Disaggregation of data by background variables – age, households, socio-economic categories Bratislava, 5-7 May 2003 Stein Terje Vikan Statistical Division.

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Disaggregation of data by background variables – age, households, socio-economic categories Bratislava, 5-7 May 2003 Stein Terje Vikan Statistical Division UNECE

NHDR Training Bratislava, May 2003 Disaggregation: Summary 1. Why breakdown 2. Possibilities to obtain breakdowns 3. Categories 4. Relevance: Examples

Statistical Division UNECE NHDR Training Bratislava, May 2003 Why breakdown? To identify special groups in society that: Stand out in specific indicators Are disadvantaged in specific areas Need special attention in policy formulation in the relevant area

Statistical Division UNECE NHDR Training Bratislava, May 2003 Sources and breakdown Censuses Easy Especially suited to identify small groups Surveys Easy, but quality decreases Not suited to identify small groups Administrative records/registers Difficult

Statistical Division UNECE NHDR Training Bratislava, May 2003 Age There exists an International Standard on Age Classifications from 1982 Gives suggested age classifications for different statistical areas Different classifications for different purposes

Statistical Division UNECE NHDR Training Bratislava, May 2003 Age Potential groups Children Adolescents Youth Adults Elderly

Statistical Division UNECE NHDR Training Bratislava, May 2003 Age - Elderly Before, all elderly were grouped together in one group (e.g. 65+) With the ageing of population, important to distinguish between different phases More elderly, so they make up a substantial group Differences between 70-year olds and 90-year olds

Statistical Division UNECE NHDR Training Bratislava, May 2003 Households Household: A socio-economic unit consisting of individuals who live together Usually defined as: one or more persons who make common provision for food or other essentials for living

Statistical Division UNECE NHDR Training Bratislava, May 2003 Household size Differences in living conditions often connected to household size But often better to look at household types

Statistical Division UNECE NHDR Training Bratislava, May 2003 Household types Illustration Lone Women Lone Man Married/cohabiting couple with children Married/cohabiting couple without children Lone mother with children Lone father with children Household of siblings Two-generation household without children Three-generation household All other households with more than one married couple Household of unrelated persons

Statistical Division UNECE NHDR Training Bratislava, May 2003 Household types Level of detail may vary Different household types face different problems Single person households often need special attention Especially women, in particular lone mothers

Statistical Division UNECE NHDR Training Bratislava, May 2003 Examples of other socio- economic categories Marital status Labour force status Education Income

Statistical Division UNECE NHDR Training Bratislava, May 2003 Marital status Illustrative classification: Never married Married Cohabitating Separated Divorced Widowed

Statistical Division UNECE NHDR Training Bratislava, May 2003 Labour force status In employment Employees Employers Own-account workers Members of producers’ cooperatives Contributing family workers Workers not classified by status Unemployed Students Homemakers Income recipients (pensioners, renters, etc.) Others (Children not at school, persons receiving public aid, etc.)

Statistical Division UNECE NHDR Training Bratislava, May 2003 Education Educational attainment Primary or lower Lower secondary Upper secondary Post-secondary non-tertiary (vocational) Tertiary (ISCED 1997)

Statistical Division UNECE NHDR Training Bratislava, May 2003 Income Need to define classifications based on national income levels

Statistical Division UNECE NHDR Training Bratislava, May 2003 Relevance Identifying groups based on these classifications may be relevant for: Poverty Proportion of people below the poverty line according to: Education Labour force status Household type Health status For instance HIV prevalence Access to health facilities Literacy Youth literacy rates Employment Youth unemployment rates (MDG indicator 45)