Editing IPCC:AR6/WGII/Chapter-7 (section)

=== 7.2.4 Observed Impacts on Other Climate-Sensitive Health Outcomes ===

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==== 7.2.4.1 Heat- and Cold-Related Mortality and Morbidity ====

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E ''xtreme heat events and extreme temperature have well-documented, observed impacts on health, mortality (very high confidence'' '') and morbidity (high confidence).'' AR5 described the thermoregulatory mechanisms and responses, including acclimatisation, linking heat, cold and health, and these have been further confirmed by recent studies and reviews (e.g., [[#Giorgini--2017|Giorgini et al., 2017]] ; [[#Ikaheimo--2018|Ikaheimo, 2018]] ; [[#McGregor--2015|McGregor et al., 2015]] ; [[#Stewart--2017|Stewart et al., 2017]] ; [[#Schuster--2017|Schuster et al., 2017]] ; [[#Zhang--2018b|Zhang et al., 2018b]] ). The health impacts of heat manifest clearly in periods of extreme heat often codified as heatwaves. For example, heatwaves across Europe (2003), Russia (2010), India (2015) and Japan (2018) resulted in significant death tolls and hospitalisations ( [[#McGregor--2017|McGregor et al., 2017]] ; [[#Hayashida--2019|Hayashida et al., 2019]] ). Heat continues to pose a significant health risk due to increases in exposure, changes in the size and spatial distribution of the human population, mounting vulnerability and an increase in extreme heat events ( ''high confidence'' ) ( [[#Harrington--2017|Harrington et al., 2017]] ; [[#Liu--2017|Liu et al., 2017]] ; [[#Mishra--2017|Mishra et al., 2017]] ; [[#Rohat--2019a|Rohat et al., 2019a]] ; [[#Rohat--2019b|Rohat et al., 2019b]] ; [[#Rohat--2019c|Rohat et al., 2019c]] ; [[#Watts--2019|Watts et al., 2019]] ). Some regions are already experiencing heat stress conditions approaching the upper limits of labour productivity and human survivability ( ''high confidence'' ). These include the Persian Gulf and adjacent land areas, parts of the Indus River Valley, eastern coastal India, Pakistan, northwestern India, the shores of the Red Sea, the Gulf of California, the southern Gulf of Mexico and coastal Venezuela and Guyana ( [[#Krakauer--2020|Krakauer et al., 2020]] ; [[#Li--2020|Li et al., 2020]] ; [[#Raymond--2020|Raymond et al., 2020]] ; [[#Saeed--2021|Saeed et al., 2021]] ; [[#Xu--2020|Xu et al., 2020]] ).

Under a variety of methods, estimates of the world’s population exposed to extreme heat indicate very large and growing numbers and an increase since pre-industrial times. For example, Li et al. (2020) estimate that globally, 1.28 billion people each year experience heatwave conditions similar to that of the lethal Chicago 1995 event, compared with 0.99 billion people that would be similarly exposed under a pre-industrial climate. Further, for the 150 most populated cities of the world, a 500% increase in the exposure to extreme heat events occurred over the 1980–2017 period ( [[#Li--2021|Li et al., 2021]] ), while for the 1986–2005 period, the total exposure to dangerous heat in Africa’s 173 largest cities was 4.2 billion person-days yr –1 ( [[#Rohat--2019a|Rohat et al., 2019a]] ). Globally the present exposure to heatwave events is estimated to be 14.8 billion person-days yr –1 , with the greatest cumulative exposures measured in person-days occurring across southern Asia (7.19 billion), sub-Saharan Africa (1.43 billion), and north Africa and the Middle East (1.33 billion) ( [[#Jones--2018|Jones et al., 2018]] ).

