Healthy lives and well-being for all at all ages: expanding representations of determinants of health within systems dynamics and integrated assessment models

Integrated Assessment Models (IAMs) and System Dynamic Models (SDMs) are starting to incorporate representations of the impact of environmental changes on health and socio-economic development into their modelling frameworks. We use this brief review to provide an overview of how health and well-being are currently represented in IAMs and SDMs. A grey literature search on 12 selected model host websites and their corresponding Wiki pages was conducted. Model descriptions, coverage and publications were then tabulated. Additional potential determinants related to health were then suggested based on emerging environmental health literature. Based on these tabulations, it was determined that many individual health outcomes are not represented and thus not analyzed. Social well-being is not represented at all. Additionally, potentially health relevant determinants such as chemical or metal exposure and water pollution are rarely represented in models. Most models have representations of climate, outdoor air pollution and food availability. Air pollution was the most analyzed determinant, especially in relation to its respiratory effects. We suggest that future modelers incorporate more representations of environmental determinants influencing health, and to analyze all available determinants in relation to a wider array of health outcomes. Perhaps, if and when broader determinants of health are represented in IAMs and SDMs, then a composite of these determinants could be used to determine a population’s ability to achieve elements that also contribute to social well-being

The use of environmental scenarios to project future health effects: a scoping review

Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts

The use of environmental scenarios to project future health effects: a scoping review

Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts

Traffic-related air pollution, road traffic noise, and Parkinson's disease: Evaluations in two Dutch cohort studies

Background: Environmental factors such as air pollution have been associated with Parkinson's disease (PD), but findings have been inconsistent. We investigated the association between exposure to several air pollutants, road traffic noise, and PD risk in two Dutch cohorts. Methods: Data from 50,087 participants from two Dutch population-based cohort studies, European Prospective Investigation into Cancer and Nutrition in the Netherlands and Arbeid, Milieu en Gezondheid Onderzoek were analyzed. In these cohorts, 235 PD cases were ascertained based on a previously validated algorithm combining self-reported information (diagnosis, medication, and symptoms) and registry data. We assigned the following traffic-related exposures to residential addresses at baseline: NO2,NOx, particulate matter (PM)2.5absorbance(as a marker for black carbon exposure), PM with aerodynamic diameter ≤2.5 m (PM2.5), ≤10 m (PM10), PMcoarse(size fraction 2.5-10 m), ultrafine particles <0.1 m (UFP), and road traffic noise (Lden). Logistic regression models were applied to investigate the associations with PD, adjusted for possible confounders. Results: Both single-and two-pollutant models indicated associations between exposure to NOx, road traffic noise, and increasing odds of developing PD. Odds ratios of fully adjusted two-pollutant models in the highest compared with the lowest exposure quartile were 1.62 (95% CI = 1.02, 2.62) for NOxand 1.47 (95% CI = 0.97, 2.25) for road traffic noise, with clear trends across exposure categories. Conclusions: Our findings suggest that NOxand road traffic noise are associated with an increased risk of PD. While the association with NOxhas been shown before, further investigation into the possible role of environmental noise on PD is warranted

Air pollution and childhood epilepsy diagnosis at a first seizure clinic in The Netherlands: A case-control study

Increasing evidence suggests that exposure to air pollution is linked to neurological disorders, but little is known about the association with epilepsy. This study aimed to quantify the association between exposure to ambient air pollutants and the diagnosis of epilepsy in Dutch children. A population-based case-control study was conducted among children presenting to the first seizure clinic at the Wilhelmina Children's Hospital in Utrecht, the Netherlands, from 1 January 2008 to 31 May 2021. Children were assigned to either cases (i.e., diagnosed with epilepsy, n = 406) or controls (n = 737). Levels of ambient air pollution (nitrogen dioxide [NO2], ozone [O3], and particulate matter with aerodynamic diameter < 10 μm [PM10] and < 2.5 μm [PM2.5]) exposure were assigned for the year of presentation to the residential addresses of study participants using EU-wide air pollution metrics. Logistic regression models, adjusted for common confounders, were applied to calculate odds ratios (ORs) with 95 % confidence intervals (CIs) for the association between air pollution and epilepsy. Overall, no association between ambient air pollution and an epilepsy diagnosis was observed, including NO2 (OR: 1.01, 95 % CI: 0.98, 1.03), O3 (OR: 1.01, 95 % CI: 0.98, 1.03), PM2.5 (OR: 0.99, 95 % CI: 0.94, 1.04), and PM10 (OR: 0.99, 95 % CI: 0.95, 1.02). Subgroup analysis was suggestive but ultimately underpowered to draw any meaningful conclusions. Additional work, including a longitudinal evaluation of air pollutants, a closer examination of epilepsy etiologies, and a wider, community-based approach, is needed to explore these findings further

Air pollution and childhood epilepsy diagnosis at a first seizure clinic in The Netherlands: A case-control study

Increasing evidence suggests that exposure to air pollution is linked to neurological disorders, but little is known about the association with epilepsy. This study aimed to quantify the association between exposure to ambient air pollutants and the diagnosis of epilepsy in Dutch children. A population-based case-control study was conducted among children presenting to the first seizure clinic at the Wilhelmina Children's Hospital in Utrecht, the Netherlands, from 1 January 2008 to 31 May 2021. Children were assigned to either cases (i.e., diagnosed with epilepsy, n = 406) or controls (n = 737). Levels of ambient air pollution (nitrogen dioxide [NO2], ozone [O3], and particulate matter with aerodynamic diameter < 10 μm [PM10] and < 2.5 μm [PM2.5]) exposure were assigned for the year of presentation to the residential addresses of study participants using EU-wide air pollution metrics. Logistic regression models, adjusted for common confounders, were applied to calculate odds ratios (ORs) with 95 % confidence intervals (CIs) for the association between air pollution and epilepsy. Overall, no association between ambient air pollution and an epilepsy diagnosis was observed, including NO2 (OR: 1.01, 95 % CI: 0.98, 1.03), O3 (OR: 1.01, 95 % CI: 0.98, 1.03), PM2.5 (OR: 0.99, 95 % CI: 0.94, 1.04), and PM10 (OR: 0.99, 95 % CI: 0.95, 1.02). Subgroup analysis was suggestive but ultimately underpowered to draw any meaningful conclusions. Additional work, including a longitudinal evaluation of air pollutants, a closer examination of epilepsy etiologies, and a wider, community-based approach, is needed to explore these findings further

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND: The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes. METHODS: On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality. RESULTS: A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM 2.5. The meta-analyses revealed that a 1 μg/m 3 increase in PM 2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO 2), ozone (O 3), sulphur dioxide (SO 2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality. CONCLUSION: This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors

Early life ambient air pollution, household fuel use, and under-5 mortality in Ghana

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

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND: The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes. METHODS: On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality. RESULTS: A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM 2.5. The meta-analyses revealed that a 1 μg/m 3 increase in PM 2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO 2), ozone (O 3), sulphur dioxide (SO 2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality. CONCLUSION: This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors

Early life ambient air pollution, household fuel use, and under-5 mortality in Ghana

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 (PM 2.5), 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 PM 2.5 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 PM 2.5 was 39.3 µg/m 3, 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