ORIGINAL PAPER
Nagoya J. Med. Sci. 85. 79–92, 2023
doi:10.18999/nagjms.85.1.79

Validation of the abbreviated version of the World HealthOrganization Quality of Life in Mongolia: a population-based
cross-sectional study among adults in Ulaanbaatar
Enkhjin Bat-Erdene1,2, Enkhnaran Tumurbaatar1,2, Gantsetseg Tumur-Ochir3,
Otgonbold Jamiyandorj4, Tsolmon Jadamba2, Eiko Yamamoto5,
Nobuyuki Hamajima5, Takakazu Oka6 and Battuvshin Lkhagvasuren1,2,6
Brain Science Institute, Graduate School, Mongolian National University of Medical Sciences,
Ulaanbaatar, Mongolia
2Brain and Mind Research Institute, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia
3
Department of Mental Health, School of Medicine, Mongolian National University of Medical Sciences,
Ulaanbaatar, Mongolia
4
Department of Healthcare, Ulaanbaatar City Government, Ulaanbaatar, Mongolia
5
Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Japan
6
Department of Psychosomatic Medicine, International University of Health and Welfare Narita Hospital,
Narita, Japan
1

ABSTRACT
There is currently no validated tool to measure the quality of life (QOL) in the Mongolian language.
This study aimed to validate the Mongolian version of the World Health Organization Quality of Life – Brief(WHOQOL-BREF) questionnaire for the general population of Mongolia. The subjects were 301 adults aged
18–65 years selected randomly by a computer from 30 centers in 8 districts of Ulaanbaatar, Mongolia,
in 2020. Reliability was measured using Cronbach’s α and intraclass correlation coefficients. Convergent,
discriminant, and construct validities were examined using exploratory and confirmatory factor analyses
for a four-domain factor structure. Among the participants, 56.1% were women, 32.9% held a bachelor’s
degree or higher, 48.8% were employed, and 61.8% were married. The overall Cronbach’s α coefficientof the WHOQOL-BREF questionnaire was 0.804. Correlations between the component scores of the
WHOQOL-BREF ranged from 0.581–0.822. All items showed higher item-total correlations with theircorresponding domains than with other domains, except the mobility item from the physical domain.
Discriminative validity was evident in physical and psychological domains. Exploratory and confirmatory
factor analyses revealed a four-factorial structure consisting of 24 items that provided an acceptable fit
to the data (RMSEA=0.084; CFI=0.860). In conclusion, the Mongolian version of the WHOQOL-BREF
demonstrated evidence of good reliability and validity for assessing QOL in the general population ofMongolia. These findings indicate that it allows the comparison of QOL of adults in Mongolia with thosein other countries.
Keywords: quality of life, WHOQOL-BREF, validation study, population-based, Mongolia
Abbreviations:
EFA: exploratory factor analysis
QOL: quality of life

Received: January 5, 2022; accepted: March 30, 2022
Corresponding Author: Battuvshin Lkhagvasuren, MD, PhD
Brain Science Institute, Graduate School, Mongolian National University of Medical Sciences,
Zorig Street 3, Ulaanbaatar 14210, Mongolia
Tel: +976-99192738, E-mail: battuvshin@mnums.edu.mn
79Enkhjin Bat-Erdene et al

WHO: World Health Organization
WHOQOL-BREF: World Health Organization Quality of Life – Brief
This is an Open Access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
License. To view the details of this license, please visit (http://creativecommons.org/licenses/by-nc-nd/4.0/).

