Maternal alcohol consumption during pregnancy and associated factors among pregnant women in Tanzania: Evidence from the 2022 Tanzania Demographic and Health Survey

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Alcohol use during pregnancy is associated with an increased risk of miscarriage, stillbirth, Fetal Alcohol Spectrum Disorders, and it can impair fetal growth and lead to low birth weight. This study aims to investigate the prevalence of alcohol use among pregnant women and identify associated factors utilizing data from the 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS). Methods This was an analytical cross-sectional survey design utilizing secondary data from the 2022 TDHS-MIS. The survey employed a multistage cluster sampling method to generate representative national and sub-national health and health-related indicators between February and July 2022. A total of 1,182 pregnant women were included in the analysis. Data analysis involved descriptive statistics and binary logistic regression using STATA version 18.5 to assess factors associated with maternal alcohol consumption. Adjusted odds ratios (aOR) with a 95% confidence interval (CI) were computed to estimate the strength of the association between independent variables and alcohol use. Results The mean age of the participants was 27.3 years (standard deviation: 6.9). The overall prevalence of alcohol consumption during pregnancy among pregnant women in Tanzania was 3.9% (95% CI: 2.75–5.39). Factors associated with alcohol consumption were; women aged 25–34 (aOR = 5.17, 95%CI: 1.62–16.51) and more than 35 years of age (aOR = 20.89, 95%CI: 6.55–66.62), women who were never married (aOR = 7.89, 95%CI: 2.20-28.25), On the other hand, women living in the western zone (aOR = 0.20, 95%CI: 0.04–0.88). Conclusion The study reveals a concerning prevalence of alcohol consumption during pregnancy in Tanzania.​ Key demographic factors influencing alcohol use include maternal age, marital status, and notable regional disparities, particularly lower rates in Zanzibar compared to the western zone. These findings highlight the necessity for targeted public health initiatives aimed at educating pregnant women. Alcohol Consumption Pregnancy Pregnant women Tanzania Background Alcohol consumption during pregnancy poses significant risks to both maternal and fetal health, leading to a series of adverse outcomes [ 1 ]. Research has shown that alcohol use during pregnancy is associated with an increased risk of miscarriage and stillbirth, with specific studies indicating that heavy drinking can impair fetal growth and lead to low birth weight [ 2 ]. Moreover, no safe amount of alcohol has been established for pregnant women, and any level of consumption can cause lifelong effects on the child, including cognitive and behavioural impairments characteristic of Fetal Alcohol Spectrum Disorders (FASD) [ 3 ]. Alcohol-related neurodevelopmental disorders can affect educational and social outcomes throughout a child's life [ 4 ]. Total abstinence from alcohol during pregnancy has been documented as the most effective strategy to ensure the health and well-being of both mother and child [ 5 ]. Still, there are reported use of alcohol during pregnancy which poses a need for continuously exploring this issue. Globally, approximately 10% of women consume alcohol while pregnant, with significant regional variations in prevalence rates [ 6 ]. In developed countries, consumption is notably higher [ 7 ], reporting rates of 25–46% among pregnant women, highlighting a concerning trend [ 3 , 6 ]. This disparity is underscored by differing cultural norms and alcohol consumption patterns, suggesting that underlying social attitudes toward drinking may influence pregnant women's behaviours regarding alcohol [ 3 , 8 ]. Additionally, nearly 14% of pregnant individuals in the United States reported current drinking, with about 5% engaging in binge drinking [ 9 ]. These figures illustrate the scale of the challenge faced globally regarding alcohol consumption during pregnancy and emphasize the need for effective public health interventions to address this issue. In Sub-Saharan Africa, the situation is similarly concerning, with studies indicating varying prevalence rates of alcohol consumption among pregnant women, ranging from approximately 2.5–59.28% across different countries [ 10 – 12 ]. Specific studies have reported that in countries like Ghana, the prevalence of alcohol consumption during pregnancy can reach as high as 48%, while in regions of Nigeria, figures have been reported as high as 59.3% [ 11 , 13 ]. In contrast, other nations such as Burkina Faso have demonstrated lower rates, with a study revealing a self-reported alcohol use of 18.5% among pregnant women [ 13 , 14 ]. The significant variations in prevalence can largely be attributed to cultural influences, social norms surrounding alcohol use, and differences in research methodologies [ 11 , 13 ]. This inconsistency underscores the urgent need for targeted public health interventions to address alcohol consumption during pregnancy within the region, considering its implications for maternal and child health. In Tanzania, the prevalence of alcohol use among pregnant women has been reported in some areas at alarming rates, with a recent study indicating that up to 42.2% consume alcohol at least once a week [ 15 , 16 ]. Previous small-scale studies have provided crucial data, demonstrating that factors such as maternal age, education level, religion, and access to antenatal care significantly influence alcohol consumption patterns among pregnant women in Tanzania [ 16 ]. Despite the established risks and increasing prevalence of alcohol use during pregnancy [ 17 ], there remains a significant gap in public health strategies aimed at addressing this critical issue within Tanzania. This highlights a pressing public health challenge that necessitates epidemiological surveys and targeted interventions to enhance awareness regarding the detrimental effects of alcohol consumption during pregnancy. This study aimed to provide an overview of the prevalence of alcohol use during pregnancy among pregnant women in Tanzania and the associated factors identified through the most recent 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS-MIS) data analysis. The findings of this study will contribute to the existing body of literature and inform policymakers and healthcare providers of the urgent need for interventions designed to reduce alcohol consumption during pregnancy, ultimately improving maternal and child health outcomes in the region. Methods Data source and design This study was an analytical cross-sectional survey that utilized secondary data from the 2022 TDHS-MIS, which conducts nationally representative population-based household surveys typically every five years. The data were extracted in the file code TZGR82FL [18]. The survey was executed by the Tanzania National Bureau of Statistics in collaboration with the Ministries of Tanzania Mainland and Zanzibar. Population and sampling Data for this study was obtained from the latest DHS conducted between 24 February to 21 July 2022 across all regions in Tanzania. The target population for the 2022 TDHS-MIS included women of reproductive age (15–49 years) across the 31 administrative regions in Tanzania. At the country level, a sampling frame is usually obtained. To minimize sampling errors, the country was stratified by geographic region and by urban/rural areas within each region, followed by a two-stage sampling to select a household to be surveyed. The first sampling was to select a primary sampling unit (PSU) and then select a household. PSUs are survey clusters that are usually based on census enumeration areas (EAs). A probability proportion to size was employed in each stratum to select the PSU. For each selected PSU, a complete household listing was done. This was then followed by selecting a fixed number of households to be surveyed using equal probability systematic sampling. All women who had spent the night before the survey in the selected households were eligible for the survey. A total of 15,254 women of reproductive age were interviewed. This study analysed data from the women who reported being pregnant during the survey of 1,182 women of reproductive age (weighted). Study variable Dependent variable The outcome variable for this study was alcohol consumption responses to the question, “During the past 30 days, how many days did you have a drink that contains alcohol?” Current alcohol consumption was defined as those pregnant women who drank daily or had drunk in the past 30 days that contained alcohol based coded as ‘1’ and otherwise ‘0’. Independent variables The independent variables were included based on the available data and literature [12,13,17]; age in years, education level (no formal education, primary, secondary or higher), husband’s education level (no formal education, primary, secondary or higher), place of residence (urban or rural), marital status (never married, married, cohabiting or separated/divorced), exposure to