Introduction
Diabetes in Bangladesh
Health systems in Bangladesh
Evidence on quality and access to diabetes care in Bangladesh
Methods
Setting
Facility | Health workers | Training on diabetes | Equipment | Patients seen/month (number of people with diabetes seen) and opening hours |
---|---|---|---|---|
Bolmari Upazilla | ||||
1 Upazilla health complex: Government | Doctors, nurses, medical assistants | Doctors received training on diabetes as part of their medical training | Blood monitoring and testing equipment available | 5000–8000 (300) 24 h/day 7/7 days |
4 community clinics: Government | Community Health Care Provider | No training | One of the community clinics reported having a glucometer | 800–1000 (8–12 in two clinics) 9 am-3 pm 6/7 days in 1 clinic Not reported in 3 clinics |
25 Pharmacies: Private | ‘Village’ doctors (untrained health worker) | No training | 11 of the pharmacies reported having glucometers | 150–200 (2–10: in 10 pharmacies) 9 am-8 pm 7/7 days |
Saltha Upazilla | ||||
No upazilla level health complex | ||||
1 Health and Family Welfare Centre: Government | Sub-assistant community medical officer, Family and welfare provider (2 staff total) | No training | No equipment for testing or monitoring diabetes | 750–800 (No people with diabetes reported) 8–2.30 pm 6/7 days |
3 community clinics: Government | Community Health Care Provider (typically 1/clinic) | No training | One of the community clinics had a glucometer | 700–900 (No people with diabetes reported) 9-3 pm 6/7 days in 1 clinic Not recorded in 2 clinics |
16 Pharmacies: Private | ‘Village’ doctor (untrained health worker), 1 pharmacy also had a homeopathic practitioner Typically 1/ facility | No training | 8 of the pharmacies reported having glucometers | 50–200 (8–30 in pharmacies with glucometers) 9 am-8 pm 7/7 days |
Nagarkanda Upazilla | ||||
1 Upazilla health complex: Government | Doctors, nurses, medical assistants | Doctors received training on diabetes as part of their medical training | Blood monitoring and testing equipment available | 10,000–15,000 (300) 24 h 7/7 days |
1 Health and Family Welfare Centre: Government | Sub-assistant community medical officer (1 staff) | No training | No equipment for testing or monitoring diabetes | 80–100 (No people with diabetes reported) 8–2.30 pm 6/7 days |
3 Community clinics (cc): Government | Community Health Care Provider (Typically 1/clinic) | No training | No equipment for testing or monitoring diabetes | 800–1000 (0) 9-3 pm 6/7 day in 1 clinic. 2 clinics – not reported |
12 Pharmacies: Private | ‘Village’ doctors (untrained health worker) (Typically 1/facility) | No training | 7 of the pharmacies reported having glucometers | 100–200 (15–30 in pharmacies with glucometers) 9 am-8 pm 7/7 days |
Modhukali Upazilla | ||||
1 Upazilla health complex: Government | Doctors, nurses, medical assistants | Doctors received training on diabetes as part of their medical training | Blood monitoring and testing equipment available | 10,00–15,000 (300) 24 h 7/7 days |
1 Health and Family Welfare Centre: Government | Sub-assistant community medical officer, Family and welfare provider (2 staff in total) | No training | No equipment for testing or monitoring diabetes | 800–1000 (No people with diabetes reported) 8–2.30 pm 6/7 days |
3 Community clinics: Government | Community Health Care Provider (typically 1/clinic) | No training | One of the community clinics had a glucometer | 800–1000 each (8–10 in one clinic, not reported in others) 9-3 pm 6/7 days in 1 clinic Not reported in two clinics |
16 Pharmacies: Private | ‘Village’ doctors (untrained health worker) (typically 1/facility) | No training | 8 of the pharmacies reported having glucometers | 50–200 (5–25 in pharmacies with glucometers) 9 am-8 pm 7/7 days |
