Data and sample

Due to the comparative nature of the research questions, this chapter uses the same information introduced in chapter 4. In more detail, it includes mortality data from the World Health Organization (WHO), whereas economic data is obtained from international databases such as the Organization of Economic Development and Cooperation (OECD), the Structural Analysis Database (STAN) and the United Na- tions National Accounts Main Aggregates Database.

Dependent variables-mortality

Since the interest lies in examining the contribution of deindustrialization and reces- sion on different causes of death, mortality data has been obtained from the World Health Organization and covers a forty year period (1971-2009). The WHO Mor- tality database (November 2011 update) contains deaths catalogued in registration systems of every country and coded in accordance with the International Classifi- cation of Diseases (ICD). The underlying cause of death is defined as“the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury”(WHO, 2013). The direct method of standardization has been implemented for the calcula- tion of the all-cause and suicide rates by using the European Standard Population. Age Standardized Mortality Rates (SMR) are calculated for the causes mentioned above covering the working age male and female population aged 20-59. The choice of this age range is based on the fact that the interest is concentrated on the trends

Chapter 5. The association - deindustrialization, recession and mortality 87 of unemployment and manufacturing employment, therefore the choice of mortality refers also to the working age population.

Suicide mortality-International classification of diseases (ICD 8th-9th-10th) For the needs of the current analysis mortality, due to suicides, covers not only the deaths defined as suicides but also mortality classified as undetermined events. In the special case of suicide, the coroner could conclude that the cause of death was stated as suicide/self-inflicted injury or, due to insufficient evidence, defined as injury undetermined whether accidentally or purposely inflicted (open-verdict) (Brock and Griffiths, 2003). However, because of the variations among and within countries, concerning the determination of suicide from the appropriate civil bodies (coroners), the inclusion of undetermined events could provide an additional and more consistent evaluation of deaths that are possibly suicides (Barr et al., 2012; Hawton et al., 2011).

Since the precision of detecting causes of mortality can differ across countries, the implementation of the International Statistical Classification of Diseases (ICD) pro- vides a consistent way to tackle any comparability issues. Although the ICD and its revisions provide a relatively uniform approach of recoding mortality, still caution is necessary when interpreting mortality data across countries and time. Most com- parability issues are concentrated on the heterogeneity of the various ICD revisions and the applicable civil authorities regarding the sufficiency of death information (Bhalla et al., 2011).

In more detail, the most recent ICD coding, ICD-10, provides more exhaustive knowledge based on a combined form of characters and numbers of causes of death compared to previous revisions (ICD-9 has 6,969 codes compared to ICD-10 which has 12,420 codes). The codes between the 9th and 10th revision of ICD vary mainly at the level of detail (third and fourth level). Various adaptations exist also between the 8th and 9th revisions of ICD. Changes in the 9th revision are mainly concen- trated on reallocations and rearrangements of diseases to different chapters or the inclusion of new sections. For instance, additional information is provided describ- ing not only the underlying cause of death but also the human organ affected through the inclusion of four and five digit subdivisions (WHO, 2010).

Chapter 5. The association - deindustrialization, recession and mortality 88 In addition, coding concerning late effects of these causes are merged in one code in the 10th revision (Y87) and not assigned in the related chapters of suicide and undetermined event as in the 9th revision (Griffiths and Rooney, 2003). However, due to small number of deaths concerning late effects, these are excluded from the analysis. Since the current chapter includes the time span from 1971 to 2009 mortality data is derived from the following ICD revisions.

Table 5.1Suicides and undetermined injuries - ICD revisions

Cause of death ICD 8 ICD 9 ICD 10

Suicides/Self-inflicted injury E950-E959 E950-E959 X60-X84 Undetermined Injury E980-E989 E980-E989 Y10-Y34

Independent variables - economic indicators

Economic data is originated by the United Nations National Accounts Main Ag- gregates Database which is a large international repository. Data is requested from national statistics offices and official publications together with the appropriate doc- umentation concerning the collection of the data. Once the appropriate inspection (i.e consistency, error checking) concerning the quality of the data occurs, then in- formation is incorporated into the database. After the data is obtained at national currency then the prices are converted to US dollars through the implementation of suitable exchange rates (UN, 2013).

The Gross Domestic Product (GDP) and in particular the GDP per capita in US dollars is a commonly used indicator describing the national economic performance (Stuckler et al., 2008; Chung and Muntaner, 2007; Granados, 2005). In more detail, GDP per capita is defined as the GDP per head and is calculated as the aggregate of production (GDP) divided by the population size (UN, 2013). It describes not only the national economic performance but also the average economic welfare of the population. The cyclical variations of GDP per capita are more representative of the changes in personal income compared to the GDP growth. Nevertheless, GDP per capita is limited to the average standard of living; therefore internal prosperity variations and inequalities are not taken into account (OECD, 2013).

Chapter 5. The association - deindustrialization, recession and mortality 89 Independent variables - manufacturing employment and unemployment The above economic measures express the overall economic performance. How- ever, when it comes to the relationship between economic fluctuations and mortality other measures could enhance the sufficiency of the analysis. Previous research, ex- amining this relationship, found that there is a closer association between variations in employment and temporary changes in health contrary to indicators measuring a country’s overall performance. Although short-term downturns in GDP are usually followed by rises in unemployment nevertheless the strength of this impact varies over time and across countries (Stuckler et al., 2009a).

Therefore the next set of indicators depicts the overall and sectoral labour market. Manufacturing employment data is obtained by the Structural Analysis Database (STAN). The STAN database is a wide-ranging tool for exploring various aspects of industrial performance (STAN, 2012). Unemployment data is derived from the Labour Force Database of the OECD for the years 1971 until 2009 (OECD, 2011b). For the analysis the civilian unemployment, excluding the armed forces, is in- cluded. Civilian unemployment includes those without work, seeking work, those currently available for work and those temporarily absent from their jobs with no formal job attachment. Furthermore, students, homemakers, those engaged in non- economic activities and those who satisfy the above criteria are also regarded as unemployed. The above criteria are defined in accordance with the ILO recom- mendations (OECD, 2011a). Overall civilian unemployment is divided by gender. Employment in manufacturing could not be separated in terms of gender due to lack of adequate data availability.