Yonago Acta medica 2013;56:39–42

Original Article

Long-Term Effects of Livestock Loss Caused by Dust Stormon Mongolian Inhabitants: A Survey 1 Year after the Dust Storm
Haosheng Mu,* Shinji Otani,† Masato Shinoda,‡ Yae Yokoyama,* Kazunari Onishi,§ Takenobu Hosoda,*
Mikizo Okamoto* and Youichi Kurozawa**Division of Health Administration and Promotion, Department of Social Medicine, School of Medicine, Tottori University Faculty of
Medicine, Yonago 683-8503, Japan, †Division of Surgical Oncology, Department of Surgery, School of Medicine, Tottori University
Faculty of Medicine, Yonago 683-8504, Japan, ‡Arid Land Research Center, Tottori University, Tottori 680-0001, Japan and §Centerof Tottori Unit of the Japan Environment and Children’s Study, Yonago 683-8503, Japaneconomic loss to the inhabitants.2
Dust storms have recently attracted more attention
in terms of causing not only social and environmental
problems but also health problems including their influence on humans. We previously reported that dust
storms can cause eye damage (deterioration of subjective symptoms).3 However, the above-described impacts
on health occur immediately after the dust storms (i.e.,
short-term effects). There is little empirical evidence todemonstrate the long-term effects of dust storms, especially in terms of the effect of mass livestock death on
the health-related quality of life (HRQoL).
HRQoL is considered to be a subset concept of quality of life (QoL). QoL has been defined as “a person’s
subjective sense of well-being, derived from current
experience of life as a whole”. However, there is no clear
agreement on the definition of HRQoL.4 In general,
HRQoL is accepted as a multidimensional concept thatencompasses physical, psychological, social, spiritualand role-functioning concepts as well as general well-being. Therefore, HRQoL is used to evaluate health status.5
An intense dust storm occurred on May 26 and 27,
2008 in eastern Mongolia. The newsletter of the United
Nations in Mongolia reported that during the storm, theair temperature dropped nearly to 0 ˚C and the windspeed was believed to have reached > 40 m/s. Fifty-two
people were killed, out of which 14 were children, andmore than 278,000 livestock died. Also, many thousandsof livestock went missing.1 According to Governmentof Mongolia and UNDP (2008), this storm may havecaused the greatest amount of dam­age since 1980.2 For
this study, we focused specifically on this dust storm.
To evaluate the association between livestock loss and
HRQoL of stricken-area inhabitants, we performed an
HRQoL survey among these inhabitants 1 year later.

ABSTRACT
Background

Every spring, windblown dust storms
damage human health and cause many domestic animal
deaths in Mongolia. In particular, mass livestock death
results in severe, direct economic loss to inhabitants.
However, there is little empirical evidence to demonstrate the long-term effects of dust storm, especially interms of health-related quality of life (HRQoL) secondary to livestock loss. We evaluated the long-term effects
of livestock loss on Mongolian inhabitants.
Methods We performed a cross-sectional survey of
HRQoL using 36-item short-form health survey (SF36, an index of the health condition) 1 year after a dust
storm. The study subjects were 64 inhabitants of stricken
areas of Mongolia. The data collection method was a
face-to-face interview with a questionnaire.
Results A total of 64 subjects were interviewed, 81%
in the victims group and 19% in the non-victims group.
The mean number of livestock victims was 83.3, s =128.3. The SF-36 subscale scores were lower amongpeople who lost livestock than among those who did
not. Multiple regression analysis displayed a significant
association between livestock loss and HRQoL (general
health: = –0.476, P = 0.021; vitality: = –0.359, P =0.013).
Conclusion Our results provide preliminary evidence
that livestock loss has long-term effects on HRQoL.
Thus, it is necessary to conduct epidemiologic surveys
on disorders associated with dust storms and devise
countermeasures for the future.
Key words dust storm; livestock loss; long-term effectIn recent years, rapid climate changes have escalated
the severity of dust storms and have made them a more
serious hazard than ever before in Mongolia.1 In fact, recent dust storms have damaged electricity and telephonelines, road networks, pasturage and agricultural products, human and animal health, and so on. The costs forrecovery have become increasingly enormous. In particular, mass livestock deaths have caused severe direct

