BioMed Research International
Volume 2016 (2016), Article ID 7059196, 7 pages
http://dx.doi.org/10.1155/2016/7059196

Research Article

Coxiella burnetii Seroprevalence and Risk Factors in Cattle Farmers and Farm Residents in Three Northeastern Provinces and Inner Mongolia Autonomous Region, China

Wu-Wen Sun, Wei Cong, Mao-Hui Li, Chun-Feng Wang, Xiao-Feng Shan, and Ai-Dong Qian

College of Animal Science and Technology, Jilin Agriculture University, Changchun, Jilin Province 130118, China

Received 21 September 2015; Revised 29 December 2015; Accepted 10 January 2016

Academic Editor: Daniele Corsaro

Copyright © 2016 Wu-Wen Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Little is known about Coxiella burnetii infection among cattle farmers and farm residents in China. Thus, the present study was conducted to detect the seroprevalence of C. burnetii infection and estimate associated risk factors among cattle farmers and farm residents in China. A cross-sectional study was designed, and sera of 362 people living or working on 106 cattle farms were tested for C. burnetii IgG and IgM antibodies by immunofluorescence assay. Overall C. burnetii seroprevalence was 35.6% (129/362, 95% CI: 30.70–40.57), and 112 participants had experienced a past infection and seventeen (4.7%) had experienced a relatively recent infection. In the final combined multilevel model, the following activities were significantly associated with presence of antibodies against C. burnetii: milking cattle, providing general healthcare to cattle, providing birth assistance, contact dead-born animals, urbanization, and presence of mice and/or rats in the stable. Moreover, presence of disinfection equipment was a significant protective factor. This is the first study addressing the seroprevalence and risk factors of C. burnetii infection in cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

1. Introduction

Q fever, caused by Coxiella burnetii (C. burnetii), is a ubiquitous zoonotic disease. Cattle, sheep, and goats are considered as the primary animal reservoirs for human infection. C. burnetii are shed in particularly high concentrations in placentas and birth fluids of infected animals, which may subsequently contaminate the stable environment [1]. Human get infections with C. burnetii mostly by inhalation of contaminated aerosols coming from parturient animals and their birth products [2–4]. Clinical symptoms of acute Q fever usually present as a self-limited febrile illness, hepatitis, or pneumonia, with very little proportion evolving into chronic infections [5–7].

Q fever has outbroken in people in some countries, including Spain [8], Switzerland [9], Great Britain [10], Germany [11], and Netherlands [12]. Infections are usual occupational risk in persons working with livestock and contacting with highly infectious aerosols from birth products, milk, urine, faeces, or semen of infected animals [13]. These occupational risk populations include workers in slaughterhouses, meat-packing plants, and tanneries as well as veterinarians and farmers [13]. In China, infection has been detected in humans as well as in a wide range of wild, domestic, and farmed animals such as cattle, goats, dogs, pigs, mice, sheep, and horses [14]. In the previous study, we reported the seroprevalence of C. burnetii infection in farmed ruminants including cattle in the three northeastern provinces and Inner Mongolia Autonomous Region, China [15]. However, information on the seroprevalence and risk factors for acquisition of C. burnetii infection in cattle farmers and farm residents is limited. Thus, the aim of the present study was to determine the seroprevalence in farmers and household members living and/or working on cattle farms and to assess the farm-related and individual risk factors for seropositivity in order to update control measures and to provide targeted advice for this occupational group and the China cattle industry.

2. Materials and Method

2.1. Study Population and Data Collection

This study was approved by the Animal Ethics Committee of Jilin Agriculture University, China. All cattle farms in three northeastern provinces and Inner Mongolia Autonomous Region with at least 50 cattle that were not vaccinated for Q-fever were selected from the register in the census of the zone. As an important cattle and sheep breeding base in China, with the development of economy, farms with different sizes were settled up quickly in Inner Mongolia Autonomous Region. The three northeastern provinces (Jilin, Liaoning, and Heilongjiang provinces) are comprehensive agricultural bases. Poultry, pigs, cattle, sheep, and deer are the main breeding animals in these areas. On eligible farms, we approached cattle farmers and one or two of their household members aged 12 years and older, and in some cases, other persons working or living on the farm such as farm employees. A maximum of five participants were included per farm. Nonresponders received a reminder 3 weeks after the initial invitation. After providing informed consent on farm and individual level, all participating farms were visited by professional laboratory assistants, who collected sera from October 2013 through July 2014. Each participant completed a questionnaire about personal characteristics (e.g., age, medical history, farm-related activities, contact with livestock and companion animals, and use of personal protective equipment). The farm owner or manager completed a questionnaire about herd size, cattle housing, presence of other livestock and companion animals, farm facilities, and hygiene measures.

