What Influences Modern Contraceptive Utilisation Among Single Mothers in Nigeria? Evidence from Pooled Cross-Sectional Surveys

What Influences Modern Contraceptive Utilisation Among Single Mothers in Nigeria? 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Evidence from Pooled Cross-Sectional Surveys Benjamin Bukky Ilesanmi, Lukman Bola Solanke, Musa Balarabe Musa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-44145/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Background: Existing studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents, never married and women of advanced reproductive age. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers but the associated factors of modern contraceptive uptake among them were largely ignored. This study therefore examines factors influencing modern contraceptive utilisation among single mothers in Nigeria. Methods: Data were extracted from four consecutive Nigeria Demographic and Health Surveys (NDHSs) implemented between 2003 and 2018. A weighted sample size of 7,215 single mothers was analysed. The outcome variable was current modern contraceptive utilisation. The explanatory variables are sets of selected socio-economic and demographic characteristics such as education, household wealth quintile, place of residence, age, parity and fertility desire. Data analysis was carried out using Stata version 14. Two multivariable logistic regression models were fitted in the study. Results: Findings reveal 11.7% current utilisation of modern contraceptives among single mothers. Improvements in educational attainment and household wealth quintile increases the odds of modern contraceptive use, Muslim single mothers had lower odds of modern contraceptive use (AOR=0.527, p<0.05; 95% CI: 0.366-0.759) and employed single mothers had higher odds of modern contraceptive use (AOR=1.449, p<0.05; 95% CI: 1.123-1.867). Findings further reveal that single mothers who had moderate exposure to the mass media (AOR=1.455, p<0.05; 95% CI: 1.049-1.807), single mothers who had high exposure to the mass media (AOR=1.442, p<0.05; 95% CI: 0.690-1.394) and younger single mothers (AOR=1.377, p<0.05; 95% CI: 1.049-1.807) had higher likelihood of modern contraceptive use. Conclusion: Modern contraceptive utilisation is low among single mothers in Nigeria. A number of socio-demographic characteristics of single mothers exert significant influence on modern contraceptive use. The contraceptive need of women involved in single motherhood may be different from the needs of other groups of women. The development of a special strategy targeting single mothers is thus imperative in the country. Sexual & Reproductive Medicine Modern contraceptive use single mothers sexual and reproductive health women Nigeria Plain English Summary Existing studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents, never married and women of advanced reproductive age. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers but the associated factors of modern contraceptive uptake among them were largely ignored. This study therefore examines factors influencing modern contraceptive utilisation among single mothers in Nigeria. Data were extracted from four consecutive Nigeria Demographic and Health Surveys. The outcome variable was current modern contraceptive utilisation. The explanatory variables are sets of selected socio-economic and demographic characteristics such as education, household wealth index, employment status, age, parity and fertility desire. Findings reveal slightly more than one-tenth prevalence of current utilisation of modern contraceptives among single mothers. Improvements in educational attainment and household wealth quintile increases the likelihood of modern contraceptive use, Muslim single mothers were less likely to use modern contraceptives. Also, employed single mothers were more likely to use modern contraceptives. Findings further reveal that single mothers who had moderate exposure to the mass media, single mothers who had high exposure to the mass media and younger single mothers were more likely to use modern contraceptives. The study concluded that modern contraceptive utilisation is low among single mothers in Nigeria and recommended the development of a special strategy targeting single mothers in the country. Background Modern contraceptives are health information, counselling, services and devices used for spacing or limiting pregnancies, preventing unintended pregnancies, and reducing incidences of sexually transmitted infections [ 1 ] Evidence abounds that modern contraceptive use particularly in high fertility countries has the potential not only to reduce maternal deaths, hunger and poverty but also to improve women’s autonomy, access to education and enhanced socio-economic participation [ 2 – 3 ]. In addition, modern contraceptives are beneficial to all women and men of reproductive age irrespective of marital or social condition. This suggests that global and national initiatives to boost modern contraceptive use across the world should target all categories of women and men. But evidence indicate that single mothers (a woman who has a dependent child or dependent children but not currently married either by choice or involuntary) are rarely focused in family planning programming [ 4 – 5 ] in spite of sustained global efforts to meet worldwide demand for family planning with modern contraceptive methods. Though, single motherhood is increasingly rising across the world [ 6 – 10 ] as an evolving family type but in many developing countries including Nigeria, single motherhood is rarely accepted in the community. Many single mothers experience discrimination, rejection and blackmail from members of their community [ 11 – 13 ] and children nurtured by single mothers are perceived to be poor trained in family values [ 14 ] in addition to having elevated risks of poor health outcomes [ 15 – 17 ]. These stigmas may encourage single mothers to desire avoiding or delaying another pregnancy which make them a key segment for contraceptive demand and use in the community. However, single mothers rarely feature in family planning programming in Nigeria. Most population and reproductive health policies and strategies in the country such as the National Population Policy for Sustainable Development, Family Planning Blue Print and 2017 National Reproductive Health Policy [ 18 – 20 ] rarely pay attention to generating more demand for modern contraceptives among single mothers. This necessitates further investigation of the prevalence and associated factors of contraceptive use among single mothers in the country. Existing studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents and young people [ 21 – 23 ], never married women [ 24 – 26 ], women of advanced reproductive age [ 27 – 30 ]. Other studies have focused the general population of childbearing women [ 31 – 34 ]. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers [ 35 – 36 , 15 , 37 ] but the associated factors of modern contraceptive uptake are largely ignored in the studies. The objective of this study was thus to examine the factors influencing modern contraceptive utilisation among single mothers in Nigeria. This is important because single mothers like other groups of women are likely to experience unintended pregnancies, sexually transmitted diseases and unsafe abortion if they do not use modern contraceptives or if they use it inconsistently. In addition, the rising profile of single motherhood across the world [ 6 – 10 ] requires that more attention be paid to the determinants of modern contraceptive use among single mothers. Findings from the study may provide inputs for strengthening existing population policy and reproductive health strategies in the aspects of scaling up modern contraceptive demand and use among important segments of women in the society. The study was guided by the research question: what influences modern contraceptive utilisation among single mothers in Nigeria? Methods Data Data were extracted from four consecutive Nigeria Demographic and Health Surveys (NDHSs) which were implemented between 2003 and 2018. The NDHS is a subset of Demographic and Health Survey (DHS) programme executed nationally in more than 90 countries with more than 300 surveys successfully conducted so far [ 38 ]. The quality of data emanating from the DHS Programme has been widely adjudged to be credible and of high quality [ 39 – 41 ]. The National Population Commission (NPC) is responsible for implementing the DHS programme in Nigeria while the financial and technical aspects are supported by ICF International through major international development partners [ 42 ]. The DHS programme seeks to make available reliable and accurate information on countries’ demographic and health characteristics, which are mostly used by policymakers to assist countries to monitor improvement in health and family planning programme [ 42 ]. The NDHS as part of the DHS programmes provide reliable national information on fertility, nutrition, marriage, family planning, mortality, HIV/AIDS, female genital mutilation and anthropometrics information in all the six geo-political zones and the 36 states of Nigeria including the Federal Capital Territory [ 42 ]. The sampling procedures in the four rounds of the NDHS were based on the same methodology that employed a multi-stage sampling process. The 36 administrative units of the country and the Federal Capital Territory were stratified into urban and rural areas from which some urban and rural areas were randomly selected. In the selected urban and rural areas, localities used as Enumeration Areas (EAs) in the population census were randomly selected and used as the primary sampling unit (cluster). In the selected clusters, households were listed and selected randomly for the surveys. Eligible men and women were then randomly selected in the households but different numbers of men and women were covered in each round of the surveys. Further details of the survey methodology of the NDHSs have been published elsewhere [ 43 – 45 ] In all the four rounds of the NDHS covered in the study, the numbers of single mothers were pooled for analysis. The inclusion criteria were being sexually active, never married, separated or divorced with at least one living child. The resulting sample size was thus a weighted sample of 7,215 women. Data Pooling Based on the inclusion criteria, the sample size of single mothers was relatively small across the four datasets. As a result, the four consecutive NDHS (2003–2018) were pooled in order to increase the observational cases, statistical power and representativeness of the results [ 46 ]. This pooled data could increase the ability of weak but scientifically important variables to predict the response variable [ 47 ]. This method has been extensively used by researchers to investigate rare issues affecting sub-grouped of population which might be practically difficult in individual data or studies [ 48 – 51 ]. The demerit attached to this approach is the difference in the sample size of each dataset which was technically addressed by applying the weighting factors with unique primary sampling unit [ 52 – 53 ]. Also, the fear of heterogeneity of the datasets and possibility of yielding spurious results were eliminated by the similarities of the datasets in terms of variable measurement, context, characteristics of respondents, sampling design, procedures and implementation and objectives [ 54 – 55 ]. Research Variables The outcome variable was current modern contraceptive utilisation with two possible responses of yes or no. Single mothers who currently use any modern contraceptive were grouped as ‘yes’ and coded ‘1’ while those who are not currently using a modern method were grouped as ‘no’ and coded ‘0’. The explanatory variables are sets of selected socio-economic and demographic characteristics. The socio-economic characteristics are maternal education (none, primary, secondary and higher), household wealth quintile (poorest, poorer, middle, richer and richest), religious affiliation (Christianity, Islam and tradition/others), employment status (employed or unemployed), place of residence (urban or rural), geographic region (northern or southern) and exposure to mass media (low, moderate and high). The three geo-political zones in the southern parts of the country, namely, southeast, south-south and southwest zones are combined as southern region while the zones in the northern parts of the country, namely, northcentral, northeast and northwest zones are combined as the northern region. Exposure to mass media was generated from three variables, namely, frequency of reading newspaper, listening to radio and watching television. Single mothers who do not access these outlets or accessed the outlets less than once a week were grouped as low exposure. Those who accessed the outlets at least once a week were grouped as moderate exposure. Other single mothers who accessed the outlets almost every day were grouped as high exposure. The demographic characteristics are age group (15–24, 25–34 and 35–49 years), age at sexual debut (less than 18 years or 18 or older), parity (one child, two-four children, and five or more children) fertility desire (wanted more children or wanted no more), and child living arrangement (lives with mother or lives elsewhere). These variables are selected based on their significance in previous studies [ 33 – 34 , 56 – 60 ]. The control variables are nature of singlehood (premarital or post marital singlehood), sexual activity (active or inactive) and most recent sexual partner (boy/man friend, commercial worker and casual friends). Data Analysis Data analysis was carried out using Stata version 14 [ 61 ]. Univariate analysis was carried out to assess the prevalence and use of modern contraceptives and to describe the sample characteristics. At the bivariate level, the relationship between each of the explanatory variables and the outcome variable was examined using the Unadjusted Odds Ratio (UOR) of binary logistic regression. Any variable that reveal no statistical significance at p < 0.025 was excluded from further analysis. The multivariable logistic regression analysis was used to examine the factors influencing the outcome variable using the Adjusted Odds Ratio (AOR) with 95% confidence interval. Statistical significance was set at p < 0.05. Results Descriptive Results Table 1 presents the socio-demographic characteristics of the respondents. More than one-fifth (23.5%) of the single mothers had no education while more than a quarter (27.2%) attained primary education. Slightly more than two-fifths (41.0%) of the single mothers attained secondary education while less than one-tenth (8.3%) of them attained higher education. The distribution of single mothers by household wealth quartile shows that single mothers who were in the middle (26.3%) and richer (25.9) wealth