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| Journal of the New Zealand Medical Association,
17-December-2004, Vol 117 No 1207
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Obesity and health-related quality of life: results from a
weight loss trial
Cliona Ni Mhurchu, Derrick Bennett, Ray Lin, Maree Hackett,
Andrew Jull, Anthony Rodgers
Overweight and obesity are increasingly prevalent in
developed and developing countries1–3 and
are important contributors to cardiovascular
disease,4–6 type 2 diabetes
mellitus,7,8 and several common
cancers.9,10 Body mass index (BMI) is the
anthropometric measure that provides the most useful population-level indicator
of excess body weight, although because it is a generalised measure that does
not distinguish between weight associated with lean body mass and fat it is
possible that measures of central body fat such as waist circumference and
waist-hip ratio may be better predictors of certain diseases including diabetes.
The World Health Organisation (WHO) guidelines define a BMI
of 18.50 to 24.99 kg/m2 as normal and >25
kg/m2 as
overweight.11 Estimations of the burden of
disease attributable to excess weight indicate that high BMI is a leading cause
of loss of healthy life worldwide;12 and across
developed regions, high BMI has been estimated to account for approximately 7%
of all disability-adjusted life years (an integrated measure of population
health incorporating both fatal and non-fatal
outcomes),12 which places high BMI close behind
tobacco (12%), high blood pressure (11%), alcohol (9%), and high cholesterol
(8%) as a leading cause of loss of healthy life in these regions.
While the physical effects of excess body weight are well
recognised, less is known about the social and psychological effects. Evidence
suggests that overweight and obese individuals are subject to stigmatisation and
discrimination in various areas of life, including employment, education, and
healthcare;13,14 and they have an increased
incidence of depression.15
Health-related quality of life (HRQoL) refers to the
‘physical, psychological, and social domains of health, seen as distinct
areas that are influenced by a person’s experiences, beliefs, expectations
and perceptions’.16 Assessment of HRQoL
can be made using a variety of measures, the most widely used and evaluated of
which is the Short Form 36-question Health Survey
(SF-36),17 a generic measure based on ratings
made by individuals themselves.18 There is
evidence that people who are overweight or obese experience significant
impairment in quality of life,19 20 but no New
Zealand-specific data exist.
The objective of these analyses was to measure HRQoL in 250
overweight and obese New Zealand adults and compare findings with the New
Zealand population. In addition, the effects of weight loss on HRQoL were
evaluated.
MethodsStudy
participants—Individuals were participants in a randomised
controlled trial of the effect of the dietary supplement, chitosan, on body
weight.21 Study participants were recruited
using newspaper advertisements and all participants provided written informed
consent. Men and women aged over 18 years who wished to lose weight and had a
BMI of between 28 and 50 kg/m2 were included.
Exclusion criteria were current treatment with chitosan containing supplements;
current or recent treatment with weight loss medications; current or recent
attendance at a commercial weight loss clinic/programme; allergy to seafood;
pregnancy or lactation; active gastrointestinal disease or obesity surgery;
involvement in another clinical trial; and individuals judged to be unlikely to
comply with study treatment and follow-up procedures.
The study was conducted at the University of Auckland,
New Zealand, between November 2001 and December 2002. The study protocol and
related documents were approved by the Auckland Ethics Committee.
HRQoL—HRQoL
was measured using the Australasian standard version (version 1) of the SF-36
questionnaire,18 a generic measure of HRQoL
that assesses eight domains of perceived health over the previous 4 weeks. These
domains are: physical functioning (PF), role limitations related to physical
problems (RP), bodily pain (BP), general health (GH), vitality (VT), social
functioning (SF), role limitations related to emotional problems (RE), and
mental health (MH). These dimensions are ordered from first to last according to
the extent to which they measure physical or mental functioning.
Scores range from 0 (worst health state) to 100 (best
health state) for all domains. For example, a score of 100 indicates the
individual can perform all activities without limitations related to health. In
three domains (GH, VT, MH), scores of 50 indicate an absence of problems. To
obtain scores in excess of 50 in these three domains, health must be evaluated
positively. Two summary component scores can be calculated from the SF-36: the
physical component summary (PCS) score and the mental component summary (MCS)
score. Both scores have a mean of 50 and a standard deviation of 10 and are
standardised using means, standard deviations, and factor score coefficients
from the general New Zealand population scores. Scores below 50 represent scores
below the population mean.
HRQoL was measured at baseline and 6 months
post-randomisation in this study. All questionnaires were checked for errors or
missing data prior to data entry and standard guidelines for handling missing
data were applied.18
Statistical
analysis—Crude PCS and MCS scores were calculated using the New
Zealand-specific factor weights.22 Participants
were stratified by baseline BMI tertile (28-32 [n= 83], 32.1-37 [n=85], >37
kg/m2 [n=80]) to ensure equal numbers of
participants across all groups, and scores were compared across these groups
using analysis of variance (ANOVA).