2.2. Serological Method

An immunofluorescence assay (IFA) (Focus Diagnostics, Cypress, CA, USA) was used to test serum samples for C. burnetii phases I and II IgM and IgG. All samples were screened at an initial dilution of 1 : 32; those with negative results were considered negative. Positive samples were further classified as indicative of relatively recent infections (IgM phase II titer >32) or past infections (IgG phase II titer >32 and IgM phase II titer <32). Samples with all other outcomes were considered negative. The term relatively recent was chosen because phase II IgM is commonly found up to 1 year after infection in acute Q fever cases, but it may persist up to 3 years [16]. Phases I and II IgG end point titers were determined for all seropositive persons. In agreement with chronic Q fever diagnostic criteria used in the Netherlands [17], phase I IgG titers ≥1,024 in samples in the past infection group were considered indicative of possible chronic infection.

2.3. Statistical Analysis

Results were analyzed with SPSS 19.0 software package. For comparison of the frequencies among the groups, the Mantel-Haenszel test and when indicated the Fisher exact test were used. Bivariate, multivariate, and multilevel analyses were used to assess the association between participant- and farm-based characteristics of the subjects and the C. burnetii infection. Variables were included in the multivariate analysis if they had a value of equal or less than 0.20 in the bivariate analysis. Adjusted odd ratio (OR) and 95% confidence interval were calculated by multivariate analysis using multiple, unconditional, and logistic regression. A value less than 0.05 was considered statistically significant.

3. Results

3.1. Descriptive Characteristics

Of all 197 invited eligible cattle farms, 106 (53.8%) farms participated in this study. The number of cattle farms from Heilongjiang, Jilin, Liaoning, and Inner Mongolia was 21, 28, 22, and 35, respectively. The mean herd size was 95 cattle (range 50–327) in participating farms. From the 106 participating farms, 362 persons provided a blood sample (mean age 46.0 years (12–68), 45.3% male) (Table 1). All of the farm-based and participant-based questionnaires were completed by the 106 farmers and 362 persons.

Table 1: Participant characteristics and Coxiella burnetii seroprevalence among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Freq. ()
Seroprevalence (%)
95% CI

Participant

362
35.64
30.70–40.57

Sex
Male
198
36.36
29.66–43.06

Female
164
34.76
27.47–42.04

Age group
<35
56
35.71
23.16–48.26

35–44
78
30.77
20.53–41.01

45–54
137
38.69
30.53–46.84

≥55
91
35.17
25.35–44.98

Function
Farmer
193
38.34
31.48–45.20

Spouse
89
31.46
21.81–41.11

Child
45
31.11
17.59–44.64

Other
35
37.14
21.14–53.15

Region
Heilongjiang
98
30.61
21.49–39.74

Jilin
76
27.63
17.58–37.69

Liaoning
92
31.52
22.03–41.02

Inner Mongolia
96
51.04
41.04–61.04

represents other family members and employees.

3.2. Seroprevalence of C. burnetii

Overall C. burnetii seroprevalence was 35.6% (129/362, 95% CI: 30.70–40.57), and seroprevalence among farmers, spouses, children, and others was 38.3%, 31.5%, 31.1%, and 37.1%, respectively (Table 1). Of the 129 seropositive participants, 112 participants had experienced a past infection and seventeen (4.7%) had experienced a relatively recent infection, as demonstrated by presence of IgM phase II antibodies. IgG phase II end titers were known for the 76 participants with a past infection with IgG phase I <1 : 32: 1 : 32 (), 1 : 64 (), 1 : 128 (), 1 : 256 (), 1 : 512 (), and ≥1 : 1024 (). For the 36 participants with a past infection with IgG phase I ≥1 : 32, 3 persons had “possible chronic Q fever” with IgG phase I titers ≥1 : 1024 according to diagnostic standard used in the Netherlands [8]. We could not confirm that these truly were chronic Q fever cases due to lack of clinical information (e.g., presence of vascular infection, endocardial involvement, or other clinical risk factors).