categories constituted more than half of the distribution. Single mothers who are in the poorest (11.0%) and poorer (18.1%) wealth categories were less than a quarter of the distribution while 18.7% of the single mothers were in the richest household wealth category. Majority of the single mothers were Christian (71.2%). The majority of the respondents (79.9%) were employed. Most of the single mothers resided in rural areas (53.2%) compared to those who resided in urban areas (46.8%). The result shows that there were more single mothers in the southern region (62.0%) than in the northern region of the country (38.0%). The majority of the respondents (62.7%) had moderate exposure to mass media but slightly more than a quarter of the women (27.1%) had low exposure to mass media. Half of the respondents (50.7%) were aged 35-49 years. Nearly half of the respondents had their first sex before age 18. More than one third (33.8%) of the respondents had at least a child while 41.7% had two-four children. Nearly half of the respondents wanted more children (48.0%) while majority of the respondents (71.8%) had at least a child living with them. Most of the respondents (72%) were post marital single mothers while 28% were premarital single mothers. Though, all the single mothers included were sexually active but 17.9% were sexually active in the last one month preceding the survey. Slightly more than half of the respondents (54.2%) had casual friends as their most recent sexual partner. The prevalence of modern contraceptive use among the single mothers was 11.7%. Bivariate Results Table 2 present the cross tabulation and multivariable results. Education and modern contraceptive use are significantly positively related. As education improves, the prevalence of modern contraceptive use increased consistently. For example while single mothers who attained primary education had 9.9% prevalence of contraceptive use, single mothers who attained higher education had 16.4% prevalence of modern contraceptive use. Similarly, household wealth quartile was positively associated with modern contraceptive use. For instance, prevalence of contraceptive use was 10.5% among single mothers in middle wealth group compared to 17.6% among single mothers in richest wealth group. Religion and modern contraceptive use revealed significant association with lower odds of contraceptive use among Muslim single mothers compared to Christians single mothers (UOR=0.307, p<0.01; 95% CI: 0.224–0.421). Employment status and modern contraceptive use are significantly positively related with higher use of modern contraceptive among employed single mothers compared to the unemployed (12.6% vs. 8.6%). Place of residence and modern contraceptive use are negatively related with lower odds of modern contraceptive use among single mothers who resided in rural areas (UOR=0.776, p<0.05; 95% CI: 0.639–0.943). The prevalence of modern contraceptive use was 7.6% among northern single mothers compared to 14.3% prevalence among southern single mothers indicating a significant positive relationship between geographic region and modern contraceptive use. Exposure to mass media and modern contraceptive use reveal significant positive relationship. The odds of modern contraceptive use are higher among single mothers who had moderate exposure to mass media (UOR=2.422, p<0.01; 95% CI: 1.927-3.044) and among single mothers who had high exposure to mass media (UOR=2.820, p<0.01; 95% CI: 2.040–3.899). The relationship between age group and modern contraceptive use had a mixed relationship with modern contraceptive use. The relationship was positive at lower age group but negative at the upper age group. For instance, while single mothers aged 25-35 had higher odds of modern contraceptive use (UOR=1.542, p<0.01; 95% CI: 1.232-1.931), single mothers aged 35-49 had lower odds of modern contraceptive use (UOR=2.820, p<0.01; 95% CI: 2.040–3.899). Age at sexual debut and modern contraceptive use reveals significant negative association. The prevalence of modern contraceptive use was 13.6% among single mothers who had first sex before reaching age 18 compared to 10.1% among single mothers who had first sex at age 18 or older ages. Parity and modern contraceptive use are negatively associated. As parity increases prevalence of modern contraceptive use tends to reduce. Likewise, fertility desire and modern contraceptive use are negatively related with lower odds of modern contraceptive use among single mothers who not desire additional children (UOR=0.558, p<0.01; 95% CI: 0.468–0.665). The relationship between child living arrangement and modern contraceptive use was significantly positive with higher odds of modern contraceptive use among single mothers whose children live elsewhere (UOR=1.280, p<0.01; 95% CI: 1.065–1.537). Multivariate Results The multivariate result (Table 2) shows that more socioeconomic characteristics of single mothers had significant effect on modern contraceptive use compared to the demographic characteristics that reveals statistical significance. As education improved, the likelihood of modern contraceptive use increased consistently. For instance single mothers who attained secondary education were more than twice more likely to use modern contraceptives compared to uneducated single mothers (AOR=2.254, p<0.01; 95% CI: 1.431–3.551). With the exclusion of poorer wealth category, the odds of modern contraceptive use increased consistently as household wealth improved. For instance single mothers in richest wealth category were more than twice more likely to use modern contraceptives compared to single mothers in poorest wealth category (AOR=2.374, p<0.01; 95% CI: 1.446–3.897). Muslim single mothers were 47.3% less likely to use modern contraceptive compared to Christian single mothers (AOR= 0.527, p<0.05; 95% CI: 0.366–0.759). Employed single mothers were 44.9% more likely to use modern contraceptives compared to unemployed single mothers (AOR=1.449, p<0.05; 95% CI: 1.123–1.867). Exposure to mass media had positive effect on modern contraceptive use. While single mothers who had moderate exposure to mass media were 45.5% (AOR=1.455, p<0.05 ; 95% CI: 1.049–1.807) more likely to use modern contraceptives, single mother who had high exposure to mass media were 44.2% (AOR=1.442, p<0.05; 95% CI: 0.690–1.394) more likely to use modern contraceptive compared to single mothers who had low exposure. Single mothers in the 25-34 age group were 37.7% more likely to use contraceptive compared to younger single mothers (AOR=1.377, p<0.05; 95% CI: 1.049–1.807). Two of the control variables reveal significant effect on the odds of modern contraceptive use. Single mothers who are recently sexually inactive and single mothers whose most recent sexual partners were causal friends had lower odds of modern contraceptive use. Discussion This study investigated the factors influencing modern contraceptive utilisation among single mothers. The study differs from existing studies that focused on other segments of childbearing women such as adolescents [21-23], never married women [24-26] and women of advanced reproductive age [27-30] by focusing on single mothers. This group of women has received little attention in family planning programming in Nigeria. The study therefore attempts to bring to the fore of family planning programming in Nigeria, the case of single mothers. Single mothers in many parts of the country are victims of discrimination, rejection and blackmail in the community [11-13]. Their children also face higher risks of adverse health outcomes in the community [14-17]. This peculiar condition of single mothers may create more demand for modern contraceptive use to avoid repeated pregnancy that may aggravate the extent of the stigmas experience in the community. Two key findings emerged from the study. Firstly, the study reveals 11.7% prevalence of modern contraceptive use among single mothers in Nigeria. This level of utilisation is rather low and further underscores poor contraceptive prevalence rate already observed in previous studies in the country [22, 24-25, 27, 29, 32]. It also point to the need to reposition the existing Family Planning Blue Print in Nigeria [19] through increasing the tempo of family planning demand generation among special groups of women such as single mothers. The Family Planning Blue Print already noted that the economic and health benefits of spacing pregnancies or limiting child birth is not well appreciated by families and providers which resulted into low contraceptive use in the country. This challenge may be addressed by two measures. One, it is important to recognise that single motherhood not only represents an unconventional family structure in the community but is also increasing in the community [6]. The peculiar contraceptive need of this group of women may thus be different from the needs of other women. This has made the development of a special strategy targeting single mothers in Nigerian communities imperative. Two, family planning service delivery points in the community such as community health extension workers (CHEWs) and proprietary patent medicine vendors (PPMVs) should be trained to maintain contacts with single mothers patronising them for various health needs in the community. This will afford the providers the unique opportunity of providing needy single mothers with more contraceptive information, counselling and services particularly those relating to long term methods such as injectables and long-acting reversible contraceptives (LARCs). Secondly, the socio-demographic characteristics of single mothers such as education, household wealth, religion, employment and mass media exposure are key drivers of modern contraceptive utilisation. As evident in the study, modern contraceptive use increased with improvement in educational level of single mothers. This finding is not only consistent with in existing studies [29-30] but also suggests that the role of educational attainment in boosting contraceptive use may not differ among single mothers and other groups of women in the country. Thus, it is important that population and health policies and programmes in the country continue to seek means of expanding women’s access to improve educational opportunities. However, public health education programme should be designed for uneducated single mothers to ensure they are not disadvantaged. Such programme could be spread using the mass media outlets since most single mothers either had moderate or high access to the mass media, and should target younger single mothers who are found to have higher odds of contraceptive use in the study. The programme should also stress the dangers of unprotected intercourse with casual friends since this not only elevates the risk of unintended pregnancy but also elevate the risk of infection with sexually transmitted diseases. This aspect is important because the study observed that more than half of the single mothers had sexual contacts with casual friends. Also, the study reveal that modern contraceptive use increase with improvements in single mothers’ household wealth quintile and employment in agreement with finding in previous studies [56-60] which provides support for the women empowerment strategies of the current national population policy [18]. It is expected that as women’s economic power improves, their say in household decision-making may improve and more women may be able to access methods that are not covered by the free user fee initiative in public health facilities in the country. Strength and Limitations This study provided information on the drivers of modern contraceptive use which has been largely ignored in several existing studies. The precision of the inferences made in the study is greatly enhanced by the use of the NDHS data which is not only potentially verifiable but is also based on internationally credible methodology. However, the study has some limitations. One, the usage of the term ‘factors influencing’ modern contraceptive use in the study do not necessarily mean the ‘cause’ of modern contraceptive use. The use is intended to connote the ‘associated factors’ of modern contraceptive use since the study was based on a cross-sectional data. Two, the associated factors examined in the study are selected among several other associated factors identified in previous studies. Other studies may examine other sets of variables that may change the pattern of result in the current study. Three, the responses analysed in the study are self-reported. It is not impossible that some of the responses may not reflect the true situation of single mothers covered in the study. We however, believed that the sound methodology of the DHS programme has greatly reduced respondents’ bias during data collection. Conclusion This study examined factors influencing modern contraceptive utilisation among single mothers in Nigeria. Data was pooled from four consecutive rounds of the NDHS due to small proportion of single mothers in each round of the NDHS. The study revealed low prevalence of modern contraceptive use among the studied women. The key drivers of modern contraceptive use among single mothers are education, household wealth, media exposure, religion, age and employment. Additional family planning strategy targeting single mothers in the country should be designed for implementation in the country. Abbreviations NDHS Nigeria Demographic and Health Survey DHS Demographic and Health Survey USAID United States Agency for International Development NPC National Population Commission FMoH Federal Ministry of Health Declarations Ethical approval In line with the DHS programme, each round of the NDHS was first approved in the United States by the International Review Board of ICF International and also approved in Nigeria by the National Health Research Ethics Committee (NHREC). Participants in the surveys provided verbal consent as a condition for commencement of interview. The datasets were formally requested and authorised. The datasets are available via https://dhsprogram.com/data/ . Ethics approval and consent to participate Each round of the NDHS was first approved in the United States by the International Review Board of ICF International and in Nigeria by the National Health Research Ethics Committee (NHREC). All participants gave verbal consent to participate in the study. Consent to publish Not Applicable Availability of data and materials The analysed datasets are available via https://dhsprogram.com/data/ . Competing Interests The authors declare no competing interests. Funding Not Applicable Authors’ contributions BBI developed the concept which was modified by BLS. All authors took part in literature review, data analysis and discussion of findings. All authors read through and approved the submitted version of the manuscript. Acknowledgements The authors are grateful to MEASURE DHS and the National Population Commission (Nigeria) authorising access to 2003-2018 NDHS datasets. Authors’ Information BBI is a doctoral student in the Department of Demography and Social Statistics, Obafemi Awolowo University, Ile-Ife, Nigeria. BLS is a Senior Lecturer in the Department. MBM is a Lecturer 1 in the Department of Sociology, Ahmadu Bello University, Zaria, Nigeria. References Sarvestani KA, Khoo SL, Malek NM, Yasin M, Ahmadi A. Determinants of Contraceptive Usage among Married Women in Shiraz, Iran. Journal of Midwifery Reproductive Health. 