Study aim, objectives and design
Quantitative data collection, management and analysis
Qualitative research data collection, management and analysis
Ethics
Results
Quantitative results: care seeking practices of people with diabetes in rural Bangladesh by gender and socioeconomic status
No prior diagnosis of diabetes (N (%)) | Prior diagnosis of diabetes (N (%)) | Crude odds ratio (95%CI) | Adjusteda odds ratio (95% CI) | |
---|---|---|---|---|
Sex | ||||
Male | 352 (70.7%) | 146 (29.3%) | Ref | Ref |
Female | 581 (79.9%) | 146 (20.1%) | 0.61 (0.46–0.79) | 0.53 (0.33–0.86) |
Wealth | ||||
Most poor | 193 (78.8%) | 52 (21.2%) | Ref | Ref |
Very poor | 208 (84.9%) | 37 (15.1%) | 0.66 (0.41–1.05) | 0.60 (0.37–0.96) |
Poor | 203 (82.9%) | 42 (17.1%) | 0.77 (0.49–1.05) | 0.59 (0.37–0.94) |
Less poor | 181 (73.3%) | 66 (26.7%) | 1.35 (0.89–1.05) | 0.89 (0.57–1.39) |
Least poor | 148 (60.9%) | 95 (39.1%) | 2.38 (1.60–3.55) | 1.22 (0.77–1.92) |
Age group | ||||
30–39 | 256 (86.8%) | 39 (13.2%) | Ref | Ref |
40–49 | 230 (76.9%) | 69 (23.1%) | 1.97 (1.28–3.03) | 2.20 (1.40–3.44) |
50–59 | 181 (69.1%) | 81 (30.9%) | 2.94 (1.92–4.50) | 3.10 (1.94–4.90) |
60–69 | 173 (70.6%) | 72 (29.4%) | 2.73 (1.77–4.22) | 2.76 (1.68–4.54) |
70 and up | 93 (75.0%) | 31 (25.0%) | 2.19 (1.29–3.71) | 2.09 (1.11–3.94) |
Occupation | ||||
Unemployed/ retired/housewife | 612 (76.8%) | 185 (23.2%) | Ref | Ref |
Manual | 213 (82.6%) | 45 (17.4%) | 0.70 (0.49–1.00) | 0.41 (0.24–0.70) |
Professional/Business | 108 (63.5%) | 62 (36.5%) | 1.90 (1.33–2.70) | 0.75 (0.44–1.28) |
Education | ||||
No formal education | 483 (82.0%) | 106 (18.0%) | Ref | Ref |
Incomplete primary | 176 (79.3%) | 46 (20.7%) | 1.20 (0.81–1.75) | 1.32 (0.87–2.00) |
Completed at least primary | 274 (66.2%) | 140 (33.8%) | 2.33 (1.74–3.12) | 2.13 (1.47–3.80) |
Marital status | ||||
Unmarried | 137 (77.8%) | 39 (22.2%) | Ref | Ref |
Married | 796 (75.9%) | 253 (24.1%) | 1.12 (7.61–1.64) | 0.98 (0.62–1.56) |
Religion | ||||
Non-Muslim | 88 (65.7%) | 46 (34.3%) | Ref | Ref |
Muslim | 845 (77.5%) | 246 (22.6%) | 0.56 (0.38–0.82) | 0.71 (0.47–1.08) |
Receives medical advice and/or medication | Takes oral medication for diabetes | Takes Insulin for diabetes | Blood sugar tested (in the last month) | Ever used non-allopathic treatment | Experiences complications | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | N (%) | Crude OR (95% CI) | Adjusted ORb (95% CI) | ||
Sex | Men [n = 146] | 128 (87.7%) | Ref | Ref | 119 (81.5%) | Ref | Ref | 78 (53.4%) | Ref | Ref | 38 (26.0%) | Ref | Ref | 17 (11.6%) | Ref | Ref | 107 (73.3%) | Ref | Ref |
Women [n = 146] | 124 (84.9%) | 0.79 (0.41–1.55) | 0.87 (0.26–2.88) | 116 (79.5%) | 0.88 (0.49–1.57) | 1.03 (0.38–2.79) | 72 (49.3%) | 0.85 (0.54–1.34) | 0.53 (0.23–1.22) | 26 (17.1%) | 0.62 (0.35–1.08) | 0.95 (0.36–2.50) | 10 (6.8%) | 0.56 (0.25–1.30) | 0.80 (0.17–3.76) | 108 (74.0%) | 1.04 (0.62–1.74) | 1.10 (0.45–2.71) | |
Wealth | Most poor [n = 52] | 43 (82.7%) | Ref | Ref | 43 (82.7%) | Ref | Ref | 22 (51.2%) | Ref | Ref | 9 (17.3%) | Ref | Ref | 5 (11.6%) | Ref | Ref | 40 (76.9%) | Ref | Ref |
Very poor [n = 37] | 30 (81.1%) | 0.90 (0.30–2.67) | 0.95 (0.31–2.94) | 27 (73.0%) | 0.57 (0.20–1.57) | 0.58 (0.20–1.68) | 17 (46.0%) | 1.15 (0.50–2.71) | 1.42 (0.58–3.44) | 4 (10.8%) | 0.58 (0.16–2.05) | 0.54 (0.15–2.00) | 4 (13.3%) | 1.14 (0.28–4.57) | 0.94 (0.22–4.03) | 30 (81.1%) | 1.29 (0.45–3.66) | 1.41 (0.48–4.15) | |
Poor [n = 42] | 34 (81.0%) | 0.89 (0.31–2.55) | 0.99 (0.32–3.06) | 31 (73.8%) | 0.59 (0.22–1.59) | 0.64 (0.22–1.90) | 18 (42.9%) | 1.02 (0.45–2.32) | 1.38 (0.57–3.33) | 5 (11.9%) | 0.65 (0.20–2.10) | 0.56 (0.16–1.93) | 5 (14.7%) | 1.27 (0.34–4.72) | 0.81 (0.20–3.31) | 27 (64.3%) | 0.54 (0.22–1.33) | 0.68 (0.26–1.78) | |
