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Don't blame the BAME: Ethnic and structural inequalities in susceptibilities to COVID-19.
American Journal of Human Biology ( IF 2.9 ) Pub Date : 2020-07-16 , DOI: 10.1002/ajhb.23478
Gillian R Bentley 1
Affiliation  

One of the striking features emerging from the COVID‐19 pandemic has been the early recognition of ethnic disparities in both vulnerability to contracting the disease, as well as its outcome. These disparities were first reported in news outlets (Blow, 2020; Cowan, 2020; Godin, 2020; The Guardian, 2020a) and, more recently, verified in academic journals (e.g., Bhala, Curry, Martineau, Agyeman, & Bhopal, 2020; Khunti, Singh, Pareek, & Hanif, 2020; Laurencin & McClinton, 2020; Webb Hooper, Nápoles, & Pérez‐Stable, 2020), as well as through organizations responsible for gathering health statistics (eg, APM Research Lab, 2020; CDC, 2020; ICNARC, 2020; ONS, 2020). In particular, Black, Asian, and minority ethnic (BAME) groups have emerged as more susceptible to higher morbidity and mortality than either UK or USA white groups. The Office for National Statistics (ONS)—the central organization responsible for producing demographic statistics in the UK—recently stated that Blacks were over four times more likely than whites in England and Wales to die from COVID‐19, figures that were equivalent across both genders. The ONS statistics included both confirmed and suspected cases of COVID‐19, as well as deaths in hospitals and the community. Similarly, in the USA, the Centers for Disease Control (CDC) has reported that almost twice as many Black and Hispanic individuals were hospitalized with COVID‐19 than are proportionally represented in the community (CDC, 2020).

From a biocultural perspective, it has been heartening to witness an early recognition in both the UK and the USA that inter‐population variation in susceptibilities to corona virus lies not in biology or our genes, but mostly in social and structural differences between human groups that have often led to health disparities (Bhala et al., 2020; Webb Hooper et al., 2020) (see Figure 1). The existence of such disparities is commonly referred to in anthropological and related literatures as “structural violence” (Farmer, Nizeye, Stulac, & Keshavjee, 2006; Galtung, 1969). Such considerations of structural inequalities in health have, for the most part, dominated emerging reports rather than questions of genes, ethnicity or(particularly, in North American parlance) the contested word “race” (Fuentes et al., 2019). For example, when socioeconomic factors as well as preexisting health conditions were controlled for in the ONS (2020) study cited above, the mortality risk for Blacks was reduced, but remained almost twice as high as whites, and higher for males (raising questions of course about what explains the residual differences); the figures for South Asians were similar (ONS, 2020). The ONS, at the time, was not able to include the types of jobs held by individuals among the confounders, which they argue could also affect their models.

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FIGURE 1
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The relationship of structural inequalities to susceptibility to COVID‐19

However, more recently, insidious and potentially racist allusions are beginning to emerge appearing to blame African Americans as somehow responsible for the relatively large number of cases and deaths from COVID‐19 in the USA, stoking age‐old tropes, and attributing morbidity and mortality to the behaviors and predispositions of BAME groups (Guardian, 2020b; Strings, 2020). The Guardian (2020b) has speculated about the political motivations behind these attributions.

