HIV and Syphilis in Pregnancy: A Cross-Sectional Analysis from Healthcare Facilities in Southern Tanzania

HIV and Syphilis in Pregnancy: A Cross-Sectional Analysis from Healthcare Facilities in Southern Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article HIV and Syphilis in Pregnancy: A Cross-Sectional Analysis from Healthcare Facilities in Southern Tanzania Vulstan James Shedura, Rehema Jumanne Kongogwa, Doreen Donald Kamori This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5871728/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Syphilis, caused by Treponema pallidum , is a chronic infection transmitted sexually, through blood transfusion, or vertically from mother to fetus. In pregnancy, it poses a significant public health risk, particularly in developing countries like Tanzania, contributing to perinatal morbidity and mortality. However, data on syphilis and its risk factors, especially among pregnant women living with HIV, are scarce. This study aimed to assess the burden and identify risk factors for syphilis infection among HIV-infected pregnant women attending Prevention of Mother-to-Child Transmission clinic services in selected health facilities in the Mtwara region. This health facility-based cross-sectional study was conducted over three months among pregnant women living with HIV attending Prevention of Mother-to-Child Transmission clinic services in the Mtwara region. A structured questionnaire was used to gather demographic, clinical, and laboratory data. Blood samples (4 ml) were collected for syphilis screening and confirmatory tests. Bivariate and multivariate logistic regression analyses identified significant factors associated with syphilis infection in pregnant women, with a p -value <0.05 considered significant. Two hundred and twenty (n=220) pregnant women living with HIV were enrolled in this study. The median age of the participants was 32.7 years (IQR: 27.6-37.6). The majority (45.5%) of the participants were married, 71.4% had primary education, 47.7% were unemployed, 77.7% were multigravida, and 40.5% were in the second trimester. The prevalence of syphilis infection was 10.9% (24/220). In addition, being in the second trimester of the gestation period [aOR=5.69: 95% CI 1.44-22.46, p =0.013] and being infected with hepatitis B virus [aOR=31.39: 95% CI 9.45-104.23, p <0.001] were independent factors associated with syphilis infection among pregnant women living with HIV in the Mtwara region. The study revealed a significant burden of syphilis infection among pregnant women living with HIV in the Mtwara region, with advanced gestational age (especially in the second trimester) and co-infection with hepatitis B virus identified as key risk factors. The findings emphasize the importance of routine, integrated screening for syphilis and other infections, including hepatitis B, to reduce infection burden, prevent vertical transmission, and improve maternal and child health outcomes. Prevalence Syphilis infection Hepatitis B virus Human immunodeficiency virus Prevention of Mother to Child Transmission Figures Figure 1 Figure 2 Introduction Syphilis is a chronic systemic infection caused by the spirochete Treponema pallidum . It can be transmitted sexually or through blood transfusion (acquired syphilis) and vertically from an infected mother to the fetus via the placenta (congenital syphilis) [ 1 ]. Congenital syphilis can result from pregnant women who have syphilis passing the infection on to their unborn child. Most pregnant women who have syphilis are not identified and treated in time to prevent the infection's negative consequences on the fetus. It continues to be a significant worldwide public health issue, and its prevalence is rising globally[ 2 , 3 ]. Over half a million instances of congenital syphilis were reported worldwide in 2016, leading to over 200,000 stillbirths and neonatal fatalities. Congenital syphilis and other unfavorable pregnancy outcomes linked to syphilis are effectively prevented and treated as long as prompt diagnosis and treatment are given[ 4 ]. However, Congenital syphilis is the leading cause of preventable stillbirth, surpassing malaria, and significantly impacts women in low-resource settings[ 5 ]. In 2007, the World Health Organization (WHO) launched a global initiative to eliminate congenital syphilis[ 5 ]. Despite the fact that almost every country in the world advises screening pregnant women for syphilis at their first antenatal care (ANC) contact, syphilis transmission from mother to child is still a public health concern, and pregnant women are frequently left undiagnosed and untreated despite the low cost of effective diagnosis and treatment[ 5 , 6 ]. In addition, women are disproportionately affected by syphilis in low-resource environments where testing rates are very low and prevalence rates are high. For instance, just 16% of women in the Democratic Republic of the Congo are screened for syphilis, despite the fact that almost 3% of them have the disease[ 7 ]. Thus, expanding syphilis screening programs for expectant mothers is essential, especially for those with HIV and in low-resource environments like Tanzania. It is widely acknowledged that preventing syphilis transmission and unfavorable pregnancy outcomes can be achieved with early detection and treatment of syphilis. Prenatal syphilis screening and treatment can cut the rate of stillbirths by 82%, preterm deliveries by 64%, and neonatal mortality by 80% in endemic countries[ 8 , 9 ]. Numerous epidemiologic studies have examined and reported on factors that influence the magnitude of syphilis serostatus, including maternal age, residence, educational attainment, husband's educational attainment, occupational status, number of pregnancies, history of abortion, history of sexually transmitted infections (STIs), and HIV status. However, there are significant contributing factors that have received little attention and are therefore poorly understood, such as gestation age, HIV viral load status, HBV status, and having two or more sexual partners[ 10 , 11 , 12 ]. In Tanzania and most developing nations, perinatal morbidity and mortality are caused by syphilis during pregnancy, which is one of the most significant public health issues, according to several research conducted throughout the globe. According to a Tanzanian study, 2.5% of expectant mothers who attended ANC had syphilis positive results[ 13 ]. In order to develop an intervention on these aspects, improve therapy, and enhance health promotion programs, it may be necessary to have a thorough grasp of the linked components. However, there is limited research on syphilis and its associated factors among pregnant women living with HIV (LWHIV) in Tanzania, particularly in the Mtwara region. This study aimed to address this gap by assessing the double burden of syphilis and HIV among pregnant women, and identifying associated factors in this population in Southern Tanzania. Material and Methods Study design Between February and April 2022, a health facility based cross-sectional study was carried out in selected health institutions in the Mtwara region to examine the prevalence and risk factors for Syphilis infection among pregnant women LWHIV undergoing Prevention of Mother to Child Transmission (PMTCT) clinics. Study setting The study was conducted in the Mtwara region, located in the southern part of Tanzania. According to the 2022 census, Mtwara, one of the 31 administrative areas in the nation, has a total size of 16,710 square kilometers and 1,270,854 residents[ 14 ]. Geographically, the region lies at latitude − 10.31°S and longitude 40.18°E. There are 221 health facilities in the Mtwara region that provide PMTCT services. Purposively chosen sites for this study were Likombe Health Center, Ndanda Hospital, Mangaka Hospital, and Mkomaindo Hospital. Compared to other health facilities in the area, these facilities were selected because of the significant volume of patients they serve for PMTCT services[ 14 ]. Study Population All pregnant women LWHIV attending PMTCT clinics at Mkomaindo district hospital, Ndanda hospital, Mangaka hospital and Likombe health center in Mtwara region and who met the inclusion criteria. Inclusion criteria Pregnant women (≥ 18 years old) of any gestation age (first, second or third trimester) LWHIV and on Antiretralviral Therapy (ART) attending PMTCT clinics in selected study