| Literature DB >> 24505476 |
Ying Li1, John Ehiri2, Eyal Oren3, Daiyu Hu4, Xingneng Luo5, Ying Liu1, Daikun Li6, Qingya Wang4.
Abstract
Multi-drug resistant tuberculosis (MDR-TB) represents a threat to health and development in countries with high TB burden. China's MDR-TB prevalence rate of 6.8% is the highest in the world. Interventions to remove barriers against effective TB control, and prevention of MDR-TB are urgently needed in the country. This paper reports a cross-sectional questionnaire survey of 513 pulmonary TB (PTB) patients, and qualitative interviews of 10 healthcare workers (HCWs), and 15 PTB patients. The objective was to assess barriers against effective control of PTB and prevention of MDR-TB by elucidating the perspectives of patients and healthcare providers. Results showed that more than half of the patients experienced patient delay of over 12.5 days. A similar proportion also experienced detection delay of over 30 days, and delay in initiating treatment of over 31 days. Consulting a non-TB health facility ≥3 times before seeking care at TB dispensary was a risk factor for both detection delay [AOR (95% CI): 1.89(1.07, 3.34) and delay in initiating treatment[AOR (95% CI): 1.88 (1.06, 3.36). Results revealed poor implementation of Directly Observed Therapy (DOT), whereby treatment of 34.3% patients was never monitored by HCWs. Only 31.8% patients had ever accessed TB health education before their TB diagnosis. Qualitative data consistently disclosed long patient delay, and indicated that patient's poor TB knowledge and socioeconomic barriers were primary reasons for patient delay. Seeking care and being treated at a non-TB hospital was an important reason for detection delay. Patient's long work hours and low income increased risk for treatment non-adherence. Evidence-based measures to improve TB health seeking behavior, reduce patient and detection delays, improve the quality of DOT, address financial and system barriers, and increase access to TB health promotion are urgently needed to address the burgeoning prevalence of MDR-TB in China.Entities:
Mesh:
Year: 2014 PMID: 24505476 PMCID: PMC3914979 DOI: 10.1371/journal.pone.0088330
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Definitions of and relations between the different types of delay among tuberculosis patients.
This figure indicates the operational definitions for patient delay, total detection delay and delay in initiating treatment. It also presented the relations of the three types of delays.
Figure 2Flow diagram of participant inclusion in the study in Chongqing, China.
This flow diagram showed the participants included in the study and final analysis of each related outcome.
Demographic and clinical characteristics of the questionnaire respondents.
| Characteristics | Frequency | Percent |
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| ||
| 16–45 | 335 | 70.4 |
| 46–60 | 100 | 21.0 |
| >60 | 41 | 8.6 |
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| Male | 325 | 68.4 |
| Female | 150 | 31.6 |
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| Han Race | 463 | 97.7 |
| Others | 11 | 2.3 |
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| Single | 204 | 43.1 |
| Married | 234 | 49.5 |
| Divorced | 23 | 4.9 |
| Windowed | 12 | 2.5 |
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| Rural | 220 | 46.6 |
| Urban | 252 | 53.4 |
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| Primary and below | 64 | 13.8 |
| Middle school | 266 | 57.5 |
| College and above | 133 | 28.7 |
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| Yes | 362 | 76.1 |
| No | 114 | 23.9 |
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| JLP | 178 | 37.4 |
| SPB | 198 | 41.6 |
| YZ | 100 | 21.0 |
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| ≤2PL | 186 | 40.1 |
| 2–3 | 13 | 2.8 |
| >3PL | 265 | 57.1 |
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| New | 436 | 97.5 |
| Retreatment | 11 | 2.5 |
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| Negative | 337 | 75.2 |
| Positive | 111 | 24.8 |
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| Yes | 448 | 94.1 |
| No | 28 | 5.9 |
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| TB hospital | 40 | 8.8 |
| Non-TB hospital | 415 | 91.2 |
|
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| 1 | 56 | 12.3 |
| 2 | 348 | 76.5 |
| ≥3 | 51 | 11.2 |
|
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| Yes | 150 | 29.6 |
| No | 360 | 70.4 |
Notes:
Missing data were excluded.
PL refers to local poverty line which is 3480 RMB Yuan per year since 2010.
TB refers to tuberculosis.
AFB smear status refers to Acid-Fast Bacilli (AFB) Smear status.
Figure 3Lengths of different types of delay among TB patients in Chongqing, China.
This figure showed lengths of patient delay (A), total detection delay (B) and delay in initiating treatment(C).