Potential confounding factors such as age, gender,
ethnicity (European/Non-European), socioeconomic status (SES) (using the New
Zealand Socio-economic Index),23 comorbidities
(sum of doctor-diagnosed conditions including diabetes, hypertension,
hyperlipidaemia, coronary heart disease, stroke, hyperthyroidism,
hypothyroidism, gallbladder disease, osteoarthritis, back pain, sleep apnoea,
shortness of breath, asthma, cancer, depression, other), and any other
confounding factors discovered during stratified analyses, were controlled for
by including these factors as covariates in an analysis of covariance (ANCOVA)
model. Due to the small size of our study sample, comorbidities were not
weighted, and a crude classification was used for adjustment as has been used in
other similar studies.24,25
We assessed whether percentage weight change from
baseline to 6 months was associated with changes in summary scores using
multiple regression analysis after adjustment for age and other confounders (see
above). Analyses were based on an intention-to-treat (ITT) approach with the
last recorded observation carried forward (LOCF) for any missing data. In the
case of missing SF-36 domain scores, scores were assumed to have remained the
same as baseline scores—i.e. no change. In the case of missing weight
data, the last recorded weight was used, which may have been recorded at
baseline or at any of the subsequent 6 follow-up visits. A ‘completers
only’ analysis (limited to participants with complete data) was also
conducted as a sensitivity analysis. All statistical analyses were conducted
using SAS for Windows (version 8.0) or Microsoft Excel (version 9.0).
ResultsParticipant
characteristics—The 250 study participants had a mean (SD) age of
48 (12) years, 206 (82%) were female, and their mean BMI was 35.4 (5.3)
kg/m2 (Table 1).
Table 1. Characteristics of the study
participants
Seventy-four percent of participants classified themselves
as New Zealand European, and the remainder were Maori (12%), Pacific peoples
(3%), or other ethnicities (11%). Seventy percent had one or more comorbidities.
Younger age (p=0.01), female sex (p=0.04), low high-density lipoprotein (HDL)
cholesterol levels (p=0.003), and high systolic blood pressure (p=0.002) were
significantly associated with higher BMI tertile, but no significant
associations were seen with other potential confounders examined including SES,
ethnicity, smoking status, and comorbidities (although they were included as
covariates in the analyses).
HRQoL—Complete
SF-36 questionnaires were available for 248 (99%) participants at baseline and
156 (62%) at follow-up. The mean (SD) PCS score for participants was 47.2 (9.0)
and mean MCS score was 46.9 (11.1). Participants in the highest BMI tertile
reported significantly lower mean [SD] PCS scores (44.1 [10.3]) compared with
those in the middle (48.0 [7.5]) and lowest BMI tertiles (49.2 [8.3]) (p=0.01),
but no significant differences were seen in MCS scores across tertiles (p=0.65)
(Table 2).
Table 2. Effect of baseline body mass index on baseline
health related quality of life
Analyses adjusted for age,
gender, ethnicity (European/Non-European), socioeconomic status (using the
New Zealand Socio-economic
Index)23,
comorbidities, baseline systolic blood pressure, and baseline HDL-cholesterol
level.
Significantly lower PF scores (p = 0.004) were also reported
by those in the highest BMI tertile (69.6 [22.8]) compared with those in the
middle (81.2 [15.2]) and lowest (82.6 [17.2]) tertiles. There was a general
trend for people in the highest tertile to have lower scores for most domains
but differences were not statistically significant for domains other than PCS
score and PF domain (Table 2).
Comparison of standardised (for age and sex) mean SF-36
domain scores reported by study participants with the New Zealand population
norms revealed significantly lower mean scores in all domains except in the case
of MH (Figure 1). The largest differences were seen in the VT (16.2), BP (13.5),
and RP (12.3) domains, but substantial differences were also seen in the GH
(10.9), PF (9.7) and RE (9.1) domains, with more modest differences seen in the
SF (4.8) domain.
Figure 1. Standardised comparison of health related
quality of life reported by overweight and obese study participants with New
Zealand population norms
 PF=physical function; RP=role
limitations related to physical problems; BP=bodily pain; GH=general health;
VT=vitality; SF=social functioning; RE=role limitations related to emotional
problems; MH=mental health; Point estimates are standardised mean differences
and bars are 95% confidence intervals around the differences.
The effect of weight change from baseline to 6 months on the
PCS score was evaluated in an ITT analysis. Twenty-three participants lost more
than 5% of their baseline weight (mean=8.2%) over the 6-month study period, 95
lost less than 5% (mean=1.7%), while 123 did not change or gained weight
(mean=+1.7%).
After controlling for age, gender, ethnicity, SES,
comorbidities, baseline SF-36 scores, baseline SBP, and baseline
HDL-cholesterol, the effect of weight change on PCS was evaluated but no
significant effect across the three categories was seen (p=0.16). A sensitivity
analysis limited to participants with complete data (n=150) was also undertaken,
but no significant effect of weight change was seen in this analysis either
(p=0.43).
DiscussionThese results demonstrate that
overweight and obese New Zealand adults experience significantly impaired HRQoL
compared to the population norms, particularly in the vitality, bodily pain, and
role physical domains. Small reductions in body weight did not significantly
improve HRQoL in this substantially overweight population.