The country level percentage of mortality attributable to non-optimum temperature (heat and cold) has been found to range from 3.4 to 11% ( [[#Gasparrini--2015|Gasparrini et al., 2015]] ; [[#Zhang--2019b|Zhang et al., 2019b]] ). Heat as a health risk factor has largely been overlooked in low- and middle-income countries ( [[#Campbell--2018|Campbell et al., 2018]] ; [[#Green--2019|Green et al., 2019]] ; [[#Dimitrova--2021|Dimitrova et al., 2021]] ). For 2019, the GBD report estimates the burden of DALYs attributable to low temperature was 2.2 times greater than the burden attributable to high temperature. However, this global figure obscures important regional variations. Countries with a high sociodemographic index—mainly mid-latitude high-income temperate to cool climate countries— were found to have a cold-related burden 15.4 times greater than the heat-related burden, while for warm lower-income regions, such as south Asia and sub-Saharan Africa, the heat-related burden was estimated to be 1.7 times and 3.6 times greater, respectively ( [[#Murray--2020|Murray et al., 2020]] ). For countries where data availability permits, there is evidence that extreme heat (and extreme cold) leads to higher rates of premature deaths ( [[#Armstrong--2017|Armstrong et al., 2017]] ; [[#Cheng--2018|Cheng et al., 2018]] ; [[#Costa--2017|Costa et al., 2017]] ).

Rapid changes and variability in temperatures are observed to increase heat-related health and mortality risks, the outcomes varying across temperate and tropical regions ( [[#Guo--2016|Guo et al., 2016]] ; [[#Cheng--2019|Cheng et al., 2019]] ; [[#Kim--2019a|Kim et al., 2019a]] ; [[#Tian--2019|Tian et al., 2019]] ; [[#Zhang--2018b|Zhang et al., 2018b]] ; [[#Zhao--2019|Zhao et al., 2019]] ).

''Several lines of evidence point to a possible decrease in population sensitivity to heat, albeit mainly for high-income countries (high confidence), arising from the implementation of heat warning systems, increased awareness and improved quality of life.'' ( [[#Sheridan--2018|Sheridan and Allen, 2018]] ). Evidence suggests a general decrease in the impact of heat on daily mortality ( [[#Diaz--2018|Diaz et al., 2018]] ; [[#Kinney--2018|Kinney, 2018]] ; [[#Miron--2015|Miron et al., 2015]] ), a decline in the relative risk attributable to heat ( [[#Åström--2018|Åström et al., 2018]] ; [[#Barreca--2016|Barreca et al., 2016]] ; [[#Petkova--2014|Petkova et al., 2014]] ) and an increase in the minimum mortality temperature (MMT) ( [[#Åström--2018|Åström et al., 2018]] ; [[#Folkerts--2020|Folkerts et al., 2020]] ; [[#Follos--2021|Follos et al., 2021]] ; [[#Chung--2018|Chung et al., 2018]] ; [[#Todd--2015|Todd and Valleron, 2015]] ; [[#Yin--2019|Yin et al., 2019]] ). It is difficult to draw conclusions regarding trends in heat sensitivity for low- to middle-income countries and specific vulnerable groups as these are under-represented in the literature ( [[#Sheridan--2018|Sheridan and Allen, 2018]] ). Trends in heat sensitivity are generally believed to be scale and situation dependent, but there is considerable variability in changes in heat sensitivity as measured by trends in heat-related mortality or MMT ( [[#Follos--2021|Follos et al., 2021]] ; [[#Kim--2019a|Kim et al., 2019a]] ; [[#Lee--2021|Lee et al., 2021]] ), with notable variability across different population groups ( [[#Lu--2021|Lu et al., 2021]] ).