INTRODUCTION
The burden of disease has been changing globally over the past few decades. The incidenceof non-communicable chronic diseases has increased in the last 30 years, influencing economic
and healthcare conditions in many countries.1 In Mongolia, the disease burden has shifted from
communicable diseases to non-communicable diseases. According to reports from the Institutefor Health Metrics and Evaluation at the University of Washington, the share of the global
burdens for non-communicable diseases, including mental and neurological disorders, increasedby 19.8% between 1990 and 2017, whereas that for communicable diseases including diarrhea
and neonatal infectious diseases decreased by 34.2% during the corresponding period.2 To meetthe shift in disease burden, Mongolia has to establish appropriate policies to improve the efficacyof healthcare services by monitoring the quality of life (QOL) nationwide. This rapid shift indisease burden may be more influential for younger people in developing countries including
Mongolia, than for those in developed countries.3
To evaluate the effectiveness of preventive, diagnostic, and treatment measures, the usage ofa QOL assessment instrument is generally recommended.4 An important requirement for this is
the establishment of its validity and reliability in the target population. Several generic QOL assessment instruments that have been examined in terms of validity and reliability across different
cultures, such as the Short-Form Health Survey (SF-36), EuroQOL (EQ-5D), and World HealthOrganization Quality of Life (WHOQOL-100). Among them, WHOQOL-100 was developed by
WHO experts by the simultaneous consideration of the context of the cultural aspects in 15
international field centers. Its abbreviated version, WHOQOL-BREF, is a concise self-reportquestionnaire that assesses health-related QOL both in general and clinical populations. It consistsof 24 Likert scale items that represent four latent domains: physical health, psychological health,social relationship, and environmental health. There are two additional exclusive questions fromthe measurement model, which estimate the subject’s satisfaction with their life and general
health. WHOQOL-BREF has been translated into more than 100 languages including Mongolian
over 20 years.5 Concerning the Mongolian version, the evaluation has not been well documented
to date. The source of the translation is not indicated, and the WHO claims no responsibility forthe translation’s content or accuracy. Furthermore, it contains several misleading interpretationsof the content of the original English version. Therefore, there was an urgent need to translate
the WHOQOL-BREF into Mongolian based on the guidelines of cross-cultural adaptation.
Of note, no studies have assessed the QOL of the general Mongolian population. In particular,
the political transition from communism to democracy, rapid urbanization, air pollution, changes
in lifestyle, the shift in disease burden, and economic turbulence over the past three decades
should have largely impacted the QOL of Mongolian people. Including but not limited to thesefactors, the subjective perception of QOL among Mongolian people may deviate from international
standards. However, before establishing the normative data of the Mongolian people, it is mandatory to determine the psychometric properties of the Mongolian version of the WHOQOL-BREF
to ensure its validity and reliability. In other countries, the instrument’s validity and reliability
are satisfactory and appropriate for both general and clinical populations, although the poor
reliability of a single domain has been reported in some countries.6,7This study aimed to evaluate the psychometric properties of the Mongolian version of the
Nagoya J. Med. Sci. 85. 79–92, 2023

80

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

WHOLQOL-BREF in a general population derived from a population-based cohort study inMongolian. Confirmation of the validity of the WHOQOL-BREF in the general population could
further promote the usage of QOL as an indicator in healthcare services and clinical research.
With instrumental validation, it will be possible to establish the normative data for the Mongolian
population for cross-cultural studies.

MATERIALS AND METHODS
Study population
This study was part of a nationwide multicenter, interdisciplinary, prospective, population-based
cohort study that investigated brain-related disorders in the general population of Mongolia by
the Brain Science Institute at the Mongolian National University of Medical Sciences. According
to the latest United Nations data, Mongolia’s population was estimated as 3,358,000, of which
1,597,000 individuals lived in Ulaanbaatar, the capital city, and the remaining lived in 4 rural
regions. The cohort was derived from 64 sampling centers, including 30 primary health centersof 8 districts in Ulaanbaatar and 34 primary health centers of 4 rural regions in Mongolia.
Primary health centers provide healthcare services to all individuals within specific geopoliticalunits, where the entire population is registered by name, age, sex, education, employment, andhousehold income.
In this cross-sectional study, the sampling size was calculated to be 385 using a confidence
level (CI) of 95%, margin of error of 5%, design effect of 1.50, and population size of 1,024,000
individuals aged older than 18 years in Ulaanbaatar. To select a representative sample thatmatches age and sex distribution of the population of Ulaanbaatar, we created 6 age-sex groups
as follows: 18–39 years (52.3%), 40–59 years (36.3%), ≥60 years (11.4%) for men (46.1%) andwomen (53.9%). Considering a response rate of 60%, 616 individuals were invited to participate
in the survey. The participants were randomly sampled using a computer program (randbetween
function of Excel). Depending on the population density, 3 or 4 individuals for each age-sex
group from 30 sampling centers of the 8 districts of Ulaanbaatar out of 9 districts were selected.
The uninvolved district, Bagakhangai, has a small population and is located geographicallyapart from other districts. Mongolian citizens who lived in the units for at least 6 months wereconsidered to meet inclusion criteria. Among the invited individuals, 297 did not come up at
the sampling center. A total of 319 participants were approached to complete the validity study,and 18 of those approached either refused to take the study or had missing data. The remaining
301 participants were included in the final analysis.
Written informed consent was obtained from all participants. The Institutional Review Board
and Ethics Committee of the Mongolian National University of Medical Sciences (MNUMS)
approved the study protocol and procedures for obtaining informed consent (number: 2020/03-05).
Data collection
The data collection started on September 7 and the preliminary dataset was extracted on
October 25, 2020. The study was conducted in the official language (Mongolian). All participants
completed paper questionnaires addressing their demographics and WHOQOL-BREF questionnaire. A total of 154 participants completed the WHOQOL-BREF questionnaire again within
2 weeks of the initial administration to assess test-retest reliability. All field study members
completed a data collection training program prior to the study.