sites and who provided consent to participate in the study. Exclusion criteria HIV-infected pregnant women who have a confirmed diagnosis of syphilis infection and have started treatment. Sample size estimation and Sampling method Sample size estimation Sample size was calculated using the Kish and Leslie formula based on the data from a prevalence study conducted in Mbeya, Tanzania, with a Syphilis prevalence of 5.1%[ 15 ]. We used a two-sided 95% confidence interval, a marginal error of 3%, and by considering a 10% non-response rate. The resulting sample size was 220. The sample size distribution per PMTCT facility The sample size distribution for pregnant women LWHIV and on ART during the study period is depicted in Fig. 1 . A total of 230 pregnant women living with HIV were initially enrolled from four PMTCT clinics in the Mtwara region. Among them, 223 women were aged over 18 years and on ART. Of these, one participant declined to participate in the study, and samples from two participants were insufficient for laboratory analysis. Consequently, 220 pregnant women were included in the final analysis (Fig. 1 ). The Probability Proportional to Size (PPS) method was employed to determine the sample size distribution across the selected health facilities. The allocation was as follows: Likombe Health Center (39 participants, 17.7%), Mangaka Hospital (36 participants, 16.4%), Mkomaindo Hospital (75 participants, 34.1%), and Ndanda Hospital (70 participants, 31.8%). Sampling method Based on their planned follow-up visits at PMTCT clinics during prenatal clinics, study participants were chosen using a systematic random sampling technique. A list of eligible women LWHIV was compiled for each facility based on the required sample size, and each participant was assigned a unique identifier. The sampling fraction was calculated by dividing the total number of eligible attendees by the sample size for the facility. A random starting point within the sampling interval was chosen, and participants were selected at defined intervals (n = 2) based on clinic attendance. If a selected participant declined, the next eligible individual within the same timeframe was included. Data collection tools and procedures A structured questionnaire was employed to collect data on socio-demographic characteristics, clinical details (including sexual history, gestational age, obstetric history such as gravidity, parity, and abortion, history of sexually transmitted infections (STIs), and surgical history), as well as socio-cultural information (e.g., history of tattooing) from the participants. Additional clinical parameters, such as recent HIV viral load, WHO clinical staging of HIV, ART regimen, and recent CD4 count results, were retrieved from participants' care and treatment cards (CTC2) and the CTC2 database. Variables Dependent variable The dependent variable was syphilis seropositivity, classified as a binary outcome: syphilis seropositive or syphilis seronegative. Independent variables The independent variables included socio-demographic characteristics such as age (categorized as 18–39 or ≥ 40 years), marital status (married, single, divorced, or cohabiting), occupation status (self-employed or unemployed), place of residence (rural or urban), education level (non-formal, primary, secondary, college, or university), facility name (Likombe Health Center, Mangaka Hospital, Mkomaindo Hospital, or Ndanda Hospital), and daily income in Tanzanian shillings ( 12000). Clinical information and parameters included history of blood transfusion (yes or no), WHO clinical staging of HIV (Stage 1, Stage 2, Stage 3, or Stage 4), recent CD4 count in cells/mm³ (< 200, 200–499, or ≥ 500), recent HIV viral load in copies/ml (< 50, 50–999, or ≥ 1000), and Hepatitis B serostatus (positive or negative). Additional clinical variables included the number of sexual partners (one, two, or more than two), history of sexually transmitted infections (yes or no), number of live children (one, two to three, or four or more), gestational period (first trimester, second trimester, or third trimester), ART regimen (first-line or second-line), and duration on ART in months ( 12). Laboratory procedures Blood samples (4 mL) were collected from participants in plain vacutainer tubes, labeled, and transported to the study site laboratories. The samples were processed into serum by centrifugation at 3000 rpm for 10 minutes and aliquoted into cryogenic tubes for temporary storage at -80°C. Syphilis screening was conducted at the health facility laboratories using the SD Bioline Syphilis 3.0 rapid test, a highly sensitive and specific lateral flow immunoassay. Positive samples were confirmed using an automated ELISA (Abbott ARCHITECT PLUS® i2000SR) at the accredited NBTS Southern Zone Laboratory in Mtwara. All procedures adhered to Standard Operating Procedures (SOPs), with strict quality control and verification of reagents and consumables. Data accuracy was ensured through careful recording and double-checking by independent personnel. Data quality assurance The data collection tools were validated through a pre-testing phase to ensure effectiveness. Calibration and quality control procedures were followed, including verification of the Abbott ARCHITECT PLUS® i2000SR immunoassay analyzer using positive and negative controls as recommended by the manufacturer. Control assays were performed daily and confirmed to meet specified concentration ranges before analyzing participant samples. All test results were thoroughly documented and independently cross-verified to ensure accuracy before data analysis. Data processing and analysis Data cleaning and analysis were conducted using Microsoft Excel® 2019 and STATA version 15 package (StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: Stata-Corp L.L.C.). Categorical variables were analyzed for frequency and proportion, while continuous variables were summarized using the median (interquartile range). Bivariate and multivariate logistic regression models were applied to assess relationships between dependent and independent variables. Bivariate analysis evaluated associations between each independent variable and the dependent variable, with variables having p -values < 0.20 included in the multivariate analysis. Statistically significant risk factors for syphilis infection were identified with p -values ≤ 0.05 and 95% confidence intervals. Ethics statement The ethical approval of the study was obtained from the Institutional Review Board (IRB) of the Muhimbili University of Health and Allied Sciences (MUHAS) with approval certificate No. MUHAS-02-2022-978. Permission to conduct the study was requested from the Regional administrative secretary’s office (RAS-Mtwara) and District Medical Officers of all selected districts as well as the medical officer in charge of Mkomaindo hospital, Ndanda hospital, Mangaka hospital and Likombe health center. Written informed consent was obtained from every participant prior to inclusion in the study. Data were anonymized before being accessed and all respondents provided informed, written consent and were assured of confidentiality through the use of special identification codes. Data were protected and kept by the principal investigator and were accessed only by authorized personnel, and for any necessary transfer, permission was given by the principal investigator. Positive results were communicated within 48–72 hours to the clinicians or nurses at the respective hospitals. Results Socio-demographic characteristics of the study participants In this study, a total of 220 pregnant women LWHIV in Mtwara region were enrolled. The study participants’ median age was 32.7 years (IQR: 27.6–37.6). The majority 34.1% (75/220) of the participants were from Mkomaindo Hospital, and the majority 71.4% (157/220) of all participants attained only a primary school level of education; 47.7% (105/220) were unemployed, 51.8% (114/220) were living in urban area and 45.5% (100/220) were married (Table 1 ). Table 1 Socio-demographic characteristics of the study participants (N = 220). Characteristic Frequency (%) Facility name Likombe health center 39 (17.7) Mangaka hospital 36 (16.4) Mkomaindo hospital 75 (34.1) Ndanda hospital 70 (31.8) Age (in years) Median (IQR) 32.7(27.6–37.6) 18–39 (Young adults) 67 (30.5) 40–59 (Mid-aged adults) 153 (69.5) Marital status Married 100 (45.5) Single 53 (24.0) Cohabiting 