Choosing Core NILS data and its impact on Research Rónán Adams Máire Brolly NILS User Forum 11 th December 2009

Aims: Understand the structure of the NILS Understand the level/impact of Census Imputation and List Inflation Understand the research implications

Identifying the Core NILS data requirement to have a core data source coverage of the data source complete information on dates of birth existing linkages between the data sources

Core Data Set Options: Data sets in Research Proposal – Agreement Census Health Card Registrations (CHI) Issues: Census –Census Office only require Age –Any missing day/month Imputed to 1 st – 1st too high, all other dates too low –Person imputation (95%) Health Card registrations –List Inflation (105%)

Existing Links between Data Sources NICR Data Central Health Index GRO Births GRO Deaths 2001 Census Records

Proposed Links between Data Sources NICR Data Central Health Index GRO Births GRO Deaths 2001 Census Records

NILS/NIMS NILS c28% of population Sample members from Health Card Registrations List Inflation an issue Census Imputation NIMS 100% of deaths Census members linked to deaths Only enumerated people can be linked

Sample Selection in NI 104 dates – 100 NI, 4 E&W For each download (6 monthly) –Is the DDMM of the DOB a NILS date? If so then they are in the sample NILS sample – a person who has ever been in one of the 6-monthly downloads

Contextual DataNILS Core DataEvents Health Card Registrations Key demographic information on NILS members (514,000 Census Date New members (c40,000) 2001 Census Database 1991 Census Births Data (baby linked to Birth Registration) 1997 births onwards Deaths Births to MothersBirths to Fathers Stillbirths & Infant Deaths Migration (Immigrants, Emigrants, Re-Entrants & Within NI Movers) VLA/Rating Data POINTER Address Database

NILSE&W LSSLS Number Dates Size500,000 (28%)500,000 (1%)300,000 (5%) Start Date Number of Censuses 142 SourceHealth Card Registration Census + GRO Births + NHSCR Immigrants Includes Enumerated, Imputed and List Inflation – can look at enumerated only Enumerated only The 3 LSs

SG Discussion LS and SLS reps included on NILS SG Recognition and Agreement between 3 LSs NILS methodology would allow future ‘UK’ analyses

Health Card Registrations Central Health Index All Live Patients (4 th May 2001) 1,768,473 Published 2001 census population One Number (29 th April 2001) 1,685,267 Enumerated 2001 census population (29 th April 2001) 1,603,641 Imputed Records 81,626 Imputed Records 81,626 Enumerated 2001 census population (29 th April 2001) 1,603,641 List Inflation 83, % 90.7% 4.7%

Imputation and List Inflation: different profiles by age, gender, geography and other characteristics NOT 4.6% & 4.7% across all groupings

AgeAll Patients Published CensusEnumerationImputationInflation The very young

Female vs Male

All People

Imputation

List Inflation

Geographical Area Small geographies Urban – Rural Administrative Areas Settlements Deprivation

Urban/Rural

Assembly Areas / Parliamentary Constituencies

DECILEEnumeratedImputed List Inflation% LI, Imp Least Deprived 157,974 5,710 2,5255% 156,166 5,375-4,6520% 158,522 6, % 162,774 6,546 1,1505% 162,128 8,177 2,1336% 166,973 8,897 3,6447% 162,667 7,946 10,10910% 162,913 9,324 11,42211% 159,247 10,095 23,68818% most Deprived 154,277 13,434 33,45823% MDM - Deciles

List Inflation –Age, gender, geographical area Census Imputation –All Census characteristics

Imputation level – Marital Status

Imputation level – Economic Activity

Imputation level – Community Background

Summary Characteristics of List Inflation & Imputation are different from Enumerated –Highest in deprived, urban areas –Affects males more than females –Affects year olds most –Unemployed, students, living alone

Impact on NILS Imputed people can’t be linked – no names, DOBs etc. List inflation people unlikely to be on other administrative data (births, deaths, …) Can only expect to link a proportion of population

‘real’ people on census 9.3% of health card registrations with no census return Don’t know who exactly they are Some will be people who didn’t fill out form Some will be people who shouldn’t be on list

Estimate for NILS 28% sample Don’t know who is ‘list inflation’ Don’t know who is ‘imputed’ Assume 28% is representative 4.6% 90.7% 4.7% Health Card Registrations with NILS Date Central Health Index All Live Patients (4 th May 2001) 508,279 Imputation 23,460 Enumerated 460,904 List Inflation 23,914

4.6% 90.7% 4.7% Health Card Registrations with NILS Date Central Health Index All Live Patients (4 th May 2001) 508,279 Imputation 23,460 Enumerated 460,904 List Inflation 23,914 Imputation 23,460 Matched 447,457 List Inflation 23,914 Unmatched 13,447 88% Match Rate 97% Match Rate Adjusted NILS Match Rate (MCR-Census)

Core NILS – CensusLI, Imp91% Core NILS – BirthsLI95% Core NILS – Births – CensusLI, Imp91% Core NILS – DeathsLI95% Core NILS – Deaths – CensusLI, Imp91% NIMS – Deaths – CensusImp95% What % can we expect to match?

Impacts Simple RatesTOO LOW –% people who move –Crude death rate –Birth Rate, TPFR Rates (census)TOO HIGH –Standardised rates –Models Relative differences?

Hypothetical Example General Fertility Rate – –number of births per 1,000 women aged ,000 births NILS members (16-44) –130,000 –GFR = 62.1 per 1,000 NILS members with Census link (16-44) –110,000 –GFR = 72.7 per 1,000 ‘true’ estimate –120,000 –GFR = 67.2 per 1,000

Dental Registrations Registration Rate for NILS members (all) Registration Rate for NILS with Census link Registration Rate for NILS with no Census link

Dental Registrations - Males

Dental Registrations - Females

Dental Registrations – Relative differences

Summary List inflation & imputation are issues Imputation can be measured – lots of information LI cannot be easily measured – limited information Match rates cannot be easily determined Characteristics of imputed and list inflation different from ‘normal’ population Need to consider impact on your research

Aim: Understand the structure of the NILS Understand the level/impact of Census Imputation and List Inflation Understand the research implications

Choosing Core NILS data and its impact on Research Rónán Adams Máire Brolly

All People

Males

Females

Assembly Areas

CSA FPS CHI NHAIS BSO H&C, CHIN HEALTH CARD REGISTRATIONS