Journal of Rural Medicine
Field report

Difference of sociodemographic characteristics
among the disabled population in Cambodia:
a cross-sectional study of the demographic andhealth survey data
Kanika Kep1, Yurie Kobashi1, Erica Jynn Abarca Lopez2, Masaharu Tsubokura3, andManabu Okawada4
1Sunrise Japan Hospital Phnom Penh, Cambodia
Department of Biostatistics, University of the Philippines Manila, Philippines
3
Department of Radiation Health Management, Fukushima Medical University School of Medicine, Japan
4
Department of Pediatrics, Sunrise Japan Hospital Phnom Penh, Cambodia
2

Abstract
Objective: There is an urgent need to raise awareness of the significance of the social security system for vulnerable populations indeveloping countries and identify the widening disparities among people with disabilities. This study determined the sociodemographic characteristics of people with disabilities in Cambodia.
Materials and Methods: This was a cross-sectional study. Data from the Cambodia Demographic and Health Survey were used
to determine the association between disability and sociodemographic characteristics such as age, gender, number of family members, residence (rural/urban), and economic status.
Results: The results showed that the proportion of people with disabilities greatly increased with age. The rural-urban residence
difference affected the disability proportion in univariate analysis; however, the effect was not significant after adjusting for covariables in multivariate analysis. The odds of having a disability were 0.85 times lower for the high economic status group than forthe low economic status group.
Conclusion: Raising awareness to expand the capacity of social support for older adults with disabilities, especially those who do
not receive care from their families, may be an urgent issue in Cambodia. Therefore, a well-designed and disease-specific study
is required. This study was the first to determine the sociodemographic disparities among people with disabilities in Cambodia.
Key words: health disparity, sociodemographic characteristics, disabled population, Cambodia(J Rural Med 2022; 17(2): 79–84)

Introduction
Health disparity is thought to emerge from the healthsystem’s shortcomings and individual characteristics whererace, gender, sexual identity, age, disability, socioeconomic
status, geographic location, environmental barriers, andReceived: March 11, 2021
Accepted: January 20, 2022
Correspondence: Yurie Kobashi, Sunrise Japan Hospital Phnom
Penh, Sangkat Chroy Changvar, Phnom Penh, Cambodia
E-mail: yurie-s@umin.ac.jp
This is an open-access article distributed under the terms of theCreative Commons Attribution Non-Commercial No Derivatives(by-nc-nd) License <http://creativecommons.org/
licenses/by-nc-nd/4.0/>.

©2022 The Japanese Association of Rural Medicine

stigmatization are concerned1, 2). In particular, people withdisabilities and the vulnerable aging population are considered unrecognized health disparity populations3). These
groups frequently require long-term care, which translates
to a substantial economic burden and the need for human
medical resources. This long-term care is sometimes neglected in developing countries because the limited resources are distributed to other medical services, including childhealth, maternal health, emergency medicine, and communicable diseases. Therefore, the disabled population requiring long-term care in developing countries needs special
consideration to reduce health disparities.
Various efforts have been made to protect the health ofpeople with disabilities—in particular, a social security system that strongly supports such people in developed coun-doi: 10.2185/jrm.2021-012 | 79

Journal of Rural Medicine
tries. In countries lacking this system, families and relatives
provide support to bridge the gap between the demand forlong-term care and fewer human and medical resources4).
In Asia, the number of people with disabilities is continuously increasing5). Therefore, there is an urgent need to raiseawareness of the importance of the social security systemfor vulnerable populations in developing countries and identify the widening disparities among people with disabilities6,
7). However, few studies have been conducted on this topic.
Cambodia is a low-middle-income country in Southeast Asia, where rural disparity has emerged as a problem8).
According to a previous study in the main teaching eyehospitals in Takeo province, 2.7% of patients reported thatthey had disabilities related to hearing, movement, or communication in addition to ophthalmic diseases9). However,the number of patients receiving rehabilitation care was
low10) —0.36% in the Takeo province study9). In addition,
women with disabilities are often targets of abuse. Previous
studies have reported that care for such people is mainly
provided by their families4). Cambodia is a country with ahigh proportion of people with disabilities who face manysocial problems, where few laws or policies exist to protect
their human rights10). Studying sociodemographic disparities among disabled people might help identify the populations requiring intervention. There have been no studies
on disability status and sociodemographic disparities acrossCambodia, indicating the necessity of such studies.
The purpose of this study was to determine the sociodemographic disparities among people with disabilities in
Cambodia as the first step in protecting the health of vulnerable populations requiring long-term care. The sociodemographic characteristics examined were age, gender, numberof family members, residence (rural/urban), and economic
status.

