Abstract
In this chapter, we projected numbers of activities-of-daily-living disabled elderly and yearly payments and workdays of home-based care for them by age, gender, race, and living arrangements from 2010 to 2050 for the United States (with low, medium, and high scenarios). The chapter focused on how changes in household structure and living arrangements may affect future home-based care costs for disabled elders based on census micro datasets, the National Long Term Care Survey data and the ProFamy extended cohort-component method. The results showed a remarkable acceleration in numbers of disabled elderly aged 65+ after 2020 with a much faster increase in disabled oldest-old aged 80+, such that after 2030 they outnumber the disabled young-old aged 65–79. Increases in yearly workdays and payments of home-based care for disabled elders will dramatically accelerate after 2020, especially for the disabled oldest-old. We also discussed similarities and differentials across racial groups and genders and the policy implications of future trends in home-based care needs and costs for disabled elderly.
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Notes
- 1.
Older adults with disabilities are more likely than those without any long-term care needs to live with their children if possible. The choice of living arrangements of elderly people also largely depends on demographic factors such as age, gender, race, marriage, divorce, cohabitation, and availability of children. Therefore, it is meaningful and practical to project elderly living arrangements first based on available demographic data and then project elderly disability status.
- 2.
The 1999 wave of NLTCS had a response rate of 88.6 % in the screening stage. The response rate for detailed interview was 93.2 % (http://www.nltcs.aas.duke.edu/pdf/99_SourceAndAccuracy.pdf, accessed on August 21, 2012).
- 3.
There are two primary reasons why we did not separate paid and unpaid care hours. First, a single question for overall care hours (without distinguishing paid and unpaid) in the 1999 NLTCS questionnaire was asked first in addition to two separate questions about paid or unpaid care hours. We believe that data from the total care hours are more reliable, because the latter two paid and unpaid questions had much higher percentage of refusal or “do not know” answers. Second, the estimates would be unstable if we further divided the age-sex-race-disability status-living arrangement-specific hours of care received per disabled elder by paid and unpaid categories, due to small sample size for subpopulations of minority groups.
- 4.
Although Zeng et al. (2013a) conducted projection scenarios of small, medium, and large family households, we do not include similar scenarios here, because the combinations of the low, medium, and high disability scenarios with small, medium and large family scenarios would result in nine (=3 × 3) composite scenarios, which would not permit a clear and meaningful presentation in one chapter.
- 5.
While we present in this chapter relatively detailed tables and graphics for projection results of numbers of disabled elders and their home-based care costs classified by age, race, and living arrangement, we only present and discuss a few summary indices of aging of households/living arrangements here due to space limitations; detailed tables are presented in Appendix 2 in Chap. 9.
- 6.
The ProFamy extended cohort-component model and its associated software produces a large amount of output for household status and living arrangement projections cross-classified by race, sex, age, marital/union status, number of co-residing children, and living with no, one, or two parents, for each of the projection years (see Table 2 in Zeng et al. 2006).