media (listening to radio or reading newspaper or watching television less than once a week or at least once a week and otherwise), wealth index (poorest, poorer, middle, richer or richest), wanted the current pregnancy (yes or no), working status (yes or no), parity (≤2 or ≥3), ever tested for HIV (yes or no), terminated a pregnancy (yes or no), visited by fieldworker in the past 12 months (yes or no), screened for cervical cancer (yes or no) and geographical zones (western, northern, central, southern, eastern or Zanzibar). Statistical analysis Data was coded and analysed using STATA version 18.5 (STATA Corp, College Station, TX). Descriptive statistics were presented using means, standard deviation (SD) and medians, interquartile range (IQR) for continuous variables, and frequency and proportion for categorical variables. The Pearson chi-square test was used to compare the differences in the proportion of alcohol use during pregnancy across participants’ characteristics. All explanatory variables in the model were evaluated for multicollinearity. We applied a sample weight (v005/1,000,000) and the ‘ svyset ’ function in Stata was used to correct for over or under-sampling and the complex design of the DHS. Finally, a weighted binary logistic regression model was fitted to determine the factors associated with alcohol consumption during pregnancy. Univariate analyses were performed by fitting each independent variable against the dependent variable. Independent variables with p-values of < 0.05 in the univariate analyses and those considered in the literature as a potential confounder were included in the development of multivariable regression model through a backward selection at p<0.2. The odds ratio (OR) and associated 95% confidence intervals (CI) were presented to estimate the magnitude and strength of the association. A statistically significant was considered for a p-value < 0.05. Ethical consideration The use of this data was approved by MEASURE Tanzania Demographic and Health Surveys after we requested the data analysis idea. We downloaded the dataset from the website of the DHS Program after being granted permission. RESULTS Characteristics of study participants Our findings show 39.1 were adolescent girls and young women, and more than half (60.4%) were married. Regarding education, 57.5% had completed primary education and among those who had a partner, more than half (58.4%) of their partner had completed primary education. We also found that more than half were currently working (61.2%), and more than two-thirds were exposed to media (67.5%). Just 16.0% had ever terminated pregnancy, and only 4.4% had been visited by fieldworkers in the past 12 months. (Table 1) The distribution of alcohol consumption was significantly different with age group, marital status, working status, parity, termination of pregnancy and geographical zones (p<0.05), as highlighted in Table 1. Table 1: Demographic characteristics and distribution of alcohol consumption during pregnancy (N=1,182) Characteristics n (%) Consumed alcohol n (%), n=46 p-value Age group (years) <0.001 15-24 462 (39.1) 4 (0.9) 25-34 512 (43.3) 19 (3.7) 35+ 208 (17.6) 23 (10.9) Mean (±SD) 27.3 (6.9) Marital status 0.001 Single 94 (8.0) 4 (4.1) Married 714 (60.4) 14 (1.9) Cohabiting 302 (25.6) 22 (7.1) Separated/Widowed 71 (6) 6 (9.2) Education level 0.531 No formal education 226 (19.1) 10 (4.2) Primary 679 (57.5) 29 (4.3) Secondary 277 (23.4) 7 (2.6) Husband’s education 0.395 No formal education 116 (11.4) 5 (4.4) Primary 594 (58.4) 24 (4.1) Secondary 307 (30.2) 6 (1.9) Currently working 0.017 No 458 (38.8) 8 (1.8) Yes 724 (61.2) 38 (5.2) Wealth index 0.240 Poorest 265 (22.5) 14 (5.2) Poorer 234 (19.8) 12 (4.9) Middle 206 (17.4) 7 (3.5) Richer 229 (19.4) 10 (4.5) Richest 247 (20.9) 3 (1.1) Exposure to media 0.644 No 385 (32.5) 13 (3.4) Yes 797 (67.5) 33 (4.1) Residence 0.054 Urban 329 (27.8) 7 (2.1) Rural 853 (72.2) 39 (4.6) Wanted current pregnancy 0.747 Wanted 1128 (95.5) 43 (3.8) Not wanted 54 (4.5) 3 (4.8) Parity 0.003 ≤2 699 (59.2) 14 (2.0) ≥3 483 (40.8) 32 (6.5) Ever terminated pregnancy 0.049 No 992 (84.0) 33 (3.3) Yes 189 (16.0) 13 (6.5) Visited by fieldworker in last 12 months 0.684 No 1130 (95.6) 43 (3.8) Yes 52 (4.4) 3 (4.9) Geographical zones 0.012 Western 121 (10.3) 4 (3.4) Northern 142 (12.0) 11 (7.5) Central 156 (13.2) 6 (3.5) Southern 190 (16.1) 15 (8.1) Eastern 178 (15.0) 3 (1.5) Zanzibar 395 (33.4) 7 (1.9 Prevalence of alcohol consumption during pregnancy The overall prevalence of alcohol consumption during pregnancy among pregnant women in Tanzania was 3.9% (95% CI: 2.75-5.39). Factors associated with alcohol consumption during pregnancy In crude analysis, women aged 25-34 and ≥35 were more likely to consume alcohol during pregnancy (cOR=4.34, 95%CI: 1.31-14.32) and (cOR=13.85, 95%CI: 3.85-49.86) respectively, compared to those aged 15-24. Women who were separated or widowed had increased odds of consuming alcohol during pregnancy compared to married women (cOR=5.23, 95%CI: 1.61-16.12). We also found that women who were working (cOR=2.96, 95%CI: 1.16-7.56) were more likely to consume alcohol compared to their counterparts. (Table 2). In adjusted analysis, after controlling for age, marital status, working status, wealth index, parity and geographical zones. Women aged 25-34 (aOR=5.17, 95%CI: 1.62-16.51) and more than 35 years of age (aOR=20.89, 95%CI: 6.55-66.62) were more likely to consume alcohol compared to those aged 15 to 24. Compared to married women, women who were never married had increased odds of consuming alcohol (aOR=7.89, 95%CI: 2.20-28.25). On the other hand, women in Zanzibar were less likely to consume alcohol during pregnancy compared to women in the western zone (aOR=0.20, 95%CI: 0.04-0.88). (Table 2) Table 2: Factors associated with alcohol consumption during pregnancy Characteristics Crude p-value Adjusted p-value OR (95%CI) OR (95%CI) Age group (years) 15-24 Ref Ref 25-34 4.34 (1.31-14.32) 0.016 5.17 (1.62-16.51) 0.006 35+ 13.85 (3.85-49.86) <0.001 20.89 (6.55-66.62) <0.001 Marital status Single 2.19 (0.65-7.32) 0.203 7.89 (2.20-28.25) 0.002 Married Ref Ref Cohabiting 4.01 (1.75-9.10) 0.001 7.70 (3.09-19.18) <0.001 Separated/Widowed 5.23 (1.61-16.12) 0.006 3.80 (1.07-13.54) 0.039 Education level No formal education 1.66 (0.52-5.33) 0.393 Primary 1.68 (0.62-4.55) 0.302 Secondary/Higher Ref - Husband’s education No formal education 2.37 (0.46-12.25) 0.301 Primary 2.18 (0.75-6.29) 0.149 Secondary Ref - Currently working No Ref - Yes 2.96 (1.16-7.56) 0.023 1.82 (0.61-5.42) 0.283 Wealth index Poorest Ref - Poorer 0.95 (0.37-2.40) 0.907 1.09 (0.37-3.24) 0.865 Middle 0.65 (0.24-1.82) 0.420 0.66 (0.20-2.18 0.498 Richer 0.87 (0.33-2.33) 0.787 1.24 (0.36-4.24 0.729 Richest 0.21 (0.04-1.02) 0.054 0.21 (0.04-1.13 0.069 Exposure to media No Ref - Yes 1.22 (0.53-2.82) 0.645 Residence Urban Ref - Rural 2.34 (0.96-5.71) 0.061 Wanted current pregnancy Yes Ref - No 1.28 (0.38-5.82) 0.747 Parity ≤2 Ref Ref ≥3 3.38 (1.45-7.81) 0.005 1.41 (0.59-3.37) 0.443 Ever terminated pregnancy No Ref - Yes 2.02 (0.98-4.12) 0.053 Visited by fieldworker in last 12 months No Ref - Yes 1.31 (0.35-4.87) 0.685 Geographical zones Western Ref Northern 2.23 (0.56-8.98) 0.257 0.97 (0.22-4.27) 0.968 Central 0.99 (0.22-4.54) 0.998 0.39 (0.08-2.14) 0.279 Southern 2.44 (0.72-8.27) 0.152 1.01 (0,27-3.89) 0.981 Eastern 0.41 (0.07-2.52) 0.335 0.18 (0.02-1.72) 0.145 Zanzibar 0.52 (0.13-2.15) 0.369 0.20 (0.04-0.88) 0.034 Discussion This study aimed to determine the prevalence of alcohol use during pregnancy and the associated factors using the most recent 2022 TDHS-MIS data analysis. Our analysis revealed that the prevalence of alcohol consumption during pregnancy is a public health concern, evidenced by a reported overall prevalence of 3.9% (95% CI: 2.75–5.39) among pregnant women. The alcohol consumption during pregnancy was associated with age, single and marital status and geographical locations. The prevalence of alcohol consumption during pregnancy reflects a broader trend observed in Sub-Saharan Africa, where rates can vary significantly due to cultural practices and social norms surrounding alcohol use. Studies indicate that while some regions report lower prevalence, such as the noted 3.9%, urban areas demonstrate much higher rates. For instance, a 2021 study in Tanzania found that up to 42.2% of pregnant women consume alcohol at least once a week [ 15 ]. In Northern Tanzania, a 2015 study reported a maternal alcohol consumption prevalence of 21.5% [ 17 ], which has shown a decreasing trend over the years; a subsequent study in Central Tanzania in 2018 reported a prevalence of 15.1% [ 16 ]. This declining trend contrasts with previous studies in Tanzania and other Sub-Saharan African contexts, where higher rates were observed [ 13 ]. The variation in prevalence can be attributed to differences in study design and coverage. Additionally, the lack of targeted public health initiatives and educational programs addressing the risks of alcohol consumption during pregnancy poses significant challenges in mitigating this issue [ 19 ]. ​Therefore, further