Global quality of life modifies terminal change in physical functioning among older adult women

Abstract

Background: the factors that moderate decline in physical functioning as death approaches are understudied. This study aimed to assess death-related decline in global quality of life (QoL) and physical functioning and to test whether baseline QoL moderates terminal decline in physical functioning.

Methods: four thousand six hundred and fifty-one decedents from the Women's Health Initiative Study (WHI) rated QoL and physical functioning each year throughout 5 years of follow-up.

Results: both QoL and physical functioning showed a steeper decline as a function of years to death than as a function of chronological age. Moreover, decedents with higher QoL at baseline showed a less steep decline in physical functioning as death approached than those with lower QoL at baseline.

Conclusion: although QoL strongly decreases across the terminal years, its beneficial influence on physical functioning is evident till the very end of life.

Evidence shows that health decline is greater when plotted as a function of distance to death (DtD) than as a function of age [1–3]. Relative to chronological age, a strong death-related or terminal decline was found both in performance-based measures—measures of function in the sensory, physical and health domains [4–6]—and in more subjective measures of function, such as cognitive-evaluative and affective aspects of well-being [7, 8].

Despite these relationships, many maintain good functioning until death. It is possible that terminal decline in performance-based measures might be moderated by subjective measures of well-being; however, studies examining these relationships are scarce, mainly focusing on clinical samples [9]. The current study addressed age- and death-related change in global quality of life (QoL) and physical functioning, and most importantly, assessed QoL as a moderator of age- and death-related change in physical functioning.

The World Health Organization defined QoL as the perception of one's position in life, in the context of relevant culture and value systems, and in relation to one's goals, expectations, standards and concerns [10]. Therefore, QoL encompasses appraisal of, and satisfaction with, many factors, such as physical, psychosocial and material well-being [11]. As QoL reflects a personal reaction rather than an objective status, the use of global measures of QoL is acceptable [12, 13]. A preserved sense of QoL in late life has been reported to help maintain physical functioning via physiological effects of positive self-perceptions with regard to cardiovascular and immune functioning [14] and via augmentation of motivational mechanisms that help preserve health behaviors and service use [15].

Based on the above, we hypothesised that death-related decline in QoL and physical functioning would be greater than age-related change, and that QoL would moderate death-related decline in physical functioning, so that those with high QoL at baseline would show less death-related decline in physical functioning. The current study focused on postmenopausal women; as relative to men, they spend a greater proportion of their life with physical malfunctioning [16].

Method

Participants and procedure

The multi-ethnic Women's Health Initiative (WHI) Clinical Trial that incorporated a diverse sample of 68,133 postmenopausal women, 50–79 years of age at study entry, was enrolled between 1993 and 1998 across 40 US clinical centres. Details of the study have been previously published [17]. All WHI participants provided written informed consent, and institutional review board approval was obtained at each of the 40 WHI clinical centres and at the Clinical Coordinating Center at the Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

In 2004–05, remaining WHI participants who provided written informed consent joined the 2005–10 Extension Study. These participants received annual mailed forms. Participants' death records were centrally adjudicated by study physicians using hospital records, autopsy reports and death certificates. Periodic checks of the National Death Index for all participants, including those lost to follow-up, were performed; the latest update was available through 1 December 2013.

In this study, we focused on the data from 6,276 deceased participants enrolled in the Extension Study; among those, 4,651 had adjudicated time of death recorded, and at least one physical functioning or QoL measure available throughout the 5 years of follow-up, composing an analytical sample used here. Mean age was 76.7 (SD = 6.59), 87% were white and the majority had some college education (49.8%).

Measures

Repeated measures of physical functioning were assessed using the 10-item SF36 subscale [18]. Ratings were averaged such that a score of 0 reflected the least favourable health state and a score of 100 the most favourable.

Global QoL was assessed by a single item (‘Overall, how would you rate your quality of life?’) with a 11-point response scale (0 indicates ‘as bad or worse than being dead’ and 10 ‘best quality of life’). This item predicted years of healthy and independent living, as well as survival [19]. It mainly reflects mental health, as it strongly correlated with mental component among community-dwelling individuals [19] and patients [20].

A 5-point Likert scale was used to assess participant's subjective health with responses ranging from 1 (excellent) to 5 (poor). Smoking, alcohol intake, history of cardiovascular disease, diabetes mellitus, stroke, arthritis and demographic data (race/ethnicity, education and income) were collected at the WHI study baseline using self-reported forms.

Individual's age was calculated for each available assessment as the number of years since birth. Similarly, DtD was constructed for each available assessment as the number of years remaining in that participant's life.

