1. Spatial microsimulation
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Predicting the need for aged care services at the small area level: The CAREMOD spatial microsimulation model

  1. Sharyn Lymer  Is a corresponding author
  2. Laurie Brown
  3. Ann Harding
  4. Mandy Yap
  1. University of Canberra, Australia
Research article
Volume 2(2) Autumn 2009
Cite this article as: S. Lymer, L. Brown, A. Harding, M. Yap; 2009; Predicting the need for aged care services at the small area level: The CAREMOD spatial microsimulation model; International Journal of Microsimulation; 2(2); 27-42. doi: 10.34196/ijm.00015
8 figures and 8 tables

Figures

Figure 1
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Structure of CAREMOD database.
Figure 2
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Construction of the CAREMOD database.
Figure 3
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Reweighting process for the CAREMOD database.
Figure 4
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Modalities of care.
Figure 5
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Mapping of level of disability to health care modality.
Figure 6
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Mapping of per cent with a moderate restriction in at least one core area amongst those aged 55 years or over, by SLA.
Figure 7
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Mapping of per cent needing high level care amongst those aged 55 years or over, by SLA.
Figure 8
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Mapping of per cent needing high level care amongst those aged 85 years or over, by SLA.

Tables

Table 1
Variable concordance between SDAC98 and 2001 census.
Benchmark variable Classes of SDAC98 variables (bold nos. in brackets are the Census classes that SDAC classes map to) Classes of Census variables (classes in bold map onto SDAC classes)
Relationship in household 00 Not applicable (excluded)
01 Husband, wife or de facto (1)
02 Group household (5)
03 Lone parent (2)
04 Child under 15 (7)
05 Dependent student (7)
06 Non-dependent child (3)
07 Brother/sister (4)
08 Father/mother (4)
09 Other related individual (4)
10 Unrelated individual living in a family household (4)
11 One person (6)
99 non-residents visitor (excluded)		 1. Husband, wife, or partner in de facto marriage
2. Lone parent
3. Non-dependent child
4. Other related or unrelated individual
5. Group household member
6. Lone person
7. Children <15 and student
8. Not applicable (excluded)
Individual income 00 No income/no source of income (1)
01 Less than $80 (1)
02 $ 80–$119 (1)
03 $120–$159 (1)
04 $160–$199 (1)
05 $200–$239 (2)
06 $240–$279 (2)
07 $280–$319 (2/3)
08 $320–$359 (3)
09 $360–$399 (3)
10 $400–$439 (4)
11 $440–$479 (4)
12 $480–$519 (4)
13 $520–$559 (4)
14 $560–$599 (4)
15 $600–$639 (5)
16 $640–$679 (5)
17 $680–$719 (5)
18 $720–$759(5)
19 $760–$799 (5)
20 $800–$839 (5)
21 $840–$879 (5)
22 $880–$919 (5)
23 $920–$959 (5)
24 $960–$999 (5)
25 $1000–$1039 (6)
26 $1040–$1079 (6)
27 $1080–$1119 (6)
28 $1120–$1159 (6)
29 $1160 and over (6)
30 Refusal (distributed to 00–29)
31 Don’t know (distributed to 00–29)
32 Not applicable (excluded)
Individuals in classes 01–29 were randomly assigned an actual dollar income which was up-rated to 2001 dollar value and then coded to one of the 6 Census classes.		 1. $0–$199
2. $200–$299
3. $300–$399
4. $400–$599
5. $600–$999
6. $1,000 or more
7. Not applicable (excluded)
8. Negative income (distributed to 1)
9. Not stated (distributed to 1–6)
Housing tenure type 0 Not applicable (5)
1 Owner without a mortgage (1)
2 Owner with mortgage (2)
3 Rented – public (4)
4 Rented – private (3)
5 Rented – other (distributed to 3 and 4)
6 Boarder (excluded)
7 Living rent-free (excluded)
8 Other (excluded)		 1. Fully Owned
2. Being Purchased
3. Rented – private
4. Rented – public
5. Not applicable (excluded)
6. Rented – not stated (distributed to 3 and 4)
7. Being Occupied rent-free (excluded)
8. Other Tenure (excluded)
9. Not Stated (distributed to 1–5)
Level of education Level of post-school educational qualification
1. Higher degree (1)
2. Post-graduate diploma (1)
3. Bachelor degree (1)
4. Undergraduate diploma (1)
5. Associate diploma (1)
6. Skilled vocational qualification (1)
7. Basic vocational qualification (1)
8. Uncodable/inadequately described out of scope/not applicable (2) 		1. Has a non-school qualification
2. Does not have a non-school qualification
3. Level of education not stated (distributed to 1 and 2)
4. Level of education inadequately described (distributed to 1 and 2)
Table 2
Comparison of synthetic estimates and census counts of constrained variables.
  Average across SLAs Standard deviation across SLAs
Constrained variable Census CAREMOD Census CAREMOD
Has non-school qualification 9,942 9,941 13,983 13,983
Wife/Husband/ spouse/in de facto relationship 13,494 14,275 18,328 19,348
Aged 65 years and over 4,176 4,176 5,597 5,597
Male 15,741 15,741 21,074 21,074
Female 16,152 16,152 21,718 21,718
Male aged 65 years or over 1,825 1,825 2,419 2,422
Home fully owned 12,311 12,177 16,753 16,526
Mortgage on home 9,243 9,093 13,889 13,653
Rental – Private 7,026 6,936 9,450 9,344
Rental – Public 1,479 1,264 3,151 2,901