Temperature interacts with heat-sensitive physiological mechanisms via multiple pathways to affect health. In the worst cases, these lead to organ failure and death ( [[#Mora--2017a|Mora et al., 2017a]] ; [[#Mora--2017b|Mora et al., 2017b]] ). Excess deaths during extreme heat events occur predominantly in older individuals and are overwhelmingly cardiovascular in origin ''(very high confidence)'' . A higher occurrence of CVD mortality in association with prolonged period of low temperatures has been well documented globally ( [[#Giorgini--2017|Giorgini et al., 2017]] ; [[#Stewart--2017|Stewart et al., 2017]] ); however, there is growing evidence that cardiovascular deaths are more related to heat events than cold spells ( [[#Chen--2019|Chen et al., 2019]] ; [[#Liu--2015a|Liu et al., 2015a]] ; [[#Bunker--2016|Bunker et al., 2016]] ). While there is strong association between ambient temperature and cardiovascular events globally, there are complex interactions and modulators of individual response ( [[#Wang--2017|Wang et al., 2017]] b). Further, some CVD morbidity sub-groups such as myocardial infarction (MI) and stroke hospitalisation display temperature sensitivity while others do not ( [[#Bao--2019|Bao et al., 2019]] ; [[#Sun--2018|Sun et al., 2018]] ; [[#Wang--2016|Wang et al., 2016]] ). Although older adults have inherent sensitivities to temperature-related health impacts ( [[#Bunker--2016|Bunker et al., 2016]] ; [[#Phung--2016|Phung et al., 2016]] ), children can also be affected by extreme heat ( [[#Xu--2014|Xu et al., 2014]] ). Cardiovascular capacity or health is also a critical determinant of individual health outcomes ( [[#Schuster--2017|Schuster et al., 2017]] ). Medications to treat CVDs, such as diuretics and beta-blockers, may impair resilience to heat stress ( [[#Stewart--2017|Stewart et al., 2017]] ). Other mediating factors in the causal pathway range from alcohol consumption ( [[#Cusack--2011|Cusack et al., 2011]] ; [[#Epstein--2019|Epstein and Yanovich, 2019]] ) and obesity ( [[#Speakman--2018|Speakman, 2018]] ) to pre-existing conditions, such as diabetes and hyperlipidaemia, and urban characteristics ( [[#Chen--2019|Chen et al., 2019]] ; [[#Sera--2019|Sera et al., 2019]] ).

Under extreme heat conditions, increases in hospitalisations have been observed for fluid disorders, renal failure, urinary tract infections, septicaemia, general heat stroke as well as unintentional injuries ( [[#Borg--2017|Borg et al., 2017]] ; [[#Phung--2017|Phung et al., 2017]] ; [[#Goggins--2017|Goggins and Chan, 2017]] ; [[#Hayashida--2019|Hayashida et al., 2019]] ; [[#Hopp--2018|Hopp et al., 2018]] ; [[#Ito--2018|Ito et al., 2018]] ; [[#Kampe--2016|Kampe et al., 2016]] ; [[#McTavish--2018|McTavish et al., 2018]] ; [[#Ponjoan--2017|Ponjoan et al., 2017]] ; [[#van%20Loenhout--2018|van Loenhout et al., 2018]] ). Hospitalisations and mortality due to respiratory disorders also occur during heat events with the interactive role of air quality being important for some locations but not others ( [[#Krug--2019|Krug et al., 2019]] ; [[#Pascal--2021|Pascal et al., 2021]] ; [[#Patel--2019|Patel et al., 2019]] ). Increased levels of heat-related hospitalisation also manifest in elevated levels of emergency service calls ( [[#Cheng--2016|Cheng et al., 2016]] ; [[#Guo--2017|Guo, 2017]] ; [[#Papadakis--2018|Papadakis et al., 2018]] ; [[#Williams--2020|Williams et al., 2020]] ).

