Health risks of natural hazards and resilience resources: Evidence from a U.S. nationwide longitudinal study

The Influence of Climate, Atmospheric Pollution, and Natural Disasters on Cardiovascular Diseases and Diabetes Mellitus in Drylands: A Scoping Review

Objectives

In the face of escalating global aridification, this study examines the complex relationship between climate variability, air pollution, natural disasters, and the prevalence of cardiovascular disease (CVD) and diabetes mellitus (DM) in arid regions.

Methods

The study conducted a scoping review of multiple databases using JBI guidelines and included 74 studies.

Results

The results show that acute myocardial infarction (n = 20) and stroke (n = 13) are the primary CVDs affected by these factors, particularly affecting older adults (n = 34) and persons with hypertension (n = 3). Elevated air temperature and heat waves emerge as critical risk factors for CVD, exacerbating various cardiovascular mechanisms. Atmospheric pollutants and natural disasters increase this risk. Indirect effects of disasters amplify risk factors such as socioeconomic vulnerability (n = 4), inadequate medical care (n = 3), stress (n = 3), and poor diet (n = 2), increasing CVD and DM risk.

Conclusion

The study underscores the need for nations to adhere to the Paris Agreement, advocating for reduced air pollutants, resilient environments, and collaborative, multidisciplinary research to develop targeted health interventions to mitigate the adverse effects of climate, pollution, and natural disasters.

"One community at a time": promoting community resilience in the face of natural hazards and public health challenges

BACKGROUND

Resilience is vital for facing natural disasters and public health challenges. Despite the significance of resilience-building activities, there is a scarcity of locally-tailored planning and response strategies, leaving communities incapable of addressing the unique challenges posed by natural disasters and public health crises. This study aims to explore how the "One Community at a Time" approach enhances community resilience in facing natural hazards and public health challenges.

METHODS

A systematic review was conducted over journal articles published from January 2001 to April 2023 through PRISMA approach. Multiple databases such as Web of Science and Scopus were thoroughly searched. We used independent screening by two researchers and painstaking data extraction using standardized forms. This approach was adopted to assure the reliability, validity, and precision of our study selection and analysis. The included studies' quality was evaluated by the Mixed Methods Appraisal Tool.

RESULTS

In the evaluation, 35 studies were deemed eligible for inclusion and underwent in-depth examination. Several major components of "One Community at a Time" have been identified, including social capital and networks, local knowledge and learning, effective governance and leadership, preparedness and response capacity, and adaptive infrastructure and resources. This framework highlights the significance of individualized approaches to resilience-building initiatives, recognizing that each community has specific strengths, needs, and challenges.

CONCLUSION

Relevant stakeholders can adapt suitable resilient strategies to help prepare and recover from natural hazards and public health challenges. By adopting a localized strategy, stakeholders can collaborate to develop a culture of readiness and resilience, ultimately leading to more sustainable and resilient communities. This framework advises community-based groups, local government, and other stakeholders on prioritizing partnerships, preparedness planning, community participation, and leadership as essential components of creating and maintaining resilience. "One Community at a Time" framework offers practical guidance for community-based organizations, local government, and other stakeholders to prioritize partnerships, preparedness planning, community participation, and leadership as essential components of creating and sustaining resilience.

Health and housing consequences of climate-related disasters: a matched case-control study using population-based longitudinal data in Australia

BACKGROUND

Understanding the role of how people are housed in reducing the long-term health and housing effects of climate-related disasters is crucial given our changing climate. We examine long-term health and housing trajectories and health effects of climate-related disasters in relation to housing vulnerabilities over a decade.

METHODS

We conducted a matched case-control study using longitudinal population-based data from the Household, Income and Labour Dynamics in Australia survey. We included data from people whose homes had been damaged by climate-related disasters (eg, flood, bushfire, or cyclone) between 2009 and 2019 and matched control cohorts with similar sociodemographic profiles who had not been exposed to disaster-related home damage during this period. We included data from de-identified individuals with at least 1 year of data before disaster and 3 years after disaster. One-to-one nearest neighbour matching was performed on the basis of demographic, socioeconomic, housing, health, neighbourhood, location, and climate characteristics 1 year before disaster. Conditional fixed-effects models for matched case-control groups were used to assess health trajectories, using eight quality-of-life domains on mental, emotional, social, and physical wellbeing, and housing trajectories, using three housing aspects of cost (ie, housing affordability and fuel poverty), security (ie, residential stability and tenure security), and condition (ie, housing quality and suitability).

FINDINGS

Exposure to home damage from climate-related disasters had significant negative effects on people's health and wellbeing at disaster year (difference between exposure and control groups in mental health score was -2·03, 95% CI -3·28 to -0·78; in social functioning score was -3·95, -5·57 to -2·33; and in emotional wellbeing score was -4·62, -7·06 to -2·18), with some effects lasting for 1-2 years after disaster. These effects were more severe for people who had housing affordability stress or were living in poor quality housing before the disaster. People in the exposure group had a slight increase in housing and fuel payment arrears following disasters. Homeowners had increased housing affordability stress (1 year after disaster: 0·29, 95% CI 0·02 to 0·57; 2 years after disaster: 0·25, 0·01 to 0·50), renters had a higher prevalence of acute residential instability (disaster year: 0·27, 0·08 to 0·47), and people who were exposed to disaster-related home damage had a higher prevalence of forced moves than did the control group (disaster year: 0·29, 0·14 to 0·45).