Nagoya J. Med. Sci. 85. 79–92, 2023

81

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

Measures
The WHOQOL-BREF, one of the most commonly used generic QOL questionnaires, wasdeveloped by the WHOQOL group in 1996.5 The WHOQOL-BREF is open-source and accessible for non-commercial use, and has been translated into more than 40 different languages. It
is suitable for large sample surveys and clinical trials. It contains one item from each of the
24 facets from the WHOQOL-100, the original version of the questionnaire. Two more single
items on the overall perception of the QOL and general health were added in this study. This
questionnaire determines QOL with four domain scores: physical, psychological, social relationship and, environmental QOL. Each item is measured on a five-point Likert scale. The scoreof each domain consists of a mean score of items multiplied by four, in which a higher scoreindicates a better QOL of that aspect. It converts each domain score to a 0–100 scale.
We translated the WHOQOL-BREF into Mongolian based on the guidelines of cross-cultural
adaptation via the following steps: initial translation of the items into Mongolian was performed
independently by three translators (one holding a PhD degree in medicine, another holding a
PhD degree in neuroscience), and the translation was combined into one version with focus on
sentence structure, word choice, and best fit to the original version.8 A subsequent pilot test
examined the understanding of items, the ability to answer, and the meaningfulness of the scale
as a whole. Back-translation was performed independently by two translators unfamiliar with theoriginal WHOQOL-BREF and revealed no meaningful disagreement with the original version.
Finally, the expert committee re-evaluated item translation based on the pilot test and reviewed
the back-translation process before administering the Mongolian version of WHOQOL-BREF to
study participants.
Statistical analysis
The normality of the data was evaluated using the Kolmogorov-Smirnoff test. Differencesin continuous or categorical variables were tested by the Mann-Whitney or Kruskal-Wallis test
as appropriate. The reliability of the questionnaire was assessed for internal consistency using
Cronbach’s α (good, ≥0.8; acceptable, ≥0.7; marginally acceptable, ≥0.6) and for external reliability using the intraclass correlation coefficient (ICC). A test-retest procedure was performed
at a 2-week interval. ICC values of <0.5, <0.75, <0.9, and >0.9 were considered to have poor,
moderate, good, and excellent test-retest reliability, respectively, according to Koo et al.9
Further, questionnaire validity was evaluated by exploratory factor analysis (EFA) using
principal component analysis with equamax rotation and confirmatory factor analysis (CFA)
to supplement EFA. Factor analysis suitability was examined by the Bartlett test of sphericity(p<0.001) and Kaiser-Meye-Olkin (KMO) test of sampling adequacy (p>0.65), followed bydetermining the number of relevant factors via eigenvalue analysis.10 The factors with eigenvalues>1 was assumed to be meaningful and retained for rotation. A threshold factor loading of 0.4
was chosen as a good indicator of sample-to-population pattern fit. The CFA was carried out
for the Mongolian version of the WHOQOL-BREF using AMOS statistical software (Amos
26; SPSS Inc). The overall model fit was assessed using the chi-square test, and alternative fit
indices with the following cut-offs for acceptable fit as follows: <0.08 for the root mean squared
error of approximation (RMSEA), ≥0.8 for the comparative fit index (CFI), and ≥0.40 for thefactor loading.11
A receiver operating characteristic (ROC) curve and area under curve (AUC) with a 95% CI
were constructed to evaluate the diagnostic capacity of different cut-off points for the QOL in
all domains to predict good QOL or poor QOL for each participant. We adopted the statisticalanalysis described in a previous study.12 Briefly, the single questions including perception of
QOL and perception of general health, were used to establish good QOL/general health andNagoya J. Med. Sci. 85. 79–92, 2023

82

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

poor QOL/general health. We used a cut-off point of 60 for the overall perception of QOL tocreate an ROC curve and the best cut-off point for each domain. Statistical significance was set
at p<0.05, and all tests were two-tailed. Data are presented as means ± standard deviation with
95% CI. Data were analyzed using SPSS v26.0.
Ethics approval and consent to participate
All procedures performed in this study were done so in accordance with the ethical standardsof the institutional and/or national research committee and the 1964 Helsinki Declaration and its
later amendments. The design and methods were reviewed and approved by the ethics committee
at the Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia (number:
MNUMS 20/03-05). This study was not a trial and did not require registration. Written informed
consent was obtained from all participants.