Corresponding author: Haosheng Mu
muhs@med.tottori-u.ac.jp
Received 2012 December 18
Accepted 2013 January 24
Abbreviations: HRQoL, health-related quality of life; GH, general
health; MH, mental health; QoL, quality of life; RP, role physical;
SF-36, 36-item short-form health survey; VT, vitality

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H. Mu et al.

SUBJETS AND METHODS
Study subjects

We performed a cross-sectional survey on HRQoL andthe livestock loss in Khentii Province, east of the capital
city of Ulaanbaatar in May 2009 (1 year after the dust
storm). The province covers an area of 80,311 km2 andhas a population of 67,770. The occupation of most inhabitants is nomadism with herding of domestic animals.
We chose Khentii Province as our study area because it
is one of the typical nomadic areas that represents theoverall population of the Mongolia desert (in terms ofsocio-economic status and demographic character) andwhere the highest number of human and livestock deaths
was recorded in that dust storm (30 people; 100,776
livestock). We visited 34 nomad gers (households) fromdoor-to-door along the main road for 3 days. The study
subjects were the heads of households and their spousesin each household. Of all households that were visited,
there were no occurrences of death in any families. The
data collection method used in this survey was a faceto-face interview with a questionnaire. The investigators
first informed the participants of the purpose of the survey and then obtained a statement of voluntary participation from each person being interviewed.

Fig. 1. Comparison of SF-36 subscale scores between victims andnon-victims groups. GH, general health; MH, mental health; RP,role physical; VT, vitality.

0.05 was accepted as statistically significant. In addition,by means of the hypothesis test, quantitative data of SF36 subscales scores (0–100) have the normal distribution, meet the conditions of multiple regression analysis.
Statistical analysis was carried out using SPSS version
18.0 (IBM SPSS, Chicago, IL).
RESULTSHRQoL

Characteristics of study subjects

HRQoL was assessed with a 36-item short-form healthsurvey (SF-36). The original questionnaire has 36 items
comprising 8 subscales. To simplify the questionnaire
for this study, only 4 subscales were investigated: general health (GH), vitality (VT), mental health (MH) androle-physical (RP). The scoring of each subscale was
performed according to a scoring protocol.6 Raw scores
were converted into numerical scores ranging from 0 to100. The higher the value, the better the outcome.

A total of 64 subjects (33 males and 31 females, mean
age was 42.1 years, s = 12.9 years) were interviewed inthis study. In terms of the state of livestock victims, 81%of total study subjects were in the victims group and
19% were in the non-victims group. The mean of livestock victims was 83.3, s = 128.3.
Relationship between livestock loss and HRQoL

Livestock loss

Figure 1 shows the results of comparison of SF-36
subscale scores between the victims and non-victims
groups. The scores of SF-36 subscales for the victims
group were lower than those for the non-victims group,

Information on livestock loss was obtained from the following 2 items: state of livestock victims (victims groupor non-victims group) and number of livestock victims.

Table 1. Results of multiple regression analysis of each
SF-36 subscale and the state of livestock victims

Statistical analyses

Dependent
variableState of livestock victims†
RP-value

GH
VT
MH
RP

–0.148–0.359–0.151–0.077

0.326
0.013
0.337
0.626

To examine the relationship between HRQoL and livestock loss, the scores of SF-36 subscales (GH, VT, MH
and RP) between the victims group and non-victims
group were compared using Student’s t-test. Furthermore, two multiple regression analysis were conductedto adjust the other variables (gender and age), using SF36 subscales as the dependent variables, and using thestate of livestock victims and the number of livestock
victims each as the independent variables. A P-value of

0.354
0.488
0.185
0.187

† Non-victims = 0; victims = 1.
Adjustment factors: gender and age.
GH, general health; MH, mental health; RP, role physical; VT,vitality.
, standardized partial regression coefficient; R, multiple correlation coefficient.

