Temporal Dynamics of HIV Testing as a Predictor of Facility Delivery among adolescent girls and young women (AGYW): Evidence from the Zimbabwe Demographic and Health Surveys (2005–2015)

Temporal Dynamics of HIV Testing as a Predictor of Facility Delivery among adolescent girls and young women (AGYW): Evidence from the Zimbabwe Demographic and Health Surveys (2005–2015) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Temporal Dynamics of HIV Testing as a Predictor of Facility Delivery among adolescent girls and young women (AGYW): Evidence from the Zimbabwe Demographic and Health Surveys (2005–2015) Hilary Takunda Takawira, Panashe Nyengera This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7802918/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Facility-based delivery is critical for reducing maternal mortality. In high-HIV-prevalence settings such as Zimbabwe, integrating HIV testing and counselling (HTC) with antenatal care is central to PMTCT. However, the effect of HTC on maternal healthcare utilization remains underexplored. This study examines HIV testing as a determinant of facility delivery in Zimbabwe from 2005–2015. Methods Our study employed a pooled cross-sectional analysis of data from the Zimbabwe Demographic and Health Surveys (ZDHS) for 2005, 2010 and 2015. The study included women aged 15–24 whose last birth occurred within three years of each survey. The primary outcome was facility-based delivery, and the key exposure was self-reported and never tested for HIV. We used multivariable logistic regression, stratified by survey year, to analyse temporal trends and tested for a significant interaction between HIV testing and survey year. Results Among 4,018 women, 78.2% delivered in a health facility, increasing from 72.7% in 2005 to 86.8% in 2015. Women who had been tested for HIV were more likely to deliver in a facility (2005: aOR = 2.65, 95% CI: 1.64–4.26; 2010: aOR = 3.33, 95% CI: 2.07–5.36; 2015: aOR = 9.71, 95% CI: 3.50–26.90). Higher education (secondary or above: 2005: aOR = 1.38, 95% CI: 0.88–2.19; 2010: aOR = 2.19, 95% CI: 1.39–3.45; 2015: aOR = 3.30, 95% CI: 1.83–5.96) and attending ≥ 4 antenatal care visits (2005: aOR = 2.09, 95% CI: 1.26–3.49; 2010: aOR = 1.57, 95% CI: 1.05–2.34; 2015: aOR = 2.09, 95% CI: 1.14–3.83) also increased the likelihood of facility delivery. Rural residence was associated with lower delivery in 2005 (aOR = 0.11, 95% CI: 0.04–0.31) but not by 2015 (aOR = 1.47, 95% CI: 0.37–5.83). Conclusion Facility delivery in Zimbabwe has improved, driven by HIV testing, education, and antenatal care. Persistent inequalities remain through residence and service engagement. HIV testing is a key entry point, highlighting the impact of the PMTCT program. Efforts should focus on expanding HIV testing, strengthening ANC, and promoting education and women’s empowerment. Facility delivery maternal health HIV testing and counselling antenatal care Figures Figure 1 Background Maternal mortality remains a significant public health issue in sub-Saharan Africa, with the adoption of facility-based delivery being a cornerstone strategy for its reduction [ 1 ]. Zimbabwe has a historically high maternal mortality ratio, and the determinants of this key behavior are multifaceted. Studies from Bangladesh, Ethiopia, and Gambia have shown that factors such as higher maternal education, greater household wealth, urban residence, and lower parity are strongly associated with increased facility deliveries [ 2 – 5 ]. The HIV epidemic in Zimbabwe adds a critical layer of complexity to maternal healthcare. Since the early 2000s, the integration of HIV testing and counselling (HTC) into antenatal care has been the primary entry point for the prevention of mother-to-child transmission (PMTCT) of HIV [ 6 ]. A woman’s knowledge of her HIV status during pregnancy is therefore vital not only for initiating life-saving antiretroviral therapy but also for influencing her subsequent engagement with the healthcare system [ 7 , 8 ]. Several studies have suggested that receiving an HIV test is a powerful motivator for completing the continuum of care, including facility delivery, as it is a key gateway to PMTCT services [ 7 , 9 ]. However, this relationship is not static. Maternal and HIV care has significantly transformed over the past decade. PMTCT programs have scaled up, “test and treat” policies have been adopted more, and the normalization of routine opt-out testing in antenatal clinics may have fundamentally altered the role of an HIV test. What was once a distinctive, motivating event may now be a standard, and perhaps less influential, component of antenatal care. While cross-sectional studies have provided some insights into this relationship [ 9 , 10 ], a critical gap remains in understanding how the importance of HIV testing as a determinant of facility delivery has evolved over time. This study aims to fill this gap by analysing nationally representative data from Zimbabwe spanning a decade of significant health system change. By tracing the temporal dynamics of this association while accounting for established sociodemographic and pregnancy-related factors, this research will determine whether the value of HIV testing as an incentive for facility delivery has been sustained, diminished, or transformed. The findings provide critical evidence to inform more effective and integrated maternal and child health policies in Zimbabwe and similar high-HIV burden settings. Methods Study design and data sources This study used a series of cross-sectional surveys, analysing secondary data from ZDHS conducted in 2005, 2010 and 2015. The DHS program employs a two-stage stratified cluster sampling design to collect nationally representative data on key health indicators. For this study, we combined individual recode (IR) files, which contain data from all women of reproductive age, with birth recode (BR) files, which contain detailed information on each live birth. Study population and sample The study population consisted of women aged 15--24 years who had given birth at least once. To focus on recent maternal health service utilization and ensure accurate recall, the sample was restricted to women whose last birth occurred within the 35 months preceding the survey year. The final sample used for the analysis was constructed by successfully merging the IR and BR files for each survey year, retaining only the most recent birth for each woman to ensure that each contributed a single observation. Data preparation and variable construction All data management and analyses were conducted in Stata/MP 18.0. The variables were harmonized across the three survey years of 2005, 2010 and 2016 to ensure consistency. The primary outcome was facility-based delivery, defined as binary variable comparing deliveries in health facilities versus those at home or elsewhere. The primary independent variable was a binary indicator of whether the woman had ever received an HIV test. Covariates known to influence maternal health service utilization were included ( Table 1 ), encompassing sociodemographic factors (survey year, age at birth, place of residence, educational attainment, wealth quintile, marital status, and parity) and a measure of women’s empowerment on the basis of decision-making autonomy. Table 1. Variables used in the analysis of maternal health service utilization in the Zimbabwe DHS (2005–2015) Variable Name Description Measurement/Categories Outcome variables Facility delivery Delivery in a health facility Binary: 0 = no, 1 = yes Exposure variable Ever tested for HIV Ever tested for HIV Binary: 0 = no, 1 = yes Demographic variables Age group Current age group (5-year) 15–19, 20–24 Mother age at birth Mother’s age at birth 15–19, 20–24 Residence Place of residence Urban, rural Education level Highest education level No education, primary, secondary, higher Wealth quintile Wealth index Poorest, poorer, middle, richer, richest Marital status Simplified marital status Married/cohabiting, never married, Widowed/divorced, separated Religion Religion Categorical Pregnancy-related variables Parity Number of children ever born Continuous Birth order Birth order of most recent child Continuous Anc 4 plus Four or more ANC visits Binary: 0 = no, 1 = yes Media exposure Media exposure Yes, No Healthcare decision Who decides on healthcare Respondent alone, Joint decision, Partner alone, Someone else, Other Several categorical variables were collapsed for statistical clarity ( Table 1 ), ensuring that there were sufficient sample sizes for stable estimates while preserving meaningful distinctions for understanding healthcare utilization patterns. Education was collapsed into two groups: less than secondary versus secondary or higher. Marital status was simplified into married/cohabiting, never married, widowed/divorced, and separated. Religion was grouped into Christian, Apostolic, Muslim, and no religion/traditional/other. Age was categorized into standard five-year intervals. These decisions balance parsimony, interpretability, and statistical robustness while preserving distinctions of substantive and policy relevance. Handling of missing data Missing data for all variables included in the analysis were handled via a complete-case approach. Observations with missing values for any of the key covariates (e.g., HIV testing status, facility delivery, sociodemographic variables) were excluded from the corresponding analyses. The proportion of missing data was minimal, and survey weights were retained in all analyses to account for the complex sampling design. Statistical analysis All analyses accounted for the complex, multistage sampling design of the DHS by applying sampling weights and adjusting for clustering at the level of the primary sampling unit and stratification. Descriptive statistics were computed to characterize the study sample and describe trends in all variables, including the outcome and key independent variables, across the three survey years. Univariable logistic regression models were used to assess the associations between each independent variable and facility-based delivery. Multivariate logistic regression was used to test for the specific hypothesis that the association between HIV testing and facility-based delivery, in Zimbabwe, evolved over time. To estimate the average association between HIV testing and facility-based delivery, a main effects model was fitted to the pooled data from all three surveys. To formally test for temporal change, a model was then specified that included an interaction term between the survey year and HIV testing status. A statistically significant interaction confirmed that the relationship between HIV testing and facility delivery was not constant across the study period. Once a significant interaction was found, the final step was to present the results through survey year-stratified models. This approach allowed for a clear interpretation of the evolving relationship, as it directly displays the magnitude, direction, and significance of the association between HIV testing and facility delivery at each time point, adjusted for all covariates. These stratified models included the full set of confounders, including residence, education, wealth, age, marital status, decision-making autonomy, and media exposure, to isolate the specific role of HIV testing within the context of each survey year. Sensitivity analysis We conducted several sensitivity analyses to assess the association between HIV testing and facility delivery in 2015. Firth penalized logistic regression was employed to address potential bias due to sparse data and quasicomplete separation, which can occur when the number of untested women is very small. To determine whether the effect size of HIV testing changed when a small number of covariates were controlled for, a reduced multivariable model comprising only HIV testing, wealth quintile, education, and residence status was fitted. A reduced multivariable model including only HIV testing, wealth quintile, education, and residence was fitted to examine whether the effect size of HIV testing changed when adjusting for a limited set of covariates. Unweighted logistic regression with cluster-robust standard errors was performed to confirm that survey weights did not substantially