Univariate analysis factors association with longer delay.
| Categories | Delay≥12.5days(N = 238) |
| Delay≥31days(N = 232) |
| Delay≥31days(N = 232) |
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|
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| 16–45 | 157(46.9) | 0.18 | 148(46.4) | 0.17 | 149(47.8) | 0.05 |
| 46–60 | 57(57.0) | 59(61.5) | 59(60.8) | |||
| >60 | 22(53.7) | 24(60.0) | 24(58.5) | |||
|
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| Male | 156(48.0) | 0.17 | 156(49.8) | 0.51 | 157(50.5) | 0.45 |
| Female | 82(54.7) | 75(53.2) | 75(45.3) | |||
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| Han Race | 232(50.1) | 0.37 | 227(51.4) | 0.03 | 228(52.2) | 0.02 |
| Others | 4(36.4) | 2(18.2) | 2(18.2) | |||
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| Single | 84(41.2) | <0.01 | 86(43.92) | 0.03 | 87(45.1) | 0.65 |
| Married | 131(56.0) | 121(54.3) | 122(55.0) | |||
| Devoiced | 14(60.9) | 15(71.4) | 14(70.0) | |||
| Windowed | 8(66.7) | 7(58.3) | 7(58.3) | |||
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| Rural | 97(44.1) | 0.02 | 98(46.7) | 0.15 | 98(47.3) | 0.14 |
| Urban | 137(54.4) | 129(53.5) | 130(54.5) | |||
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| Primary and below | 36(56.3) | 0.25 | 37(60.7) | 0.14 | 37(60.7) | 0.15 |
| Middle school | 135(50.8) | 129(51.2) | 129(52.4) | |||
| College and above | 59(44.4) | 58(45.3) | 59(45.7) | |||
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| Yes | 175(48.3) | 0.33 | 175(49.7) | 0.41 | 175(50.6) | 0.45 |
| No | 61(53.5) | 56(54.4) | 57(54.8) | |||
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| SPB | 65(32.8) | <0.01 | 113(71.5) | <0.001 | 113(73.4) | <0.01 |
| JLP | 124(69.7) | 65(33.9) | 65(33.9) | |||
| YZQ | 49(49.0) | 53(50.5) | 54(51.9) | |||
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| <2PL | 78(41.9) | 0.02 | 73(41.2) | 0.02 | 75(42.4) | <0.01 |
| 3-Feb | 6(46.2) | 5(38.5) | 6(46.2) | |||
| >3PL | 146(55.1) | 148(58.0) | 146(58.4) | |||
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| No | 89(54.6) | 0.13 | 94(59.9) | <0.01 | 94(60.3) | <0.01 |
| Sometimes | 110(48.5) | 104(48.1) | 105(49.3) | |||
| Often | 32(41.0) | 29(38.7) | 29(39.2) | |||
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| Non-smoking | 146(49.8) | 0.29 | 139(49.6) | 0.71 | 139(50.9) | 0.62 |
| Smoking | 60(46.5) | 64(51.2) | 64(50.4) | |||
| Quit | 32(59.3) | 28(56.0) | 29(58.0) | |||
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| Non-drinking | 160(49.7) | 0.97 | 157(50.9) | 0.76 | 157(51.8) | 0.79 |
| Drinking | 49(49.0) | 49(51.6) | 49(50.5) | |||
| Quit | 25(51.0) | 22(47.8) | 23(50.0) | |||
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| New | 224(51.4) | 0.69 | 219(52.1) | 0.89 | 220(53.5) | 0.82 |
| Retreatment | 5(45.5) | 5(50.0) | 5(50.0) | |||
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| Negative | 76(68.5) | <0.01 | 69(65.1) | <0.01 | 69(65.1) | <0.01 |
| Positive | 154(45.7) | 155(47.7) | 156(49.4) | |||
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| Yes | 231(51.6) | <0.01 | 225(52.4) | <0.01 | 226(53.4) | <0.01 |
| No | 5(17.9) | 6(23.1) | 6(22.2) | |||
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| Yes | 157(63.6) | <0.01 | 149(63.9) | <0.01 | 151(64.3) | <0.01 |
| No | 78(34.5) | 81(37.0) | 80(37.7) | |||
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| Yes | 54(41.9) | 0.02 | 55(44.4) | 0.88 | 55(44.7) | 0.07 |
| No | 182(52.6) | 176(53.3) | 177(54.3) | |||
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| TB hospital | — | — | 16(40.0) | 0.15 | 16(41.0) | 0.17 |
| Non-TB hospital | — | 215(51.8) | 216(52.6) | |||
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| 1 | — | — | 22(39.3) | <0.01 | 22(40.7) | <0.01 |
| 2 | — | 171(49.1) | 172(50.0) | |||
| ≥3 | — | 38(74.5) | 38(73.1) | |||
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| No | — | — | 21(63.6) | 0.13 | 21(67.7) | 0.62 |
| Yes | — | 209(49.8) | 210(50.4) | |||
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| No | — | — | 163(48.8) | 0.14 | 163(49.2) | 0.085 |
| Yes | — | 68(56.7) | 69(58.5) | |||
|
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| Yes | 62(40.3) | <0.01 | 59(39.1) | <0.01 | 59(40.4) | 0.02 |
| No | 170(53.5) | 168(56.0) | 169(56.3) | |||
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| Yes | 214(50.0) | 0.77 | 206(50.2) | 0.32 | 208(51.5) | 0.36 |
| No | 22(47.8) | 25(58.1) | 24(58.5) | |||
Notes:
Missing data were excluded.
