The sample included 8,471 individuals representing a total population of 13.2-million persons who needed or received help with ADLs/IADLs in the 2 weeks prior to being interviewed ().2
As expected, most people received informal or unpaid help. Help from one or more paid helpers was received by 3.2-million persons (23.9 percent); 11.7-million persons received help from a primary unpaid helper (88.5 percent), which tended to be a spouse or often a parent, and 4.0 million (30.1 percent) received additional help from one or more secondary unpaid helpers, often children and friends. Of all recipients of help, 65 percent were female, and 17 percent were non-White. The average age was 60.6 years—6.9-million working-age persons (18–64 years) and 6.2-million older persons (65 years and over). The average education was just under completion of the eleventh grade. Almost a quarter (24 percent) lived alone. Sixty-two percent had Medicare. Twenty-six percent had Medicaid, and 73 percent lived in urban areas. On average, recipients had 1.6 helpers, 0.3 paid and 1.3 unpaid. Those who received paid help were 69.5 years old—almost 10 years older than those who received unpaid help—and they were more likely to live alone, have higher incomes, to be on Medicare, to be helped with ADLs, and to be helped with housework. People who got help from one or more secondary unpaid helpers were less likely to be helped with bathing and dressing than those who got help from a primary unpaid helper but were about as likely to be helped with other ADLs and IADLs.
In order to impute missing hours, we estimated linear prediction models for the three sources of hours of help. shows the estimated multiple regression imputation models for the log of paid hours of help and hours provided by unpaid primary and secondary helpers. The model for paid hours accounted for 44.3 percent of the variation, adjusted for the number of predictor variables. Being non-White, living in an urban area, and the number of paid caregivers were positive predictors of paid hours of care, whereas the number of unpaid helpers was a significant negative predictor. Thus, the greater the number of informal helpers a person has, the lower the hours that are provided by paid helpers—the more paid helpers, the more paid hours. With respect to the need factors, these models predict the number of hours that each individual received based on the activities that the particular class of helper(s) actually helped with. The coefficients represent the independent effects of each activity. Bathing was the only ADL factor that was a significant predictor of paid hours, in the positive direction. Six IADLs were significant positive predictors of paid hours, with the strongest factor being help in preparing meals. One IADL—receiving heavy housework—was a negative predictor of paid hours of care. Heavy housework is the most common activity in which people get help, and it represents the group with the lowest level of disability.
Estimated Weighted Regression Models for the Log Hours of Personal Assistance Services Among Populations with Paid Helper(s), a Primary Unpaid Helper, and Secondary Unpaid Helper(s)
The model for hours provided by the primary unpaid helper was different from the paid helper model. Non-White persons had higher unpaid hours, as they did for paid hours, and the number of unpaid caregivers had a negative association with hours received from the primary unpaid helper. Thus, the greater the number of informal helpers that a person has, the lower the hours that are provided by the primary informal helper. Unlike paid hours, the number of paid helpers was not associated with informal hours. As with paid hours, age had no impact. However, being female, having higher levels of education, living alone, and having a higher monthly income were negative predictors of unpaid hours, and Medicare was a positive predictor, although none of these variables were significant predictors of paid hours. As with paid hours, getting help with bathing was significant. Dressing and eating had no effect on paid hours but were associated with greater unpaid hours. Walking and getting outside were two IADLs that increased unpaid hours, but not paid hours. As with paid hours, preparing meals had the largest effect on unpaid hours. This model explained 51 percent of the variance.
The model for secondary unpaid hours was different from the model for primary unpaid helper hours. Being non-White was more strongly significant. Older persons received fewer hours from secondary unpaid helpers. This is the only model in which age had any effect on hours. People with higher education and those who lived alone received fewer secondary hours, whereas the number of unpaid helpers was a positive factor. Bathing was a significant positive factor, but unlike for primary helper hours, dressing and eating were not significant. Preparing meals and walking were the strongest IADL factors, followed by light housework, managing medication, and getting outside. The model for unpaid secondary hours explained slightly less variance than the other two models (40 percent). In both unpaid models, living alone had a very large impact with an absolute effect as large as that of help with meal preparation, the strongest of the need (ADL/IADL) predictors. Walking and getting outside increased hours of unpaid help, especially among secondary unpaid helpers.
The final results of the imputation on the estimated total hours, which is the sum of the hours over the three populations, are shown in . The mean hours per person were 30.9 for the known cases and 31.4 for the multiple regression model imputation method. The greatest difference was for paid hours. The multiple regression model imputation method produced an estimate of 17.6 hours compared with 19.1 for the known cases. This resulted because, of those who received paid services, the missing data were more likely among those with less disability, which the regression model adjusts for.
Estimated Means and Standard Deviations of Hours of Assistance in ADLs/IADLs for Respondents with Known Hours and Including Imputed Hours
shows the total paid and unpaid hours, including the imputed data, for all persons receiving help. Those who received paid help got 17.6 hours of paid help, and those who received unpaid help got 30.7 hours of unpaid help per week. Thus, although the minority of recipients got paid help, they also got lower hours of paid help than unpaid help.
Estimated Paid, Unpaid, and Total Hours of Personal Assistance Services Provided to Adults Living at Home
Those who get help with any ADLs average 57.0 hours of help per week. The 8.3-million people who do not receive help with ADLs but received help with any of the IADLs received just 16.3 hours per week. The total hours of help increased from those needing help in bathing receiving an average of 63.6 hours per week to those needing help in eating receiving 106.7 hours. Unpaid hours increase more with the number of ADLs and IADLs a person gets help with than do paid hours. Of persons getting help with five ADLs, those who get unpaid help get 108.7 unpaid hours, and those who get paid help get 50.8 paid hours.
More than 9-million individuals received help with heavy housework, but these individuals received the fewest hours (30.5 hours per week) compared with the other IADLs.
The fewest number of persons (1.3 million) received help with using the telephone, but they received an average of 87.2 total hours of help per week, the highest number of hours of the IADLs.