Heat- and cold-related health outcomes vary by location ( [[#Dialesandro--2021|Dialesandro et al., 2021]] ; [[#Hu--2019|Hu et al., 2019]] ; [[#Phung--2016|Phung et al., 2016]] ), suggesting outcomes are highly moderated by socioeconomic, occupational and other non-climatic determinants of individual health and socioeconomic vulnerability ( [[#Åström--2020|Åström et al., 2020]] ; [[#McGregor--2017|McGregor et al., 2017]] ; [[#McGregor--2017|McGregor et al., 2017]] ; [[#Schuster--2017|Schuster et al., 2017]] ; [[#Benmarhnia--2015|Benmarhnia et al., 2015]] ; [[#Watts--2019|Watts et al., 2019]] ) ( ''high confidence'' ). For example, access to air conditioning is an important determinant of heat-related health outcomes for some locations ( [[#Guirguis--2018|Guirguis et al., 2018]] ; [[#Ostro--2010|Ostro et al., 2010]] ). Although there is a paucity of global level studies of the effectiveness of air conditioning for reducing heat-related mortality, a recent assessment indicates increases in air conditioning explains only part of the observed reduction in heat-related excess deaths, amounting to 16.7% in Canada, 20.0% in Japan, 14.3% in Spain and 16.7% in the US ( [[#Sera--2020|Sera et al., 2020]] ).

Significant effects of heat exposure are evident in sport and work settings with exertional heat illness leading to death and injury ( [[#Adams--2020|Adams and Jardine, 2020]] ). Although most studies of heat-related sports injuries refer to high-income countries, these point to an increasing number of heat injuries with widening participation in sport and an increasing frequency of extreme heat events. The highest rates of exertional heat illness are reported for endurance type events (running, cycling and adventure races), American football and athletics ( [[#Gamage--2020|Gamage et al., 2020]] ; [[#Grundstein--2017|Grundstein et al., 2017]] ; [[#Kerr--2020|Kerr et al., 2020]] ; [[#McMahon--2021|McMahon et al., 2021]] ; [[#Yeargin--2019|Yeargin et al., 2019]] ). The health, safety and productivity consequences of working in extreme heat are widespread ( [[#Ma--2019|Ma et al., 2019]] ; [[#Morabito--2021|Morabito et al., 2021]] ; [[#Kjellstrom--2019|Kjellstrom et al., 2019]] ; [[#Orlov--2020|Orlov et al., 2020]] ; [[#Smith--2021|Smith et al., 2021]] ; [[#Vanos--2019|Vanos et al., 2019]] ; [[#Varghese--2020|Varghese et al., 2020]] ; [[#Williams--2020|Williams et al., 2020]] ). Occupational heat strain in outdoor workers manifests as dehydration, mild reduction in kidney function, fatigue, dizziness, confusion, reduced brain function, loss of concentration and discomfort ( [[#Al-Bouwarthan--2020|Al-Bouwarthan et al., 2020]] ; [[#Boonruksa--2020|Boonruksa et al., 2020]] ; [[#Habibi--2021|Habibi et al., 2021]] ; [[#Levi--2018|Levi et al., 2018]] ; [[#Venugopal--2021|Venugopal et al., 2021]] ; [[#Xiang--2014|Xiang et al., 2014]] ). In the case of armed forces, a global review of the available literature points to a slightly higher incidence of heat stroke in men compared to women but a higher proportion of heat intolerance and greater risk of exertional heat illness amongst women ( [[#Alele--2020|Alele et al., 2020]] ). There is also some evidence that for healthcare workers, the risk of occupational heat stress grew during the COVID-19 pandemic due to the need to wear personal protective equipment ( [[#Foster--2020|Foster et al., 2020]] ; [[#Lee--2020|Lee et al., 2020]] ; [[#Messeri--2021|Messeri et al., 2021]] ). Based on a systematic review of the literature, one study estimates global costs from heat-related lost work time were USD 280 billion in 1995 and USD 311 billion in 2010, with low- and middle-income countries and countries with warmer climates experiencing greater losses as a proportion of gross domestic project (GDP) ( [[#Borg--2021|Borg et al., 2021]] ). Other global level assessments note an increase in the potential hours of work lost due to heat over the 2000–2018 period; in 2018, 133.6 billion potential work hours were lost, amounting to 45 billion hours more than in 2000 ( [[#Watts--2019|Watts et al., 2019]] ). For China, heat-related productivity losses have been estimated at 9.9 billion hours in 2019, equivalent to 0.5% of the total national work hours for that year, with Guangdong province, one of the warmest regions in China, accounting for almost a quarter of the losses ( [[#Cai--2021|Cai et al., 2021]] ).