influence the results. These complementary analyses were conducted to ensure that the observed association was robust and not an artifact of modelling choices or sparse data. Ethics approval and consent to participate Zimbabwe Demographic and Health Survey (ZDHS) protocols were approved by the Medical Research Council of Zimbabwe (MRCZ). Permission to use the data for this analysis was sought from The Demographic and Health Surveys (DHS) Program. All DHS datasets are available to the public and fully anonymized prior to release, thus no further ethical approval was needed for this secondary analysis. All procedures were performed following appropriate guidelines and regulations. Results Sociodemographic characteristics and bivariate associations for the pooled dataset A total of 4,018 women were eligible for this analysis (Table 2). A total of 4,018, 78.2% (N= 3,140) reported delivering in a health facility. Across the entire study period, 3,076 women (76.6%) had ever been tested for HIV. Women were mostly living in rural areas (63.8%) and had achieved secondary or higher education (74.7%). Almost one in five were from the lowest wealth quintile (19.1%), which was similar to the highest (19.2%). The majority (72.8%) of women reported attending a minimum of four ANC visits. In the age group, over two-thirds were 20–24 years old (69.9%), and most were married or cohabiting (77.9%). Slightly more than half of the women had media exposure (52.4%). In terms of religion, the majority were Christians (52.1%) and Apostolics (39.7%). The majority of the women were primiparous (68.6%), and more than half delivered at ages 15–19 years (53.0%). In relation to household decision-making, the majority reported that decisions about medical care were made with a partner (24.6%) or by someone else (41.4%), although 19.3% said they made the decisions alone. Table 2. Sociodemographic characteristics of the women included in the study and bivariate associations with facility delivery, Zimbabwe DHS combined sample (2005–2015). Characteristic Total N (%) Facility Delivery N (%) Pearson χ² P value Total sample 4,018 3,140 (78.2%) – Ever tested for HIV <0.001 No 942 (23.4) 522 (55.4%) Yes 3,076 (76.6) 2,618 (85.1%) Place of residence <0.001 Urban 1,456 (36.2) 1,339 (92.0%) Rural 2,562(63.8) 1,801 (70.3%) Education <0.001 Less than secondary 1,018 (25.3) 614 (60.3%) Secondary or higher 3,000 (74.7) 2,526 (84.2%) Wealth quintile <0.001 Poorest 767 (19.1) 464 (60.5%) Poorer 707(17.6) 481 (68.0%) Middle 724(18.0) 560 (77.4%) Richer 1,049 (26.1) 908 (86.6%) Richest 771 (19.2) 727 (94.3%) ANC visits (≥4) <0.001 No 745 (27.2) 508 (68.2%) Yes 1,995 (72.8) 1,697 (85.1%) Age group 0.002 15–19 947 (30.1) 684 (72.2%) 20–24 2,202 (69.9) 1,705 (77.4%) Marital status 0.542 Married/Cohabiting 3,130 (77.9) 2,449 (78.2%) Never married 486 (12.1) 387 (79.6%) Widowed/Divorced 202 (5.0) 153 (75.7%) Separated 200 (5.0) 151 (75.5%) Media exposure <0.001 No 1,823 (47.6) 1,296 (71.1%) Yes 2,007 (52.4) 1,687 (84.1%) Religion <0.001 Christian 2,091 (52.1) 1,782 (85.2%) Apostolic 1,593 (39.7) 1,137 (71.4%) Muslim 20 (0.5) 18 (90.0%) No religion/Traditional 312 (7.8) 202 (64.7%) Parity <0.001 One 2,755 (68.6) 2,219 (80.5%) Two 1,165 (29.0) 853 (73.2%) Three 95 (2.4) 66 (69.5%) Four plus 3 (0.1) 2 (66.7%) Mother’s age at birth <0.001 15–19 1,842 (53.0) 1,357 (73.7%) 20–24 1,632 (47.0) 1,311 (80.3%) Healthcare decision autonomy 0.017 Respondent alone 273 (19.3) 230 (84.3%) Joint decision 348 (24.6) 256 (73.6%) Partner alone 207 (14.7) 162 (78.3%) Someone else 585 (41.4) 456 (77.9%) Facility delivery and HIV testing trends by sociodemographic factors, stratified by year Facility delivery increased steadily in Zimbabwe between 2005 and 2015. In 2005, 72.7% of women delivered in a health facility, increasing slightly to 74.4% in 2010 and reaching 86.8% in 2015, indicating substantial improvements in the utilization of facility-based delivery services over the decade ( Ta ble 3 ). Table 3. Sociodemographic characteristics of women and bivariate associations with facility delivery, stratified by survey year (Zimbabwe DHS 2005, 2010, and 2015) DHS 2005 Facility Delivery N= 1,194 DHS 2010 Facility Delivery N=1,440 DHS 2015 Facility Delivery N= 1,384 Characteristic Category Total N Yes N (%) χ² p value Total N Yes N (%) χ² p value Total N Yes N (%) χ² p value Total sample 868(72.7) 1,071(74.4) 1,201(86.8) Ever tested for HIV No 662 410 (61.9) <0.001 209 92 (44.0) <0.001 71 20 (28.2) <0.001 Yes 532 458 (86.1) 1,231 979 (79.5) 1,313 1,181 (89.9) Residence Urban 397 374 (94.2) <0.001 494 438 (88.7) <0.001 565 527 (93.3) <0.001 Rural 797 494 (62.0) 946 633 (66.9) 819 674 (82.3) Education Less than secondary 355 181 (51.0) <0.001 336 186 (55.4) <0.001 327 247 (75.5) <0.001 Secondary or higher 839 687 (81.9) 1,104 885 (80.2) 1,057 954 (90.3) Wealth quintile Poorest 250 122 (48.8) <0.001 278 163 (58.6) <0.001 239 179 (74.9) <0.001 Poorer 224 134 (59.8) 264 166 (62.9) 219 181 (82.7) Middle 227 167 (73.6) 269 196 (72.9) 228 197 (86.4) Richer 286 246 (86.0) 360 298 (82.8) 403 364 (90.3) Richest 207 199 (96.1) 269 248 (92.2) 295 280 (94.9) ANC ≥4 visits No 234 141 (60.3) <0.001 299 195 (65.2) <0.001 212 172 (81.1) <0.001 Yes 597 481 (80.6) 667 538 (80.7) 731 678 (92.8) Age group 15–19 277 167 (60.3) <0.001 325 218 (67.1) 0.067 345 299 (86.7) 0.656 20–24 697 517 (74.2) 773 561 (72.6) 732 627 (85.7) Marital status Married/Cohabiting 933 689 (73.9) 0.224 1,147 845 (73.7) 0.412 1,050 915 (87.1) 0.248 Never married 134 90 (67.2) 153 121 (79.1) 199 176 (88.4) Widowed/Divorced 76 56 (73.7) 67 48 (71.6) 59 49 (83.1) Separated 51 33 (64.7) 73 57 (78.1) 76 61 (80.3) Media exposure No 624 404 (64.7) <0.001 681 462 (67.8) <0.001 518 430 (83.0) 0.002 Yes 522 428 (82.0) 708 567 (80.1) 777 692 (89.1) Religion Christian 641 529 (82.5) <0.001 746 608 (81.5) <0.001 704 645 (91.6) <0.001 Apostolic sect 404 255 (63.1) 599 405 (67.6) 590 477 (80.9) Muslim 10 9 (90.0) 4 3 (75.0) 6 6 (100.0) No religion/Tradition 138 75 (54.4) 91 55 (60.4) 83 72 (86.7) Parity One 836 626 (74.9) 0.054 975 742 (76.1) 0.023 944 851 (90.2) <0.001 Two 319 218 (68.3) 439 307 (69.9) 407 328 (80.6) Three 37 23 (62.2) 26 22 (84.6) 32 21 (65.6) Four plus 2 1 (50.0) – – 1 1 (100.0) Mother’s age at birth 15–19 554 361 (65.2) <0.001 626 426 (68.1) <0.001 662 570 (86.1) 0.903 20–24 517 404 (78.1) 606 470 (77.6) 509 437 (85.9) Healthcare decision Respondent alone 39 28 (71.8) 0.011 127 104 (81.9) 0.034 107 98 (91.6) 0.027 Joint decision 75 44 (58.7) 106 77 (72.6) 167 135 (80.8) Partner alone 207 162 (78.3) – – – – Someone else 115 79 (68.7) 186 128 (68.8) 284 249 (87.7) HIV testing coverage also increased with time, with women who ever tested being consistently more likely to deliver in a facility (Fig 1). In 2005, among women who had ever been tested for HIV, facility-based delivery was 86.1% versus 61.9% among those who had not. By 2015, this gap had increased; among those tested, 89.9% delivered in a facility, and among those not tested, 28.2% (p<0.001), indicating increased levels of testing coverage as well as a strengthened association with facility delivery over time. Urban women continued to have significantly higher facility delivery coverage than rural women (94.2% vs 59.9% in 2005, 93.3% vs 82.3% in 2015). Women in the richest quintile near universal coverage for facility delivery across the survey years (95.7%,→96.5%) compared to the poorest (45.1% →75.%). Univariate analysis Several factors were significantly associated with increased odds of facility delivery in univariate analyses. Those living in rural areas also had significantly lower odds than those living in urban areas did (OR = 0.22, 95% CI: 0.17–0.29). Women who had ever received an HIV test (OR = 2.53, 95% CI: 2.14–3.00), had a higher education level (OR=3.41, 95% CI: 2.92–3.97), were exposed to mass media (OR = 2.03; 95% CI: [1·71–2·30]), and attended four or more ANC visits (OR = 2.61; [CI: [1·59–3]). A good nexus with wealth and maternal age at birth is a good relationship with wealth, i.e., it is a sign of lifestyle; this attitude indicates that a good number of children are not considered influential for women or their reproductive health. Some variables, such as marital status and decision-making autonomy, were not found to be significantly associated with facility delivery via these univariate analyses. Determinants of facility delivery: Multivariable analysis There was a statistically significant survey year and HIV testing interaction (adjusted Wald test, F (2, 758) = 3.12, p = 0.045), suggesting that the effect of HIV testing on facility delivery differed by survey year. Thus, the association between HIV testing and facility delivery became much stronger in 2015 than in previous years. We explored the factors associated with facility delivery across different years of the DHS surveys (2005, 2010 and 2015). Ever testing for HIV was strongly associated with increased odds of delivering in a health facility (Table 4: Appendix 2). Women who underwent an HIV test were far more likely to deliver in a facility than women who had never been tested. The difference increased over the study period: by 2005, tested women were approximately 2.7 times more likely to deliver in a health facility (aOR=2.7: 95% CI: 1.64–4.26) than were those who were not tested. In 2010, those tested were three times more likely to deliver in a health facility than those who were not tested (aOR= 3.33; 95% CI: 2.07–5.36), and those who had been tested in 2015 were almost tenfold more likely (aOR= 9.41; 95% CI: 3.50--26.90) to have delivered at a facility than those who were not tested. Other associated factors for giving birth in a facility were attending 4+ ANC visits and having a higher level of education. Women with at least four ANC visits were twice as likely to have a facility delivery in 2005 (OR = 2.09, 95% CI: 1.26–3.49) than those who had fewer than 4 ANC visits. In 2010, women who attended at least four ANC visits had 57% greater odds of delivering in a health facility than those with fewer than four ANC visits did (OR = 1.57, 95% CI: 1.05–2.34). The odds for delivery in a facility doubled in 2015 (OR = 2.09; 95% CI: 1.14–3.83) for those with at least four ANC visits compared with those with fewer than four ANC visits. Having secondary education or higher was also associated with giving birth in a health facility (Table 4: Appendix 2). In 2010, women who had achieved secondary or higher education were more than twice as likely to give birth in a health facility (OR = 2.19, 95% CI: 1.39–3.45) than those without secondary education. By the year 2015, women who had secondary education or higher were more than three times more likely to give birth in a health facility than were those who had primary or no education (OR = 3.30; 95% CI: 1.83–5.96). There was no clear effect on facility delivery by place of residence, wealth status or exposure to mass media between the survey years. In 2005, rural women were far less likely to have a facility for childbirth, but by 2010 and 2015, this difference was no longer apparent (Table 4: Appendix 2). Living in rural areas was strongly protective against facility delivery in 2005, with women in rural settings having approximately 89% lower odds of delivering in a facility than their urban counterparts (OR = 0.11, 95% CI: 0.04–0.31). However, this effect diminished and was not statistically significant in 2010 and 2015. Wealth and media exposure were not consistent in direction of association and attenuated over time (Table 4: Appendix 2). Marital status, religion, and the mother’s age at birth were nonsignificant determinants of facility delivery for all survey years. Because of the very low number of women untested in 2015, we carried out sensitivity analyses to determine whether our findings on the association between HIV testing and facility delivery were robust. Firth penalized logistic regression (accounting for sparse data and separation) yielded a strongly adjusted odds ratio of HIV testing (aOR = 12.0, 95% CI: 5.2–27.8). A more parsimonious model that included only HIV testing, wealth quintile, education and residence yielded a comparable slightly higher estimate (aOR = 19.7; 95% CI: 9.9–39.4). Notably, logistic regression with only sample weights also produced