depicts the flow of participants through different stages of the study. During the 22-month follow-up, of the 766 participants (384 in the control group and 382 in the intervention group) who received interventions, 271 (123 + 148) were excluded from the analysis because they discontinued the intervention (due to death, no longer interested, or other reasons). An additional 43 (27 + 16) participants were excluded from the analysis because their 22-month follow-up assessments were completed by proxies. The mortality rates of the intervention group and the control group were the same (18% in both groups, p = .90). The dropout rates for reasons other than death were higher in the intervention group (20% vs. 14% in the control group, p = .02), primarily due to the fact that more participants in the intervention group were “no longer interested” in the program (41 versus 18). Despite this difference, further analysis showed that those who dropped out of the study had similar mortality rates (28% in the control group and 27% in the intervention group, p = .91).
We compared those who were included in this analysis (n = 452) with those who were excluded (n = 314). We found that participants who were excluded were older; were more likely to have an informal caregiver; had more IADL disability and cognitive impairment; were more likely to have congestive heart failure (CHF), stroke, and chronic obstructive pulmonary disease; were less likely to be overweight or obese; and were more likely to have past health services use (results not shown).
shows sociodemographics, health and physical function, and health services use prior to enrollment of participants at baseline for the study sample and by intervention and urban–rural status. The mean age of the sample was 76 years, and more than two thirds (71%) were female, 37% lived alone, and 70% had informal caregivers. Participants in the control and the intervention group had similar characteristics, with the exception of two variables: percent with CHF and stroke. In the urban sample, the only significant difference between the intervention and the control group was that more participants reported having CHF. In the rural sample, fewer participants in the intervention group reported being married. Urban and rural participants were similar with respect to sociodemographics, most health status measures, and past health services use, with the exception of the following: rural participants reported having fewer ADL dependencies, more myocardial infarction, and better self-rated health compared with their urban counterparts.
Baseline Characteristics of the Sample by Intervention and Urban–Rural
shows the unadjusted results of functional change for the study sample. The average participant demonstrated functional decline between the baseline and the 22-month follow-up, as evident by the increased mean number of ADL dependencies over time. The decline in function was much smaller in the intervention group (.23) when compared with that of the control group (.50), indicating a 54% ([.50 − .23] × 100/.50) reduction in functional decline among the intervention group.
Changes in mean number of activities of daily living by intervention.
illustrates functional change over 22 months by intervention and urban–rural status, indicating that the intervention is much more effective among rural participants. Rural participants who received the intervention had an 81% ([.62 − .12] × 100/.62) reduction in mean number of ADL dependencies compared with a 36% ([.45 − .29] × 100/.45) reduction among urban participants.
Changes in mean number of activities of daily living by intervention and rural status. MSA = Metropolitan Statistical Area.
shows the results from the OLS regression analyses, including the stratified analysis by urban–rural status. Coefficient estimates from the OLS models confirmed our finding of the intervention effect in reducing functional decline (coefficient estimate −0.27, p = .03) in the unadjusted analysis for the overall sample. When the same model was estimated for urban and rural participants separately, the intervention effect was no longer statistically significant among urban participants (−0.09, p = .56). However, the intervention effect among rural participants was more than double (−0.57, p = .01) the overall effect. Other significant predictors of functional change include age, baseline functional status, CPS, stroke, overweight or obese, self-rated health, and skilled home health care use during the year prior to enrollment.
Effect of the Intervention on the Changes in ADL and by Urban–Rural
Average total health care expenditures were 11% ($3,100, p
.30) lower in the intervention group during the 22-month study period ($26,100 in the intervention group and $29,200 in the control group). shows the adjusted results of the impact of intervention on average total health care expenditures for the study sample and by urban–rural status. The result suggested that the intervention is cost neutral even factoring in the substantial cost of delivering the intervention ($3,500 per participant). Other significant predictors of total health care expenditures include baseline ADL, self-rated health, and skilled home health care use.
Effect of the Intervention on Total Health Care Expenditures and by Metropolitan Statistical Area