Wide ranging knowledge regarding the specific detection of heat- and cold-related mortality/morbidity and its attribution to observed climate change is lacking ''.'' Although there has been an observed increase in winter-season temperatures for a number of regions, to date there is variable evidence for a consequential reduction in winter mortality and susceptibility to cold over time due to milder winters; some countries demonstrate decreasing trends, while other countries show stable or even increasing trends in cold-attributable mortality fractions over time (e.g., [[#Arbuthnott--2020|Arbuthnott et al. (2020)]] ; [[#Åström--2013|Åström et al. (2013)]] ; [[#Diaz--2019|Diaz et al. (2019)]] ; [[#Hajat--2017|Hajat (2017)]] ; Hanigan et al. (2021); [[#Lee--2018b|Lee et al. (2018b)]] ). While there is a burgeoning literature on the attribution of extreme heat events to climate change (e.g., [[#Vautard--2020|Vautard et al. (2020)]] ), the number of studies that assess the extent to which observed changes in heat-related mortality may be attributable to climate change is small ( [[#Ebi--2020|Ebi et al., 2020]] ). During the 2003 European heatwave, anthropogenic climate change increased the risk of heat-related mortality by approximately 70% and 20% for London and Paris, respectively ( [[#Mitchell--2016|Mitchell et al., 2016]] ). For the severe heat event across Egypt in 2015, the impact on human discomfort was 69% (±17%) more likely due to anthropogenic climate change ( [[#Mitchell--2016|Mitchell, 2016]] ), and for Stockholm, Sweden, it has been estimated that mortality due to temperature extremes for 1980 to 2009 was double what would have occurred without climate change ( [[#Åström--2013|Åström et al., 2013]] ). To date there has only been one multi-country attempt to quantify the heat-related human health impacts that have already occurred due to climate change. Based on an analysis of 732 locations spanning 43 countries for the 1991–2018 period, the study found that on average 37.0% (inter-quartile range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change, equivalent to an average mortality rate of 2.2/100,000 (median: 1.67/100,000; interquartile range: 1.08–2.34/100,000). Regions with a high attributed percentage (&gt; 50%) include southern and western Asia (Iran and Kuwait), Southeast Asia (Philippines and Thailand) and several countries in Central and South America. Those with lower values (&lt; 35%) include Western Europe (the Netherlands, Germany and Switzerland), eastern Europe (Moldova, the Czech Republic and Romania), southern Europe (Greece, Italy, Portugal and Spain), North America (USA) and eastern Asia (China, Japan and South Korea) ( [[#Vicedo-Cabrera--2021|Vicedo-Cabrera et al., 2021]] ). Due to data restrictions, some of the poorest and most susceptible regions to climate change and increases in heat exposure, such as west and east Africa ( [[#Asefi-Najafabady--2018|Asefi-Najafabady et al., 2018]] ; [[#Sylla--2018|Sylla et al., 2018]] ) and south Asia, could not be included in the analysis ( [[#Mitchell--2021|Mitchell, 2021]] ).

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==== 7.2.4.2 Injuries Arising from Extreme Weather Events Other than Heat and Cold ====

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Injuries comprise a substantial portion of the global burden of disease. In 2019, injuries comprised 9.82% of total global DALYs and 7.61% of deaths (Vos et al., 2020). The causal pathways for many injuries, particularly those from heat and extreme weather events, flooding and fires, exhibit clear climate sensitivity ( [[#Roberts--2007|Roberts and Arnold, 2007]] ; [[#Roberts--2005|Roberts and Hillman, 2005]] ), as do some injuries occurring in occupational settings ( [[#Marinaccio--2019|Marinaccio et al., 2019]] ; [[#Sheng--2018|Sheng et al., 2018]] ), but a comprehensive assessment of climate sensitivity in injury causal pathways has not been done. Certain groups, including Indigenous Peoples, children and the elderly ( [[#Ahmed--2020|Ahmed et al., 2020]] ) are at greater risk for a wide range of injuries. Extreme events impose substantial disease burden directly as a result of traumatic injuries, drowning and burns and large mental health burdens associated with displacement ( [[#Fullilove--1996|Fullilove, 1996]] ), depression and post-traumatic stress disorder (PTSD), but the overall injury burden associated with extreme weather is not known. It is known that the Asia-Pacific region has experienced the highest relative burden of injuries from extreme weather in recent decades ( [[#Hashim--2016|Hashim and Hashim, 2016]] ).