MethodDatasetThis was a cross-sectional study. Data from the countrywide Cambodia Demographic and Health Survey(CDHS) were used to determine the association between
disability and sociodemographic characteristics11). The
primary purpose of the CDHS is to provide policymakers
and planners with detailed health information11). The 2014
CDHS performed a stratified sample that was selected in
two stages. First, from the 611 clusters, 16,356 households
were selected; among these, 15,825 households completed
the household questionnaire. Of these, 69,471 individuals were included in the household questionnaire survey11).
During the 2014 CDHS, four questionnaires were administered: the household questionnaire, woman’s questionnaire,
man’s questionnaire, and micronutrient questionnaire. The
household questionnaire was used to list all family mem-bers in the selected households and obtain basic information
on each participant’s characteristics, including age, gender,
dwelling, and disability status11). This was the only questionnaire that included data on residents aged over 50. The 2014
CDHS defined the difference between urban and rural areas in terms of living space, with the degree of population
concentration or density12). The present study extracted dataon age, gender, economic status, residence, and disability
status from the household questionnaire.

Data definition
Data were collected from June 2 to December 12, 2014.
Participants over 19 years were included in the analysis, andthose with missing disability status data were excluded. In
the 2014 CDHS, the wealth quantile was divided into fivestates: lowest, second, middle, fourth, and highest. In thepresent study, economic status was reclassified into threegroups to have sufficient participants in each grouping forstatistical analysis. “Lowest” and “second” were grouped
under “low”. “Middle” was grouped under “middle”.
“Fourth” and “highest” were grouped under “high”. We
used strata for urban and rural areas for residences.
Primary outcome
The primary outcome was the presence of disability related to each type (vision, hearing, walking, concentrating,self-care, and communication) to determine the association
between disability and sociodemographic characteristics.
In this study, disability refers to impairment, a problem inbody function, and activity limitations, which is a difficulty
encountered by an individual when executing a task. This isdifferent from the aging process. The presence of disability
has been used as an outcome in previous studies; the relationship between disabilities and sociodemographic characteristics has also been reported. We defined the presence ofdisability as a disability with at least some difficulty.
Analysis
Frequencies and proportions were used to describe theparticipants’ sociodemographic characteristics. Next, theproportion of participants with at least one disability wasdetermined by age group, economic status, or residence.
Chi-square tests were performed for each age group. Univariate logistic regression analysis was performed for age,sex, number of family members, economic status, and residence to determine the association between each characteristic and the presence of a disability. Then, multivariate
logistic regression was conducted with age, gender, number of family members, economic status, and residence as
independent variables, and disability status as the dependent variable. The association between disability proportion and sociodemographic characteristics was statisticallyanalyzed, and a P-value of 0.05 was considered statistically2022; 17(2): 79–84 | doi: 10.2185/jrm.2021-012 | 80

Journal of Rural Medicine
significant. Data analyses were performed using Stata/IC
15 (Lightstone, version 15, TX, USA). The study obtained
ethics approval from the CDHS Review Committee. Only
individuals who provided informed consent were includedin the survey. The informed consent statement highlighted
that participation was voluntary. Interviewers were prohibited from divulging participant information by the membersof the DHS program team. Data processing began on 25
personal computers on July 6, 2014. Field check tables werecreated regularly to check data quality, and double data entry and data cleaning was performed11). All participants’ information was anonymized as a series of numbers.