research and community-wide educational interventions are urgently needed to raise awareness and reduce the associated health risks for mothers and children in Tanzania and other regions. In Tanzania, increasing age among pregnant women exhibit a significantly higher likelihood of consuming alcohol compared to younger adolescent girls, indicating a substantial age-related risk factor for alcohol use during pregnancy [ 17 ]. This trend reflects broader patterns observed across Sub-Saharan Africa, where older women are often more socially accepted and encouraged to participate in alcohol consumption, sometimes due to cultural norms and lifestyle choices [ 15 , 19 ]. Furthermore, studies indicate that older women may perceive alcohol use as socially acceptable or even beneficial in certain cultural contexts, complicating efforts to reduce consumption rates among this demographic [ 13 ]. The implications of this finding are significant, as alcohol use during pregnancy is associated with serious health risks for both the mother and the fetus, including adverse birth outcomes and developmental disorders. Addressing alcohol consumption among this age group in Tanzania and other similar contexts is essential, necessitating tailored public health interventions that consider cultural perceptions and existing social norms surrounding alcohol use. This study found that women who were never married were more likely to consume alcohol compared to their married counterparts, which shows a heightened tendency toward alcohol use in this demographic. This finding was also supported by the study conducted in Ethiopia [ 12 ]. This phenomenon is reflective of broader sociocultural trends observed across Sub-Saharan Africa, where marital status often correlates with social expectations and norms regarding alcohol consumption [ 11 , 13 ]. Unmarried women may experience different social pressures or greater freedom in their choices, leading to higher rates of alcohol consumption, as they might be less accountable to family or community expectations that often accompany marriage [ 20 ]. Furthermore, studies suggest that unmarried women are more susceptible to environments where alcohol is readily available and socially accepted, potentially contributing to patterns of risky drinking behaviors in urban areas [ 21 ]. Addressing this disparity is crucial for public health initiatives aimed at reducing alcohol-related risks among vulnerable populations, emphasizing the need for targeted interventions that consider the unique challenges faced by never-married women in Tanzania and the surrounding region. Significant disparities in alcohol consumption during pregnancy were noted between different regions, notably highlighting low consumption by women in Zanzibar compared to those in the western zone. This difference may be attributed to these regions' varying cultural practices, societal norms, and economic conditions [ 22 ]. Zanzibar, with its predominantly Islamic population, often experiences stricter social norms surrounding alcohol consumption, which may contribute to the lower prevalence of drinking among pregnant women. In contrast, the western zone of Tanzania, which may have more diverse cultural influences and higher accessibility to alcohol, shows higher rates of alcohol use among pregnant women [ 19 , 23 ]. Such regional disparities in alcohol consumption during pregnancy are emblematic of broader trends observed throughout Sub-Saharan Africa, where cultural, educational, and socioeconomic factors play crucial roles in influencing women's health behaviors and attitudes towards alcohol during pregnancy. Addressing these disparities is vital for public health interventions aimed at reducing alcohol-related risks and improving maternal and child health outcomes across Tanzania. This study on alcohol consumption during pregnancy in Tanzania presents several strengths, including the use of the most recent 2022 TDHS-MIS data, which offers a reliable estimate of the overall prevalence and informs public health policies. This study effectively identifies demographic factors such as age and marital status associated with alcohol consumption and highlights regional disparities, particularly the lower prevalence in Zanzibar, thus contextualizing cultural influences on health behaviors. However, the study is limited by its reliance on self-reported data, which may introduce biases, and the cross-sectional design that hampers causal inferences. Additionally, the absence of detailed insights into underlying reasons for alcohol consumption limits the ability to design targeted interventions. Furthermore, not all potential confounding variables, such as socioeconomic status or access to healthcare, are accounted for, which could influence the study’s outcomes. Conclusion In conclusion, the prevalence of alcohol consumption during pregnancy in Tanzania presents a significant public health challenge, evidenced by the reported overall prevalence of 3.9% among pregnant women. This study highlights critical demographic factors influencing alcohol use, including age, marital status, and regional disparities, notably lower consumption rates observed in Zanzibar compared to the western zone. The findings underscore the need for targeted public health initiatives that educate and empower vulnerable populations, particularly unmarried women and older expectant mothers, to mitigate the associated health risks for both mothers and their children. It is essential that such interventions take into account the diverse cultural norms and socio-economic conditions present across different regions of Tanzania. Future research must also focus on improving community awareness and access to resources that can effectively reduce alcohol consumption during pregnancy, ultimately contributing to better maternal and child health outcomes in the country and throughout Sub-Saharan Africa. Abbreviations APR Adjusted Odds Ratio CI Confidence Interval CPR Crude Odds Ratio DHS Demographic Health Survey EA Enumeration area EA Enumeration Area IQR Interquartile Range PSU Primary Sampling Unit SSA Sub-Saharan Africa SD Standard deviation TDHS Tanzania Demographic Health Survey WHO World Health Organization Declarations Acknowledgements We thank the DHS program for making the data available for this study. Authors’ Contribution MJM performed formal analysis. VG, EE, MJM, MB, IPK and AN conceptualized the idea, interpreted the results and drafted the manuscript. VG, EE, MJM, MB, IPK and AN supported in results interpretation and reviewed all the versions of the manuscript. All authors read and approved the final manuscript. Funding Not Applicable. Availability of data and materials The dataset used for this study is openly available and can be accessed via dhsprogram.com Ethics approval and consent to participate The Ethical Review Committee of Tanzania Health Services and the Institutional Review Board approved the protocol for the 2022 Tanzania Malaria Indicator Survey. Prior to conducting interviews, participants provided informed consent. Additionally, all methods employed were in accordance with the guidelines and procedures. Consent for publication Not applicable. Competing interests None declared. References Mitchell AM, Porter RR, Pierce-Bulger M, McKnight-Eily LR. Addressing Alcohol Use in Pregnancy. Am J Nurs. 2020;120:22–4. Broccia M, Hansen BM, Winckler JM, Larsen T, Strandberg-Larsen K, Torp-Pedersen C, et al. Heavy prenatal alcohol exposure and obstetric and birth outcomes: a Danish nationwide cohort study from 1996 to 2018. 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Cite Share Download PDF Status: Published Journal Publication published 27 Mar, 2025 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 09 Dec, 2024 Reviews received at journal 08 Dec, 2024 Reviews received at journal 04 Dec, 2024 Reviewers agreed at journal 28 Nov, 2024 Reviews received at journal 26 Nov, 2024 Reviewers agreed at journal 20 Nov, 2024 Reviewers agreed at journal 19 Nov, 2024 Reviewers agreed at journal 19 Nov, 2024 Reviewers agreed at journal 18 Nov, 2024 Reviewers agreed at journal 18 Nov, 2024 Reviewers agreed at journal 17 Nov, 2024 Reviewers invited by journal 14 Nov, 2024 Editor invited by journal 06 Nov, 2024 Editor assigned by journal 31 Oct, 2024 Submission checks completed at journal 31 Oct, 2024 First submitted to journal 31 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5368966","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375926196,"identity":"eb7576e2-ad96-4e9b-9231-a582cd159b97","order_by":0,"name":"Victoria Godfrey","email":"data:image/png;base64,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","orcid":"","institution":"Dodoma Regional Referral Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Godfrey","suffix":""},{"id":375926197,"identity":"32d0e696-ad89-45f3-8186-4cbaa9e9fc1f","order_by":1,"name":"Elihuruma Eliufoo","email":"","orcid":"","institution":"University of Dodoma","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Elihuruma","middleName":"","lastName":"Eliufoo","suffix":""},{"id":375926198,"identity":"a09f9f38-a7e5-417c-ba1b-cdbdeb7cdcef","order_by":2,"name":"Immaculata