Relevance of Lifestyle and Attitudinal Factors to Spine Surgery Outcomes: Empirical Results on a Heterogeneous Sample

doi:10.4236/ss.2011.23024

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Surgical Science, 2011, 2, 121-126

doi:10.4236/ss.2011.23024 Published Online May 2011 (http://www.scirp.org/journal/ss)

Relevance of Lifestyle and Attitudinal Factors to Spine

Surgery Outcomes: Empirical Results

on a Heterogeneous Sample

Carolyn E. Schwartz1,2, Brian Quaranto1,3,4, Emily Samaha3,4, Mariam Kahn-Woods 4,5, Paul Glazer6

1DeltaQuest Founda tion, Concord, MA, USA

2Departments o f Med i ci ne an d Ort h opaedic Sur gery, Tufts Universi t y Sch ool of Medi ci n e , Boston, MA, USA

3Boston College, Chestnut Hill, MA, USA

4Foundation for Orthopaedic Spine Research, Chestnut Hill, MA, USA

5University of Pennsylvania School of Nursing, Philadelphia, PA, USA

6Department of Orthopaedic Surgery, Beth Israel Deaconess Medical Center,

Harvard Medical School, Boston, MA, USA

E-mail: [email protected]

Received January 13, 2011; revised April 4, 2011; accepted April 12, 2011

Abstract

Background Context: Patient demographic and medical indicators influence the well-being of spine surgery

patients. It may, however, be worthwhile to evaluate other lifestyle and attitudinal factors. We hypothesized

that such factors would explain at least as much variance in outcome as more commonly considered covari-

ates. Purpose: To compare explained variance in outcome of lifestyle and attitudinal factors as compared to

standard demographic and medical covariates. Study Design/Setting: Cross-sectional observational study of

patients drawn from an active clinic and internet-based support group. Patient Sample: A heterogeneous

sample of 376 patients was recruited, comprised of people with diagnoses of cervical (n = 80), lumbar (n =

228), and scoliosis (n = 68) spine disorders. Outcome Measures: Quality of Life (QOL) outcomes were

measured using the Oswestry Disability Index, Neck Disability Index, Rand-36, PROMIS Pain Impact, NRS

Back and Leg Pain, Scoliosis Research Society-22r, and Global Health. Methods: This study compared ex-

plained variance in QOL outcomes of demographic and medical versus lifestyle and attitudinal factors. De-

mographic and medical factors included age, gender, body mass index, and co-morbidities. Lifestyle factors

included exercise and commuting practice. Attitudinal factors related to social connectedness: giving and

receiving emotional support, feeling overwhelmed by others’ needs, helping orientation, and general helping

behaviors. Regression analyses estimated explained variance. Patient groups differed in most factors evalu-

ated, so the regression analyses were computed separately by group. R2 statistics were characterized as null,

small (0.02), medium (0.15), and large (0.35) effect sizes (ES), and proportions were compared for the medi-

cal/demographic versus lifestyle/attitudinal factors by group. Results: Similar proportions of variance were

explained by demographic/medical and lifestyle/attitudinal covariates across groups, with half of effect sizes

being small in magnitude and 6% being medium. Lumbar patients tended to have more small effect sizes

among lifestyle and attitudinal covariates than among medical/demographic covariates (z = –1.29, p < 0.10).

Similar patterns were found for both generic and disease-specific outcomes. Conclusions: Spine surgery

outcome research should investigate lifestyle and attitudinal factors to enhance the personal and salutogenic

relevance of the research. Time spent commuting, exercise practice, and social connectedness appear to be

relevant factors. A pre-operative evaluation of overweight and smoking status, limited social connectedness,

and long daily commutes could alert the surgeon to delay or avoid performing procedures on these patients to

avoid poor outcomes.

Keywords: Spine Surgery Outcomes, Predictors, Behaviors, Attitudes, Lumbar, Cervical, Scoliosis

C. E. SCHWARTZ ET AL.

122

1. Background Context

Medical outcome research has evolved greatly in recent

years, with increasing sophistication in estimating effects

of medical and surgical interventions to quantify the im-

portance of such effects. Measurement science has ex-

tended such work to facilitate the interpretation of

changes in outcomes in terms of their clinical signifi-

cance [1-3], and has paved the way for evidence-based

clinical treatment guidelines [4-6]. As part of this evolu-

tion, studies in spine research have documented a wide

range of factors that influence treatment outcome, in-

cluding medical factors (e.g., co-morbidities [7]), socio-

demographic factors [8] (e.g., gender, age), and behavio-

ral factors [8,9] (workers’ compensation status [10,11]).

