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

=== 7.2.1 Observed Impacts on Health and Well-Being ===

<div id="h2-9-siblings" class="h2-siblings"></div>

''Eleven categories of diseases and health outcomes have been identified in this assessment as being climate-sensitive through direct pathways (e.g., heat and floods) and indirect pathways mediated through natural and human systems and economic and social disruptions (e.g., disease vectors, allergens, air and water pollution, and food system disruption) (high confidence)'' . A key challenge in quantifying the specific relationship between climate and health outcomes is distinguishing the extent to which observed changes in prevalence of a climate-sensitive disease or condition are attributable directly or indirectly to climatic factors as opposed to other non-climatic causal factors ( [[#Ebi--2020|Ebi et al., 2020]] ). A subsequent challenge is then determining the extent to which those observed changes in health outcomes associated with climate are attributable to events or conditions associated with natural climate variability compared to persistent human induced shifts in the mean and/or the variability characteristics of climate (i.e., anthropogenic climate change). The context within which the impacts of climate change affect health outcomes and health systems is described in this chapter as being a function of risk, which is in turn a product of interactions between hazard, exposure and vulnerability (Chapter 1), with the impacts in turn having the potential to reinforce vulnerability and/or exposure to risk (Figure 7.4).

<div id="_idContainer015" class="Figure"></div>

[[File:ccbe467c63489f5bbcd9fd274136e8e6 IPCC_AR6_WGII_Figure_7_004.png]]

'''Figure 7.4 |''' '''Interactions between hazard, exposure and vulnerability that generate impacts on health systems and outcomes, with selected examples.''' WBD: waterborne disease, VBD: Vector-borne disease, and FBD: Food-borne disease.

<div id="box-7.2" class="h2-container box-container"></div>

'''Box 7.2 | The Global Burden of Climate-Sensitive Health Outcomes Assessed in this Chapter'''
<div id="h2-26-siblings" class="h2-siblings"></div>

Global statistics for death and loss of health are increasingly described in terms of ''burden'' , which describes gaps between a population’s actual health status and what its status would be if its members lived free of disease and disability to their collective life expectancy ( [[#Shaffer--2019|Shaffer et al., 2019]] ). Burden for each disease/health outcome is estimated by adding together the number of years of life lost (YLL) by a person because of early death and the number of years of life lived with disability (YLD) from the considered outcome. The resulting statistic, the disability-adjusted life year (DALY) represents the loss of one year of life lived in full health. The total global burden of disease (Vos et al., 2020), expressed in DALYs, is what the world’s health systems must manage and is reported annually in Global Burden of Disease Study (Vos et al., 2020). The estimated current global burden of climate-sensitive diseases and conditions described in this chapter, and the geographical regions most affected, are summarised in Table Box 7.2.1. As was observed in [[IPCC:Wg2:Chapter:Chapter-11|Chapter 11]] (‘Human Health’) of AR5, the ‘background climate-related disease burden of a population is often the best single indicator of vulnerability to climate change – doubling of risk of disease in a low disease population has much less absolute impact than doubling of the disease when the background rate is high.’

The global magnitude of climate-sensitive diseases was estimated in 2019 to be 39,503,684 deaths (69.9% of total annual deaths) and 1,530,630,442 DALYs (Vos et al., 2020). Of these, cardiovascular diseases (CVDs) comprised the largest proportion of climate-sensitive diseases (32.8% of deaths and 15.5% DALYs). The next largest category consists of respiratory diseases – with chronic respiratory disease contributing to 7% of deaths and 4.1% of DALYs and respiratory infection and tuberculosis contributing to 6.5% of deaths and 6% of DALYs. The observed trend of climate-sensitive disease deaths since 1990 is marked by increasing cardiovascular mortality and decreasing mortality from respiratory infections, enteric diseases and other infectious diseases (Vos et al., 2020). Figure Box 7.2.1 illustrates specific global trends between 1990 and 2017 of selected health outcomes estimated by GBDs (Ahmad Kiadaliri et al. 2018).

[[File:58b7a32815254cc1672186732a478901 IPCC_AR6_WGII_Figure_7_Box_7_2_1.png]]

'''Figure Box 7.2.1 |''' '''Global trends of selected health outcomes estimated by GBDs.''' Source: Ahmad Kiadaliri et al. (2018a).

'''Table Box 7.2.1 |''' Global burden of climate-sensitive health risks assessed in this chapter (in order of assessment) (Vos et al., 2020) and synthesis of major observed and projected impacts in most affected regions. Blue represents an increase in positive health impacts, green represents an increase in negative health impacts and yellow represents an increase in both positive and negative impacts, but not necessarily in equal proportions. The confidence level refers to both the attributed observed and projected changes to climate change. No assessment means the evidence is insufficient for assessment.

