5 km (n = 625,279) and examined changes in local traffic before and after toll implementation. Using a difference-in-differences design, we compared four markers of adverse birth outcomes (term birth weight, term low birth weight, preterm birth, very preterm birth) among infants from pregnant people residing

Abstract Background Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments. Methods National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions. Results Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 μg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls. Conclusions We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health

Abstract Background Patients with advanced cancer are prone to develop different opportunistic oral infection due to anti-cancer treatment or the malignancies themselves. Studies of oral fungal samples show an increased prevalence of non-Candida albicans species in mixed oral infections with Candida albicans. Non-C. albicans and C. albicans are associated with varying degrees of resistance to azoles, which may have implications for treatment. This study aimed to assess the diversity and antifungal susceptibility of Candida species detected in the oral cavity. Methods An observational study with microbiological analysis was conducted. Clinical fungal isolates were collected from patients in a hospice unit in 2014–2016. Isolates were re-grown on chromID® Candida plates in 2020. Single colony of each species was re-cultivated and prepared for biochemical identification with a VITEK2® system and verified by gene sequencing. Etest was performed on RPMI agar, and the antifungals fluconazole, amphotericin B, anidulafungin and nystatin were applied. Results Fifty-six isolates from 45 patients were identified. Seven different Candida species and one Saccharomyces species were detected. The results of biochemical identification were confirmed with sequencing analysis. Thirty-six patients had mono infection, and nine out of 45 patients had 2–3 different species detected. Of C. albicans strains, 39 out of 40 were susceptible to fluconazole. Two non-C. albicans species were resistant to fluconazole, one to amphotericin B and three to anidulafungin. Conclusion C. albicans was the predominant species, with a high susceptibility to antifungal agents. Different Candida species occur in both mono and mixed infections. Identification and susceptibility testing may therefore lead to more effective treatment and may prevent the development of resistance among patients with advanced cancer. Trail registration The study Oral Health in Advanced Cancer was registered at ClinicalTrials.gov (#NCT02067572) in 20/02/2014.

Abstract Background Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy.

Abstract Background Many epidemiological studies examining the relationships between adverse health outcomes and exposure to air pollutants use ambient air pollution measurements as a proxy for personal exposure levels. When pollution levels vary at neighbourhood levels, using ambient pollution data from sparsely located fixed monitors may inadequately capture the spatial variation in ambient pollution. A major constraint to moving toward exposure assessments and epidemiological studies of air pollution at a neighbourhood level is the lack of readily available data at appropriate spatial resolutions. Spatial property assessment data are widely available in North America and may provide an opportunity for developing neighbourhood level air pollution exposure assessments. Results This paper provides a detailed description of spatial property assessment data available in the Pacific Northwest of Canada and the United States, and provides examples of potential applications of spatial property assessment data for improving air pollution exposure assessment at the neighbourhood scale, including: (1) creating variables for use in land use regression modelling of neighbourhood levels of ambient air pollution; (2) enhancing wood smoke exposure estimates by mapping fireplace locations; and (3) using data available on individual building characteristics to produce a regional air pollution infiltration model. Conclusion Spatial property assessment data are an extremely detailed data source at a fine spatial resolution, and therefore a source of information that could improve the quality and spatial resolution of current air pollution exposure assessments.

Background: Animal and epidemiologic studies indicate that air pollution may adversely affect fertility. However, the level of evidence is limited and specific pollutants driving the association are inconsistent across studies. Methods: We used data from a web-based preconception cohort study of pregnancy planners enrolled during 2013–2019 (Pregnancy Study Online; PRESTO). Eligible participants self-identified as female, were aged 21–45 years, resided in the United States (U.S.) or Canada, and were trying to conceive without fertility treatments. Participants completed a baseline questionnaire and bi-monthly follow-up questionnaires until conception or 12 months. We analyzed data from 8,747 participants (U.S.: 7,304; Canada: 1,443) who had been trying to conceive for