A recent book on psychological factors related to

spine surgery noted a cluster of about ten psychosocial

and medical risk factors with sufficient empirical docu-

mentation to merit continued consideration [8]. Such

factors included psychological or personality factors (e.g.,

hostility, anxiety, depression, history of psychological

disturbance), behavioral factors (e.g., smoking, substance

abuse, worker’s compensation status, obesity), social

support, and attitudinal factors (e.g., job dissatisfyac-

tion) [8]. They note that psychosocial factors are often

found to be stronger predictors of surgical outcome than

are medical diagnostic factors, and derived an algorithm

for determining surgical prognosis on the basis of these

risk factors [8]. We believe that more research on psy-

chosocial factors in spine outcome research is warranted,

and present preliminary findings to support this recom-

mendation.

2. Purpose

The purpose of the present work was to evaluate the as-

sociation of several heretofore-unexamined lifestyle and

attitudinal factors with quality-of-life (QOL) outcomes in

a sample of patients with spinal disorders, and to com-

pare variance explained by these factors and more com-

monly considered medical and demographic factors.

3. Methods

3.1. Design

To achieve a heterogeneous sample, this cross-sectional

study recruited patients from different sources. First,

patients were recruited from an active spine surgeon’s

practice, comprised of people with diagnoses of cervical,

lumbar, and scoliosis spine disorders. Over half of the

scoliosis patient sample (53%) was additionally recruited

from other sources, including local support groups, via

an article in the Scoliosis Association of America, and

via an internet chat room for people with flatback syn-

drome. Second, this study included people representing a

broad range of time since surgery and number of spinal

surgeries. Approximately one quarter of the data were

collected within a month of a planned spinal surgery, and

three quarters of the sample had an average of 4.1 years

since surgery. Since many patients have had repeated

spinal surgeries over the course of their lifetime, com-

bining them into one analytic sample is a reasonable ap-

proach to enhancing the generalizability of the findings

as well as maximizing the sample size. Thus, it is impor-

tant to note that in the present work, “outcomes” refers to

standardized measures of physical, psychological, and

social functioning and well-being, which can pertain to

spine surgery patients at all stages of the treatment tra-

jectory.

3.2. Patient Sample

Three hundred and seventy-six people with diagnoses of

cervical (n = 80), lumbar (n = 228), and scoliosis (n = 68)

spine disorders.

3.3. Outcome Measures

Quality of Life (QOL) outcomes were measured using

the self-reported Oswestry Disability Index (ODI) [12],

Neck Disability Index (NDI) [12,13], Rand-36 [14] for

cervical and lumbar patients and the Rand-12 [15] for

scoliosis patients, PROMIS1 Pain Impact [16], Numeric

Rating Scale (NRS) items for Back and Leg Pain [17],

Scoliosis Research Society-22r [18], and a 10-point Lik-

ert scaled Global Health item. Co-morbidities were

measured by the Self-Administered Co-morbidity Ques-

tionnaire [19]. Demographic factors included age in

years, gender, dummy variables for normal- and obese-

body mass index (BMI), having a college education,

current smoker, currently on worker’s compensation, a

summative score of co-morbidities, and whether the pa-

tient endorsed having diabetes or depression. Lifestyle

measures included: 1) a three-item index of exercise

comprised of strength-building, aerobic activity, and

yoga or Pilates, with response options of rarely/never (a),

1 - 2 times per week (b), or 3 or more times per week (c);

and 2) commuting practices, as measured by daily

amount of time in hours spent commuting. Attitudinal

factors included the Schwartz Altruism Questionnaire, a

validated 18-item measure self-report measure that as-

sesses four aspects of social connectedness: Community

Connection, Community Pressure, Helping Orientation,

1Refers to measure developed by NIH Roadmap Initiative called the

Patient-Reported Outcome Measurement Information System (PRO-

MIS). This measure is a static short-form. See

www.nihpromis.org for details.

C. E. SCHWARTZ ET AL. 123

and General Helping Behavior [20].