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Long-term effects of dust storm

spiritual health status). Up to now, there is little research
to demonstrate QoL decline in conjunction with theeconomic loss, but some studies reported it to be significantly correlated with economic income level.4,9 The
key steps in promoting QoL include the improvement ofpeople’s income.10,11 We suggest economic support orthe construction of a compensation insurance system toimprove the QoL level of inhabitants.
Many studies have explored the acute health effects
associated with short-term exposure to dust storms insome countries and regions. Substantial evidence showsthat short-term exposure is linked to a variety of adverse
effects on mortality, hospital admissions, outpatients,
asthma attacks, etc.12–15 However, these studies show
only short-term effects. Our study provides preliminary
evidence of the long-term effects of livestock loss for the
first time. Therefore, saving lives, animal husbandry andmedical health support after disasters (e.g., medical carepatrols, psychological consultations, etc.) are necessary.
At the same time, developing an early warning system toameliorate damage is also need.16 Thus, it is necessary
to conduct epidemiologic surveys on disorders associated with dust storms and devise countermeasures forthe future.
Our study has some limitations. The obtained data
were based on self-reports, the sample size was small,and certain conditions were not ruled out because of thelack of past medical histories. Therefore, future studies should consider these parameters. Our study used across-sectional design, which does not establish causeand-effect relationships and which may result in bias.
We believe, however, that this study provides sufficient
information to establish a hypothesis for a follow-up
study.

Table 2. Results of multiple regression analysis of each
SF-36 subscale and the number of livestock victims
Dependent
variable

Number of livestock victims
R

P-value

GH
VT
MH
RP

–0.476–0.393–0.142–0.319

0.021
0.055
0.510
0.128

0.494
0.499
0.076
0.404

Adjustment factors: gender and age.
GH, general health; MH, mental health; RP, role physical; VT,vitality.
, standardized partial regression coefficient; R, multiple correlation coefficient.

and VT displayed a statistically significant association
with livestock victims (P = 0.007). Table 1 shows the results of multiple regression analysis in which the state oflivestock victims was the independent variable and each
SF-36 subscale was a dependent variable. There was astatistically significant correlation between the state oflivestock victims and VT ( = –0.359, P = 0.013). Table
2 shows the results of multiple regression analysis inwhich the number of livestock victims was the independent variable and each SF-36 subscale was a dependent
variable. There was a statistically significant correlation
between the number of livestock victims and GH ( =–0.476, P = 0.021).

DISCUSSION
HRQoL is an evaluation index of the health condition.
A large number of HRQoL evaluation methods havebeen developed over the past 3 decades. The SF-36 was
designed for use in clinical practice and research, healthpolicy evaluation and general population surveys.7
The SF-36 is one of the most frequently used genericmeasurements of HRQoL.8 In this study, we assessed
HRQoL of inhabitants in Mongolia using the SF-36.
HRQoL was assessed using a 4-subscale survey that
evaluated GH, VT, MH and RP.
The SF-36 subscale scores were lower among thepeople in the livestock victims group than among thosein the non-livestock victim group. HRQoL displayed asignificant association with livestock loss; in particular,
there was a significant correlation between livestock
loss and GH or VT. GH is a subscale that reflects both
“QoL of physical health” and “QoL of spiritual health”.
VT contributes to the spiritual function, which means
the decline of spiritual health status.6 The stock-raisingindustry is a key industry in Mongolia, and an economic
loss occurs if there is a high loss of livestock. This maylead to a decline in the QoL of people (particularly the