In reality, structural or social inequalities that affect individual vulnerabilities to SARS‐CoV‐2 include exposures through types of employment, whether people are working in essential transport networks carrying large numbers of people, or in small grocery shops that place BAME communities at greater risk of contracting COVID‐19 (Figure 1). These communities are also frequently at higher risk for metabolic disorders including obesity, cardiovascular diseases, hypertension and type 2 diabetes, some of which are linked to higher risks for contracting COVID‐19, and poorer outcomes once contracted (Azkur et al., 2020). Given that mortality appears to result more from the inflammatory response engendered from exposure to COVID‐19, as well as its ability to attack many organs in the body, metabolic diseases render many individuals at high risk for adverse outcomes once they become ill (Matricardi, Dal Negro, & Nisini, 2020). Front‐line health workers are also at high risk for contracting COVID‐19. In England, the National Health Service (NHS) has long imported qualified doctors, nurses, and carers from abroad (now 13% of all staff), and proportionally twice as many BAME individuals work for the NHS as in the rest of the economy (Baker, 2019). A recent report also suggested that BAME health workers have had less access to personal protective equipment than their white European counterparts (Royal College of Nursing, 2020). In the USA, there are additional social problems faced by minority groups, such as the potential lack of health care due to costs of health insurance. This is a problem that BAME groups do not face in the UK with its national health service. In addition, BAME communities often live in neighborhoods classified as food deserts which affect access to healthy foods, or they lack green spaces for exercise and fresh air. Ethnic minorities frequently live in areas or regions that are more polluted than others, situations which can be exacerbated by lack of service provision including garbage collection.

These kinds of “structural violence” are common for ethnic minorities in many northern nations, and can mostly explain inter‐group susceptibility to COVID‐19. Nevertheless, are there potentially any underlying biological realities that could also render some groups more vulnerable to poorer outcomes after contracting the disease? There are clearly differences in susceptibility based on both age and gender that remain little understood, at present, and that are not wholly due to either social or behavioral differences. In addition, there may be variation in the way that some individuals respond to drugs—so‐called pharmacogenetic differences—that might explain recovery times or reactions to particular pharmaceutical interventions (Shah, 2005). Just as some individuals appear immune to HIV‐AIDS (Carrington et al., 1996), similarly some individuals may also, for unknown reasons, be immune to SARS‐CoV‐2, or are asymptomatic carriers (Azkur et al., 2020).

There have been a few attempts to explore these underlying biological issues in relation to SARS viruses. One example is the study of population differences in genetic polymorphisms in the angiotensin‐converting enzyme‐2 (ACE2) receptor, found in many human organs such as the lung, brain, kidney, heart and gut, and through which related corona viruses (SARS‐CoV‐1, and the more recent SARS‐CoV‐2) binds to the new host, primarily through lung entry. Although East Asians appear to have higher expression of ACE2 levels compared to people of European descent, there does not seem to be any association between genetic variants and COVID‐19 outcome (Cao et al., 2020). Similarly, Nguyen et al. (2020) performed an in silico analysis of different classes of human leukocyte antigen (HLA) genotypes for their response to exposure to SARS‐CoV‐2, and also mapped different HLA variants globally to estimate the potential epidemiological impact at the population level. Again, while one HLA variant appeared to confer greater protection, another might render an individual more susceptible to COVID‐19, but neither were suggested to have an impact at a global level.

More recently, Genomics England (2020) has announced that they will begin a study of 20 000 hospitalized patients who have experienced the worst symptoms of COVID‐19, and will compare them to 15 000 patients who have had only mild symptoms, in an effort to explore potential genomic differences in susceptibility to the disease. The study will undoubtedly take some time to complete, and it is not known how the research will either collect or address other risk factors alongside genetic variability. Similarly, the Biobank longitudinal study in the UK has requested its current participants to enroll in a subsidiary study to examine those factors (genetic or otherwise) that could influence susceptibility to COVID‐19 (Biobank, 2020), although the proportion of BAME individuals participating in Biobank is lower than in the national population (Fry et al., 2017).Other physiological reasons for differential ethnic susceptibility to COVID‐19 have been suggested, including the potential of Vitamin D deficiency to increase susceptibility which would adversely affect people with darker skin living in countries at higher latitudes; this connection has since been downplayed (Hamiel, Kozer, & Youngster, 2020).

