Determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia: an analysis of PMA-ET 2021 data

Determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia: an analysis of PMA-ET 2021 data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia: an analysis of PMA-ET 2021 data Fitsum Tariku Fantaye, Solomon Abrha Damtew, Kelemua Menegesha Sene This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4142531/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background In Ethiopia, although many activities have been performed to control rapid population growth and reduce the average number of births per woman, in the last ten years, it has not been feasible to achieve the desired level of change, as was planned and intended in the National Health Sector Transformation Plan (HSTP) and reproductive health (RH) strategies. The annual growth of the population and fertility rates continue to increase at 2.7 and 4.6, respectively. Fertility is one of the fundamental aspects affecting population dynamics, while the fertility desire of women to have children is one of the key elements of fertility and can be a precursor to actual fertility performance, a useful tool for understanding aggregate fertility trends, and important for understanding future reproductive behavior. Women's fertility desire is the number of children they want to have in the next few years, based on their assessment of the costs and benefits of childbearing. Methods This analysis used cross-sectional data from Performance Monitoring for Action Ethiopia (PMA-ET) 2021. A total of 4138 married or cohabiting individual women between the ages of 15 and 49 who were not pregnant were included in this analysis. Sampling weighting factors and design were applied in this analysis, and chi-square test statistics were computed to determine the overall association and used to assess the adequacy of the cell sample size. Multilevel binary logistic regression was used to identify important predictors of women’s fertility desire. The results are presented as percentages and odds ratios with 95% confidence intervals (CIs). Statistical significance was declared at a significance level of 0.05. Results Approximately three-quarters (74.1%, 95% CI; 71.5% − 76.6%) of reproductive-aged married/cohabiting women in Ethiopia desired to have a child. Women who reported having a forced pregnancy by their spouse, being of the Muslim religion, being aged 19 and above at first sex, and having attained secondary or higher education were found to be positively and significantly associated with the likelihood of fertility desire to have a child. However, women who reported 40 years of age or older, partner’s age 45 years of or older, who had three or more live births, who had a family size of five or more members, and who had ever used FPs were found to have lower odds of having a fertile desire to have a child. Conclusion The prevalent high-fertility desire to have a child in Ethiopia hinders the quick reduction of fertility rates and calls for the implementation of multifaceted strategies that preserve this high-fertility desire. Accordingly, sociocultural and demographic variables were determined to influence the desire for children. Understanding these determinants is vital to developing successful fertility programs and policies specifically designed for different populations, prioritizing and adopting interventions that increase everyone's access to and use of family planning options, and messaging that speaks to a range of religious and cultural groups. fertility desire desire for more children fertility intention PMA Ethiopia Background Globally, there has been a shift from a traditional to a transitional pattern, which has led to a decline in fertility rates, and for the first time since 1950, the overall population growth rate dropped below one percent per year in 2020 [ 1 ]. However, recent United Nations projections indicate that the world population will reach 8.5 billion in 2030 and 9.7 billion in 2050. Similarly, between 2022 and 2050, the population of sub-Saharan Africa (SSA) may double, surpassing 2 billion inhabitants by the end of the 2040s [ 1 , 2 ]. Remarkably, in 2022, SSA had the largest annual population growth rate among the eight world sustainable development goal (SDG) regions, at 2.5%, or double the global annual average of 0.8% [ 2 ]. In Ethiopia, although many activities have been performed to control rapid population growth and reduce the average number of births per woman [ 3 – 5 ], in the last decade, it has not been feasible to achieve the desired level of change, as was planned and intended in the national health sector transformation plane (HSTP) and reproductive health (RH) strategies [ 6 – 8 ]. Both the annual population growth and fertility rate remain high at 2.7 and 4.6, respectively [ 9 ]. Rapid population growth can exacerbate the challenge of eradicating poverty (SDG 1) and put more pressure on already depleted resources, thereby creating a greater challenge to ensure sustainable development goals (SDGs) [ 10 ]. Studies show that if the current population increases by 40%, the economy, food production, general environment, and global climate will be severely affected [ 11 , 12 ]. Fertility is among the fundamental aspects influencing population dynamics [ 13 , 14 ], and women’s fertility desire is one of the key elements of fertility since it can be a precursor to actual fertility performance, an instructive tool for discovering overall fertility patterns and important for understanding future reproductive behaviors [ 15 – 20 ]. A woman's fertility desire is the number of children she would like to have in the near future based on her own assessment of the costs and benefits of childbearing [ 21 – 23 ]. Fertility desire can be influenced by several factors that operate at the societal and individual levels. At the societal level, the desire for fertility is often driven by social and cultural pressures and the desire to maintain the stability of society [ 24 , 25 ], such as strong cultural preferences for large families [ 24 , 26 ] and the desire for boys over girls [ 27 – 30 ]. At the individual level, characteristics including age [ 31 , 32 ], number of living children [ 33 , 34 ], marital status, wealth, education level [ 35 – 39 ], and place of residence [ 40 – 42 ] and others [ 35 , 36 ] are associated with fertility desire. Although numerous factors have been shown to influence fertility desire in different parts of the world, there is a relative dearth of literature in Ethiopia and many other sub-Saharan African countries, and more than half of women who have several children still desire to have more [ 35 , 43 ]. A thorough understanding of fertility desire and its determinants at the aggregate level will help to design and implement public policy initiatives such as family planning (FP) programs and provide helpful resources for understanding fertility patterns, as family planning initiatives are unlikely to succeed if the desired fertility does not decrease [ 18 , 19 , 44 ]. It will also be important to take meaningful steps to sustain development and human well-being, including investing in reproductive health services and contraceptive technologies to slow and eventually change population growth, thereby creating socioeconomic structural transformation within society [ 18 , 23 , 45 ]. This provides an opportunity to comprehend the determinants influencing fertility desire among married or cohabiting women, who make up more than half of the adult population in Ethiopia. Methods and data sources This analysis used cross-sectional data from Performance Monitoring for Action Ethiopia (PMA-ET) 2021, which was conducted November 2021 to January 2022 [ 46 ]. The rationale for using PMA data includes the fact that, currently, PMA data are the best available recent and real-time data on reproductive, maternal, and newborn health indicators to inform national and regional government priorities and policies. In addition, the PMA collects data via resident enumerators using smartphones with customized ODK applications, which facilitates real-time data collection and timely feedback in correcting errors. PMA-ET 2021 A cross-sectional survey with a two-stage cluster design and urban‒rural and major regions as strata was used. A total of 243 enumeration areas (EAs) were selected from the master sample frame of the Central Statistical Agency (CSA). A complete census was conducted in the selected enumeration areas, followed by a selection of 35 households per enumeration area using simple random sampling. All reproductive-age women aged 15–49 who reside in the selected households and guests who slept there the night before the survey were interviewed after the household survey. A total of 8,365 households (98.9%) and 7,988 women (98.8%) completed the cross-sectional survey [ 46 ]. A detailed description of the sampling procedure and other methodological issues are provided in a previous report [ 47 ]. The PMA-ET offers important data that may be used to track health developments in crucial areas of the Ethiopian health system, such as family planning, women and girls’ RH empowerment, sexual violence, the quality of contraceptive counseling, vaccination, and other relevant newborn and maternal health data. It is executed by Addis Ababa University’s School of Public Health in collaboration with the Ethiopian Public Health Association with assistance from the Federal Ministry of Health, the Central Statistical Agency, and the Bill & Melinda Gates Institute for Population and Reproductive Health (Johns Hopkins Bloomberg School of Public Health). For this analysis, out of the 8203 reproductive-age women included in the survey, 2951 women who were not married or cohabiting at the time of the survey were dropped at the initial step. After the exclusion of 662 pregnant women and 430 women who reported being sterilized, who did not know/undecided about fertility desire, who could not become pregnant, who had missing values or incomplete survey results leaving, an unweighted sample size of 4160. Thus, a sample of 4160 married or cohabiting individual women between the ages of 15 and 49 who are currently not pregnant and who were suitable for our analysis for our purpose were selected. Sampling weighting factors were applied to the data files to ensure that the computed results would be proportional at the national level, resulting in a final weighted sample size of 4138 [ 48 ]. Dependent Variable "Women’s fertility desire" was the study's outcome variable. Although population specialists have been notably unsuccessful in reaching an agreement on the most appropriate way to measure fertility desire, virtually the majority of fertility surveys, including demographic and health surveys (DHSs), conducted in recent decades have used consistent measurements [ 18 , 23 , 49 ]. The dependent variable “Would you like to have a/another child or would you prefer not to have any/any more children?”, with five response categories, was dichotomized into two to calculate the outcome variables "No more/prefer no children = 0" (for married/cohabiting reproductive age women who reported that she prefers not to have any/any more children) and "Have a/another child = 1" (for married/cohabiting reproductive age women who reported that she prefers to have a/another child) (Table 1 ). The reason for the exclusion of the remaining categories of “undecided/do not know" and "no response" was that they did not specify their preferred fertility desire, and those who said they "cannot become pregnant" were unlikely to become pregnant. It was necessary to exclude them from the sample for these reasons to avoid obtaining biased estimates. Table 1 Description of the dependent variables Women’s Fertility Desire Variable Question & Responses Categories Item Response Fertility Desire Would you like to have a/another child, or would you prefer not to have any/any more children? Have a/another child = 1 1 = Have a/another child No more/prefer no child = 2 0 = No more/prefer no child Says she can’t get pregnant = 3 Excluded categories Undecided/Don’t know = -88 No response = -99 Independent Variable After reviewing the related literature, possible determining factors correlated with fertility desire were extracted from the survey data. Independent variables were broadly classified into individual-level variables and enumeration area-level variables. Individual-level variables included age, education, wealth status, religion, parity, FP ever used, etc. The enumeration area variables are region and residence. The list of potential variables that are correlated with fertility desire and the details of how each of these variables was coded are provided in Table 2 . Composite variables were constructed using the Yes or No questions for the “FP knowledge” and “FP information” variables. “Region” was grouped into five categories: “other regions” represented Afar, Somali, Benishangul, and Gambella, Harari. The remaining regions except Tigray (because of the outbreak of the existing war during the study period, Tigray was not included in the 2021 PMA) were categorized accordingly. Statistical analysis Merged household and female respondent datasets were used and annualized by STATA v16. Tabularization was performed for every variable to check the item nonresponse rate and lack of response, which was subsequently excluded from the analysis. These variables were subsequently recoded to create biologically plausible categories. This was followed by checking the distribution of the variable using the mean and proportion whenever appropriate categories were merged to ensure cell sample size adequacy [ 50 ]. Frequencies and percentages were computed to characterize the study population. Chi-square test statistics were computed to determine the overall associations of the independent variables with the two categories of fertility desire. It is also used to cross-check cell sample size adequacy. Sample weights determined by using the multistage sampling strategy were considered in all exploratory data analyses [ 48 ]. Multicollinearity among the predictors was checked using the variance inflation factor (VIF), and no sign of multicollinearity was detected. (mean VIF = 1.68, maximum VIF = 3.20, and minimum VIF = 1.02) Multilevel binary logistic regression was used to identify important predictors of women’s fertility desire. In the bivariate analysis, a p value cutoff of 0.25 was used to select a candidate variable for multilevel multivariable logistic regression analysis [ 51 ]. The results are presented as percentages and odds ratios with 95% confidence intervals (CIs). A p value of 0.05 indicated statistical significance. Four models were run; the first was the intercept-only model, in which no factors were included, following which the intra-cluster correlation coefficient (ICC) was calculated to quantify the proportion of variability in the outcome variable among enumeration areas (EAs) relative to the total variability. The ICC was found to be 0.1524, an indication of substantial clustering or group-level variation, which supports the use of multilevel logistics regression. In the second model, individual-level variables were included, while in the third model, only enumeration area-level variables were included. In the final model, both individual and enumeration area-level independent variables were included. For each model, the ICC, Akaike information criterion (AIC), Bayesian information criterion (BIC), and log-likelihood were calculated to check for model goodness-of-fit. Based on the analyses, the model with a lower AIC and BIC and a higher log-likelihood was selected as the best-fit model, from which the adjusted odds ratio was computed and reported. Ethical Consideration The PMA Ethiopia survey was conducted strictly under the ethical rules and regulations of the World Health Organization and the IIRB of the Ethiopian Health and Nutrition Research Institute (EHNRI). A PMA survey was also conducted after ethical approval was obtained from the Bloomberg School of Public Health at Johns Hopkins University in Baltimore, USA. Since this was just a secondary analysis of the data, which is already in the public domain, we did not need additional approval for this analysis. Nonetheless, we applied for authorization via the PMA website, and on March 14, 2022, access to the data was granted after an evaluation and approval of our request. Results Table 2 presents the sample characteristics and fertility desire across individuals and enumeration area-level independent variables. A little higher than 1 in 5 (22.4%) of women aged 25–29 and their husbands were aged above 45 years (23.7%), whereas 19 percent of all women had secondary and above educational levels, and 33 percent of their husbands were not educated. Women living in rural areas outnumbered their urban counterparts (73.9%), and 64.1% of households had one to five household members. Orthodox Christianity was identified as the most common religion (40.4%), followed by Muslims (32.3%), while nearly 1 in 2 (43.8%) women fall into the bottom wealth quintile, and 43.2% reside in the Oromia region. One in five (23.63) had six or more live births, while 72.9 percent reported that they had ever used FPs. Nearly 1 in 7 women (15.1%) said they married more than once, though 1 in 10 women (10.4%) indicated that they were in polygamous marriage. Table 2 Sample characteristics and fertility desire across individuals and enumeration area-level independent variables, PMA 2021 (weighted, n = 4,138) Variables Weighted Freq. Weighted % Fertility Desire No more Have a child Age 15–19 years 185 4.5 5.7 94.3 20–24 years 717 17.3 4.7 95.3 25–29 years 927 22.4 8.6 91.4 30–34 years 734 17.7 22.2 77.8 35–39 years 748 18.1 36.9 63.1 40–44 years 479 11.6 60.3 39.7 45–49 years 348 8.4 62.6 37.4 Husband/Partner Age 16 to 34 years 1542 37.5 6.9 93.1 35 to 45 years 1596 38.8 28.1 71.9 45 above years 974 23.7 51.9 48.1 Education No Education 1744 42.2 36.3 63.7 Primary 1607 38.8 22.0 78.0 Secondary Plus 787 19.0 10.5 89.5 Partner Education No Education 1355 33.0 33.6 66.4 Primary 1667 40.6 25.7 74.3 Secondary Plus 1085 26.4 16.3 83.7 Religion Orthodox 1646 40.4 28.5 71.5 Protestant 1115 27.3 26.7 73.3 Muslim 1318 32.3 21.0 79.0 wealth quintile Lower quintile 1811 43.8 29.6 70.5 Middle quintile 772 18.7 29.2 70.9 Higher quintile 1555 37.6 19.9 80.1 Marriage type Monogamy 3702 89.6 25.1 74.9 Polygamy 429 10.4 32.3 67.7 Parity Two and below births 1490 39.1 8.8 91.2 Three to five births 1427 37.4 30.6 69.4 Six or more births 895 23.5 54.7 45.3 FP Knowledge Poor Knowledge 2016 48.7 27.5 72.5 Good Knowledge 2120 51.3 24.2 75.8 FP information No Information 2541 61.5 28.2 71.8 Have an Information 1594 38.5 22.0 78.0 Husband forced pregnancy Not Forced 3721 90.2 27.1 72.9 Forced 407 9.9 13.3 86.7 Family Size 1 to 5 members 2651 64.1 18.4 81.6 Above 5 members 1487 35.9 39.2 60.8 Age at first sex 10 to 15 years 1354 33.0 34.1 65.9 16 to 18 years 1606 39.2 25.3 74.7 19 and above 1143 27.9 16.6 83.4 Marriage History Only once 3512 84.9 25.1 74.9 More than once 626 15.1 30.0 70.0 Visited facility No 1733 41.9 28.8 71.2 Yes 2402 58.1 23.7 76.3 FP ever used No 1122 27.1 21.5 78.5 Yes 3015 72.9 27.4 72.6 Regions Other Regions 315 7.6 16.1 84.0 Amhara 1006 24.3 24.1 75.9 Oromia 1789 43.2 29.3 70.8 SNNPR 814 19.7 25.4 74.6 A. Ababa/D. Dawa 215 5.2 21.7 78.3 Residence Urban 1080 26.1 18.2 81.8 Rural 3058 73.9 28.6 71.4 The fertility desire to have a child was high among the higher wealth quantile (80.1%), women with secondary and above educational levels (89.5%), those whose partners had a higher level of education (83.7%), women aged 20–24 (95.3%), urban residents (81.8%), women who had two or fewer live births (91.2%), and women from other regions (84%). A similar observation was made among women aged at first sex above twenty (83.4%), those with 1–5 family sizes (81.6%), Muslims (79%), and those who were forced to become pregnant by their partners (86.7%). Table 3 Prevalence of fertility desire with 95% CI (weighted n = 4138) Dependent Variable Freq. (W) Prevalence [95%_Conf Interval] No more/prefer no child 1070 0.259 0.234 0.285 Have a/another child 3068 0.741 0.715 0.766 Table 3 shows the weighted prevalence of fertility desire with 95% CIs. Approximately three-quarters, 74.1% (95% CI; 71.5% − 76.6%), of reproductive-aged married/cohabiting women in Ethiopia desired to have a child, whereas 25.9% (95% CI; 23.4% − 28.5%) preferred not to have a child. Table 4 Results of multilevel binary logistic regression analysis of the determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia, PMA 2021. Variables Null Model Model II AOR 95% CI Model III AOR 95% CI Model IV AOR 95% CI Age 15–19 years 1 1 20–24 years 0.91 (0.24–3.49) 0.92 (0.24–3.52) 25–29 years 0.81 (0.2–3.37) 0.82 (0.2–3.4) 30–34 years 0.47 (0.1–2.12) 0.48 (0.11–2.17) 35–39 years 0.24 (0.05–1.07) 0.25 (0.05–1.11) 40–44 years 0.1 (0.02–0.48) 0.1 (0.02–0.51)** 45–49 years 0.09 (0.02–0.42) 0.09 (0.02–0.42)** Husband/Partner Age 16 to 34 years 1 1 35 to 45 years 0.66 (0.41–1.06) 0.65 (0.4–1.05) 45 above years 0.54 (0.3–0.99) 0.53 (0.29–0.96)** Education No Education 1 1 Primary 1.1 (0.84–1.45) 1.12 (0.85–1.47) Secondary Plus 1.68 (1.02–2.77) 1.74 (1.04–2.92)** Partner Education No Education 1 1 Primary 1.14 (0.83–1.55) 1.17 (0.86–1.6) Secondary Plus 1.02 (0.6–1.72) 1.06 (0.63–1.79) Religion Orthodox 1 1 Protestant 1.03 (0.72–1.47) 1.05 (0.7–1.56) Muslim 2.16 (1.48–3.18) 2.31 (1.56–3.42)*** wealth quintile Lower quintile 1 1 Middle quintile 0.82 (0.59–1.13) 0.84 (0.61–1.15) Higher quintile 0.73 (0.48–1.11) 0.9 (0.56–1.45) Marriage type Monogamy 1 1 Polygamy 0.87 (0.57–1.31) 0.9 (0.59–1.37) Parity Two and below births 1 1 Three to five births 0.51 (0.34–0.78) 0.5 (0.33–0.77)*** Six or more births 0.27 (0.16–0.45) 0.27 (0.16–0.45)*** FP Knowledge Poor Knowledge 1 1 Good Knowledge 1.08 (0.83–1.41) 1.09 (0.83–1.43) FP information No Information 1 1 Have an Information 1.28(0.96–1.71) 1.32 (0.99–1.76) Husband forced pregnancy Not Forced 1 1 Forced 2.55 (1.71–3.8) 2.48 (1.67–3.68)*** Family Size 