| Literature DB >> 36120505 |
Helmut A Nyawale1, Elieza Chibwe2, Fridolin Mujuni2, Lidya Maiga1, Albert Silvin1, Alda Ester Chongo3, Bertrand Msemwa4, Vitus Silago2, Mtebe Majigo5, Doreen Kamori5, Stephen E Mshana2, Mariam M Mirambo2.
Abstract
Background: Stillbirth adversely affects pregnancy outcomes in low- and middle-income countries (LMICs). Viral infections have been implicated as one of the causes of stillbirths. Despite high rates of stillbirths and high viral prevalence in LMICs, there is limited information regarding their association. This study investigated the magnitude of herpes simplex 2 virus (HSV-2) and human cytomegalovirus (HCMV) among women with macerated stillbirth.Entities:
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Year: 2022 PMID: 36120505 PMCID: PMC9477628 DOI: 10.1155/2022/2156835
Source DB: PubMed Journal: J Pregnancy ISSN: 2090-2727
Summary of hospitals involved in this study.
| SNO | Hospital | Location | Deliveries per month | Stillbirth per month |
|---|---|---|---|---|
| 1 | Bugando Medical Centre | Nyamagana | 740 | 10 |
| 2 | Sekou Toure | Nyamagana | 700 | 20 |
| 3 | Nyamagana District hospital | Nyamagana | 449 | 15 |
| 4 | Magu District hospital | Magu | 230 | 9 |
| 5 | Sumve Hospital | Misungwi | 130 | 3 |
| 6 | Sengerema Hospital | Sengerema | 746 | 27 |
| 7 | Misungwi Hospital | Misungwi | 200 | 4 |
| 8 | Bukumbi Hospital | Misungwi | 82 | 2 |
| 9 | Ngudu District Hospital | Kwimba | 245 | 7 |
Sociodemographic characteristics and obstetrics history of 279 women with macerated stillbirth in Mwanza Tanzania.
| Participant's characteristics | Number ( | Percentage/IQR/SD |
|---|---|---|
| Age | 279 | 27.76 ± 7.22 |
| Gravidity | 279 | 3.25 ± 2.39 |
| Parity | 279 | 2.93 ± 2.18 |
| Gestation age | 279 | 35.62 ± 3.58 |
| Education | ||
| Primary | 229 | 82.08% |
| Secondary | 36 | 12.90% |
| Tertiary | 14 | 5.02% |
| Occupation | ||
| Business | 44 | 15.77% |
| Employed | 25 | 8.96% |
| Farming | 178 | 63.80% |
| Unemployed/employed | 32 | 11.47% |
| Marital status | ||
| Married | 228 | 81.72% |
| Single | 51 | 18.28% |
| Fever | ||
| Yes | 73 | 26.14% |
| No | 206 | 73.84% |
| G/rash | ||
| Yes | 25 | 8.96% |
| No | 254 | 91.04% |
| Headache | ||
| Yes | 87 | 31.18% |
| No | 192 | 68.82% |
| History of abortion | ||
| Yes | 51 | 18.28% |
| No | 228 | 68.82% |
| History congenital malformation | ||
| Yes | 1 | 0.36% |
| No | 278 | 99.64% |
Univariate and multivariate logistic regression analyses of the factors associated with HSV-2 IgG seropositivity among 279 women with stillbirth in Mwanza, Tanzania.