We should also remember that developmental and epigenetic influences mediated through the environment (socioeconomic and otherwise) can also impact individuals in later life and, through this route, affect their susceptibility to pathogens (Conching & Thayer, 2019; Nelson, 2009; Wells, 2016). South Asians, for example, are suggested to have a particular thin‐fat phenotype in response to long‐standing conditions of fetal under‐nutrition that render them particularly vulnerable to metabolic disorders in later life (Yajnik et al., 2003. These phenotypic traits also appear to be inter‐generationally preserved (van Steijn et al., 2009) and, as mentioned above, are currently linked to risks for COVID‐19 morbidity and mortality (Azkur et al., 2020).

Life course events such as allostatic load also seem to affect the rate at which individuals age biologically, such that their biological age is higher or lower than their chronological age. These discrepancies have been measured using a variety of techniques such as analyses of telomerelength, or epigenetic age, and many ethnic minorities appear to have higher biological ages relative to their chronological ages (eg, Levine & Crimmins, 2014; Simons et al., 2016). Given that COVID‐19 vulnerability is positively correlated with age, those individuals with a higher biological age might also be increasingly susceptible to the effects of COVID‐19.

More broadly, at a wider geographical level, long‐standing differences between countries in terms of Gross Domestic Product, infra‐structure and histories of colonial oppression, are thought to make many southern hemisphere, lower and middle‐income countries (LMICs) much more vulnerable to the emerging spread of corona virus and its health consequences (Bhutta, Basnya, Saha, & Laxminarayan, 2020; Roberton et al., 2020). There has also been speculation about the potentially catastrophic consequences of poor health, crowded conditions, lack of sufficient health personnel, and inability to socially distance in most of the camps housing refugees in various parts of the world (Kassem, 2020; Nott, 2020).

The statistics, in fact, looked encouraging early on, in that the numbers of cases and deaths appeared much lower in LMICs than in Europe, although the African Continent has been temporally behind Europe in exposure to SARS‐CoV‐2 (Hashim, 2020). In South Asia, the lower mortality rate was variably assigned to the demographic structure of the population, with a majority of younger individuals who may have been less likely to transmit SARS‐CoV‐2 (Hashim, 2020). In addition, it was speculated that exposure to more diseases during early life, or a more intense pattern of childhood immunizations, might somehow prime individuals to be more resistant to the virus. Early reports, however, that there might be some protection afforded by theBacillus Calmette‐Guérin(BCG) vaccination against tuberculosis (which was also routinely given to most children in the UK until 2005) have since been questioned (Kumar & Meena, 2020; Redelman‐Sidi, 2020). Another factor that might shield refugee camps from the pandemic is that they remain relatively isolated from tourist and visitor trails, while travel by inmates outside the camps is often restricted (Abdalfatah, 2020). However, more recently, the pandemic has been accelerating in southern countries, with rapidly increasing rates in the African Continent and in South Asia, providing challenges to the health care systems in many countries (Johns Hopkins University, 2020; Vaidyanathan, 2020), and an ominous portent of what might be the ultimate morbidity and mortality rates in LMICs.

Finally, and by no means least in relation to structural inequalities, as we develop new potential treatments and vaccines to treat COVID‐19, we must also be aware of the need to test and gather data on ethnic minorities, who are generally poorly represented in clinical trials and longitudinal health cohort studies (Jackson & Kuhlman, 2019).

The study of health in relation to structural inequalities, racism, and so‐called “racial medicine” has often been the focus of anthropology (eg, Conching & Thayer, 2019; Ifekwunigwe et al., 2017; Weigmann, 2006).We should be reassured, barring selective political rhetoric that has the potential to be extremely damaging, by the evident recognition in press outlets, popular science sources, and elsewhere, that ethnic inequalities in health do not reflect underlying human biology or genes, but rather the social environment in which human individuals find themselves embedded. We can only hope that the current pandemic might be an eventual catalyst to addressing and remediating these inequalities after decades of increasingly widening inequality gaps within human societies (Dorling, 2013; Marmot, 2015).