2017;5(4):1041–52. doi: 10.22038/JMRH.2017.8771 . Cleland J, Bernstein S, Ezeh A, Faundes A, Glasier A, Innis J. Family planning: the unfinished agenda. Lancet. 2006;368:1810–27. doi: 10.1016/S0140-6736(06)69480-4 . Bongaarts J, Sinding SW. Family Planning as an Economic Investment. SAIS Review. 2011;XXXI(2):35–44. Bongaarts J, Cleland J, Townsend JW, Bertrand JT, Gupta MD. Family Planning Programs for the 21st Century: Rationale and Design. New York: Population Council; 2011. Goodkind D, Choi LLY, McDevitt T, West L. The demographic impact and development benefits of meeting demand for family planning with modern contraceptive methods. Global Health Action. 2018;11(1):1423861. doi: 10.1080/16549716.2018.1423861 . Ntoimo LFC, Isiugo-Abanihe U. Patriarchy and Singlehood among Women in Lagos, Nigeria. J Fam Issues. 2013;35(14):1980–2008. doi: 10.1177/0192513X13511249 . Oshi DC, Mckenzie J, Baxter M, Robinson R, Neil S, Greene T, et al. Association between single-parent family structure and age of sexual debut among young persons in Jamaica. J Biosoc Sci. 2018. doi: 10.1017/s0021932018000044 . Steinbach A, Kuhnt AN, Knull M. The prevalence of single-parent families and stepfamilies in Europe: can the Hajnal line help us to describe regional patterns? The History of the Family. 2016;21(4):578–95. doi: 10.1080/1081602X.2016.1224730 . Mikkonen HM, Salonen MK, Hakkinen A, Olkkola M, Pesonen A, Raikkonen K, et al. The lifelong socioeconomic disadvantage of single-mother background - the Helsinki Birth Cohort study 1934–1944. BMC Public Health. 2016;16:817. doi: 10.1186/s12889-016-3485-z . Lu Y, Walker R, Richard P, Younis M. Inequalities in Poverty and Income between Single Mothers and Fathers. Int J Environ Res Public Health. 2020;17:135. doi: 10.3390/ijerph17010135 . Amroussia N, Hernandez A, Vives-Cases C, Goicolea I. “Is the doctor God to punish me?!” An intersectional examination of disrespectful and abusive care during childbirth against single mothers in Tunisia. Reprod Health. 2017;14:32. doi: 10.1186/s12978-017-0290-9 . Anyebe EE, Lawal H, Dodo R, Adeniyi BR. Community Perception of Single Parenting in Zaria, Northern Nigeria. J Nurs Care. 2017;6(4):411. doi: 10.4172/2167-1168.1000411 . Essien AM, Bassey AA. The socio and religious challenges of single mothers in Nigeria. American Journal of Social Issues Humanities. 2012;2(4):240–51. Newlin M. Public Perceptions Towards Children Brought Up by Single Mothers: A Case of Queenstown, South Africa. Journal of Human Ecology. 2017;58(3):169–80. doi: 10.1080/09709274.2017.1324695 . Ntoimo LFC, Odimegwu CO. Health effects of single motherhood on children in sub-Saharan Africa: a cross-sectional study. BMC Public Health. 2014;14:1145. https://doi.org/10.1186/1471-2458-14-1145 . Scharte M, Bolte G, et al. Increased health risks of children with single mothers: the impact of socio-economic and environmental factors. Eur J Pub Health. 2012;23(3):469–75. doi: 10.1093/eurpub/cks062 . Richter D, Lemola S. Growing up with a single mother and life satisfaction in adulthood: A test of mediating and moderating factors. PLoS ONE. 2017;12(6):e0179639. https://doi.org/10.1371/journal.pone.0179639 . Natioanl Population Commission. National Policy on Population for Sustainable Development. Abuja: NPC; 2004. Federal Ministry of Health. Natioanl Family Planning Blue Print. Abuja: FMoH; 2014. Federal Ministry of Health. 2017 National Reproductive Health Policy, Abuja Nigeria; FMoH;2017. Casey SE, Gallagher MC, Kakesa J, Kalyanpur A, Muselemu JB, Rafanoharana RV, Spilotros N. Contraceptive use among adolescents and young women in North and South Kivu, Democratic Republic of the Congo: A cross sectional population-based survey. Plos Medicine. 2020;17(3):e1003086. https://doi.org/10.1371/journal.pmed.1003086 . Abiodun OM, Balogun OR. Sexual activity and contraceptive use among young female students of tertiary educational institutions in Ilorin, Nigeria. Contraception. 2009;79:146–9. doi: 10.1016/j.contraception.2008.08.002 . Ahinkorah BO, Hagan JE Jr, Seidu A-A, Sambah F, Adoboi F, Schack T, et al. Female adolescents’ reproductive health decision-making capacity and contraceptive use in sub- Saharan Africa: What does the future hold? PLoS ONE. 2020;15(7):e0235601. https://doi.org/10.1371/journal.pone.0235601 . Ahmed ZD, Sule IB, Abolaji ML, Mohammed Y, Nguku P. Knowledge and utilization of contraceptive devices among unmarried undergraduate students of a tertiary institution in Kano State, Nigeria 2016. Pan African Medical Journal. 2017;26:103. doi: 10.11604/pamj.2017.26.103.11436 . Ajayi AI, Nwokocha EE, Adeniyi OV, Goon DT, Akpan W. Unplanned pregnancy-risks and use of emergency contraception: a survey of two Nigerian Universities. BMC Health Services Research. 2017;17:382. doi: 10.1186/s12913-017-2328-7 . Cohen N, Mendy FT, Wesson J, Protti A, Cissé C, Gueye EB, et al. Behavioral barriers to the use of modern methods of contraception among unmarried youth and adolescents in eastern Senegal: a qualitative study. BMC Public Health. 2020;20:1025. https://doi.org/10.1186/s12889-020-09131-4 . Olaolorun FM, Hindin MJ. Having a say matters: Infleunce of Decision-making Power on Contracpetive Use among Nigeria Women ages 35–49 years. Plos One. 2014;9(6):e98702. doi: 10.1371/journal.pone.0098702 . Tepper NK, Godfrey EM, Folger SG, Whiteman MK, Marchbanks PA, Curtis KM. Hormonal contraceptive use among women of older reproductive age: considering risks and benefits. Journal of Women’s Health. 2018. doi: 10.1089/jwh.2018.6985 . Solanke BL. Factors influencing contraceptive use and non-use among women of advanced reproductive age in Nigeria. J Health Popul Nutr. 2017;36(1):1–14. https://doi.org/10.1186/s41043-016-0077-6 . Ama NO, Olaomi JO. Family planning desires of older adults (50 years and over) in Bostwana. South African Family Practice. 2018;61(1):30–8. doi: 10.1080/20786190.2018.1531584 . Abdulahi M, Kakaire O, Namusoke F. Determinants of modern contraceptive use among married Somali women living in Kampala; a cross sectional survey. Reproductive Health. 2020;17:72. https://doi.org/10.1186/s12978-020-00922-x . Austin A. Unmet contraceptive need among married Nigerian women: an examination of trends and drivers. Contraception. 2015;91:31–8. http://dx.doi.org/10.1016/j.contraception.2014.10.002 . Ogboghodo EO, Adam VY, Wagbatsoma VA. Prevalence and determinants of contraceptive use among women of child-bearing age in a rural community in Southern Nigeria. Journal of Community Medicine Primary Health Care. 2017;29(2):97–107. Komasawa M, Yuasa M, Shirayama Y, Sato M, Komasawa Y, Alouri M. Demand for family planning satisfied with modern methods and its associated factors among married women of reproductive age in rural Jordan: A cross-sectional study. Plos One. 2020;15(3):e0230421. https://doi.org/10.1371/journal.pone.0230421 . Agnafors S, Bladh M, Svedin CG, Sydsjo G. Mental health in young mothers, single mothers and their children. BMC Psychiatry. 2019;19:112. https://doi.org/10.1186/s12888-019-2082-y . Dronkers J, Veerman GM, Pong S. Mechanisms Behind the Negative Influence of Single Parenthood on School Performance: Lower Teaching and Learning Conditions? Journal of Divorce Remarriage. 2017;58(7):471–86. doi: 10.1080/10502556.2017.1343558 . Mainthia R, Reppart L, Reppart J, Pearce EC, Cohen JJ, Netterville JL. (2013). A Model for Improving the Health and Quality of Life of Single Mothers in the Developing World. Afr J Reprod Health. 2013;17(4):14–25. United States Agency for International Development. (2018). The DHS Program and Health Surveys. USA: USAID. Retrieved from https://data2.unhcr.org/en/documents/download/64979 . A systematic review of Demographic and Health Surveys: data availability and utilization for research 10.2471/BLT.11.095513 Fabic MS, Choia YJ, Bird S. A systematic review of Demographic and Health Surveys: data availability and utilization for research. Bulletin of World Health Organisation. 2012;90:604–12, doi: 10.2471/BLT.11.095513 . Corsi DJ, Neuman M, Finlay JE, Subramanian SV. Demographic and health surveys: a profile. Int J Epidemiol. 2012;41:1602–13. AI Zalak Z, Goujon A. Assessment of the data quality in Demographic and Health Surveys in Egypt, Vienna Institute of Demography Working Papers, No. 06;2017, Austrian Academy of Sciences (OAW), Vienna Institute of Demography (VID), Vienna. Available at. http://hdl.handle.net/10419/175538 . National Population Commission, ICF. Nigeria Demographic and Health Survey 2018. Abuja, Nigeria and Rockville, Maryland, USA: NPC &ICF;2019. National Population Commission, ORC Macro. Nigeria Demographic and Health Survey 2003. Maryland: Calverton; 2004. NPC & ORC Macro. National Population Commission, ICF Macro. Nigeria Demographic and Health Survey 2008. Abuja: NPC & ICF Macro; 2009. National Population Commission, ICF International. Nigeria Demographic and Health Survey 2013. Nigeria: Abuja; 2014. NPC & ICF International. Lewis T. Estimation Strategies Involving Pooled Survey Data, 1–15. Retrieved from https://support.sas.com/resources/papers/proceedings17/0767-2017.pdf ;2017. Henry H, Singh V, Johnson SC, Wahba G. Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Proc Natl Acad Sci USA. 2018;115(7):1481–6. doi: 10.1073/pnas.1719747115 . Ezeh OK, Agho KE, Dibley MJ, Hall JJ, Page AN. Risk factors for postneonatal, infant, child and under-5 mortality in Nigeria: a pooled cross-sectional analysis. BMJ Open. 2015;5:e006779. doi: 10.1136/bmjopen-2014-006779 . Solanke BL. Individual and community factors associated with indications of caesarean delivery in Southern Nigeria: Pooled analyses of 2003–2013 Nigeria demographic and health surveys. Health Care Women Int. 2018;39(6):697–716. doi: 10.1080/07399332.2018.1443107 . Yaya S, Amouzou A, Uthman OA, Ekholuenetale M, Bishwajit G, Ogochukwu U, et al. Prevalence and determinants of terminated and unintended pregnancies among married women: analysis of pooled cross-sectional surveys in Nigeria. BMJ Glob Health. 2018;3:e000707. doi: 10.1136/bmjgh-2018-000707 . Dahiru T. First-day and Early Neonatal Mortality in Nigeria: A Pooled Cross-sectional Analysis of Nigeria DHS Data. British Journal of Medicine Medical Research. 2017;19(9):1–12. doi: 10.9734/BJMMR/2017/28247 . van der Steen JT, Kruse RL, Szafara KL, et al. Benefits and pitfalls of pooling datasets from comparable observational studies: combining US and Dutch nursing home studies. Palliat Med. 2008;22(6):750–9. doi: 10.1177/0269216308094102 . Bhalotra S. Sibling-Linked Data in the Demographic and Health Surveys. Economic Political Weekly. 2008;43(48):39–43. Bangdiwala SI, Bhargava A, Connor DPO, Robinson TN, Michie S, Murray DM, Pratt CA. Statistical methodologies to pool across multiple intervention studies. Transl Behav Med. 2016;6(2):228–35. doi: 10.1007/s13142-016-0386-8 . Appropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data https://doi.org/10.1186/s12199-018-0737-9 Geremew A, Mengistie B, Mellor J, Lantagne DS, Alemayehu E, Sahilu G. Appropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data. Environ Health Prev Med. 2018; 23:46, https://doi.org/10.1186/s12199-018-0737-9 . Lasong J, Zhang Y, Gebremedhin SA, Opoku S, Abaidoo CS, Mkandawire T, et al. Determinants of modern contraceptive use among married women of sectional study reproductive age: a cross in rural Zambia. BMJ Open. 2020;10:e030980. https://doi.org/10.1136/bmjopen-2019-030980 . Yaya AA, Caroline G, Abderahim MN. Use of Female Contraception Mixed and Multicentric Study in Chad. Am J Public Health. 2020;8(1):22–7. https://doi.org/10.12691/ajphr-8-1-4 . Oladosun M, Akanbi M, Fasina F, Samuel O. Key predictors of modern contraceptive use among women in marital relationship in South-west region of Nigeria. International Journal of Reproduction Contraception Obstetrics Gynecology. 2019;8(7):2638–46. http://dx.doi.org/10.18203/2320-1770.ijrcog20193018 . Medhanyie AB, Desta A, Alemayehu M, Gebrehiwot T, Abraha TA, Abrha A, et al. Factors associated with contraceptive use in Tigray, North Ethiopia. Reprod Health. 2017;14:27. doi: 10.1186/s12978-017-0281-x . Achana FS, Bawah AA, Jackson EF, Welaga P, Awine T, Asuo-Mante E, et al. Spatial and socio-demographic determinants of contraceptive use in the Upper East region of Ghana. Reproductive Health. 