1 to 5 members 1 1 Above 5 members 0.61 (0.45–0.83) 0.62 (0.45–0.84)*** Age at first sex 10 to 15 years 1 1 16 to 18 years 1.18 (0.85–1.63) 1.22 (0.88–1.7) 19 and above 1.69 (1.13–2.53) 1.79 (1.19–2.7)*** Marriage History Only once 1 1 More than once 1.21 (0.82–1.8) 1.17 (0.78–1.75) Visited facility No 1 1 Yes 0.97 (0.75–1.26) 0.96 (0.74–1.25) FP ever used No 1 1 Yes 0.53 (0.38–0.74) 0.52 (0.37–0.71)*** Regions Other Regions 1 1 Amhara 0.6 (0.31–1.14) 1.1 (0.43–2.79) Oromia 0.43 (0.23–0.83) 0.44 (0.18–1.05) SNNPR 0.54 (0.28–1.04) 0.93 (0.38–2.29) A. Ababa/D. Dawa 0.42 (0.2–0.85) 0.5 (0.2–1.27) Residence Urban 1 1 Rural 0.52 (0.38–0.71) 1.47 (0.87–2.47) Var (EA) 0.59 1.04 0.48 0.87 ICC EA_ID 0.152 0.241 0.127 0.208 Loglikelihood -2277.72 -1527.36 -2261.15 -1513.52 AIC 4559.45 3114.74 4536.31 3097.05 BIC 4572.10 3300.85 4580.60 3314.18 *= p value < 0.05 ** = p value < 0.01 *** = p value < 0.001 Table 4 presents the multilevel binary logistic regression modeling results on the determinants of fertility desire among reproductive-age married women in Ethiopia. With an EA-level variance of 59%, the null model of the random effects revealed statistically significant variations in the odds of fertility desire to have a child. Furthermore, variations across EAs were explained by 20.8% of the overall variability in the fertility desire to have a child, according to the final model's intraclass correlation coefficient (ICC). When comparing the models, the best-fitting model is model IV, which has a higher log-likelihood (-1513.52) and the lowest AIC and BIC (3097.05) and (3314.18), respectively. Conditional on EA-level random effects, the odds of fertility desire to have a child varied across categories for age, education, religion, and age at first sex. Women who reported having a forced pregnancy by their husband or partner, who were followers of the Muslim religion, who were aged 19 and above at first sex, and who had attained secondary or higher education were found to have higher odds of having a desire to have a child. However, women who reported 40 years of age or older, partner’s age 45 years or older, who had three or more live births, who had a family size of five or more members, and who had ever used FPs were found to have lower odds of having a desire for fertility. Based on the final fitted model, an increase in women aged 40–44 years and 45–49 years was found to decrease the odds of fertility desire to have a child (AOR: 0.1 (95% CI: 0.02–0.51)) compared with women aged 15–19 years. Similarly, women who reported a husband/partner age greater than 45 years were found to have 47% (AOR: 0.53 (95% CI: 0.29–0.96)) lower odds of fertility desire to have a child compared with a husband/partner aged 16–34 years. The odds of fertility desire to have a child were 73% lower among reproductive-aged women who had six or more live births (AOR: 0.27 (95% CI: 0.16–1.45) and 50% (AOR: 0.5 (95% CI: 0.33–0.77) less odds among three to five live births,) than among reproductive-aged women who had two or fewer live births. Similarly, a family size of more than five members lowers the odds of fertility desire to have a child by 38% (AOR: 0.62 (95% CI: 0.45–0.84)) compared to one to five family members. Similarly, the fertility desire to have a child was 48% lower odds among reproductive-aged women who had ever used FPs (AOR: 0.52 (95% CI: 0.37–0.71)) than among reproductive-aged women who had never used FPs. In contrast, compared with women who attended no formal education, those who had more than a secondary plus level of education (AOR: 1.74 (95% CI: 1.04–2.92)) had increased odds of fertility desire to have a child. The odds of fertility desire to have a child were 2.31 (AOR: 2.31 (95% CI: 1.56–3.42)) times greater among reproductive-age women who follow the Muslim religion than among women who follow the Orthodox religion. Similarly, the odds of fertility desire to have a child were 2.48 (AOR: 2.48 (95% CI: 1.67–3.68)) times greater among women who were forced to become pregnant by their husband or partner than among women who were not forced. In addition, women who reported being 19 years of age or older at first sex were found to have greater odds of having a desire to have a child (AOR: 1.79 (95% CI: 1.19–2.7)) than women 10 to 15 years of age at first sex. Discussion High fertility desire is often one of the primary causes of rapid population growth, and it plays a predominant role in explaining current fertility trends [ 19 , 43 ]. Therefore, it is critical to concentrate on issues linked to the fertility desire to have a child to predict fertility behavior and restrict population growth [ 20 ]. Hence, in the midst of a rapid increase in the population of Ethiopia, this study determined and identified the determinants of fertility desire to have a child among reproductive-age married or cohabiting women in Ethiopia, thereby generating up-to-date national-level evidence to preserve such rapid population growth. Accordingly, nationally, 74.1% (95% CI; 71.5–76.6%) of women desire to have a child, while 25.9% (95% CI; 23.4–28.5%) of women reported that they desire not to have any more children. This finding is comparable to that of Senegal (74.1%), Cote d’Ivoire (75.8%), Burkina Faso (72.8%), Congo DR (72.8%), and Comoros (72.2%) in a previous study conducted in SSA countries [ 35 ]. However, this number is higher than that reported in other studies conducted in Ethiopia, Uganda, Nigeria, and Ghana [ 26 , 30 , 36 – 38 , 41 , 52 ], and it is also lower than that reported in studies conducted in Niger and other SSA countries [ 35 , 53 ]. Multiple possible explanations may account for this disparity in each study. However, differences in outcome variable measurement, study period, sample size, and categories of the outcome variable might be related to the study setting. Existing conditions, such as differences in sociocultural norms and expectations regarding family size, differences in economic conditions, government policies related to family planning, and disparities in access to contraception services and health care infrastructure, may also contribute to these differences [ 54 – 56 ]. The analysis indicated that fertility desire to have a child is associated with a woman's and her partner's age in Ethiopia. As indicated in this study, older women (aged 40–49) were found to have lower odds of having a child than were their younger (aged 15–19) counterparts; similarly, women who reported a partner age greater than 45 years were found to have lower odds of desire to have a child. Such differences in fertility desires might be linked to several conditions. Biological reasons play a role since fertility decreases with age, and older women and older partners may prioritize their health and vitality, and they may prefer to focus on their existing family needs rather than extending it. Economically, raising children involves expenses related to school, healthcare, and other essentials [ 57 ]. Older women and older partners may emphasize their current family’s well-being and may have fulfilled their desired family size or concentrated on other life priorities. Additionally, studies conducted on the effect of advanced paternal age on fertility have shown that advanced paternal age is associated with reduced fertility and a greater risk of genetic abnormalities in offspring [ 58 , 59 ]. This finding is in line with studies in Uganda, Niger, Ghana, Nigeria, Guatemala, and Ethiopia [ 26 , 30 , 35 – 38 , 41 , 52 , 53 , 60 , 61 ]. In line with previous studies [ 35 , 53 , 61 , 62 ], parity was found to be associated with lower odds of fertility desire to have a child. Women who had three or more live births were more likely to have a reduced fertility desire to have a child than women who had two or fewer live births. Similarly, having a family size of more than five individuals reduces the likelihood of desiring to have a child compared to families with one to five members. This is in line with a study conducted in Asia [ 63 ] and a qualitative study conducted in South Africa and Malawi [ 22 ]. A possible explanation for these results could be that women who have experienced multiple pregnancies may be more aware of the physical and emotional challenges associated with childbirth and may choose to limit further pregnancies. With each additional pregnancy, women may face increased physical discomfort, such as nausea, fatigue, and stiffness [ 64 ]. Additionally, such women may have reached or exceeded their desired family size and might be worried about parental resources such as time, energy, and financial stability, which will become more pronounced with each additional child. As a result, women who have had three or more live births may feel overwhelmed and less inclined to have an additional child. Furthermore, women who have ever used family planning are less likely to desire to have a child. This confirms earlier research [ 26 , 35 , 36 , 38 , 44 , 56 , 65 ]. The probable explanation is that women who are using family planning might not want to give birth to additional children, may be at different stages in their lives with different priorities and goals, and may adopt several mechanisms to achieve this goal, including the use of family planning. John Bongaarts (2020) also reported that family planning programs can reduce desired fertility, which implies and suggests that their impact can be significant [ 55 ]. Similarly, Caldwell (2005) also indicated that one of the causes of Asian fertility decline was strong government family planning programs [ 66 ]. Women who have more than a secondary level of education have increased odds of fertility desire to have a child. This could result from both better-favorable positions among secondary-plus educated people and a lack of resources among individuals with no education [ 67 ]. Women who have more than a secondary plus level of education may be more likely to prioritize their career or educational goals at an earlier age, leading them to delay having children. They may, however, be more ready to start a family if they achieve stable employment or complete their educational objectives. Similarly, they may have greater awareness of the biological limitations of fertility and the potential risks associated with delaying childbirth. Consequently, they may feel a sense of urgency to have children before the decline in fertility due to old age becomes worrying. Testa (2014), in her article on the positive correlation between education and fertility intentions in Europe, argued that women in Europe who spend more resources on human capital do not necessarily plan to have fewer children than their less educated counterparts [ 65 , 68 ]. Hashemzadeh M. (2021), in his systematic review, stated that in nations where there are more options for women to acquire high levels of education, other structural conditions impacting fertility are also available, such as life satisfaction, feelings of well-being, and levels of trust [ 69 ]. Accordingly, studies conducted in Guatemala, Ethiopia, and Uganda also reported similar findings [ 26 , 30 , 38 , 41 , 60 ]. However, these results contrast with earlier studies showing that higher education is associated with lower fertility desire [ 19 , 35 – 37 ]. The discrepancy might be attributed to differences in the study population, design, and measurement; moreover, further study is required to examine the association between the level of education and fertility desire in this population group. Consistent with the literature, women's religion was found to be associated with fertility desire [ 19 , 36 , 38 , 52 , 61 , 70 ]. The likelihood of fertility desire to have a child was greater among women of the Muslim religion. According to social identity theory, an individual’s sense of identity is shaped by his or her membership in social groups, such as religious or cultural communities [ 71 ]. A recent qualitative analysis performed by Abdi et al. [ 72 ] in two Muslim communities in Kenya indicated that Muslim women prefer the desire for more children since they believe that children are a blessing from God and a source of joy. Cranney (2015) also reported that religion is positively associated with fertility desire and that more religious people tend to have greater desires than nonbelievers [ 73 ]. Other factors that were found to significantly increase fertility desire to have a child were age at first sex and forced pregnancy. There is an expectation or preference to delay the age of entry into sexual intercourse and childbearing until certain milestones, such as the completion of education, marriage, or employment, are reached in most Ethiopian cultures and social contexts [ 74 ]. Women who adhere to these norms by delaying age at entry into sexual intercourse may also be more likely to express a desire to have children when they feel it aligns with societal expectations or personal aspirations. Similarly, women who delay their sexual debut may be more selective in choosing their partners and establishing committed relationships. They can prioritize partners who share their values and family formation goals, making them more likely to express a desire for children in the context of stable and supportive relationships [ 75 , 76 ]. Women who are forced into pregnancy may have limited autonomy and control over their own reproductive decisions. This can indicate a significant power imbalance within the relationship. This imbalance may extend to other aspects of the relationship, where the partner exerts control over the woman's reproductive choices. In such cases, a partner's pressure may influence the woman's desire to have a child rather than her own preferences [ 25 , 34 , 77 , 78 ]. A qualitative study conducted in Malawi and South Africa revealed that women in both cultures expressed the assumption that all marriages produce babies, and married women generally reported being unable to oppose a husband’s ambition and request for sex or pregnancy [ 22 ]. The study is effective since it utilizes nationwide datasets and uses a multistage sampling technique to choose participants. Therefore, the findings may be generalized to all Ethiopian women of reproductive age. Despite these strengths, it is impractical to show the trend and impossible to include the Tigray region because of the existing conflict. Conclusion Nearly three-quarters of married or cohabiting women of reproductive age in Ethiopia reported a desire to have a child. The prevalent high-fertility desire to have a child in Ethiopia hinders the quick reduction of fertility rates and calls for the implementation of multifaceted strategies that preserve this high-fertility desire. Accordingly, sociocultural and demographic variables were determined to influence the desire for children among married women of reproductive age in Ethiopia. Women who had been forced into pregnancy by their spouse, identified as Muslim, were 19 years of age or older at first sexual intercourse and had completed secondary school or above were considerably more likely to desire to have a child. Women aged 40 and above, with partners aged 45 and above, who have had three or more live births, who have a family size of five or more members, and who have used family planning were found to have a decreased likelihood of having a child. Understanding these interactions is vital to developing successful fertility programs and policies specifically designed for different populations, keeping in mind determinants such as age, education level, and religious affiliation. Education about reproductive rights and family planning alternatives should be prioritized, particularly for young women and members of underprivileged communities. Adopting interventions that support women's autonomy in making reproductive decisions and gender equality will help solve the problem of forced pregnancy. Everyone's access to and use of family planning options increase, especially for those who would rather have fewer children. Interventions and messaging that speak to a range of religious and cultural groups should be created. Accordingly, these determinants should be critically taken into account by specific public health interventions to control fertility, as well as those aimed at designing and strengthening existing fertility programs at the regional and national levels. Abbreviations AIC Akaike information criterion AOR Adjusted Odds Ratio BIC Bayesian Information Criteria CI Confidence interval CSA Central Statistical Agency DHS Demographic and Health Survey EA Enumeration areas FP Family Planning HSTP Health Sector Transformation Plan ICC Intracluster correlation coefficient PMA-ET Performance Monitoring for Action Ethiopia RH Reproductive Health SDG Sustainable Development Goal SSA Sub-Saharan Africa VIF Variance Inflation Factor Declarations Ethics approval and consent to participate This study involved a secondary analysis of deidentified data from the PMA in Ethiopia. The PMA Ethiopia survey was conducted strictly under the ethical rules and regulations of the World Health Organization and IIRB of the Ethiopian Health and Nutrition Research Institute (EHNRI). Informed consent was obtained from the respondents. PMA was also administered after ethical approval was obtained from the Bloomberg School of Public Health at Johns Hopkins University in Baltimore, USA. Consent for publication N/A not applicable Availability of data and materials The datasets generated during the study are publicly available from the PMA website. https://www.pmadata.org/data/request-access-datasets. Competing interests The authors declare that they have no competing interests. Funding The authors did not obtain any funding. Author contributions FT conceptualized the study, obtained and analyzed the data, wrote the original and final drafts of the manuscript, interpreted the results and critically revised the final manuscript. SA contributed to the conceptualization of the study, analyzed and interpretation of the results and critically reviewed the final manuscript. FT and SA also participated in field work implementation and project facilitation. KM contributed to the conception of the idea and critically reviewed the final manuscript, including language and grammar corrections and editions. All authors reviewed and approved the final manuscript. Acknowledgments The authors express gratitude to the PMA project for granting permission and supplying the data for further analysis. We acknowledge the PMA Ethiopia project data-collecting team members and research participants. References Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). World Population Prospects 2022: Summary of Results. 2022. United Nations Department of Economic and Social Affairs PD. World Population Prospects 2022: Summary of Results. UN DESA/POP/2022/TR/NO. Volume 3. UN; 2022. Kesetebirhan AJFDRE. Ministry of Health. National guideline for family planning services in Ethiopia. 2011:20 – 3. Workie NW, Ramana GN. The health extension program in Ethiopia. 2013. Assefa Y, Gelaw YA, Hill PS, Taye BW, Van Damme W. 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Evid PMA Ethiopia. 2024;19(2):e0298516. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4142531","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":282442255,"identity":"c34e1601-8c2a-49d2-b524-ce672e161059","order_by":0,"name":"Fitsum Tariku Fantaye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYHACgwMMBUCKmfnggw8VYEYDEVoMgBQ7W7LhjDMgLYyEtYARAz+PmTRnG0iAgBZ59+aNB38Y2CT2MwO1MM6rjeZvB2r5UbENpxbDM8cKDvMYpCXObGYrti7cdjx3xmHGBsaeM7dxa5mRY3CYweCwscFh5o23Z247ltsA1MLM2IZfC9Bhh43tgRqleeccy51PSIu8RI7BAR6Dw3IGzCxG0rwNNbkbCGkx4IH4RU7iMCiQjx3I3QjUchCfX+Tbmzd//FFhw8PffxgYlTV1ufPOAxk/KvDYcgCVfxhMHsBQh2xLAyq/Dp/iUTAKRsEoGKEAAIrLXg0VAuebAAAAAElFTkSuQmCC","orcid":"","institution":"FTF Research Consulting PLC","correspondingAuthor":true,"prefix":"","firstName":"Fitsum","middleName":"Tariku","lastName":"Fantaye","suffix":""},{"id":282442257,"identity":"a6a5ecd3-ff96-454d-82ac-f4f444cb766f","order_by":1,"name":"Solomon Abrha Damtew","email":"","orcid":"","institution":"Wolaita Sodo University","correspondingAuthor":false,"prefix":"","firstName":"Solomon","middleName":"Abrha","lastName":"Damtew","suffix":""},{"id":282442259,"identity":"37625c33-b3fc-4f7a-a37b-00034e6c7633","order_by":2,"name":"Kelemua Menegesha Sene","email":"","orcid":"","institution":"Kotebe University of Education","correspondingAuthor":false,"prefix":"","firstName":"Kelemua","middleName":"Menegesha","lastName":"Sene","suffix":""}],"badges":[],"createdAt":"2024-03-21 09:57:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4142531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4142531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53429463,"identity":"1587ac30-5f69-4263-a0f0-5d17aa8fc74d","added_by":"auto","created_at":"2024-03-25 21:56:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":529269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4142531/v1/487088cc-e13a-435c-9ebb-3c66355eb306.