Abstract Recent studies have identified inequality in the distribution of air pollution attributable health impacts, but to our knowledge this has not been examined in Canadian cities. We evaluated the extent and sources of inequality in air pollution attributable mortality at the census tract (CT) level in seven of Canada's largest cities. We first regressed fine particulate matter (PM2.5) and nitrogen dioxide (NO2) attributable mortality against the neighborhood (CT) level prevalence of age 65 and older, low income, low educational attainment, and identification as an Indigenous (First Nations, Métis, Inuit) or Black person, accounting for spatial autocorrelation. We next examined the distribution of baseline mortality rates, PM2.5 and NO2 concentrations, and attributable mortality by neighborhood (CT) level prevalence of these characteristics, calculating the concentration index, Atkinson index, and Gini coefficient. Finally, we conducted a counterfactual analysis of the impact of reducing baseline mortality rates and air pollution concentrations on inequality in air pollution attributable mortality. Regression results indicated that CTs with a higher prevalence of low income and Indigenous identity had significantly higher air pollution attributable mortality. Concentration index, Atkinson index, and Gini coefficient values revealed different degrees of inequality among the cities. Counterfactual analysis indicated that inequality in air pollution attributable mortality tended to be driven more by baseline mortality inequalities than exposure inequalities. Reducing inequality in air pollution attributable mortality requires reducing disparities in both baseline mortality and air pollution exposure.

Despite an increasing number of studies demonstrating the potential mental health benefits of greenspace, few longitudinal studies have been reported. We aimed to assess associations between two metrics of residential greenspace exposure and anxiety symptoms in a cohort of Australian women living in major cities.Our study comprised 3,938 women, born between 1973 and 78. Anxiety symptoms in the previous month were assessed at follow-up every three years during 2003–2018, using the anxiety subscale of the Goldberg Anxiety and Depression Scale. The three-month seasonal average normalized difference vegetation index (NDVI) was estimated from 30 m Landsat satellite images in a 500 m buffer (NDVI500m) around participants’ address at each survey (higher NDVI indicates more green vegetation). The annual fractional cover of non-photosynthesising vegetation was estimated (fNPV500m, with higher values indicating greater levels of dead leaf litter or dry grass).A generalised estimating equation assessed associations between greenspace measures and anxiety symptoms (as odds ratios [ORs]), adjusting for repeated outcomes and individual-level covariates. Additional analyses focused on women experiencing substantial changes in between-survey exposure due to moving, and adjusting for nitrogen dioxide (NO2) and fine particulate matter (PM2.5) exposure, among others.A standard deviation (SD) (0.12 units) increase in NDVI500m was significantly associated with lower odds of anxiety symptoms (OR: 0.96, 95% CI: 0.93–0.99) in the adjusted model. An SD (5.2%) increase in annual fNPV500m was consistent with the direction expected for that exposure, but not significant in the adjusted model (OR: 1.03, 95% CI: 0.99–1.07). NDVI500m was modestly attenuated when air pollutants were adjusted for, while fNPV500m only became significant when PM2.5 was adjusted for. Between-survey contrasts had no clear effect for NDVI500m. Moving to a higher fNPV500m area, compared with a similar fNPV500m area, was consistently associated with anxiety symptoms (OR: 1.15, 95% CI: 1.02–1.31). NDVI500m was generally associated with lower odds of anxiety symptoms, while fNPV500m was generally associated with higher odds of anxiety, depending on the covariates considered.

BackgroundLiving in greener areas of cities was linked to increased physical activity levels, improved mental well-being, and lowered harmful environmental exposures, all of which may affect human health. However, whether living in greener areas may be associated with lower risk of cardiovascular disease incidence, progression, and premature mortality is unclear.ObjectivesWe conducted a cohort study to examine the associations between residential green spaces and the incidence of acute myocardial infarction (AMI) and heart failure (HF), post-AMI and HF hospital readmissions, and mortality.MethodsWe simultaneously followed four large population-based cohorts in Ontario, Canada, including the entire adult population, adults free of AMI and HF, and survivors of AMI or HF from 2000 to 2014. We estimated residential exposure to green spaces using satellite-derived observations and ascertained health outcomes using validated disease registries. We estimated the associations using spatial random-effects Cox proportional hazards models. We conducted various sensitivity analyses, including further adjusting for property values and performing exploratory mediation analysis.ResultsEach interquartile range increase in residential greenness was associated with a 7% [95% confidence interval (CI): 4%, 9%] decrease in incident AMI and a 6% (95% CI: 4%, 7%) decrease in incident HF. Residential greenness was linked to a ∼10% decrease in cardiovascular mortality in both adults free of AMI and HF and the entire adult population. These associations remained consistent in sensitivity analyses and were accentuated among younger adults. Additionally, we estimated that the decreases in AMI and HF incidence associated with residential greenness explained ∼53% of the protective association between residential greenness and cardiovascular mortality. Conversely, residential greenness was not associated with any delay in readmission or mortality among AMI and HF patients.ConclusionsLiving in urban areas with more green spaces was associated with improved cardiovascular health in people free of AMI and HF but not among individuals who have already developed these conditions. https://doi.org/10.1289/EHP6161.