  1. Notes: CAREMOD estimates based on reweighted SDAC population, averaged across all SLA including those four SLAs for which GREGWT failed to provide a convergent set of weights; Census and CAREMOD SLA coverage excludes the “Offshore and Migratory” SLA.

  2. Source: ABS Census 2001, CAREMOD.

Table 3
Comparison of synthetic estimate and census counts of unconstrained variables.
  Average across SLAs Standard deviation across SLAs
Unconstrained variables Census CAREMOD Census CAREMOD
Living in non private dwelling 993 1,848 1,336 2,157
Not in labour force 9,066 7,734 12,379 10,521
Employed 13,819 14,543 18,959 20,182
Australian Born 24,327 25,334 31,108 34,205
Unemployed 1,065 1,102 1,542 1,566
Married or de facto marital status 13,494 13,799 18,328 18,664
Males aged 65 years and over who were employed 197 239 228 317

  1. Notes: Based on all SDAC population excluding the Offshore and migratory SLA but including all other SLAs, even those that have been deemed not to converge.

  2. Source: ABS Census 2001, CAREMOD.

Table 4
Imputation models for survey variables.
Variable Type of Model Predictors
Presence of disability (disability defined as having at least a moderate restriction in 1 core area) Logistic regression sex, age group, relationship in household, tenure type, income group
Number of core areas has disability (0, 1, 2 or 3) Ordinal logit age group, sex, relationship in household, tenure type, and income group
Which areas out of mobility, self care or communication were restricted Multinomial logit Sex, education level age group relationship in household tenure type and income group
Disability Status (8 levels) Ordinal logit age group, income group, tenure type and relationship in the household

  1. Note: Models were built on main effects only i.e. no interaction terms were modelled.

Table 5
Disability status model development.
Model Variables Wald x2 P-value
Age 8,676.0 < 0.001
Age + relationship in household 9,537.6 < 0.001
Age + relationship in household + tenure type 9,771.8 <0.001
Age + relationship in household + tenure type + income 100,073.0 < 0.001
Age + relationship in household + tenure type + income + sex 10,131.1 <0.001
Age + relationship in household + tenure type + income + sex +education 10,133.9 0.07
Table 6
Comparison of CAREMOD to SDAC estimates (%).
Variable CAREMOD 2001 SDAC 1998
Profound Disability 3.3 2.9
Severe Disability 4.0 3.5
Moderate Disability 2.9 3.5
At least Moderate disability 10.2 9.6a
  1. a

    95% Confidence interval for this estimate = 5.4–13.8%.

Table 7
Comparison of methods in the development of CAREMOD.
Method Estimate of at least moderate disability (%)
Reweighting 13.4
Reweighting + cloning 15.0
Reweighting + cloning + regression modelling 13.8
Reweighting + cloning + regression modelling + scaling 10.2
Table 8
Correlation between disability and constrained variables.
Variables Pearson’s R
Education −0.01
Tenure Type 0.00
Income 0.11
Relationship in Household −0.13
Age −0.45
Sex −0.01

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