2015;12:29. doi: 10.1186/s12978-015-0017-8 . StatCorp. Stata. Release 14. Statistical Software. College Station: StataCorp LP; 2015. Tables Table 1 Percentage distribution of respondents by socio-economic and demographic characteristics Characteristic Frequency (n = 7,215) Percentage (%) Characteristic Frequency (n = 7215) Percentage (%) Education Age at sexual debut None 1,697 23.5 Less than 18 years 3,393 47.0 Primary 1,965 27.2 18 years or older 3,822 53.0 Secondary 2,954 41.0 Parity Higher 599 8.3 1 child 2,441 33.8 Household wealth quintile 2–4 children 3,006 41.7 Poorest 796 11.0 5 or more children 1,768 24.5 Poorer 1,303 18.1 Desire for more children Middle 1,895 26.3 Wanted more 3,467 48.0 Richer 1,872 25.9 Wanted no more 3,748 52.0 Richest 1,349 18.7 Child living arrangement Religion Lives with mother 5,183 71.8 Christianity 5,139 71.2 Lives elsewhere 2,031 28.2 Islam 1,820 25.2 Nature of singlehood Traditional 256 3.6 Premarital 2,017 28.0 Employment status Post marital 5,198 72.0 Unemployed 1,452 20.1 Sexual activity Employed 5,763 79.9 Active 1,290 17.9 Place of residence Inactive 5,925 82.1 Urban 3,374 46.8 Most recent sexual partner Rural 3,841 53.2 Boy/Man friend 2,987 41.4 Geographic region Commercial sex worker 318 4.4 Northern 2,743 38.0 Casual friends 3,909 54.2 Southern 4,472 62.0 Modern contraceptive use Age group Not using 6,369 88.3 15–24 years 1,555 21.6 Using 846 11.7 25–34 years 2,001 27.7 35–49 years 3,659 50.7 Exposure to mass media Low exposure 1,956 27.1 Moderate exposure 4,520 62.7 High exposure 739 10.2 Table 2 Cross tabulation and multivariable results Characteristic predicting modern contraceptive use Prevalence (%) Unadjusted Model Adjusted Model UOR p-value 95% CI AOR p-value 95% CI Education None ref 3.5 1.00 - - 1.00 - - Primary 9.9 3.034** p < 0.01 2.184–4.216 1.690** p < 0.01 1.165–2.451 Secondary 16.8 5.576** p < 0.01 4.128–7.556 2.146** p < 0.01 1.524–3.072 Higher 16.4 5.440** p < 0.01 3.681–8.041 2.254** p < 0.05 1.431–3.551 Household wealth quintile Poorest ref 4.9 1.00 - - 1.00 - - Poorer 8.0 1.684** p < 0.01 1.139–2.487 1.494 0.0606 0.973–2.293 Middle 10.5 2.251** p < 0.01 1.515–3.356 1.734* p < 0.05 1.121–2.683 Richer 14.2 3.191** p < 0.01 2.160–4.715 2.122** p < 0.05 1.362–3.307 Richest 17.6 4.126** p < 0.01 2.761–6.176 2.374** p < 0.01 1.446–3.897 Religion Christianity ref 14.4 1.00 - - 1.00 - - Islam 4.9 0.307** p < 0.01 0.224–0.421 0.527** p < 0.05 0.366–0.759 Traditional 7.0 0.450* p < 0.05 0.259–0.780 0.600 0.079 0.339–1.061 Employment status Unemployed ref 8.6 1.00 - - 1.00 - - Employed 12.6 1.530** p < 0.01 1.219–1.919 1.449** p < 0.05 1.123–1.867 Place of residence Urban ref 13.1 1.00 - - 1.00 - - Rural 10.5 0.776* p < 0.05 0.639–0.943 0.957 0.691 0.768–1.191 Geographic region Northern ref 7.6 1.00 - - 1.00 - - Southern 14.3 2.020** p < 0.01 1.614–2.529 0.887 0.367 0.684–1.151 Exposure to mass media Low exposure ref 6.1 1.00 - - 1.00 - - Moderate exposure 13.6 2.422** p < 0.01 1.927–3.044 1.455* p < 0.05 1.049–1.807 High exposure 15.5 2.820** p < 0.01 2.040–3.899 1.442* p < 0.05 0.690–1.394 Age group 15–24 years ref 12.2 1.00 - - 1.00 - - 25–34 years 17.6 1.542 p < 0.01 1.232–1.931 1.377* p < 0.05 1.049–1.807 35–49 years 8.3 0.652 p < 0.01 0.516–0.824 0.981 0.915 0.691–1.394 Age at sexual debut Less than 18 years ref 13.6 1.00 - - 1.00 - - 18 years or older 10.1 0.711** p < 0.01 0.600-0.842 0.871 0.165 0.716–1.058 Parity 1 child ref 15.8 1.00 - - 1.00 - - 2–4 children 11.4 0.641** p < 0.01 0.535–0.768 0.903 0.433 0.702–1.164 5 or more children 8.3 0.453** p < 0.01 0.357–0.576 1.084 0.649 0.764–1.537 Desire for more children Wanted more ref 14.8 1.00 - - 1.00 - - Wanted no more 8.9 0.558** p < 0.01 0.468–0.665 1.189 0.134 0.960–1.489 Child living arrangement Lives with mother ref 10.9 1.00 - - 1.00 - - Lives elsewhere 13.6 1.280** p < 0.01 1.065–1.537 1.189 0.112 0.960–1.471 Nature of singlehood Premarital 1.00 - - Post marital 0.930 0.582 0.717–1.205 Sexual activity Active ref 1.00 - - Inactive 0.406** p < 0.01 0.327–0.505 Most recent sexual partner Boy/Man friend ref 1.00 - - Commercial sex worker 0.868 0.562 0.538-1.400 Casual friends 0.154** p < 0.01 0.047–0.162 Notes: ref (reference category), *p < 0.05, **p < 0.01 Cite Share Download PDF Status: Under Revision Version 1 posted Review # 3 received at journal 14 Nov, 2020 Editorial decision: Major revision 14 Nov, 2020 Reviewer # 5 agreed at journal 23 Oct, 2020 Review # 2 received at journal 17 Aug, 2020 Reviewer # 4 agreed at journal 16 Aug, 2020 Reviewer # 3 agreed at journal 07 Aug, 2020 Review # 1 received at journal 07 Aug, 2020 Reviewer # 1 agreed at journal 02 Aug, 2020 Reviewer # 2 agreed at journal 02 Aug, 2020 Reviewers invited by journal 31 Jul, 2020 Editor assigned by journal 21 Jul, 2020 Editor invited by journal 20 Jul, 2020 Submission checks completed at journal 17 Jul, 2020 First submitted to journal 16 Jul, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Evidence from Pooled Cross-Sectional Surveys\u003c/p\u003e","fulltext":[{"header":"Plain English Summary","content":" \u003cp\u003eExisting studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents, never married and women of advanced reproductive age. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers but the associated factors of modern contraceptive uptake among them were largely ignored. This study therefore examines factors influencing modern contraceptive utilisation among single mothers in Nigeria. Data were extracted from four consecutive Nigeria Demographic and Health Surveys. The outcome variable was current modern contraceptive utilisation. The explanatory variables are sets of selected socio-economic and demographic characteristics such as education, household wealth index, employment status, age, parity and fertility desire. Findings reveal slightly more than one-tenth prevalence of current utilisation of modern contraceptives among single mothers. Improvements in educational attainment and household wealth quintile increases the likelihood of modern contraceptive use, Muslim single mothers were less likely to use modern contraceptives. Also, employed single mothers were more likely to use modern contraceptives. Findings further reveal that single mothers who had moderate exposure to the mass media, single mothers who had high exposure to the mass media and younger single mothers were more likely to use modern contraceptives. The study concluded that modern contraceptive utilisation is low among single mothers in Nigeria and recommended the development of a special strategy targeting single mothers in the country.\u003c/p\u003e "},{"header":"Background","content":" \u003cp\u003eModern contraceptives are health information, counselling, services and devices used for spacing or limiting pregnancies, preventing unintended pregnancies, and reducing incidences of sexually transmitted infections [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Evidence abounds that modern contraceptive use particularly in high fertility countries has the potential not only to reduce maternal deaths, hunger and poverty but also to improve women\u0026rsquo;s autonomy, access to education and enhanced socio-economic participation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, modern contraceptives are beneficial to all women and men of reproductive age irrespective of marital or social condition. This suggests that global and national initiatives to boost modern contraceptive use across the world should target all categories of women and men. But evidence indicate that single mothers (a woman who has a dependent child or dependent children but not currently married either by choice or involuntary) are rarely focused in family planning programming [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] in spite of sustained global efforts to meet worldwide demand for family planning with modern contraceptive methods.\u003c/p\u003e \u003cp\u003eThough, single motherhood is increasingly rising across the world [\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] as an evolving family type but in many developing countries including Nigeria, single motherhood is rarely accepted in the community. Many single mothers experience discrimination, rejection and blackmail from members of their community [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and children nurtured by single mothers are perceived to be poor trained in family values [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] in addition to having elevated risks of poor health outcomes [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These stigmas may encourage single mothers to desire avoiding or delaying another pregnancy which make them a key segment for contraceptive demand and use in the community. However, single mothers rarely feature in family planning programming in Nigeria. Most population and reproductive health policies and strategies in the country such as the National Population Policy for Sustainable Development, Family Planning Blue Print and 2017 National Reproductive Health Policy [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] rarely pay attention to generating more demand for modern contraceptives among single mothers. This necessitates further investigation of the prevalence and associated factors of contraceptive use among single mothers in the country.\u003c/p\u003e \u003cp\u003eExisting studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents and young people [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], never married women [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], women of advanced reproductive age [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Other studies have focused the general population of childbearing women [\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] but the associated factors of modern contraceptive uptake are largely ignored in the studies. The objective of this study was thus to examine the factors influencing modern contraceptive utilisation among single mothers in Nigeria. This is important because single mothers like other groups of women are likely to experience unintended pregnancies, sexually transmitted diseases and unsafe abortion if they do not use modern contraceptives or if they use it inconsistently. In addition, the rising profile of single motherhood across the world [\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] requires that more attention be paid to the determinants of modern contraceptive use among single mothers. Findings from the study may provide inputs for strengthening existing population policy and reproductive health strategies in the aspects of scaling up modern contraceptive demand and use among important segments of women in the society. The study was guided by the research question: what influences modern contraceptive utilisation among single mothers in Nigeria?\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData\u003c/h2\u003e \u003cp\u003eData were extracted from four consecutive Nigeria Demographic and Health Surveys (NDHSs) which were implemented between 2003 and 2018. The NDHS is a subset of Demographic and Health Survey (DHS) programme executed nationally in more than 90 countries with more than 300 surveys successfully conducted so far [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The quality of data emanating from the DHS Programme has been widely adjudged to be credible and of high quality [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The National Population Commission (NPC) is responsible for implementing the DHS programme in Nigeria while the financial and technical aspects are supported by ICF International through major international development partners [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The DHS programme seeks to make available reliable and accurate information on countries\u0026rsquo; demographic and health characteristics, which are mostly used by policymakers to assist countries to monitor improvement in health and family planning programme [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The NDHS as part of the DHS programmes provide reliable national information on fertility, nutrition, marriage, family planning, mortality, HIV/AIDS, female genital mutilation and anthropometrics information in all the six geo-political zones and the 36 states of Nigeria including the Federal Capital Territory [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe sampling procedures in the four rounds of the NDHS were based on the same methodology that employed a multi-stage sampling process. The 36 administrative units of the country and the Federal Capital Territory were stratified into urban and rural areas from which some urban and rural areas were randomly selected. In the selected urban and rural areas, localities used as Enumeration Areas (EAs) in the population census were randomly selected and used as the primary sampling unit (cluster). In the selected clusters, households were listed and selected randomly for the surveys. Eligible men and women were then randomly selected in the households but different numbers of men and women were covered in each round of the surveys. Further details of the survey methodology of the NDHSs have been published elsewhere [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] In all the four rounds of the NDHS covered in the study, the numbers of single mothers were pooled for analysis. The inclusion criteria were being sexually active, never married, separated or divorced with at least one living child. The resulting sample size was thus a weighted sample of 7,215 women.\u003c/p\u003e \u003c/div\u003e \n\u003ch2\u003eData Pooling\u003c/h2\u003e\n \u003cp\u003eBased on the inclusion criteria, the sample size of single mothers was relatively small across the four datasets. As a result, the four consecutive NDHS (2003\u0026ndash;2018) were pooled in order to increase the observational cases, statistical power and representativeness of the results [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This pooled data could increase the ability of weak but scientifically important variables to predict the response variable [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This method has been extensively used by researchers to investigate rare issues affecting sub-grouped of population which might be practically difficult in individual data or studies [\u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The demerit attached to this approach is the difference in the sample size of each dataset which was technically addressed by applying the weighting factors with unique primary sampling unit [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Also, the fear of heterogeneity of the datasets and possibility of yielding spurious results were eliminated by the similarities of the datasets in terms of variable measurement, context, characteristics of respondents, sampling design, procedures and implementation and objectives [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \n\u003ch2\u003eResearch Variables\u003c/h2\u003e\n \u003cp\u003eThe outcome variable was current modern contraceptive utilisation with two possible responses of yes or no. Single mothers who currently use any modern contraceptive were grouped as \u0026lsquo;yes\u0026rsquo; and coded \u0026lsquo;1\u0026rsquo; while those who are not currently using a modern method were grouped as \u0026lsquo;no\u0026rsquo; and coded \u0026lsquo;0\u0026rsquo;. The explanatory variables are sets of selected socio-economic and demographic characteristics. The socio-economic characteristics are maternal education (none, primary, secondary and higher), household wealth quintile (poorest, poorer, middle, richer and richest), religious affiliation (Christianity, Islam and tradition/others), employment status (employed or unemployed), place of residence (urban or rural), geographic region (northern or southern) and exposure to mass media (low, moderate and high). The three geo-political zones in the southern parts of the country, namely, southeast, south-south and southwest zones are combined as southern region while the zones in the northern parts of the country, namely, northcentral, northeast and northwest zones are combined as the northern region. Exposure to mass media was generated from three variables, namely, frequency of reading newspaper, listening to radio and watching television. Single mothers who do not access these outlets or accessed the outlets less than once a week were grouped as low exposure. Those who accessed the outlets at least once a week were grouped as moderate exposure. Other single mothers who accessed the outlets almost every day were grouped as high exposure.\u003c/p\u003e \u003cp\u003eThe demographic characteristics are age group (15\u0026ndash;24, 25\u0026ndash;34 and 35\u0026ndash;49\u0026nbsp;years), age at sexual debut (less than 18\u0026nbsp;years or 18 or older), parity (one child, two-four children, and five or more children) fertility desire (wanted more children or wanted no more), and child living arrangement (lives with mother or lives elsewhere). These variables are selected based on their significance in previous studies [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The control variables are nature of singlehood (premarital or post marital singlehood), sexual activity (active or inactive) and most recent sexual partner (boy/man friend, commercial worker and casual friends).