| Variables | Mean (SD) (%) | Univariate, OD (95%CL) |
| Multivariate OD (95%CL) |
|
|---|---|---|---|---|---|
| Age | 27.76 ± 7.22 | 0.92 (0.86-0.98) | 0.015 | 0.93 (0.87-0.99) | 0.025 |
| Residence | |||||
| Rural | 16 (10.26%) | 1.0 | |||
| Urban | 12 (7.76%) | 0.95 (0.43-2.08) | 0.890 | ||
| Parity | 2.93 ± 2.18 | 0.92 (0.76-1.12) | 0.414 | ||
| Education | |||||
| Primary | 24 (10.48%) | 1.0 | |||
| Secondary | 3 (8.33%) | 1.18 (1.11-12.42) | 0.889 | ||
| Tertiary | 1 (7.14%) | 1.52 (0.19-12.15) | 0.692 | ||
| Occupation | |||||
| Unemployed | 4 (12.50%) | 1.0 | |||
| Business | 4 (9.09%) | 1.15 (0.19-6.77) | 0.877 | ||
| Employed | 2 (8.0%) | 1.64 (0.27-9.78) | 0.586 | ||
| Farming | 18 (10.11%) | 1.28 (0.28-5.94) | 0.741 | ||
| Marital status | |||||
| Single | 8 (15.69%) | 1.0 | |||
| Married | 20 (8.77%) | 1.93 (0.79-4.68) | 0.143 | 1.45 (0.58-3.64) | 0.418 |
| Fever | |||||
| No | 21 (10.19%) | 1.0 | |||
| Yes | 7 (9.59%) | 0.93 (0.38-2.29) | 0.882 | ||
| H/rash | |||||
| No | 26 (10.24%) | 1.0 | |||
| Yes | 2 (8.00%) | 0.76 (0.17-3.42) | 0.723 | ||
| Headache | |||||
| No | 21 (10.94%) | 1.0 | |||
| Yes | 7 (8.05%) | 0.71 (0.29-1.74) | 0.458 | ||
| H/abortion | |||||
| No | 25 (10.96%) | 1.0 | |||
| Yes | 3 (5.88%) | 0.51 (0.15-1.75) | 0.283 | ||
| H/low birth weight | |||||
| No | 23 (9.66%) | 1.0 | |||
| Yes | 5 (12.20%) | 1.29 (0.46-3.63) | 0.619 | ||
| Stillbirth | |||||
| No | 21 (11.35%) | 1.0 | |||
| Yes | 7 (7.45%) | 0.62 (0.25-1.54) | 0.308 | ||
| HIV status | |||||
| Negative | 26 (9.96%) | 1.0 | |||
| Positive | 2 (11.11%) | 1.12 (0.25-5.19) | 0.8 |
Univariate and multinomial logistic regression analysis of the factors associated with HCMV IgG seropositivity among 168 women with stillbirth in Mwanza, Tanzania.
| Variable | HCMV Seropositivity%/mean SD, median IQR | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|---|
| RRR: 95% CI |
| RRR: 95% CI |
| ||
| Age | 27, IQR: 22-34 | 1.02 (0.97-1.07) | 0.406 | ||
| Parity | 2.92 ± 2.2 | 0.99 (0.85-1.16) | 0.926 | ||
| Gestation age | 37 IQR:33-38 | 1.00 (0.91-1.10) | 0.999 | ||
| Residence | |||||
| Rural | 61 (65.59%) | 1 | |||
| Urban | 70 (93.33%) | 7.34 (2.69-20.03) | <0.001 | 4.43 (1.53-12.80) | 0.006 |
| Education level | |||||
| None | 12 (70.59%) | 1 | |||
| Primary | 89 (76.72%) | 0.82 | 0.992 | ||
| Secondary | 19 (79.17%) | 0.94 | 0.992 | ||
| Tertiary | 11 (100%) | 1.3 | 0.992 | ||
| Occupation | |||||
| Unemployed | 18 (90.00%) | 1 | |||
| Business | 76 (70.37%) | 0.26 (0.06-1.2) | 0.085 | 0.50 (0.10-2.50) | 0.400 |
| Farming | 18 (85.71%) | 0.39 (0.11-1.44 | 0.159 | 0.61 (0.15-2.38) | 0.481 |
| S/employed | 18 (90.00%) | NA | NA | NA | |
| Marital status | |||||
| Single | 20 (71.43%) | 1 | |||
| Married | 111 (79.29%) | 0.65 (0.26-1.63) | 0.362 | ||
| History of abortion | |||||
| No | 106 (79.70%) | 1 | |||
| Yes | 25 (71.43%) | 1.57 (0.67-1.66) | 0.296 | ||
| History of LBW | |||||
| No | 113 (79.58%) | 1 | |||
| Yes | 18 (69.23%) | 1.73 (0.68-4.38) | 0.246 | ||
| History of premature birth | |||||
| No | 126 (78.26%) | 1 | |||
| Yes | 5 (71.43%) | 1.73 (0.68-4.38) | |||
Figure 1Avidity index values of IgG seropositive individuals with high titters.