中文翻译:

不要责怪 BAME:对 COVID-19 易感性的种族和结构不平等。

COVID-19 大流行的显着特征之一是早期认识到在感染该疾病的脆弱性及其结果方面存在种族差异。这些差异首先在新闻媒体中报道(Blow,2020 年;Cowan,2020 年;Godin,2020 年;《卫报》,2020a),最近在学术期刊(例如 Bhala、Curry、Martineau、Agyeman 和 Bhopal,2020 年)中得到证实; Khunti, Singh, Pareek, & Hanif, 2020 ; Laurencin & McClinton, 2020 ; Webb Hooper, Nápoles, & Pérez‐Stable, 2020 ),以及通过负责收集健康统计数据的组织(例如,APM 研究实验室,2020 年;疾病预防控制中心,2020 年;ICNARC,2020 年;国家统计局,2020)。特别是,与英国或美​​国的白人群体相比,黑人、亚裔和少数族裔 (BAME) 群体的发病率和死亡率更高。英国负责编制人口统计数据的中央组织国家统计局 (ONS) 最近表示,在英格兰和威尔士,黑人死于 COVID-19 的可能性是白人的四倍以上,两者的数字相当性别。ONS 统计数据包括 COVID-19 确诊和疑似病例,以及医院和社区的死亡人数。同样,在美国,疾病控制中心 (CDC) 报告说,因 COVID-19 住院的黑人和西班牙裔人数几乎是社区中按比例表示的人数的两倍 (CDC, 2020 )。

从生物文化的角度来看,令人振奋的是,英国和美国早早认识到,群体间对冠状病毒的易感性差异不在于生物学或我们的基因,而主要在于人类群体之间的社会和结构差异。经常导致健康差异(Bhala 等人,2020 年;Webb Hooper 等人,2020 年)(见图 1)。这种差异的存在在人类学和相关文献中通常被称为“结构性暴力”(Farmer, Nizeye, Stulac, & Keshavjee, 2006; 加尔通,1969)。在大多数情况下,对健康结构性不平等的这种考虑主导了新出现的报告,而不是基因、种族或(特别是用北美的说法)有争议的“种族”一词(Fuentes 等人,2019 年)的问题。例如,当在上面引用的 ONS ( 2020 ) 研究中控制了社会经济因素和先前存在的健康状况时,黑人的死亡风险降低了,但几乎是白人的两倍,而男性的死亡率更高(提出了以下问题:关于如何解释剩余差异的课程);南亚人的数据相似(ONS,2020)。当时,ONS 无法将个人从事的工作类型包括在混杂因素中,他们认为这也可能影响他们的模型。

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图1
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结构性不平等与 COVID-19 易感性的关系

然而,最近,开始出现阴险和潜在的种族主义暗示,似乎将非裔美国人归咎于美国相对大量的 COVID-19 病例和死亡,引发了古老的比喻,并归因于发病率和死亡率BAME 群体的行为和倾向(Guardian,2020b;Strings,2020)。《卫报》(2020b)推测了这些归因背后的政治动机。

实际上,影响个人对 SARS-CoV-2 脆弱性的结构性或社会不平等包括通过就业类型暴露,无论人们是在承载大量人员的基本交通网络中工作,还是在使 BAME 社区面临更大风险的小型杂货店工作感染 COVID-19(图 1)。这些社区也经常面临更高的代谢紊乱风险,包括肥胖、心血管疾病、高血压和 2 型糖尿病,其中一些与感染 COVID-19 的风险较高以及一旦感染后的结果较差有关(Azkur 等人,2020)。鉴于死亡率似乎更多是由于暴露于 COVID-19 引起的炎症反应,以及它攻击身体许多器官的能力,代谢疾病使许多人一旦生病就面临不良后果的高风险(Matricardi,达尔·内格罗和尼西尼,2020 年)。一线卫生工作者感染 COVID-19 的风险也很高。在英格兰,国民健康服务体系 (NHS) 长期以来一直从国外引进合格的医生、护士和护理人员(现在占所有员工的 13%),在 NHS 工作的 BAME 个人比例是其他经济体的两倍(贝克,2019)。最近的一份报告还表明,与欧洲白人同行相比,BAME 卫生工作者获得个人防护设备的机会更少(皇家护理学院,2020 年)。在美国,少数群体面临着额外的社会问题,例如由于医疗保险费用而可能缺乏医疗保健。这是 BAME 团体在英国的国家卫生服务中没有遇到的问题。此外,BAME 社区通常居住在被归类为食物荒漠的社区,这会影响健康食品的获取,或者他们缺乏锻炼和新鲜空气的绿色空间。少数民族经常生活在比其他人污染更严重的地区或地区,这种情况可能因缺乏包括垃圾收集在内的服务提供而加剧。