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData analysis was carried out using Stata version 14 [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Univariate analysis was carried out to assess the prevalence and use of modern contraceptives and to describe the sample characteristics. At the bivariate level, the relationship between each of the explanatory variables and the outcome variable was examined using the Unadjusted Odds Ratio (UOR) of binary logistic regression. Any variable that reveal no statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.025 was excluded from further analysis. The multivariable logistic regression analysis was used to examine the factors influencing the outcome variable using the Adjusted Odds Ratio (AOR) with 95% confidence interval. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDescriptive Results\u0026nbsp;\u0026nbsp; \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 presents the socio-demographic characteristics of the respondents. More than one-fifth (23.5%) of the single mothers had no education while more than a quarter (27.2%) attained primary education. Slightly more than two-fifths (41.0%) of the single mothers attained secondary education while less than one-tenth (8.3%) of them attained higher education. The distribution of single mothers by household wealth quartile shows that single mothers who were in the middle (26.3%) and richer (25.9) wealth categories constituted more than half of the distribution. Single mothers who are in the poorest (11.0%) and poorer (18.1%) wealth categories were less than a quarter of the distribution while 18.7% of the single mothers were in the richest household wealth category. Majority of the single mothers were Christian (71.2%). The majority of the respondents (79.9%) were employed. Most of the single mothers resided in rural areas (53.2%) compared to those who resided in urban areas (46.8%). The result shows that there were more single mothers in the southern region (62.0%) than in the northern region of the country (38.0%). The majority of the respondents (62.7%) had moderate exposure to mass media but slightly more than a quarter of the women (27.1%) had low exposure to mass media. Half of the respondents (50.7%) were aged 35-49 years. Nearly half of the respondents had their first sex before age 18. More than one third (33.8%) of the respondents had at least a child while 41.7% had two-four children. Nearly half of the respondents wanted more children (48.0%) while majority of the respondents (71.8%) had at least a child living with them. Most of the respondents (72%) were post marital single mothers while 28% were premarital single mothers.\u0026nbsp; Though, all the single mothers included were sexually active but 17.9% were sexually active in the last one month preceding the survey. Slightly more than half of the respondents (54.2%) had casual friends as their most recent sexual partner. The prevalence of modern contraceptive use among the single mothers was 11.7%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBivariate Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 present the cross tabulation and multivariable results. Education and modern contraceptive use are significantly positively related. As education improves, the prevalence of modern contraceptive use increased consistently. For example while single mothers who attained primary education had 9.9% prevalence of contraceptive use, single mothers who attained higher education had 16.4% prevalence of modern contraceptive use. Similarly, household wealth quartile was positively associated with modern contraceptive use. For instance, prevalence of contraceptive use was 10.5% among single mothers in middle wealth group compared to 17.6% among single mothers in richest wealth group. Religion and modern contraceptive use revealed significant association with lower odds of contraceptive use among Muslim single mothers compared to Christians single mothers (UOR=0.307, p\u0026lt;0.01; 95% CI: 0.224\u0026ndash;0.421). Employment status and modern contraceptive use are significantly positively related with higher use of modern contraceptive among employed single mothers compared to the unemployed (12.6% vs. 8.6%). Place of residence and modern contraceptive use are negatively related with lower odds of modern contraceptive use among single mothers who resided in rural areas (UOR=0.776, p\u0026lt;0.05; 95% CI: 0.639\u0026ndash;0.943). The prevalence of modern contraceptive use was 7.6% among northern single mothers compared to 14.3% prevalence among southern single mothers indicating a significant positive relationship between geographic region and modern contraceptive use. Exposure to mass media and modern contraceptive use reveal significant positive relationship. The odds of modern contraceptive use are higher among single mothers who had moderate exposure to mass media (UOR=2.422, p\u0026lt;0.01; 95% CI: 1.927-3.044) and among single mothers who had high exposure to mass media (UOR=2.820, p\u0026lt;0.01; 95% CI: 2.040\u0026ndash;3.899).\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; The relationship between age group and modern contraceptive use had a mixed relationship with modern contraceptive use. The relationship was positive at lower age group but negative at the upper age group. For instance, while single mothers aged 25-35 had higher odds of modern contraceptive use (UOR=1.542, p\u0026lt;0.01; 95% CI: 1.232-1.931), single mothers aged 35-49 had lower odds of modern contraceptive use (UOR=2.820, p\u0026lt;0.01; 95% CI: 2.040\u0026ndash;3.899). Age at sexual debut and modern contraceptive use reveals significant negative association. \u0026nbsp;The prevalence of modern contraceptive use was 13.6% among single mothers who had first sex before reaching age 18 compared to 10.1% among single mothers who had first sex at age 18 or older ages. Parity and modern contraceptive use are negatively associated. As parity increases prevalence of modern contraceptive use tends to reduce. Likewise, fertility desire and modern contraceptive use are negatively related with lower odds of modern contraceptive use among single mothers who not desire additional children (UOR=0.558, p\u0026lt;0.01; 95% CI: 0.468\u0026ndash;0.665). The relationship between child living arrangement and modern contraceptive use was significantly positive with higher odds of modern contraceptive use among single mothers whose children live elsewhere (UOR=1.280, p\u0026lt;0.01; 95% CI: 1.065\u0026ndash;1.537).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate Results \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multivariate result (Table 2) shows that more socioeconomic characteristics of single mothers had significant effect on modern contraceptive use compared to the demographic characteristics that reveals statistical significance. As education improved, the likelihood of modern contraceptive use increased consistently. For instance single mothers who attained secondary education were more than twice more likely to use modern contraceptives compared to uneducated single mothers (AOR=2.254, p\u0026lt;0.01; 95% CI: 1.431\u0026ndash;3.551). With the exclusion of poorer wealth category, the odds of modern contraceptive use increased consistently as household wealth improved. For instance single mothers in richest wealth category were more than twice more likely to use modern contraceptives compared to single mothers in poorest wealth category (AOR=2.374, p\u0026lt;0.01; 95% CI: 1.446\u0026ndash;3.897). Muslim single mothers were 47.3% less likely to use modern contraceptive compared to Christian single mothers (AOR= 0.527, p\u0026lt;0.05; 95% CI: 0.366\u0026ndash;0.759). Employed single mothers were 44.9% more likely to use modern contraceptives compared to unemployed single mothers (AOR=1.449, p\u0026lt;0.05; 95% CI: 1.123\u0026ndash;1.867). Exposure to mass media had positive effect on modern contraceptive use. While single mothers who had moderate exposure to mass media were 45.5% (AOR=1.455, p\u0026lt;0.05 ; 95% CI: 1.049\u0026ndash;1.807) more likely to use modern contraceptives, single mother who had high exposure to mass media were 44.2% (AOR=1.442, p\u0026lt;0.05; 95% CI: 0.690\u0026ndash;1.394) more likely to use modern contraceptive compared to single mothers who had low exposure. Single mothers in the 25-34 age group were 37.7% more likely to use contraceptive compared to younger single mothers (AOR=1.377, p\u0026lt;0.05; 95% CI: 1.049\u0026ndash;1.807). Two of the control variables reveal significant effect on the odds of modern contraceptive use. Single mothers who are recently sexually inactive and single mothers whose most recent sexual partners were causal friends had lower odds of modern contraceptive use.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the factors influencing modern contraceptive utilisation among single mothers. The study differs from existing studies that focused on other segments of childbearing women such as adolescents [21-23], never married women [24-26] and women of advanced reproductive age [27-30] by focusing on single mothers. This group of women has received little attention in family planning programming in Nigeria. The study therefore attempts to bring to the fore of family planning programming in Nigeria, the case of single mothers. Single mothers in many parts of the country are victims of discrimination, rejection and blackmail in the community [11-13]. Their children also face higher risks of adverse health outcomes in the community [14-17]. This peculiar condition of single mothers may create more demand for modern contraceptive use to avoid repeated pregnancy that may aggravate the extent of the stigmas experience in the community. Two key findings emerged from the study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Firstly, the study reveals 11.7% prevalence of modern contraceptive use among single mothers in Nigeria. This level of utilisation is rather low and further underscores poor contraceptive prevalence rate already observed in previous studies in the country [22, 24-25, 27, 29, 32]. It also point to the need to reposition the existing Family Planning Blue Print in Nigeria [19] through increasing the tempo of family planning demand generation among special groups of women such as single mothers. The Family Planning Blue Print already noted that the economic and health benefits of spacing pregnancies or limiting child birth is not well appreciated by families and providers which resulted into low contraceptive use in the country. This challenge may be addressed by two measures. One, it is important to recognise that single motherhood not only represents an unconventional family structure in the community but is also increasing in the community [6]. The peculiar contraceptive need of this group of women may thus be different from the needs of other women. This has made the development of a special strategy targeting single mothers in Nigerian communities imperative. Two, family planning service delivery points in the community such as community health extension workers (CHEWs) and proprietary patent medicine vendors (PPMVs) should be trained to maintain contacts with single mothers patronising them for various health needs in the community. This will afford the providers the unique opportunity of providing needy single mothers with more contraceptive information, counselling and services particularly those relating to long term methods such as injectables and long-acting reversible contraceptives (LARCs). \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Secondly, the socio-demographic characteristics of single mothers such as education, household wealth, religion, employment and mass media exposure are key drivers of modern contraceptive utilisation. As evident in the study, modern contraceptive use increased with improvement in educational level of single mothers. This finding is not only consistent with\u0026nbsp; in existing studies [29-30] but also suggests that the role of educational attainment in boosting contraceptive use may not differ among single mothers and other groups of women in the country. Thus, it is important that population and health policies and programmes in the country continue to seek means of expanding women\u0026rsquo;s access to improve educational opportunities. However, public health education programme should be designed for uneducated single mothers to ensure they are not disadvantaged. Such programme could be spread using the mass media outlets since most single mothers either had moderate or high access to the mass media, and should target younger single mothers who are found to have higher odds of contraceptive use in the study. The programme should also stress the dangers of unprotected intercourse with casual friends since this not only elevates the risk of unintended pregnancy but also elevate the risk of infection with sexually transmitted diseases. This aspect is important because the study observed that more than half of the single mothers had sexual contacts with casual friends. Also, the study reveal that modern contraceptive use increase with improvements in single mothers\u0026rsquo; household wealth quintile and employment in agreement with finding in previous studies [56-60] which provides support for the women empowerment strategies of the current national population policy [18]. It is expected that as women\u0026rsquo;s economic power improves, their say in household decision-making may improve and more women may be able to access methods that are not covered by the free user fee initiative in public health facilities in the country.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrength and Limitations\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provided information on the drivers of modern contraceptive use which has been largely ignored in several existing studies. The precision of the inferences made in the study is greatly enhanced by the use of the NDHS data which is not only potentially verifiable but is also based on internationally credible methodology. However, the study has some limitations. One, the usage of the term \u0026lsquo;factors influencing\u0026rsquo; modern contraceptive use in the study do not necessarily mean the \u0026lsquo;cause\u0026rsquo; of modern contraceptive use. The use is intended to connote the \u0026lsquo;associated factors\u0026rsquo; of modern contraceptive use since the study was based on a cross-sectional data. Two, the associated factors examined in the study are selected among several other associated factors identified in previous studies. Other studies may examine other sets of variables that may change the pattern of result in the current study. Three, the responses analysed in the study are self-reported. It is not impossible that some of the responses may not reflect the true situation of single mothers covered in the study. We however, believed that the sound methodology of the DHS programme has greatly reduced respondents\u0026rsquo; bias during data collection.