Extreme weather imposes a substantial morbidity and mortality burden that is quite variable by location and hazard. The proportion of this burden related specifically to injuries is not established. From 1998 to 2017 there were 526,000 deaths from 11,500 extreme weather events, and the average annual attributable all-cause mortality incidence in the ten most affected countries was 3.5 per 100,000 population ( [[#Eckstein--2017|Eckstein et al., 2017]] ). Rates can be much higher; mortality incidence in Puerto Rico and Dominica from extreme weather were 90.2 and 43.7 per 100,000 population in 2017, respectively ( [[#Eckstein--2017|Eckstein et al., 2017]] ). Not all of these deaths are from injuries, and the proportion of mortality and morbidity associated with injuries varies by location and hazard. One review found that one-year post-event prevalence rates for injuries associated with extreme events (floods, droughts, heatwaves and storms) in developing countries ranged from 1.4% to 37.9% ( [[#Rataj--2016|Rataj et al., 2016]] ). Other literature has documented an increase in the risk of motor vehicle accidents in association with extreme precipitation ( [[#Liu--2017|Liu et al., 2017]] ; [[#Stevens--2019|Stevens et al., 2019]] ), temperature ( [[#Leard--2019|Leard and Roth, 2019]] ) and sandstorms ( [[#Islam--2019|Islam et al., 2019]] ) and an increased risk of traumatic occupational injuries associated with temperature extremes, particularly extreme heat, likely from fatigue and decreased psychomotor performance ( [[#Varghese--2019|Varghese et al., 2019]] ).

There is clear evidence of climate sensitivity for multiple injuries from floods, fires and storms, but there is a need for additional evidence regarding the current injury burden attributable to climate change. It is ''as likely as not'' that climate change has increased the current burden of disease from injuries related to extreme weather, particularly in low-income settings ''(low confidence)'' . Approximately 120 million people are exposed to coastal flooding annually ( [[#Nicholls--2007|Nicholls et al., 2007]] ), causing an estimated 12,000 deaths ( [[#Shultz--2005|Shultz et al., 2005]] ), and there is significant concern for worsening flooding associated with climate change ( [[#Shultz--2018a|Shultz et al., 2018a]] ; [[#Shultz--2018b|Shultz et al., 2018b]] ; [[#Woodward--2018|Woodward and Samet, 2018]] ) but very limited quantification of attributable burden. A range of adverse health outcomes has been identified in a study of fires in sub-zero temperatures that are thought to be increasing in frequency due to climate change ( [[#Metallinou--2017|Metallinou and Log, 2017]] ).

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==== 7.2.4.3 Observed Impacts on Maternal, Foetal and Neonatal Health ====

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Maternal and neonatal disorders accounted for 3.7% of total global deaths and 7.8% of global DALYs in 2019 (Vos et al., 2020). Children and pregnant women have potentially higher rates of vulnerability and/or exposure to climatic hazards, extreme weather events and undernutrition ( [[#Garcia--2016|Garcia and Sheehan, 2016]] ; [[#Sorensen--2018|Sorensen et al., 2018]] ; [[#Chersich--2018|Chersich et al., 2018]] ). Available evidence suggests that heat is associated with higher rates of pre-term birth ( [[#Wang--2020|Wang et al., 2020]] ), low birthweight, stillbirth, neonatal stress ( [[#Cil--2017|Cil and Cameron, 2017]] ; [[#Kuehn--2017|Kuehn and McCormick, 2017]] ) and adverse child health ( [[#Kuehn--2017|Kuehn and McCormick, 2017]] ). Extreme weather events are associated with reduced access to prenatal care, unattended deliveries ( [[#Abdullah--2019|Abdullah et al., 2019]] ) and decreased paediatric healthcare access ( [[#Haque--2019|Haque et al., 2019]] ).

