| Literature DB >> 27769249 |
Lauretta Ovadje1, Jerome Nriagu2.
Abstract
BACKGROUND: Poor malaria knowledge can negatively impact malaria control programmes. This study evaluates knowledge distribution in the domains of causation, transmission, vulnerability, symptoms, and treatment of malaria. It assesses the association between a caregiver's knowledge about malaria and ownership and use of insecticide-treated nets (ITNs) by children.Entities:
Keywords: Behaviour change communication; Insecticide-treated net; Malaria control; Malaria knowledge; Misperceptions; Nigeria
Mesh:
Year: 2016 PMID: 27769249 PMCID: PMC5073728 DOI: 10.1186/s12936-016-1557-2
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Association between sociodemographic characteristics of the children and caregivers and ITN ownership and use
| Variable | ITN ownership | ITN use the week before the survey | Every day | p value | ||||
|---|---|---|---|---|---|---|---|---|
| N | Frequency (%) | |||||||
| N | Frequency (%) | p value | Never | Partial | ||||
| Location | <0.001 | 0.09 | ||||||
| Lagos | 813 | 474 (58) | 460 | 94 (20) | 169 (37) | 197 (43) | ||
| Oyo | 1126 | 453 (40) | 447 | 113 (25) | 171 (38) | 163 (37) | ||
| Gender of caregiver | 0.03 | 0.09 | ||||||
| Male | 776 | 345 (45) | 341 | 67 (20) | 125 (37) | 149 (44) | ||
| Female | 1139 | 565 (50) | 550 | 137 (25) | 208 (38) | 205 (37) | ||
| Gender of child | 0.13 | 0.32 | ||||||
| Male | 919 | 413 (45) | 406 | 83 (20) | 154 (38) | 169 (42) | ||
| Female | 996 | 483 (49) | 471 | 116 (25) | 174 (37) | 181 (38) | ||
| Age range of caregiver (years) | <0.001 | <0.001 | ||||||
| ≤30 | 334 | 189 (57) | 184 | 22 (12) | 89 (48) | 73 (40) | ||
| 31–40 | 784 | 361 (46) | 355 | 91 (26) | 127 (36) | 137 (38) | ||
| >40 | 723 | 312 (43) | 305 | 87 (29) | 103 (34) | 115 (38) | ||
| Age range of child (years) | 0.23 | 0.59 | ||||||
| 4–7 | 1253 | 570 (46) | 561 | 134 (24) | 203 (36) | 224 (40) | ||
| 8–14 | 522 | 254 (49) | 247 | 53 (22) | 98 (40) | 96 (39) | ||
| Level of education | <0.001 | 0.04 | ||||||
| Primary school or less | 345 | 191 (55) | 185 | 28 (15) | 80 (43) | 77 (42) | ||
| Secondary school | 434 | 169 (39) | 168 | 41 (24) | 57 (34) | 70 (42) | ||
| Polytechnic/vocational/technical college | 498 | 212 (43) | 206 | 43 (21) | 81 (39) | 82 (40) | ||
| University | 624 | 333 (53) | 328 | 92 (28) | 117 (36) | 119 (36) | ||
| Income range | <0.001 | 0.14 | ||||||
| <20,000 Naira/month | 612 | 262 (43) | 259 | 46 (18) | 113 (44) | 100 (39) | ||
| 20,000 to 100,000 Naira/month | 715 | 342 (48) | 334 | 86 (26) | 119 (36) | 129 (39) | ||
| >100,000 Naira/month | 291 | 167 (57) | 163 | 40 (25) | 62 (38) | 61 (37) | ||
Mean scores for the different malaria knowledge domains
| Score | All (n = 1892) | ITN owners (n = 883) |
|---|---|---|
| Mean (SD) | Mean (SD) | |
| Total knowledge | 53.77 (14.14) | 53.54 (14.76) |
| Cause | 43.86 (28.55) | 44.56 (29.85) |
| Transmission | 31.61 (26.39) | 31.73 (26.04) |
| Vulnerability | 83.31 (26.74) | 80.41 (28.90) |
| Symptoms | 56.93 (25.14) | 55.59 (25.81) |
| Treatment | 50.14 (22.16) | 49.92 (23.33) |