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examined factors influencing modern contraceptive utilisation among single mothers in Nigeria. Data was pooled from four consecutive rounds of the NDHS due to small proportion of single mothers in each round of the NDHS. The study revealed low prevalence of modern contraceptive use among the studied women. The key drivers of modern contraceptive use among single mothers are education, household wealth, media exposure, religion, age and employment. Additional family planning strategy targeting single mothers in the country should be designed for implementation in the country.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNDHS\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Nigeria Demographic and Health Survey\u003c/p\u003e\n\u003cp\u003eDHS\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Demographic and Health Survey\u003c/p\u003e\n\u003cp\u003eUSAID\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; United States Agency for International Development\u003c/p\u003e\n\u003cp\u003eNPC\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; National Population Commission\u003c/p\u003e\n\u003cp\u003eFMoH\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Federal Ministry of Health\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003eIn line with the DHS programme, each round of the NDHS was first approved in the United States by the International Review Board of ICF International and also approved in Nigeria by the National Health Research Ethics Committee (NHREC). Participants in the surveys provided verbal consent as a condition for commencement of interview. The datasets were formally requested and authorised. The datasets are available via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/data/\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach round of the NDHS was first approved in the United States by the International Review Board of ICF International and in Nigeria by the National Health Research Ethics Committee (NHREC). All participants gave verbal consent to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysed datasets are available via \u003ca href=\"https://dhsprogram.com/data/\"\u003ehttps://dhsprogram.com/data/\u003c/a\u003e. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBBI developed the concept which was modified by BLS. All authors took part in literature review, data analysis and discussion of findings. All authors read through and approved the submitted version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to MEASURE DHS and the National Population Commission (Nigeria) authorising access to 2003-2018 NDHS datasets. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBBI is a doctoral student in the Department of Demography and Social Statistics, Obafemi Awolowo University, Ile-Ife, Nigeria. BLS is a Senior Lecturer in the Department. MBM is a Lecturer 1 in the Department of Sociology, Ahmadu Bello University, Zaria, Nigeria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003eSarvestani KA, Khoo SL, Malek NM, Yasin M, Ahmadi A. Determinants of Contraceptive Usage among Married Women in Shiraz, Iran. Journal of Midwifery Reproductive Health. 2017;5(4):1041\u0026ndash;52. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22038/JMRH.2017.8771\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCleland J, Bernstein S, Ezeh A, Faundes A, Glasier A, Innis J. Family planning: the unfinished agenda. Lancet. 2006;368:1810\u0026ndash;27. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(06)69480-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBongaarts J, Sinding SW. Family Planning as an Economic Investment. SAIS Review. 2011;XXXI(2):35\u0026ndash;44.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBongaarts J, Cleland J, Townsend JW, Bertrand JT, Gupta MD. Family Planning Programs for the 21st Century: Rationale and Design. New York: Population Council; 2011.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGoodkind D, Choi LLY, McDevitt T, West L. The demographic impact and development benefits of meeting demand for family planning with modern contraceptive methods. Global Health Action. 2018;11(1):1423861. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/16549716.2018.1423861\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNtoimo LFC, Isiugo-Abanihe U. Patriarchy and Singlehood among Women in Lagos, Nigeria. J Fam Issues. 2013;35(14):1980\u0026ndash;2008. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0192513X13511249\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eOshi DC, Mckenzie J, Baxter M, Robinson R, Neil S, Greene T, et al. Association between single-parent family structure and age of sexual debut among young persons in Jamaica. J Biosoc Sci. 2018. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/s0021932018000044\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eSteinbach A, Kuhnt AN, Knull M. The prevalence of single-parent families and stepfamilies in Europe: can the Hajnal line help us to describe regional patterns? The History of the Family. 2016;21(4):578\u0026ndash;95. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/1081602X.2016.1224730\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMikkonen HM, Salonen MK, Hakkinen A, Olkkola M, Pesonen A, Raikkonen K, et al. The lifelong socioeconomic disadvantage of single-mother background - the Helsinki Birth Cohort study 1934\u0026ndash;1944. BMC Public Health. 2016;16:817. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-016-3485-z\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLu Y, Walker R, Richard P, Younis M. Inequalities in Poverty and Income between Single Mothers and Fathers. Int J Environ Res Public Health. 2020;17:135. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph17010135\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAmroussia N, Hernandez A, Vives-Cases C, Goicolea I. \u0026ldquo;Is the doctor God to punish me?!\u0026rdquo; An intersectional examination of disrespectful and abusive care during childbirth against single mothers in Tunisia. Reprod Health. 2017;14:32. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12978-017-0290-9\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAnyebe EE, Lawal H, Dodo R, Adeniyi BR. Community Perception of Single Parenting in Zaria, Northern Nigeria. J Nurs Care. 2017;6(4):411. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4172/2167-1168.1000411\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eEssien AM, Bassey AA. The socio and religious challenges of single mothers in Nigeria. American Journal of Social Issues Humanities. 2012;2(4):240\u0026ndash;51.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNewlin M. Public Perceptions Towards Children Brought Up by Single Mothers: A Case of Queenstown, South Africa. Journal of Human Ecology. 2017;58(3):169\u0026ndash;80. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/09709274.2017.1324695\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNtoimo LFC, Odimegwu CO. Health effects of single motherhood on children in sub-Saharan Africa: a cross-sectional study. BMC Public Health. 2014;14:1145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2458-14-1145\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eScharte M, Bolte G, et al. Increased health risks of children with single mothers: the impact of socio-economic and environmental factors. Eur J Pub Health. 2012;23(3):469\u0026ndash;75. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurpub/cks062\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eRichter D, Lemola S. Growing up with a single mother and life satisfaction in adulthood: A test of mediating and moderating factors. PLoS ONE. 2017;12(6):e0179639. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0179639\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNatioanl Population Commission. National Policy on Population for Sustainable Development. Abuja: NPC; 2004.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eFederal Ministry of Health. Natioanl Family Planning Blue Print. Abuja: FMoH; 2014.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eFederal Ministry of Health. 2017 National Reproductive Health Policy, Abuja Nigeria; FMoH;2017.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCasey SE, Gallagher MC, Kakesa J, Kalyanpur A, Muselemu JB, Rafanoharana RV, Spilotros N. Contraceptive use among adolescents and young women in North and South Kivu, Democratic Republic of the Congo: A cross sectional population-based survey. Plos Medicine. 2020;17(3):e1003086. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pmed.1003086\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAbiodun OM, Balogun OR. Sexual activity and contraceptive use among young female students of tertiary educational institutions in Ilorin, Nigeria. Contraception. 2009;79:146\u0026ndash;9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.contraception.2008.08.002\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAhinkorah BO, Hagan JE Jr, Seidu A-A, Sambah F, Adoboi F, Schack T, et al. Female adolescents\u0026rsquo; reproductive health decision-making capacity and contraceptive use in sub- Saharan Africa: What does the future hold? PLoS ONE. 2020;15(7):e0235601. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0235601\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAhmed ZD, Sule IB, Abolaji ML, Mohammed Y, Nguku P. Knowledge and utilization of contraceptive devices among unmarried undergraduate students of a tertiary institution in Kano State, Nigeria 2016. Pan African Medical Journal. 2017;26:103. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11604/pamj.2017.26.103.11436\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAjayi AI, Nwokocha EE, Adeniyi OV, Goon DT, Akpan W. Unplanned pregnancy-risks and use of emergency contraception: a survey of two Nigerian Universities. BMC Health Services Research. 2017;17:382. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12913-017-2328-7\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCohen N, Mendy FT, Wesson J, Protti A, Ciss\u0026eacute; C, Gueye EB, et al. Behavioral barriers to the use of modern methods of contraception among unmarried youth and adolescents in eastern Senegal: a qualitative study. BMC Public Health. 2020;20:1025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-020-09131-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eOlaolorun FM, Hindin MJ. Having a say matters: Infleunce of Decision-making Power on Contracpetive Use among Nigeria Women ages 35\u0026ndash;49 years. Plos One. 2014;9(6):e98702. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0098702\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eTepper NK, Godfrey EM, Folger SG, Whiteman MK, Marchbanks PA, Curtis KM. Hormonal contraceptive use among women of older reproductive age: considering risks and benefits. Journal of Women\u0026rsquo;s Health. 2018. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/jwh.2018.6985\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eSolanke BL. Factors influencing contraceptive use and non-use among women of advanced reproductive age in Nigeria. J Health Popul Nutr. 2017;36(1):1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s41043-016-0077-6\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAma NO, Olaomi JO. Family planning desires of older adults (50 years and over) in Bostwana. South African Family Practice. 2018;61(1):30\u0026ndash;8. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/20786190.2018.1531584\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAbdulahi M, Kakaire O, Namusoke F. Determinants of modern contraceptive use among married Somali women living in Kampala; a cross sectional survey. Reproductive Health. 2020;17:72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12978-020-00922-x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAustin A. Unmet contraceptive need among married Nigerian women: an examination of trends and drivers. Contraception. 2015;91:31\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.contraception.2014.10.002\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eOgboghodo EO, Adam VY, Wagbatsoma VA. Prevalence and determinants of contraceptive use among women of child-bearing age in a rural community in Southern Nigeria. Journal of Community Medicine Primary Health Care. 2017;29(2):97\u0026ndash;107.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKomasawa M, Yuasa M, Shirayama Y, Sato M, Komasawa Y, Alouri M. Demand for family planning satisfied with modern methods and its associated factors among married women of reproductive age in rural Jordan: A cross-sectional study. Plos One. 2020;15(3):e0230421. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0230421\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAgnafors S, Bladh M, Svedin CG, Sydsjo G. Mental health in young mothers, single mothers and their children. BMC Psychiatry. 2019;19:112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-019-2082-y\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eDronkers J, Veerman GM, Pong S. Mechanisms Behind the Negative Influence of Single Parenthood on School Performance: Lower Teaching and Learning Conditions? Journal of Divorce Remarriage. 2017;58(7):471\u0026ndash;86. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10502556.2017.1343558\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMainthia R, Reppart L, Reppart J, Pearce EC, Cohen JJ, Netterville JL. (2013). A Model for Improving the Health and Quality of Life of Single Mothers in the Developing World. Afr J Reprod Health. 2013;17(4):14\u0026ndash;25.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eUnited States Agency for International Development. (2018). The DHS Program and Health Surveys. USA: USAID. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data2.unhcr.org/en/documents/download/64979\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cdiv class=\"BibDataset\"\u003e \u003cdiv class=\"DatasetTitle\"\u003eA systematic review of Demographic and Health Surveys: data availability and utilization for research\u003c/div\u003e \u003cdiv type=\"DOI\" class=\"DatasetID\"\u003e10.2471/BLT.11.095513\u003c/div\u003e \u003c/div\u003e \u003cspan\u003eFabic MS, Choia YJ, Bird S. A systematic review of Demographic and Health Surveys: data availability and utilization for research. Bulletin of World Health Organisation. 