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==== 7.2.4.4 Observed Impacts on Malnutrition ====

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''Climate variability and change contribute to food insecurity that can lead to malnutrition, including undernutrition, overweight and obesity, and to disease susceptibility, particularly in low- and middle-income countries'' ( ''high confidence'' ) ''.'' Since AR5, analyses of the links between climate change and food expanded beyond undernutrition to include the impacts of climate change on a wider set of diet- and weight-related risk factors and their impacts on NCDs, along with the role of dietary choices for GHG emissions ( [[#IPCC--2019b|IPCC, 2019b]] ) including dietary inadequacy (deficiencies, excesses or imbalances in energy, protein and micronutrients), infections and sociocultural factors (Global Nutrition Report 2020). Undernutrition exists when a combination of insufficient food intake, health, and care conditions results in one or more of the following: underweight for age, short for age (stunted), thin for height (wasted), or functionally deficient in vitamins and/or minerals (micronutrient malnutrition or ‘hidden hunger’). Food insecurity and poor access to nutrient-dense food contribute not only to undernutrition but also to obesity and susceptibility to NCDs in low- and middle-income countries ( [[#FAO--2018|FAO et al., 2018]] ; [[#Swinburn--2019|Swinburn et al., 2019]] ).

Globally, more than 690 million people are undernourished, 144 million children are stunted (chronic undernutrition), 47 million children are wasted (acute undernutrition), and more than 2 billion people have micronutrient deficiencies ( [[#FAO--2020|FAO, 2020]] ). More than 135 million people across 55 countries experienced acute hunger requiring urgent food, nutrition and livelihood assistance in 2019 (FSIN/GNAFC, 2020). The COVID-19 pandemic is projected to increase the number of acutely food insecure people to 270 million people ( [[#FSIN--2020|FSIN, 2020]] ) and worsen malnutrition levels ( [[#FAO--2020|FAO et al., 2020]] ; [[#Rippin--2020|Rippin et al., 2020]] ). The relationships between climate change and obesity vary based on geography, population sub-groups and/or stages of economic growth and population growth (An et al., 2017). Increasing temperatures could contribute to obesity through reduced physical activity, increased prices of produce or shifts in eating patterns of populations towards more processed foods ( [[#An--2018|An et al., 2018]] ). In the largest global study to date exploring the connections between child diet diversity and recent climate, data from 19 countries in six regions (Asia, Central America, South America, north Africa, southeast Africa and west Africa) indicated significant reductions in diet diversity associated with higher temperatures and significant increases in diet diversity associated with higher precipitation ( [[#Niles--2021|Niles et al., 2021]] ).

Climate change can affect the four aspects of food security: food production and availability, stability of food supplies, access to food and food utilisation ( [[#IPCC--2019b|IPCC, 2019b]] ). Access to sufficient food does not guarantee nutrition security. Extreme weather and climate events can result in inadequate or insufficient food consumption, increasing susceptibility to infectious diseases ( [[#Rodriguez-Llanes--2016|Rodriguez-Llanes et al., 2016]] ; [[#Gari--2017|Gari et al., 2017]] ; [[#Kumar--2016|Kumar et al., 2016]] ; [[#Lazzaroni--2016|Lazzaroni and Wagner, 2016]] ) but also to being overweight or obese and increasing susceptibility to non-communicable diseases in low- and middle-income countries (FAO, 2018; [[#Swinburn--2019|Swinburn et al., 2019]] ).

