| Literature DB >> 23503560 |
Polycarp Uche Agu1, Johnbull Sonny Ogboi, Kesiena Akpoigbe, Tochukwu Okeke, Euzebus Ezugwu.
Abstract
INTRODUCTION: Malaria and hookworm infections are common in sub-Saharan Africa and they increase the prevalence of anaemia in pregnancy with resultant poor pregnancy outcomes. This study was carried out to assess the impact of Plasmodium falciparum and hookworm infections on the frequency of anaemia among pregnant women in two rural communities in Enugu, South East Nigeria.Entities:
Keywords: Enugu; Malaria; Nigeria; hookworm; parasites
Mesh:
Substances:
Year: 2013 PMID: 23503560 PMCID: PMC3597852 DOI: 10.11604/pamj.2013.14.27.1925
Source DB: PubMed Journal: Pan Afr Med J
Socio-demographic characteristics of study population
| Frequency | Percentage (%) | |
|---|---|---|
|
| ||
| 0-19* | 12 | 5.3 |
| 20-29 | 150 | 66.4 |
| 30-40 | 64 | 28.3 |
|
| ||
| NoSchool | 179 | 79.2 |
| Primary | 34 | 15.1 |
| Secondary | 12 | 5.3 |
| Tertiary | 1 | 0.4 |
|
| ||
| Business | 5 | 2.2 |
| Farmer | 1 | 0.4 |
| Housewife | 198 | 87.6 |
| Teacher | 1 | 0.5 |
| Trader | 21 | 9.3 |
|
| ||
| Married | 222 | 98.2 |
| Single | 4 | 1.8 |
|
| ||
| NoMalaria | 107 | 47.3 |
| Malaria | 119 | 52.7 |
|
| ||
| Ascarislumbricoides | 14 | 6.2 |
| Giardialamblia | 1 | 0.4 |
| Hookworm | 60 | 26.6 |
| Hookworm/Ascaris | 2 | 0.9 |
| Strongyloides | 1 | 0.4 |
| Negative | 148 | 65.5 |
|
| ||
| First | 65 | 28.9 |
| Second | 113 | 50.2 |
| Third | 47 | 20.9 |
Figure 1Percentage of anemia in pregnant women
Distribution of Anaemia among demographic characteristics in the study population
| Parameters | Normal individuals (Hb>10g/dl) N(%)136(60.2%) | Anaemia individuals (Hb<10d/dl) N(%)90(39.8%) | p-value |
|---|---|---|---|
|
| |||
| 0-19 | 7(5.2) | 5(5.6) | 0.882 |
| 20-29 | 92(67.7) | 58(64.4) | |
| 30-40 | 37(27.2) | 27(30.0) | |
|
| |||
| Absence | 97(71.3) | 10(11.1) | 0.000 |
| Presence | 39(28.7) | 80(88.9) | |
|
| |||
| Absence | 120(88.2) | 46(51.1) | 0.000 |
| Presence | 16(11.8) | 44(48.9) | |
|
| |||
| First | 41(30.3) | 24(26.7) | 0.406 |
| Second | 63(46.7) | 50(55.6) | |
| Third | 31(23.0) | 16(17.8) | |
|
| |||
| Trader | 15(11.0) | 6(6.7) | 0.619 |
| Housewife | 116(85.3) | 82(91.1) | |
| Business | 3(2.3) | 2(2.2) | |
| Farmer | 1(0.7) | - | |
| Teacher | 1(0.7) | - | |
|
| |||
| NoSchool | 104(76.5) | 75(83.4) | 0.498 |
| Primary | 22(16.2) | 12(13.3) | |
| Secondary | 9(6.6) | 3(3.3) | |
| Tertiary | 1(0.7) | - |
Distribution of anaemia among demographic characteristics in the study population with the relationship between anaemia and malaria parasite being significant with p<0.001.
Figure 2Percentage of anaemia amongst those infected with malaria
Figure 3Percentage of anaemia seen amongst those infected with hookworm parasite
Logistic regression analysis for factors associated with anemia in pregnancy
| Variables | N(%) 226(100%) | Unadjusted OR(95%CI) | P | Adjusted OR(95%CI) | P |
|---|---|---|---|---|---|
|
| |||||
| 0-19 | 12(5.3) | ||||
| 20-29 | 150(66.4) | 0.88(0.27-2.92) | 0.838 | 0.98(0.26-3.73) | 0.977 |
| 30-40 | 64(28.3) | 1.02(0.29-3.58) | 0.973 | 1.04(0.23-4.65) | 0.958 |
|
| |||||
| Absence | 107(47.3) | ||||
| Presence | 119(52.7) | 19.90(9.33-42.41) | 0.000 | 18.06(8.15-39.99) | 0.000 |
|
| |||||
| Absence | 166(73.4) | ||||
| Presence | 60(26.6) | 7.17(3.68-13.98) | 0.000 | 5.28(2.26-12.38) | 0.000 |
|
| |||||
| FirstTrimester | 65(28.9) | ||||
| SecondTrimester | 113(50.2) | 1.36(0.72-2.54) | 0.341 | 1.02(0.43-2.44) | 0.961 |
| ThirdTrimester | 47(20.9) | 0.88(0.40-1.94) | 0.754 | 0.80(0.26-2.43) | 0.689 |
|
| |||||
| Trader | 21(9.29) | ||||
| Housewife | 198(87.6) | 1.77(0.66-4.76) | 1.13 | 1.35(0.37-4.92) | 0.648 |
| Business | 5(2.2) | 1.67(0.22-12.67) | 0.49 | 4.94(0.85-28.70) | 0.075 |
|
| |||||
| NoSchool | 179(79.2) | ||||
| Primary | 34(15.0) | 0.76(0.35-1.63) | 0.474 | 0.75(0.27-2.04) | 0.571 |
| Secondary | 12(5.3) | 0.46(0.12-1.77) | 0.260 | 0.47(0.11-2.08) | 0.321 |
Base Case;
Farmers, Teachers in occupational category and Tertiary in educational category were dropped because of insufficient observations for running a logistic regression.