P Kessy","email":"","orcid":"","institution":"TILAM International","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Immaculata","middleName":"P","lastName":"Kessy","suffix":""},{"id":375926199,"identity":"2042b49f-4dcc-4a97-bc8a-b7c079568e03","order_by":3,"name":"Mussa Bago","email":"","orcid":"","institution":"University of Dodoma","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mussa","middleName":"","lastName":"Bago","suffix":""},{"id":375926200,"identity":"c3002b90-a5df-482e-b2a7-83667ebf72f4","order_by":4,"name":"Mtoro J. Mtoro","email":"","orcid":"","institution":"TILAM International","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mtoro","middleName":"J.","lastName":"Mtoro","suffix":""},{"id":375926201,"identity":"5f3e570c-6188-4237-9638-8f693355bc73","order_by":5,"name":"Azan Nyundo","email":"","orcid":"","institution":"The University of Dodoma","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Azan","middleName":"","lastName":"Nyundo","suffix":""}],"badges":[],"createdAt":"2024-10-31 19:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5368966/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5368966/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-025-07149-3","type":"published","date":"2025-03-27T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79604999,"identity":"87dce56a-709b-4397-a8e3-280c9231dcd8","added_by":"auto","created_at":"2025-03-31 16:10:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1167353,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5368966/v1/64b211b3-84c2-44f1-943a-d669b6af8dab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal alcohol consumption during pregnancy and associated factors among pregnant women in Tanzania: Evidence from the 2022 Tanzania Demographic and Health Survey","fulltext":[{"header":"Background","content":"\u003cp\u003eAlcohol consumption during pregnancy poses significant risks to both maternal and fetal health, leading to a series of adverse outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Research has shown that alcohol use during pregnancy is associated with an increased risk of miscarriage and stillbirth, with specific studies indicating that heavy drinking can impair fetal growth and lead to low birth weight [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Moreover, no safe amount of alcohol has been established for pregnant women, and any level of consumption can cause lifelong effects on the child, including cognitive and behavioural impairments characteristic of Fetal Alcohol Spectrum Disorders (FASD) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Alcohol-related neurodevelopmental disorders can affect educational and social outcomes throughout a child's life [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Total abstinence from alcohol during pregnancy has been documented as the most effective strategy to ensure the health and well-being of both mother and child [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Still, there are reported use of alcohol during pregnancy which poses a need for continuously exploring this issue.\u003c/p\u003e \u003cp\u003eGlobally, approximately 10% of women consume alcohol while pregnant, with significant regional variations in prevalence rates [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In developed countries, consumption is notably higher [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], reporting rates of 25\u0026ndash;46% among pregnant women, highlighting a concerning trend [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This disparity is underscored by differing cultural norms and alcohol consumption patterns, suggesting that underlying social attitudes toward drinking may influence pregnant women's behaviours regarding alcohol [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, nearly 14% of pregnant individuals in the United States reported current drinking, with about 5% engaging in binge drinking [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These figures illustrate the scale of the challenge faced globally regarding alcohol consumption during pregnancy and emphasize the need for effective public health interventions to address this issue.\u003c/p\u003e \u003cp\u003eIn Sub-Saharan Africa, the situation is similarly concerning, with studies indicating varying prevalence rates of alcohol consumption among pregnant women, ranging from approximately 2.5\u0026ndash;59.28% across different countries [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Specific studies have reported that in countries like Ghana, the prevalence of alcohol consumption during pregnancy can reach as high as 48%, while in regions of Nigeria, figures have been reported as high as 59.3% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In contrast, other nations such as Burkina Faso have demonstrated lower rates, with a study revealing a self-reported alcohol use of 18.5% among pregnant women [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The significant variations in prevalence can largely be attributed to cultural influences, social norms surrounding alcohol use, and differences in research methodologies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This inconsistency underscores the urgent need for targeted public health interventions to address alcohol consumption during pregnancy within the region, considering its implications for maternal and child health.\u003c/p\u003e \u003cp\u003eIn Tanzania, the prevalence of alcohol use among pregnant women has been reported in some areas at alarming rates, with a recent study indicating that up to 42.2% consume alcohol at least once a week [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Previous small-scale studies have provided crucial data, demonstrating that factors such as maternal age, education level, religion, and access to antenatal care significantly influence alcohol consumption patterns among pregnant women in Tanzania [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Despite the established risks and increasing prevalence of alcohol use during pregnancy [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], there remains a significant gap in public health strategies aimed at addressing this critical issue within Tanzania. This highlights a pressing public health challenge that necessitates epidemiological surveys and targeted interventions to enhance awareness regarding the detrimental effects of alcohol consumption during pregnancy. This study aimed to provide an overview of the prevalence of alcohol use during pregnancy among pregnant women in Tanzania and the associated factors identified through the most recent 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS-MIS) data analysis. The findings of this study will contribute to the existing body of literature and inform policymakers and healthcare providers of the urgent need for interventions designed to reduce alcohol consumption during pregnancy, ultimately improving maternal and child health outcomes in the region.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData source and design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was an analytical cross-sectional survey that utilized secondary data from the 2022 TDHS-MIS, which conducts nationally representative population-based household surveys typically every five years. The data were extracted in the file code TZGR82FL\u0026nbsp;[18]. The survey was executed by the Tanzania National Bureau of Statistics in collaboration with the Ministries of Tanzania Mainland and Zanzibar.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePopulation and sampling\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for this study was obtained from the latest DHS conducted between 24 February to 21 July 2022 across all regions in Tanzania. The target population for the 2022 TDHS-MIS included women of reproductive age (15\u0026ndash;49 years) across the 31 administrative regions in Tanzania. At the country level, a sampling frame is usually obtained. To minimize sampling errors, the country was stratified by geographic region and by urban/rural areas within each region, followed by a two-stage sampling to select a household to be surveyed. The first sampling was to select a primary sampling unit (PSU) and then select a household. PSUs are survey clusters that are usually based on census enumeration areas (EAs). A probability proportion to size was employed in each stratum to select the PSU. For each selected PSU, a complete household listing was done. This was then followed by selecting a fixed number of households to be surveyed using equal probability systematic sampling. All women who had spent the night before the survey in the selected households were eligible for the survey. A total of 15,254 women of reproductive age were interviewed. This study analysed data from the women who reported being pregnant during the survey of 1,182 women of reproductive age (weighted).