BackgroundEvidence suggests a link between air pollution and dementia. Cardiovascular disease (CVD) may be a potential determinant of dementia. This motivated us to quantify the contribution of CVD to the association between air pollution and dementia.MethodsA cohort of Canadian-born residents of Ontario, who participated in the 1996-2003 Canadian Community Health Surveys, was followed through 2013 or until dementia diagnosis. Exposure to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) was estimated with a 3-year average and 5-year lag before dementia diagnosis. Incident CVD was evaluated as a mediator. We used multi-level Cox proportional and Aalen additive hazard regression models, adjusting for individual- and neighbourhood-level risk factors to estimate associations with NO2 and PM2.5. We estimated the total, direct and indirect effects of air pollution on dementia through cardiovascular disease.ResultsThis study included 34 391 older adults. At baseline, the mean age of this cohort was 59 years. The risk of dementia was moderately higher among those more exposed to NO2 (hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.99-1.19; and 100 additional cases per 100 000 [standard error (SE)

Abstract Urbanization may influence physical activity (PA) levels, although little evidence is available for low- and middle- income countries where urbanization is occurring fastest. We evaluated associations between urbanization and total PA, as well as work-, leisure-, home-, and transport-specific PA, for 138,206 adults living in 698 communities across 22 countries within the Prospective Urban and Rural Epidemiology (PURE) study. The 1-week long-form International PA Questionnaire was administered at baseline (2003–2015). We used satellite-derived population density and impervious surface area estimates to quantify baseline urbanization levels for study communities, as well as change measures for 5- and 10-years prior to PA surveys. We used generalized linear mixed effects models to examine associations between urbanization measures and PA levels, controlling for individual, household and community factors. Higher community baseline levels of population density (− 12.4% per IQR, 95% CI − 16.0, − 8.7) and impervious surface area (− 29.2% per IQR, 95% CI − 37.5, − 19.7), as well as the rate of change in 5-year population density (− 17.2% per IQR, 95% CI − 25.7, − 7.7), were associated with lower total PA levels. Important differences in the associations between urbanization and PA were observed between PA domains, country-income levels, urban/rural status, and sex. These findings provide new information on the complex associations between urbanization and PA.

Abstract Aims The aims of the present study were to investigate socioeconomic and behavioral risk indicators for severe periodontitis in a 65-year-old Norwegian population, and to investigate how periodontitis impacts oral health-related quality of life. Material and methods A sample of 65-year-old residents in Oslo, born in 1954, was randomly selected for this study. The participants answered a questionnaire regarding country of birth, education, diabetes, smoking habits, dental attendance pattern, and tooth-brushing habits. In addition, oral health-related quality of life (OHRQoL) was assessed by the Oral Health Impact Profile-14 questionnaire (OHIP-14). Negative impact on OHRQoL was defined as responding “fairly often” or “very often” to at least one of the OHIP-14 items. The diagnosis of periodontitis was based on clinical and radiographic periodontal measurements and classified based on the consensus report from the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. Results Of 796 eligible participants, 460 individuals agreed to participate in the present study (response rate 58%). Seven participants were excluded from the analyses due to

Abstract Background Treatment seeking children and adolescents with severe obesity often experience barriers to physical activity. Studies objectively measuring physical activity in this group and investigating explanatory factors for physical activity levels could inform clinical practice. Objectives This study aimed to compare objectively measured physical activity levels among treatment seeking children and adolescents with severe obesity and normal weight peers, and to investigate explanatory factors for time spent in moderate physical activity and vigorous physical activity among children and adolescents with severe obesity. Methods Children with severe obesity (n = 85) were matched 1:1 by age, gender, and the season for accelerometer measurements with normal weight peers (n = 85). Children wore accelerometers for seven consecutive days, yielding measures of physical activity, sleep duration and timing. Parents reported on screen time, parental body mass index and participation in organized sports. Results Children and adolescents with severe obesity spent significantly less time in moderate physical activity (12 min, p