3.3. Risk Factors for C. burnetii Infection

All individual and farm-based variables, which were tested in the bivariate analysis for relationship with human C. burnetii seropositivity, are shown in Tables 2 and 3.

Table 2: Bivariate logistic regression analysis of participant-based characteristics associated with Coxiella burnetii positivity among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Freq. ()
Seroprevalence (%)
OR (95% CI)
value

Work and/or live on farm
Work and live
245
40.41
2.03 (0.98–4.22)
0.023

Work, but not live
73
26.03
1.06 (0.45–2.49)

Not working, but live
44
25.00
Reference

Hours working on farm
Fulltime
174
37.36
1.32 (0.65–2.66)
0.853

Halftime
109
35.78
1.23 (0.59–2.59)

Quarter week
34
32.35
1.06 (0.41–2.76)

Sometimes/never
45
31.11
Reference

How often in stable
Every day
189
38.62
1.39 (0.70–2.79)
0.426

Every week
104
35.58
1.22 (0.58–2.58)

Every month
38
28.95
0.90 (0.35–2.32)

Less than once a month/never
31
25.81
Reference

Feeding cattle
Yes
299
38.45
2.19 (1.16–4.14)
0.014

No
63
22.22
Reference

Milking cattle
Yes
203
43.84
2.32 (1.48–3.65)
<0.001

No
159
25.16
Reference

General healthcare of cattle
Yes
241
42.32
2.56 (1.55–4.21)
<0.001

No
121
22.31
Reference

Remove manure
Yes
286
35.66
1.01 (0.59–1.71)
0.982

No
76
35.53
Reference

Spread manure
Yes
258
40.31
2.13 (1.28–3.57)
0.002

No
104
24.04
Reference

Clean stables
Yes
269
39.03
1.84 (1.09–3.11)
0.022

No
93
25.81
Reference

Birth assistance
Yes
216
42.59
2.19 (1.38–3.46)
<0.001

No
146
25.34
Reference

Administration
Yes
219
38.81
1.43 (0.91–2.23)
0.076

No
143
30.77
Reference

Wear overalls or boots
Yes
233
38.63
1.45 (0.92–2.30)
0.110

No
129
30.23
Reference

Having a dog
Yes
294
35.03
0.87 (0.51–1.50)
0.619

No
68
38.24
Reference

Having a cat
Yes
278
35.25
0.93 (0.56–1.55)
0.782

No
84
36.90
Reference

Direct contact with cattle in their own or other farms
Yes
287
38.68
2.00 (1.12–3.57)
0.018

No
75
24.00
Reference

Direct contact with horses in their own or other farms
Yes
210
39.52
2.56 (1.61–4.07)
<0.001

No
152
23.68
Reference

Contact with raw milk
Yes
243
43.21
3.01 (1.80–5.04)
<0.001

No
119
20.17
Reference

Contact with cattle manure
Yes
225
44.00
2.80 (1.73–4.54)
<0.001

No
137
21.90
Reference

Contact with dead-born animals
Yes
196
45.41
2.62 (1.67–4.12)
<0.001

No
166
24.10
Reference

Contact with placenta/birth material
Yes
188
38.30
1.27 (0.83–1.96)
0.272

No
174
32.76
Reference

Table 3: Bivariate logistic regression analysis of farm-based characteristics associated with Coxiella burnetii positivity among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Number of humans tested
Positive (%)
OR (95% CI)
value

Region
Heilongjiang
98
30.61
Reference

Jilin
76
27.63
0.87 (0.45–1.68)
0.667

Liaoning
92
31.52
1.04 (0.56–1.93)
0.892

Inner Mongolia
96
51.04
2.36 (1.31–4.25)
0.004

Urbanization
Moderate or minor urban area
149
20.81
Reference
<0.001

Rural area
213
46.01
3.24 (2.01–5.24)

Herd size
Small (50–100)
197
32.48
Reference
0.393

Medium (100–150)
104
39.42
1.35 (0.83–2.22)

Large (>150)
61
39.34
1.35 (0.74–2.44)

