| Literature DB >> 28335816 |
Khadija Said1,2,3, Jerry Hella4,5,6, Grace Mhalu4,5,6, Mary Chiryankubi7, Edward Masika7, Thomas Maroa4, Francis Mhimbira4,5,6, Neema Kapalata7, Lukas Fenner8,9,10,11.
Abstract
BACKGROUND: Tanzania is among the 30 countries with the highest tuberculosis (TB) burdens. Because TB has a long infectious period, early diagnosis is not only important for reducing transmission, but also for improving treatment outcomes. We assessed diagnostic delay and associated factors among infectious TB patients.Entities:
Keywords: Diagnostic delay; Geographic information system; Health-seeking; Pharmacy; Tanzania; Transmission; Tuberculosis
Mesh:
Year: 2017 PMID: 28335816 PMCID: PMC5364704 DOI: 10.1186/s40249-017-0276-4
Source DB: PubMed Journal: Infect Dis Poverty ISSN: 2049-9957 Impact factor: 4.520
Fig. 1Flow chart of patient selection
Fig. 3Association between health-seeking behaviour and geographical distances to pharmacies. The regression coefficient plot (with corresponding 95% confidence intervals) shows the association of the Euclidean distance between participants’ households to the nearest pharmacy with purchase of medication prior to TB diagnosis, diagnostic delay (> 3 weeks), and visit of any HCF before TB diagnosis. Odds Ratios (OR) above 1 indicate that the factor is more likely with increasing distance away from the nearest pharmacy, and an OR below 1 that the factor is more likely the closer the household is to a pharmacy. HCF, health care facility
Patient characteristics of new smear-positive adult pulmonary tuberculosis (TB) cases in the Temeke District, Dar es Salaam, Tanzania
| Variable | All | Delay duration | Prior medication | HC facility visits | |||
|---|---|---|---|---|---|---|---|
|
| (weeks) | ||||||
|
| ≤ 3 | > 3 | Not used | Used | ≤ 2 visits | > 2 visits | |
| Total | 513 (100) | 406 (79) | 107 (21) | 52 (10) | 461 (90) | 297 (58) | 216 (42) |
| Age, years | |||||||
| 18–24 | 91 (18) | 73 (18) | 18 (17) | 6 (12) | 85 (18) | 58 (20) | 33 (15) |
| 25–45 | 333 (65) | 264 (65) | 69 (64) | 37 (71) | 296 (64) | 199 (67) | 134 (59) |
| > 45 | 89 (17) | 69 (17) | 20 (19) | 9 (17) | 80 (17) | 40 (13) | 49 (23) |
| Sex | |||||||
| Male | 353 (69) | 280 (69) | 73 (68) | 38 (73) | 315 (68) | 209 (70) | 144 (67) |
| Female | 160 (31) | 126 (31) | 34 (32) | 14 (27) | 146 (32) | 88 (30) | 72 (33) |
| HIV status | |||||||
| Positive | 146 (28) | 119 (29) | 27 (25) | 16 (31) | 130 (28) | 73 (25) | 73 (34) |
| Negative | 367 (72) | 287 (71) | 80 (75) | 36 (69) | 331 (72) | 224 (75) | 143 (66) |
| Education | |||||||
| No education | 92 (18) | 73 (18) | 19 (18) | 8 (15) | 84 (18) | 46 (15) | 46 (21) |
| Primary/Secondary | 404 (79) | 316 (78) | 88 (82) | 44 (85) | 360 (78) | 243 (82) | 161 (75) |
| University | 17 (3) | 17 (4) | 0 (0) | 0 (0) | 17 (4) | 8 (3) | 9 (4) |
| Occupation | |||||||
| Unemployed or h/wife | 103 (20) | 86 (21) | 17 (16) | 4 (8) | 99 (21) | 46 (15) | 57 (26) |
| Unskilled labour | 69 (13) | 52 (13) | 17 (16) | 11 (21) | 58 (13) | 38 (13) | 31 (14) |
| Semiskilled labour | 341 (67) | 268 (66) | 73 (68) | 37 (71) | 304 (66) | 213 (72) | 128 (60) |
| Household income | |||||||
| < $200 per month | 408 (80) | 329 (81) | 79 (74) | 37 (71) | 371 (80) | 225 (76) | 183 (85) |
| ≥ $200 per month | 105 (20) | 77 (19) | 28 (26) | 15 (29) | 90 (20) | 72 (24) | 33 (15) |
| BMI category, kg/m2 | |||||||
| < 18.5 | 36 (7) | 29 (7) | 7 (7) | 3 (6) | 33 (7) | 25 (8) | 11 (5) |
| 18–24.9 | 273 (53) | 204 (50) | 69 (64) | 20 (38) | 253 (55) | 163 (55) | 110 (51) |
| 25–29.9 | 154 (30) | 129 (32) | 25 (23) | 19 (37) | 135 (29) | 78 (26) | 76 (35) |
| > 30 | 50 (210) | 44 (11) | 6 (6) | 10 (19) | 40 (9) | 31 (11) | 19 (9) |
| Household size, persons | |||||||
| ≥ 4 | 137 (27) | 123 (30) | 14 (13) | 3 (6) | 134 (29) | 56 (19) | 81 (37) |
| 2–3 | 331 (64) | 256 (63) | 75 (70) | 43 (83) | 288 (63) | 208 (70) | 123 (57) |
| Single | 45 (9) | 27 (7) | 18 (17) | 6 (12) | 39 (8) | 33 (11) | 12 (6) |
| House ownership | |||||||