45 (20.5) Divorced 20 (9.1) Widow 2 (0.9) Residence Rural 106 (48.2) Urban 114 (51.8) Occupation Employed 12 (5.5) Self-employed 103 (46.8) Unemployed 105 (47.7) Prevalence of Syphilis infection among pregnant women LWHIV The study revealed that the prevalence of syphilis infection among pregnant women LWHIV in the Mtwara region was 10.9% (24/220) (Fig. 2 ). The highest prevalence of Syphilis was 10.9%, 9.5%, and 9.1%, seen among pregnant women who were on first-line ART regimen, with HIV-1 viral load of less than 50 copies/ml and multigravida respectively (Table 2 ). Table 2 Prevalence of syphilis infection in socio-demographic and clinical characteristics of the study participants (N = 220). Characteristic Prevalence of syphilis infection n (%) Facility name Likombe health center 4 (1.8) Mangaka hospital 3 (1.4) Mkomaindo hospital 8 (3.6) Ndanda hospital 9 (4.1) Age (in years) 18–39 (Young adults) 9 (4.1) 40–59 (Mid-aged adults) 15 (6.8) Number of pregnancies Primigravida 3 (1.4) Multigravida 20 (9.1) Grand multigravida 1 (0.5) HVL status (copies/ml) < 50 21 (9.5) 50–999 1 (0.5) ≥ 1000 1 (0.5) Missing 1 (0.5) WHO clinical stage of HIV Stage 1 20 (9.1) Stage 2 4 (1.8) Stage 3 0 (0.0) ART regimen First -line regimen 24 (10.9) Second-line regimen 0 (0.0) Duration on ART (in months) Less than 6 0 (0.0) 6 to 12 3 (1.4) More than 12 21 (9.5) Risk factors of syphilis infection among HIV-infected Pregnant women The results of the multivariate logistic regression showed that those pregnant women LWHIV and on ART who were in the second trimester of their pregnancy were 5 times more likely to be infected with syphilis as compared to those who were in the first trimester (Table 3 ). Table 3 Logistic regression on socio-demographic and behavioural characteristics of the study participants on syphilis infection (N = 220). Characteristic Syphilis infection status Bivariate Multivariate Negative n (%) Positive n (%) cOR (95% CI) p -value aOR (95% CI) p -value Age (in years) 18–39 (Young adults) 58 (86.6) 9 (13.4) 1 1 40–59 (Mid-aged adults) 138 (90.2) 15 (9.8) 0.70 (0.29–1.69) 0.429 0.51 (0.18–1.46) 0.211 Residence Rural 94 (88.7) 12 (11.3) 1 1 Urban 102 (89.5) 12 (10.5) 0.92 (0.39–2.15) 0.850 1.29 (0.42–4.01) 0.654 Occupation Self-employed 91 (88.3) 12 (11.7) 1.02 (0.44–2.39) 0.960 1.30 (0.50–3.42) 0.589 Unemployed 93 (88.6) 12 (11.4) 1 1 Number of pregnancies Primigravida 30 (90.9) 3 (9.1) 1 1 Multigravida 151 (88.3) 20 (11.7) 1.32 (0.37–4.74) 0.666 1.25 (0.32–4.93) 0.748 Grand multigravida 15 (93.8) 1 (6.2) 0.67 (0.06–6.97) 0.735 0.72 (0.06–9.14) 0.803 Current gestation age First trimester 67 (95.7) 3 (4.3) 1 1 Second trimester 75 (84.3) 14 (15.7) 4.17 (1.15–15.14) 0.030 5.69 (1.44–22.46) 0.013 Third trimester 54 (88.5) 7 (11.5) 2.90 (0.71–11.73) 0.136 2.97 (0.66–13.42) 0.157 The results of the multivariate logistic regression showed that the pregnant women LWHIV who were infected with hepatitis B virus were 31 times more likely to acquire syphilis infection as compared to those with no hepatitis B virus infection (Table 4 ). Table 4 Logistic regression of clinical and immunological characteristics of the study participants and syphilis infection (N = 220). Characteristic Syphilis infection status Bivariate Multivariate Negative n (%) Positive n (%) cOR (95% CI) p-value aOR (95% CI) p -value History of blood transfusion No 159 (89.3) 19 (10.7) 1(Ref) 1(Ref) Yes 37 (88.1) 5 (11.9) 1.13 (0.40–3.23) 0.818 2.12 (0.61–7.36) 0.238 CD4 count (cells/mm 3 ) < 200 27 (87.1) 4 (12.9) 1.93 (0.45–8.31) 0.380 1.44 (0.25–8.45) 0.685 200–499 77 (87.5) 11(12.5) 1.86 (0.56–6.15) 0.311 1.66 (0.40–6.95) 0.486 ≥ 500 52 (92.9) 4 (7.1) 1 (Ref) 1 (Ref) HVL status (copies/ml) < 50 177 (89.4) 21 (10.6) 1 (Ref) 1 (Ref) 50–999 11 (91.7) 1 (8.3) 0.77 (0.09–6.24) 0.803 0.38 (0.03–4.17) 0.429 ≥ 1000 4 (80.0) 1 (20.0) 2.11 (0.22–19.74) 0.514 0.38 (0.02–7.66) 0.526 WHO clinical stage of HIV Stage 1 170 (89.5) 20 (10.5) 1 (Ref) 1 (Ref) Stage 2 23 (85.2) 4 (14.8) 1.48 (0.46–4.71) 0.508 0.80 (0.17–3.85) 0.781 Duration on ART (in months) 6 to 12 16 (84.2) 3 (15.8) 1.54 (0.42–5.75) 0.517 1.95 (0.38–9.96) 0.423 More than 12 173 (89.2) 21 (10.8) 1 (Ref) 1 (Ref) Hepatitis B status Negative 186 (94.4) 11 (5.6) 1 (Ref) 1 (Ref) Positive 10 (43.5) 13 (56.5) 21..98 (7.89–61.23) < 0.001 31.39 (9.45-104.23) < 0.001 Discussion The present study reveals a notably high burden of syphilis infection (10.9%) among pregnant women LWHIV in the Mtwara region. This prevalence surpasses findings from a study conducted in southern Ethiopia, which reported a prevalence of 5.1% among pregnant women[ 1 ]. The elevated prevalence observed calls for an urgent need for strategic interventions, including enhancing routine syphilis screening services within PMTCT clinics. Comparatively, lower prevalence rates have been reported in Brazil (4.4%) and in regions of Ethiopia such as Jinka Town public health facilities (4.1%) and Northwest Ethiopia (3.7%) [ 4 , 12 ]. The study further identified a significant association between gestational age and syphilis infection. Pregnant women LWHIV and on ART in their second trimester were found to be five times more likely to contract syphilis compared to those in their first trimester. This elevated risk may be attributed to the progressive decline in immunity as pregnancy advances, a finding supported by similar studies emphasizing the susceptibility of second-trimester pregnant women to syphilis infection [ 1 ]. These findings highlight the necessity for targeted interventions during antenatal care to mitigate infection risks during the critical stages of pregnancy. Additionally, a compelling relationship between hepatitis B virus (HBV) co-infection and syphilis infection was observed. Pregnant women LWHIV who were co-infected with HBV were 31 times more likely to acquire syphilis compared to those without HBV infection. This can be attributed to the immunosuppressive effects of HBV, which weaken the body’s defense mechanisms, rendering it more susceptible to opportunistic pathogens like Treponema pallidum . Similar findings have been documented in studies conducted in Northern Ethiopia and Sudan, which also noted a significant association between HBV and HIV-syphilis co-infections[ 4 , 10 ]. These findings are consistent with global reports emphasizing the syndemic nature of Sexually Transmitted Infections (STI) among vulnerable populations. For instance, WHO highlights the importance of integrating syphilis screening with HIV and HBV testing in antenatal care settings to address co-infection risks [ 8 ]. Such integrated approaches are critical in areas like Mtwara, where overlapping infections amplify the burden of maternal and neonatal complications. The high prevalence observed in this study calls for the public health response, particularly in scaling up antenatal care services that incorporate routine testing for syphilis, HBV, and HIV[ 8 ]. Educational initiatives to raise awareness about STIs prevention, coupled with prompt treatment interventions, are imperative. Strengthening health systems through adequate training of healthcare providers, ensuring the availability of diagnostic tools, and promoting community-level engagement can significantly reduce the dual burden of HIV and syphilis co-infection[ 8 ]. The present study involved participants from the selected health facilities in the Mtwara region. This may be affected by the similar characteristics of the participants living in the same region; and thus; we recommend further study that will include participants from different regions and that will include a large sample size to give further information about this topic. Conclusion The study found a significant burden of syphilis infection among pregnant women living with HIV in the Mtwara region. It identified advanced gestational age, particularly in the second trimester, and co-infection with hepatitis B virus as key risk factors for syphilis infection. These findings highlight the need for routine and integrated screening for syphilis and other infections, including hepatitis B, in pregnant women LWHIV. Such screening is crucial for reducing the burden of these infections, preventing vertical transmission to newborns, and improving maternal and child health outcomes. Abbreviations ART, Antiretroviral Therapy; ELISA, Enzyme-Linked Immunosorbent Assay; HBV, Hepatitis B Virus; HIV, Human Immunodeficiency Virus; LWHIV, Living with HIV; PMTCT, Prevention of Mother-to-Child Transmission. Declarations Acknowledgments The authors thank the Ministry of Health and the Mtwara Southern Zone Referral Hospital administration for their tremendous support in conducting this research work. Special thanks to the Regional Medical Officer (RMO) of the Mtwara region, District Medical Officers (DMOs) of the selected districts, as well as Medical Officers in charge of Mkomaindo Hospital, St. Benedict’s Ndanda Hospital, Mangaka Hospital, and Likombe Health Center. Author Contributions V.S. and R.K. wrote the main manuscript text, and D.K. prepared figures 1-2. All authors reviewed the manuscript. Data availability statement Data is provided within the manuscript and the supplementary information files. Competing interests All authors declare that they have no commercial or other associations that may pose a conflict of interest. Clinical Trial Not applicable Funding No funding was obtained for this study. References M. Srivastava, A. Grover, and A. Srivastava, “Syphilis, Lymphogranuloma Venereum, and Granuloma Inguinale Infection in Pregnancy,” Infections and Pregnancy , pp. 285–305, 2022, doi: 10.1007/978-981-16-7865-3_20. S. J. Hawkes, G. B. Gomez, and N. 