Beef cattle on the farm
Yes
202
37.13
1.16 (0.75–1.79)
0.505

No
160
33.75
Reference

Number of stables
>3 stables
117
32.48
0.81 (0.51–1.30)
0.386

≤3 stables
245
37.14
Reference

Use of artificial insemination
Yes
84
46.43
1.81 (1.10–2.98)
0.018

No
278
32.37
Reference

Laying hens on farm
Yes
243
40.33
1.92 (1.18–3.11)
0.008

No
119
26.05
Reference

Presence of cat(s) in cattle stable
Present
198
36.36
1.07 (0.70–1.65)
0.751

Absent
164
34.76
Reference

Use of silage
Yes
276
40.22
2.54 (1.43–4.51)
0.001

No
86
20.93
Reference

Use of maize
Yes
288
38.19
1.79 (1.01–3.17)
0.045

No
74
25.68
Reference

Feeding method
Fodder mixer or automatic
241
32.37
0.66 (0.42–1.03)
0.067

Hand/wheelbarrow
121
42.15
Reference

Presence of mice and/or rats in the stable
Present
199
45.23
2.63 (1.67–4.14)
<0.001

Absent
163
23.93
Reference

Farm visitors
Yes
143
37.76
1.17 (0.75–1.81)
0.495

No
219
34.25
Reference

Farm boots for staff
Yes
277
36.46
1.17 (0.70–1.95)
0.553

No
85
32.94
Reference

Presence of hygienic locker room
Yes
269
31.97
0.55 (0.34–0.88)
0.013

No
93
46.24
Reference

Presence of disinfection equipment
Yes
224
29.46
0.50 (0.32–0.77)
0.002

No
138
45.65
Reference

Birds in stable
Yes
90
45.56
1.75 (1.08–2.85)
0.023

No
272
32.35
Reference

Veterinary service
Yes
301
31.62
1.40 (0.78–2.54)
0.273

No
61
29.51
Reference

Type of farm management
Closed herd
298
34.89
0.84 (0.48–1.46)
0.528

Purchase of cattle
64
39.06
Reference

In the multivariate analyses, from 14 individual variables which were associated in the bivariate analysis, six were independently associated with C. burnetii seropositivity (Table 4). Moreover, 5/18 farm-based variables included in the multilevel analyses were significantly independent risk or protective factors and together were used as the full multilevel start model (Table 5).

Table 4: Multivariate logistic regression analysis of participant-based characteristics associated with Coxiella burnetii positivity among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Adjusted odds ratio
95% confidence interval
value

Milking cattle
Yes
1.88
1.21–2.94
0.005

No
Reference

General healthcare of cattle
Yes
2.40
1.46–3.93
<0.001

No
Reference

Birth assistance
Yes
2.07
1.31–3.27
0.002

No
Reference

Contact raw milk
Yes
2.47
1.50–4.06
<0.001

No
Reference

Contact cattle manure
Yes
3.23
1.92–5.44
<0.001

No
Reference

Contact dead-born animals
Yes
3.45
2.16–5.50
<0.001

No
Reference

The variables included were those with a obtained in the bivariate analysis.

Adjusted by age and the rest of characteristics included in this table.

Table 5: Multivariate logistic regression analysis of farm-based characteristics associated with Coxiella burnetii positivity among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Adjusted odds ratio
95% confidence interval
value

Urbanization
Rural area
3.66
2.25–5.96
<0.001

Moderate or minor urban area
Reference

Laying hens on farm
Yes
2.04
1.25–3.32
0.004

No
Reference

Use of silage
Yes
1.99
1.15–3.44
0.013

No
Reference

Presence of mice and/or rats in the stable
Present
2.49
1.58–3.91
<0.001

Absent
Reference

Presence of disinfection equipment
Yes
0.58
0.37–0.90
0.015

No
Reference

The variables included were those with a obtained in the bivariate analysis.

Adjusted by age and the rest of characteristics included in this table.

In the final combined multilevel model, significant risk factors were milking cattle, general healthcare of cattle, birth assistance, contact dead-born animals, urbanization, and presence of mice and/or rats in the stable. Moreover, presence of disinfection equipment was a significant protective factor (Table 6).

Table 6: Combined multilevel analysis of participant- and farm-based characteristics associated with Coxiella burnetii seropositivity among cattle farmers and farm residents in three northeastern provinces and Inner Mongolia Autonomous Region, China.