Results
Table 1 shows the sociodemographic characteristics of
38,312 participants. The median age was 38 years [range,
28–52 years], and 32.73% of the participants were classified
in the low economic status group. Disability related to vision was the most common among the five disability types
examined.
The proportion of people with disabilities greatly increased with age, as observed in other countries. The majority of participants over 70 years had at least one disability
in the current study. In all age groups, the number of ruralparticipants with disabilities was higher than that of theirurban counterparts; however, analysis using the chi-square
test was not significant in any age group except the 20s. In
addition, for all age groups, a higher proportion of those in
the low economic status group had disabilities than in theother groups; however, analysis using the chi-square test
was not significant in any age group except for those in their
20s, 30s, and 70s (Figure 1).
Table 2 shows the results of the multivariate logistic regression analysis to determine the association between thepresence of disability and sociodemographic characteristics.
The rural-urban residence difference affected the disability
proportion in univariate analysis; however, after adjustingfor gender, age, number of families, and economic status in
the multivariate regression model, the effect was not significant. The multivariate analyses showed that the odds of having a disability were 0.85 times lower for the high economic
status group than for the low economic status group. The
proportion of those with disabilities significantly decreasedin the middle and high economic status groups.
The multivariate analyses using the aforementioned
regression model for each disability type are presented inTable 3. A significant decrease in the number of participants
with disabilities related to vision, hearing, self-care, andcommunication was observed in the high economic statusgroup; however, the number of participants with disabilities
associated with walking and concentrating was not high inthis group. Moreover, female participants were significantly
higher among those with disabilities related to vision andconcentration.

Discussion
There is an urgent need to raise awareness of the importance of the social security system for vulnerable popula-

Table 1 Participant characteristics (N=38,312)n (%)
GenderMale
Female17,867 (46.64)
20,445 (53.36)

Age (median [25th, 75th centiles])38 [28–52]

Number of family members (median [25th, 75th centiles])5 [4–7]

Economic status
Low
MiddleHigh

12,535 (32.72)
6,681 (17.44)
19,096 (49.84)

Residence
Rural
Urban

26,224 (68.45)
12,088 (31.55)

Disability
VisionHearing
Walking
Concentrating
Self-careCommunication

2,570 (6.71)
1,350 (3.52)
1,888 (4.47)
1,941 (5.07)
562 (1.47)
719 (1.88)

2022; 17(2): 79–84 | doi: 10.2185/jrm.2021-012 | 81

Journal of Rural Medicine

Figure 1 Proportion of residents with disabilities*P<0.05, with χ2 test. (a) Disability proportion according to economic status. (b) Disability proportion by residence.

tions in developing countries and identify the widening disparities among people with disabilities. This study aimed todetermine the sociodemographic disparities among people
with disabilities in Cambodia.
It showed that the proportion of people with disabilities significantly increased with age; most residents over 70
years old had at least one disability. A previous study reported that families of people with disabilities were providing
the required long-term care due to the shortage of caregivers
in Cambodia4). The present study results show that there are
already many aging people with disabilities compared to theyouth; therefore, providing care and social support, especially to those who do not receive care from their families,

should be considered.
This study, based on previous evidence, found that the
proportion of people with disabilities was higher in the low
economic status group; the odds of having a disability were0.85 times lower for the high economic status group thanfor the low economic status group. It has been reported thata higher proportion of people with disabilities live below
the poverty line13). Another study reported that disparities
among people with disabilities are not limited to economic
status14). Information on people with disabilities in Cambodia is limited; thus, details on the problems faced by suchpeople should be gathered alongside other information.
The participants’ sociodemographic characteristics

2022; 17(2): 79–84 | doi: 10.2185/jrm.2021-012 | 82

Journal of Rural Medicine
Table 2 Multivariate logistic regression analysis to determine the association between the presence of disability and sociodemographic characteristics
Univariate analysis
Unadjusted OR (95% CI)

Multivariate analysis (N=38,312)
Adjusted OR (95% CI)

Ref.
1.21 (1.14–1.29)**1.08 (1.07–1.08)**
0.94 (0.92–0.95)**

Ref.
1.03 (0.96–1.10)
1.08 (1.07–1.08)**
1.00 (0.98–1.01)

Ref.
0.87 (0.81–0.93)**

Ref.
0.97 (0.89–1.06)