Data analyses

To approximate normality, physical functioning scores were log transformed. Separate growth curve models [21] for either change in physical functioning or change in QoL over chronological age and DtD indicators were fitted. These models were specified as follows:

$$\text{Qo}{\text{L}}_{ti}={\beta }_{0i}+{\beta }_{1i}(\text{Dt}{\text{D}}_{ti}|\text{Ag}{\text{e}}_{ti})+{ϵ}_{ti}$$

and

$$\text{Log}(\mathrm{Physical}\mathrm{functionin}{\text{g}}_{ti})={\beta }_{0i}+{\beta }_{1i}(\text{Dt}{\text{D}}_{ti}|\mathrm{Ag}{\text{e}}_{ti})+{ϵ}_{ti}$$

The scores on raw QoL or log-transformed physical functioning measures for person i at time t, QoL_ti|Log (Physical Functioning_ti), are functions of an individual-specific intercept parameter, β_0i, and an individual-specific linear parameters, β_1i, that capture change over the selected time dimensions (age or DtD), and residual error, ϵ_ti. Individual deviations from parameter estimates β_0i and β_1i were assumed to be multivariate normally distributed, correlated with each other and uncorrelated with the residual error ϵ_ti.

Unconditional growth model was fitted to investigate variability over time in QoL and physical functioning scores as a function of either chronological age or DtD, alternating between these two time metrics. Furthermore, to examine whether QoL moderates age- or death-related change in physical functioning, we fitted separate models with demographic variables, chronic conditions, subjective health, health behaviours and baseline QoL as predictors of between-person differences in intercepts (β_0i) and linear slopes (β_1i).

All models were fit to the data using R package ‘nlme’ (version 3.0.2). All variables were centred to ease an interpretation, and full information maximum-likelihood estimation was used to integrate all available information based on missing-at-random assumptions for QoL or physical functioning variables and list-wise deletion for predictors.

Results

Inter-class correlation estimates in the unconditional means models indicated that 44% of the total variance in QoL and 33% of the total variance in physical functioning is attributable to within-person characteristics. Table 1 presents estimates of unconditional growth models.

Table 1.

Growth curve models for global quality of life and physical functioning as a function of distance to death and chronological age

Fixed effects	Global quality of life		Physical functioning
	Chronological age	Distance to death	Chronological age	Distance to death
Intercept	6.85 (0.03)	6.93 (0.03)	3.59 (0.02)	3.63 (0.01)
Slope	−0.05 (0.003)	0.25 (0.01)	−0.04 (0.002)	0.15 (0.006)
Random effects
Intercept	2.25 (0.08)	2.16 (0.07)	0.76 (0.02)	0.76 (0.02)
Slope	0.004 (0.0002)	0.11 (0.01)	0.003 (0.0003)	0.04 (0.004)
Corr. intercept × Slope	0.25 (0.07)	−0.32 (0.04)	0.56 (0.04)	−0.61 (0.03)
Residual	1.88 (0.03)	1.59 (0.02)	0.40 (0.005)	0.30 (0.007)
Goodness of fit
Schwarz's Bayesian criterion	51,487.17	50,790.97	29,843.92	28,826.2
Pseudo R2	0.03	0.16	0.07	0.26

N = 4,651. P < 0.001 for all effects. Physical function scores are on a log-transformed scale.

When QoL was regressed on age/DtD, the estimate for the slope for the DtD was twice as large as the one for age. Furthermore, the DtD model explained 16% of variance in longitudinal dynamics in QoL, whereas the age model explained merely 3%. Similarly, when physical functioning was regressed on age/DtD, the estimates for the slope for DtD was almost four times as large as the slope for age. The DtD and age models explained 26 and 7% of variance in physical functioning, respectively.

Results from models examining the association of baseline QoL and other characteristics with between-person differences in physical functioning status and longitudinal dynamics are reported in Table 2.

Table 2.

Growth curve models for physical functioning as a function of distance to death, chronological age and their interaction with baseline global quality of life