Nearly half of all deaths in children under five years of age are attributable to undernutrition, putting children at greater risk of dying from common infections. Undernutrition in the first 1,000 days of a child’s life can lead to stunted growth, which can result in impaired cognitive ability and reduced future school and work performance and the associated costs of stunting in terms of lost economic growth can be of the order of 10% of GDP yr –1 in Africa (UNICEF/WHO/WBG, 2019).

At the same time, diseases associated with high-calorie, unhealthy diets are increasing globally, with 38.3 million overweight children under five years of age (Global Nutrition Report, 2018), 2.1 billion overweight or obese adults and the global prevalence of diabetes almost doubling in the past 30 years ( [[#Swinburn--2019|Swinburn et al., 2019]] ). Unbalanced diets, such as diets low in fruits and vegetables and high in red and processed meat, are the number one risk factor for mortality globally and in most regions (Gakidou et al., 2018; [[#Afshin--2019|Afshin et al., 2019]] ).

Socioeconomic factors that mediate the influence of climate change on nutrition include cultural and societal norms; governance, institutions, policies and fragility; human capital and potential; and social position and access to healthcare, education and food aid ( [[#Rozenberg--2017|Rozenberg, 2017]] ; Alkerwi et al. 2015; [[#Tirado--2017|Tirado, 2017]] ; [[#FAO--2018|FAO et al., 2018]] ; Global Nutrition Report 2020). Extreme events may affect access to adequate diets, leading to malnutrition and increasing the risk of disease ( [[#Beveridge--2019|Beveridge et al., 2019]] ; [[#Rodriguez-Llanes--2016|Rodriguez-Llanes et al., 2016]] ; [[#Gari--2017|Gari et al., 2017]] ; [[#Kumar--2016|Kumar et al., 2016]] ; [[#Lazzaroni--2016|Lazzaroni and Wagner, 2016]] ; [[#Thiede--2020|Thiede and Gray, 2020]] ).

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==== 7.2.4.5 Observed Impacts on Exposure to Chemical Contaminants ====

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''Climate change in northern regions, including Arctic ecosystems, is causing permafrost to thaw, creating the potential for mercury (Hg) to enter the food chain'' ( ''medium agreement, low evidence'' ) ''as methyl mercury (MeHg), which is highly neurotoxic and nephrotoxic and bioaccumulates and biomagnifies throughout the food chain via dietary uptake of fish, seafood and mammals.'' Mercury methylation processes in aquatic environments have been found to be exacerbated by ocean warming, coupled with more acidic and anoxic sediments ( [[#FAO--2020|FAO, 2020]] ). Consumption of mercury-contaminated fish has been found to be linked to neurological disorders due to methyl mercury poisoning (i.e., Minamata disease) that is associated with climate change-contaminant interactions that alter the bioaccumulation and biomagnification of toxic and fat-soluble persistent organic pollutants and polychlorinated biphenyls (PCBs) ( [[#Alava--2017|Alava et al., 2017]] ) in seafood and marine mammals ( ''medium confidence)'' . Indigenous Peoples have a higher exposure to such risks because of the accumulation of such toxins in traditional foods (J.J. et al., 2017). Contamination of food with PCBs and dioxins has a range of adverse health impacts ( [[#Lake--2015|Lake et al., 2015]] ).

[[IPCC:Wg2:Chapter:Chapter-5|Chapter 5]] (Sections 5.4.3, 5.5.2.3, 5.8.1, 5.8.2, 5.8.3, 5.9.1, 5.11.1, 5.11.3, 5.12.3) discusses the possible impacts of climate change on food safety, including exposure to toxigenic fungi, PCBs and other POPs, mercury and harmful algal blooms.

''Climate change may affect animal health management practices, potentially leading to an increased use of pesticides or veterinary drugs (such as preventive antimicrobials) that could result in increased levels of residues in foods'' ( ''high agreement, medium/low evidence'' ) ( [[#Beyene--2015|Beyene et al., 2015]] ; [[#FAO%20and%20WHO--2018|FAO and WHO, 2018]] ; European Food Safety Authority, 2020; [[#MacFadden--2018|MacFadden et al., 2018]] ).

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