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcome variable for this study was alcohol consumption responses to the question, \u0026ldquo;During the past 30 days, how many days did you have a drink that contains alcohol?\u0026rdquo; Current alcohol consumption was defined as those pregnant women who drank daily or had drunk in the past 30 days that contained alcohol based coded as \u0026lsquo;1\u0026rsquo; and otherwise \u0026lsquo;0\u0026rsquo;.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe independent variables were included based on the available data and literature [12,13,17]; age in years, education level (no formal education, primary, secondary or higher), husband\u0026rsquo;s education level (no formal education, primary, secondary or higher), place of residence (urban or rural), marital status (never married, married, cohabiting or separated/divorced), exposure to media (listening to radio or reading newspaper or watching television less than once a week or at least once a week and otherwise), wealth index (poorest, poorer, middle, richer or richest), wanted the current pregnancy (yes or no), working status (yes or no), parity (\u0026le;2 or \u0026ge;3), ever tested for HIV (yes or no), terminated a pregnancy (yes or no), visited by fieldworker in the past 12 months (yes or no), screened for cervical cancer (yes or no) and geographical zones (western, northern, central, southern, eastern or Zanzibar). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was coded and analysed using STATA version 18.5 (STATA Corp, College Station, TX). Descriptive statistics were presented using means, standard deviation (SD) and medians, interquartile range (IQR) for continuous variables, and frequency and proportion for categorical variables. The Pearson chi-square test was used to compare the differences in the proportion of alcohol use during pregnancy across participants\u0026rsquo; characteristics.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll explanatory variables in the model were evaluated for multicollinearity.\u003c/p\u003e\n\u003cp\u003eWe applied a sample weight (v005/1,000,000) and the \u0026lsquo;\u003cem\u003esvyset\u003c/em\u003e\u0026rsquo; function in Stata was used to correct for over or under-sampling and the complex design of the DHS. Finally, a weighted binary logistic regression model was fitted to determine the factors associated with alcohol consumption during pregnancy. Univariate analyses were performed by fitting each independent variable against the dependent variable. Independent variables with p-values of \u0026lt;\u0026thinsp;0.05 in the univariate analyses and those considered in the literature as a potential confounder were included in the development of multivariable regression model through a backward selection at p\u0026lt;0.2.\u0026nbsp;The odds ratio (OR) and associated 95% confidence intervals (CI) were presented to estimate the magnitude and strength of the association. A statistically significant was considered for a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe use of this data was approved by MEASURE Tanzania Demographic and Health Surveys after we requested the data analysis idea. We downloaded the dataset from the website of the DHS Program after being granted permission.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eCharacteristics of study participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings show 39.1 were adolescent girls and young women, and more than half (60.4%) were married. Regarding education, 57.5% had completed primary education and among those who had a partner, more than half (58.4%) of their partner had completed primary education. We also found that more than half were currently working (61.2%), and more than two-thirds were exposed to media (67.5%). Just 16.0% had ever terminated pregnancy, and only 4.4% had been visited by fieldworkers in the past 12 months. (Table 1)\u003c/p\u003e\n\u003cp\u003eThe distribution of alcohol consumption was significantly different with age group, marital status, working status, parity, termination of pregnancy and geographical zones (p\u0026lt;0.05), as highlighted in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1: Demographic characteristics and distribution of alcohol consumption during pregnancy (N=1,182)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsumed alcohol n (%), n=46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e462 (39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e512 (43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e19 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e35+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e208 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e23 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cem\u003eMean (\u0026plusmn;SD)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u003cem\u003e27.3 (6.9)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e94 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e4 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e714 (60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e14 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eCohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e302 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e22 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eSeparated/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e71 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e6 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e226 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e10 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e679 (57.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e29 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e277 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e7 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHusband\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e116 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e5 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e594 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e24 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e307 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently working\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e458 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e8 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e724 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e38 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e265 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e14 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e234 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e12 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e206 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e7 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e229 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e10 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e247 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e3 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure to media\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e385 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e13 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e797 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e33 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e329 (27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e7 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e853 (72.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e39 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWanted current pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eWanted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e1128 (95.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e43 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNot wanted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e54 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e3 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u0026le;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e699 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e14 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e483 (40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e32 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver terminated pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.049\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e992 (84.