Medication use by the “quilombola” population: a survey in
          Southwestern Bahia, Brazil

A population-based cross-sectional study was conducted with 797 adult quilombola in Vitória da Conquista, BA, Northeastern Brazil, in 2011. Analysis of variance was used to compare means of drugs by subject, according to demographic, socioeconomic and health-related behavior variables. Prevalence, prevalence ratios and their 95% confidence intervals were estimated. Multivariate analysis was carried out using Poisson regression with robust variance.

RESULTS

The most widely consumed drugs by the population were those for the cardiovascular and nervous systems. Prevalence of medication use was 41.9%, significantly higher among women (50.3%) than men (31.9%). After adjusted analysis, medication use was associated with being female gender, being aged 60 or older, higher economic level, worse self-rated health, greater number of self-reported diseases and number of medical appointments.

CONCLUSIONS

Strategies to improve rational drug use should preferentially focus on women and older adults. Thus, special attention should be given to promote rational prescription in everyday health services.

African Continental Ancestry Group; Drug Utilization; Socioeconomic Factors; Risk Groups; Health Vulnerability; Ethnicity and Health; Cross-Sectional Studies

Correspondence
: Danielle Souto de Medeiros - Instituto Multidisciplinar em Saúde - Universidade Federal da Bahia - Campus Anísio Teixeira - Rua Rio de Contas, 58 Quadra 17 Lote 58 Candeias - 45055-090 Vitória da Conquista, BA, Brasil - E-mail: danielle.medeiros@ufba.br

COMQUISTA Project was supported by the Ministério da Saúde/Conselho Nacional de Desenvolvimento Científico e Tecnológico/Fundação de Amparo à Pesquisa , state of Bahia/Health Department of the state of Bahia, Terms of Award no. 00017/2010. Projeto de Doutorado Interinstitucional (DINTER) financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Edital 05/2009, Ação Novas Fronteiras.

The authors declare that there are no conflict of interests.

SCIMAGO INSTITUTIONS RANKINGS

Núcleo de Epidemiologia e Saúde Coletiva . Instituto Multidisciplinar em Saúde. Universidade Federal da Bahia. Vitória da Conquista, BA, Brasil Universidade Federal da BahiaBrasilVitória da Conquista, BA, Brasil Núcleo de Epidemiologia e Saúde Coletiva . Instituto Multidisciplinar em Saúde. Universidade Federal da Bahia. Vitória da Conquista, BA, Brasil

Division of Clinical Epidemiology . McGill University Health Center. McGill University. Montrèal, CanadaMcGill UniversityCanadaMontrèal, Canada Division of Clinical Epidemiology . McGill University Health Center. McGill University. Montrèal, Canada

Departamento de Medicina Preventiva e Social. Faculdade de Medicina . Universidade Federal de Minas Gerais. Belo Horizonte, MG, Brasil Universidade Federal de Minas GeraisBrasilBelo Horizonte, MG, Brasil Departamento de Medicina Preventiva e Social. Faculdade de Medicina . Universidade Federal de Minas Gerais. Belo Horizonte, MG, Brasil

Departamento de Farmácia Social. Faculdade de Farmácia. Universidade Federal de Minas Gerais. Belo Horizonte , MG, Brasil Universidade Federal de Minas GeraisBrasilBelo Horizonte, MG, Brasil Departamento de Farmácia Social. Faculdade de Farmácia. Universidade Federal de Minas Gerais. Belo Horizonte , MG, Brasil

Tables

Tables (4)

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Table 1
. Characteristics of the studied quilombola population. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

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Table 2
. Distribution of medications by group and subgroup according to anatomical and therapeutic classification (1^stand 2^ndlevels of the ATC),^aand ratio of number of medications per individual. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

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Table 3
. Prevalence and prevalence ratio (PR) for medication use, mean and standard deviation (SD) for the number of active ingredients according to the variables analyzed. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011. (N = 797)

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Table 4
. Prevalence ratios, adjusted for medication use, of the variables included in the final regression model. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

Table 1 . Characteristics of the studied quilombola population. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

Variable	Total
Variable	n	%

Sex
Male	364	45.7
Female	433	54.3
Age (years)
18 to 34	289	36.3
35 to 59	331	41.5
60 and over	177	22.2
Marital status
No partner	308	38.6
With partner	489	61.4
Schooling (completed years of study)
0	274	34.6
1 to 4	299	37.8
5 and over	219	27.7
Work situation
Currently not working	408	51.2
Currently working	389	48.8
Economic class
E	275	34.8
D	401	50.8
C and B2	114	14.4
Self-perceived health state
Very good/good	356	44.8
Regular	337	42.4
Bad/very bad	101	12.7
Number of self-reported morbidities
None	328	41.2
1	280	35.1
2 or more	189	23.7
Frequency of visits by CHW or health care professional
Monthly	393	50.3
1 to 6 times/year	193	24.7
Never	195	25.0
Number of medical appointments (last 12 months)
None	399	50.1
1 to 2	247	31.0
3 or more	151	18.9
Use of medications (preceding 15 days)
No	463	58.1
Yes	334	41.9

CHW: community health worker

Table 2 . Distribution of medications by group and subgroup according to anatomical and therapeutic classification (1^stand 2^ndlevels of the ATC),^aand ratio of number of medications per individual. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

