1
|
Prina M, Khan N, Akhter Khan S, Caicedo JC, Peycheva A, Seo V, Xue S, Sadana R. Climate change and healthy ageing: An assessment of the impact of climate hazards on older people. J Glob Health 2024; 14:04101. [PMID: 38783708 PMCID: PMC11116931 DOI: 10.7189/jogh.14.04101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
Background Climate change not only directly impacts older people's longevity but also healthy ageing, which is the process of maintaining physical and mental capacities while optimising functional abilities. The urgency to address both population ageing and climate change necessitates a rethink and assessment of the impact of climate change on older people. This includes identifying what can be done to anticipate, mitigate and adapt to climate change and engage older persons. Methods A review of climate change and healthy ageing forms the basis of evidence in this report. We developed a comprehensive search to assess current literature, combining terms related to ageing and climate change across four major data sets and assessing articles published up to the end of 2021. Results We summarised the current and future impact of climate change on older people and developed a framework identifying climate change impacts on older persons, recognising social and environmental determinants of healthy ageing. Major hazards and some key exposure pathways include extreme temperatures, wildfire, drought, flooding, storm and sea level rise, air quality, climate-sensitive infectious diseases, food and water insecurities, health and social care system displacement, migration, and relocation. Strategies to address climate change require interventions to improve systems and infrastructure to reduce vulnerability and increase resilience. As a heterogeneous group, older people's perceptions of climate change should be integrated into climate activism. Increasing climate change literacy among older people and enabling them to promote intergenerational dialogue will drive the development and implementation of equitable solutions. Pathways may operate via direct or indirect exposures, requiring longitudinal studies that enable assessment of exposures and outcomes at multiple time points, and analyses of cumulative impacts of hazards across the life course. Conclusions The lack of systematic reviews and primary research on the impact of most climate hazards, except for heat, on older people is apparent. Future research should include outcomes beyond mortality and morbidity and assess how older people interact with their environment by focusing on their capacities and optimising abilities for being and doing what they value.
Collapse
Affiliation(s)
- Matthew Prina
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, England, UK
| | - Nusrat Khan
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, England, UK
| | - Samia Akhter Khan
- Department of Global Health & Social Medicine, King’s College London, London, England, UK
- Department of Health Service & Population Health, King’s College London, London, England, UK
| | | | - Anna Peycheva
- Department of Child and Adolescent Psychiatry, King’s College London, London, England, UK
| | - Veri Seo
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, Massachusetts, USA
| | - Siqi Xue
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Ritu Sadana
- World Health Organization, Geneva, Switzerland
| |
Collapse
|
2
|
Ocobock C. Human cold adaptation: An unfinished agenda v2.0. Am J Hum Biol 2024; 36:e23937. [PMID: 37345289 DOI: 10.1002/ajhb.23937] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND Research on human extreme cold climate adaptations has benefitted from a recent resurgence since Ted Steegmann laid out his Human Cold Adaptation Agenda in 2007. Human biologists have drastically expanded our knowledge in this area during the last 15 years, but we still have a great deal more work to do to fulfill the cold climate adaptation agenda. METHODS Here, I follow Steegmann's example by providing a review of cold climate adaptations and setting forth a new, expanded agenda. RESULTS I review the foundational work on cold climate adaptations including classic Bergmann, Allen, and Thomson rules as well as early work assessing metabolic differences among Indigenous cold climate populations. From there, I discuss some of the groundbreaking work currently taking place on cold climate adaptations such as brown adipose tissue (a heat generating organ), physical activity levels, metabolic rates, and behavioral/cultural mechanisms. Finally, I present a path forward for future research with a focus on some of the basic extreme cold adaptations as well as how human biologists should approach the effects of climate change on human health and well-being, particularly within a cold climate context. CONCLUSION The Arctic has felt the dramatic effects of climate change sooner and more acutely than other parts of the world, making it an ideal location for studying both cold climate adaptations and climate change resilience. Human biologists have a great deal to contribute to the conversation on not only adaptations to extreme cold, but also the ways in which climate change is being embodied by cold climate populations.
