Longitudinal data : an excellent tool for demographers

1. Longitudinal data : an excellent tool for demographers LessonsfromBelgium Michel POULAIN University of Louvain Belgium/ Tallinn UniversityEstonia

2. Building a longitudinal database in Belgium

3. Individual linkage methodology • From 1991 onwards, the PIN is used and its unicity ensures the completeness of the linkage and its reliability (censuses, population registration system, permanent longitudinal sample for health care, social security data, income tax, and various surveys). • Death records may be linked with other individual data by using sex, date of birth and date of death as linkage key. • In order to link data prior 1991, several variables are used:

4. Linkage between 1981 and 1991 censuses Data available for linkage in the data of census 1981 Sex Full date of birth Place of birth Month and year of marriage Municipality of residence on 1er March 1981 (census date) Data available for linkage in the data of census 1991 Sexe Full date of birth Place of birth / place of residence of the mother at the time of birth Municipality of residence on 1er March 1981 (previous census date) Date of marriage (could be found in the population register data) Municipality of residence on 1er March 1991 (census date)

5. Different steps of the linkage • 9 978 681 were enumerated in the 1991 census and, among these, 1 008 261 were younger than 10 years old while 531 998 immigrated between the two censuses . • Step 1 : Using a key including SEX + FULL DATE OF BIRTH + RESIDENCE IN 1981, 4.511.271 are found with a unique possibility of linkage (53 %). • Step 2 : For the remaining cases, we used a different key composed by SEX + FULL DATE OF BIRTH + PLACE OF BIRTH. An additional number of 1 083.946 persons are linked (66%). • Step 3. For the remaining cases, we used a slightly different key composed by SEX + FULL DATE OF BIRTH + PLACE OF RESIDENCE OF MOTHER AT BIRTH. An additional number of 128 872 persons are linked (68%). • Step 4. By recomposing married couples in 1981 and 1991 and linking these couples based on the date of birth of the spouses. This last step bring the linkage level to 79%.

6. Two types of data are available • Stock data : characteristics of persons enumerated in census but also on their living arrangement, housing as well as their physical and social environment. • Flow data or events occuring continuously and captured through population registration systems. It include the traditional demographic events that are births, marriage, divorce and deaths, but also all types of migrations and changes of living arrangements as widowhood, institutionnalisation, cohabitation, departure of the last child from the family nest…

7. Three main types of investigation 1. Analysis of survival starting at a given time (census date) according various characteristics observed at census time e.g. • Probability to die according various characteristics observed at census • Probability to enter in institution according these characteristics • Probability to leave a given dwelling according individual characteristics and the ones of the dwelling

8. Three main types of investigation 2. Analysis of duration between events and associated survival analysis e.g. • Duration between two successive migrations (changes of place of usual residence) that is the duration of presence in a given dwelling or in the country. • Duration between marriage and the first child or between two successive births that are the proto-genesic and inter-genesic intervals. • Duration between widowhood or divorce and remarriage. • Duration between widowhood and the possible entry in institution. • Duration between widowhood and death • Duration between entry in institution and death…

9. Three main types of investigation 3. Analysis of transition probability between the situation of individual observed at two fixed moments (census dates) according various characteristics observed at both censuses • Transition probability between places of usual residence at two successive censuses according individual characteristics. • Transition probability between marital status observed at two successive censuses according individual characteristics. • living arrangement observed at two successive censuses according individual characteristics.

10. Institutionnalisation and deathThe prevision of number of beds in nursing homesand the problem of higher mortality risk in institution • With census data only • With death record and census data (without linkage) • With data from two successive censuses linked • With death record and census data linked • With data on entry in institution and data on death (or exit) linked.

11. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters STOCK DATA at T+N : age, gender, marital status, living arrangement and some soc-ecocharacters Deaths by age, gender, marital status and somesocio-economiccharacteristics Entries in institution by age, gender, marital status and somesocio-economiccharacteristics

12. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters

13. Absolutenumbers of persons living in nursing homes in Belgium (2002)

14. Proportion living in nursing homes by gender and marital status in Belgium (2002)

15. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters Deaths by age, gender, marital status and somesocio-economiccharacteristics

16. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters Entries in institution by age, gender, marital status and somesocio-economiccharacteristics

17. Absolutenumbers of personsentering in institution by age and gender, Belgium

18. Probability to enter in institution by age and gender, Belgium

19. Probability to enter an institutionfor newlywidowedpersonsduring the first year of widowhood by tenth of year and group of agesatwidowhood

20. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters Deaths by age, gender, marital status and somesocio-economiccharacteristics

21. Odd ratios of mortality risk for persons living in collective household compared to those living with others

22. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters STOCK DATA at T+N : age, gender, marital status, living arrangement and some soc-ecocharacters

23. Probability to live in institution in T+5 according the living arrangement at T (Male and femaleBelgianaged 80-84 or 85+ in 2001)

24. Linkingindividual data fromdifferent data sources Deaths by age, gender, marital status and somesocio-economiccharacteristics Entries in institution by age, gender, marital status and somesocio-economiccharacteristics

25. Probability to die during the two first years after entering an institution by age group at entry and gender

26. Comparing the probability to die during the FIRST year after entering an institution by age at entry and gender

27. Relative over risk to die during the FIRST year in institution by sex and age at entry

28. Linkingindividual data fromdifferent data sources STOCK DATA at T : age, gender, marital status, living arrangement and some soc-ecocharacters Deaths by age, gender, marital status and somesocio-economiccharacteristics Entries in institution by age, gender, marital status and somesocio-economiccharacteristics