Acknowledgments: The authors thank Professor D. Chimgee of
School of Economic Studies, National University of Mongolia,
and Dr. B. Battsetseg (DVM) of the Institute of Veterinary Medicine, Mongolia, who supported our survey. We also wish to cordially thank the local inhabitants.
This work was supported in part by Grant-in-Aid for Scientific
Research B (No. 21310121) of the Japan Society for the Promotionof Science, and conducted as part of the GCOE program, Global
Center of Excellence for Dryland Science, Tottori University.
The authors declare no conflict of interest.
REFERENCES
1 New Horizons [Internet]. The newsletter of the united nations
in Mongolia. [cited 2009 Aug 11]. Available from: http://www.
ilo.org/public/english/anniversary/90th/download/events/mon-41

H. Mu et al.
golia/unnewsletter.
2 Chimgee D, Shinoda M, Tachiiri K, Kurosaki Y. Why did a
synoptic storm cause a dramatic damage in a limited area ofMongolia? Mongolian Population J. 2010;19:63-8.
3 Mu H, Battsetseg B, Ito YT, Otani S, Onishi K, Kurozawa Y.
Health Effects of Dust Storms: Subjective Eye and Respiratory System Symptoms in Inhabitants in Mongolia. J Environ
Health. 2011;73:18-20.
4 Wang H, Kindig D, Mullahy J. Variation in Chinese population health related quality of life: Results from a EuroQol
study in Beijing China. Qual Life Res. 2005;14:119-32.
5 Mu H, Battsetseg B, Ito YT, Otani S, Onishi K, Kurozawa Y.
Effects of Asian Dust Storm on health-related quality of life:
a survey immediately after an Asian Dust storm in Mongolia.
Intern J Health Res. 2010;3:87-92.
6 Fukuhara S, Suzukamo Y. Manual of SF-36v2, Japanese version. Kyoto: Institute for Health Outcomes and Process Evaluation Research; 2004. Japanese.
7 Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 health survey manual and interpretation guide. Boston: Health Instituteat New England Medical Center; 1993.
8 Ohsawa I, Ishiba T, Oshida Y, Yamanouchi K, Sato Y. Subjective health values of individuals with diabetes in Japan: comparison of utility values with the SF-36 scores. Diabetes Res
Clin Pract. 2003;62:9-16.
9 Mu H, Kurozawa Y, Kotani K, Liu G, Liu P, Tsunekawa A, etal. Health-related quality of life and recognition of desertifica-tion among inhabitants of the loess plateau region of China:
findings for city and village communities. J Environ Health.
2008;70:38-43.
10 Zhang H, Lu ZQ, Wang SH, Cheng ZY, Zhang CF, Qi L. Exploring on the quality of life among the 601 elderly in the pastoral area in Baotou city. J Baotou Med College. 2001;17:262-4.
11 Li NX, Liu CJ, Li J, Ren XH. Factors that influence the quality of life Sichuan population. J West Chin Univ Med Sci.
2001;32:247-9.
12 Chen B, Kan H. Air pollution and population health: a global
challenge. Environ Health Prev Med. 2008;13:94-101. DOI:
10.1007/s12199-007-0018-5.
13 Cheng MF, Ho SC, Chiu HF, Wu TN, Chen PS, Yang
CY. Consequences of exposure to Asian dust storms on
daily pneumonia hospital admissions in Taipei, Taiwan. J
Toxicol Environ Health A. 2008;71:1295-9. DOI: 10.1080/
15287390802114808.
14 Yang CY. Effects of Asian dust storms on daily clinical visits
for conjunctivitis in Taipei, Taiwan. J Toxicol Environ HealthA. 2006;69:1673-80.
15 Yang CY, Chen YS, Chiu HF, Goggins WB. Effects of Asian
dust storms on daily stroke admissions in Taipei, Taiwan. Environ Res. 2005;99:79-84.
16 Shinoda M, Gillies JA, Mikami M, Shao Y. Temperate
grasslands as a dust source: knowledge, uncertainties, andchallenges. Aeolian Res. 2011;3:271-93. DOI: 10.1016/
j.aeolia.2011.07.001.

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