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Appendices
Appendix 1: The Estimated and Assumed Demographic Summary Measures in the Baseline and Future Years for the United States
White non-Hispanic | Black non-Hispanic | Hispanic | Asian and other non-Hispanic | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
2010 | 2025 | 2050 | 2010 | 2025 | 2050 | 2010 | 2025 | 2050 | 2010 | 2025 | 2050 | |
Male life exp. e0 | 75.3 | 76.3 | 77.5 | 68.8 | 70.1 | 73.6 | 77.4 | 78.4 | 79.3 | 77.2 | 77.4 | 78.3 |
Female life exp. e0 | 80.4 | 81.1 | 82.1 | 75.8 | 77.1 | 80.0 | 82.9 | 83.7 | 84.4 | 80.5 | 81.4 | 83.3 |
TFR-all births | 1.86 | 1.90 | 1.89 | 2.02 | 1.91 | 1.88 | 2.65 | 2.53 | 2.29 | 1.86 | 1.90 | 1.89 |
TFR(1)-1st birth | 0.82 | 0.86 | 0.86 | 0.84 | 0.82 | 0.84 | 0.95 | 0.95 | 0.95 | 0.88 | 0.95 | 0.95 |
TFR(2)-2nd birth | 0.61 | 0.61 | 0.60 | 0.68 | 0.63 | 0.60 | 0.88 | 0.81 | 0.69 | 0.57 | 0.55 | 0.55 |
TFR(3)-3rd birth | 0.29 | 0.29 | 0.28 | 0.28 | 0.26 | 0.25 | 0.47 | 0.43 | 0.37 | 0.27 | 0.26 | 0.26 |
TFR(4)-4th birth | 0.10 | 0.10 | 0.10 | 0.13 | 0.12 | 0.11 | 0.21 | 0.20 | 0.17 | 0.10 | 0.09 | 0.09 |
TFR(5)-5+ birth | 0.05 | 0.05 | 0.05 | 0.09 | 0.08 | 0.08 | 0.14 | 0.13 | 0.11 | 0.05 | 0.04 | 0.04 |
General marriage rate | 0.05 | 0.05 | 0.05 | 0.02 | 0.02 | 0.02 | 0.05 | 0.05 | 0.05 | 0.05 | 0.05 | 0.05 |
General divorce rate | 0.02 | 0.03 | 0.03 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 |
General cohabiting rate | 0.09 | 0.10 | 0.10 | 0.07 | 0.08 | 0.08 | 0.09 | 0.09 | 0.10 | 0.10 | 0.10 | 0.10 |
General union break rate | 0.26 | 0.26 | 0.26 | 0.32 | 0.32 | 0.32 | 0.19 | 0.19 | 0.29 | 0.29 | 0.29 | 0.29 |
Male mean age 1st mar. | 28.0 | 29.00 | 29.00 | 31.0 | 32.15 | 32.15 | 27.9 | 28.50 | 28.50 | 31.6 | 32.80 | 32.80 |
Female mean age 1st mar. | 26.5 | 27.8 | 27.8 | 30.4 | 32.1 | 32.1 | 27.0 | 28.1 | 28.1 | 29.8 | 31.2 | 31.2 |
Mean age at births | 28.7 | 29.8 | 29.8 | 25.5 | 25.9 | 25.9 | 26.0 | 26.2 | 26.2 | 29.1 | 29.9 | 29.9 |
Mean age at births | 29.2 | 30.3 | 30.3 | 25.9 | 26.3 | 26.3 | 26.4 | 26.7 | 26.7 | 29.6 | 30.4 | 30.4 |
Appendix 2: A Two-Step Procedure to Estimate Age-Sex-Race-Living Arrangement-Disability Status-Specific Care Hours and Care Costs Per Elder
Because of too small sub-sample size for minority sub-groups, especially for the oldest-old aged 80+, we did not use the unreliable directly-computed age-sex-race-living arrangement-disability status-specific care hours and care costs per elder. Instead, we applied a “two-step” approach to obtain our estimates after careful investigations and tests:
-
Step one: We first calculated baseline sex-age-specific values with all of the other attributes combined (including racial groups, disability status, and living arrangement types) for home-based care costs per elder from the data directly;
-
Step two: We then estimated the sex-age-attribute-specific care costs per elder by multiplying the baseline sex-age-specific care costs per elder by the multivariate regression estimates of the corresponding odds ratios of care needs/costs among persons with different attributes, as compared to the baseline.
Why did we adopt the two-step approach rather than the “one-step” approach of multivariate regression models to directly estimate the age- race- sex- living arrangement- disability status-specific care need/costs per elder? In general, multivariate regression models are powerful in explanatory analysis of associations with socio-economic and demographic covariates. When the primary purpose is, however, to estimate the age-specific schedules (or trajectories) and propensities of the occurrence of the events rather than explanatory analysis, the classic regression approach may not be ideal. This is because the estimate of the age covariate coefficients in the regression model may not accurately represent the age trajectory, unless the age trajectory follows precisely linear or log-linear or another kind of analytical distribution, which is unlikely (Land et al. 1994: 304), especially in the case of age-race- sex-living arrangement- disability status-specific care costs per elder. Furthermore, regression models presume that all sources of individual-level variations are explained by the covariates that enter the regressions. That is, the regression models assume that no “hidden heterogeneity” is present in the age and other covariate specific rates estimated based on the regression coefficients. This specification is almost surely not true empirically, especially for extended periods of more than 1 year (Land et al. 1994: 304).