RESULTS
Demographic characteristics
This study comprised 301 participants aged 18–65 years with a mean age and standard deviationof 40.1±15.5 years. Among them, 56.1% were women, 32.9% held a bachelor’s degree or higher,
48.8% were employed, and 61.8% were married. The mean age and sex were relatively close
to the general population of Ulaanbaatar: 56.1% of the study subjects vs. 53.9% of the general
population for women; 45.8% for 18–39 years, 41.2% for 40–59 years, and 13.0% for 60 years
or older in the study subjects vs 52.3%, 36.3%, and 11.4% in the general population, respectively.
Table 1

Demographic characteristics of the study subjects (n=301)

Characteristics

Total (%)

Male (%)

Female (%)

Number301 (100)132 (100)

169 (100)Age (years)

Mean±SD40.1±15.5

39.6±15.440.5±15.6

Age-group

18–39

138 (45.8)

61 (46.2)

77 (45.6)

40–59

124 (41.2)

56 (42.4)

68 (40.2)

Marital status

Education

Employment≥60

39 (13.0)

15 (11.4)

24 (14.2)

Married186 (61.8)

83 (62.9)

103 (60.9)

Never-married74 (24.6)

37 (28.0)

37 (21.9)

Others*41 (13.6)

12 (9.1)

29 (17.2)≤ Middle school

130 (43.2)

63 (47.7)

67 (39.6)

Associate’s degree

72 (23.9)25 (18.9)47 (27.8)

Bachelor’s degree

85 (28.2)

36 (27.3)

49 (29.0)≥ Master’s degree

14 (4.7)

8 (6.1)6 (3.6)Student

43 (14.3)

20 (15.2)

23 (13.6)

Pensioner

70 (23.3)

26 (19.7)

44 (26.0)

Unemployed41 (13.6)

12 (9.1)

29 (17.2)

Employed

147 (48.8)

74 (56.1)

73 (43.2)

SD: standard deviation*re-married, co-habiting, separated, divorced, and widowed.
Nagoya J. Med. Sci. 85. 79–92, 2023

83

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

Table 2

Cronbach’s α of the Mongolian version of WHOQOL-BREF (n=301)

Mean ± standard
deviation

Corrected item-total
correlation

Cronbach’s α

Perception on quality of life

3.9±0.8

0.626

0.920

Perception on general health

3.7±0.9

0.581

0.921

Domain 1: Physical*

60.9±17.1

0.666

0.871

Domain 2: Psychological*

73.1±16.1

0.810

0.816

Domain 3: Social*

69.9±17.7

0.662

0.874

Domain 4: Environment*

68.9±16.1

0.822

0.811

Components

WHOQOL-BREF (overall)

0.804*Score ranges from 0 to 100
Table 3Intraclass correlation coefficients (ICC) of the Mongolian version of WHOQOL-BREF (n=154)

Domains

Mean ± standard deviation
Test

RetestICC

Perception on quality of life

3.8±0.8

3.9±0.7

0.602

Perception on general health3.7±1.0

3.8±0.9

0.723

Domain 1: Physical61.4±13.555.1±13.4

0.356

Domain 2: Psychological63.5±17.2

66.3±14.9

0.669

Domain 3: Social

63.6±21.2

64.3±20.8

0.674

Domain 4: Environment63.5±15.3

63.9±15.4

0.722

As presented in Table 1, there were no significant differences in mean age, age group, marital
status, education, and employment (p=0.629, 0.731, 0.413, 0.507, and 0.140, respectively).
Reliability
Item analyses included inspecting means, medians, standard deviations, item-to-total correlations, and Cronbach’s α to determine internal consistency (Table 2).
The Cronbach’s α coefficients of the Mongolian version of the WHOQOL-BREF questionnaire
were as follows: perception on quality of life, 0.920; perception on general health, 0.921; physicaldomain, 0.871; psychological domain, 0.816; social relationship domain, 0.874; and environmental
domain, 0.811. The overall Cronbach’s α coefficient of the WHOQOL-BREF questionnaire was
0.804. The component scores were significantly correlated with the WHOQOL-BREF score,
which was 0.581–0.822.
ICC was calculated using a two-factor mixed-effects model with a 95% CI to determine
external reliability (Table 3).
A total of 154 participants completed the WHOQOL-BREF questionnaire within 2 weeks
of initial administration to assess test-retest reliability. Results from ICC analyses showed thatthe overall result of the domains was 0.602–0.723, which indicates moderate reliability, but thephysical domain (0.356) showed poor reliability.
Validity
EFA using the equamax rotation and maximum likelihood extraction method for 24 items ofdata identified five components with eigenvalue greater than 1, as presented by the scree plot
Nagoya J. Med. Sci. 85. 79–92, 2023

84

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

Fig. 1

Scree plot for 24 items of the Mongolian version of WHOQOL-BREF (n=301)

Table 4

Exploratory factor analysis of the Mongolian version of WHOQOL-BREF (n=301)