| Own | 225 (44) | 178 (79) | 47 (21) | 17 (33) | 208 (45) | 127 (43) | 98 (45) |
| Rented | 288 (56) | 228 (79) | 60 (21) | 35 (67) | 253 (55) | 170 (57) | 118 (55) |
| Coughing | |||||||
| No | 2 (0.5) | 2 (0.5) | 0 | 0 (0) | 2 (0.4) | 1 (0.3) | 1 (0.5) |
| Yes | 511 (99.5) | 404 (99.5) | 107 (100) | 52 (100) | 459 (99.6) | 296 (99.7) | 215 (99.5) |
| Fever | |||||||
| No | 38 (7) | 37 (9) | 1 (1) | 3 (6) | 35 (8) | 33 (11) | 5 (2) |
| Yes | 475 (93) | 369 (91) | 106 (99) | 49 (94) | 426 (92) | 264 (89) | 211 (98) |
| Chest pain | |||||||
| No | 102 (20) | 69 (17) | 33 (31) | 40 (77) | 62 (14) | 94 (32) | 8 (4) |
| Yes | 411 (80) | 337 (83) | 74 (69) | 12 (23) | 399 (87) | 203 (68) | 208 (96) |
| Haemoptysis | |||||||
| No | 336 (71) | 324 (80) | 42 (39) | 52 (100) | 314 (68) | 185 (62) | 181 (84) |
| Yes | 147 (29) | 82 (20) | 65 (61) | 0 | 147 (32) | 112 (38) | 35 (16) |
| Night sweat | |||||||
| No | 26 (5) | 25 (6) | 1 (1) | 1 (2) | 25 (5) | 24 (8) | 2 (1) |
| Yes | 487 (95) | 381 (94) | 106 (99) | 51 (98) | 436 (95) | 273 (92) | 214 (99) |
| Unexplained weight loss | |||||||
| No | 20 (4) | 18 (4) | 2 (2) | 1 (2) | 19 (4) | 15 (5) | 5 (2) |
| Yes | 493 (96) | 388 (96) | 105 (98) | 51 (98) | 442 (96) | 282 (95) | 211 (98) |
BMI body mass index, h/wife housewife, TB tuberculosis, HC facility health care facility
Associations of diagnosis delay (defined as > 3 weeks) with socio-demographic and clinical characteristics among new pulmonary TB patients
| Characteristic | Cases | Unadjusted | Adjusted | ||
|---|---|---|---|---|---|
|
|
|
| a |
| |
| Age, years | 0.7 | 0.7 | |||
| 18–24 | 91 (18) | 1 | 1 | ||
| 25–45 | 333 (65) | 1.06 (0.59–1.89) | 0.81 (0.39–1.67) | ||
| > 45 | 189 (17) | 1.18 (0.57–2.41) | 1.08 (0.44–2.66) | ||
| Sex | 0.9 | 0.6 | |||
| Female | 160 (31) | 1 | 1 | ||
| Male | 353 (69) | 0.97 (0.61–1.53) | 0.84 (0.46–1.51) | ||
| HIV status | 0.4 | 0.5 | |||
| Negative | 366 (71) | 1 | 1 | ||
| Positive | 147 (29) | 0.81 (0.50–1.30) | 0.83 (0.46–1.52) | ||
| Occupation | 0.4 | 0.1 | |||
| Unemployed, or h/wife | 103 (20) | 1 | 1 | ||
| Unskilled labor | 69 (13) | 1.65 (0.78–3.52) | 1.24 (0.48–3.26) | ||
| Semiskilled labor | 341 (67) | 1.38 (0.77–2.46) | 0.69 (0.32–1.51) | ||
| Household income | 0.1 | 0.3 | |||
| < $200 per month | 408 (80) | 1 | 1 | ||
| ≥ $200 per month | 105 (20) | 1.51 (0.92–2.49) | 1.34 (0.73–2.47) | ||
| Household size, persons | < 0.001 | 0.2 | |||
| ≥ 4 | 137 (27) | 1 | 1 | ||
| 2–3 | 331 (64) | 2.57 (1.40–4.74) | 1.38 (0.67–2.83) | ||
| Single | 45 (9) | 5.86 (2.60–13.21) | 1.81 (0.71–4.59) | ||
| Visits to a HCF | < 0.001 | 0.9 | |||
| > 2 | 216 (42) | 1 | 1 | ||
| ≤ 2 | 297 (58) | 3.31 (2.01–5.46) | 0.99 (0.52–1.90) | ||
| Prior purchase of medication | 0.001 | 0.01 | |||
| No | 52 (10) | 1 | 1 | ||
| Yes | 461 (90) | 0.37 (0.20–0.68) | 0.31 (0.14–0.71) | ||
| Chest pain | 0.002 | <0.001 | |||
| Yes | 411 (80) | 1 | 1 | ||
| No | 102 (20) | 2.18 (1.34–3.54) | 7.97 (3.15–20.19) | ||
| Hemoptysis | <0.001 | <0.001 | |||
| No | 366 (71) | 1 | 1 | ||
| Yes | 147 (29) | 6.11 (3.87–9.66) | 25.37 (11.15–57.74) | ||
OR odds ratio, aOR adjusted odds ratio, 95% CI, 95% confidence interval, h/wife housewife, HCF health care facility
Model was adjusted for age, sex, HIV status, occupation, house hold income, household size, visit to HCF, prior use of medication, chest pain and hemoptysis
Fig. 2Geographical analyses of health care facilities (HCFs) and pathways to care of patients with tuberculosis (TB) symptoms in the study area, Temeke District, Dar es Salaam, Tanzania. Panel a: Localization of the two governmental TB clinics which serve as recruitment sites in the study area (in red). Panel b: Spatial distribution of pharmacies and HCFs in the study area. Panel c: Five examples of possible pathways to care of patients with TB symptoms seeking care. Various types of HCFs as the entry point into the health care system (single or multiple visits) until final diagnosis at the TB clinic are presented