Abstract Aims The aims of this cross-sectional study were to describe the prevalence and severity of periodontal disease in a 65-year-old population in Oslo, Norway, and to investigate to what extent the radiographic bone level threshold for periodontitis case definition influences the prevalence. Materials and methods A random sample of 454 subjects underwent a clinical and radiographic examination and answered a questionnaire regarding general health, medications, and smoking habits. Clinical periodontal parameters (periodontal pocket depths, bleeding on probing, mobility, and furcation involvement) and radiographic bone loss were used to identify periodontitis cases and to assess periodontal stage and grade. Results Of the 454 participants, 52.6% were defined as “periodontitis cases”. Of the total study population “unstable cases of recurrent periodontitis” were present in 38.1%, 16.5% of the participants were assigned to stage II, 32.8% to stage III, and 3.3% to stage IV. When lowering the radiographic bone loss cutoff from > 3 mm to > 2 mm or > 1 mm the prevalence of periodontitis increased to 91.9% and 99.6%. Conclusions Periodontitis was common among 65 year-olds living in Oslo, and in the majority of those with periodontitis, the disease was recurrent and unstable. This study also shows that the choice of bone loss cutoff for defining a periodontitis case affects the prevalence estimates to a large extent. In addition, this study addresses weaknesses in the use of the consensus report of the 2017 World Workshop on the Classification of Periodontal and Peri-implant Diseases and Conditions for epidemiologic studies in its current form.

Introduction: The World Health Organization (WHO) recently revised its health guidelines for Nitrogen dioxide (NO2) air pollution, reducing the annual mean NO2 level to 10 μg/m3 (5.3 ppb) and the 24-h mean to 25 μg/m3 (13.3 ppb). NO2 is a pollutant of global concern, but it is also a criteria air pollutant that varies spatiotemporally at fine resolutions due to its relatively short lifetime (~hours). Current models have limited ability to capture both temporal and spatial NO2 variation and none are available with global coverage. Land use regression (LUR) models that incorporate timevarying predictors (e.g., meteorology and satellite NO2 measures) and land use characteristics (e.g., road density, emission sources) have significant potential to address this need.Methods: We created a daily Land use regression model with 50 × 50 m2 spatial resolution using 5.7 million daily air monitor averages collected from 8,250 monitor locations.Results: In cross-validation, the model captured 47%, 59%, and 63% of daily, monthly, and annual global NO2 variation. Daily, monthly, and annual root mean square error were 6.8, 5.0, and 4.4 ppb and absolute bias were 46%, 30%, and 21%, respectively. The final model has 11 variables, including road density and built environments with fine (30 m or less) spatial resolution and meteorological and satellite data with daily temporal resolution. Major roads and satellite-based estimates of NO2 were consistently the strongest predictors of NO2 measurements in all regions.Discussion: Daily model estimates from 2005–2019 are available and can be used for global risk assessments and health studies, particularly in countries without NO2 monitoring.

BackgroundPatients suffering from psychiatric disorders face many difficulties due to their condition, medications and lifestyle. Oral health and nutrition may be affected, further complicating their lives. Our aim was to provide in-depth information on oral health and nutritional factors in a small group of patients in short-term psychiatric ward.MethodsTwenty-three patients (mean age 36, average medications five) were recruited during short-term hospitalization in a psychiatric ward. Inclusion criteria: anxiety, psychosis and/or depression, and use of at least one antidepressant or anxiolytic/antipsychotic drug with xerostomia as a known side effect. Subjective oral dryness was evaluated using the Shortened Xerostomia Inventory (SXI). Oral examination included Clinical Oral Dryness Score (CODS), secretion of unstimulated (UWS) and stimulated whole saliva (SWS), and evaluation of dental, gingival, and periodontal status. Self-reported complaints of oral disorders were recorded. The Oral Health Impact Profile-14 (OHIP-14) was used to explore oral health-related quality of life. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment Short Form (PG-SGA-SF), and diet quality was assessed using the Mediterranean diet score (KIDMED).ResultsCompared to healthy controls, the patients had significantly higher SXI scores and CODS, and SWS secretion was lower. Complaints of dysgeusia and halitosis were significantly more frequent among patients. Gingivitis was more common in patients. OHIP-14 scores were much higher in the patients, and they reported significantly poorer oral and general health. Most patients lacked a regular meal pattern. Very low diet quality was observed in five patients, while improvements were needed in twelve. “Dry mouth” and “No appetite, just did not feel like eating” were the most common symptoms preventing patients from eating enough. The PG-SGA-SF symptoms component score showed a strong negative correlation with self-reported oral health, and a strong positive correlation with OHIP-14.ConclusionThis relatively small group of patients in short-term psychiatric ward had both reduced oral health and poor oral health-related quality of life. Furthermore, their nutritional intake was affected by their oral health problems. Although larger groups need to be studied, these findings indicate that oral health and nutrition should be evaluated and adjusted in these patients to improve their overall care.