Components
Question 3: Pain

Factor loadings
Factor 1

Factor 2

Factor 3

Factor 4

0.074

0.099

0.047

0.874

Question 4: Medication

0.013

0.012

0.066

0.884

Question 5: Positive

0.575

0.394

0.280

0.173

Question 6: Spiritual

0.649

0.208

0.363

0.159

Question 7: Think

0.517

0.332

0.146

0.295

Question 8: Safety

0.484

0.439

0.302

0.190

Question 9: Environment

0.405

0.417

0.314

0.157

Question 10: Energy

0.327

0.603

0.268

0.359

Question 11: Body

0.580

0.199

0.297

0.231

Question 12: Finance

0.254

0.630

0.380

0.092

Question 13: Information

0.274

0.614

0.433

0.018

Question 14: Leisure

0.188

0.540

0.473

0.143

Question 15: Mobility–0.500

0.229

0.294

–0.243

Question 16: Sleep

0.184

0.521

0.305

0.418

Question 17: Activity

0.421

0.458

0.456

0.254

Question 18: Work

0.458

0.319

0.422

0.212

Question 19: Esteem

0.555

0.174

0.518

0.225

Question 20: Relationship

0.663

0.199

0.390

0.152

Question 21: Sex

0.473

0.370

–0.0740.001

Question 22: Support

0.080

0.344

0.521

–0.011

Question 23: Home

0.587

0.319

0.478

0.139

Question 24: Service

0.027

0.166

0.717

0.247

Question 25: Transport

0.210–0.089

0.669

0.164

Question 26: Negative

0.013

0.703

–0.137

0.271

Nagoya J. Med. Sci. 85. 79–92, 2023

85

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

in Fig. 1.
Meanwhile, the results of EFA indicated a four-factor solution (Table 4). Items with factor
loadings ≥0.40 on the dimensions were retained, as well as Question 15 “Mobility” (0.294) offactor 4 to keep the high Cronbach’s α. Together, these factors accounted for 41.2% of the total

Fig. 2

Confirmatory factor analysis for the four domains of the Mongolian versionof WHOQOL-BREF (n=301)

Nagoya J. Med. Sci. 85. 79–92, 2023

86

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

variance. KMO and Bartletts test results were 0.91 and p<0.001, respectively. The WHOQOLBREF was invariant across sex, education level, and marital status. However, scalar invariancecould not be established for age and employment in the physical health domain. RMSEA was
0.08, and CFI was 0.86 for the overall model fit.
We applied a four-dimensional measurement model to evaluate how well the four domains
were combined to identify the underlying latent construct of QOL. Figure 2 presents the factor
correlations and loading of the Mongolian version of the WHOQOL-BREF.
The arrows in Fig. 2 are the factor loadings, representing direct effects of the indicatorson the latent QOL. The value ranged from 0.33–0.90 for the correlation coefficients between
the domains and from 0.77–0.92 for the standardized regression weights. The squared multiple
correlations were 0.59–0.85, whereas the measurement errors were represented from e1 to e24.
The ROC curve in Fig. 3 describes the sensitivity and specificity of the four domains in thisstudy to predict QOL.
AUC value for Domain 1 (physical) to Domain 4 (environmental) was 0.765 (95%CI,
0.590-0.940), 0.814 (95%CI, 0.642–0.986), 0.781 (95%CI, 0.598–0.964), and 0.785 (95%CI,
0.621–0.950), respectively. The cut-off points were 48, 60, 54, and 54, yielding a sensitivity of>80% (81.0%, 83.1%, 83.1%, and 82.8%) and a specificity >60% (81.8%, 81.8%, 72.7%, and63.6%), respectively.
To determine convergent validity, we analyzed the correlation of each item with its corresponding domain (corrected item-total correlations) and inter-item correlations between thedomains (Table 5).
We expected each item to be more strongly correlated (r≥0.4) with its corresponding domain
than with the other domains. In line with this, no items correlated more strongly with anotherdomain than with its corresponding domain. However, the mobility item from the physicaldomain was the only item that showed a weak correlation with the corresponding domain (r<0.4).
Therefore, 23 out of 24 items (95.8%) met the criterion for item convergence. These results

Fig. 3

Receiver operating characteristic curves of the Mongolian version of WHOQOL-BREF
according to domain (n=301)

Nagoya J. Med. Sci. 85. 79–92, 2023

87

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

Table 5

Convergent validity of the Mongolian version of WHOQOL-BREF (n=301)

Domains, rItems / Domains
Item convergence(r ≥ 0.4)

Physical

Psychological

SocialEnvironment

6/7

6/6

3/3

8/8

Corrected item-total correlations
Domain 1: Physical health
Q3 PainQ4 Medication
Q10 Energy
Q15 Mobility
Q16 Sleep
Q17 Activity
Q18 Work