similar results (aOR = 19.9, 95% CI: 10.2–38.8), suggesting that the effect was not influenced by weighting. These results confirm that HIV testing was highly correlated with facility-based delivery and highlight the magnitude of its association, bearing in mind the caution expressed regarding the small sample size of untested women. Discussion In our study, to analyse trends in facility-based delivery in Zimbabwe during the 2005–2015 period, interesting findings were reported. HIV testing transformed from a strong correlation to the most influential determinant over the years. Although our results reinforce the importance (in terms of interactions) of socioeconomic and antenatal care factors, they report broad historical constancy that emphasizes the striking and resilient increase in the relative influence of HIV testing on facility delivery. The persistent, yet stable, associations we observed for higher maternal education, wealth, and urban residence are well-documented pillars of healthcare access, corroborating evidence from Bangladesh, Nepal, Ethiopia, and Rwanda [1, 11-15]. The slight weakening of the rural residence barrier is an encouraging sign of progress, potentially indicating a reduction in the urban‒rural gap, a disparity still prominently noted in recent studies in Bangladesh [16] and Nepal [12]. Similarly, the strong, consistent link between attending four or more antenatal care (ANC) visits and facility delivery is strongly supported by the literature, which establishes ANC as a critical entry point that builds a continuum of care [11,12]. As studies from Bangladesh and Rwanda emphasize, ANC is often the most important predictor of subsequent service utilization, providing a platform for education, risk assessment, and linkage to care [1]. It is against this backdrop of stable or diminishing sociodemographic influences that the extraordinary trajectory of HIV testing becomes clear. The single most impressive finding is the strong and rapidly increasing relationship between HIV testing and facility delivery. The odds ratio rose from 2.7 in 2005 to 9.7 in 2015, with a statistically significant interaction between survey year and HIV testing status. This burgeoning relationship must be seen against the backdrop of Zimbabwe's PMTCT policy and health system strengthening quickly evolving during this time. From 2005–2015, Zimbabwe phased in more effective PMTCT regimens by implementing single-dose nevirapine and then rolling out Option A followed by the introduction of Option B+, which recommended lifelong ART for all HIV-positive pregnant women. The implications of this policy shift for both the process and content of antenatal care were extensive. The second reason is that in the era of ART and where facility delivery is mandatory, providing supportive care at the health facility ensures that a mother can theoretically initiate or continue this life-saving therapy and hence offer immediate protection for her baby [17]. This may have helped to reinforce counselling messages regarding the importance of facility delivery for PMTCT and made them more real and close. Second, the systematic inclusion of HIV care in antenatal and postnatal care, a core component of this period, could have reduced stigma, which has previously been shown to be a barrier in studies among Kenyan women[8], and increased rates of testing and treatment through the provision of standard services. When universal HIV testing was implemented as part of the ANC package, deciding to be tested represented not only a decision to test but also an indicator that someone had engaged with a modern health system. This was also in line with the observations of [9] for Zimbabwe following the call for the integration of HIV services into ANC to improve maternal health worldwide. The very high aOR in 2015 should be interpreted with caution, as the small number residing within the untested group of women (n=225) led to statistical separation. However, the increase in the facility delivery gap from 22 percentage points in 2005 to 64 percentage points in 2015 provides a compelling indication of a real and dynamic trend. This reflects that by 2012, mature PMTCT programs directed women who accepted HIV testing increasingly to facilities, and women who refused HIV testing became an increasingly hard-to-reach group of women with a set of intertwined barriers to care. This is a valuable addition to the cross-sectional view reported before because it indicates a temporal dimension of how facility delivery became associated with HIV testing through the evolution of the health system [10]. Given that the sample size of the 2015 untested women was small, we also conducted sensitivity analyses to address issues of sparse data and separation with Firth penalization logistic regression. HIV testing remained an independent strong predictor for facility delivery (aOR 12.0, 95% CI: 5.2–27.8), and testing for HIV was not a strong predictor because low-frequency events were the driving force behind the reported associations. However, the magnitude of the effect should be interpreted cautiously because in the remaining untested subsample, some amount of overlap with multiple barriers to care likely exists. These results convey both the success of HIV programs in fostering nearly universal facility delivery and the high bar for engaging the relatively small group that has yet to be recruited through testing and safe delivery services. Decaying effects of wealth and media exposure over time and a sustained, although nontime wholes in terms of the effect of education, provides further suggestive evidence for this interpretation that PMTCT integration opened up new impetus to access facility delivery. This finding indicates that macrolevel policies and programs have been effective in decreasing certain disparities such that a very specific health action, such as HIV testing, is now the more potent predictor. This finding contrasts with findings from Gambia, where HIV testing during ANC was a positive correlate of service utilization (although not in the same progressive association as we have shown) [5]. Therefore, our study highlights the continued importance of socioeconomic and educational factors for facility delivery, in line with findings from South Asia and sub-Saharan African countries[18, 19]. Its most important contribution, however, is in highlighting how active and powerful HIV testing is. A rise in association over time can support the idea that PMTCT programs had a sweeping effect on increasing facility delivery, not only for HIV+ women who visit testing services but also for all women attending these facilities. This highlights the need for an integrated health policy approach that targets specific health problems but highlights the need for a whole maternity programme. Future work should seek to ensure that attempts are made to include populations previously screened by the HBP and, through the use of points of care, such as HIV testing and ANC, are critically important for ensuring safe delivery for all mothers [20]. Our study has several limitations. The study relies on self-reports with associated risks of recall bias and social desirability bias. Moreover, the findings are regional, and the generalizability of these dramatic shifts to other regions could be limited. The dynamics of this association underscore the need for continued surveillance on the basis of more recent data. Conclusion This study has underscored the effects of sustained socioeconomic and educational factors on facility delivery combined with the emerging importance of HIV testing as a determinant. These findings on the growing connection between HIV testing and facility delivery imply that programs to prevent mother‒child transmission might influence wider gains in maternal care use. These results emphasize the necessity of a comprehensive health policy focused on specific health-related problems that reinforces the maternity care system in general. Interventions going forward could focus on further scaling up such integrated service applications to reach underserved and use entry points, such as antenatal care and HIV testing services, towards the promotion of safe delivery for all mothers. Abbreviations AGYW: Adolescent Girls and Young Women ANC: Antenatal Care aOR: Adjusted odds ratio BR: Birth Recode (DHS file) CI: Confidence interval DHS: Demographic and Health Survey(s) F: F statistic HIV: Human immunodeficiency virus HTC: HIV Testing and Counselling IR: Individual Recode (DHS file) IRR: Incidence rate ratio (mentioned in the literature, not the primary results) OR: Odds ratio p: p value PMTCT: Prevention of Mother-to-Child Transmission (of HIV) Ref: Reference (category) SSA: Sub-Saharan Africa ZDHS: Zimbabwe Demographic and Health Survey(s) Declarations Acknowledgements The authors gratefully acknowledge the Demographic and Health Surveys (DHS) Program for providing the data used in this analysis. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author information Authors and affiliations Department of Applied Biosciences and Biotechnology, Faculty of Science and Technology, Zimbabwe Hilary Takunda Takawira Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe Hilary Takunda Takawira Contributions H.T.T. conceptualized the study; conducted the data processing, formal analysis, and investigation; and drafted the original manuscript. P.N. contributed to the methodology, validated the analysis, assisted with the interpretation of the results, and reviewed and edited the manuscript. All the authors reviewed and approved the final manuscript. Corresponding author Please send correspondence to Hilary Takunda Takawira ( [email protected] ). Ethics approval and consent to participate Ethical Approval Zimbabwe Demographic and Health Survey (ZDHS) protocols were approved by the Medical Research Council of Zimbabwe (MRCZ). Permission to use the data for this analysis was obtained from the Demographic and Health Surveys (DHS) Program. All DHS datasets are available to the public and fully anonymized prior to release; thus, no further ethical approval was needed for this secondary analysis. All procedures were performed following appropriate guidelines and regulations. Data availability This research was based on secondary data from the Zimbabwe Demographic Health Surveys (2005–06, 2010–11, and 2015–16). These datasets are generally publicly available at the Demographic and Health Surveys (DHS) Program. Data can be accessed upon reasonable request following registration and through data requests at https://dhsprogram.com/data/. All personal information has been processed to be anonymous, and this study does not include any individually identifiable data. Consent for publication Not applicable. (This study uses anonymized, publicly available survey data.) 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PLoS ONE. 2025;20(5 MAY). https://doi.org/10.1371/journal.pone.0322309 Yaya S, Oladimeji O, Oladimeji KE, Bishwajit G. Prenatal care and uptake of HIV testing among pregnant women in Gambia: A crosssectional study. BMC Public Health. 2020;20(1). https://doi.org/10.1186/s12889020086184 Tuthill EL, Odhiambo BC, Maltby AE. Understanding mother-to-child transmission of HIV among mothers engaged in HIV care in Kenya: a case report. Int Breastfeed J. 2024;19(1). https://doi.org/10.1186/s13006024006223 Gill MM, Machekano R, Isavwa A, Ahimsibwe A, Oyebanji O, Akintade OL, et al. The Association Between HIV Status and Antenatal Care Attendance Among Pregnant Women in Rural Hospitals in Lesotho. J Acquir Immune Defic Syndr. 2015. https://doi.org/10.1097/qai.0000000000000481 Turan JM, Hatcher AH, MedemaWijnveen J, Onono M, Miller S, Bukusi EA, et al. The role of HIV-related stigma in utilization of skilled childbirth services in rural Kenya: A prospective mixed methods study. PLoS Med. 2012;9(8). https://doi.org/10.1371/journal.pmed.1001295 Maruva M, Gwavuya S, Marume M, Musarandega R, Madzingira N. Knowledge of HIV Status at ANC and Utilization of Maternal Health Services in the 201011 Zimbabwe Demographic and Health Survey. ICF International; 2014. Buzdugan R, McCoy SI, Webb K, Mushavi A, Mahomva A, Padian NS, et al. Facility-based delivery in the context of Zimbabwe's HIV epidemic missed opportunities for improving engagement with care: A community-based serosurvey. BMC Pregnancy Childbirth. 