| Literature DB >> 26845546 |
Dele Abegunde1, Nosa Orobaton1, Amos Bassi1, Olugbenga Oguntunde1,2, Moyosola Bamidele1, Masduq Abdulkrim1, Ezenwa Nwizugbe1.
Abstract
BACKGROUND: Malaria accounts for about 300,000 childhood deaths and 30% of under-five year old mortality in Nigeria annually. We assessed the impact of intervention strategies that integrated Patent Medicines Vendors into community case management of childhood-diseases, improved access to artemisinin combination therapy (ACT) and distributed bed nets to households. We explored the influence of household socioeconomic characteristics on the impact of the interventions on fever in the under-five year olds in Bauchi State Nigeria.Entities:
Mesh:
Year: 2016 PMID: 26845546 PMCID: PMC4742484 DOI: 10.1371/journal.pone.0148586
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Description of variables.
| Pre-intervention | Post- intervention | |||||
|---|---|---|---|---|---|---|
| Variable description | Control group | Intervention group | Pre-intervention Total | Control group | Intervention group | Post intervention Total |
| 1,120 | 1,157 | 2,277 | 730 | 903 | 1,633 | |
| 676 (60.4%) | 613 (53.0%) | 1,289 (56.6%) | 327 (44.9%) | 366 (40.6%) | 693 (42.5%) | |
| 444 (39.6%) | 544 (47.0%) | 988 (43.4%) | 402 (55.1%) | 536 (59.4%) | 938 (57.5%) | |
| 815 (72.8%) | 849 (73.4%) | 1,664 (73.1%) | 554 (75.9%) | 869 (96.2%) | 1,423 (87.1%) | |
| 305 (27.2%) | 308 (26.6%) | 613 (26.9%) | 176 (24.1%) | 34 (3.8%) | 210 (12.9%) | |
| 27.0 | 27.8 | 27.3 | 26.8 | 28.2 | 27.5 | |
| Low (base case) | 337 (30.1%) | 324 (28.0%) | 661 (29.0%) | 367 (50.3%) | 371 (41.1%) | 738 (45.2%) |
| Middle | 230 (20.5%) | 256 (22.1%) | 486 (21.3%) | 100 (13.7%) | 117 (13.0%) | 217 (13.3%) |
| High | 553 (49.4%) | 577 (49.9%) | 1,130 (49.6%) | 263 (36.0%) | 415 (46.0%) | 678 (41.5%) |
| None (base case) | 1,001(89.4%) | 796 (68.8%) | 1,797 (78.9%) | 649 (88.9%) | 569 (63.0%) | 1,218(74.6%) |
| Primary | 75 (6.7%) | 255 (22.0%) | 330 (14.5%) | 6 (9.0%)6 | 237 (26.2%) | 303 (18.6%) |
| Secondary | 41 (3.7%) | 93 (8.0%) | 13 (5.9%)4 | 15 (2.1%) | 89 (9.9%) | 104 (6.4%) |
| Higher | 3 (0.3%) | 13 (1.1%) | 16 (0.7%) | 0 (0.0%) | 8 (0.9%) | 8 (0.5%) |
| 2.6 | 2.3 | 2.5 | 2.2 | 2.3 | 2.2 | |
Contingency Table of the Effect of Household Possession of Bed Nets, on the Risk of Fever in Children.
| Category | No. with Fever | No. with no Fever | Total | Proportion with fever | Odds Ratio (95% Confidence Interval) | Prevention Fraction. (95% Confidence Interval) | Statistic |
|---|---|---|---|---|---|---|---|
| 1525 | 1560 | 3085 | 49.4% | ||||
| 457 | 366 | 823 | 55.6% | 0.783 | 0.217 | ||
| 1982 | 1926 | 3908 | 50.72% | (0.67–0.92) | (0.08–0.33) | Pr>chi2 = 0.0 | |
| 979 | 1080 | 2059 | 47.6% | ||||
| 1003 | 846 | 1849 | 54.4% | 0.765 | 0.235 | ||
| 1982 | 1926 | 3908 | 50.72% | (0.67–0.87) | (0.13–0.33) | Pr>chi2 = 0.0 | |
| 693 | 938 | 1631 | 42.5% | ||||
| 1289 | 988 | 2277 | 56.5% | 0.566 | 0.434 | ||
| 1982 | 1926 | 3908 | 50.72% | (0.50–0.65) | (0.36–0.50) | Pr>chi2 = 0.0 |
Results of the Logistic Regression of Childhood Fever on Household Possession of Bed Nets, and Household Characteristics.
| Fever | Odds Ratio | Standard Error. | z | P>z | 95% Confidence Interval | |
|---|---|---|---|---|---|---|
| 0.722 | 0.071 | -3.290 | 0.001 | 0.595 | 0.877 | |
| 1.005 | 0.004 | 1.170 | 0.241 | 0.997 | 1.013 | |
| Middle | 1.195 | 0.090 | 2.350 | 0.019 | 1.030 | 1.386 |
| Highest | 1.179 | 0.087 | 2.240 | 0.025 | 1.021 | 1.362 |
| Primary education | 1.007 | 0.085 | 0.090 | 0.931 | 0.854 | 1.189 |
| Secondary education | 0.688 | 0.083 | -3.100 | 0.002 | 0.544 | 0.872 |
| Tertiary education | 0.449 | 0.161 | -2.240 | 0.025 | 0.222 | 0.906 |
| Number of under-5 in household | 0.995 | 0.001 | -5.220 | 0.000 | 0.994 | 0.997 |
| 0.390 | 0.032 | -11.310 | 0.000 | 0.332 | 0.460 | |
| 0.562 | 0.046 | -7.090 | 0.000 | 0.480 | 0.659 | |
| 1.703 | 0.198 | 4.590 | 0.000 | 1.357 | 2.138 | |
| 2.269 | 0.380 | 4.900 | 0.000 | 1.635 | 3.150 | |
Log Pseudolikelihood = -1089646, Wald chi2 (11) = 205.9, Probability > chi2 = 0.0000, Pseudo R2 = 0.34