2012;90:604\u0026ndash;12, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2471/BLT.11.095513\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eCorsi DJ, Neuman M, Finlay JE, Subramanian SV. Demographic and health surveys: a profile. Int J Epidemiol. 2012;41:1602\u0026ndash;13.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAI Zalak Z, Goujon A. Assessment of the data quality in Demographic and Health Surveys in Egypt, Vienna Institute of Demography Working Papers, No. 06;2017, Austrian Academy of Sciences (OAW), Vienna Institute of Demography (VID), Vienna.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAvailable at. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://hdl.handle.net/10419/175538\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Population Commission, ICF. Nigeria Demographic and Health Survey 2018. Abuja, Nigeria and Rockville, Maryland, USA: NPC \u0026amp;ICF;2019.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Population Commission, ORC Macro. Nigeria Demographic and Health Survey 2003. Maryland: Calverton; 2004. NPC \u0026amp; ORC Macro.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Population Commission, ICF Macro. Nigeria Demographic and Health Survey 2008. Abuja: NPC \u0026amp; ICF Macro; 2009.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Population Commission, ICF International. Nigeria Demographic and Health Survey 2013. Nigeria: Abuja; 2014. NPC \u0026amp; ICF International.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLewis T. Estimation Strategies Involving Pooled Survey Data, 1\u0026ndash;15. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://support.sas.com/resources/papers/proceedings17/0767-2017.pdf\u003c/span\u003e\u003c/span\u003e;2017.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHenry H, Singh V, Johnson SC, Wahba G. Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Proc Natl Acad Sci USA. 2018;115(7):1481\u0026ndash;6. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.1719747115\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eEzeh OK, Agho KE, Dibley MJ, Hall JJ, Page AN. Risk factors for postneonatal, infant, child and under-5 mortality in Nigeria: a pooled cross-sectional analysis. BMJ Open. 2015;5:e006779. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2014-006779\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eSolanke BL. Individual and community factors associated with indications of caesarean delivery in Southern Nigeria: Pooled analyses of 2003\u0026ndash;2013 Nigeria demographic and health surveys. Health Care Women Int. 2018;39(6):697\u0026ndash;716. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/07399332.2018.1443107\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYaya S, Amouzou A, Uthman OA, Ekholuenetale M, Bishwajit G, Ogochukwu U, et al. Prevalence and determinants of terminated and unintended pregnancies among married women: analysis of pooled cross-sectional surveys in Nigeria. BMJ Glob Health. 2018;3:e000707. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjgh-2018-000707\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eDahiru T. First-day and Early Neonatal Mortality in Nigeria: A Pooled Cross-sectional Analysis of Nigeria DHS Data. British Journal of Medicine Medical Research. 2017;19(9):1\u0026ndash;12. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.9734/BJMMR/2017/28247\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003evan der Steen JT, Kruse RL, Szafara KL, et al. Benefits and pitfalls of pooling datasets from comparable observational studies: combining US and Dutch nursing home studies. Palliat Med. 2008;22(6):750\u0026ndash;9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0269216308094102\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBhalotra S. Sibling-Linked Data in the Demographic and Health Surveys. Economic Political Weekly. 2008;43(48):39\u0026ndash;43.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBangdiwala SI, Bhargava A, Connor DPO, Robinson TN, Michie S, Murray DM, Pratt CA. Statistical methodologies to pool across multiple intervention studies. Transl Behav Med. 2016;6(2):228\u0026ndash;35. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s13142-016-0386-8\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cdiv class=\"BibDataset\"\u003e \u003cdiv class=\"DatasetTitle\"\u003eAppropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data\u003c/div\u003e \u003cdiv type=\"DOI\" class=\"DatasetID\"\u003ehttps://doi.org/10.1186/s12199-018-0737-9\u003c/div\u003e \u003c/div\u003e \u003cspan\u003eGeremew A, Mengistie B, Mellor J, Lantagne DS, Alemayehu E, Sahilu G. Appropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data. Environ Health Prev Med. 2018; 23:46, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12199-018-0737-9\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLasong J, Zhang Y, Gebremedhin SA, Opoku S, Abaidoo CS, Mkandawire T, et al. Determinants of modern contraceptive use among married women of sectional study reproductive age: a cross in rural Zambia. BMJ Open. 2020;10:e030980. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2019-030980\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYaya AA, Caroline G, Abderahim MN. Use of Female Contraception Mixed and Multicentric Study in Chad. Am J Public Health. 2020;8(1):22\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.12691/ajphr-8-1-4\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eOladosun M, Akanbi M, Fasina F, Samuel O. Key predictors of modern contraceptive use among women in marital relationship in South-west region of Nigeria. International Journal of Reproduction Contraception Obstetrics Gynecology. 2019;8(7):2638\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.18203/2320-1770.ijrcog20193018\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMedhanyie AB, Desta A, Alemayehu M, Gebrehiwot T, Abraha TA, Abrha A, et al. Factors associated with contraceptive use in Tigray, North Ethiopia. Reprod Health. 2017;14:27. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12978-017-0281-x\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAchana FS, Bawah AA, Jackson EF, Welaga P, Awine T, Asuo-Mante E, et al. Spatial and socio-demographic determinants of contraceptive use in the Upper East region of Ghana. Reproductive Health. 2015;12:29. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12978-015-0017-8\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eStatCorp. Stata. Release 14. Statistical Software. College Station: StataCorp LP; 2015.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage distribution of respondents by socio-economic and demographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;7,215)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;7215)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eAge at sexual debut\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLess than 18\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u0026nbsp;years or older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold wealth quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;4 children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 or more children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDesire for more children\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWanted more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWanted no more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eChild living arrangement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLives with mother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLives elsewhere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNature of singlehood\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraditional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePremarital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePost marital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSexual activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMost recent sexual partner\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoy/Man friend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographic region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCommercial sex worker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCasual friends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eModern contraceptive use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot using\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;24\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUsing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;49\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure to mass media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCross tabulation and multivariable results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic predicting modern contraceptive use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eUnadjusted Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eAdjusted Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eUOR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eAOR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.034**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.184\u0026ndash;4.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.690**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.165\u0026ndash;2.451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.576**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.128\u0026ndash;7.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.146**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.524\u0026ndash;3.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.440**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.681\u0026ndash;8.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.254**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.431\u0026ndash;3.551\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold wealth quintile\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.684**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.139\u0026ndash;2.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.973\u0026ndash;2.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.251**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.515\u0026ndash;3.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.734*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.121\u0026ndash;2.683\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.191**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.160\u0026ndash;4.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.122**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.362\u0026ndash;3.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.126**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.761\u0026ndash;6.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.374**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.446\u0026ndash;3.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.307**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u0026ndash;0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.527**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.366\u0026ndash;0.759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraditional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.450*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.259\u0026ndash;0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.339\u0026ndash;1.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.530**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.219\u0026ndash;1.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.449**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.123\u0026ndash;1.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.776*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.639\u0026ndash;0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.768\u0026ndash;1.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographic region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.020**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.614\u0026ndash;2.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.684\u0026ndash;1.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure to mass media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow exposure \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.422**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.927\u0026ndash;3.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.455*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.049\u0026ndash;1.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.820**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.040\u0026ndash;3.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.442*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.690\u0026ndash;1.394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;24\u0026nbsp;years \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.232\u0026ndash;1.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.377*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.049\u0026ndash;1.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;49\u0026nbsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.516\u0026ndash;0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.691\u0026ndash;1.394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at sexual debut\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 18\u0026nbsp;years \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026nbsp;years or older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.711**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.600-0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.716\u0026ndash;1.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 child \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;4 children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.641**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.535\u0026ndash;0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.702\u0026ndash;1.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 or more children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.453**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.357\u0026ndash;0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.764\u0026ndash;1.537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDesire for more children\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWanted more \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWanted no more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.558**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.468\u0026ndash;0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.960\u0026ndash;1.489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild living arrangement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLives with mother \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLives elsewhere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.280**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.065\u0026ndash;1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.960\u0026ndash;1.471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNature of singlehood\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremarital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost marital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.717\u0026ndash;1.