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e33 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e189 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e13 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisited by fieldworker in last 12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e1130 (95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e43 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e52 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e3 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographical zones\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eWestern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e121 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e4 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eNorthern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e142 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e11 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eCentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e156 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e6 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eSouthern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e190 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e15 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eEastern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e178 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e3 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.8803%;\"\u003e\n \u003cp\u003eZanzibar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0684%;\"\u003e\n \u003cp\u003e395 (33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0598%;\"\u003e\n \u003cp\u003e7 (1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9915%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of alcohol consumption during pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall prevalence of alcohol consumption during pregnancy among pregnant women in Tanzania was 3.9% (95% CI: 2.75-5.39).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with alcohol consumption during pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn crude analysis,\u0026nbsp;\u003c/strong\u003ewomen aged 25-34 and \u0026ge;35 were more likely to consume alcohol during pregnancy (cOR=4.34, 95%CI: 1.31-14.32) and (cOR=13.85, 95%CI: 3.85-49.86) respectively, compared to those aged 15-24. Women who were separated or widowed had increased odds of consuming alcohol during pregnancy compared to married women (cOR=5.23, 95%CI: 1.61-16.12). We also found that women who were working (cOR=2.96, 95%CI: 1.16-7.56) were more likely to consume alcohol compared to their counterparts. (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn adjusted analysis,\u0026nbsp;\u003c/strong\u003eafter controlling for age, marital status, working status, wealth index, parity and geographical zones. Women aged 25-34 (aOR=5.17, 95%CI: 1.62-16.51) and more than 35 years of age (aOR=20.89, 95%CI: 6.55-66.62) were more likely to consume alcohol compared to those aged 15 to 24. Compared to married women, women who were never married had increased odds of consuming alcohol (aOR=7.89, 95%CI: 2.20-28.25). On the other hand, women in Zanzibar were less likely to consume alcohol during pregnancy compared to women in the western zone (aOR=0.20, 95%CI: 0.04-0.88). (Table 2)\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2: Factors associated with alcohol consumption during pregnancy\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e4.34 (1.31-14.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e5.17 (1.62-16.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e35+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e13.85 (3.85-49.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e20.89 (6.55-66.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.19 (0.65-7.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e7.89 (2.20-28.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eCohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e4.01 (1.75-9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e7.70 (3.09-19.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eSeparated/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e5.23 (1.61-16.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e3.80 (1.07-13.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e1.66 (0.52-5.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e1.68 (0.62-4.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eSecondary/Higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHusband\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.37 (0.46-12.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.18 (0.75-6.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently working\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.96 (1.16-7.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e1.82 (0.61-5.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.95 (0.37-2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e1.09 (0.37-3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.65 (0.24-1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.66 (0.20-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.498\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.87 (0.33-2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e1.24 (0.36-4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.21 (0.04-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.21 (0.04-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure to media\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e1.22 (0.53-2.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.34 (0.96-5.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWanted current pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e1.28 (0.38-5.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u0026le;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e3.38 (1.45-7.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e1.41 (0.59-3.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver terminated pregnancy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.02 (0.98-4.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisited by fieldworker in last 12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e1.31 (0.35-4.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographical zones\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eWestern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eNorthern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.23 (0.56-8.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.97 (0.22-4.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eCentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.99 (0.22-4.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.39 (0.08-2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eSouthern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e2.44 (0.72-8.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e1.01 (0,27-3.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eEastern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.41 (0.07-2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.18 (0.02-1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4476%;\"\u003e\n \u003cp\u003eZanzibar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6273%;\"\u003e\n \u003cp\u003e0.52 (0.13-2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9617%;\"\u003e\n \u003cp\u003e0.20 (0.04-0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9817%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to determine the prevalence of alcohol use during pregnancy and the associated factors using the most recent 2022 TDHS-MIS data analysis. Our analysis revealed that the prevalence of alcohol consumption during pregnancy is a public health concern, evidenced by a reported overall prevalence of 3.9% (95% CI: 2.75\u0026ndash;5.39) among pregnant women. The alcohol consumption during pregnancy was associated with age, single and marital status and geographical locations.\u003c/p\u003e \u003cp\u003eThe prevalence of alcohol consumption during pregnancy reflects a broader trend observed in Sub-Saharan Africa, where rates can vary significantly due to cultural practices and social norms surrounding alcohol use. Studies indicate that while some regions report lower prevalence, such as the noted 3.9%, urban areas demonstrate much higher rates. For instance, a 2021 study in Tanzania found that up to 42.2% of pregnant women consume alcohol at least once a week [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In Northern Tanzania, a 2015 study reported a maternal alcohol consumption prevalence of 21.5% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which has shown a decreasing trend over the years; a subsequent study in Central Tanzania in 2018 reported a prevalence of 15.1% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This declining trend contrasts with previous studies in Tanzania and other Sub-Saharan African contexts, where higher rates were observed [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The variation in prevalence can be attributed to differences in study design and coverage. Additionally, the lack of targeted public health initiatives and educational programs addressing the risks of alcohol consumption during pregnancy poses significant challenges in mitigating this issue [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. ​Therefore, further research and community-wide educational interventions are urgently needed to raise awareness and reduce the associated health risks for mothers and children in Tanzania and other regions.