2015;15(1). https://doi.org/10.1186/s128840150782y Rahman MM, Haque SE, Sarwar S, Rahaman MM, Mostofa MG. Effects of women’s empowerment on maternal healthcare utilization in Bangladesh: evidence from a nationally representative cross-sectional survey. J Biosoc Sci. 2021;53(5):687-702. Thapa B, Karki A, Sapkota S, Hu Y. Determinants of institutional delivery service utilization in Nepal. PLoS ONE. 2023;18(9 September). https://doi.org/10.1371/journal.pone.0292054 Shahabuddin ASM, Delvaux T, Utz B, Bardají A, De Brouwere V. Determinants and trends in health facility-based deliveries and caesarean sections among married adolescent girls in Bangladesh. BMJ Open. 1993. https://doi.org/10.1136/bmjopen2016012424 Arefaynie M, Kefale B, Yalew M, Adane B, Dewau R, Damtie Y. Number of antenatal care utilization and associated factors among pregnant women in Ethiopia: zeroinflated Poisson regression of 2019 intermediate Ethiopian Demography Health Survey. Reprod Health. 2022;19(1). https://doi.org/10.1186/s12978022013474 Woldeyohannes B, Yohannes Z, Likassa HT, Mekebo GG, Wake SK, Sisay AL, et al. Count regression models analysis of factors affecting antenatal care utilization in Ethiopia. Ann Med Surg. 2023;85(10):4882–4886. https://doi.org/10.1097/ms9.0000000000000705 Alam ATMS, Alam S, Mobasshira K, Anik SMN, Hasan MN, Chowdhury MAB, Uddin MJ. Exploring urban‒rural inequalities of maternal healthcare utilization in Bangladesh. Heliyon. 2025 Jan 15;11(2):e41945. doi: 10.1016/j.heliyon.2025.e41945. PMID: 39911430; PMCID: PMC11795031. World Health Organization. The World Health Report 2005: Make every mother and child count. World Health Organization; 2005. Arefaynie M, Kefale B, Yalew M, Adane B, Dewau R, Damtie Y. Number of antenatal care utilization and associated factors among pregnant women in Ethiopia: zeroinflated Poisson regression of 2019 intermediate Ethiopian Demography Health Survey. Reprod Health. 2022;19(1). https://doi.org/10.1186/s12978022013474 Woldeyohannes B, Yohannes Z, Likassa HT, Mekebo GG, Wake SK, Sisay AL, et al. Count regression models analysis of factors affecting antenatal care utilization in Ethiopia. Ann Med Surg. 2023;85(10):4882–4886. https://doi.org/10.1097/ms9.0000000000000705 Choulagai B, Onta S, Subedi N, Mehata S, Bhandari GP, Poudyal A, et al. Barriers to using skilled birth attendants' services in mid and northwestern Nepal: a cross-sectional study. BMC Int Health Hum Rights. 2013;13:49. http://www.biomedcentral.com/1472698X/13/49 Additional Declarations No competing interests reported. Supplementary Files Appendices.docx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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06:56:23","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":163499,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7802918/v1/eb2cf824f75984f036f59c64.html"},{"id":93107588,"identity":"b5812e4e-514b-43f0-be9a-a11c83930ac8","added_by":"auto","created_at":"2025-10-09 06:56:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends in HIV testing across facility-based deliveries: Zimbabwe Demographic and Health Surveys (2005-2015).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7802918/v1/830be5eea0eb88f79b8b1b62.png"},{"id":93109556,"identity":"39223915-7a47-4600-8464-e53f779be607","added_by":"auto","created_at":"2025-10-09 07:25:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1642172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7802918/v1/b1efa954-ac7d-4e4c-b096-1d8a69a598f9.pdf"},{"id":93107587,"identity":"3905ee5e-4e9e-427f-9fe4-1e2ec07992b7","added_by":"auto","created_at":"2025-10-09 06:56:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24081,"visible":true,"origin":"","legend":"","description":"","filename":"Appendices.docx","url":"https://assets-eu.researchsquare.com/files/rs-7802918/v1/24584919fdceec8ca54e3301.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Temporal Dynamics of HIV Testing as a Predictor of Facility Delivery among adolescent girls and young women (AGYW): Evidence from the Zimbabwe Demographic and Health Surveys (2005–2015)","fulltext":[{"header":"Background","content":"\u003cp\u003eMaternal mortality remains a significant public health issue in sub-Saharan Africa, with the adoption of facility-based delivery being a cornerstone strategy for its reduction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Zimbabwe has a historically high maternal mortality ratio, and the determinants of this key behavior are multifaceted. Studies from Bangladesh, Ethiopia, and Gambia have shown that factors such as higher maternal education, greater household wealth, urban residence, and lower parity are strongly associated with increased facility deliveries [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe HIV epidemic in Zimbabwe adds a critical layer of complexity to maternal healthcare. Since the early 2000s, the integration of HIV testing and counselling (HTC) into antenatal care has been the primary entry point for the prevention of mother-to-child transmission (PMTCT) of HIV [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A woman\u0026rsquo;s knowledge of her HIV status during pregnancy is therefore vital not only for initiating life-saving antiretroviral therapy but also for influencing her subsequent engagement with the healthcare system [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral studies have suggested that receiving an HIV test is a powerful motivator for completing the continuum of care, including facility delivery, as it is a key gateway to PMTCT services [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, this relationship is not static. Maternal and HIV care has significantly transformed over the past decade. PMTCT programs have scaled up, \u0026ldquo;test and treat\u0026rdquo; policies have been adopted more, and the normalization of routine opt-out testing in antenatal clinics may have fundamentally altered the role of an HIV test. What was once a distinctive, motivating event may now be a standard, and perhaps less influential, component of antenatal care. While cross-sectional studies have provided some insights into this relationship [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], a critical gap remains in understanding how the importance of HIV testing as a determinant of facility delivery has evolved over time.\u003c/p\u003e\u003cp\u003eThis study aims to fill this gap by analysing nationally representative data from Zimbabwe spanning a decade of significant health system change. By tracing the temporal dynamics of this association while accounting for established sociodemographic and pregnancy-related factors, this research will determine whether the value of HIV testing as an incentive for facility delivery has been sustained, diminished, or transformed. The findings provide critical evidence to inform more effective and integrated maternal and child health policies in Zimbabwe and similar high-HIV burden settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and data sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used a series of cross-sectional surveys, analysing secondary data from ZDHS conducted in 2005, 2010 and 2015. The DHS program employs a two-stage stratified cluster sampling design to collect nationally representative data on key health indicators. For this study, we combined individual recode (IR) files, which contain data from all women of reproductive age, with birth recode (BR) files, which contain detailed information on each live birth.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population and sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population consisted of women aged 15--24 years who had given birth at least once. To focus on recent maternal health service utilization and ensure accurate recall, the sample was restricted to women whose last birth occurred within the 35 months preceding the survey year. The final sample used for the analysis was constructed by successfully merging the IR and BR files for each survey year, retaining only the most recent birth for each woman to ensure that each contributed a single observation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData preparation and variable construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data management and analyses were conducted in Stata/MP 18.0. The variables were harmonized across the three survey years of 2005, 2010 and 2016 to ensure consistency. The primary outcome was facility-based delivery, defined as binary variable comparing deliveries in health facilities versus those at home or elsewhere. The primary independent variable was a binary indicator of whether the woman had ever received an HIV test. Covariates known to influence maternal health service utilization were included (\u003cstrong\u003eTable 1\u003c/strong\u003e), encompassing sociodemographic factors (survey year, age at birth, place of residence, educational attainment, wealth quintile, marital status, and parity) and a measure of women\u0026rsquo;s empowerment on the basis of decision-making autonomy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Variables used in the analysis of maternal health service utilization in the Zimbabwe DHS (2005\u0026ndash;2015)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eVariable Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eMeasurement/Categories\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cem\u003eOutcome variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003eFacility delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eDelivery in a health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eBinary: 0 = no, 1 = yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003e\u003cem\u003eExposure variable\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003eEver tested for HIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eEver tested for HIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eBinary: 0 = no, 1 = yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cem\u003eDemographic variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eCurrent age group (5-year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003e15\u0026ndash;19, 20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eMother age at birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s age at birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003e15\u0026ndash;19, 20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003ePlace of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eUrban, rural\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eHighest education level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eNo education, primary, secondary, \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; higher\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eWealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eWealth index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003ePoorest, poorer, middle, richer, richest\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eSimplified marital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eMarried/cohabiting, never married, Widowed/divorced, separated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eCategorical\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cem\u003ePregnancy-related variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eNumber of children ever born\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eContinuous\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eBirth order\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBirth order of most recent child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eContinuous\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\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: 149px;\"\u003e\n \u003cp\u003eAnc 4 plus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eFour or more ANC visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eBinary: 0 = no, 1 = yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eMedia exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eMedia exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eYes, No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eHealthcare decision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eWho decides on healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 306px;\"\u003e\n \u003cp\u003eRespondent alone, Joint decision, Partner alone, Someone else, Other\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSeveral categorical variables were collapsed for statistical clarity (\u003cstrong\u003eTable 1\u003c/strong\u003e), ensuring that there\u0026nbsp;were sufficient sample sizes for stable estimates while preserving meaningful distinctions for understanding healthcare utilization patterns. Education was collapsed into two groups: less than secondary versus secondary or higher. Marital status was simplified into married/cohabiting, never married, widowed/divorced, and separated. Religion was grouped into Christian, Apostolic, Muslim, and no religion/traditional/other. Age was categorized into standard five-year intervals. These decisions balance parsimony, interpretability, and statistical robustness while preserving distinctions of substantive and policy relevance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHandling of missing data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMissing data for all variables included in the analysis were handled via a complete-case approach. Observations with missing values for any of the key covariates (e.g., HIV testing status, facility delivery, sociodemographic variables) were excluded from the corresponding analyses. The proportion of missing data was minimal, and survey weights were retained in all analyses to account for the complex sampling design.