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia: an analysis of PMA-ET 2021 data","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, there has been a shift from a traditional to a transitional pattern, which has led to a decline in fertility rates, and for the first time since 1950, the overall population growth rate dropped below one percent per year in 2020 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, recent United Nations projections indicate that the world population will reach 8.5\u0026nbsp;billion in 2030 and 9.7\u0026nbsp;billion in 2050. Similarly, between 2022 and 2050, the population of sub-Saharan Africa (SSA) may double, surpassing 2\u0026nbsp;billion inhabitants by the end of the 2040s [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Remarkably, in 2022, SSA had the largest annual population growth rate among the eight world sustainable development goal (SDG) regions, at 2.5%, or double the global annual average of 0.8% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Ethiopia, although many activities have been performed to control rapid population growth and reduce the average number of births per woman [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], in the last decade, it has not been feasible to achieve the desired level of change, as was planned and intended in the national health sector transformation plane (HSTP) and reproductive health (RH) strategies [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Both the annual population growth and fertility rate remain high at 2.7 and 4.6, respectively [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRapid population growth can exacerbate the challenge of eradicating poverty (SDG 1) and put more pressure on already depleted resources, thereby creating a greater challenge to ensure sustainable development goals (SDGs) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Studies show that if the current population increases by 40%, the economy, food production, general environment, and global climate will be severely affected [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFertility is among the fundamental aspects influencing population dynamics [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and women\u0026rsquo;s fertility desire is one of the key elements of fertility since it can be a precursor to actual fertility performance, an instructive tool for discovering overall fertility patterns and important for understanding future reproductive behaviors [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A woman's fertility desire is the number of children she would like to have in the near future based on her own assessment of the costs and benefits of childbearing [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFertility desire can be influenced by several factors that operate at the societal and individual levels. At the societal level, the desire for fertility is often driven by social and cultural pressures and the desire to maintain the stability of society [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], such as strong cultural preferences for large families [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and the desire for boys over girls [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. At the individual level, characteristics including age [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], number of living children [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], marital status, wealth, education level [\u003cspan additionalcitationids=\"CR36 CR37 CR38\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and place of residence [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and others [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] are associated with fertility desire. Although numerous factors have been shown to influence fertility desire in different parts of the world, there is a relative dearth of literature in Ethiopia and many other sub-Saharan African countries, and more than half of women who have several children still desire to have more [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA thorough understanding of fertility desire and its determinants at the aggregate level will help to design and implement public policy initiatives such as family planning (FP) programs and provide helpful resources for understanding fertility patterns, as family planning initiatives are unlikely to succeed if the desired fertility does not decrease [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It will also be important to take meaningful steps to sustain development and human well-being, including investing in reproductive health services and contraceptive technologies to slow and eventually change population growth, thereby creating socioeconomic structural transformation within society [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This provides an opportunity to comprehend the determinants influencing fertility desire among married or cohabiting women, who make up more than half of the adult population in Ethiopia.\u003c/p\u003e"},{"header":"Methods and data sources","content":"\u003cp\u003eThis analysis used cross-sectional data from Performance Monitoring for Action Ethiopia (PMA-ET) 2021, which was conducted November 2021 to January 2022 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The rationale for using PMA data includes the fact that, currently, PMA data are the best available recent and real-time data on reproductive, maternal, and newborn health indicators to inform national and regional government priorities and policies. In addition, the PMA collects data via resident enumerators using smartphones with customized ODK applications, which facilitates real-time data collection and timely feedback in correcting errors.\u003c/p\u003e \u003cp\u003ePMA-ET 2021 A cross-sectional survey with a two-stage cluster design and urban‒rural and major regions as strata was used. A total of 243 enumeration areas (EAs) were selected from the master sample frame of the Central Statistical Agency (CSA). A complete census was conducted in the selected enumeration areas, followed by a selection of 35 households per enumeration area using simple random sampling. All reproductive-age women aged 15\u0026ndash;49 who reside in the selected households and guests who slept there the night before the survey were interviewed after the household survey. A total of 8,365 households (98.9%) and 7,988 women (98.8%) completed the cross-sectional survey [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. A detailed description of the sampling procedure and other methodological issues are provided in a previous report [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe PMA-ET offers important data that may be used to track health developments in crucial areas of the Ethiopian health system, such as family planning, women and girls\u0026rsquo; RH empowerment, sexual violence, the quality of contraceptive counseling, vaccination, and other relevant newborn and maternal health data. It is executed by Addis Ababa University\u0026rsquo;s School of Public Health in collaboration with the Ethiopian Public Health Association with assistance from the Federal Ministry of Health, the Central Statistical Agency, and the Bill \u0026amp; Melinda Gates Institute for Population and Reproductive Health (Johns Hopkins Bloomberg School of Public Health).\u003c/p\u003e \u003cp\u003eFor this analysis, out of the 8203 reproductive-age women included in the survey, 2951 women who were not married or cohabiting at the time of the survey were dropped at the initial step. After the exclusion of 662 pregnant women and 430 women who reported being sterilized, who did not know/undecided about fertility desire, who could not become pregnant, who had missing values or incomplete survey results leaving, an unweighted sample size of 4160.\u003c/p\u003e \u003cp\u003eThus, a sample of 4160 married or cohabiting individual women between the ages of 15 and 49 who are currently not pregnant and who were suitable for our analysis for our purpose were selected. Sampling weighting factors were applied to the data files to ensure that the computed results would be proportional at the national level, resulting in a final weighted sample size of 4138 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDependent Variable\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e\"Women\u0026rsquo;s fertility desire\" was the study's outcome variable. Although population specialists have been notably unsuccessful in reaching an agreement on the most appropriate way to measure fertility desire, virtually the majority of fertility surveys, including demographic and health surveys (DHSs), conducted in recent decades have used consistent measurements [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The dependent variable \u0026ldquo;Would you like to have a/another child or would you prefer not to have any/any more children?\u0026rdquo;, with five response categories, was dichotomized into two to calculate the outcome variables \"No more/prefer no children\u0026thinsp;=\u0026thinsp;0\" (for married/cohabiting reproductive age women who reported that she prefers not to have any/any more children) and \"Have a/another child\u0026thinsp;=\u0026thinsp;1\" (for married/cohabiting reproductive age women who reported that she prefers to have a/another child) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The reason for the exclusion of the remaining categories of \u0026ldquo;undecided/do not know\" and \"no response\" was that they did not specify their preferred fertility desire, and those who said they \"cannot become pregnant\" were unlikely to become pregnant. It was necessary to exclude them from the sample for these reasons to avoid obtaining biased estimates.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of the dependent variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eWomen\u0026rsquo;s Fertility Desire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eQuestion \u0026amp; Responses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFertility Desire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eWould you like to have a/another child, or would you prefer not to have any/any more children?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHave a/another child\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Have a/another child\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo more/prefer no child\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;=\u0026thinsp;No more/prefer no child\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSays she can\u0026rsquo;t get pregnant\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eExcluded categories\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUndecided/Don\u0026rsquo;t know = -88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo response = -99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eIndependent Variable\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eAfter reviewing the related literature, possible determining factors correlated with fertility desire were extracted from the survey data. Independent variables were broadly classified into individual-level variables and enumeration area-level variables. Individual-level variables included age, education, wealth status, religion, parity, FP ever used, etc. The enumeration area variables are region and residence. The list of potential variables that are correlated with fertility desire and the details of how each of these variables was coded are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eComposite variables were constructed using the Yes or No questions for the \u0026ldquo;FP knowledge\u0026rdquo; and \u0026ldquo;FP information\u0026rdquo; variables. \u0026ldquo;Region\u0026rdquo; was grouped into five categories: \u0026ldquo;other regions\u0026rdquo; represented Afar, Somali, Benishangul, and Gambella, Harari. The remaining regions except Tigray (because of the outbreak of the existing war during the study period, Tigray was not included in the 2021 PMA) were categorized accordingly.