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2.3.7.1 Study-level variables

Type of incidence study

I recorded five types of incidence study: first contact, first admission, first diagnosis, first GP record and a case register. A priori, I expected that type of incidence study would influence reported incidence rates. First admission studies were anticipated to record a lower incidence as they would only capture in-patient cases and exclude those who remained in the community unless, of course, such services were the only available treatment option. Based on a study showing a threefold increase in incidence rates in a case register compared with a first contact study (Hogerzeil et al., 2014), I also expected that case registers reported higher rates of disorder. I therefore systematically assessed the impact of study type on incidence rates.

Mid-year point of case ascertainment

This variable refers to the mid-year point of case ascertainment of each study. So, if a study recruited participants from 2004-2006, the mid-year point would be 2005. I included this to assess whether incidence of psychotic disorders varied over time. If a study reported data from more than one distinct time period, I used the mid-point for each time period and derived the arithmetic mean for regression purposes.

2.3.7.2 Meta-level variables

Study quality

I systematically assessed study quality and risk of bias, using seven criteria (Table 2.3), and include this in meta-regression. These quality criteria were originally developed for the English meta-analysis (Kirkbride et al., 2012), and were based on epidemiological theory of best practice.

Table 2.3: Quality criteria

Criterion Reason for inclusion

Clearly defined catchment area Assessing accuracy of incidence rates (numerator)

Accurate denominator data Assessing accuracy of incidence rates (denominator)

Population-based case-finding Minimising selection bias

Usage of standardised research diagnosis Minimising diagnostic bias / assessing diagnostic reliability Blinding of clinician to demographic variables Minimising diagnostic bias / assessing diagnostic reliability Inclusion criteria clearly listed Measure of reporting quality

Leakage study conducted Minimising ascertainment bias

Gini Index of economic inequality

The Gini Index is a measure of the income distribution of a country’s residents. It is frequently used as a measure of inequality, and official data is kept by the World Bank (The World Bank, 2017). The index ranges from 0 (perfect equality) to 100 (perfect inequality). Looking at data collected since 2001, the

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highest recorded score was 69.2 (Jamaica, 2001, and the lowest recorded score was 23.7 (Slovenia, 2008). I obtained data for countries in the meta-analysis for the most recent year available (2005 for France, 2010 for Italy, the Netherlands, Spain, and England, and 2012 for Brazil, see Section 2.4.2).

Self-reported levels of trust

The World Values Survey was started in 1981 and aims to investigate changing human values and their impact on social and political life. Surveys are carried out in four-year waves, the most recent completed wave lasted from 2010 – 2014 (World Values Survey Association, 2015). For each country, I used the most up-to-date data (2005-2007 for England, France and Italy, and 2010-2012 for Brazil, the Netherlands and Spain). The minimum sampling size per country was 1,200 participants, who must be representative of the general adult population. Exact sampling strategies varied per country, but were quality-checked centrally (World Values Survey Association, 2017). I could only obtain results for the UK as a whole, not for England specifically.

For the meta-regression I was interested in both self-reported levels of freedom and trust. Levels of trust were ascertained using the following question:

Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?

With the following answering options: 1. Most people can be trusted 2. Need to be very careful

I downloaded raw data for each country from the World Values Survey website, and derived the percentage in each country answering that most people can be trusted (option 1. above). Self-reported levels of freedom

I derived self-reported levels of freedom from the same World Values Survey questionnaires using the following question:

Some people feel they have completely free choice and control over their lives, while other people feel what they do has no real effect on what happens to them. Please use this scale where 1 means ‘no choice at all’ and 10 means ‘a great deal of choice’ to indicate how much freedom of choice and control you feel you have over the way your life turns out.

45 Urbanicity

I ranked settings from 1 to 21, with 1 being the most urban setting and 21 being the most rural setting. Cities were accounted for in terms of number of inhabitants, and the urbanicity of rural areas was approximated by looking at population density (number of inhabitants per square kilometre). Because exact details of catchment areas were often not available, I could not rely on official governmental statistics and had to rely on data available in the public domain (eg. Google). The index was created jointly by HEJ and JBK.

Latitude

The latitude of each setting was recorded as degrees away from the equator. When studies took part across different geographical settings, and incidence data was unavailable per setting, I averaged latitude for regression purposes. I used data available from the public domain (as above).