Fig. 1Percentage of correct answers to the malaria knowledge statements
Correlations between ITN ownership, ITN use, TKI, and individual domain scores
| Cause | Transmission | Vulnerability | Symptom | Treatment | Ownership of any bed net | Ownership of ITN | Did child sleep under an ITN in preceding night | How often did child sleep under ITN in past | ||
|---|---|---|---|---|---|---|---|---|---|---|
| Cause | Correlation coefficient | |||||||||
| Sig. (2-tailed) | ||||||||||
| Transmission | Correlation coefficient | 0.271** | ||||||||
| Sig. (2-tailed) | 0 | |||||||||
| Vulnerability | Correlation coefficient | 0.029 | 0.145** | |||||||
| Sig. (2-tailed) | 0.316 | 0 | ||||||||
| Symptom | Correlation coefficient | 0.160** | 0.184** | 0.453** | ||||||
| Sig. (2-tailed) | 0 | 0 | 0 | |||||||
| Treatment | Correlation coefficient | 0.139** | 0.112** | 0.417** | 0.400** | |||||
| Sig. (2-tailed) | 0 | 0 | 0 | 0 | ||||||
| Ownership of any bed net | Correlation coefficient | 0.05 | 0.01 | 0.018 | 0.009 | 0.05 | ||||
| Sig. (2-tailed) | 0.07 | 0.702 | 0.453 | 0.773 | 0.075 | |||||
| Ownership of ITN | Correlation coefficient | 0.092** | 0.044 | 0.052** | 0.011 | 0.078** | 0.838** | |||
| Sig. (2-tailed) | 0.001 | 0.079 | 0.034 | 0.722 | 0.005 | 0 | ||||
| Did child sleep under an ITN in preceding night | Correlation coefficient | 0.059* | 0.023 | 0.077** | 0.021 | 0.077** | 0.557** | 0.653** | ||
| Sig. (2-tailed) | 0.034 | 0.368 | 0.002 | 0.487 | 0.006 | 0 | 0 | |||
| How often did child sleep under ITN in past | Correlation coefficient | 0.068* | 0.035 | 0.078** | 0.024 | 0.064* | 0.659** | 0.775** | 0.861** | |
| Sig. (2-tailed) | 0.015 | 0.171 | 0.002 | 0.425 | 0.024 | 0 | 0 | 0 | ||
| Total Knowledge Index (TKI) | Correlation coefficient | 0.594** | 0.501** | 0.534** | 0.738** | 0.612** | 0.07 | 0.122** | 0.095* | 0.108** |
| Sig. (2-tailed) | 0 | 0 | 0 | 0 | 0 | 0.066 | 0.001 | 0.014 | 0.005 | |
* Correlation is significant at the 0.05 level (2-tailed)
** Correlation is significant at the 0.01 level (2-tailed)
Association between malaria knowledge scores and ITN use the week before the survey
| Score | N | Partial | Everyday | ||
|---|---|---|---|---|---|
| OR (95 % CI) | p value | OR (95 % CI) |
| ||
| Total correct score >54 % | 347 | 1.584 (1.002–2.505) | 0.49 | 1.539 (0.981-2.413) | 0.061 |
| Total correct score ≤54 % | 279 | Ref | |||
| Cause >44 % | 271 | 1.091 (0.702–1.696) | 0.7 | 0.883 (0.572–1.364) | 0.576 |
| Cause ≤44 % | 370 | Ref | |||
| Transmission >32 % | 444 | 1.336 (0.841–2.122) | 0.219 | 1.266 (0.799–2.005) | 0.316 |
| Transmission ≤32 % | 197 | Ref | |||
| Vulnerability >80 % | 397 | 1.863 (1.178–2.946) | 0.008 | 1.249 (0.789–1.979) | 0.343 |
| Vulnerability ≤80 % | 244 | Ref | |||
| Symptoms >56 % | 395 | 1.271 (0.811–1.994) | 0.296 | 1.599 (1.029–2.486) | 0.037 |
| Symptoms ≤56 % | 246 | Ref | |||
| Treatment >50 % | 498 | 1.116 (0.633–1.966) | 0.705 | 1.682 (0.978–2.891) | 0.06 |
| Treatment ≤50 % | 143 | Ref | |||
Multinomial logistic regression models were adjusted for state of residence, income level of caregiver, educational level of caregiver, age, and gender of both child and caregiver