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Manyahi et al. , “Prevalence of HIV and syphilis infections among pregnant women attending antenatal clinics in Tanzania, 2011 Disease epidemiology - Infectious,” BMC Public Health , vol. 15, no. 1, pp. 1–9, May 2015, doi: 10.1186/S12889-015-1848-5/TABLES/5. “Sub-national HDI - Area Database - Global Data Lab,” hdi.globaldatalab.org , Accessed: Jun. 13, 2022. [Online]. Available: https://hdi.globaldatalab.org/areadata/shdi/ A. Amsalu, G. Ferede, and D. Assegu, “High seroprevalence of syphilis infection among pregnant women in Yiregalem hospital southern Ethiopia,” BMC Infect Dis , vol. 18, no. 1, Mar. 2018, doi: 10.1186/s12879-018-2998-8. Additional Declarations No competing interests reported. Supplementary Files S1.RawdataoftheHIVinfectedpregnantwomeninMtwaraRegion..xlsx Supporting information S1. Raw data of the HIV infected pregnant women in Mtwara Region. 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Raw data of the HIV infected pregnant women in Mtwara Region.\u003c/p\u003e","description":"","filename":"S1.RawdataoftheHIVinfectedpregnantwomeninMtwaraRegion..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5871728/v1/985cb4d5f595fc37e94a43ef.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"HIV and Syphilis in Pregnancy: A Cross-Sectional Analysis from Healthcare Facilities in Southern Tanzania","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSyphilis is a chronic systemic infection caused by the spirochete \u003cem\u003eTreponema pallidum\u003c/em\u003e. It can be transmitted sexually or through blood transfusion (acquired syphilis) and vertically from an infected mother to the fetus via the placenta (congenital syphilis) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Congenital syphilis can result from pregnant women who have syphilis passing the infection on to their unborn child. Most pregnant women who have syphilis are not identified and treated in time to prevent the infection's negative consequences on the fetus. It continues to be a significant worldwide public health issue, and its prevalence is rising globally[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver half a million instances of congenital syphilis were reported worldwide in 2016, leading to over 200,000 stillbirths and neonatal fatalities. Congenital syphilis and other unfavorable pregnancy outcomes linked to syphilis are effectively prevented and treated as long as prompt diagnosis and treatment are given[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, Congenital syphilis is the leading cause of preventable stillbirth, surpassing malaria, and significantly impacts women in low-resource settings[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2007, the World Health Organization (WHO) launched a global initiative to eliminate congenital syphilis[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite the fact that almost every country in the world advises screening pregnant women for syphilis at their first antenatal care (ANC) contact, syphilis transmission from mother to child is still a public health concern, and pregnant women are frequently left undiagnosed and untreated despite the low cost of effective diagnosis and treatment[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, women are disproportionately affected by syphilis in low-resource environments where testing rates are very low and prevalence rates are high. For instance, just 16% of women in the Democratic Republic of the Congo are screened for syphilis, despite the fact that almost 3% of them have the disease[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, expanding syphilis screening programs for expectant mothers is essential, especially for those with HIV and in low-resource environments like Tanzania.\u003c/p\u003e \u003cp\u003eIt is widely acknowledged that preventing syphilis transmission and unfavorable pregnancy outcomes can be achieved with early detection and treatment of syphilis. Prenatal syphilis screening and treatment can cut the rate of stillbirths by 82%, preterm deliveries by 64%, and neonatal mortality by 80% in endemic countries[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous epidemiologic studies have examined and reported on factors that influence the magnitude of syphilis serostatus, including maternal age, residence, educational attainment, husband's educational attainment, occupational status, number of pregnancies, history of abortion, history of sexually transmitted infections (STIs), and HIV status. However, there are significant contributing factors that have received little attention and are therefore poorly understood, such as gestation age, HIV viral load status, HBV status, and having two or more sexual partners[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Tanzania and most developing nations, perinatal morbidity and mortality are caused by syphilis during pregnancy, which is one of the most significant public health issues, according to several research conducted throughout the globe. According to a Tanzanian study, 2.5% of expectant mothers who attended ANC had syphilis positive results[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In order to develop an intervention on these aspects, improve therapy, and enhance health promotion programs, it may be necessary to have a thorough grasp of the linked components. However, there is limited research on syphilis and its associated factors among pregnant women living with HIV (LWHIV) in Tanzania, particularly in the Mtwara region. This study aimed to address this gap by assessing the double burden of syphilis and HIV among pregnant women, and identifying associated factors in this population in Southern Tanzania.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eBetween February and April 2022, a health facility based cross-sectional study was carried out in selected health institutions in the Mtwara region to examine the prevalence and risk factors for Syphilis infection among pregnant women LWHIV undergoing Prevention of Mother to Child Transmission (PMTCT) clinics.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy setting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in the Mtwara region, located in the southern part of Tanzania. According to the 2022 census, Mtwara, one of the 31 administrative areas in the nation, has a total size of 16,710 square kilometers and 1,270,854 residents[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Geographically, the region lies at latitude \u0026minus;\u0026thinsp;10.31\u0026deg;S and longitude 40.18\u0026deg;E. There are 221 health facilities in the Mtwara region that provide PMTCT services. Purposively chosen sites for this study were Likombe Health Center, Ndanda Hospital, Mangaka Hospital, and Mkomaindo Hospital. Compared to other health facilities in the area, these facilities were selected because of the significant volume of patients they serve for PMTCT services[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003e All pregnant women LWHIV attending PMTCT clinics at Mkomaindo district hospital, Ndanda hospital, Mangaka hospital and Likombe health center in Mtwara region and who met the inclusion criteria.