INTERPRETATION

Findings support the need for recovery planning and resilience building to consider housing affordability, tenure security, and housing condition. Interventions might require divergent strategies for populations in different precarious housing circumstances, and policies should target long-term housing support services for highly vulnerable groups.

FUNDING

The National Health and Medical Research Council Centre of Research Excellence in Healthy Housing, University of Melbourne Affordable Housing Hallmark Research Initiative Seed Funding, Australian Research Council's Centre of Excellence for Children and Families over the Life Course, and Lord Mayor's Charitable Foundation.

Vulnerability and recovery: Long-term mental and physical health trajectories following climate-related disasters

Extreme weather and climate-related disaster events are associated with a range of adverse health outcomes. People are not equally vulnerable to the adversity, experiencing varied patterns of long-term health trajectories in recovery depending on their vulnerabilities, capacities, and resiliencies. This study aims to identify latent mental and physical health trajectories and their associations with person- and place-based pre-disaster predictors. Using an Australian, population-based, longitudinal dataset spanning 2009-19, group-based multi-trajectory modelling was applied to identify the distinct mental, social, emotional, and physical health trajectories of people who had experienced damage to their home following a climate-related disaster event. Multinomial logistic regression was used to assess a series of social vulnerability predictors (demographic, socioeconomic, housing, health, neighbourhood, and geographical) of health patterns. We identified three distinct health trajectories. Most individuals experienced small or minimal health impacts at the time of the disaster year followed by a fast recovery. However, one-fifth of the exposed population were severely affected during and post disaster. This cohort had the worst mental and physical health prior to the disaster and experienced the largest decreases in mental and physical health and the lowest recoveries. Pre-existing mental and physical conditions were the most substantial risk factors, increasing the probability of experiencing high impact and slow recovery by 61% for mental health and 51% for physical health. In addition, vulnerability in the form of housing affordability stress, lower household income, and lack of community attachment, participation and safety were also significant independent risk factors for ongoing post-disaster health problems. Critically, people's mental and physical health recovery is dependent on pre-disaster vulnerabilities in health, resource access, and capacities. These findings could assist policymakers and health practitioners to more effectively target people most at risk and design prevention and response strategies to prevent the exacerbation of poor health and wellbeing.

The Health and Retirement Study: Contextual Data Augmentation

The Health and Retirement Study is an amazing resource for those studying aging in the United States, and a fantastic model for other countries who have created similar longitudinal studies. The raw amount of information, from data on income, wealth, and use of health services to employment, retirement, and family connections on to the collection of clinical biomarkers can be both empowering and overwhelming to a researcher. Luckily through the process of engagement with the research community and constant improvement, these reams of data are not only consistently growing in a thoughtful and focused direction, they are also explained and summarized to increase the ease of use for all. One of the very useful areas of the HRS is the Contextual Data File (CDF), which is the focus of this review. The CDF provides access to easy-to-use helpful community-level data in a secure environment that has allowed researchers to answer questions that would have otherwise been difficult or impossible to tackle. The current CDF includes data in six categories (University of Michigan Institute for Social Research. 2017. HRS Data Book: The Health and Retirement Study: Aging in the 21st Century, Challenges and Opportunities for Americans. Ann Arbor: University of Michigan. Also available at https://hrs.isr.umich.edu/about/data-book, 17): 1. Socio-economic Status and Demographic Structure 2. Psychosocial Stressors 3. Health Care 4. Physical Hazards 5. Amenities 6. Land Use and the Built Environment. Each of these areas have allowed researchers to answer interesting questions such as what is the impact of air pollution on cognition in older adults (Ailshire, J., and K. M. Walsemann. 2021. "Education Differences in the Adverse Impact of PM 2.5 on Incident Cognitive Impairment Among U.S. Older Adults." Journal of Alzheimer's Disease 79 (2): 615-25), the impact of neighborhood characteristics on obesity in older adults (Grafova, I. B., V. A. Freedman, R. Kumar, and J. Rogowski. 2008. "Neighborhoods and Obesity in Later Life." American Journal of Public Health 98: 2065-71), or even what do we gain from introducing contextual data to a survey analysis (Wilkinson, L. R., K. F. Ferraro, and B. R. Kemp. 2017. "Contextualization of Survey Data: What Do We Gain and Does it Matter?" Research in Human Development 14 (3): 234-52)? My review focuses on the potential to expand contextual data in a few of these areas. From new data sets developed and released by the U.S. Census Bureau, to improved measurements of climate and environmental risk, there are numerous new data sources that would be a boon to the research community if they were joined together with the HRS. The following section begins by breaking down the opportunity provided by community or place-based data before moving on to specific recommendations for new data that could be included in the HRS contextual data file.