Less poor [n = 66] | 59 (89.4%) | 1.76 (0.61–5.11) | 1.77 (0.55–5.67) | 54 (81.8%) | 0.94 (0.36–2.44) | 0.94 (0.33–2.66) | 37 (56.1%) | 1.73 (0.83–3.63) | 2.68 (1.17–6.15) | 16 (24.2%) | 1.53 (0.61–3.81) | 1.30 (0.47–3.50) | 7 (11.9%) | 1.12 (0.33–3.74) | 0.81 (0.21–3.13) | 46 (69.7%) | 0.69 (0.30–1.59) | 0.75 (0.30–1.87) | |
Least poor [n = 95] | 86 (90.5%) | 2.00 (0.74–5.40) | 1.72 (0.55–5.39) | 80 (84.2%) | 1.11 (0.45–2.76) | 0.96 (0.34–2.70) | 56 (59.0%) | 1.96 (0.99–3.89) | 3.23 (1.43–7.27) | 30 (31.6%) | 2.21 (0.95–5.10) | 1.90 (0.72–4.94) | 6 (5.2%) | 0.63 (0.18–2.19) | 0.41 (0.10–1.73) | 72 (75.8%) | 0.94 (0.42–2.09) | 1.06 (0.42–2.64) | |
Total (%) | 292 (100%) | 252 (86.3%) | 235 (80.5%) | 150 (51.3%) | 64 (21.9%) | 27 (9.2%) | 215 (73.6%) |
Qualitative results: experiences of care seeking (access and quality)
Access: initial diagnosis and availability of services
“My doctor prescribed medication [for fever and weakness] but my health didn’t improve..…..so I went to Faridpur, but the doctor was not there. So I went to another doctor who did blood tests. He later told me I had typhoid, and I was also suffering from diabetes”Men’s FGD(013)
Access: cost and distance
“The visits are difficult for me. My home is at the far end of Nagarkondha and I have to go to Faridpur. The travel causes me much pain”Diabetic man SSI026
“It costs 50 taka [approx. 1USD] to go to Faridpur [one way]. It is difficult for a poor person to spend 100 taka [2USD] on a check-up. If a farmer or a day labourer goes to the hospital s/he does not earn their livelihood that day. They also pay for the doctor’s bills, tests and medicine”Health worker SSI010
“I was given a course of treatment [at the diabetic hospital] and felt a little better and came back home. I did not go for further check-ups after that as my husband was abroad.”Woman’s FGD(021)
Acceptability of care: experiences of health services
“the diabetes hospital is the best option to receive treatment for diabetes. They will give proper guidelines and a diet plan”Woman diabetic SSI015
“It takes a long time. They take blood, urine. So we have to wait…sometimes it takes a whole day.”Women’s FGD029
Acceptability of care: trust in health workers
“I came to know of him [her doctor] as everyone in this area likes him. We did not know anyone for diabetes. But people suggested that we go to him”Woman diabetic SSI025
Participant 1: The most corruption right now is in the health department.Participant 2: Yes…among the doctors….they are taking money that you do not even understand.Participant 1: this is 500 taka and that is 2700 taka, they take money for nothingMen’s FGD(023)
“if a patient gets well because of me then that is important to me as a doctor. And if you talk nicely with the patients they are able to understand. It is due to this that I have attained a place here”Health worker SSI028
Qualitative results: care-seeking practices (check-ups, advice and medication)
Care received: medical check-ups and behavioural advice
“We maintain rules, he [the doctor] tells me ‘eat a little, try to eat ruti two times a day and do some walking…and take medicine’”Woman’s FGD11
Medication adherence
“But as I am a poor woman, sometimes if I feel good I don’t buy the medicines and I do not take them”Woman participant SSI025
Non-allopathic medication
“taking bitter leaves may control diabetes. The juice from the leaves work, but not fully.”Men’s FGD13
“If one is active and takes medicine – allopathic, homeopathic or herbal – then your physical condition will be good”Health care worker SSI010