\u003c/p\u003e\n\u003ch3\u003eInclusion criteria\u003c/h3\u003e\n\u003cp\u003ePregnant women (\u0026ge;\u0026thinsp;18 years old) of any gestation age (first, second or third trimester) LWHIV and on Antiretralviral Therapy (ART) attending PMTCT clinics in selected study sites and who provided consent to participate in the study.\u003c/p\u003e\n\u003ch3\u003eExclusion criteria\u003c/h3\u003e\n\u003cp\u003eHIV-infected pregnant women who have a confirmed diagnosis of syphilis infection and have started treatment.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample size estimation and Sampling method\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eSample size estimation\u003c/h2\u003e \u003cp\u003eSample size was calculated using the \u003cem\u003eKish and Leslie\u003c/em\u003e formula based on the data from a prevalence study conducted in Mbeya, Tanzania, with a Syphilis prevalence of 5.1%[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We used a two-sided 95% confidence interval, a marginal error of 3%, and by considering a 10% non-response rate. The resulting sample size was 220.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eThe sample size distribution per PMTCT facility\u003c/h3\u003e\n\u003cp\u003eThe sample size distribution for pregnant women LWHIV and on ART during the study period is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 230 pregnant women living with HIV were initially enrolled from four PMTCT clinics in the Mtwara region. Among them, 223 women were aged over 18 years and on ART. Of these, one participant declined to participate in the study, and samples from two participants were insufficient for laboratory analysis. Consequently, 220 pregnant women were included in the final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Probability Proportional to Size (PPS) method was employed to determine the sample size distribution across the selected health facilities. The allocation was as follows: Likombe Health Center (39 participants, 17.7%), Mangaka Hospital (36 participants, 16.4%), Mkomaindo Hospital (75 participants, 34.1%), and Ndanda Hospital (70 participants, 31.8%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSampling method\u003c/h2\u003e \u003cp\u003eBased on their planned follow-up visits at PMTCT clinics during prenatal clinics, study participants were chosen using a systematic random sampling technique. A list of eligible women LWHIV was compiled for each facility based on the required sample size, and each participant was assigned a unique identifier. The sampling fraction was calculated by dividing the total number of eligible attendees by the sample size for the facility. A random starting point within the sampling interval was chosen, and participants were selected at defined intervals (n\u0026thinsp;=\u0026thinsp;2) based on clinic attendance. If a selected participant declined, the next eligible individual within the same timeframe was included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData collection tools and procedures\u003c/h2\u003e \u003cp\u003eA structured questionnaire was employed to collect data on socio-demographic characteristics, clinical details (including sexual history, gestational age, obstetric history such as gravidity, parity, and abortion, history of sexually transmitted infections (STIs), and surgical history), as well as socio-cultural information (e.g., history of tattooing) from the participants. Additional clinical parameters, such as recent HIV viral load, WHO clinical staging of HIV, ART regimen, and recent CD4 count results, were retrieved from participants' care and treatment cards (CTC2) and the CTC2 database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eVariables\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eDependent variable\u003c/h2\u003e \u003cp\u003eThe dependent variable was syphilis seropositivity, classified as a binary outcome: syphilis seropositive or syphilis seronegative.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eIndependent variables\u003c/h2\u003e \u003cp\u003eThe independent variables included socio-demographic characteristics such as age (categorized as 18\u0026ndash;39 or \u0026ge;\u0026thinsp;40 years), marital status (married, single, divorced, or cohabiting), occupation status (self-employed or unemployed), place of residence (rural or urban), education level (non-formal, primary, secondary, college, or university), facility name (Likombe Health Center, Mangaka Hospital, Mkomaindo Hospital, or Ndanda Hospital), and daily income in Tanzanian shillings (\u0026lt;\u0026thinsp;2400, 2400\u0026ndash;12000, or \u0026gt;\u0026thinsp;12000). Clinical information and parameters included history of blood transfusion (yes or no), WHO clinical staging of HIV (Stage 1, Stage 2, Stage 3, or Stage 4), recent CD4 count in cells/mm\u0026sup3; (\u0026lt;\u0026thinsp;200, 200\u0026ndash;499, or \u0026ge;\u0026thinsp;500), recent HIV viral load in copies/ml (\u0026lt;\u0026thinsp;50, 50\u0026ndash;999, or \u0026ge;\u0026thinsp;1000), and Hepatitis B serostatus (positive or negative). Additional clinical variables included the number of sexual partners (one, two, or more than two), history of sexually transmitted infections (yes or no), number of live children (one, two to three, or four or more), gestational period (first trimester, second trimester, or third trimester), ART regimen (first-line or second-line), and duration on ART in months (\u0026lt;\u0026thinsp;6, 6\u0026ndash;12, or \u0026gt;\u0026thinsp;12).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory procedures\u003c/h2\u003e \u003cp\u003eBlood samples (4 mL) were collected from participants in plain vacutainer tubes, labeled, and transported to the study site laboratories. The samples were processed into serum by centrifugation at 3000 rpm for 10 minutes and aliquoted into cryogenic tubes for temporary storage at -80\u0026deg;C. Syphilis screening was conducted at the health facility laboratories using the SD Bioline Syphilis 3.0 rapid test, a highly sensitive and specific lateral flow immunoassay. Positive samples were confirmed using an automated ELISA (Abbott ARCHITECT PLUS\u0026reg; i2000SR) at the accredited NBTS Southern Zone Laboratory in Mtwara. All procedures adhered to Standard Operating Procedures (SOPs), with strict quality control and verification of reagents and consumables. Data accuracy was ensured through careful recording and double-checking by independent personnel.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eData quality assurance\u003c/h2\u003e \u003cp\u003eThe data collection tools were validated through a pre-testing phase to ensure effectiveness. Calibration and quality control procedures were followed, including verification of the Abbott ARCHITECT PLUS\u0026reg; i2000SR immunoassay analyzer using positive and negative controls as recommended by the manufacturer. Control assays were performed daily and confirmed to meet specified concentration ranges before analyzing participant samples. All test results were thoroughly documented and independently cross-verified to ensure accuracy before data analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eData processing and analysis\u003c/h2\u003e \u003cp\u003eData cleaning and analysis were conducted using Microsoft Excel\u0026reg; 2019 and STATA version 15 package (StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: Stata-Corp L.L.C.). Categorical variables were analyzed for frequency and proportion, while continuous variables were summarized using the median (interquartile range). Bivariate and multivariate logistic regression models were applied to assess relationships between dependent and independent variables. Bivariate analysis evaluated associations between each independent variable and the dependent variable, with variables having \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.20 included in the multivariate analysis. Statistically significant risk factors for syphilis infection were identified with \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026le;\u0026thinsp;0.05 and 95% confidence intervals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement\u003c/h2\u003e \u003cp\u003e The ethical approval of the study was obtained from the Institutional Review Board (IRB) of the Muhimbili University of Health and Allied Sciences (MUHAS) with approval certificate No. MUHAS-02-2022-978. Permission to conduct the study was requested from the Regional administrative secretary\u0026rsquo;s office (RAS-Mtwara) and District Medical Officers of all selected districts as well as the medical officer in charge of Mkomaindo hospital, Ndanda hospital, Mangaka hospital and Likombe health center. Written informed consent was obtained from every participant prior to inclusion in the study. Data were anonymized before being accessed and all respondents provided informed, written consent and were assured of confidentiality through the use of special identification codes. Data were protected and kept by the principal investigator and were accessed only by authorized personnel, and for any necessary transfer, permission was given by the principal investigator. Positive results were communicated within 48\u0026ndash;72 hours to the clinicians or nurses at the respective hospitals.