We have empirically tested the “one-step” approach of the multivariate regression model to directly estimate the race- sex- age- living arrangement- disability status-specific care costs per elder, without the estimates of the sex-age-specific baseline care needs/costs per elder. The results are out of an empirically plausible range for some age groups. Even after correcting the logic errors by introducing some constraints to the regression, the estimates are still unreasonable. In short, our empirical tests and theoretical considerations lead us to believe that the “two-step” approach is much more robust than the “one-step” approach in estimating the race- sex- age- living arrangement- disability status-specific care costs per elder.
Appendix 3: Age-Sex-Race-Living Arrangement-Specific Disability Rates, Home-Based Care Hours, and Care Costs ($), Based on Data from NLTCS 1999 Wave, the United States
Males | Females | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
Age | 65–69 | 70–74 | 75–79 | 80–84 | 85+ | 65–69 | 70–74 | 75–79 | 80–84 | 85+ |
Disability (%) | ||||||||||
Living alone | ||||||||||
White non-Hispanic | 2.31 | 2.54 | 3.84 | 6.12 | 11.13 | 2.65 | 3.32 | 4.87 | 7.90 | 15.26 |
Black non-Hispanic | 3.93 | 4.33 | 6.48 | 10.16 | 17.92 | 4.51 | 5.62 | 8.15 | 12.91 | 23.88 |
Hispanic | 2.19 | 2.41 | 3.64 | 5.81 | 10.59 | 2.51 | 3.14 | 4.62 | 7.50 | 14.55 |
Asia and other non-Hispanic | 1.94 | 2.13 | 3.23 | 5.17 | 9.47 | 2.23 | 2.79 | 4.10 | 6.69 | 13.07 |
Living with spouse/partner, may (or may not) live with children/others | ||||||||||
White non-Hispanic | 4.32 | 4.76 | 7.11 | 11.10 | 19.44 | 4.95 | 6.17 | 8.92 | 14.06 | 25.74 |
Black non-Hispanic | 7.28 | 8.00 | 11.75 | 17.84 | 29.73 | 8.29 | 10.25 | 14.53 | 22.03 | 37.79 |
Hispanic | 4.10 | 4.51 | 6.74 | 10.56 | 18.57 | 4.70 | 5.85 | 8.48 | 13.40 | 24.68 |
Asia and other non-Hispanic | 3.64 | 4.00 | 6.00 | 9.44 | 16.74 | 4.17 | 5.20 | 7.56 | 12.03 | 22.42 |
Not living with spouse/partner but living with children/others | ||||||||||
White non-Hispanic | 6.14 | 6.75 | 9.98 | 15.31 | 25.99 | 7.01 | 8.69 | 12.41 | 19.09 | 33.52 |
Black non-Hispanic | 10.21 | 11.20 | 16.21 | 23.96 | 38.26 | 11.57 | 14.22 | 19.76 | 28.95 | 47.06 |
Hispanic | 5.82 | 6.40 | 9.48 | 14.60 | 24.91 | 6.65 | 8.25 | 11.81 | 18.25 | 32.27 |
Asia and other non-Hispanic | 5.18 | 5.69 | 8.46 | 13.11 | 22.61 | 5.92 | 7.36 | 10.58 | 16.48 | 29.57 |
Home-based care hours per week received by disabled elders | ||||||||||
Living alone | ||||||||||
White non-Hispanic | 9.95 | 11.36 | 12.43 | 14.57 | 17.27 | 7.99 | 9.20 | 10.71 | 12.01 | 21.21 |
Black non-Hispanic | 13.31 | 15.48 | 16.83 | 19.62 | 23.10 | 10.46 | 12.21 | 14.49 | 16.21 | 27.68 |
Hispanic | 13.63 | 15.79 | 17.21 | 19.98 | 23.56 | 10.75 | 12.51 | 14.78 | 16.48 | 27.76 |
Asia and other non-Hispanic | 12.15 | 14.11 | 15.36 | 17.95 | 21.19 | 9.57 | 11.15 | 13.21 | 14.81 | 25.74 |
