| Literature DB >> 32127873 |
Jeremiah Ogah1, Olatunji Kolawole1, Daniel Awelimobor2.
Abstract
BACKGROUND: Nigeria accounts for 25% of cases of Female genital mutilation (FGM) worldwide, with increased incidence of cervical cancer.Entities:
Keywords: HPV; female genital mutilation
Mesh:
Year: 2019 PMID: 32127873 PMCID: PMC7040333 DOI: 10.4314/ahs.v19i4.19
Source DB: PubMed Journal: Afr Health Sci ISSN: 1680-6905 Impact factor: 0.927
Demographic characters of the study population
| Demographic Characteristics | Study | |
| Age of subjects | 15–20years | 12 (6) |
| 21–30years | 128 (64) | |
| 31–40years | 56 (28) | |
| 41–50years | 4 (2) | |
| Total | 200 (100) | |
| Type of Education | Formal Education | 180 (90) |
| Informal Education | 20 (10) | |
| Total | 200 (100) | |
| Highest level of | Primary Education | 12 (6) |
| Secondary Education | 60 (30) | |
| Tertiary Education | 108 (54) | |
| Informal Education | 20 (8) | |
| Total | 200 (100) | |
| Religion | Christian | 12 (6) |
| Muslims | 184 (92) | |
| Others | 4 (2) | |
| Total | 200 (100) | |
| Marital status | Married | 196 (98) |
| Single | 4 (2) | |
| Widow | 0 (0) | |
| Total | 200 (100) | |
Relationship between female genital mutilation and HPV infection
| Risk factors | Subjects with female | X2(p value) | 95 % CI | Odds ratio | ||
| Yes | No | |||||
| Positive | 18 | 5 | 7.63 (0.01) | 1.56 to 12.28 | 4.37 | |
| Negative | 80 | 97 | ||||
| High Risk | 19 | 1 | 5.88 (0.15) | 1.18 to 13.60 | 12.67 | |
| Low Risk | 6 | 4 | ||||
| Multiple HPV infections | 9 | 2 | 0.01 (0.67) | 0.13 to 9.61 | 1.11 | |
| Single HPV infection | 10 | 2 | ||||
P value <0.005 is statistically significant
Risk factors associated with HPV infection
| HPV Infection | |||||
| Yes | No | X2 (P value) | OR (95% CI) | ||
| 15–20years | 2 | 8 | 8.3 (0.04) | 0.08 (0.03–0.13) | |
| 21–30years | 15 | 73 | |||
| 31–40years | 6 | 62 | |||
| 41–50years | 0 | 34 | |||
| Yes | 17 | 80 | 6.72 (0.01) | 0.29 (0.11–0.77) | |
| No | 6 | 97 | |||
| Yes | 15 | 70 | 5.49(0.02) | 0.3489 (0.14–0.87) | |
| No | 8 | 107 | |||
| Yes | 16 | 62 | 10.21 (0.00) | 0.2359 (0.09–0.60) | |
| No | 7 | 115 | |||
Regression analysis of the relationship between HPV Infection and FGM
| Coefficients | ||||||||
| Model | Unstandardized | Standardized | t | Sig. | 95.0% Confidence Interval | |||
| B | Std. | Beta | Lower | Upper Bound | ||||
| (Constant) | 1.682 | 0.071 | 23.849 | 0.000 | 1.543 | 1.821 | ||
| Subjects with FGM | 0.135 | 0.044 | 0.211 | 3.037 | 0.003 | 0.047 | 0.222 | |
| (Constant) | 1.480 | 0.098 | 15.131 | 0.000 | 1.287 | 1.673 | ||
| Subjects with FGM | 0.134 | 0.044 | 0.209 | 3.068 | 0.002 | 0.048 | 0.219 | |
| Age of subjects | 0.077 | 0.027 | 0.199 | 2.911 | 0.004 | 0.025 | 0.129 | |
| (Constant) | 1.506 | 0.097 | 15.520 | 0.000 | 1.314 | 1.697 | ||
| Subjects with FGM | 0.904 | 0.305 | 1.417 | 2.960 | 0.003 | 0.302 | 1.506 | |
| Age of subjects | 0.074 | 0.026 | 0.189 | 2.809 | 0.005 | 0.022 | 0.125 | |
| Sex at an Early Age | - | 0.305 | -1.220 | -2.548 | 0.012 | -1.381 | -0.176 | |
| (Constant) | 1.377 | 0.107 | 12.843 | 0.000 | 1.166 | 1.589 | ||
| Subjects with FGM | 0.922 | 0.301 | 1.444 | 3.063 | 0.003 | 0.328 | 1.515 | |
| Age of subjects | 0.078 | 0.026 | 0.201 | 3.028 | 0.003 | 0.027 | 0.129 | |
| Sex at an Early Age | - | 0.303 | -1.347 | -2.842 | 0.005 | -1.456 | -0.263 | |
| Been Wife in a | 0.132 | 0.050 | 0.202 | 2.634 | 0.009 | 0.033 | 0.231 | |
Dependent Variable: HPV Infection
Analysis showed a minimal effect in the odds ratio of subjects with FGM in the second model when the predictor age was added. Thus age alone was not a confounding variable. However, in the models 3 and 4 when two additional predictors were added, there was a corresponding positive increase in the odds ratio of the predictors.