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics of the study participants\u003c/h2\u003e \u003cp\u003eIn this study, a total of 220 pregnant women LWHIV in Mtwara region were enrolled. The study participants\u0026rsquo; median age was 32.7 years (IQR: 27.6\u0026ndash;37.6). The majority 34.1% (75/220) of the participants were from Mkomaindo Hospital, and the majority 71.4% (157/220) of all participants attained only a primary school level of education; 47.7% (105/220) were unemployed, 51.8% (114/220) were living in urban area and 45.5% (100/220) were married (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the study participants (N\u0026thinsp;=\u0026thinsp;220).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility name\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLikombe health center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (17.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMangaka hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (16.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMkomaindo hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (34.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNdanda hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (31.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (in years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.7(27.6\u0026ndash;37.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;39 (Young adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (30.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;59 (Mid-aged adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e153 (69.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (24.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (20.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106 (48.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114 (51.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103 (46.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105 (47.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Syphilis infection among pregnant women LWHIV\u003c/h2\u003e \u003cp\u003eThe study revealed that the prevalence of syphilis infection among pregnant women LWHIV in the Mtwara region was 10.9% (24/220) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The highest prevalence of Syphilis was 10.9%, 9.5%, and 9.1%, seen among pregnant women who were on first-line ART regimen, with HIV-1 viral load of less than 50 copies/ml and multigravida respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of syphilis infection in socio-demographic and clinical characteristics of the study participants (N\u0026thinsp;=\u0026thinsp;220).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrevalence of syphilis infection\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFacility name\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLikombe health center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMangaka hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMkomaindo hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNdanda hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (4.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (in years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;39 (Young adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (4.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;59 (Mid-aged adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of pregnancies\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e20 (9.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrand multigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHVL status (copies/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e21 (9.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO clinical stage of HIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst -line regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24 (10.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond-line regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration on ART (in months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 to 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e21 (9.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eRisk factors of syphilis infection among HIV-infected Pregnant women\u003c/h2\u003e \u003cp\u003eThe results of the multivariate logistic regression showed that those pregnant women LWHIV and on ART who were in the second trimester of their pregnancy were 5 times more likely to be infected with syphilis as compared to those who were in the first trimester (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression on socio-demographic and behavioural characteristics of the study participants on syphilis infection (N\u0026thinsp;=\u0026thinsp;220).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSyphilis infection status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAge (in years)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;39 (Young adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (86.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;59 (Mid-aged adults)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e138 (90.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 (0.29\u0026ndash;1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51 (0.18\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94 (88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.39\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.29 (0.42\u0026ndash;4.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91 (88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.44\u0026ndash;2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.30 (0.50\u0026ndash;3.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93 (88.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of pregnancies\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (90.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151 (88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32 (0.37\u0026ndash;4.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25 (0.32\u0026ndash;4.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrand multigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.06\u0026ndash;6.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72 (0.06\u0026ndash;9.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent gestation age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (95.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.17 (1.15\u0026ndash;15.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.69 (1.44\u0026ndash;22.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThird trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (88.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.90 (0.71\u0026ndash;11.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.97 (0.66\u0026ndash;13.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results of the multivariate logistic regression showed that the pregnant women LWHIV who were infected with hepatitis B virus were 31 times more likely to acquire syphilis infection as compared to those with no hepatitis B virus infection (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression of clinical and immunological characteristics of the study participants and syphilis infection (N\u0026thinsp;=\u0026thinsp;220).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSyphilis infection status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eaOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of blood transfusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.40\u0026ndash;3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.12 (0.61\u0026ndash;7.