Living with spouse/partner, may (or may not) live with children/others | ||||||||||
White non-Hispanic | 23.43 | 26.62 | 28.57 | 32.10 | 36.31 | 18.84 | 21.51 | 25.18 | 27.32 | 40.17 |
Black non-Hispanic | 29.32 | 32.57 | 34.69 | 38.34 | 42.39 | 24.22 | 27.04 | 31.17 | 33.28 | 45.72 |
Hispanic | 29.74 | 33.09 | 35.30 | 38.64 | 42.77 | 24.62 | 27.41 | 31.39 | 33.33 | 45.30 |
Asia and other non-Hispanic | 27.46 | 30.68 | 32.73 | 36.47 | 40.55 | 22.49 | 25.30 | 29.37 | 31.57 | 44.38 |
Not living with spouse/partner but living with children/others | ||||||||||
White non-Hispanic | 24.85 | 28.08 | 30.07 | 33.72 | 37.91 | 20.08 | 22.83 | 26.69 | 28.87 | 41.84 |
Black non-Hispanic | 30.78 | 33.98 | 36.12 | 39.84 | 43.81 | 25.61 | 28.44 | 32.69 | 34.80 | 47.18 |
Hispanic | 31.24 | 34.55 | 36.77 | 40.18 | 44.23 | 26.04 | 28.84 | 32.93 | 34.87 | 46.78 |
Asia and other non-Hispanic | 28.91 | 32.10 | 34.16 | 37.99 | 42.01 | 23.84 | 26.67 | 30.89 | 33.10 | 45.89 |
Care payment ($) per month of home-based care for disabled elders | ||||||||||
Living alone | ||||||||||
White non-Hispanic | 192.16 | 240.46 | 272.40 | 348.29 | 389.17 | 117.20 | 216.24 | 251.62 | 297.58 | 429.53 |
Black non-Hispanic | 117.27 | 146.27 | 167.61 | 223.70 | 259.53 | 71.66 | 131.54 | 154.62 | 190.83 | 285.12 |
Hispanic | 169.40 | 209.93 | 238.58 | 304.40 | 342.06 | 104.23 | 190.73 | 222.54 | 263.17 | 381.74 |
Asia and other non-Hispanic | 116.79 | 142.22 | 162.78 | 212.27 | 242.87 | 72.26 | 130.84 | 153.97 | 185.60 | 275.05 |
Living with spouse/partner, may (or may not) live with children/others | ||||||||||
White non-Hispanic | 67.56 | 87.98 | 101.73 | 133.42 | 160.46 | 95.98 | 178.16 | 207.62 | 253.40 | 372.39 |
Black non-Hispanic | 38.46 | 50.85 | 58.94 | 77.83 | 94.97 | 57.27 | 106.49 | 124.78 | 158.10 | 238.66 |
Hispanic | 58.91 | 76.45 | 88.47 | 114.78 | 137.95 | 84.22 | 155.05 | 180.98 | 220.14 | 324.40 |
Asia and other non-Hispanic | 38.87 | 49.43 | 57.28 | 75.26 | 90.62 | 56.76 | 103.51 | 121.67 | 149.94 | 224.73 |
Not living with spouse/partner but living with children/others | ||||||||||
White non-Hispanic | 114.03 | 147.11 | 169.18 | 222.55 | 262.30 | 102.75 | 190.82 | 222.75 | 270.83 | 397.03 |
Black non-Hispanic | 66.07 | 86.06 | 99.51 | 133.86 | 161.77 | 61.53 | 113.73 | 133.89 | 168.99 | 255.59 |
Hispanic | 98.80 | 126.52 | 145.73 | 190.02 | 224.40 | 90.50 | 166.50 | 194.82 | 236.16 | 347.56 |
Asia and other non-Hispanic | 65.38 | 82.04 | 94.78 | 125.31 | 149.00 | 61.51 | 111.73 | 131.75 | 161.72 | 242.45 |
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Zeng, Y., Land, K.C., Gu, D., Wang, Z. (2014). Effects of Changes in Household Structure and Living Arrangements on Future Home-Based Care Costs for Disabled Elders in the United States. In: Household and Living Arrangement Projections. The Springer Series on Demographic Methods and Population Analysis, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8906-9_10
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