Anatomical and therapeutic group	n	%	Number of medications per individual

Alimentary tract and metabolism	81	11.3	0.10
Drugs for acid-related disorders	18	2.5	0.02
Antiemetics and antinauseants	6	0.8	0.01
Drugs used in diabetes	33	4.6	0.04
Vitamins	13	1.8	0.02
Blood and blood forming organs	27	3.8	0.03
Antithrombotic agents	18	2.5	0.02
Antianemic preparations	8	1.1	0.01
Cardiovascular system	314	44.0	0.39
Cardiac therapy	10	1.4	0.01
Diuretics	118	16.5	0.15
Beta blocking agents	36	5.0	0.05
Calcium channel blockers	22	3.1	0.03
Agents acting on the renin-angiotensin system	102	14.3	0.13
Lipid modifying agents	22	3.1	0.03
Genitourinary system and sex hormones	26	3.6	0.03
Sex hormones and modulators of the genital system	23	3.2	0.03
Anti-infectives for systemic use	19	2.7	0.02
Antibacterials for systemic use	18	2.5	0.02
Musculo-skeletal system	80	11.2	0.10
Anti-inflammatory and antirheumatic products	56	7.8	0.07
Muscle relaxants	23	3.2	0.03
Nervous system	108	15.1	0.14
Analgesics	64	9.0	0.08
Antiepileptics	17	2.4	0.02
Psycholeptics	13	1.8	0.02
Respiratory system	27	3.8	0.03
Drug for obstructive airway diseases	7	1.0	0.01
Cough and cold preparations	7	1.0	0.01
Anti-histamines for systemic use	13	1.8	0.02
Sensory organs	11	1.5	0.01
Ophthalmologicals	11	1.5	0.01

Total	714	100.0	0.90

^aIt includes anatomical therapeutic groups (1^stATC level) with frequency above 2% and the most frequent therapeutic subgroups (2^ndATC level), totaling less than 80.0% within each level.

Table 3 . Prevalence and prevalence ratio (PR) for medication use, mean and standard deviation (SD) for the number of active ingredients according to the variables analyzed. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011. (N = 797)

Variable	Medication use
Variable	%	PR	95%CI	Mean	SD

Sex				p^b= 0.0057^a
Male	31.9	1		0.9	1.8
Female	50.3	1.58	1.32;1.89	1.2	1.7
Age (years)				p^b= 0.0000^a
18 to 34	29.8	1		0.6	1.1
35 to 59	38.4	1.29	1.03;1.61	0.9	1.5
60 and over	68.4	2.30	1.87;2.82	2.1	2.4
Marital status				p^b= 0.6268
No partner	38.0	1		1.0	1.8
With partner	44.4	1.17	0.98;1.39	1.1	1.7
Schooling (complete years of studies)				p^b= 0.0001^a
No studies	49.3	1		1.3	2.1
1 to 4	42.1	0.86	0.71;1.02	1.1	1.7
5 or more	32.4	0.66	0.52;0.82	0.7	1.2
Work situation				p^b= 0.0000^a
Currently not working	50.2	1		1.3	1.8
Currently working	33.2	0.66	0.56;0.78	0.8	1.7
Economic class				p^b= 0.0062^a
E	33.8	1		0.9	1.6
D	45.1	1.33	1.10;1.63	1.1	1.7
C and B2	50.9	1.50	1.18;1.92	1.5	2.1
Self-perceived health				p^b= 0.0000^a
Very good/good	28.7	1		0.6	1.3
Regular	50.4	1.76	1.45;2.14	1.4	2.0
Bad/very bad	60.4	2.11	1.68;2.65	1.6	1.9
Number of self-reported morbidities				p^b= 0.0000^a
None	23.8	1		0.5	0.9
1	40.4	1.70	1.33;2.16	1.0	1.7
2 or more	75.7	3.18	2.58;3.93	2.3	2.2
Frequency of visits by CHW or health care professional				p^b= 0.6795^a
Monthly	41.5	1		1.0	1.7
1 to 6 times/year	43.5	1.05	0.86;1.28	1.2	1.9
Never	41.5	1.00	0.82;1.23	1.0	1.6
Number of medical appointments (last 12 months)				p^b= 0.0000^a
None	27.8	1		0.6	1.3
1 to 2	50.2	1.80	1.48;2.21	1.4	2.1
3 or more	65.6	2.36	1.94;2.87	1.7	1.8

CHW: community health worker

^aSignificant values (p < 0.05)

^bp estimated by variance analysis

Table 4 . Prevalence ratios, adjusted for medication use, of the variables included in the final regression model. COMQUISTA Project, Vitória da Conquista, BA, Northeastern Brazil, 2011.

Variables	PR	95%CI

Sex
Male	1
Female	1.53	1.31;1.79^a
Age (years)
18 to 34	1
35 to 59	1.05	0.85;1.29
60 and over	1.47	1.19;1.81^a
Economic class
E	1
D	1.26	1.06;1.49^a
C and B2	1.40	1.12;1.74^a
Self-perceived health
Very good/good	1
Regular		0.99;1.44
Bad/very bad	1.33	1.06;1.66^a
Number of self-reported morbidities
None	1
1	1.42	1.12;1.81^a
2 or more	2.18	1.73;2.75^a
Number of medical appointments (last 12 months)
None	1
1 to 2	1.34	1.11;1.62^a
3 or more	1.64	1.36;1.99^a

^aSignificant values (p < 0.05) – Wald test (Z)

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Medication use by the “quilombola” population: a survey in Southwestern Bahia, Brazil

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[1] Correspondence
: Danielle Souto de Medeiros - Instituto Multidisciplinar em Saúde - Universidade Federal da Bahia - Campus Anísio Teixeira - Rua Rio de Contas, 58 Quadra 17 Lote 58 Candeias - 45055-090 Vitória da Conquista, BA, Brasil - E-mail: danielle.medeiros@ufba.br