0.707***
0.673***
0.742***
0.133*
0.761***
0.723***
0.635***

0.362***
0.327***
0.687***– 0.126*
0.549***
0.640***
0.617***

0.236***
0.105
0.472***– 0.1100.480***
0.619***
0.506***

0.282***
0.241***
0.675***– 0.0110.575***
0.720***
0.617***

0.549***
0.464***
0.487***
0.449***
0.545***
0.348***

0.764***
0.755***
0.700***
0.766***
0.751***
0.558***

0.480***
0.513***
0.403***
0.448***
0.633***
0.300***

0.636***
0.640***
0.567***
0.557***
0.651***
0.363***

0.491***
0.251***
0.325***

0.664***
0.407***
0.360***

0.724***
0.699***
0.732***

0.628***
0.347***
0.490***

0.532***
0.455***
0.503***
0.480***
0.532***
0.538***
0.429***
0.309***

0.653***
0.558***
0.604***
0.610***
0.594***
0.711***
0.442***
0.360***

0.468***
0.457***
0.511***
0.567***
0.459***
0.648***
0.369***
0.329***

0.729***
0.723***
0.777***
0.767***
0.736***
0.771***
0.661***
0.590***    1
0.664***

1

Domain 2: Psychological health
Q5 Positive
Q6 Spirit
Q7 Think
Q11 Body
Q19 Esteem
Q26 Negative
Domain 3: Social relationship
Q20 Relationship
Q21 Sex
Q22 Support
Domain 4: Environmental health
Q8 Safety
Q9 Environment
Q12 FinanceQ13 Information
Q14 Leisure
Q23 Home
Q24 Service
Q25 Transport

Inter-item correlations for domains
Physical domain
Psychological domain
Social domain
Environment domain    10.659***
0.479***
0.657***    1
0.640***
0.787****p<0.05***p<0.001
p-values were calculated using Pearson’s correlations.

Nagoya J. Med. Sci. 85. 79–92, 2023

88

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

Table 6

Associations of domains with the general facet items (n=301)

General facet

Domains, standardized Beta (r)Physical

Psychological

SocialEnvironment

R2

Perception on quality of life

0.101
(0.487)0.351***(0.606)0.046(0.452)0.202*(0.575)0.398

Perception on general health0.399***(0.568)0.131(0.497)0.066(0.392)0.077(0.487)

0.355

Both perceptions

0.303***(0.619)0.273***(0.640)0.066(0.491)0.158*(0.616)0.492*p<0.05***p<0.001
p-values were analyzed using multiple linear regressions.

Table 7Discriminant validity of the Mongolian version of WHOQOL-BREF (n=286)

Relation with illness

Domain scores (mean ± SD)
Physical

Psychological

SocialEnvironment

Healthy participants (n=165)

63.20±16.47

74.92±14.87

70.15±16.99

69.60±14.96

Ill participants (n=121)

56.08±16.26

69.93±16.53

69.21±17.77

66.27±16.47

t-value

3.632

2.671

0.452

1.243

p-value<0.001

0.008

0.652

0.215

p-values were analyzed with Student-t test.

support the existence of a four-domain structure.
An additional method (face validity) was adopted to provide further support for the instrument’s construct validity. According to the WHOQOL group, all domains should have strong andsignificant associations with the general facet items: perception on QOL, perception on general
health, and the combined variable.6 Using a multiple linear regression for each general facet
item, we analyzed their correlations (r) and associations (standardized β) with all four domains(Table 6).
Perception on QOL and the combined variable were strongly associated with all four domains,which explained 39.8% and 49.2% of their variances, respectively. Perception of general healthwas predicted only by the physical and psychological domains.
To determine discriminant validity, we compared the domain scores between healthy and illparticipants using an independent samples t-test (Table 7).
The results revealed that discriminant validity was significant in the physical and psychologicaldomains of the tested questionnaire. The ability of the other domains to discriminate between
ill and healthy participants was insufficient.

DISCUSSION
The study suggested that the Mongolian version of the WHOQOL-BREF showed good validity
and reliability for measuring QOL in Mongolian general populations. The results indicated that
the Mongolian version of WHOQOL had good internal consistency and moderate test-retest
Nagoya J. Med. Sci. 85. 79–92, 2023

