| Literature DB >> 33713630 |
Nga T T Do1, Huong T L Vu1, Chuc T K Nguyen2, Sureeporn Punpuing3, Wasif Ali Khan4, Margaret Gyapong5, Kwaku Poku Asante6, Khatia Munguambe7, F Xavier Gómez-Olivé8, Johannes John-Langba9, Toan K Tran2, Malee Sunpuwan3, Esperanca Sevene7, Hanh H Nguyen2, Phuc D Ho10, Mohammad Abdul Matin4, Sabeena Ahmed4, Mohammad Mahbubul Karim4, Olga Cambaco11, Samuel Afari-Asiedu6, Ellen Boamah-Kaali6, Martha Ali Abdulai6, John Williams12, Sabina Asiamah12, Georgina Amankwah12, Mary Pomaa Agyekum12, Fezile Wagner8, Proochista Ariana13, Betuel Sigauque11, Stephen Tollman8, H Rogier van Doorn14, Osman Sankoh15, John Kinsman16, Heiman F L Wertheim17.
Abstract
BACKGROUND: Antimicrobial misuse is common in low-income and middle-income countries (LMICs), and this practice is a driver of antibiotic resistance. We compared community-based antibiotic access and use practices across communities in LMICs to identify contextually specific targets for interventions to improve antibiotic use practices.Entities:
Year: 2021 PMID: 33713630 PMCID: PMC8050200 DOI: 10.1016/S2214-109X(21)00024-3
Source DB: PubMed Journal: Lancet Glob Health ISSN: 2214-109X Impact factor: 26.763
Key demographic indicators and antibiotic access at surveyed sites
| Bangladesh | Mozambique | Vietnam | Ghana | Thailand | South Africa | ||
|---|---|---|---|---|---|---|---|
| Site name | Matlab | Manhica | Filabavi | Dodowa; Kintampo | Kanchanaburi | Agincourt | |
| Site population | 225 000 | 165 346 | 262 000 | 117 341; 142 977 | 59 966 | 120 000 | |
| Under-5 mortality per 1000 livebirths (year) | 37·4 (2011) | 76·1 (2014) | 8·4 (2011) | 32·8 (2011); 62·6 (2011) | 8·5 (2009) | 48·0 (2009) | |
| Number of antibiotics suppliers | 301 | 47 | 502 | 122 | 293 | 15 | |
| Non-licensed, n (%) | 156 (52%) | 10 (21%) | 325 (65%) | 5 (4%) | 0 | 0 | |
| Private, n (%) | 278 (92%) | 18 (38%) | 467 (93%) | 97 (80%) | 278 (95%) | 3 (20%) | |
Mean data for both sites are presented. Separate data for each site are provided in the appendix (p 11).
Care-seeking behaviours among households included in the household survey—first point of contact when household members were unwell
| N | 4424 | 985 | 3627 | 9742 | 3707 | 2422 |
| Drug store | 4024 (91·0%) | 57 (5·8%) | 2630 (72·5%) | 4967 (51·0%) | 1548 (41·8%) | 10 (0·4%) |
| Private facility | 36 (0·8%) | 35 (3·6%) | 241 (6·6%) | 978 (10·0%) | 1134 (30·6%) | 90 (3·7%) |
| Public facility | 327 (7·4%) | 797 (80·9%) | 411 (11·3%) | 2840 (29·2%) | 920 (24·8%) | 2303 (95·1%) |
| Other | 37 (0·8%) | 96 (9·7%) | 347 (9·5%) | 957 (9·8%) | 105 (2·8%) | 19 (0·8%) |
| N | 4419 | 984 | 3629 | 9746 | 3706 | 2422 |
| Drug store | 28 (0·6%) | 9 (0·9%) | 5 (0·1%) | 218 (2·2%) | 2 (0·1%) | 8 (0·3%) |
| Private facility | 1672 (37·8%) | 29 (2·9%) | 841 (23·2%) | 1714 (17·6%) | 590 (15·9%) | 126 (5·2%) |
| Public facility | 2716 (61·5%) | 907 (92·2%) | 2690 (74·1%) | 7111 (73·0%) | 3093 (83·5%) | 2275 (93·9%) |
| Other | 3 (0·1%) | 39 (4·0%) | 93 (2·6%) | 703 (7·2%) | 21 (0·6%) | 13 (0·5%) |
Data are n (%), unless otherwise specified.
The number of responses for the most common first point of contact for the individual household members in each site.
Most common first point of contact.
Includes communal health stations.
Figure 1Reasons for choosing the selected first point of contact in case of mild and severe illness for household members
For mild illness in Ghana and Thailand, more than one option was selected in similar proportions to those shown.