Collapse
Affiliation(s)
- Cara Ocobock
- Department of Anthropology, University of Notre Dame, Notre Dame, Indiana, USA
- Department of Gender Studies, University of Notre Dame, Notre Dame, Indiana, USA
- Eck Institute for Global Health, Institute for Educational Initiatives, University of Notre Dame, Notre Dame, Indiana, USA
| |
Collapse
|
3
|
Hoke MK, Long AM. Human biology and the study of precarity: How the intersection of uncertainty and inequality is taking us to new extremes. Am J Hum Biol 2024; 36:e24018. [PMID: 38053455 DOI: 10.1002/ajhb.24018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/31/2023] [Accepted: 11/03/2023] [Indexed: 12/07/2023] Open
Abstract
Inequality represents an extreme environment to which humans must respond. One phenomenon that contributes to this growing extreme is precarity or the intersection of uncertainty and some form of inequality. While precarity has an important intellectual history in the fields of sociology and sociocultural anthropology, it has not been well studied in the field of human biology. Rather human biologists have engaged with the study of closely related concepts such as uncertainty and resource insecurity. In this article, we propose that human biology take on the study of precarity as a novel way of investigating inequality. We first provide a brief intellectual history of precarity which is followed by a review of research on uncertainty and resource security in human biology which, while not exhaustive, illustrates some key gaps that precarity may aid us in addressing. We then review some of the pathways through which precarity comes to affect human biology and health and some of the evidence for why the unpredictable nature of precarity may make it a unique physiological stress. A case study based on research in Nuñoa, Peru provides an important example of how precarity can elucidate the influences of health in an extreme setting, albeit with insights that apply more broadly. We conclude that precarity holds important potential for the study of human biology, including helping us more effectively operationalize and study uncertainty, encouraging us to explore the predictability of resources and stressors, and reminding us to think about the intersectional nature of stressors.
Collapse
Affiliation(s)
- Morgan K Hoke
- Department of Anthropology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Anneliese M Long
- Department of Anthropology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| |
Collapse
|
4
|
Zhang HZ, Wang DS, Wu SH, Huang GF, Chen DH, Ma HM, Zhang YT, Guo LH, Lin LZ, Gui ZH, Liu RQ, Hu LW, Yang JW, Zhang WJ, Dong GH. The association between childhood adiposity in northeast China and anthropogenic heat flux: A new insight into the comprehensive impact of human activities. Int J Hyg Environ Health 2023; 254:114258. [PMID: 37703624 DOI: 10.1016/j.ijheh.2023.114258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/13/2023] [Accepted: 09/06/2023] [Indexed: 09/15/2023]
Abstract
Anthropogenic heat has been reported to have significant health impacts, but research on its association with childhood adiposity is still lacking. In this study, we matched the 2008-2012 average anthropogenic heat flux, as simulated by a grid estimation model using inventory methods, with questionnaire and measurement data of 49,938 children randomly recruited from seven cities in Northeast China in 2012. After adjusting for social demographic and behavioral factors, we used generalized linear mixed-effect models to assess the association between anthropogenic heat flux and adiposity among children. We also examined the effect modification of various social demographic and behavioral confounders. We found that each 10 W/m2 increase in total anthropogenic heat flux and that from the industry source was associated with an increase of 5.82% (95% CI = 0.84%-11.05%) and 6.62% (95% CI = 0.87%-12.70%) in the odds of childhood adiposity. Similarly, the excess rate of adiposity among children were 5.26% (95% CI = -1.33%-12.29%) and 8.51% (95% CI = 2.24%-15.17%) per 1 W/m2 increase in the anthropogenic heat flux from transportation and buildings, and was 7.94% (95% CI = 2.28%-13.91%) per 0.001 W/m2 increase in the anthropogenic heat flux from human metabolism. We also found generally greater effect estimates among female children and children who were exposed to passive smoking during pregnancy, born by caesarean section, non-breastfed/mixed-fed, or lived within 20 m adjacent to the main road. The potential deleterious effect of anthropogenic heat exposure on adiposity among children may make it a new but major threat to be targeted by future mitigation strategies.
Collapse
Affiliation(s)
- Hong-Zhi Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Dao-Sen Wang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Si-Han Wu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Guo-Feng Huang
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Duo-Hong Chen
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Hui-Min Ma
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Yun-Ting Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Hao Guo
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Zi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhao-Huan Gui
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ru-Qing Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jie-Wen Yang
- Guangzhou Social Welfare Institution, Guangzhou, 510520, China.