89

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

reliability (external reliability), although a single domain was poor. Previous validation studies
for general populations reported that Cronbach’s α were marginally acceptable for some domains.
For example, the WHOQOL group reported good values for Cronbach’s α for the physical(0.82), psychological (0.81), and environmental domains (0.80), but a marginal value for thesocial relationship domain (0.68), based on results from 24 sampling centers across the world.6
Another validation study in Bangladesh reported relatively low values (0.57–0.69) for the social
relationship and environmental domains.13 Similarly, the Cronbach’s α for the social relationshipdomain was only marginally acceptable in studies conducted in Iran and Japan.14,15 In contrast,
in a China study, the physical domain (0.67) was marginal, whereas the psychological (0.76),
social (0.72), and environmental domains (0.78), were acceptable.16 Compared with these studies’
results, our results showed a high level of reliability (≥0.8) in terms of internal consistency.
However, the test-retest reliability of the physical domain was relatively weak, whereas that of theother domains were strong. The weak correlation in the test-retest was lower than the reliability
results of the WHOQOL group, but similar to a previous report from the general population in
Bangladesh.6,13 The correlation variation could be because of the mobility item that showed avery weak corrected item-total correlation with the physical domain in our study. Future studies
should address this issue by carefully redesigning the items.
Convergent, discriminative, and construct validities were assessed. The results showed that allitems had higher item-total correlations with their corresponding domains than with other domains,except for the mobility item from the physical domain. Discriminative validity was evident for thephysical and psychological domains, whereas there was no discrimination capacity in the socialand environmental domains. Healthy participants reported better QOL scores than ill participantsin the physical and psychological domains, but not in the social and environmental domains.
This finding is congruent with that of WHOQOL studies in Italy, Norway, Spain, and the UK.6
However, the status of participants, whether they were healthy or ill, as defined by self-report
was not confirmed by health professionals using any diagnostic manual. All participants wereconsidered to have non-patient status because of limited resources. Future studies should use afully structured design and protocol to differentiate the sample populations based on physicaland mental diseases.
Furthermore, CFA of the Mongolian version of the WHOQOL-BREF resulted in a four-factor
structure, same as the original factorial structure of the instrument and supported the use of the
instrument in diverse populations.6,17 The EFA suggested that a four-domain model was appropriate
and potentially equivalent in terms of factor loadings and factor correlations among the study
population, although a single question was not fit. The reason for the low component loadingson that question might be due to variations in culture and demographics. Our results displayedhigh loadings across several domains, indicating that QOL may be better represented by a single
dimension. However, it suggested that one-dimensional factor structure had a rather acceptable
fit to data in the clinical population than the general population.18 Moreover, using the cut-off
criteria to estimate the prevalence of QOL, we found that the cut-of-points were set at relatively
low levels compared to previous studies.16
The main limitations of this study were: (1) as the participants were recruited from only thecapital city, the population surveyed did not represent the entire Mongolian population; (2) asa cross-sectional study, it did not provide information regarding the persistence of QOL overtime; and (3) although convergent, discriminant, and construct validities were assessed, this study
did not examine the incremental and criterion validity. Despite these limitations, this is the firststudy to evaluate the psychometric properties of the WHOQOL-BREF in the Mongolian language
within the general population. To improve the validity of the instrument, future studies should
compare the WHOQOL-BREF scores with other relevant measures. To further assess sensitivity
Nagoya J. Med. Sci. 85. 79–92, 2023

90

doi:10.18999/nagjms.85.1.79

Mongolian version of WHOQOL-BREF

and specificity of the instrument, the assessment needs to be conducted in both population-based
and hospital-based settings using a longitudinal design.
Hence, this study validated the WHOQOL-BREF in Mongolia, and provided an assessmentof the tool’s advantages and disadvantages for future work on QOL both in clinical and general
populations. The current research supported the convergent, discriminant, and construct validitiesof the Mongolian version of the WHOQOL-BREF by providing evidence of acceptable internalconsistency, external reliability, and four-factor structure. In conclusion, this study suggested that
the Mongolian version of the WHOQOL-BREF is a valid and reliable instrument for determining
QOL in the general population of Mongolia.

AUTHOR CONTRIBUTIONS
BL conceived and designed the study; EB, ET, GT, TJ, and BL performed and collected
data; EB, GT, and BL analyzed the data; OJ and TJ contributed materials; EY, OT, NH, andBL reviewed and edited the paper; EB, NH, and BL wrote the paper.

AVAILABILITY OF DATA AND MATERIALSThe data are available in the Brain Science Institute at the Mongolian National University of
Medical Sciences, Ulaanbaatar, Mongolia, and can be obtained upon request.
Data can be accessed by contacting:Director, Brain Science Institute+976-70161717
Zorig Street 3, Ulaanbaatar 14210, Mongolia

ACKNOWLEDGMENTS
We greatly appreciate those who participated in our study and 30 sampling center coordinators
who supported collecting study data from Ulaanbaatar City.

CONFLICT OF INTEREST
The authors declare no conflict of interest.

FUNDING
This study was supported by the International Brain Research Organization RHF-2014 to BL.