“—”refers this variable was not included in the logistic model for this independent variable.
PL refers to local poverty line which is 3480 RMB Yuan per year since 2010; TB refers to tuberculosis.
AFB smear status refers to Acid-Fast Bacilli (AFB) Smear status.
Multivariate analysis for factors associated with delay.
| Variable | Delay≥12.5 days | Total detection delay Delay≥30 days | Delay in initiatingtreatment≥31 days†AOR(95%CI) |
|
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| Single | Reference | Reference | : |
| Married | 0. 5(0.1, 2.1) | 1.2 (0.2, 9.6) | : |
| Devoiced | 0.5 (0.1, 2.5) | 0.9 (0.1, 7.4) | : |
| Windowed | 0.6(0.1, 3.4) | 1.1(0.7, 1.7) | : |
|
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| SPB | Reference | : | : |
| JLP | 3.3(1.8, 5.9) | : | : |
| YZQ | 0.7 (0.4, 1.3) | : | : |
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| Rural | Reference | : | : |
| Urban | 1.5(0.9, 2.3) | : | : |
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| ≤2PL | : | Reference | Reference |
| 2–3 | : | 0.4(0.8, 2.1) | 0.7(0.1, 3.7) |
| >3PL | : | 1.2 (0. 9, 1.6) | 1.2(0.88, 1.6) |
|
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| No | : | Reference | Reference |
| Sometimes | : | 0.4 (0. 9, 5.0) | 0.1(0.1, 4.2) |
| often | : | 0.67(0.5, 1.0) | 0. 7(0.4,1.0) |
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| Positive | Reference | Reference | Reference |
| Negative | 1.8 (1.1, 3.0) | 1.0 (0.5, 2.1) | 0.9 (0.5, 1.9) |
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| 1 | : | Reference | Reference |
| 2 | : | 0.3(0.1, 1.0) | 0.3(0.2, 1.1) |
| ≥3 | : | 1. 9(1.1, 3.3) | 1.9(1.1, 3.4) |
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| Yes | Reference | Reference | Reference |
| No | 1.3(0.8, 2.1) | 1.5 (0.8, 2.8) | 1. 6(0.8, 2. 9) |
| Cough | |||
| No | Reference | Reference | Reference |
| Yes | 3.3 (2.3, 4.8) | 1.7(0.9, 2.9) | 0.9 (0.5, 1.6) |
|
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| Yes | Reference | : | : |
| No | 1.3 (0.8, 2.1) | : | : |
Note:
Missing data were excluded.
*Adjusted for age and gender.
Adjusted for age, gender, residence, district† Adjusted by age, gender, residence, district.
refers this variable was not included in the logistic model for this independent variable.
PL refers to local poverty line which is 3480 RMB Yuan per year since 2010; TB refers to tuberculosis.
AFB smear status refers to Acid-Fast Bacilli (AFB) Smear status.
Figure 4Adherence to treatment, self-reported reasons for non-adherence, and treatment supervision among TB patients in Chongqing, China.
This figure presented the adherence to anti-TB treatment(A), self-reported reasons for missed dose (B), self-reported reasons for interrrupted treatment(C), self-reported reasons for lack of follow-up exam(D) and treatment supervision by HCWs of different levels(E).
Figure 5TB knowledge and access to TB health promotion among TB patients in Chongqing, China.
This figure demonstrated current TB knowledge of TB patients (A) and access to TB health education before TB diagnosis (B).