3.4. Procedure

The study was reviewed and approved by the Beth Israel

Deaconess Medical Center Institutional Review Board,

and all patients provided written informed consent prior

to completing the questionnaires. Data were collected

online using a secure, HIPAA-compliant interface

(www.surveygizmo.com).

3.5. Statistical Analysis

This study compared explained variance in QOL out-

comes in demographic and medical factors versus life-

style and attitudinal factors. Linear regressions estimated

explained variance. R2 statistics were characterized as

null, small (0.02), medium (0.15); and large (0.35) effect

sizes (ES) [21], and proportions were compared for the

demographic/medical vs. lifestyle and attitudinal factors

by group.

4. Results

Descriptive statistics for the three patient groups are pre-

sented in Table 1. The three patient groups differed in

most factors evaluated, with the scoliosis patients being

younger, a higher proportion female, a smaller propor-

tion overweight or obese, and a larger proportion with

some college education. Scoliosis patients also reported

the longest time since surgery, with a mean of over 13

years as compared to a mean of about 2 years in the cer-

vical and lumbar patients. Scoliosis patients also had a

higher number of surgeries as compared to the cervical

and lumbar patients (mean = 1.64, 1.2, and 1.1, respec-

tively). The cervical and lumbar patients reported similar

numbers of medical co-morbidities, and substantially

fewer co-morbidities than the scoliosis patients. The

prevalence of depression and diabetes was highest

among cervical patients.

Regarding the lifestyle factors investigated, the scolio-

sis patients reported more frequent engagement in all

types of exercise, with a particularly notable difference

in the practice of yoga or Pilates compared to the other

patient groups. Similar proportions of patients were of

Caucasian race, married, currently employed, and current

smokers. The mean time spent commuting was also sim-

ilar across groups. Regarding the attitudinal factors, pa-

tient groups differed on four of the five subscales of the

Altruism scale, with scoliosis patients reporting lower

levels of giving support and helping orientations, higher

reported levels of feeling overwhelmed by others’ de-

mands, and higher reported levels of engaging in general

helping behaviors. There were no differences in reported

Table 1. Descriptive statistics of subsamples.

Cervical

(n = 80)

Lumbar

(n = 228) Scoliosis

(n = 68) F or X2

Statistica

Demographic and Medical C h a r a c t er i s t i c s

Mean Age (Sd) 57.9 (13.6)56.9(14.3) 54.7 (11.9)0.55

Gender: % Female 58.4 48.0 92.6 38.7****

% Adolescent Onset

Scoliosis − − 69.1 −

Mean Body Mass

Index (Sd) 27.5 (7.2)27.8 (5.3) 24.7 (3.6)10.85***

% Underweight 10.0 6.3 0

% Normal Weight 27.1 28.3 58.6

% Overweight 37.1 40.3 34.5

% Obese 25.7 25.1 6.9

26.5****

Marital: % Married 64.5 64.0 65.1 0.03

Race: % Caucasian 94.9 92.8 95.0 4.07

Education: % Some

College or Greater 80.0 82.4 92.6 7.42

% Currently Working45.1 42.9 43.9 18.6

% Worker’S Com-

pensation 0 0.44 0 11.2*

Smoking: % Current

Smokers 8.75 7.46 − 11.9†

Katz Comorbidity

Score Mean (Sd) 3.91 (3.69)3.28 (3.50) 5.00 (3.75)11.1***

% Depression

Comorbidity 32.1 22.9 20.3 3.9

Lifestyle Characteristics

Strength-building (sd)1.67 (0.85)1.80 (0.84) 2.03 (0.83)9.84*

Aerobic (sd) 1.72 (0.91)1.79 (0.89) 2.01 (0.83)15.8**

Yoga/Pilates (sd) 1.03 (0.23)1.11 (0.73) 2.59 (0.74)233.7***

Total (sd) 4.39 (1.59)4.68 (1.63) 6.63 (1.64)34.9****

Mean Travel

hours/day (sd) 1.40 (1.96)1.31 (1.01) 1.54 (1.23)1.29

Attitudinal Characteristics

Altruism Scale

Receive Support (sd)1.87 (0.84)1.96 (0.84) 2.07 (.67)0.09

Give Support (sd) 2.09 (.80)2.01 (.91) 1.84 (0.70)0.66

Overwhelm (sd) 0.78 (0.82)0.82 (0.80) 2.42 (1.1)90.02****

Helping Orientation

(sd) 4.64 (0.71)4.31 (1.1) 1.88 (1.2)102.76****

General Helping

Behaviors (sd) 2.04 (0.81)1.91 (0.92) 2.81 (1.0)36.00****

Altruism Total Score

(sd) 35.5 (8.0)34.7 (8.9) 39.2 (7.9)10.8**

a. † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001

C. E. SCHWARTZ ET AL.

124

Table 2. Outcome scores of the subsamples.