Variable
Category
Adjusted odds ratio
95% confidence interval
value

Milking cattle
Yes
2.09
1.33–3.27
0.001

No
Reference

General healthcare of cattle
Yes
2.25
1.38–3.67
0.001

No
Reference

Birth assistance
Yes
1.86
1.18–2.92
0.005

No
Reference

Contact dead-born animals
Yes
2.67
1.69–4.45
<0.001

No
Reference

Urbanization
Rural area
2.34
1.41–3.45
<0.001

Moderate or minor urban area
Reference

Presence of mice and/or rats in the stable
Present
1.95
1.38–3.01
0.002

Absent
Reference

Presence of disinfection equipment
Yes
0.37
0.20–0.49
<0.001

No
Reference

The variables included were those with a obtained in the bivariate analysis.

Adjusted by age and the rest of characteristics included in this table.

4. Discussion

This is the first study exploring the seroprevalence in cattle farmers and farm residents in China, and one of few risk factor studies on human C. burnetii infections in farm populations worldwide [18–20], suggesting that living and or working on cattle farm has a high lifetime risk for acquiring C. burnetii infection. Farmers and other household members are usually at highest risk for acquiring C. burnetii infection due to close contact with infected cattle and contaminated stables on farms.

The detected seroprevalence was high not only for the farmers (38.3%), as expected, but also among spouses (31.5%), children (31.1%), and others (37.1%) who lived and often also worked at the farm. The present seroprevalence obviously overs the estimates of 10.2% in the people studied to date in China [14]. The seroprevalence was also lower than those in other studies focusing on, nonfurther specified, farm populations, such as 49% among farmers from Northern Ireland [21], 72.1% in dairy cattle farmers in the Netherlands [18], but was comparable to the 27% seroprevalence in a farm cohort in the United Kingdom [10]. However, it is complicated to compare these seroprevalences due to some differences, including geographical conditions, the different study populations, diagnostic methods, and living styles. Moreover, in the present study, females have a higher seroprevalence than males. It is contrary to other places in the world where studies have suggested that males are more susceptible to C. burnetii infection [2]. Routine activities of women in rural areas including taking care of livestock and cleaning stables result in the high prevalence in females in China [14].

Several independent individual and farm-based risk factors for C. burnetii seropositivity were found such as working and/or living in farm, milking cattle, general healthcare of cattle, birth assistance, contacting raw milk, contacting cattle manure, contacting dead-born animals, urbanization, laying hens on farm, use of silage, presence of mice and/or rats in the stable, presence of disinfection equipment, and birds in stable. The individual risk factor involving direct contact with cattle or dust-producing activities in the cattle stable, such as milking, general healthcare of cattle, clean stables, birth assistance, contacting raw milk, contacting cattle manure, and contacting dead-born animals, reflects the stable environment contact [22]. Under these circumstances the risk of inhalation of contaminated aerosols is high, with a potential increased risk for acquiring an infection. The degree of total farm animal contact has been reported to seem more important than particular animal exposure, suggesting that risk of C. burnetii exposure is largely connected with farm environment contact [6, 22].

Two farm-related risk factors were identified to be associated with human seropositivity among cattle farm residents/staff: urbanization and presence of mice and/or rats in the stable. The concentration and management of cattle farming in the rural area of the study regions possibly promoted transmission between farms. The presence of mice and/or rats in the stable was observed as risk factor for human seropositivity, suggesting C. burnetii introduction or facilitation of spread by infected wild animals [23–25]. Moreover, presence of disinfection equipment was observed as protective factor for human seropositivity.

It is worth noting that Q fever is out of notifiable diseases in China and thus it is not easy to get test facilities. Most cases are diagnosed through retrospective and epidemiological studies which implies that misdiagnosis often occurred for acute cases, resulting in the greater possibility of chronic infections which have a poor prognosis and high mortality [14]. Thus, routine serological follow-up is helpful for prevention as well as basic biological safety rules, such as hygiene measures and the use of protection clothes.

To conclude, high C. burnetii seroprevalences demonstrate that cattle farmers and farm residents have a substantial lifetime risk for acquiring this zoonotic infection. We recommend reinforcing routine biosecurity measures to avoid indirect spread, avoiding access of companion and wild animals to the stable, and offer advice on eliminating nuisance animals in the cattle stables. Clinicians should strengthen their awareness to consider Q fever in this occupational group presenting with compatible symptoms or relevant sequelae to allow diagnosis and therapy in time.

Conflict of Interests

The authors declare that there is no conflict of interests in this paper.

Acknowledgment

Project support was provided by the project National Natural Science Foundation of China (Grant no. 31272566).

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