REFERENCES
1

2

GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries
and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet.
2020;396(10258):1204–1222. doi:10.1016/S0140-6736(20)30925-9.
Roser MR, Hannah. Burden of Disease 2016. https://ourworldindata.org/burden-of-disease. Published 2016.

Nagoya J. Med. Sci. 85. 79–92, 2023

91

doi:10.18999/nagjms.85.1.79

Enkhjin Bat-Erdene et al

3

4
5

6

7

8

9
10
11
12

13

14

15
16

17

18

Accessed September 28, 2020.
Bollyky TJ, Templin T, Cohen M, Dieleman JL. Lower-income countries that face the most rapid shift innoncommunicable disease burden are also the least prepared. Health Aff (Millwood). 2017;36(11):1866–1875.
doi:10.1377/hlthaff.2017.0708.
Basch E. New frontiers in patient-reported outcomes: adverse event reporting, comparative effectiveness,and quality assessment. Annu Rev Med. 2014;65:307–317. doi:10.1146/annurev-med-010713-141500.
The Whoqol Group. The World Health Organization Quality of Life Assessment (WHOQOL): development and general psychometric properties. Soc Sci Med. 1998;46(12):1569–1585. doi:10.1016/s02779536(98)00009-4.
Skevington SM, Lotfy M, O’Connell KA, WHOQOL Group. The World Health Organization’s WHOQOLBREF quality of life assessment: psychometric properties and results of the international field trial. A reportfrom the WHOQOL group. Qual Life Res. 2004;13(2):299–310. doi:10.1023/B:QURE.0000018486.91360.00.
Taylor WJ, Myers J, Simpson RT, McPherson KM, Weatherall M. Quality of life of people with rheumatoid
arthritis as measured by the World Health Organization Quality of Life Instrument, short form (WHOQOLBREF): score distributions and psychometric properties. Arthritis Rheum. 2004;51(3):350–357. doi:10.1002/
art.20398.
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptationof self-report measures. Spine (Phila Pa 1976). 2000;25(24):3186–3191. doi:10.1097/00007632-20001215000014.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability
research. J Chiropr Med. 2016;15(2):155–163. doi:10.1016/j.jcm.2016.02.012.
Cattell RB. The scree test for the number of factors. Multivariate Behav Res. 1966;1(2):245–276.
doi:10.1207/s15327906mbr0102_10.
Brown TA. Confirmatory factor analysis of the Penn State Worry Questionnaire: multiple factors or method
effects? Behav Res Ther. 2003;41(12):1411–1426. doi:10.1016/s0005-7967(03)00059-7.
Silva PA, Soares SM, Santos JF, Silva LB. Cut-off point for WHOQOL-bref as a measure of quality oflife of older adults[in English, Portuguese]. Rev Saude Publica. 2014;48(3):390–397. doi:10.1590/s00348910.2014048004912.
Tsutsumi A, Izutsu T, Kato S, et al. Reliability and validity of the Bangla version of WHOQOL-BREF inan adult population in Dhaka, Bangladesh. Psychiatry Clin Neurosci. 2006;60(4):493–498. doi:10.1111/j.14401819.2006.01537.x.
Nedjat S, Montazeri A, Holakouie K, Mohammad K, Majdzadeh R. Psychometric properties of the Iranianinterview-administered version of the World Health Organization’s Quality of Life Questionnaire (WHOQOLBREF): a population-based study. BMC Health Serv Res. 2008;8:61. doi:10.1186/1472-6963-8-61.
Yoshitake N, Sun Y, Sugawara M, et al. The psychometric properties of the WHOQOL-BREF in Japanese
couples. Health Psychol Open. 2015;2(2):2055102915598089. doi:10.1177/2055102915598089.
Xia P, Li N, Hau KT, Liu C, Lu Y. Quality of life of Chinese urban community residents: a psychometricstudy of the mainland Chinese version of the WHOQOL-BREF. BMC Med Res Methodol. 2012;12:37.
doi:10.1186/1471-2288-12-37.
Krägeloh CU, Kersten P, Rex Billington D, et al. Validation of the WHOQOL-BREF quality of life
questionnaire for general use in New Zealand: confirmatory factor analysis and Rasch analysis. Qual Life
Res. 2013;22(6):1451–1457. doi:10.1007/s11136-012-0265-9.
Kalfoss MH, Reidunsdatter RJ, Klöckner CA, Nilsen M. Validation of the WHOQOL-Bref: psychometricproperties and normative data for the Norwegian general population. Health Qual Life Outcomes.
2021;19(1):13. doi:10.1186/s12955-020-01656-x.

References End

Nagoya J. Med. Sci. 85. 79–92, 2023

92

doi:10.18999/nagjms.85.1.79