Fixed effects	Chronological age		Distance to death (DtD)
	Estimate (SE)	P value	Estimate (SE)	P value
Intercept	4.37 (0.08)	<0.001	4.36 (0.07)	<0.001
Slope	−0.02 (0.01)	0.08	0.13 (0.03)	<0.001
Baseline global quality of life (QoL)	0.16 (0.009)	<0.001	0.15 (0.009)	<0.001
DtD/Age	0.12 (0.005)	<0.001	−0.03 (0.002)	<0.001
Race/ethnicity	0.02 (0.04)	0.67	0.02 (0.04)	0.62
Education	0.008 (0.008)	0.31	0.01 (0.007)	0.16
Income	−0.00007 (0.009)	0.99	−0.005 (0.009)	0.96
Subjective health	−0.25 (0.02)	<0.001	−0.24 (0.02)	<0.001
Smoking	0.0003 (0.02)	0.98	−0.01	0.47
Alcohol consumption	0.02 (0.009)	0.008	0.03 (0.009)	0.003
Stroke	−0.44 (0.11)	<0.001	−0.36 (0.10)	<0.001
Diabetes	−0.16 (0.05)	0.002	−0.19 (0.05)	<0.001
Cardiovascular disease	−0.03 (0.03)	0.33	−0.02 (0.03)	0.47
Arthritis	−0.12 (0.03)	<0.001	−0.13 (0.03)	<0.001
Slope × Baseline global QoL	0.004 (0.001)	0.002	−0.02 (0.004)	<0.001
Slope × DtD/Age	0.005 (0.0008)	<0.001	0.006 (0.0009)	<0.001
Slope × Race/ethnicity	−0.0009 (0.005)	0.87	−0.02 (0.02)	0.34
Slope × Education	−0.003 (0.001)	0.78	0.002 (0.003)	0.47
Slope × Income	0.00009 (0.001)	0.94	0.003 (0.004)	0.36
Slope × Subjective health	0.002 (0.003)	0.41	0.002 (0.008)	0.77
Slope × Smoking	−0.0004 (0.003)	0.88	−0.009 (0.009)	0.31
Slope × Alcohol consumption	−0.003 (0.001)	0.06	0.003 (0.004)	0.38
Slope × Stroke	−0.001 (0.02)	0.93	0.08 (0.04)	0.08
Slope × Diabetes	−0.001 (0.008)	0.88	−0.03 (0.02)	0.21
Slope × Cardiovascular disease	0.001 (0.005)	0.81	0.003 (0.01)	0.83
Slope × Arthritis	0.002 (0.004)	0.56	−0.03 (0.01)	0.03
Random effects
Intercept	0.46 (0.02)	<0.001	0.48 (0.01)	<0.001
Slope	0.002 (0.0003)	<0.01	0.03 (0.005)	<0.01
Corr. intercept × Slope	0.64 (0.035)	<0.001	−0.66 (0.035)	<0.001
Residual	0.36 (0.006)	<0.001	0.30 (0.007)	<0.001
Goodness of fit
Schwarz's Bayesian criterion	23,374.91		22,929.44
Pseudo R2 statistics
Explained within-subject variance	0.13		0.27
Explained between-subject variance—intercept	0.39		0.36
Explained between-subject variance—slope	0.33		0.25

N = 3,775. Physical function scores are on a log-transformed scale.

The results suggest that baseline QoL is indeed significantly associated with initial late-life physical functioning scores if modelled as a function of age or as a function of DtD. Moreover, QoL was a significant correlate of change in physical functioning in both models, but the magnitude of the effect was almost five times stronger in the DtD model.

Discussion

Supporting our hypotheses, we found that a death-related change in QoL and physical functioning was stronger than age-related change. These findings add to previous evidence for a stronger death-related decline in subjective aspects of well-being [7, 8] and in performance-based measures of functioning [4–6].

Most importantly, baseline QoL moderated death-related decline in physical decline. That is, participants with high QoL showed a more moderate decline in physical functioning as death approached than those with low QoL. The moderating effect of QoL on age-related decline in physical functioning was smaller.

Well-being is known to contribute to better health and longevity through a myriad of psychosocial and behavioural factors [22, 23]. The current finding adds to the literature by showing that the health benefits’ effects of QoL are also observable at the very end of life when deteriorating functioning and the breakdown of overall system coordination become inevitable [3].

Future efforts should be directed at understanding the mechanisms behind the moderation effect. It is possible that high QoL provides a more constructive outlook of present and future functional status and, thus, promotes proactive steps to regain control over life [24].Favourable QoL assessment can also be related to higher will to live [25] which in turn can increase the preference for health behaviours, thus mitigating death-related decline [26].

Our findings should be interpreted in light of the study's limitations. First, our follow-up period extended to 5 years, so it is needed to assess death-related decline across longer periods. It is also possible that physical decline prior to death was under-observed, and therefore, the reported trends may underestimate their magnitude. Finally, as QoL was assessed using a single item, an assessment with more detailed and differential measures is in order in the context of terminal process.

To conclude, the current findings suggest that decline in physical functioning can be mitigated by QoL. Therefore, clinicians should be aware that although QoL strongly decreases across the terminal years, its beneficial impact on physical functioning is evident till the very end of life.

Key points.

• Subjective and performance-based health domains show a more rapid decline as death approaches than as age increases.

• Global QoL and physical functioning showed a steeper decline as a function of years to death than as a function of chronological age.

• Decedents with high global quality of life at baseline showed a moderate decline in physical functioning as death approached.

• Global quality of life decreases before death but still maintains its ability to moderate physical functioning till the very end of life.

Conflicts of interest

None declared.

Funding

The WHI program is funded by the National Heart, Lung and Blood Institute, National Institute of Health, US. Department of Health, and Human Services through Contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221.