Prospective Outcomes of Informal and Formal Home Care: Mortality and Institutionalization. 3.3 Multivariate Analysis

12/19/1990

The next step in our analytic strategy, then, is to control for the set of confounders while evaluating the association between caregiving arrangements and the outcome. Thus we can estimate an adjusted odds ratio that takes into account social and health variables related to the outcomes. Table 3-5 reports the results for mortality. The table includes the crude odds ratio between caregiving arrangements and mortality. It also includes the odds ratio after adjusting only for social, then only for health variables, and finally, for both social and health variables. The table illustrates how confounders can affect the association between two variables. For example, the association between disability and, finally, mortality is decreased by adjusting for social variables. Nonetheless, there remains a significant association between disability and mortality. (The odds ratio falls from 2.60 to 1.83). However, after controlling for health variables, only a trivial association between disability and mortality remains, an odds ratio of 1.11. Controlling for both health and social variables (Column 4) results-in an odds ratio very close to 1, meaning no association. This indicates that, in large part, the apparent excess mortality associated with disability was really related to severity of illness. Considering only the adjustment for health variables, the association between receiving help and mortality also is, in part, a function of illness severity. After controlling for health variables the odds ratio dropped from 3.27 to 2.56. However, this odds ratio is still statistically significant, indicating that the health confounders did not account entirely for the associations of help with mortality. Adding in the social variables decreases the odds ratios further to 2.48. It is conceivable that the health variables measured here simply are not as sensitive to illness severity as the measure of receiving help itself is. Conversely, we might conclude that receiving help is, in fact, a risk factor for mortality.

TABLE 3-5. Odds of Dying During Two-Year Follow-Up by Characteristics of Disability and Caregiving
Caregiving Arrangements Crude Odds Ratio Net Odds Ratios Controlling for:
Social Variables Health Variables Both Health and Social
Disability vs.
No Disability
2.60** 1.83** 1.11 1.02
Help vs.
No Help
3.27** 4.69** 2.56* 2.48*
Any Unpaid Help vs.
All Paid Help
1.52* 1.22 1.19 1.09
Any Close Family Unpaid Help vs.
No Close Family Unpaid Help
0.66 0.76 0.86 0.93
All Unpaid Help vs.
Some Paid, Some Unpaid
1.06 1.04 0.68 0.73
All Unpaid Help, Close Family vs.
All Unpaid Help, Not Close Family
0.64 0.77 1.21 1.29
* = significant at <0.05; ** = significant at <0.001

In assessing the association between the contrast, any unpaid help versus all paid help, and mortality, we find that the association decreases substantially and becomes insignificant when controlling for either social variables or health variables. It approaches no association, an odds ratio of 1.09, when both sets of variables are controlled. A similar pattern is seen for receiving unpaid help from close family members versus only distant or non-relatives.

In contrast, the crude odds ratio for all unpaid help versus some paid and some unpaid help is close to 1 and remains unchanged after controlling for social confounders. However, after controlling for health confounders, this association becomes much stronger, having an odds ratio of 0.68. This illustrates a classic suppressor effect. In this instance more severe illness is positively related to mortality but negatively related to receiving all unpaid help. This makes it appear that all unpaid help is unrelated to mortality, whereas, in reality, receiving all unpaid help is negatively related to mortality. Those receiving all unpaid help are 47 percent less likely to die than those receiving some paid and some unpaid help. However, the association, though moderate in magnitude, is not statistically significant. This may be a function of small numbers of individuals in these categories.

A distorter effect is observed for the subset of all unpaid help from close family members versus distant relatives or non-relatives. The crude odds ratio is 0.64 indicating that help from close family members is associated with a lower odds of dying in the follow-up period. However, after controlling for health variables, the odds ratio becomes positive, 1.21, indicating that those receiving unpaid help from close family members are more likely to die than those receiving unpaid help from others.

TABLE 3-6. Odds of Entering a Nursing Home During Two-Year Follow-Up by Characteristics of Disability and Caregiving
Caregiving Arrangements Crude Odds Ratio Net Odds Ratios Controlling for:
Social Variables Health Variables Both Health and Social
Disability vs.
No Disability
4.37** 2.15** 2.00** 1.58*
Help vs.
No Help
1.73 1.36 1.19 1.12
Any Unpaid Help vs.
All Paid Help
1.24 1.02 1.01 1.04
Any Close Family Unpaid Help vs.
No Close Family Unpaid Help
1.03 1.05 1.16 1.03
All Unpaid Help vs.
Some Paid, Some Unpaid
1.41 1.21 1.30 1.12
All Unpaid Help, Close Family vs.
All Unpaid Help, Not Close Family
1.36 1.65 2.02 1.80
* = significant at <0.05; ** = significant at <0.001

We also performed a similar analysis for entering a nursing home. In Table 3-6 a pattern of classical confounders is observed for the association of disability with entering a nursing home. After controlling for both health and social behaviors, the odds ratio falls from 4.37 to 1.58. The odds ratio remains statistically significant. In most instances the odds ratio falls from a larger association to a smaller association after controlling for social health variables or both. The exception to the rule in this pattern is for the last comparison of persons receiving all unpaid help from close members versus receiving all unpaid help from distant relative and non-relatives. The crude odds ratio is 1.36. This increases slightly after control for social variables and increases even more after control for health variables, reaching an odds ratio of 2.02. Together, the adjustment for health and social variables results in odds ratios of 1.8. Such an odds ratio is not trivial in terms of its substantive importance. However, because of the small number of cases in this analysis, it is not statistically significant.

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