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eStatistical analysis\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eMerged household and female respondent datasets were used and annualized by STATA v16. Tabularization was performed for every variable to check the item nonresponse rate and lack of response, which was subsequently excluded from the analysis. These variables were subsequently recoded to create biologically plausible categories. This was followed by checking the distribution of the variable using the mean and proportion whenever appropriate categories were merged to ensure cell sample size adequacy [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrequencies and percentages were computed to characterize the study population. Chi-square test statistics were computed to determine the overall associations of the independent variables with the two categories of fertility desire. It is also used to cross-check cell sample size adequacy.\u003c/p\u003e \u003cp\u003eSample weights determined by using the multistage sampling strategy were considered in all exploratory data analyses [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Multicollinearity among the predictors was checked using the variance inflation factor (VIF), and no sign of multicollinearity was detected. (mean VIF\u0026thinsp;=\u0026thinsp;1.68, maximum VIF\u0026thinsp;=\u0026thinsp;3.20, and minimum VIF\u0026thinsp;=\u0026thinsp;1.02)\u003c/p\u003e \u003cp\u003eMultilevel binary logistic regression was used to identify important predictors of women\u0026rsquo;s fertility desire. In the bivariate analysis, a p value cutoff of 0.25 was used to select a candidate variable for multilevel multivariable logistic regression analysis [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The results are presented as percentages and odds ratios with 95% confidence intervals (CIs). A p value of 0.05 indicated statistical significance.\u003c/p\u003e \u003cp\u003eFour models were run; the first was the intercept-only model, in which no factors were included, following which the intra-cluster correlation coefficient (ICC) was calculated to quantify the proportion of variability in the outcome variable among enumeration areas (EAs) relative to the total variability. The ICC was found to be 0.1524, an indication of substantial clustering or group-level variation, which supports the use of multilevel logistics regression. In the second model, individual-level variables were included, while in the third model, only enumeration area-level variables were included. In the final model, both individual and enumeration area-level independent variables were included. For each model, the ICC, Akaike information criterion (AIC), Bayesian information criterion (BIC), and log-likelihood were calculated to check for model goodness-of-fit. Based on the analyses, the model with a lower AIC and BIC and a higher log-likelihood was selected as the best-fit model, from which the adjusted odds ratio was computed and reported.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEthical Consideration\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe PMA Ethiopia survey was conducted strictly under the ethical rules and regulations of the World Health Organization and the IIRB of the Ethiopian Health and Nutrition Research Institute (EHNRI). A PMA survey was also conducted after ethical approval was obtained from the Bloomberg School of Public Health at Johns Hopkins University in Baltimore, USA. Since this was just a secondary analysis of the data, which is already in the public domain, we did not need additional approval for this analysis. Nonetheless, we applied for authorization via the PMA website, and on March 14, 2022, access to the data was granted after an evaluation and approval of our request.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the sample characteristics and fertility desire across individuals and enumeration area-level independent variables. A little higher than 1 in 5 (22.4%) of women aged 25\u0026ndash;29 and their husbands were aged above 45 years (23.7%), whereas 19 percent of all women had secondary and above educational levels, and 33 percent of their husbands were not educated. Women living in rural areas outnumbered their urban counterparts (73.9%), and 64.1% of households had one to five household members. Orthodox Christianity was identified as the most common religion (40.4%), followed by Muslims (32.3%), while nearly 1 in 2 (43.8%) women fall into the bottom wealth quintile, and 43.2% reside in the Oromia region. One in five (23.63) had six or more live births, while 72.9 percent reported that they had ever used FPs. Nearly 1 in 7 women (15.1%) said they married more than once, though 1 in 10 women (10.4%) indicated that they were in polygamous marriage.\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\u003eSample characteristics and fertility desire across individuals and enumeration area-level independent variables, PMA 2021 (weighted, n\u0026thinsp;=\u0026thinsp;4,138)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeighted Freq.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeighted %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFertility Desire\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo more\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHave a child\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband/Partner Age\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 to 34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35 to 45 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45 above years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.7\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Education\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.4\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ewealth quintile\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarriage type\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonogamy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolygamy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo and below births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree to five births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSix or more births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP Knowledge\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP information\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave an Information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband forced pregnancy\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Forced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily Size\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 5 members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove 5 members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first sex\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 to 15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 to 18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarriage History\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly once\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than once\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVisited facility\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP ever used\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegions\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Regions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA. Ababa/D. Dawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.8\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe fertility desire to have a child was high among the higher wealth quantile (80.1%), women with secondary and above educational levels (89.5%), those whose partners had a higher level of education (83.7%), women aged 20\u0026ndash;24 (95.3%), urban residents (81.8%), women who had two or fewer live births (91.2%), and women from other regions (84%). A similar observation was made among women aged at first sex above twenty (83.4%), those with 1\u0026ndash;5 family sizes (81.6%), Muslims (79%), and those who were forced to become pregnant by their partners (86.7%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of fertility desire with 95% CI (weighted n\u0026thinsp;=\u0026thinsp;4138)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreq.\u0026nbsp;(W)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[95%_Conf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInterval]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo more/prefer no child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave a/another child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the weighted prevalence of fertility desire with 95% CIs. Approximately three-quarters, 74.1% (95% CI; 71.5% \u0026minus;\u0026thinsp;76.6%), of reproductive-aged married/cohabiting women in Ethiopia desired to have a child, whereas 25.9% (95% CI; 23.4% \u0026minus;\u0026thinsp;28.5%) preferred not to have a child.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of multilevel binary logistic regression analysis of the determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia, PMA 2021.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNull Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003cp\u003eAOR 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel III\u003c/p\u003e \u003cp\u003eAOR 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel IV\u003c/p\u003e \u003cp\u003eAOR 95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.24\u0026ndash;3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92 (0.24\u0026ndash;3.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 (0.2\u0026ndash;3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.2\u0026ndash;3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.47 (0.1\u0026ndash;2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48 (0.11\u0026ndash;2.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24 (0.05\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25 (0.05\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1 (0.02\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1 (0.02\u0026ndash;0.51)**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.02\u0026ndash;0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09 (0.02\u0026ndash;0.42)**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband/Partner Age\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 to 34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35 to 45 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66 (0.41\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65 (0.4\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45 above years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54 (0.3\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53 (0.29\u0026ndash;0.96)**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.84\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12 (0.85\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68 (1.02\u0026ndash;2.