这些类型的“结构性暴力”在许多北方国家的少数民族中很常见,并且主要可以解释群体间对 COVID-19 的易感性。然而,是否有任何潜在的生物学现实也可能使某些群体在感染该疾病后更容易受到较差结果的影响?目前,基于年龄和性别的易感性存在明显差异,这些差异目前仍知之甚少,并且不完全是由于社会或行为差异造成的。此外,某些个体对药物的反应方式可能存在差异——即所谓的药物遗传学差异——这可能解释恢复时间或对特定药物干预的反应(Shah,2005)。正如有些人似乎对 HIV-AIDS 免疫(Carrington 等人,1996 年),同样,有些人也可能由于未知原因对 SARS-CoV-2 免疫,或者是无症状携带者(Azkur 等人,2020 年) .

已经有一些尝试探索这些与 SARS 病毒有关的潜在生物学问题。一个例子是血管紧张素转换酶 2 (ACE2) 受体基因多态性的人群差异研究,该受体存在于肺、脑、肾、心脏和肠道等许多人体器官中,相关的冠状病毒 (SARS ‐CoV‐1 和最近的 SARS‐CoV‐2)主要通过肺部进入与新宿主结合。尽管与欧洲人后裔相比,东亚人的 ACE2 水平似乎更高,但基因变异与 COVID-19 结果之间似乎没有任何关联(Cao 等人,2020 年)。同样,Nguyen 等人。( 2020) 对不同类别的人类白细胞抗原 (HLA) 基因型对暴露于 SARS-CoV-2 的反应进行了计算机分析,并在全球范围内绘制了不同的 HLA 变体,以估计对人群水平的潜在流行病学影响。同样,虽然一种 HLA 变体似乎可以提供更大的保护,但另一种可能会使个体更容易感染 COVID-19,但都没有建议在全球范围内产生影响。

最近,Genomics England ( 2020 ) 宣布,他们将开始对 20,000 名经历过 COVID-19 最严重症状的住院患者进行研究,并将他们与仅出现轻微症状的 15,000 名患者进行比较,以努力探索对疾病易感性的潜在基因组差异。这项研究无疑需要一些时间才能完成,目前尚不清楚该研究将如何收集或解决其他风险因素以及遗传变异性。同样,英国的 Biobank 纵向研究已要求其当前参与者参加一项附属研究,以检查可能影响 COVID-19 易感性的那些因素(遗传或其他)(Biobank,2020),尽管参与 Biobank 的 BAME 个体的比例低于全国人口(Fry 等人,2017 年)。已经提出了导致不同种族对 COVID-19 易感性的其他生理原因,包括维生素 D 缺乏症的可能性增加易感性,这将对生活在高纬度国家的肤色较深的人产生不利影响;此后,这种联系被淡化了(Hamiel、Kozer 和 Youngster,2020 年)。