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexual activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.406**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.327\u0026ndash;0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMost recent sexual partner\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoy/Man friend \u003csup\u003eref\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommercial sex worker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.538-1.400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCasual friends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.154**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.047\u0026ndash;0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: ref (reference category), *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Modern contraceptive use, single mothers, sexual and reproductive health, women, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-44145/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-44145/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Existing studies in Nigeria and elsewhere have examined the associated factors of modern contraceptive utilisation among different segments of women such as adolescents, never married and women of advanced reproductive age. However, the associated factors of modern contraceptive utilisation among single mothers have been rarely explored. Though, some studies have examined the health and socio-economic conditions of single mothers but the associated factors of modern contraceptive uptake among them were largely ignored. This study therefore examines factors influencing modern contraceptive utilisation among single mothers in Nigeria. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data were extracted from four consecutive Nigeria Demographic and Health Surveys (NDHSs) implemented between 2003 and 2018. A weighted sample size of 7,215 single mothers was analysed. The outcome variable was current modern contraceptive utilisation. The explanatory variables are sets of selected socio-economic and demographic characteristics such as education, household wealth quintile, place of residence, age, parity and fertility desire. Data analysis was carried out using Stata version 14. Two multivariable logistic regression models were fitted in the study.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Findings reveal 11.7% current utilisation of modern contraceptives among single mothers. Improvements in educational attainment and household wealth quintile increases the odds of modern contraceptive use, Muslim single mothers had lower odds of modern contraceptive use (AOR=0.527, p\u0026lt;0.05; 95% CI: 0.366-0.759) and employed single mothers had higher odds of modern contraceptive use (AOR=1.449, p\u0026lt;0.05; 95% CI: 1.123-1.867). Findings further reveal that single mothers who had moderate exposure to the mass media (AOR=1.455, p\u0026lt;0.05; 95% CI: 1.049-1.807), single mothers who had high exposure to the mass media (AOR=1.442, p\u0026lt;0.05; 95% CI: 0.690-1.394) and younger single mothers (AOR=1.377, p\u0026lt;0.05; 95% CI: 1.049-1.807) had higher likelihood of modern contraceptive use. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eModern contraceptive utilisation is low among single mothers in Nigeria. A number of socio-demographic characteristics of single mothers exert significant influence on modern contraceptive use. The contraceptive need of women involved in single motherhood may be different from the needs of other groups of women. The development of a special strategy targeting single mothers is thus imperative in the country.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"What Influences Modern Contraceptive Utilisation Among Single Mothers in Nigeria? Evidence from Pooled Cross-Sectional Surveys","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-07-21 17:01:09","doi":"10.21203/rs.3.rs-44145/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2020-11-15T00:00:00+00:00","index":3,"fulltext":"Recommendation: Major Revision\nForm responses:\n---\n\nComments to Author:\n---\nREPH-D20-00478: What influences modern contraceptive utilisation among single mothers in Nigeria? Evidence from pooled cross-sectional surveys\n\nThis manuscript collates data from four DHS surveys in Nigeria to explore reported contraceptive use and correlates among single mothers. This is a novel analysis and interesting premise but there are methodologic and interpretation issues that need to be addressed. Further, the manuscript would benefit from review by a native English speaker to improve phrasing and overall, there are opportunities to make the manuscript more concise. \n\nAbstract:\n* The Background section of the abstract can be abbreviated and, in reading the full article, the correlation between current sexual activity and contraceptive use needs to be reported as this is a major mitigating factor and adjusting for it is not sufficient to manage the way it is interpreted.\n\nIntroduction:\n* This section can be abbreviated by removing some repetitive statements (expanding single parent family structure globally) and statements that potentially over-generalize (\"In addition, modern contraceptives are beneficial to all women and men of reproductive age irrespective of marital or social condition.\").\n* The authors make the valid point that women who are unmarried and have children frequently face social discrimination. However, the lack of family planning program directed at unmarried women is likely over-stated, unless concrete examples from the Nigerian context can be provided.\n\nMethods:\n* Similar to the Background section, this section can be made more concise, particularly by describing methods more directly and reducing the description of DHS data collection and rationale as the DHS program is familiar to most readers and this manuscript presents a secondary analysis.\n* While I appreciate the need to pool data for relatively rare populations, the argument for not introducing a modifying variable to assess for degree of change between subsequent surveys is not convincing. If the authors make the point that social norms are changing to result in increased proportions of single mother-led families globally, this is also likely to be the case in Nigeria. These norms may have changed over the 15 year time span captured in this analysis, and by the same token, so may have the use of modern contraceptives. I recommend the authors add a variable to control for clustering by survey year in all comparative analyses.\n* Please explain why variables regarding partnership status are \"control variables\". Being previously vs. never married, current sexual activity, and having a long-term partner are critical covariates to understanding whether these women are in need of contraception and whether they might be in a stable relationship. \n\nResults:\n* Suggest starting the Results section with an overall total number of women included in each DHS analysis and the number and proportion who were single mothers from each of the included years.\n* There is quite a bit of repetition of data in the narrative and the tables. For example, many of the variables in Table 1 are presented along with percentages as well as directing the reader to the Table. I suggest abbreviating the text to just focus on interesting differences without accompanying percentages and direct the reader to Table 1.\n* Reporting around sexual activity and contraceptive need raises concern in this analysis. Using an pre-existing data set comes with a host of limitations but the low proportion of women who reported being sexually active within the last month before taking the survey and the low proportion reporting contraceptive use is not prominently featured and should be - are these the same group of people? If women are not sexually active, regardless of partnership status, frequently they will not use contraceptives, particularly those with demanding proper use schedules (e.g., OCPs) or undesirable side-effects (e.g., DMPA). The authors found that contraceptive use was negatively associated with reporting no recent sexual activity in bivariate and multivariable analysis. However, this does not feature as an important finding in the abstract or discussion, which is a notable omission and nuances how the results are interpreted.\n* Table 2 is confusing relative to the text as bivariate associations with \"control\" variables are reported but not shown in the table. This is relevant to the previous comment as well. It would also be helpful to add the proposed time clustering variable to assess whether these results are consistent across the multiple data sets used, particularly as some of the datasets may contain the same individuals. \nDiscussion:\n* The first paragraph is repetitive with the Background and should be removed or substantially shortened.\n* The issue I find most concerning about this section is that the data reveal that the bulk of single mothers have been previously married and thus may not differ as much from their age-matched peers as the authors contend, borne out by the similar findings of education, employment, and wealth quintile here and in other populations in Nigeria. \n* The authors do not raise lack of recent sexual activity as being linked with reported contraceptive use or perceived or actual need, which seems central to the research question. Table 1 suggests a substantial proportion of women in this analysis are not in a relationship and this should be considered as the motivator for contraceptive counseling and provision, as this likely influences women's perceptions of their own need. \n* The limitations section needs further consideration. For example, the second limitation can be stated more clearly by having the authors say they purposively chose critical factors for inquiry but may not have included all potentially associated correlates of contraceptive use. Thus, there may be correlates that were not detected in this analysis.\n* The lack of considering clustering by time between surveys as well as possible inclusion of the same women in several of the surveys is not addressed as a limitation.\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Level of interest: **An article whose findings are important to those with closely related research interests**\n* Quality of written English: **Needs some language corrections before being published**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"decision","content":"Major revision","date":"2020-11-15T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-10-23T12:00:00+00:00","index":5,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-08-17T12:00:00+00:00","index":2,"fulltext":"Recommendation: Minor Revision\nForm responses:\n---\n\nComments to Author:\n---\nIntroduction\n\nI disagree with this opening sentence and definition that health information and counselling are modern contraceptives. Modern contraceptives are tangible methods and devices used to prevent pregnancy. Health information and counselling are associated services. This opening sentence should be reviewed. (Line 114)\n\n\nIn line 126, the authors reported increasing rate of single motherhood and provides evidence for this.\n\n\nIn line 128 Author reported stigma/discrimination against single mothers. Also why? Evidently because of clash of values. This need to reflect here.\n\nPlease read Kathryn A. Levine MSW PhD (2009) Against All Odds: Resilience in Single Mothers of Children with Disabilities, Social Work in Health Care, 48:4, 402-419, DOI: 10.1080/00981380802605781\n\n\nBut we need to know why this is so. The author needs to provide a little background about factors leading to increase in single motherhood, particularly in the context of Africa and Nigeria. Divorce rate is increasing, new values, i.e., 'baby mama', that promote single motherhood are emerging. These are some of the factors that could be cited with reference to other published works.\n\nSentence in 131-133 need reference\n\nThe sentences in line 143-147 can be combined as one\n\nLine 149-151 needs a reference\n\nMethods\n\nThe time intervals of NDHS data (2013-2018) collection should be listed as one of the weaknesses of this manuscript. The two points are long enough for a change in policy or social dynamics that can affect social behaviour. \n\nThe narratives in the methods section should be consistently written in past tense.\n\nResults\n\nWhat I get from the descriptive section of the result does not completely and accurately reflect the information in the introduction. While the introduction reports stigma associated with single parenting -- a situation which is mostly associated with unintended or teenage pregnancy. We found more than 50% of single parents between age 35-49, most of whom might be divorced, separated or widowed. The is the more reason the literature in the introduction section should reflect the diverse factors influencing single parenting across the age categories.\n\nThe term \"Muslim single mothers\" should be written as 'Single Muslim mothers' and \"Christian single mothers\" as Single Christian mother\" because the subject is single parenting. Same for \"norther single mothers\"\n\n\nDiscussion\n\nHow are these results different from the results of other findings that focused on other subpopulation as claimed in your introduction? This should be the main focus of this section.\n\n\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Level of interest: **An article of importance in its field**\n* Quality of written English: **Needs some language corrections before being published**\n* Declaration of competing interests: **I declare that I have no competing interest**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"reviewerAgreed","content":"","date":"2020-08-16T12:00:00+00:00","index":4,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-07T12:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-08-07T12:00:00+00:00","index":1,"fulltext":"Recommendation: Major Revision\nForm responses:\n---\n\nComments to Author:\n---\nThis study examined the determinants of modern contraceptive usage among single mothers in Nigeria by analysing weighted secondary data extracted from previous Nigeria Demographic and Health Surveys (NDHSs) implemented between 2003 and 2018.\nAuthors integrated datasets in answering a research question on a sub-group from pooled data analysis with potential implications for policy and practice. 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