| Literature DB >> 28521791 |
Philip Emeka Anyanwu1, John Fulton2, Etta Evans2, Timothy Paget2.
Abstract
BACKGROUND: Malaria remains a global health issue with the burden unevenly distributed to the disadvantage of the developing countries of the world. Poverty contributes to the malaria burden as it has the ability to affect integral aspects of malaria control. There have been renewed efforts in the global malaria control, resulting in reductions in the global malaria burden over the last decade. However, the development of resistance to artemisinin-based combination therapy threatens the sustainability of the present success in malaria control. Anti-malarial drug use practices/behaviours remain very important drivers of drug resistance. This study adopted a social epidemiological stance in exploring the underlying socioeconomic factors that determine drug use behaviours promoting anti-malarial drug resistance.Entities:
Keywords: Antimalarial drugs; Behaviour; Drug resistance; Drug use; Education; Malaria; Socioeconomic factors; Treatment seeking
Mesh:
Substances:
Year: 2017 PMID: 28521791 PMCID: PMC5437569 DOI: 10.1186/s12936-017-1849-1
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Fig. 1Map of Nigeria with study areas highlighted in green
Key terms used and their meaning in the context of this study
| Terms | Meanings |
|---|---|
| Pharmacy | Used to refer to the registered pharmacy shops that are usually found in the cities. These shops are usually owned or run by a trained pharmacist. Some pharmacies in Nigeria are however run by pharmacy attendants or nurses |
| Chemist/drug vendors | Used to refer to drug vendors or patent medicine vendors in the study setting. These are usually traders with little or no pharmaceutical trainings who either hawk or sell drugs in a small shop. They are mostly common in the rural and suburban areas in Nigeria. The term chemist and drug vendors were used interchangeably in this study |
Socio-demographic description of participants
| Characteristics | Number (%) |
|---|---|
| Total no. of participants | 15 (100) |
| Household heads [ | |
| Drug vendor [ | |
| Pharmacy attendant [ | |
| Sex | |
| Males | 7 (46.7) |
| Females | 8 (53.3) |
| Age | |
| Mean age | 40 |
| Mode age | 31 |
| Relationship status | |
| Single | 3 (20) |
| Married | 6 (40) |
| Widowed | 6 (40) |
| Educational level | |
| No formal education | 1 (6.7) |
| Some primary school education | 3 (20) |
| Some secondary school education | 2 (13.3) |
| O’level/SSCE holder | 2 (13.3) |
| Tertiary education/degree | 4 (26.7) |
| Post graduate degree | 3 (20) |
| Income level | |
| Below ₦18,000 (£63) | 7 (46.7) |
| ₦18,000 to ₦50,000 (£64 to £177) | 1 (6.7) |
| ₦50,001 to ₦100,000 (£178 to £355) | 2 (13.3) |
| ₦100,001 to ₦300,000 (£356 to £1065) | 3 (20) |
| Above ₦300,000 (£1065) | 2 (13.3) |
| Type of settlement | |
| Urban | 7 (46.7) |
| Owerri in Imo state [ | |
| Abuja Municipal city [ | |
| Rural | 8 (53.3) |
| Nkwumeato community in Imo state [ | |
| Zuba community in Abuja [ | |
Fig. 2Adapted Donabedian model showing study findings