Ethnicity as an analytic variable

Ethnic variation is a starting point not an explanation

Some authors argue that ethnicity cannot meaningfully be treated as a cause because it is an attribute which does not allow for counterfactual states (e.g. a Black person not exposed to

‘Blackness’) [297-298]. I do not agree with this position, nor do I believe ethnicity is a single, non-modifiable attribute. For example, while a Black person may necessarily be exposed to ‘Blackness’, this Blackness need not include (for example) the experience of discrimination in the labour market.

Nevertheless, I certainly agree with Rutter [299] that multifaceted, non-homogenous concepts like ethnicity only become meaningful explanatory variables when broken down into their constituent parts [see also 202]. Moreover, different factors may be relevant for different ethnic groups or for different health outcomes. Researchers must therefore not confuse the description of ethnic variation in health with an explanation for that variation [287, 289, 292, 300-301]. Instead, the observation of any ethnic difference should be a starting point for further investigation into operative causal mechanisms. Identifying these mechanisms may then enable the imagining of counterfactual states, and so inform the design of public health interventions.

Of course, this situation is not unique to ethnicity but applies to all complex and multifaceted socio-cultural and economic factors. For example, variation between manual and non-manual occupational groups or between urban and rural residents is not informative in itself; there will rarely be anything intrinsically ‘manual’ or intrinsically

‘rural’ about health differences. Rather further research into causal mechanisms is necessary to understand why such differences exist.

Causes of ethnic variation should be directly measured not assumed

Causes of ethnic variation in health may include differences in allele frequency; lifestyle and cultural factors; socio-economic position (SEP); or how individuals and groups are treated by society. It is therefore crucial to investigate causal mechanisms directly, by testing key assumptions and by comparing and contrasting alternative explanation. Again,

73 this is not unique to ethnicity but applies to all multi-faceted phenomena such as manual occupation or rural residency.

Yet despite the multiple dimensions of ethnicity, several commentators have lamented a tendency to assume without evidence that ethnic differences have genetic or cultural causes [246-247, 302]. This risks pathologising minority ethnic groups and may ignore other structural sources of disadvantage such as racism or low SEP [290, 303]. The importance of considering multiple axes of disadvantage is illustrated by the 1999 Health Survey for England, which showed greater health disparities between different income tertiles in the same ethnic group than between different ethnic groups in the same tertile [304].

Section_3.1.3 therefore focuses on the necessity and the challenges of considering socio-economic inequalities when analysing ethnic differences.

Analysing socio-economic position and ethnicity

In Britain, SEP is strongly associated both health [305] and ethnicity (see Section 3.2). Yet while SEP is therefore an important potential confounder when comparing ethnic groups, controlling for SEP is far from straightforward. Of course, this is true to some extent across epidemiology. It is particularly acute here, however, because migration and membership of a minority ethnic group may result in different facets of SEP being ‘pulled apart’.

For example, downward social mobility upon migration may result in minority ethnic individuals having above-average educational qualifications at any given income level.

Given the protective effect of parental education against child mental health problems, adjustment for income alone might result in substantial residual confounding. In this case the nature of the residual confounding would be to create a misleadingly favourable impression of the mental health of minority ethnic children relative to Whites. Conversely, controlling only for parent education might under-adjust for material deprivation and create a misleadingly unfavourable impression of minority ethnic child mental health. Under-adjustment for SEP may also occur through ignoring the cumulative effects of multiple disadvantages, if these are disproportionately common among minority ethnicities. I present emprical evidence on these points in Section 3.2.2.

74 Using single, crude measures of SEP when comparing ethnic groups may therefore lead to substantial residual confounding, and this may either exaggerate or mask ethnic differences.

Multiple or composite indicators are one way to improve adjustment for SEP in any epidemiological study [306], and may be useful when studying minority ethnic groups [307]. Yet even with such indicators, there remain formidable challenges in measuring SEP accurately and dealing adequately with the complexity of the relationship between SEP and ethnicity. This warns against accepting too readily that one has ever fully adjusted for SEP when comparing ethnic groups.

Finally, even if SEP proves central to explaining ethnic differences in health, this does not mean that ethnicity is irrelevant or nothing remains to be ‘explained’. For one thing, the socio-economic disadvantage of many minority ethnic groups may partly reflect aspects of their minority ethnic status. These might include language barriers to employment, exclusionary racist practices, or a preference among minority ethnic individuals for investing in assets in their country of origin. Moreover, socio-economic inequalities are themselves like ethnic inequalities in being a starting point for further analysis rather than an explanation in their own right.

What is therefore needed is an approach which examines in detail the association between ethnicity and multiple indices of SEP, and which investigates the individual- and family-level mechanisms underlying any variations in health. One major aim of this thesis is to use B-CAMHS to develop precisely such an approach for child mental health in Britain.

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