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD4 count (cells/mm\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (87.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.93 (0.45\u0026ndash;8.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.44 (0.25\u0026ndash;8.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u0026ndash;499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77 (87.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.86 (0.56\u0026ndash;6.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.66 (0.40\u0026ndash;6.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHVL status (copies/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177 (89.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (91.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77 (0.09\u0026ndash;6.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38 (0.03\u0026ndash;4.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.11 (0.22\u0026ndash;19.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38 (0.02\u0026ndash;7.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO clinical stage of HIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (85.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48 (0.46\u0026ndash;4.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80 (0.17\u0026ndash;3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration on ART (in months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 to 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.54 (0.42\u0026ndash;5.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95 (0.38\u0026ndash;9.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173 (89.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHepatitis B status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e186 (94.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21..98 (7.89\u0026ndash;61.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.39 (9.45-104.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study reveals a notably high burden of syphilis infection (10.9%) among pregnant women LWHIV in the Mtwara region. This prevalence surpasses findings from a study conducted in southern Ethiopia, which reported a prevalence of 5.1% among pregnant women[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The elevated prevalence observed calls for an urgent need for strategic interventions, including enhancing routine syphilis screening services within PMTCT clinics. Comparatively, lower prevalence rates have been reported in Brazil (4.4%) and in regions of Ethiopia such as Jinka Town public health facilities (4.1%) and Northwest Ethiopia (3.7%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study further identified a significant association between gestational age and syphilis infection. Pregnant women LWHIV and on ART in their second trimester were found to be five times more likely to contract syphilis compared to those in their first trimester. This elevated risk may be attributed to the progressive decline in immunity as pregnancy advances, a finding supported by similar studies emphasizing the susceptibility of second-trimester pregnant women to syphilis infection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These findings highlight the necessity for targeted interventions during antenatal care to mitigate infection risks during the critical stages of pregnancy.\u003c/p\u003e \u003cp\u003eAdditionally, a compelling relationship between hepatitis B virus (HBV) co-infection and syphilis infection was observed. Pregnant women LWHIV who were co-infected with HBV were 31 times more likely to acquire syphilis compared to those without HBV infection. This can be attributed to the immunosuppressive effects of HBV, which weaken the body\u0026rsquo;s defense mechanisms, rendering it more susceptible to opportunistic pathogens like \u003cem\u003eTreponema pallidum\u003c/em\u003e. Similar findings have been documented in studies conducted in Northern Ethiopia and Sudan, which also noted a significant association between HBV and HIV-syphilis co-infections[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese findings are consistent with global reports emphasizing the syndemic nature of Sexually Transmitted Infections (STI) among vulnerable populations. For instance, WHO highlights the importance of integrating syphilis screening with HIV and HBV testing in antenatal care settings to address co-infection risks [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Such integrated approaches are critical in areas like Mtwara, where overlapping infections amplify the burden of maternal and neonatal complications.\u003c/p\u003e \u003cp\u003eThe high prevalence observed in this study calls for the public health response, particularly in scaling up antenatal care services that incorporate routine testing for syphilis, HBV, and HIV[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Educational initiatives to raise awareness about STIs prevention, coupled with prompt treatment interventions, are imperative. Strengthening health systems through adequate training of healthcare providers, ensuring the availability of diagnostic tools, and promoting community-level engagement can significantly reduce the dual burden of HIV and syphilis co-infection[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe present study involved participants from the selected health facilities in the Mtwara region. This may be affected by the similar characteristics of the participants living in the same region; and thus; we recommend further study that will include participants from different regions and that will include a large sample size to give further information about this topic.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study found a significant burden of syphilis infection among pregnant women living with HIV in the Mtwara region. It identified advanced gestational age, particularly in the second trimester, and co-infection with hepatitis B virus as key risk factors for syphilis infection. These findings highlight the need for routine and integrated screening for syphilis and other infections, including hepatitis B, in pregnant women LWHIV. Such screening is crucial for reducing the burden of these infections, preventing vertical transmission to newborns, and improving maternal and child health outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eART, Antiretroviral Therapy; ELISA, Enzyme-Linked Immunosorbent Assay; HBV, Hepatitis B Virus; HIV, Human Immunodeficiency Virus; LWHIV, Living with HIV; PMTCT, Prevention of Mother-to-Child Transmission.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors thank the Ministry of Health and the Mtwara Southern Zone Referral Hospital administration for their tremendous support in conducting this research work. Special thanks to the Regional Medical Officer (RMO) of the Mtwara region, District Medical Officers (DMOs) of the selected districts, as well as Medical Officers in charge of Mkomaindo Hospital, St. Benedict\u0026rsquo;s Ndanda Hospital, Mangaka Hospital, and Likombe Health Center.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eV.S. and R.K. wrote the main manuscript text, and D.K. prepared figures 1-2. All authors reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData availability statement\u003c/p\u003e\n\u003cp\u003eData is provided within the manuscript and the supplementary information files.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no commercial or other associations that may pose a conflict of interest.\u003c/p\u003e\n\u003cp\u003eClinical Trial\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this study. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eM. Srivastava, A. Grover, and A. Srivastava, \u0026ldquo;Syphilis, Lymphogranuloma Venereum, and Granuloma Inguinale Infection in Pregnancy,\u0026rdquo; \u003cem\u003eInfections and Pregnancy\u003c/em\u003e, pp. 285\u0026ndash;305, 2022, doi: 10.1007/978-981-16-7865-3_20.\u003c/li\u003e\n \u003cli\u003eS. J. Hawkes, G. B. Gomez, and N. Broutet, \u0026ldquo;Early Antenatal Care: Does It Make a Difference to Outcomes of Pregnancy Associated with Syphilis? A Systematic Review and Meta-Analysis,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 8, no. 2, p. e56713, Feb. 2013, doi: 10.1371/JOURNAL.PONE.0056713.