Data collection for demographic & vital statistics

Data collection for demographic & vital statistics (Session 01)

Module Objectives At the end of this module, you will be able to • Explain basic concepts of routine demographic and epidemiological data collection procedures • Describe and correctly use several commonly occurring data summary measures • Discuss the value of various techniques for organising specialised studies in demography & epidemiology • Undertake some data summarisation and description tasks, and • Understand, and look critically at, reports of demographic and epidemiological studies

Learning Objectives At the end of this session, you will be able to • Recognise the broad scope of demography, and its dependence on basic measures • Explain stock and flow measurement • Critically discuss some data collection quality issues, and • List some of the definitional difficulties faced in demographic studies

What is demography? Demography is the scientific study of human populations, primarily with respect to their size, their structure and their development (UN Multinational Demographic Dictionary 1958). Major themes birth/fertility, death/mortality, as well as marriage, social mobility, geographic distribution & migration. Numerical summaries, but also social scientific theories to answer questions like, “When and why do birth rates fall?”

Demographic data sources • Population census Measures population STOCK. Often decennial; aims to count entire popul.n plus some inform.n about each member. Large size means study must be kept very simple*; many temporary enumerators, & everyone able to answer the questions. *e.g. often replaces “household” by “people who slept here on 30th June” Find and look at form for your last Census.

Demographic data sources 2. Vital registration Measures population FLOW/CHANGE. Usually continuous; “vital” registration covers births, marriages and deaths. Often problems as to completeness. International migration data often collected by different bodies; few countries can routinely keep track of internal population movements. How good is vital registration where you live? What encourages/discourages compliance?

Demographic data sources 3. Special studies – usually surveys. Measure stocks or flows in more specialised circumstances that are inadequately covered in routine data collection systems Usually more complex questions, so need very well trained interviewers. Thus usually relatively small sample sizes. Sometimes hard to ascertain if individuals “qualify” as part of special population being sampled – suggest some examples.

Nature of demographic data Age & some count variables used e.g. no of live births a woman aged x has had. Very many demographic statistics use binary data e.g. individual died while aged x [i.e. 0] or lived from exact age x to exact age (x+ 1) [i.e. 1]. A binary datum contains the least amount of information that we can “measure”; it is “hydrogen atom” of data collection ~ needs a big sample size to provide “weight” of evidence. Suggest demographic examples of variables of each type.

Large samples Nationally, a census or even a demographic survey usually has very big sample size, so sampling error/standard deviation of national estimate is often so small it can be ignored. National estimates often published with no measure of accuracy for this reason. However non-sampling errors may be substantial and serious. Three main categories are frame errors, non-response errors, and measurement errors.

Frame Errors Example ~ an out-of-date urban-biased sampling frame • Omits a disproportionate number of relatively new households; undocumented in-migrants; homeless, nomadic and peripheral (e.g. forest dependent) people • What might this do to estimates of (i) population age distribution? (ii) access to health services data? (iii) length-of-stay data?

Non-response Errors Example ~ when interviewer leaves an item blank it could mean • he forgot to ask this question; • the response was “zero”; • the respondent refused to answer; • the respondent could not understand … or could not convey an answer that the interviewer understood. How should this be avoided?

Measurement Error Example ~ Q. “How many family members are disabled?” This is weakly conceptualised: who counts as a family member e.g. orphans taken in? What constitutes “disabled” e.g. temporary incapacity? Bad questions usually occur along with poor training of enumerators, and careless completion. All leads to useless data! Discuss how you would improve on above Q.

The term “demographics” Many surveys collect data such as individuals’ age and sex. Set of data classifying a sample unit referred to as “the demographics”. The term is used more widely e.g. in business survey basic characteristics such as turnover, number of employees, number of sales outlets may be referred to in this way. Often these define rows and columns in tables e.g. tables “by age and sex”. Suggest other variables, not very interesting in themselves, but needed to subdivide results.

Primary importance of demographics The demographic variables that are in use constantly - to define almost every output table - are very important. They must not be missing, and must be accurate. Example ~ in a business survey, respondents may not know, or willingly tell, some “size” measure. If that is used in all tables, the rest of the responses will never be used in a case where the size is missing! Discuss problems with “marital status” Qs.

Difficult concepts Much of demography (and related social science) centres on the household or the family. Either must be very carefully defined having regard to local social patterns and study needs e.g. someone employed as daytime primary carer of household children may be close or distant relative – how to count? Some temporary migrants would be household and family members, but are away – include or not? Find out about/discuss variants used in NSS.

Difficult information to elicit Example ~ asking 45-year-old woman her complete fertility history including all pregnancies, spontaneous and induced abortions, still- and live-births, multiple births e.g. twins, one stillborn, and survival of live-born children. She may need event calendar prompts to remember all events and dates; may be emotionally difficult; complex to record accurately. Think of/discuss other difficulties like this.

Practical work follows to ensure learning objectives are achieved…

Data collection for demographic & vital statistics