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.74 (1.04\u0026ndash;2.92)**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Education\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.83\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17 (0.86\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Plus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02 (0.6\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06 (0.63\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (0.72\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.05 (0.7\u0026ndash;1.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.16 (1.48\u0026ndash;3.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.31 (1.56\u0026ndash;3.42)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ewealth quintile\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82 (0.59\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84 (0.61\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.48\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9 (0.56\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarriage type\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonogamy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolygamy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.57\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9 (0.59\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo and below births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThree to five births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51 (0.34\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5 (0.33\u0026ndash;0.77)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSix or more births\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27 (0.16\u0026ndash;0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27 (0.16\u0026ndash;0.45)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP Knowledge\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.83\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (0.83\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP information\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave an Information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28(0.96\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32 (0.99\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband forced pregnancy\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Forced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.55 (1.71\u0026ndash;3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48 (1.67\u0026ndash;3.68)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily Size\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 5 members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove 5 members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61 (0.45\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62 (0.45\u0026ndash;0.84)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first sex\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 to 15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 to 18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18 (0.85\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.88\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.69 (1.13\u0026ndash;2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.79 (1.19\u0026ndash;2.7)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarriage History\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly once\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than once\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21 (0.82\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17 (0.78\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVisited facility\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.75\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.74\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFP ever used\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53 (0.38\u0026ndash;0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52 (0.37\u0026ndash;0.71)***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegions\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Regions\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\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmhara\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\u003e0.6 (0.31\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1 (0.43\u0026ndash;2.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOromia\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\u003e0.43 (0.23\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44 (0.18\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNNPR\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\u003e0.54 (0.28\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.38\u0026ndash;2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA. Ababa/D. Dawa\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\u003e0.42 (0.2\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52 (0.38\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.47 (0.87\u0026ndash;2.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVar (EA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICC EA_ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoglikelihood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2277.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1527.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2261.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1513.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4559.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3114.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4536.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3097.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4572.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3300.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4580.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3314.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e*= p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** = p value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 *** = p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the multilevel binary logistic regression modeling results on the determinants of fertility desire among reproductive-age married women in Ethiopia. With an EA-level variance of 59%, the null model of the random effects revealed statistically significant variations in the odds of fertility desire to have a child. Furthermore, variations across EAs were explained by 20.8% of the overall variability in the fertility desire to have a child, according to the final model's intraclass correlation coefficient (ICC). When comparing the models, the best-fitting model is model IV, which has a higher log-likelihood (-1513.52) and the lowest AIC and BIC (3097.05) and (3314.18), respectively.\u003c/p\u003e \u003cp\u003eConditional on EA-level random effects, the odds of fertility desire to have a child varied across categories for age, education, religion, and age at first sex. Women who reported having a forced pregnancy by their husband or partner, who were followers of the Muslim religion, who were aged 19 and above at first sex, and who had attained secondary or higher education were found to have higher odds of having a desire to have a child. However, women who reported 40 years of age or older, partner\u0026rsquo;s age 45 years or older, who had three or more live births, who had a family size of five or more members, and who had ever used FPs were found to have lower odds of having a desire for fertility.\u003c/p\u003e \u003cp\u003eBased on the final fitted model, an increase in women aged 40\u0026ndash;44 years and 45\u0026ndash;49 years was found to decrease the odds of fertility desire to have a child (AOR: 0.1 (95% CI: 0.02\u0026ndash;0.51)) compared with women aged 15\u0026ndash;19 years. Similarly, women who reported a husband/partner age greater than 45 years were found to have 47% (AOR: 0.53 (95% CI: 0.29\u0026ndash;0.96)) lower odds of fertility desire to have a child compared with a husband/partner aged 16\u0026ndash;34 years. The odds of fertility desire to have a child were 73% lower among reproductive-aged women who had six or more live births (AOR: 0.27 (95% CI: 0.16\u0026ndash;1.45) and 50% (AOR: 0.5 (95% CI: 0.33\u0026ndash;0.77) less odds among three to five live births,) than among reproductive-aged women who had two or fewer live births. Similarly, a family size of more than five members lowers the odds of fertility desire to have a child by 38% (AOR: 0.62 (95% CI: 0.45\u0026ndash;0.84)) compared to one to five family members. Similarly, the fertility desire to have a child was 48% lower odds among reproductive-aged women who had ever used FPs (AOR: 0.52 (95% CI: 0.37\u0026ndash;0.71)) than among reproductive-aged women who had never used FPs.\u003c/p\u003e \u003cp\u003eIn contrast, compared with women who attended no formal education, those who had more than a secondary plus level of education (AOR: 1.74 (95% CI: 1.04\u0026ndash;2.92)) had increased odds of fertility desire to have a child. The odds of fertility desire to have a child were 2.31 (AOR: 2.31 (95% CI: 1.56\u0026ndash;3.42)) times greater among reproductive-age women who follow the Muslim religion than among women who follow the Orthodox religion. Similarly, the odds of fertility desire to have a child were 2.48 (AOR: 2.48 (95% CI: 1.67\u0026ndash;3.68)) times greater among women who were forced to become pregnant by their husband or partner than among women who were not forced. In addition, women who reported being 19 years of age or older at first sex were found to have greater odds of having a desire to have a child (AOR: 1.79 (95% CI: 1.19\u0026ndash;2.7)) than women 10 to 15 years of age at first sex.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHigh fertility desire is often one of the primary causes of rapid population growth, and it plays a predominant role in explaining current fertility trends [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, it is critical to concentrate on issues linked to the fertility desire to have a child to predict fertility behavior and restrict population growth [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Hence, in the midst of a rapid increase in the population of Ethiopia, this study determined and identified the determinants of fertility desire to have a child among reproductive-age married or cohabiting women in Ethiopia, thereby generating up-to-date national-level evidence to preserve such rapid population growth.