我们还应该记住,通过环境(社会经济和其他方式)介导的发育和表观遗传影响也会影响个人的晚年生活,并通过这条途径影响他们对病原体的易感性(Conching & Thayer, 2019 ; Nelson, 2009 ; Wells, 2016)。例如,南亚人被认为具有特殊的瘦脂肪表型,以应对胎儿长期营养不良的状况,这使得他们在晚年特别容易受到代谢紊乱的影响(Yajnik 等人,2003 年。这些表型特征似乎也被代际保存(van Steijn et al., 2009) 并且如上所述,目前与 COVID-19 发病率和死亡率的风险有关(Azkur 等人,2020 年)。

生命历程事件(例如自体静力负荷)似乎也影响个体生物学衰老的速度,使得他们的生物学年龄高于或低于他们的实际年龄。这些差异已使用多种技术进行测量,例如分析端粒长度或表观遗传年龄,并且许多少数民族似乎具有相对于他们的实际年龄更高的生物学年龄(例如,Levine & Crimmins,2014;Simons 等,2016)。鉴于 COVID-19 的易感性与年龄呈正相关,生物学年龄较高的个体也可能越来越容易受到 COVID-19 的影响。

更广泛地说,在更广泛的地理层面上,各国在国内生产总值、基础设施和殖民压迫历史方面的长期差异被认为使许多南半球、中低收入国家 (LMIC)易受新出现的日冕病毒传播及其健康后果的影响(Bhutta、Basnya、Saha 和 Laxminarayan,2020 年;Roberton 等人,2020 年)。在世界各地的大多数难民营中,也有人猜测健康状况不佳、拥挤的条件、缺乏足够的卫生人员以及无法与社会保持距离的潜在灾难性后果(Kassem,2020 年;Nott,2020 年) .

事实上,这些统计数据在早期看起来令人鼓舞,因为中低收入国家的病例和死亡人数似乎远低于欧洲,尽管非洲大陆在 SARS-CoV-2 的暴露方面暂时落后于欧洲(Hashim,2020 年) . 在南亚,较低的死亡率取决于人口的人口结构,大多数年轻人可能不太可能传播 SARS-CoV-2(Hashim,2020)。此外,据推测,在生命早期接触更多疾病,或更强烈的儿童免疫模式,可能会以某种方式促使个体对病毒具有更强的抵抗力。然而,早期报道称,卡介苗 (BCG) 疫苗接种可能会提供一些保护作用(直到 2005 年,英国大多数儿童也经常接种该疫苗),但此后受到质疑(Kumar 和 Meena,2020 年;Redelman ‐西迪,2020 年)。另一个可能使难民营免受大流行病影响的因素是,它们与游客和游客的踪迹相对隔离,而难民营外的囚犯旅行通常受到限制(Abdalfatah,2020)。然而,最近,这种流行病在南部国家加速发展,非洲大陆和南亚的发病率迅速上升,给许多国家的医疗保健系统带来了挑战(约翰霍普金斯大学,2020 年;Vaidyanathan,2020 年),以及中低收入国家最终发病率和死亡率的不祥预兆。

最后,在结构性不平等方面,当我们开发新的潜在治疗方法和疫苗来治疗 COVID-19 时,我们还必须意识到有必要测试和收集少数族裔的数据,他们在临床试验和纵向健康队列研究(Jackson & Kuhlman,2019)。

与结构性不平等、种族主义和所谓的“种族医学”相关的健康研究通常是人类学的重点(例如,Conching & Thayer,2019 年;Ifekwunigwe 等人,2017 年;Weigmann,2006 年)). 我们应该放心,除非有选择性的政治言论有可能造成极大的破坏,通过在新闻媒体、科普资源和其他地方的明显承认,健康方面的种族不平等并不反映潜在的人类生物学或基因,而是而是人类个体发现自己所处的社会环境。我们只能希望,在人类社会数十年来日益扩大的不平等差距之后,当前的大流行最终可能成为解决和补救这些不平等的催化剂(Dorling,2013 年;Marmot,2015 年)。

更新日期:2020-07-16
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