{| class="wikitable"
|-
!
! colspan="2"| '''Data from Global Burden of Disease 2019 (Vos et al. 2020)'''

! colspan="3"| '''[https://www.ipcc.ch/report/ar6/wg2/chapter/chapter-7 Chapter 7] Assessment'''

|-
| '''Health outcome (disease/condition)'''

| '''Global annual deaths'''

| '''Regions most affected (deaths)'''

| '''Climate change observed impacts'''

| '''Climate change projected impacts in most affected regions'''

| '''Selected key references of the Assessment'''

|-
| '''Malaria'''

| 643,381

| Africa (92%)

| \****

| \***

| [[#M’Bra--2018|M’Bra et al. (2018)]] ; Caminade et al. (2019); [[#Gibb--2020|Gibb et al. (2020)]] ; [[#Tompkins--2016b|Tompkins and Caporaso (2016b)]] ; [[#Ebi--2021a|Ebi et al. (2021a)]]

|-
| '''Dengue'''

| 36,055

| Asia (96%)

| \***

| \***

| [[#Bhatt--2013|Bhatt et al. (2013)]] ; Rocklöv &amp; Dubrow (2020); [[#Messina--2019|Messina et al. (2019)]] ; [[#Monaghan--2018|Monaghan et al. (2018)]]

|-
| '''Diarrhoeal diseases'''

| 1,534,443

| Asia (56%)

| \***

| \**

| Cissé (2019); Levy et al. (2018); [[#Lo%20Iacono--2017|Lo Iacono et al. (2017)]] ; [[#Carlton--2016|Carlton et al. (2016)]]

|-
| '''Salmonella'''

| 79,046

| Africa (89%)

| \***

| \**

| Cissé (2019); [[#Smith--2019|Smith and Fazil (2019)]] ; [[#Lake--2017|Lake (2017)]]

|-
| '''RTIs'''

| 2,493,200

| Asia (47%)

| \**

|
| Geier et al. (2018); [[#Oluwole--2017|Oluwole (2017)]]

|-
| '''Non-communicable respiratory illness'''

| 3,741,705

| Asia (74%)

| \***

| \**

| [[#Schweitzer--2018|Schweitzer et al. (2018)]] ; Hansel et al. (2016); [[#Collaco--2018|Collaco et al. (2018)]] ; [[#D’Amato--2020|D’Amato et al. (2020)]] ; [[#Silva--2017|Silva et al. (2017)]] ; Doherty et al. (2017); [[#Beggs--2021|Beggs (2021)]]

|-
| '''CVD'''

| 18,562,510

| Asia (58%)

| \**

| \***

| [[#Stewart--2017|Stewart et al. (2017)]] ; Phung (2016); Sun (2018); Wang (2016); Tian (2019); Chen (2019); Zhang (2018)

|-
| '''Death from malignant neoplasms'''

| 10,079,637

| Asia (55%)

| \***

|
| [[#Ahmed--2014|Ahmed et al. (2014)]] ; Modenese et al. (2018); [[#Prueksapanich--2018|Prueksapanich et al. (2018)]]

|-
| '''Diabetes'''

| 1,551,170

| Asia (56%)

| \**

| \**

| [[#Hajat--2017|Hajat et al. (2017)]] ; [[#Xu--2019b|Xu et al. (2019b)]] ; [[#Li--2014|Li et al. (2014)]] ; [[#Yang--2016|Yang et al. (2016)]] ; Velez-Valle et al. (2016); [[#Quast--2019|Quast and Feng (2019)]]

|-
| '''Environmental heat and cold exposure'''

| 47,461

| Asia (46%)

| \***

| \****

| [[#Zhang--2019b|Zhang et al. (2019b)]] ; [[#Green--2019|Green et al. (2019)]] ; [[#Murray--2020|Murray et al. (2020)]] ; [[#Ma--2021|Ma and Yuan (2021)]] ; [[#Jones--2018|Jones et al. (2018)]] ; [[#Russo--2019|Russo et al. (2019)]] ; [[#Gosling--2017|Gosling et al. (2017)]]

|-
| '''Nutritional deficiencies'''

| 251,577

| Africa (43%)

| \***

| \***

| [[#Mbow--2019|Mbow et al. (2019)]] ; [[#Lloyd--2018|Lloyd (2018)]] ; [[#Springmann--2016b|Springmann et al. (2016b)]] ; [[#Zhu--2018|Zhu et al. (2018)]] ; [[#Weyant--2018|Weyant et al. (2018)]]

|-
| '''Mental health''' a

| n.a.

| n.a.

| \****

| \****

| Cianconi et al. (2020); [[#Charlson--2021|Charlson et al. (2021)]] ; [[#Hayes--2018|Hayes and Poland (2018)]] ; Hrabok et al. (2020); [[#Obradovich--2018|Obradovich et al. (2018)]]

|-
| colspan="6"| '''Legend'''

|-
| colspan="2"| '''Climate change impacts'''

|
| colspan="2"| '''Confidence'''

|
|-
| colspan="2"| ''Positive health impacts''

|
| colspan="2"| ''Very high''

| \****

|-
| colspan="2"| ''Negative health impacts''

|
| colspan="2"| ''High''

| \***

|-
| colspan="2"| ''Positive and negative impacts''

|
| colspan="2"| ''Medium''

| \**

|-
| colspan="2"| ''No assessment''

|
| colspan="2"| ''Low''

| \*

|}

Notes:

(a) Mental health data were not available (n.a.) due to lack of information in GBD 2019 related to annual deaths and the most affected regions.

<div id="7.2.2" class="h2-container"></div>

<span id="observed-impacts-on-communicable-diseases"></span>