Cervical

(n = 80) Lumbar

(n = 228) Scoliosis

(n = 68)

F or X2

Statistic

Mean SF-36 Physi-

cal Component

Score (sd)

40.1

(11.2)

39.7

(11.9) − 0.32

Mean SF-36 Mental

Component Score

(sd)

45.2

(14.2)

46.1

(13.1) − 1.28

Mean SF-12 Physi-

cal Component

Score (sd)

− − 40.1

(11.2) −

Mean SF-12 Mental

Component Score

(sd)

− − 49.1

(11.7) −

Mean Scoliosis

Research Soci-

ety-22r Total Score

(sd)

− − 3.5

(0.8) −

Oswestry Disability

Index (sd) − 42.3

(16.8) --- 0.41

Neck Disability

Index (sd)

53.7

(19.0) − −

NRS Leg Pain (sd) 2.2

(2.6)

3.2

(3.06) − 6.99**

NRS Back Pain (sd) 3.0

(2.93)

3.8

(2.95) − 3.84*

PROMIS Pain

Impact Short-Form

T score (sd)

58.6

(10.5)

59.4

(10.3) − 0.54

Global Health (sd) 6.5

(2.1)

6.4

(2.1)

6.8

(2.0) 1.82

levels of received support.

Table 2 presents mean outcome scores by patient

group. There were similar scores on the RAND physical

and mental component scores, the ODI/NDI, the

PROMIS Pain Impact Score, and the Global Health item.

Patient responses to the NRS leg and back pain items

differed, with lumbar patients reporting higher levels of

both leg and back pain as compared to cervical patients.

Figure 1 summarizes the findings from the univariate

regressions examining explained variance in QOL out-

come by type of covariate. We found that adjusting for

whether the data were drawn from the pre-surgical vs.

post-surgical sample did not change the effect size for

the covariates of interest. Thus, the reported regression

models did not adjust for type of sample. Similar propor-

tions of variance were explained by demographic/me-

dical and behavioral covariates across groups, with half

of effect sizes being small in magnitude and 6% being

medium. Lumbar patients tended to have more small

effect sizes among behavioral covariates (51%) than

among medical/demographic covariates (37%) (z = –

1.29, p < 0.10). Similar patterns were found for both ge-

neric and disease-specific outcomes.

Figure 2 shows more detail in explained variance in

Figure 1. A comparison of variance explained by demo-

graphic versus behavioral characteristics. Summarizes the

findings from the univariate regressions examining vari-

ance in QOL outcomes by type of covariate. Similar pro-

portions of variance were explained by demographic/

medical and behavioral (lifestyle/attitudinal) covariates

across groups.

Figure 2. Number of small effect sizes by QOL outcome,

separately by diagnostic group. Key points are that generic

and disease-specific outcomes appeared to yield similar

numbers of statistically important effect sizes, although

there were more statistically important behavioral covari-

ates predicting MCS scores than any other QOL outcome.

Additionally, cervical patients generally had more effect

sizes across the QOL outcomes than other patient groups.

Figure 3. Relative importance of behavioral covariates to

QOL outcomes. All three types of behavioral covariates are

important across patient groups and, for cervical and lum-

bar patients, have similar relative importance for the cer-

vical and lumbar patients. For scoliosis patients, however,

altruism and exercise are more important than commuting

practice for explaining spine outcomes.

QOL outcomes by groups. For the sake of simplicity, the

number of small effect sizes is plotted, since these were

C. E. SCHWARTZ ET AL. 125

the most prevalent effect sizes detected. This figure

highlights several points. First, cervical patients gener-

ally had more effect sizes across the QOL outcomes than

other patient groups. Second, there appeared to be a lar-

ger number of statistically important behavioral covari-

ates predicting MCS scores than any other QOL outcome.