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eAll analyses accounted for the complex, multistage sampling design of the DHS by applying sampling weights and adjusting for clustering at the level of the primary sampling unit and stratification. Descriptive statistics were computed to characterize the study sample and describe trends in all variables, including the outcome and key independent variables, across the three survey years. Univariable logistic regression models were used to assess the associations between each independent variable and facility-based delivery.\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression was used to test for the specific hypothesis that the association between HIV testing and facility-based delivery, in Zimbabwe, evolved over time. To estimate the average association between HIV testing and facility-based delivery, a main effects model was fitted to the pooled data from all three surveys. To formally test for temporal change, a model was then specified that included an interaction term between the survey year and HIV testing status. A statistically significant interaction confirmed that the relationship between HIV testing and facility delivery was not constant across the study period.\u003c/p\u003e\n\u003cp\u003eOnce a significant interaction was found, the final step was to present the results through survey year-stratified models. This approach allowed for a clear interpretation of the evolving relationship, as it directly displays the magnitude, direction, and significance of the association between HIV testing and facility delivery at each time point, adjusted for all covariates. These stratified models included the full set of confounders, including residence, education, wealth, age, marital status, decision-making autonomy, and media exposure, to isolate the specific role of HIV testing within the context of each survey year.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted several sensitivity analyses to assess the association between HIV testing and facility delivery in 2015. Firth penalized logistic regression was employed to address potential bias due to sparse data and quasicomplete separation, which can occur when the number of untested women is very small. To determine whether the effect size of HIV testing changed when a small number of covariates were controlled for, a reduced multivariable model comprising only HIV testing, wealth quintile, education, and residence status was fitted.\u003c/p\u003e\n\u003cp\u003eA reduced multivariable model including only HIV testing, wealth quintile, education, and residence was fitted to examine whether the effect size of HIV testing changed when adjusting for a limited set of covariates. Unweighted logistic regression with cluster-robust standard errors was performed to confirm that survey weights did not substantially influence the results. These complementary analyses were conducted to ensure that the observed association was robust and not an artifact of modelling choices or sparse data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZimbabwe Demographic and Health Survey (ZDHS) protocols were approved by the Medical Research Council of Zimbabwe (MRCZ). Permission to use the data for this analysis was sought from The Demographic and Health Surveys (DHS) Program. All DHS datasets are available to the public and fully anonymized prior to release, thus no further ethical approval was needed for this secondary analysis. All procedures were performed following appropriate guidelines and regulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSociodemographic characteristics and bivariate associations for the pooled dataset\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 4,018 women were eligible for this analysis (Table 2).\u0026nbsp;A total of 4,018, 78.2% (N=\u0026nbsp;3,140)\u0026nbsp;reported delivering in a health facility. Across the entire study period, 3,076 women (76.6%) had ever been tested for HIV. Women were mostly living in rural areas (63.8%) and had achieved secondary or higher education (74.7%). Almost one in five were from the lowest wealth quintile (19.1%), which was similar to the highest (19.2%). The majority (72.8%) of women reported attending a minimum of four ANC visits. In the age group, over two-thirds were 20\u0026ndash;24 years old (69.9%), and most were married or cohabiting (77.9%). Slightly more than half of the women had media exposure (52.4%). In terms of religion, the majority were Christians (52.1%) and Apostolics (39.7%). The majority of the women were primiparous (68.6%), and more than half delivered at ages 15\u0026ndash;19 years (53.0%). In relation to household decision-making, the majority reported that decisions about medical care were made with a partner (24.6%) or by someone else (41.4%), although 19.3% said they made the decisions alone.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Sociodemographic characteristics of the women included in the study and bivariate associations with facility delivery, Zimbabwe DHS combined sample (2005\u0026ndash;2015).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePearson \u0026chi;\u0026sup2; P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e4,018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3,140 (78.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver tested for HIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e942 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e522 (55.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e3,076 (76.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2,618 (85.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,456 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,339 (92.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2,562(63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,801 (70.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eLess than secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,018 \u0026nbsp;(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e614 (60.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eSecondary or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e3,000 (74.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2,526 (84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth quintile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e767 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e464 (60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e707(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e481 (68.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e724(18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e560 (77.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,049 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e908 (86.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e771 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e727 (94.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANC visits (\u0026ge;4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e745 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e508 (68.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,995 (72.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,697 (85.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e15\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e947 (30.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e684 (72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2,202 (69.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,705 (77.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eMarried/Cohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e3,130 (77.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2,449 (78.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e486 \u0026nbsp;(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e387 (79.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eWidowed/Divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e202 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e153 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e200 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e151 (75.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedia exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,823 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,296 (71.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2,007 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,687 (84.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2,091 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,782 (85.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eApostolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,593 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,137 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e20 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e18 (90.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eNo religion/Traditional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e312 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e202 (64.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2,755 (68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2,219 (80.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,165 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e853 (73.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eThree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e95 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e66 (69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eFour plus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e3 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026rsquo;s age at birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e15\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,842 (53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,357 (73.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1,632 (47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,311 (80.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare decision autonomy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eRespondent alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e273 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e230 (84.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eJoint decision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e348 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e256 (73.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003ePartner alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e207 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e162 (78.