\u003c/p\u003e \u003cp\u003eIn Tanzania, increasing age among pregnant women exhibit a significantly higher likelihood of consuming alcohol compared to younger adolescent girls, indicating a substantial age-related risk factor for alcohol use during pregnancy [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This trend reflects broader patterns observed across Sub-Saharan Africa, where older women are often more socially accepted and encouraged to participate in alcohol consumption, sometimes due to cultural norms and lifestyle choices [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Furthermore, studies indicate that older women may perceive alcohol use as socially acceptable or even beneficial in certain cultural contexts, complicating efforts to reduce consumption rates among this demographic [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The implications of this finding are significant, as alcohol use during pregnancy is associated with serious health risks for both the mother and the fetus, including adverse birth outcomes and developmental disorders. Addressing alcohol consumption among this age group in Tanzania and other similar contexts is essential, necessitating tailored public health interventions that consider cultural perceptions and existing social norms surrounding alcohol use.\u003c/p\u003e \u003cp\u003eThis study found that women who were never married were more likely to consume alcohol compared to their married counterparts, which shows a heightened tendency toward alcohol use in this demographic. This finding was also supported by the study conducted in Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This phenomenon is reflective of broader sociocultural trends observed across Sub-Saharan Africa, where marital status often correlates with social expectations and norms regarding alcohol consumption [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Unmarried women may experience different social pressures or greater freedom in their choices, leading to higher rates of alcohol consumption, as they might be less accountable to family or community expectations that often accompany marriage [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, studies suggest that unmarried women are more susceptible to environments where alcohol is readily available and socially accepted, potentially contributing to patterns of risky drinking behaviors in urban areas [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Addressing this disparity is crucial for public health initiatives aimed at reducing alcohol-related risks among vulnerable populations, emphasizing the need for targeted interventions that consider the unique challenges faced by never-married women in Tanzania and the surrounding region.\u003c/p\u003e \u003cp\u003eSignificant disparities in alcohol consumption during pregnancy were noted between different regions, notably highlighting low consumption by women in Zanzibar compared to those in the western zone. This difference may be attributed to these regions' varying cultural practices, societal norms, and economic conditions [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Zanzibar, with its predominantly Islamic population, often experiences stricter social norms surrounding alcohol consumption, which may contribute to the lower prevalence of drinking among pregnant women. In contrast, the western zone of Tanzania, which may have more diverse cultural influences and higher accessibility to alcohol, shows higher rates of alcohol use among pregnant women [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Such regional disparities in alcohol consumption during pregnancy are emblematic of broader trends observed throughout Sub-Saharan Africa, where cultural, educational, and socioeconomic factors play crucial roles in influencing women's health behaviors and attitudes towards alcohol during pregnancy. Addressing these disparities is vital for public health interventions aimed at reducing alcohol-related risks and improving maternal and child health outcomes across Tanzania.\u003c/p\u003e \u003cp\u003eThis study on alcohol consumption during pregnancy in Tanzania presents several strengths, including the use of the most recent 2022 TDHS-MIS data, which offers a reliable estimate of the overall prevalence and informs public health policies. This study effectively identifies demographic factors such as age and marital status associated with alcohol consumption and highlights regional disparities, particularly the lower prevalence in Zanzibar, thus contextualizing cultural influences on health behaviors. However, the study is limited by its reliance on self-reported data, which may introduce biases, and the cross-sectional design that hampers causal inferences. Additionally, the absence of detailed insights into underlying reasons for alcohol consumption limits the ability to design targeted interventions. Furthermore, not all potential confounding variables, such as socioeconomic status or access to healthcare, are accounted for, which could influence the study\u0026rsquo;s outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the prevalence of alcohol consumption during pregnancy in Tanzania presents a significant public health challenge, evidenced by the reported overall prevalence of 3.9% among pregnant women. This study highlights critical demographic factors influencing alcohol use, including age, marital status, and regional disparities, notably lower consumption rates observed in Zanzibar compared to the western zone. The findings underscore the need for targeted public health initiatives that educate and empower vulnerable populations, particularly unmarried women and older expectant mothers, to mitigate the associated health risks for both mothers and their children. It is essential that such interventions take into account the diverse cultural norms and socio-economic conditions present across different regions of Tanzania. Future research must also focus on improving community awareness and access to resources that can effectively reduce alcohol consumption during pregnancy, ultimately contributing to better maternal and child health outcomes in the country and throughout Sub-Saharan Africa.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAPR Adjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003eCI Confidence Interval\u003c/p\u003e\n\u003cp\u003eCPR Crude Odds Ratio\u003c/p\u003e\n\u003cp\u003eDHS Demographic Health Survey\u003c/p\u003e\n\u003cp\u003eEA Enumeration area\u003c/p\u003e\n\u003cp\u003eEA Enumeration Area\u003c/p\u003e\n\u003cp\u003eIQR Interquartile Range\u003c/p\u003e\n\u003cp\u003ePSU Primary Sampling Unit\u003c/p\u003e\n\u003cp\u003eSSA Sub-Saharan Africa\u003c/p\u003e\n\u003cp\u003eSD Standard deviation\u003c/p\u003e\n\u003cp\u003eTDHS Tanzania Demographic Health Survey\u003c/p\u003e\n\u003cp\u003eWHO World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the DHS program for making the data available for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMJM performed formal analysis. VG, EE, MJM, MB, IPK and AN conceptualized the idea, interpreted the results and drafted the manuscript. VG, EE, MJM, MB, IPK and AN supported in results interpretation and reviewed all the versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used for this study is openly available and can be accessed via dhsprogram.com\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ethical Review Committee of Tanzania Health Services and the Institutional Review Board approved the protocol for the 2022 Tanzania Malaria Indicator Survey. Prior to conducting interviews, participants provided informed consent. Additionally, all methods employed were in accordance with the guidelines and procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMitchell AM, Porter RR, Pierce-Bulger M, McKnight-Eily LR. Addressing Alcohol Use in Pregnancy. Am J Nurs. 2020;120:22\u0026ndash;4. \u003c/li\u003e\n\u003cli\u003eBroccia M, Hansen BM, Winckler JM, Larsen T, Strandberg-Larsen K, Torp-Pedersen C, et al. Heavy prenatal alcohol exposure and obstetric and birth outcomes: a Danish nationwide cohort study from 1996 to 2018. Lancet Public Health. 2023;8:e28\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003ePopova S, Dozet D, Shield K, Rehm J, Burd L. Alcohol\u0026rsquo;s Impact on the Fetus. Nutrients. 2021;13:3452. \u003c/li\u003e\n\u003cli\u003eMillians MN. Educational Needs and Care of Children with FASD. Curr Dev Disord Rep. 2015;2:210\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eUjhelyi Gomez K, Goodwin L, Chisholm A, Rose AK. Alcohol use during pregnancy and motherhood: Attitudes and experiences of pregnant women, mothers, and healthcare professionals. PLOS ONE. 2022;17:e0275609. \u003c/li\u003e\n\u003cli\u003eDoherty E, Wiggers J, Wolfenden L, Anderson AE, Crooks K, Tsang TW, et al. Antenatal care for alcohol consumption during pregnancy: pregnant women\u0026rsquo;s reported receipt of care and associated characteristics. BMC Pregnancy Childbirth. 2019;19:299. \u003c/li\u003e\n\u003cli\u003eM\u0026aring;rdby A-C, Lupattelli A, Hensing G, Nordeng H. Consumption of alcohol during pregnancy-A multinational European study. Women Birth J Aust Coll Midwives. 