Sustancias!bioactivas!con!actividad!biológica!

The methodological rigour of this systematic review and meta-analysis has been assessed on the basis of the AMSTAR criteria (see Section 2.3.12) (Table 2.18).

Table 2.18: AMSTAR Checklist

AMSTAR Item Done? Section

A priori design Yes 2.3

Duplicate study selection and data extraction No 2.3.4 / 2.3.5

Comprehensive literature search Yes 2.3.3

Status of publication as inclusion criterion Yes 2.3.3

List of studies included and excluded Yes 2.4.1 / Appendix 2B

Characteristics included Yes 2.4.1

Scientific quality assessment Yes 2.3.8 / 2.4.1

Method of combining data items appropriate Yes 2.3.9 / 2.4.6

Publication bias assessed Yes 2.3.8

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The only item on the AMSTAR checklist that this review does not meet is the duplicate data extraction. The majority of English citations (all those published until 31/12/2009) were included in Kirkbride et al’s meta- analysis and as such data was extracted by this study team. HEJ independently extracted the data for the remaining English citations and for all citations from other settings. This was closely supervised by JBK and overseen by PBJ. HEJ and JBK had regular meetings to assess progress and this included cross-checks of the spreadsheet used for data-extraction.

There are however some further limitations arising from this work. The first is that the present review only covered six countries, whereas McGrath et al’s global systematic review included citations from 31 countries (McGrath et al., 2004). As the countries covered in the present review accounted for almost half (42.3%) of citations included in McGrath’s review, this is predominantly a limitation in terms of

generalisability: the countries covered in this review are predominantly European and it is therefore difficult to extrapolate beyond this context. The countries covered in this review are also very similar in terms of latitude (with the exception of Brazil), and are on a relatively narrow range of income equality and self-reported freedom.

Some citations provided data from more than one catchment area or diagnostic outcome, and these centres were included in any meta-analyses as separate estimates of incidence (Cocchi et al., 2015; Kirkbride et al., 2006; Kroon et al., 2013). If either of these studies is biased, it might have skewed the pooled incidence rates in the respective analyses. As the emphasis of interpretation is on assessment of variance rather than pooled incidence, this isn’t a major limitation. Heterogeneity can also be artificially lowered by treating these centres as different studies when they in fact used the exact same methodology, but this appears not to have played a major role (heterogeneity remained high).

Imperfect measurement threatens the validity of meta-regression, and may have contributed to the null- findings. Study quality, type of study, the median year of recruitment and latitude could be obtained accurately, but the measurement of urbanicity is less reliable. The number of inhabitants of a city or population density of an area is subject to change over time. This was researched in 2015, and changes in urbanicity between recruitment into the included studies and this systematic review are possible (although there is no direct evidence for this). Furthermore, data was obtained from the public domain, and not from official governmental sources (as the exact catchment areas were unknown), and the reliability of this data is unknown. Similarly, not all national-level variables (Gini index, self-reported levels of trust, self-reported levels of freedom) have been collected at the same time (see Section 2.4.2). All data on inequality was retrieved from the World Bank for all years since 2002. For the meta-regression the most recent year was used, but for Brazil an increase in inequality of more than ten percent was observed in this time period, and for all other countries in the analysis inequality had increased too. It is therefore possible that these indicators do not accurately reflect the reality at the time when the incidence data was collected.

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In interpreting the results from the meta-regression, attention should also be paid to the ecological fallacy as data from a larger geographical area is applied to a smaller catchment area and it is not possible to say how typical these catchment areas are of the wider geographical area. This is most obvious with the data collected at the national level, but it also pertains to the urbanicity measure: this is a relatively crude indicator obtained for an entire city or area, and the catchment area might not be representative of this. This review also benefits from a number of methodological strengths. The research question, search strategy, data extraction procedure, inclusion criteria and statistical methodology had all been specified and published before the systematic review was started. The search strategy was inclusive and based on a previously used strategy (Kirkbride et al., 2012). The literature search was carried out after consultation with a librarian, and was comprehensive. It incorporated four electronic databases (Embase, PsycINFO, PubMed and Web of Science), and two supplementary strategies: references of all included studies were checked manually, and all lead authors were approached to identify missing studies. Studies that met the inclusion criteria were included regardless of their publication status. Some unpublished and preliminary data were found from conference proceedings (Appendix 2B) but this could not be included in this Chapter as these citations covered the EU-GEI study, and one of the aims of this Chapter was to aid in the

contextualisation of findings from this study (as presented in Chapter 4).

I presented details on included and excluded studies to aid transparency, and reporting in this review was transparent in general, in line with the AMSTAR criteria (Table 2.19). The method of combining data items was also appropriate, I assessed small study effects and included information on conflicts of interest.