The strengths of this study include the large, well-defined
study population and the use of the SF-36 questionnaire to measure HRQoL. The
SF-36 is widely used,17 and norms (by age and
sex) have been produced for New Zealand and other populations allowing
international comparisons.
However, our study population may differ from overweight and
obese New Zealand adults generally because study participants were relatively
healthy and ambulant. Their HRQoL scores might be expected to reflect this and
perhaps be higher than those of overweight and obese New Zealanders in general.
However, it is equally possible that these trial participants may have been
particularly keen to lose weight, thus biasing the sample towards
dissatisfaction and lower HRQoL. In addition, the SF-36 (a generic measure) may
have failed to evaluate the impact that excess weight would have on
obesity-specific aspects of HRQoL. This might explain why no effect of BMI was
detected on MCS despite it being recognised that people who are overweight or
obese are more likely to suffer from
discrimination13 and
depression.15
An additional point to note is that a crude classification
(sum of comorbidities) similar to that used in other
studies24,25 was used to adjust for the effect
of comorbidities, but it is possible that there could be a differential impact
of comorbidities associated with pain (e.g. osteoarthritis) and those that are
asymptomatic (e.g. hypertension), although unfortunately it was beyond the scope
of this small study sample to weight individual comorbidities accordingly.
Finally, the New Zealand population norms for HRQoL are
based on data collected in 1996/7 and the indications are that the population
prevalence of overweight and obesity has increased since
then.26 This shifting baseline may have
influenced the comparison of HRQoL data collected in our weight loss study
(2001/2) with the population data (1996/7).
Mean PCS and MCS scores in this group of overweight and
obese adults were 47.2 (9.0) and 46.9 (11.1) respectively. Because the
standardised means of the summary scores are set at 50, these scores indicate
some impairment in both physical and mental domains. This places obesity in the
same category as chronic conditions such as visual impairments, cerebrovascular
and/or neurological conditions, cancer, and respiratory conditions, which have
also been found to have a negative impact on both summary
scores.27
Participants with BMI levels exceeding 32
kg/m2 also had significantly lower PCS scores
of approximately 5 points, when compared with those who had a BMI in the lowest
tertile (28–32 kg/m2). It is suggested
that a difference of 5 points in summary scores is clinically and socially
significant (John Ware, personal communication, 2001).
Age and sex standardised analyses demonstrated significant
differences in HRQoL domain scores between this group of overweight adults and
New Zealand population norms of up to 16 points, with differences being most
pronounced with respect to the vitality, bodily pain, and role physical domains.
It is uncertain what difference in domain scores is clinically significant, but
differences of 9–16 points (compared with population norms across most
domains) suggests impairment in HRQoL that is socially as well as statistically
significant.18
We found no significant association between reduction in
body weight and HRQoL. This finding is contrary to previous
studies,28,29 that found a linear relationship
between HRQoL and weight loss. There are two reasons why this discrepancy may
have occurred. Firstly, previous study participants on average lost
10%29 to 17%20
of their weight over a 1-year period, whereas only a minority (23) of our study
participants lost more than 5% body weight over the 6-month period.
Several studies have confirmed that there is a dose-response
effect of weight loss on HRQoL30,31 so it seems
likely that people who are very overweight and obese may need to lose in excess
of 10% of their body weight in order to experience a positive impact on HRQoL.
Secondly, previous studies28,29 used
obesity-specific measures of HRQoL, whereas we used a generic measure that may
be less sensitive to obesity specific issues.
It seems likely that differences in proportional weight loss
are most likely to account for discordance because Fontaine et al used the SF-36
questionnaire and found that weight loss was significantly associated with
higher scores relative to baseline on the PF, RP, GH, VT, and MH
domains.32 The participants in the study by
Fontaine et al also lost on average 10% of their body weight over the 13-week
treatment programme.
The prevalence of overweight and obesity is increasing
rapidly in New Zealand33 and the results of our
study confirm that obesity has a significant negative impact on HRQoL in
addition to the known increase in risk of disease and death, suggesting that the
psychosocial consequences of obesity should also be considered in the management
of obesity. However, our results also imply that small reductions in weight have
little impact on HRQoL in people who are substantially overweight, supporting
the urgent need for more effective interventions to prevent and treat overweight
and obesity in New Zealand.
Author information:
Cliona Ni Mhurchu, Senior Research Fellow; Derrick Bennett, Senior
Biostatistician; Ray Lin, Biostatistician; Maree Hackett, Research Fellow;
Andrew Jull, Research Fellow; Anthony Rodgers, Director, Clinical Trials
Research Unit, University of Auckland, Auckland
Acknowledgements:
The Health Research Council of New Zealand provided research funding, and two
authors (CNM and AR) held fellowships from the National Heart Foundation of New
Zealand during the period of research. We thank the staff at the Clinical Trials
Research Unit and the Human Nutrition Unit, University of Auckland, who assisted
with the conduct of the ECHO study; and we also thank the 250 study
participants.
Correspondence: Dr
Cliona Ni Mhurchu, Clinical Trials Research Unit, University of Auckland,
Private Bag 92019, Auckland. Fax: (09) 373 1710; email: c.nimhurchu@ctru.auckland.ac.nz
References:
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