\u003c/li\u003e\n \u003cli\u003eT. Lemmet \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;High syphilis prevalence and incidence in people living with HIV and Preexposure Prophylaxis users: A retrospective review in the French Dat\u0026rsquo;AIDS cohort,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 17, no. 5, p. e0268670, May 2022, doi: 10.1371/JOURNAL.PONE.0268670.\u003c/li\u003e\n \u003cli\u003eA. F. B. Rocha, M. A. L. Ara\u0026uacute;jo, M. M. Taylor, E. O. Kara, and N. J. N. Broutet, \u0026ldquo;Treatment administered to newborns with congenital syphilis during a penicillin shortage in 2015, Fortaleza, Brazil,\u0026rdquo; \u003cem\u003eBMC Pediatr\u003c/em\u003e, vol. 21, no. 1, pp. 1\u0026ndash;9, Dec. 2021, doi: 10.1186/S12887-021-02619-X/TABLES/4.\u003c/li\u003e\n \u003cli\u003eD. Brandenburger and E. Ambrosino, \u0026ldquo;The impact of antenatal syphilis point of care testing on pregnancy outcomes: A systematic review,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 16, no. 3, p. e0247649, Mar. 2021, doi: 10.1371/JOURNAL.PONE.0247649.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization, \u0026ldquo;Infection Surveillance,\u0026rdquo; \u003cem\u003eSouth Med J\u003c/em\u003e, vol. 70, no. Supplement, p. 74, 2018, Accessed: Jun. 13, 2022. [Online]. Available: file:///C:/Users/Amlan Roy/Desktop/Project_rony.SEU/manuscript..final/references/Report on global sexually transmitted.pdf\u003c/li\u003e\n \u003cli\u003eA. Storey, F. Seghers, L. Pyne-Mercier, R. W. Peeling, M. N. Owiredu, and M. M. Taylor, \u0026ldquo;Syphilis diagnosis and treatment during antenatal care: the potential catalytic impact of the dual HIV and syphilis rapid diagnostic test,\u0026rdquo; \u003cem\u003eLancet Glob Health\u003c/em\u003e, vol. 7, no. 8, pp. e1006\u0026ndash;e1008, Aug. 2019, doi: 10.1016/S2214-109X(19)30248-7/ATTACHMENT/3F3B8326-3F68-432D-BBAD-A8E48C9CDCD7/MMC1.PDF.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;Global health sector strategy on sexually transmitted infections 2016-2021: toward ending STIs | Geneva; World Health Organization; 2016. (WHO/RHR/16.09). | WHOLIS.\u0026rdquo; Accessed: Jun. 13, 2022. [Online]. Available: https://pesquisa.bvsalud.org/portal/resource/pt/who-246296\u003c/li\u003e\n \u003cli\u003eH. Blencowe, S. Cousens, M. Kamb, S. Berman, and J. E. Lawn, \u0026ldquo;Lives saved tool supplement detection and treatment of syphilis in pregnancy to reduce syphilis related stillbirths and neonatal mortality,\u0026rdquo; \u003cem\u003eBMC Public Health\u003c/em\u003e, vol. 11, no. SUPPL. 3, pp. 1\u0026ndash;16, Apr. 2011, doi: 10.1186/1471-2458-11-S3-S9/TABLES/2.\u003c/li\u003e\n \u003cli\u003eK. Tareke, A. Munshea, and E. Nibret, \u0026ldquo;Seroprevalence of syphilis and its risk factors among pregnant women attending antenatal care at Felege Hiwot Referral Hospital, Bahir Dar, northwest Ethiopia: A cross-sectional study,\u0026rdquo; \u003cem\u003eBMC Res Notes\u003c/em\u003e, vol. 12, no. 1, pp. 1\u0026ndash;7, Jan. 2019, doi: 10.1186/S13104-019-4106-6/TABLES/3.\u003c/li\u003e\n \u003cli\u003eC. Kengne-Nde \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Highlighting a population-based re-emergence of Syphilis infection and assessing associated risk factors among pregnant women in Cameroon: Evidence from the 2009, 2012 and 2017 national sentinel surveillance surveys of HIV and syphilis,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 15, no. 11, p. e0241999, Nov. 2020, doi: 10.1371/JOURNAL.PONE.0241999.\u003c/li\u003e\n \u003cli\u003eM. Enbiale, A. Getie, F. Haile, B. Tekabe, and D. Misekir, \u0026ldquo;Magnitude of syphilis sero-status and associated factors among pregnant women attending antenatal care in Jinka town public health facilities, Southern Ethiopia, 2020,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 16, no. 9, p. e0257290, Sep. 2021, doi: 10.1371/JOURNAL.PONE.0257290.\u003c/li\u003e\n \u003cli\u003eJ. Manyahi \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Prevalence of HIV and syphilis infections among pregnant women attending antenatal clinics in Tanzania, 2011 Disease epidemiology - Infectious,\u0026rdquo; \u003cem\u003eBMC Public Health\u003c/em\u003e, vol. 15, no. 1, pp. 1\u0026ndash;9, May 2015, doi: 10.1186/S12889-015-1848-5/TABLES/5.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;Sub-national HDI - Area Database - Global Data Lab,\u0026rdquo; \u003cem\u003ehdi.globaldatalab.org\u003c/em\u003e, Accessed: Jun. 13, 2022. [Online]. Available: https://hdi.globaldatalab.org/areadata/shdi/\u003c/li\u003e\n \u003cli\u003eA. Amsalu, G. Ferede, and D. Assegu, \u0026ldquo;High seroprevalence of syphilis infection among pregnant women in Yiregalem hospital southern Ethiopia,\u0026rdquo; \u003cem\u003eBMC Infect Dis\u003c/em\u003e, vol. 18, no. 1, Mar. 2018, doi: 10.1186/s12879-018-2998-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prevalence, Syphilis infection, Hepatitis B virus, Human immunodeficiency virus, Prevention of Mother to Child Transmission","lastPublishedDoi":"10.21203/rs.3.rs-5871728/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5871728/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSyphilis, caused by \u003cem\u003eTreponema pallidum\u003c/em\u003e, is a chronic infection transmitted sexually, through blood transfusion, or vertically from mother to fetus. In pregnancy, it poses a significant public health risk, particularly in developing countries like Tanzania, contributing to perinatal morbidity and mortality. However, data on syphilis and its risk factors, especially among pregnant women living with HIV, are scarce. This study aimed to assess the burden and identify risk factors for syphilis infection among HIV-infected pregnant women attending Prevention of Mother-to-Child Transmission clinic services in selected health facilities in the Mtwara region. This health facility-based cross-sectional study was conducted over three months among pregnant women living with HIV attending Prevention of Mother-to-Child Transmission clinic services in the Mtwara region. A structured questionnaire was used to gather demographic, clinical, and laboratory data. Blood samples (4 ml) were collected for syphilis screening and confirmatory tests. Bivariate and multivariate logistic regression analyses identified significant factors associated with syphilis infection in pregnant women, with a \u003cem\u003ep\u003c/em\u003e-value \u0026lt;0.05 considered significant. Two hundred and twenty (n=220) pregnant women living with HIV were enrolled in this study. The median age of the participants was 32.7 years (IQR: 27.6-37.6). The majority (45.5%) of the participants were married, 71.4% had primary education, 47.7% were unemployed, 77.7% were multigravida, and 40.5% were in the second trimester. The prevalence of syphilis infection was 10.9% (24/220). In addition, being in the second trimester of the gestation period [aOR=5.69: 95% CI 1.44-22.46, \u003cem\u003ep\u003c/em\u003e=0.013] and being infected with hepatitis B virus [aOR=31.39: 95% CI 9.45-104.23, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001] were independent factors associated with syphilis infection among pregnant women living with HIV in the Mtwara region. The study revealed a significant burden of syphilis infection among pregnant women living with HIV in the Mtwara region, with advanced gestational age (especially in the second trimester) and co-infection with hepatitis B virus identified as key risk factors. The findings emphasize the importance of routine, integrated screening for syphilis and other infections, including hepatitis B, to reduce infection burden, prevent vertical transmission, and improve maternal and child health outcomes.\u003c/p\u003e","manuscriptTitle":"HIV and Syphilis in Pregnancy: A Cross-Sectional Analysis from Healthcare Facilities in Southern Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-28 09:27:08","doi":"10.21203/rs.3.rs-5871728/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c4efe2a-72dd-446d-b6c7-463db180f6b1","owner":[],"postedDate":"January 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-28T09:27:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-28 09:27:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5871728","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5871728","identity":"rs-5871728","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}