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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: 227px;\"\u003e\n \u003cp\u003eSomeone else\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e585 (41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e456 (77.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\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\u003cstrong\u003eFacility delivery and HIV testing trends by sociodemographic factors, stratified by year\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFacility delivery increased steadily in Zimbabwe between 2005 and 2015. In 2005, 72.7% of women delivered in a health facility, increasing slightly to 74.4% in 2010 and reaching 86.8% in 2015, indicating substantial improvements in the utilization of facility-based delivery services over the decade (\u003cstrong\u003eTa\u003c/strong\u003e\u003cstrong\u003eble 3\u003c/strong\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Sociodemographic characteristics of women and bivariate associations with facility delivery, stratified by survey year (Zimbabwe DHS 2005, 2010, and 2015)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDHS 2005\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=\u003c/strong\u003e1,194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDHS 2010\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN=1,440\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDHS 2015\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=\u003c/strong\u003e1,384\u003c/p\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e868(72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1,071(74.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1,201(86.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver tested for HIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e410 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e92 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e20 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e458 (86.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e979 (79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1,181 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e374 (94.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e438 (88.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e527 (93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e494 (62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e633 (66.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e674 (82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eLess than secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e181 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e186 (55.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e247 (75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eSecondary or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e687 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e885 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e954 (90.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth quintile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e122 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e163 (58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e179 (74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e134 (59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e166 (62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e181 (82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e167 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e196 (72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e197 (86.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e246 (86.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e298 (82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e364 (90.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e199 (96.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e248 (92.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e280 (94.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANC \u0026ge;4 visits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e141 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e195 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e172 (81.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e481 (80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e538 (80.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e678 (92.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e15\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e167 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e218 (67.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e299 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e517 (74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e561 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e627 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMarried/Cohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e689 (73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e845 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1,050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e915 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e90 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e121 (79.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e176 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eWidowed/Divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e56 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e48 (71.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e49 (83.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e33 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e57 (78.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e61 (80.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedia exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e404 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e462 (67.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e430 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e428 (82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e567 (80.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e692 (89.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e529 (82.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e608 (81.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e645 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eApostolic sect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e255 (63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e405 (67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e477 (80.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e9 (90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e6 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNo religion/Tradition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e75 (54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e55 (60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e72 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e626 (74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e742 (76.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e851 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e218 (68.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e307 (69.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e328 (80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eThree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e23 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e22 (84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e21 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eFour plus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026rsquo;s age at birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e15\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e361 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e426 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e570 (86.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e404 (78.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e470 (77.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e437 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare decision\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eRespondent alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e28 (71.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e104 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e98 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eJoint decision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e44 (58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e77 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e135 (80.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003ePartner alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e162 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eSomeone else\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e79 (68.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e128 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e249 (87.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\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\u003eHIV testing coverage also increased with time, with women who ever tested being consistently more likely to deliver in a facility \u003cstrong\u003e(Fig 1).\u0026nbsp;\u003c/strong\u003eIn 2005, among women who had ever been tested for HIV, facility-based delivery was 86.1% versus 61.9% among those who had not. By 2015, this gap had increased; among those tested, 89.9% delivered in a facility, and among those not tested, 28.2% (p\u0026lt;0.001), indicating increased levels of testing coverage as well as a strengthened association with facility delivery over time.\u003c/p\u003e\n\u003cp\u003eUrban women continued to have significantly higher facility delivery coverage than rural women (94.2% vs 59.9% in 2005, 93.3% vs 82.3% in 2015). Women in the richest quintile near universal coverage for facility delivery across the survey years (95.7%,\u0026rarr;96.5%) compared to the poorest (45.1% \u0026rarr;75.%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral factors were significantly associated with increased odds of facility delivery in univariate analyses. Those living in rural areas also had significantly lower odds than those living in urban areas did (OR = 0.22, 95% CI: 0.17\u0026ndash;0.29). Women who had ever received an HIV test (OR = 2.53, 95% CI: 2.14\u0026ndash;3.00), had a higher education level (OR=3.41, 95% CI: 2.92\u0026ndash;3.97), were exposed to mass media (OR = 2.03; 95% CI: [1\u0026middot;71\u0026ndash;2\u0026middot;30]), and attended four or more ANC visits (OR = 2.61; [CI: [1\u0026middot;59\u0026ndash;3]). A good nexus with wealth and maternal age at birth is a good relationship with wealth, i.e., it is a sign of lifestyle; this attitude indicates that a good number of children are not considered influential for women or their reproductive health. Some variables, such as marital status and decision-making autonomy, were not found to be significantly associated with facility delivery via these univariate analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of facility delivery: Multivariable analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was a statistically significant survey year and HIV testing interaction (adjusted Wald test, F (2, 758) = 3.12, p = 0.045), suggesting that the effect of HIV testing on facility delivery differed by survey year. Thus, the association between HIV testing and facility delivery became much stronger in 2015 than in previous years.\u003c/p\u003e\n\u003cp\u003eWe explored the factors associated with facility delivery across different years of the DHS surveys (2005, 2010 and 2015). Ever testing for HIV was strongly associated with increased odds of delivering in a health facility (Table 4: Appendix 2). Women who underwent an HIV test were far more likely to deliver in a facility than women who had never been tested. The difference increased over the study period: by 2005, tested women were approximately 2.7 times more likely to deliver in a health facility (aOR=2.7: 95% CI: 1.64\u0026ndash;4.26) than were those who were not tested. In 2010, those tested were three times more likely to deliver in a health facility than those who were not tested (aOR= 3.33; 95% CI: 2.07\u0026ndash;5.36), and those who had been tested in 2015 were almost tenfold more likely (aOR= 9.41; 95% CI: 3.50--26.90) to have delivered at a facility than those who were not tested.