Third, generic and disease-specific outcomes appeared to

yield similar numbers of statistically important effect

sizes, with the above-noted exception of MCS. The dis-

ease-specific scoliosis measure appeared to have sub-

stantially more statistically important effect sizes among

behavioral covariates, suggesting that these factors are

particularly important for this patient population.

Figure 3 shows the proportion of QOL outcome meas-

ures for which each behavioral characteristic is statisti-

cally important. These pie charts suggest that all three

types of behavioral covariates are important across pa-

tient groups. Additionally, the three types of behavioral

covariates have similar relative importance for the cervi-

cal and lumbar patients, but for scoliosis patients, altru-

ism and exercise are more important than commuting

practice for explaining spine outcomes.

5. Discussion

This study suggests that in addition to considering

known demographic and medical factors related to pa-

tient outcome, spine surgery researchers should also con-

sider including measures of lifestyle and behavioral fac-

tors. Factors such as exercise practice, average daily

commute, and social connectedness were found to have

similar value in explaining condition-specific and ge-

neric outcome measures as those demographic and

medical covariates generally considered in spine out-

come research. In our heterogeneous spine patient sam-

ple, the effect sizes were generally small for the exam-

ined covariates. Nonetheless, such factors may have a

synergistic effect on treatment outcomes, such that ad-

justing for them increases the detected effect of clinical

interventions.

This study utilized a heterogeneous sample of people

with spinal disorders expressly as a first, exploratory

endeavor to evaluate the utility of such lifestyle and atti-

tudinal factors. To build on this preliminary work, future

research might evaluate the relationship between these

factors and patient outcomes, after adjusting for the de-

mographic and medical factors. It would be useful to

know, for example, whether the examined aspects of

exercise practice, commuting burden, and social con-

nectedness have a similar association with outcomes

across patient age, gender, co-morbidity, diagnosis, and

surgery subgroups. Engaging in a balanced regimen of

exercise (i.e., integrating aerobic, strengthening, and

stretching types of exercise) may reflect other important

patient factors, including socioeconomic status, amount

of leisure time, education level, and motivation. Com-

muting burden may also reflect other factors, such as

type of occupation (i.e., more or less amenable to tele-

commuting, professional occupation rather than laborer

or service occupation), education level, and income sta-

tus (i.e., longer commutes are often related to lower

rent/housing cost further from the urban center). Social

connectedness may play a more important role later in

the recovery process, and may be more relevant for

mental health outcomes rather than disability outcomes.

In past research in adults, such altruistic social interest

behaviors were associated with higher levels of mental

health [22], and lower mortality [23], and males and fe-

males seemed to have different aspects of well-being

associated with such behaviors [20].

The limitations of the present work include the rela-

tively small numbers of cervical and scoliosis patients

that prevent subgroup analyses, and the cross-sectional

design that prevents causal inference. These limitations

are offset by the strength lent by the heterogeneous re-

cruitment strategy. This strategy enhanced the gener-

alizability and statistical power to detect small effect

sizes.

Future research using the analytical approach exem-

plified above may predict poorer outcomes in specific

patient population subsets (such as those who are over-

weight, smoke, have limited social connectedness, and

have longer commutes). A pre-operative evaluation of

these factors might then alert the surgeon to delay or

avoid performing procedures on these patients to avoid

poor outcomes.

In conclusion, this study supports the importance of

including lifestyle and attitudinal factors in an evaluation

of spine surgery outcomes. Such factors should be con-

sidered relevant as covariates for adjusting in data analy-

sis, and possibly even as stratification or matching in

clinical trials. Further, such characteristics should be

addressed clinically before and after spine surgery, since

our findings suggest that they are relevant to QOL and

well-being. One might, for example, encourage the bal-

anced integration of exercise as soon as it is safe after

surgery to improve patient outcomes, both directly and

via reduced BMI. Encouraging the patient to consider

ways to reduce daily time spent in a car may also result

in better outcomes, both by reducing back pain symp-

toms and by freeing up time in the day for activities that

enhance fitness (i.e., exercise) and mood (e.g., social

connectedness activities).

6. Acknowledgements

Funding for this work was provided in part from the

C. E. SCHWARTZ ET AL.

126

Foundation for Orthopaedic Spine Research.

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