| | - Wang-Jian Zhang
- Department of Biostatistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| |
Collapse
|
5
|
Rosinger AY. Extreme climatic events and human biology and health: A primer and opportunities for future research. Am J Hum Biol 2023; 35:e23843. [PMID: 36449411 PMCID: PMC9840683 DOI: 10.1002/ajhb.23843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 11/17/2022] [Accepted: 11/18/2022] [Indexed: 12/05/2022] Open
Abstract
Extreme climatic events are increasing in frequency, leading to hotter temperatures, flooding, droughts, severe storms, and rising oceans. This special issue brings together a collection of seven articles that describe the impacts of extreme climatic events on a diverse set of human biology and health outcomes. The first two articles cover extreme temperatures extending from extreme heat to cold and changes in winter weather and the respective implications for adverse health events, human environmental limits, well-being, and human adaptability. Next, two articles cover the effects of exposures to extreme storms through an examination of hurricanes and cyclones on stress and birth outcomes. The following two articles describe the effects of extreme flooding events on livelihoods, nutrition, water and food insecurity, diarrheal and respiratory health, and stress. The last article examines the effects of drought on diet and food insecurity. Following a brief review of each extreme climatic event and articles covered in this special issue, I discuss future research opportunities-highlighting domains of climate change and specific research questions that are ripe for biological anthropologists to investigate. I close with a description of interdisciplinary methods to assess climate exposures and human biology outcomes to aid the investigation of the defining question of our time - how climate change will affect human biology and health. Ultimately, climate change is a water, food, and health problem. Human biologists offer a unique perspective for a combination of theoretical, methodological, and applied reasons and thus are in a prime position to contribute to this critical research agenda.
Collapse
Affiliation(s)
- Asher Y. Rosinger
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA, USA
- Department of Anthropology, Pennsylvania State University, University Park, PA, USA
| |
Collapse
|
6
|
Ocobock C, Niclou A. Commentary—fat but fit…and cold? Potential evolutionary and environmental drivers of metabolically healthy obesity. Evol Med Public Health 2022; 10:400-408. [PMID: 36071988 PMCID: PMC9447378 DOI: 10.1093/emph/eoac030] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/04/2022] [Indexed: 11/29/2022] Open
Abstract
As global obesity rates continue to rise, it is important to understand the origin, role and range of human variation of body mass index (BMI) in assessing health and healthcare. A growing body of evidence suggests that BMI is a poor indicator of health across populations, and that there may be a metabolically healthy obese phenotype. Here, we review the reasons why BMI is an inadequate tool for assessing cardiometabolic health. We then suggest that cold climate adaptations may also render BMI an uninformative metric. Underlying evolutionary and environmental drivers may allow for heat conserving larger body sizes without necessarily increasing metabolic health risks. However, there may also be a potential mismatch between modern obesogenic environments and adaptations to cold climates, highlighting the need to further investigate the potential for metabolically healthy obese phenotypes among circumpolar and other populations as well as the broader meaning for metabolic health.
Collapse
Affiliation(s)
- Cara Ocobock
- Department of Anthropology, University of Notre Dame , Notre Dame, IN, USA
- Eck Institute for Global Health, Institute for Educational Initiatives, University of Notre Dame , Notre Dame, IN, USA
| | - Alexandra Niclou
- Department of Anthropology, University of Notre Dame , Notre Dame, IN, USA
| |
Collapse
|
7
|
Ohanyan H, Portengen L, Huss A, Traini E, Beulens JWJ, Hoek G, Lakerveld J, Vermeulen R. Machine learning approaches to characterize the obesogenic urban exposome. ENVIRONMENT INTERNATIONAL 2022; 158:107015. [PMID: 34991269 DOI: 10.1016/j.envint.2021.107015] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously. OBJECTIVES We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches. METHODS A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations. RESULTS The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations. DISCUSSION The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution.
Collapse
Affiliation(s)
- Haykanush Ohanyan
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Noord-Holland, the Netherlands; Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands; Upstream Team, www.upstreamteam.nl. Amsterdam UMC, VU University Amsterdam, Amsterdam, Noord-Holland, the Netherlands.
| | - Lützen Portengen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands
| | - Anke Huss
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands
| | - Eugenio Traini
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands
| | - Joline W J Beulens
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Noord-Holland, the Netherlands; Upstream Team, www.upstreamteam.nl. Amsterdam UMC, VU University Amsterdam, Amsterdam, Noord-Holland, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherland
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands
| | - Jeroen Lakerveld
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Noord-Holland, the Netherlands; Upstream Team, www.upstreamteam.nl. Amsterdam UMC, VU University Amsterdam, Amsterdam, Noord-Holland, the Netherlands
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Utrecht, the Netherlands
| |
Collapse
|