\u003c/p\u003e\n\u003cp\u003eOther associated factors for giving birth in a facility were attending 4+ ANC visits and having a higher level of education. Women with at least four ANC visits were twice as likely to have a facility delivery in 2005 (OR = 2.09, 95% CI: 1.26\u0026ndash;3.49) than those who had fewer than 4 ANC visits. In 2010, women who attended at least four ANC visits had 57% greater odds of delivering in a health facility than those with fewer than four ANC visits did (OR = 1.57, 95% CI: 1.05\u0026ndash;2.34). The odds for delivery in a facility doubled in 2015 (OR = 2.09; 95% CI: 1.14\u0026ndash;3.83) for those with at least four ANC visits compared with those with fewer than four ANC visits. Having secondary education or higher was also associated with giving birth in a health facility (Table 4: Appendix 2). In 2010, women who had achieved secondary or higher education were more than twice as likely to give birth in a health facility (OR = 2.19, 95% CI: 1.39\u0026ndash;3.45) than those without secondary education. By the year 2015, women who had secondary education or higher were more than three times more likely to give birth in a health facility than were those who had primary or no education (OR = 3.30; 95% CI: 1.83\u0026ndash;5.96).\u003c/p\u003e\n\u003cp\u003eThere was no clear effect on facility delivery by place of residence, wealth status or exposure to mass media between the survey years. In 2005, rural women were far less likely to have a facility for childbirth, but by 2010 and 2015, this difference was no longer apparent (Table 4: Appendix 2). Living in rural areas was strongly protective against facility delivery in 2005, with women in rural settings having approximately 89% lower odds of delivering in a facility than their urban counterparts (OR = 0.11, 95% CI: 0.04\u0026ndash;0.31). However, this effect diminished and was not statistically significant in 2010 and 2015. Wealth and media exposure were not consistent in direction of association and attenuated over time (Table 4: Appendix 2). Marital status, religion, and the mother\u0026rsquo;s age at birth were nonsignificant determinants of facility delivery for all survey years.\u003c/p\u003e\n\u003cp\u003eBecause of the very low number of women untested in 2015, we carried out sensitivity analyses to determine whether our findings on the association between HIV testing and facility delivery were robust. Firth penalized logistic regression (accounting for sparse data and separation) yielded a strongly adjusted odds ratio of HIV testing (aOR = 12.0, 95% CI: 5.2\u0026ndash;27.8). A more parsimonious model that included only HIV testing, wealth quintile, education and residence yielded a comparable slightly higher estimate (aOR = 19.7; 95% CI: 9.9\u0026ndash;39.4). Notably, logistic regression with only sample weights also produced similar results (aOR = 19.9, 95% CI: 10.2\u0026ndash;38.8), suggesting that the effect was not influenced by weighting. These results confirm that HIV testing was highly correlated with facility-based delivery and highlight the magnitude of its association, bearing in mind the caution expressed regarding the small sample size of untested women.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, to analyse trends in facility-based delivery in Zimbabwe during the 2005\u0026ndash;2015 period, interesting findings were reported. HIV testing transformed from a strong correlation to the most influential determinant over the years. Although our results reinforce the importance (in terms of interactions) of socioeconomic and antenatal care factors, they report broad historical constancy that emphasizes the striking and resilient increase in the relative influence of HIV testing on facility delivery.\u003c/p\u003e\n\u003cp\u003eThe persistent, yet stable, associations we observed for higher maternal education, wealth, and urban residence are well-documented pillars of healthcare access, corroborating evidence from Bangladesh, Nepal, Ethiopia, and Rwanda [1, 11-15]. The slight weakening of the rural residence barrier is an encouraging sign of progress, potentially indicating a reduction in the urban‒rural gap, a disparity still prominently noted in recent studies in Bangladesh [16] and Nepal [12]. Similarly, the strong, consistent link between attending four or more antenatal care (ANC) visits and facility delivery is strongly supported by the literature, which establishes ANC as a critical entry point that builds a continuum of care [11,12]. As studies from Bangladesh and Rwanda emphasize, ANC is often the most important predictor of subsequent service utilization, providing a platform for education, risk assessment, and linkage to care [1]. It is against this backdrop of stable or diminishing sociodemographic influences that the extraordinary trajectory of HIV testing becomes clear.\u003c/p\u003e\n\u003cp\u003eThe single most impressive finding is the strong and rapidly increasing relationship between HIV testing and facility delivery. The odds ratio rose from 2.7 in 2005 to 9.7 in 2015, with a statistically significant interaction between survey year and HIV testing status. This burgeoning relationship must be seen against the backdrop of Zimbabwe\u0026apos;s PMTCT policy and health system strengthening quickly evolving during this time. From 2005\u0026ndash;2015, Zimbabwe phased in more effective PMTCT regimens by implementing single-dose nevirapine and then rolling out Option A followed by the introduction of Option B+, which recommended lifelong ART for all HIV-positive pregnant women.\u003c/p\u003e\n\u003cp\u003eThe implications of this policy shift for both the process and content of antenatal care were extensive. The second reason is that in the era of ART and where facility delivery is mandatory, providing supportive care at the health facility ensures that a mother can theoretically initiate or continue this life-saving therapy and hence offer immediate protection for her baby [17]. This may have helped to reinforce counselling messages regarding the importance of facility delivery for PMTCT and made them more real and close. Second, the systematic inclusion of HIV care in antenatal and postnatal care, a core component of this period, could have reduced stigma, which has previously been shown to be a barrier in studies among Kenyan women[8], and increased rates of testing and treatment through the provision of standard services. When universal HIV testing was implemented as part of the ANC package, deciding to be tested represented not only a decision to test but also an indicator that someone had engaged with a modern health system. This was also in line with the observations of [9] for Zimbabwe following the call for the integration of HIV services into ANC to improve maternal health worldwide.\u003c/p\u003e\n\u003cp\u003eThe very high aOR in 2015 should be interpreted with caution, as the small number residing within the untested group of women (n=225) led to statistical separation. However, the increase in the facility delivery gap from 22 percentage points in 2005 to 64 percentage points in 2015 provides a compelling indication of a real and dynamic trend. This reflects that by 2012, mature PMTCT programs directed women who accepted HIV testing increasingly to facilities, and women who refused HIV testing became an increasingly hard-to-reach group of women with a set of intertwined barriers to care. This is a valuable addition to the cross-sectional view reported before because it indicates a temporal dimension of how facility delivery became associated with HIV testing through the evolution of the health system [10].\u003c/p\u003e\n\u003cp\u003eGiven that the sample size of the 2015 untested women was small, we also conducted sensitivity analyses to address issues of sparse data and separation with Firth penalization logistic regression. HIV testing remained an independent strong predictor for facility delivery (aOR 12.0, 95% CI: 5.2\u0026ndash;27.8), and testing for HIV was not a strong predictor because low-frequency events were the driving force behind the reported associations. However, the magnitude of the effect should be interpreted cautiously because in the remaining untested subsample, some amount of overlap with multiple barriers to care likely exists. These results convey both the success of HIV programs in fostering nearly universal facility delivery and the high bar for engaging the relatively small group that has yet to be recruited through testing and safe delivery services.\u003c/p\u003e\n\u003cp\u003eDecaying effects of wealth and media exposure over time and a sustained, although nontime wholes in terms of the effect of education, provides further suggestive evidence for this interpretation that PMTCT integration opened up new impetus to access facility delivery. This finding indicates that macrolevel policies and programs have been effective in decreasing certain disparities such that a very specific health action, such as HIV testing, is now the more potent predictor. This finding contrasts with findings from Gambia, where HIV testing during ANC was a positive correlate of service utilization (although not in the same progressive association as we have shown) [5]. Therefore, our study highlights the continued importance of socioeconomic and educational factors for facility delivery, in line with findings from South Asia and sub-Saharan African countries[18, 19]. Its most important contribution, however, is in highlighting how active and powerful HIV testing is. A rise in association over time can support the idea that PMTCT programs had a sweeping effect on increasing facility delivery, not only for HIV+ women who visit testing services but also for all women attending these facilities. This highlights the need for an integrated health policy approach that targets specific health problems but highlights the need for a whole maternity programme. Future work should seek to ensure that attempts are made to include populations previously screened by the HBP and, through the use of points of care, such as HIV testing and ANC, are critically important for ensuring safe delivery for all mothers [20].\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. The study relies on self-reports with associated risks of recall bias and social desirability bias. Moreover, the findings are regional, and the generalizability of these dramatic shifts to other regions could be limited. The dynamics of this association underscore the need for continued surveillance on the basis of more recent data.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study has underscored the effects of sustained socioeconomic and educational factors on facility delivery combined with the emerging importance of HIV testing as a determinant. These findings on the growing connection between HIV testing and facility delivery imply that programs to prevent mother‒child transmission might influence wider gains in maternal care use. These results emphasize the necessity of a comprehensive health policy focused on specific health-related problems that reinforces the maternity care system in general. Interventions going forward could focus on further scaling up such integrated service applications to reach underserved and use entry points, such as antenatal care and HIV testing services, towards the promotion of safe delivery for all mothers.