Ref.
0.93 (0.85–1.02)
0.85 (0.79–0.91)**

Ref.
0.88 (0.79–0.97)**0.85 (0.78–0.93)**

GenderMale
FemaleAge
Number of family
Residence
Rural
Urban
Economic status
Low
MiddleHigh**P<0.01. OR: Odds ratio; CI: Confidence interval.
Table 3 Multivariate logistic regression analysis by disability type to determine the association between the presence of disability and sociodemographic characteristics
Multivariate analysis (N=38,312), Adjusted OR (95% CI)

GenderMale
FemaleVisionHearing

Walking

Concentrating

Self-careCommunication

Ref.
1.16 (1.06–1.27)

Ref.
1.04 (0.92–1.17)

Ref.
1.02 (0.92–1.13)

Ref.
1.26 (1.14–1.39)*

Ref.
0.94 (0.79–1.12)

Ref.
1.04 (0.89–1.21)

Age

1.09 (1.09–1.09)** 1.08 (1.08–1.09)** 1.09 (1.10–1.10)**1.07 (1.07–1.08)**

1.10 (1.09–1.11)**1.07 (1.07–1.08)**

Number of family

0.99 (0.97–1.01)

1.03 (1.00–1.05)*

1.00 (0.98–1.02)

1.00 (0.98–1.02)

1.04 (1.00–1.07)

1.04 (1.01–1.07)*

Residence
Rural
Urban

Ref.
1.01 (0.90–1.13)

Ref.
1.02 (0.88–1.19)

Ref.
0.90 (0.79–1.03)

Ref.
1.01 (0.89–1.14)

Ref.
1.13 (0.90–1.43)

Ref.
0.97 (0.78–1.19)

Economic status
Low
Middle
High

Ref.
Ref.
Ref.
0.85 (0.75–0.97)* 0.76 (0.65–0.89)** 1.05 (0.91–1.21)
0.85 (0.76–0.95)** 0.61 (0.52–0.71)** 0.98 (0.86–1.11)

Ref.
0.89 (0.77–1.03)
0.89 (0.79–1.01)

Ref.
0.73 (0.57–0.94)*
0.64 (0.51–0.80)*

Ref.
0.84 (0.68–1.03)
0.57 (0.47–0.69)**P<0.05, **P<0.01. OR: Odds ratio; CI: Confidence interval.

differed for each disability type in the present study. The
number of women was higher among those with vision andconcentration-related disabilities. On the other hand, there
was no significant association between economic status andthe number of people with walking and concentration-related disabilities. Residents in lower economic status groups
might need to engage in manual labor even after they research retirement age. This might affect the results—for
instance, those related to the number of people with disabilities related to walking. The increase in noncommunicable diseases is a major problem in Southeast Asia, including Cambodia15–17). The increase in obesity and the lack of
exercise among wealthy older adults might impact the disability proportion vis-à-vis disability related to walking. A
well-designed, disease-specific study for each residence isrequired to understand the causes and background of disparities in the disabled population.
The limitations of this study should be considered wheninterpreting these findings. First, detailed information onsocial demographics could not be obtained from the CDHS.
Second, the information obtained was limited to household
questionnaires. Third, only six disability types were examined. Fourth, the survey was performed using a questionnaire survey; thus, the disability status was reported subjectively. Fifth, economic status was classified into only threegroups. Finally, as the survey was conducted in 2014, thedata might not reflect the current situation in Cambodia.
Despite these limitations, this is the first study to determine
sociodemographic disparities among people with disabilities in Cambodia.

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Journal of Rural Medicine
Conclusion
The proportion of people with disabilities was significantly higher among the elderly in Cambodia, similar toother countries. The proportion of those with at least one
disability was higher in the low economic status group, irrespective of residence. A well-designed, disease-specificstudy is required to identify issues among aging disabledresidents.
Author contributions: The corresponding authors had
full access to all data in the study and had final responsibility for the decision. YK and EL contributed to data analysis. KK, YK, EL, and TM contributed to writing the manuscript. YK, MT, and MO contributed to the research design,
management, and coordination of local stakeholders. All
authors contributed to the review of this manuscript.
Funding: YK received a personal research fee from the
National Mutual Insurance Federation of Agricultural Co-

operatives for the aforementioned research. This research
did not receive any specific grants from any funding agency.
Conflicts of interest: The funding source had no rolein the design, practice, or analysis of this study. All authors
declare no conflicts of interest for this article.

