This chapter presents ten subject-matter topics: education; work; poverty; power and decision-making; environment; food security; population, households and families; health; migration, displaced persons and refugees; violence against women. Each topic is split in a number of sub-topics and for each sub-topic, four inter-related aspects are shown: gender issues, data needed to address those gender issues, sources of data, and gender-specific conceptual and measurement issues related to the data needed.
The section on gender issues presents short examples of relevant gender issues and aims to help statisticians recognize the types of policy-relevant questions or concerns related to gender that can be raised within a particular topic of interest or field of statistics. This is important because, as explained, gender statistics have to reflect problems, issues and questions related to women and men in society. The examples given do not necessarily reflect the situation in all countries and they are not limited to those for which statistics are widely available.
The section on data needed shows what data are required to address the gender issues highlighted for each sub-topic and at what level of disaggregation. The disaggregation needed usually include, besides sex and age, other variables identifying (i) population subgroups where gender inequality is likely to be more pronounced, or (ii) some of the explanatory factors of gender inequality. Examples of indicators derived from the gender statistics presented are shown for each sub-topic.
The section on sources of data presents sources that can provide the data needed. In many cases, data can be derived from more than one source of data, and all those sources are listed. The section specifies when the data collection vehicle has to be focused on the particular topic or sub-topic discussed and when a module or just a few questions added to another data collection vehicle is sufficient to obtain the data. Advantages and disadvantages of various sources of data are presented only to the extent that they relate to gender issues or gender specific measurement issues.
The last section, on gender-specific conceptual and measurement issues, refers to aspects that may induce sex-biased misreporting or underreporting in data collection and may affect the adequacy of gender statistics. More information on how to avoid gender bias in data collection is presented in Chapter 3 on integrating a gender perspective in data collection.