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAGYW:\u003c/strong\u003e Adolescent Girls and Young Women\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANC:\u003c/strong\u003e Antenatal Care\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eaOR:\u003c/strong\u003e Adjusted odds ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBR:\u003c/strong\u003e Birth Recode (DHS file)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCI:\u003c/strong\u003e Confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDHS:\u003c/strong\u003e Demographic and Health Survey(s)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eF:\u003c/strong\u003e F statistic\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHIV:\u003c/strong\u003e Human immunodeficiency virus\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHTC:\u003c/strong\u003e HIV Testing and Counselling\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIR:\u003c/strong\u003e Individual Recode (DHS file)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRR:\u003c/strong\u003e Incidence rate ratio (mentioned in the literature, not the primary results)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR:\u003c/strong\u003e Odds ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ep:\u003c/strong\u003e p value\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePMTCT:\u003c/strong\u003e Prevention of Mother-to-Child Transmission (of HIV)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRef:\u003c/strong\u003e Reference (category)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSSA:\u003c/strong\u003e Sub-Saharan Africa\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZDHS:\u003c/strong\u003e Zimbabwe Demographic and Health Survey(s)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the Demographic and Health Surveys (DHS) Program for providing the data used in this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eDepartment of Applied Biosciences and Biotechnology, Faculty of Science and Technology, Zimbabwe\u003c/strong\u003e\n \u003cul\u003e\n \u003cli\u003eHilary Takunda Takawira\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eZvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe\u003c/strong\u003e\n \u003cul\u003e\n \u003cli\u003eHilary Takunda Takawira\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.T.T. conceptualized the study; conducted the data processing, formal analysis, and investigation; and drafted the original manuscript. P.N. contributed to the methodology, validated the analysis, assisted with the interpretation of the results, and reviewed and edited the manuscript. All the authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlease send correspondence to Hilary Takunda Takawira ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical Approval\u003c/p\u003e\n\u003cp\u003eZimbabwe Demographic and Health Survey (ZDHS) protocols were approved by the Medical Research Council of Zimbabwe (MRCZ). Permission to use the data for this analysis was obtained from the Demographic and Health Surveys (DHS) Program. All DHS datasets are available to the public and fully anonymized prior to release; thus, no further ethical approval was needed for this secondary analysis. All procedures were performed following appropriate guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was based on secondary data from the Zimbabwe Demographic Health Surveys (2005\u0026ndash;06, 2010\u0026ndash;11, and 2015\u0026ndash;16). These datasets are generally publicly available at the Demographic and Health Surveys (DHS) Program. Data can be accessed upon reasonable request following registration and through data requests at https://dhsprogram.com/data/. All personal information has been processed to be anonymous, and this study does not include any individually identifiable data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. (This study uses anonymized, publicly available survey data.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTwagirumukiza E, Bubanje V, Girimpundu R, Sebera E. Evolution and determinants of antenatal care services utilization among women of reproductive age in Rwanda: a scoping review. BMC Health Serv Res. 2024;24(1). https://doi.org/10.1186/s12913024120380\u003c/li\u003e\n\u003cli\u003eBasha GW. Factors affecting the utilization of a minimum of four antenatal care services in Ethiopia. Obstet Gynecol Int. 2019;2019. https://doi.org/10.1155/2019/5036783\u003c/li\u003e\n\u003cli\u003eSakib MMH, Alam MK, Yasmin N, Rois R. Unveiling the sociodemographic and socioeconomic determinants of antenatal care utilization in Bangladesh: insights from the 2017\u0026ndash;18 BDHS. J Health Popul Nutr. 2025;44(1). https://doi.org/10.1186/s4104302500839w\u003c/li\u003e\n\u003cli\u003eThasineku OC, Pandit S, Acharya D, Gurung YB. Associated factors for the utilization of institutional delivery services in Nepal: Findings from the Nepal Demographic Health Survey, 2022. PLoS ONE. 2025;20(5 MAY). https://doi.org/10.1371/journal.pone.0322309\u003c/li\u003e\n\u003cli\u003eYaya S, Oladimeji O, Oladimeji KE, Bishwajit G. Prenatal care and uptake of HIV testing among pregnant women in Gambia: A crosssectional study. BMC Public Health. 2020;20(1). https://doi.org/10.1186/s12889020086184\u003c/li\u003e\n\u003cli\u003eTuthill EL, Odhiambo BC, Maltby AE. Understanding mother-to-child transmission of HIV among mothers engaged in HIV care in Kenya: a case report. Int Breastfeed J. 2024;19(1). https://doi.org/10.1186/s13006024006223\u003c/li\u003e\n\u003cli\u003eGill MM, Machekano R, Isavwa A, Ahimsibwe A, Oyebanji O, Akintade OL, et al. The Association Between HIV Status and Antenatal Care Attendance Among Pregnant Women in Rural Hospitals in Lesotho. J Acquir Immune Defic Syndr. 2015. https://doi.org/10.1097/qai.0000000000000481\u003c/li\u003e\n\u003cli\u003eTuran JM, Hatcher AH, MedemaWijnveen J, Onono M, Miller S, Bukusi EA, et al. The role of HIV-related stigma in utilization of skilled childbirth services in rural Kenya: A prospective mixed methods study. PLoS Med. 2012;9(8). https://doi.org/10.1371/journal.pmed.1001295\u003c/li\u003e\n\u003cli\u003eMaruva M, Gwavuya S, Marume M, Musarandega R, Madzingira N. Knowledge of HIV Status at ANC and Utilization of Maternal Health Services in the 201011 Zimbabwe Demographic and Health Survey. ICF International; 2014.\u003c/li\u003e\n\u003cli\u003eBuzdugan R, McCoy SI, Webb K, Mushavi A, Mahomva A, Padian NS, et al. Facility-based delivery in the context of Zimbabwe\u0026apos;s HIV epidemic missed opportunities for improving engagement with care: A community-based serosurvey. BMC Pregnancy Childbirth. 2015;15(1). https://doi.org/10.1186/s128840150782y\u003c/li\u003e\n\u003cli\u003eRahman MM, Haque SE, Sarwar S, Rahaman MM, Mostofa MG. Effects of women\u0026rsquo;s empowerment on maternal healthcare utilization in Bangladesh: evidence from a nationally representative cross-sectional survey. J Biosoc Sci. 2021;53(5):687-702.\u003c/li\u003e\n\u003cli\u003eThapa B, Karki A, Sapkota S, Hu Y. Determinants of institutional delivery service utilization in Nepal. PLoS ONE. 2023;18(9 September). https://doi.org/10.1371/journal.pone.0292054\u003c/li\u003e\n\u003cli\u003eShahabuddin ASM, Delvaux T, Utz B, Bardaj\u0026iacute; A, De Brouwere V. Determinants and trends in health facility-based deliveries and caesarean sections among married adolescent girls in Bangladesh. BMJ Open. 1993. https://doi.org/10.1136/bmjopen2016012424\u003c/li\u003e\n\u003cli\u003eArefaynie M, Kefale B, Yalew M, Adane B, Dewau R, Damtie Y. Number of antenatal care utilization and associated factors among pregnant women in Ethiopia: zeroinflated Poisson regression of 2019 intermediate Ethiopian Demography Health Survey. Reprod Health. 2022;19(1). https://doi.org/10.1186/s12978022013474\u003c/li\u003e\n\u003cli\u003eWoldeyohannes B, Yohannes Z, Likassa HT, Mekebo GG, Wake SK, Sisay AL, et al. Count regression models analysis of factors affecting antenatal care utilization in Ethiopia. Ann Med Surg. 2023;85(10):4882\u0026ndash;4886. https://doi.org/10.1097/ms9.0000000000000705\u003c/li\u003e\n\u003cli\u003eAlam ATMS, Alam S, Mobasshira K, Anik SMN, Hasan MN, Chowdhury MAB, Uddin MJ. Exploring urban‒rural inequalities of maternal healthcare utilization in Bangladesh. Heliyon. 2025 Jan 15;11(2):e41945. doi: 10.1016/j.heliyon.2025.e41945. PMID: 39911430; PMCID: PMC11795031.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. The World Health Report 2005: Make every mother and child count. World Health Organization; 2005.\u003c/li\u003e\n\u003cli\u003eArefaynie M, Kefale B, Yalew M, Adane B, Dewau R, Damtie Y. Number of antenatal care utilization and associated factors among pregnant women in Ethiopia: zeroinflated Poisson regression of 2019 intermediate Ethiopian Demography Health Survey. Reprod Health. 2022;19(1). https://doi.org/10.1186/s12978022013474\u003c/li\u003e\n\u003cli\u003eWoldeyohannes B, Yohannes Z, Likassa HT, Mekebo GG, Wake SK, Sisay AL, et al. Count regression models analysis of factors affecting antenatal care utilization in Ethiopia. Ann Med Surg. 2023;85(10):4882\u0026ndash;4886. https://doi.org/10.1097/ms9.0000000000000705\u003c/li\u003e\n\u003cli\u003eChoulagai B, Onta S, Subedi N, Mehata S, Bhandari GP, Poudyal A, et al. Barriers to using skilled birth attendants\u0026apos; services in mid and northwestern Nepal: a cross-sectional study. BMC Int Health Hum Rights. 2013;13:49. http://www.biomedcentral.com/1472698X/13/49\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Facility delivery, maternal health, HIV testing and counselling, antenatal care","lastPublishedDoi":"10.21203/rs.3.rs-7802918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7802918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eFacility-based delivery is critical for reducing maternal mortality. In high-HIV-prevalence settings such as Zimbabwe, integrating HIV testing and counselling (HTC) with antenatal care is central to PMTCT. However, the effect of HTC on maternal healthcare utilization remains underexplored. This study examines HIV testing as a determinant of facility delivery in Zimbabwe from 2005\u0026ndash;2015.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eOur study employed a pooled cross-sectional analysis of data from the Zimbabwe Demographic and Health Surveys (ZDHS) for 2005, 2010 and 2015. The study included women aged 15\u0026ndash;24 whose last birth occurred within three years of each survey. The primary outcome was facility-based delivery, and the key exposure was self-reported and never tested for HIV. We used multivariable logistic regression, stratified by survey year, to analyse temporal trends and tested for a significant interaction between HIV testing and survey year.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 4,018 women, 78.2% delivered in a health facility, increasing from 72.7% in 2005 to 86.8% in 2015. Women who had been tested for HIV were more likely to deliver in a facility (2005: aOR\u0026thinsp;=\u0026thinsp;2.65, 95% CI: 1.64\u0026ndash;4.26; 2010: aOR\u0026thinsp;=\u0026thinsp;3.33, 95% CI: 2.07\u0026ndash;5.36; 2015: aOR\u0026thinsp;=\u0026thinsp;9.71, 95% CI: 3.50\u0026ndash;26.90). Higher education (secondary or above: 2005: aOR\u0026thinsp;=\u0026thinsp;1.38, 95% CI: 0.88\u0026ndash;2.19; 2010: aOR\u0026thinsp;=\u0026thinsp;2.19, 95% CI: 1.39\u0026ndash;3.45; 2015: aOR\u0026thinsp;=\u0026thinsp;3.30, 95% CI: 1.83\u0026ndash;5.96) and attending\u0026thinsp;\u0026ge;\u0026thinsp;4 antenatal care visits (2005: aOR\u0026thinsp;=\u0026thinsp;2.09, 95% CI: 1.26\u0026ndash;3.49; 2010: aOR\u0026thinsp;=\u0026thinsp;1.57, 95% CI: 1.05\u0026ndash;2.34; 2015: aOR\u0026thinsp;=\u0026thinsp;2.09, 95% CI: 1.14\u0026ndash;3.83) also increased the likelihood of facility delivery. Rural residence was associated with lower delivery in 2005 (aOR\u0026thinsp;=\u0026thinsp;0.11, 95% CI: 0.04\u0026ndash;0.31) but not by 2015 (aOR\u0026thinsp;=\u0026thinsp;1.47, 95% CI: 0.37\u0026ndash;5.83).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eFacility delivery in Zimbabwe has improved, driven by HIV testing, education, and antenatal care. Persistent inequalities remain through residence and service engagement. HIV testing is a key entry point, highlighting the impact of the PMTCT program. Efforts should focus on expanding HIV testing, strengthening ANC, and promoting education and women\u0026rsquo;s empowerment.\u003c/p\u003e","manuscriptTitle":"Temporal Dynamics of HIV Testing as a Predictor of Facility Delivery among adolescent girls and young women (AGYW): Evidence from the Zimbabwe Demographic and Health Surveys (2005–2015)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-09 06:56:18","doi":"10.21203/rs.3.rs-7802918/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e8690af-8b35-4560-8330-a0a1e02f2d46","owner":[],"postedDate":"October 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-09T07:24:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-09 06:56:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7802918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7802918","identity":"rs-7802918","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}