2017;30:e207\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eMeurk CS, Broom A, Adams J, Hall W, Lucke J. Factors influencing women\u0026rsquo;s decisions to drink alcohol during pregnancy: findings of a qualitative study with implications for health communication. BMC Pregnancy Childbirth. 2014;14:246. \u003c/li\u003e\n\u003cli\u003eDEJONG K, OLYAEI A, LO JO. Alcohol Use in Pregnancy. Clin Obstet Gynecol. 2019;62:142\u0026ndash;55. \u003c/li\u003e\n\u003cli\u003eAbetew MM, Alemu AA, Zeleke H, Ayenew AA, Aynalem FG, Kassa GM, et al. Alcohol consumption and its determinants among pregnant women in Gozamin district, Amhara, Ethiopia, 2020. SAGE Open Med. 2022;10:20503121221130903. \u003c/li\u003e\n\u003cli\u003eAddila AE, Bisetegn TA, Gete YK, Mengistu MY, Beyene GM. Alcohol consumption and its associated factors among pregnant women in Sub-Saharan Africa: a systematic review and meta-analysis\u0026rsquo; as given in the submission system. Subst Abuse Treat Prev Policy. 2020;15:29. \u003c/li\u003e\n\u003cli\u003eBete T, Asfaw H, Nigussie K, Alemu A, Eyeberu Gebrie A, Dechasa DB, et al. Alcohol consumption and associated factors among pregnant women attending antenatal care at governmental hospitals in Harari regional state, Eastern, Ethiopia. Subst Abuse Treat Prev Policy. 2023;18:61. \u003c/li\u003e\n\u003cli\u003eMulat B, Alemnew W, Shitu K. Alcohol use during pregnancy and associated factors among pregnant women in Sub-Saharan Africa: further analysis of the recent demographic and health survey data. BMC Pregnancy Childbirth. 2022;22:361. \u003c/li\u003e\n\u003cli\u003eSanou AS, Diallo AH, Holding P, Nankabirwa V, Engebretsen IMS, Ndeezi G, et al. Maternal alcohol consumption during pregnancy and child\u0026rsquo;s cognitive performance at 6\u0026ndash;8 years of age in rural Burkina Faso: an observational study. PeerJ. 2017;5:e3507. \u003c/li\u003e\n\u003cli\u003eWest K, Pauley A, Buono M, Mikindo M, Sawe Y, Kilasara J, et al. The Burden of Generational Harm due to Alcohol use in Tanzania: a mixed method study of pregnant women [Internet]. medRxiv; 2024 [cited 2024 Sep 29]. p. 2024.08.22.24312125. Available from: https://www.medrxiv.org/content/10.1101/2024.08.22.24312125v2\u003c/li\u003e\n\u003cli\u003eMpelo M, Kibusi SM, Moshi F, Nyundo A, Ntwenya JE, Mpondo BCT. Prevalence and Factors Influencing Alcohol Use in Pregnancy among Women Attending Antenatal Care in Dodoma Region, Tanzania: A Cross-Sectional Study. J Pregnancy. 2018;2018:8580318. \u003c/li\u003e\n\u003cli\u003eIsaksen AB, \u0026Oslash;stbye T, Mmbaga BT, Daltveit AK. Alcohol consumption among pregnant women in Northern Tanzania 2000\u0026ndash;2010: a registry-based study. BMC Pregnancy Childbirth. 2015;15:205. \u003c/li\u003e\n\u003cli\u003eMinistry of Health (MoH) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. Tanzania Demographicand Health Survey and Malaria Indicator Survey 2022 Key Indicators Report. Dodoma, Rockville: MoH, NBS, OCGS, and ICF; 2023. \u003c/li\u003e\n\u003cli\u003eWest K. Sociodemographic and Psychological Profiles of Pregnant Women Who Consume Alcohol in Moshi, Tanzania: A Latent Class Analysis. 2024 [cited 2024 Sep 30]; Available from: https://hdl.handle.net/10161/31005\u003c/li\u003e\n\u003cli\u003eDinescu D, Turkheimer E, Beam CR, Horn EE, Duncan G, Emery RE. Is Marriage a Buzzkill? A Twin Study of Marital Status and Alcohol Consumption. J Fam Psychol JFP J Div Fam Psychol Am Psychol Assoc Div 43. 2016;30:698\u0026ndash;707. \u003c/li\u003e\n\u003cli\u003eThe effects of marital status transitions on alcohol use trajectories. Longitud Life Course Stud [Internet]. 2012 [cited 2024 Sep 30]; Available from: http://www.llcsjournal.org/index.php/llcs/article/view/187\u003c/li\u003e\n\u003cli\u003eTanzania, including Zanzibar - Traveler view | Travelers\u0026rsquo; Health | CDC [Internet]. [cited 2024 Sep 30]. Available from: https://wwwnc.cdc.gov/travel/destinations/traveler/none/tanzania\u003c/li\u003e\n\u003cli\u003eStaton CA, Zhao D, Ginalis EE, Hirshon JM, Sakita F, Swahn MH, et al. Alcohol Availability, Cost, Age of First Drink and Association with At-Risk Alcohol Use in Moshi, Tanzania. Alcohol Clin Exp Res. 2020;44:2266\u0026ndash;74. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Alcohol Consumption, Pregnancy, Pregnant women, Tanzania","lastPublishedDoi":"10.21203/rs.3.rs-5368966/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5368966/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAlcohol consumption during pregnancy remains a significant public health concern, particularly in Tanzania. Alcohol use during pregnancy is associated with an increased risk of miscarriage, stillbirth, Fetal Alcohol Spectrum Disorders, and it can impair fetal growth and lead to low birth weight. This study aims to investigate the prevalence of alcohol use among pregnant women and identify associated factors utilizing data from the 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was an analytical cross-sectional survey design utilizing secondary data from the 2022 TDHS-MIS. The survey employed a multistage cluster sampling method to generate representative national and sub-national health and health-related indicators between February and July 2022. A total of 1,182 pregnant women were included in the analysis. Data analysis involved descriptive statistics and binary logistic regression using STATA version 18.5 to assess factors associated with maternal alcohol consumption. Adjusted odds ratios (aOR) with a 95% confidence interval (CI) were computed to estimate the strength of the association between independent variables and alcohol use.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age of the participants was 27.3 years (standard deviation: 6.9). The overall prevalence of alcohol consumption during pregnancy among pregnant women in Tanzania was 3.9% (95% CI: 2.75\u0026ndash;5.39). Factors associated with alcohol consumption were; women aged 25\u0026ndash;34 (aOR\u0026thinsp;=\u0026thinsp;5.17, 95%CI: 1.62\u0026ndash;16.51) and more than 35 years of age (aOR\u0026thinsp;=\u0026thinsp;20.89, 95%CI: 6.55\u0026ndash;66.62), women who were never married (aOR\u0026thinsp;=\u0026thinsp;7.89, 95%CI: 2.20-28.25), On the other hand, women living in the western zone (aOR\u0026thinsp;=\u0026thinsp;0.20, 95%CI: 0.04\u0026ndash;0.88).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study reveals a concerning prevalence of alcohol consumption during pregnancy in Tanzania.​ Key demographic factors influencing alcohol use include maternal age, marital status, and notable regional disparities, particularly lower rates in Zanzibar compared to the western zone. These findings highlight the necessity for targeted public health initiatives aimed at educating pregnant women.\u003c/p\u003e","manuscriptTitle":"Maternal alcohol consumption during pregnancy and associated factors among pregnant women in Tanzania: Evidence from the 2022 Tanzania Demographic and Health Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-12 06:06:24","doi":"10.21203/rs.3.rs-5368966/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-09T18:31:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-08T20:39:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-04T06:42:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200985083646161935250765473456622519651","date":"2024-11-28T08:06:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-26T06:06:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314185679854871750568055572055555891584","date":"2024-11-20T16:42:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228853255535616120399412313123915702421","date":"2024-11-20T01:18:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113115423664711839390821714677253583485","date":"2024-11-19T06:34:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252122501267360324822602280280194970961","date":"2024-11-19T04:20:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100308807996667379496796107860271383796","date":"2024-11-18T16:40:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206451302934465346566896268933371089359","date":"2024-11-17T19:45:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-14T15:52:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-06T13:39:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-01T00:41:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-01T00:40:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-10-31T19:38:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"590e62ed-dd38-4571-876e-afc0aabc8853","owner":[],"postedDate":"November 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-31T16:05:11+00:00","versionOfRecord":{"articleIdentity":"rs-5368966","link":"https://doi.org/10.1186/s12884-025-07149-3","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2025-03-27 15:57:34","publishedOnDateReadable":"March 27th, 2025"},"versionCreatedAt":"2024-11-12 06:06:24","video":"","vorDoi":"10.1186/s12884-025-07149-3","vorDoiUrl":"https://doi.org/10.1186/s12884-025-07149-3","workflowStages":[]},"version":"v1","identity":"rs-5368966","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5368966","identity":"rs-5368966","version":["v1"]},"buildId":"cTy_lsJlmDsVRNrSptgXS","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}