Family use of antibiotics in the previous month in the first survey round and associated factors
| Bangladesh | 498/1009 (49·4%) | 511/1009 (50·6%) | 1 (ref) | .. |
| Mozambique | 161/639 (25·2%) | 478/639 (74·8%) | 0·59 (0·46–0·75) | <0·0001 |
| Vietnam | 416/925 (45·0%) | 509/925 (55·0%) | 0·71 (0·56–0·89) | 0·0038 |
| Ghana (Kintampo) | 465/1100 (42·3%) | 635/1100 (57·7%) | 0·73 (0·57–0·94) | 0·014 |
| Ghana (Dodowa) | 263/847 (31·1%) | 584/847 (68·9%) | 0·50 (0·39–0·65) | <0·0001 |
| Thailand | 294/1053 (27·9%) | 759/1053 (72·1%) | 0·50 (0·39–0·64) | <0·0001 |
| South Africa | 63/616 (10·2%) | 553/616 (89·8%) | 0·21 (0·15–0·29) | <0·0001 |
| 1–4 | 1050/3553 (29·6%) | 2503/3553 (70·4%) | 1 (ref) | .. |
| >4 | 1108/2624 (42·2%) | 1516/2624 (57·8%) | 1·00 (1·00–1·00) | 0·38 |
| Male | 592/1853 (31·9%) | 1261/1853 (68·1%) | 1 (ref) | .. |
| Female | 1559/4314 (36·1%) | 2755/4314 (63·9%) | 1·09 (0·99–1·20) | 0·082 |
| Secondary school or higher | 1706/4727 (36·1%) | 30 201/4727 (63·9%) | 1 (ref) | .. |
| Primary school or less | 454/1462 (31·1%) | 1008/1462 (68·9%) | 0·95 (0·84–1·06) | 0·34 |
| Free health insurance | 963/2937 (32·8%) | 1974/2937 (67·2%) | 1 (ref) | .. |
| Paid health insurance | 388/1094 (35·5%) | 706/1094 (64·5%) | 0·98 (0·84–1·13) | 0·76 |
| Out-of-pocket payment | 809/2158 (37·5%) | 1349/2158 (62·5%) | 0·82 (0·70–0·96) | 0·013 |
| Public hospitals | 965/3208 (30·1%) | 2243/3208 (69·9%) | 1 (ref) | .. |
| Private hospitals | 632/1782 (35·5%) | 1150/1782 (64·5%) | 1·13 (0·97–1·32) | 0·11 |
| Drug stores | 419/822 (51·0%) | 403/822 (49·0%) | 1·26 (1·07–1·47) | 0·0054 |
| Other options | 144/377 (38·2%) | 233/377 (61·8%) | 1·16 (0·86–1·57) | 0·33 |
| Public hospitals | 1011/3311 (30·5%) | 2300/3311 (69·5%) | 1 (ref) | .. |
| Private hospitals | 473/1336 (35·4%) | 863/1336 (64·6%) | 0·96 (0·83–1·13) | 0·64 |
| Drug stores | 487/1086 (44·8%) | 599/1086 (55·2%) | 0·96 (0·82–1·13) | 0·64 |
| Other suppliers | 189/456 (41·4%) | 267/456 (58·6%) | 1·21 (0·91–1·61) | 0·19 |
| Convenience | 612/1782 (34·3%) | 1170/1782 (65·7%) | 1 (ref) | .. |
| Trust | 846/2320 (36·5%) | 1474/2320 (63·5%) | 1·01 (0·90–1·14) | 0·81 |
| Cost | 491/1501 (32·7%) | 1010/1501 (67·3%) | 1·02 (0·89–1·16) | 0·79 |
| Other factors | 211/586 (36·0%) | 375/586 (64·0%) | 0·95 (0·77–1·17) | 0·64 |
| Health-care facilities | 495/1817 (27·2%) | 1322/1817 (72·8%) | 1 (ref) | .. |
| Drug stores | 798/1969 (40·5%) | 1171/1969 (59·5%) | 1·17 (1·03–1·33) | 0·016 |
| Print materials | 163/540 (30·2%) | 377/540 (69·8%) | 1·23 (1·02–1·50) | 0·034 |
| Other sources | 704/1863 (37·8%) | 1159/1863 (62·2%) | 1·07 (0·94–1·23) | 0·32 |
| 0 | 226/1073 (21·1%) | 847/1073 (78·9%) | 1 (ref) | .. |
| 1 | 746/1979 (37·7%) | 1233/1979 (62·3%) | 1·43 (1·23–1·67) | <0·0001 |
| 2 | 340/830 (41·0%) | 490/830 (59·0%) | 1·66 (1·38–1·99) | <0·0001 |
| 3 | 353/951 (37·1%) | 598/951 (62·9%) | 1·65 (1·37–1·98) | <0·0001 |
| 4 | 482/1315 (36·7%) | 833/1315 (63·3%) | 1·54 (1·28–1·85) | <0·0001 |
Other comparisons across the two sites in Ghana are presented in the appendix (appendix p 11). OR=odds ratio.
ORs are adjusted using a generalised linear model that include all the listed variables.
Figure 2Reported indications for antibiotics obtained at drug suppliers through exit interviews and reported antibiotic use by household members in the past month, obtained through household surveys
Bars represent counts of individuals with specific indication, counts are not mutually exclusive except for the “Others” category. Respiratory category includes throat, cough, nose, chest pain, and dyspnoea symptoms. Systemic category includes headache, non-localised pain, weakness, and fever symptoms. Genitourinary category includes sexually transmitted infections, gynaecological, male genital, and urinary tract infection.