Acknowledgements
Since the corresponding authors received a personal research fee for the research entitled “Health survey among
farmers in rural Asian developing countries” from the
National Mutual Insurance Federation of Agricultural Cooperatives, a preliminary report will be presented at the
Kyosai-Examiner-Tsuushin. The National Mutual Insurance
Federation of Agricultural Cooperatives approved the publication of papers using data obtained using a research grantfrom the National Mutual Insurance Federation of Agricultural Cooperatives in 2020.

References
1. Braveman P. What are health disparities and health equity? We need to be clear. Public Health Rep 2014; 129(Suppl 2): 5–8. [Medline] [CrossRef]
2. The U.S. Department of Health and Human Services. Disparities 2020; https://www.healthypeople.gov/2020/about/foundation-health-measures/Disparities(Accessed Feb. 25, 2021)
3. Krahn GL, Walker DK, Correa-De-Araujo R. Persons with disabilities as an unrecognized health disparity population. Am J Public Health 2015; 105(Suppl
2): S198–S206. [Medline] [CrossRef]
4. Sakurai-Doi Y, Mochizuki N, Phuong K, et al. Who provides nursing services in Cambodian hospitals? Int J Nurs Pract 2014; 20(Suppl 1): 39–46. [Medline] [CrossRef]
5. Zheng X, Chen G, Song X, et al. Twenty-year trends in the prevalence of disability in China. Bull World Health Organ 2011; 89: 788–797. [Medline][CrossRef]
6. Kang Q, Chen G, Lu J, et al. Health disparities by type of disability: health examination results of adults (18–64 years) with disabilities in Shanghai, China.
PLoS One 2016; 11: e0155700. [Medline] [CrossRef]
7. The World Bank. Disability inclusion 2020; https://www.worldbank.org/en/topic/disability (Accessed Feb. 28, 2021)
8. Kobashi Y, Chou K, Slaiman N, et al. Improving the rural-urban balance in Cambodia’s health services. Int J Health Policy Manag 2020. [Medline] [CrossRef]
9. Mörchen M, Bonn TS, Lewis D. Towards Universal Eye Health: hospital-based disability-disaggregated data collection in Takeo province, Cambodia.
Disabil Health J 2018; 11: 660–664. [Medline] [CrossRef]
10. MacLeod M, Pann M, Cantwell R, et al. Issues in access to safe drinking water and basic hygiene for persons with physical disabilities in rural Cambodia.
J Water Health 2014; 12: 885–895. [Medline] [CrossRef]
11. Ministry of Planning, Ministry of Health, and ICF International. Cambodia demographic and health survey 2014; https://dhsprogram.com/pubs/pdf/fr312/
fr312.pdf (Accessed 16th Feb. 16, 2021)
12. Pierce H. Increasing health facility deliveries in Cambodia and its influence on child health. Int J Equity Health 2019; 18: 67. [Medline] [CrossRef]
13. United Nations. Disability and development report 2018; https://www.un.org/development/desa/disabilities/wp-content/uploads/sites/15/2019/07/disability-report-chapter2.pdf (Accessed Feb. 20, 2021)
14. Pérez-Hernández B, Rubio-Valverde JR, Nusselder WJ, et al. Socioeconomic inequalities in disability in Europe: contribution of behavioral, work-related
and living conditions. Eur J Public Health 2019; 29: 640–647. [Medline] [CrossRef]
15. World Health Organization. Noncommunicable diseases 2018; https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases (Accessed
Feb. 16, 2021)
16. Ministry of Health. National strategic plan for the prevention and control of noncommunicable diseases 2013; https://www.iccp-portal.org/system/files/
plans/KHM_B3_NSP-NCD%202013-2020_Final%20approved.pdf (Accessed Feb. 28, 2021)
17. Kobashi Y, Chhay H, Savat T, et al. Health disparity toward noncommunicable diseases among residents in rural Cambodia: a descriptive study. J Rural
Med 2020; 15: 212–216. [Medline] [CrossRef]

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