\u003c/p\u003e \u003cp\u003eAccordingly, nationally, 74.1% (95% CI; 71.5\u0026ndash;76.6%) of women desire to have a child, while 25.9% (95% CI; 23.4\u0026ndash;28.5%) of women reported that they desire not to have any more children. This finding is comparable to that of Senegal (74.1%), Cote d\u0026rsquo;Ivoire (75.8%), Burkina Faso (72.8%), Congo DR (72.8%), and Comoros (72.2%) in a previous study conducted in SSA countries [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, this number is higher than that reported in other studies conducted in Ethiopia, Uganda, Nigeria, and Ghana [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], and it is also lower than that reported in studies conducted in Niger and other SSA countries [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Multiple possible explanations may account for this disparity in each study. However, differences in outcome variable measurement, study period, sample size, and categories of the outcome variable might be related to the study setting. Existing conditions, such as differences in sociocultural norms and expectations regarding family size, differences in economic conditions, government policies related to family planning, and disparities in access to contraception services and health care infrastructure, may also contribute to these differences [\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis indicated that fertility desire to have a child is associated with a woman's and her partner's age in Ethiopia. As indicated in this study, older women (aged 40\u0026ndash;49) were found to have lower odds of having a child than were their younger (aged 15\u0026ndash;19) counterparts; similarly, women who reported a partner age greater than 45 years were found to have lower odds of desire to have a child. Such differences in fertility desires might be linked to several conditions. Biological reasons play a role since fertility decreases with age, and older women and older partners may prioritize their health and vitality, and they may prefer to focus on their existing family needs rather than extending it. Economically, raising children involves expenses related to school, healthcare, and other essentials [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Older women and older partners may emphasize their current family\u0026rsquo;s well-being and may have fulfilled their desired family size or concentrated on other life priorities. Additionally, studies conducted on the effect of advanced paternal age on fertility have shown that advanced paternal age is associated with reduced fertility and a greater risk of genetic abnormalities in offspring [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This finding is in line with studies in Uganda, Niger, Ghana, Nigeria, Guatemala, and Ethiopia [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn line with previous studies [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], parity was found to be associated with lower odds of fertility desire to have a child. Women who had three or more live births were more likely to have a reduced fertility desire to have a child than women who had two or fewer live births. Similarly, having a family size of more than five individuals reduces the likelihood of desiring to have a child compared to families with one to five members. This is in line with a study conducted in Asia [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and a qualitative study conducted in South Africa and Malawi [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A possible explanation for these results could be that women who have experienced multiple pregnancies may be more aware of the physical and emotional challenges associated with childbirth and may choose to limit further pregnancies. With each additional pregnancy, women may face increased physical discomfort, such as nausea, fatigue, and stiffness [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Additionally, such women may have reached or exceeded their desired family size and might be worried about parental resources such as time, energy, and financial stability, which will become more pronounced with each additional child. As a result, women who have had three or more live births may feel overwhelmed and less inclined to have an additional child.\u003c/p\u003e \u003cp\u003eFurthermore, women who have ever used family planning are less likely to desire to have a child. This confirms earlier research [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. The probable explanation is that women who are using family planning might not want to give birth to additional children, may be at different stages in their lives with different priorities and goals, and may adopt several mechanisms to achieve this goal, including the use of family planning. John Bongaarts (2020) also reported that family planning programs can reduce desired fertility, which implies and suggests that their impact can be significant [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Similarly, Caldwell (2005) also indicated that one of the causes of Asian fertility decline was strong government family planning programs [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWomen who have more than a secondary level of education have increased odds of fertility desire to have a child. This could result from both better-favorable positions among secondary-plus educated people and a lack of resources among individuals with no education [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Women who have more than a secondary plus level of education may be more likely to prioritize their career or educational goals at an earlier age, leading them to delay having children. They may, however, be more ready to start a family if they achieve stable employment or complete their educational objectives. Similarly, they may have greater awareness of the biological limitations of fertility and the potential risks associated with delaying childbirth. Consequently, they may feel a sense of urgency to have children before the decline in fertility due to old age becomes worrying.\u003c/p\u003e \u003cp\u003eTesta (2014), in her article on the positive correlation between education and fertility intentions in Europe, argued that women in Europe who spend more resources on human capital do not necessarily plan to have fewer children than their less educated counterparts [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Hashemzadeh M. (2021), in his systematic review, stated that in nations where there are more options for women to acquire high levels of education, other structural conditions impacting fertility are also available, such as life satisfaction, feelings of well-being, and levels of trust [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Accordingly, studies conducted in Guatemala, Ethiopia, and Uganda also reported similar findings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However, these results contrast with earlier studies showing that higher education is associated with lower fertility desire [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The discrepancy might be attributed to differences in the study population, design, and measurement; moreover, further study is required to examine the association between the level of education and fertility desire in this population group.\u003c/p\u003e \u003cp\u003eConsistent with the literature, women's religion was found to be associated with fertility desire [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. The likelihood of fertility desire to have a child was greater among women of the Muslim religion. According to social identity theory, an individual\u0026rsquo;s sense of identity is shaped by his or her membership in social groups, such as religious or cultural communities [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. A recent qualitative analysis performed by Abdi et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] in two Muslim communities in Kenya indicated that Muslim women prefer the desire for more children since they believe that children are a blessing from God and a source of joy. Cranney (2015) also reported that religion is positively associated with fertility desire and that more religious people tend to have greater desires than nonbelievers [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOther factors that were found to significantly increase fertility desire to have a child were age at first sex and forced pregnancy. There is an expectation or preference to delay the age of entry into sexual intercourse and childbearing until certain milestones, such as the completion of education, marriage, or employment, are reached in most Ethiopian cultures and social contexts [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Women who adhere to these norms by delaying age at entry into sexual intercourse may also be more likely to express a desire to have children when they feel it aligns with societal expectations or personal aspirations. Similarly, women who delay their sexual debut may be more selective in choosing their partners and establishing committed relationships. They can prioritize partners who share their values and family formation goals, making them more likely to express a desire for children in the context of stable and supportive relationships [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWomen who are forced into pregnancy may have limited autonomy and control over their own reproductive decisions. This can indicate a significant power imbalance within the relationship. This imbalance may extend to other aspects of the relationship, where the partner exerts control over the woman's reproductive choices. In such cases, a partner's pressure may influence the woman's desire to have a child rather than her own preferences [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. A qualitative study conducted in Malawi and South Africa revealed that women in both cultures expressed the assumption that all marriages produce babies, and married women generally reported being unable to oppose a husband\u0026rsquo;s ambition and request for sex or pregnancy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study is effective since it utilizes nationwide datasets and uses a multistage sampling technique to choose participants. Therefore, the findings may be generalized to all Ethiopian women of reproductive age. Despite these strengths, it is impractical to show the trend and impossible to include the Tigray region because of the existing conflict.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNearly three-quarters of married or cohabiting women of reproductive age in Ethiopia reported a desire to have a child. The prevalent high-fertility desire to have a child in Ethiopia hinders the quick reduction of fertility rates and calls for the implementation of multifaceted strategies that preserve this high-fertility desire. Accordingly, sociocultural and demographic variables were determined to influence the desire for children among married women of reproductive age in Ethiopia. Women who had been forced into pregnancy by their spouse, identified as Muslim, were 19 years of age or older at first sexual intercourse and had completed secondary school or above were considerably more likely to desire to have a child. Women aged 40 and above, with partners aged 45 and above, who have had three or more live births, who have a family size of five or more members, and who have used family planning were found to have a decreased likelihood of having a child.\u003c/p\u003e \u003cp\u003eUnderstanding these interactions is vital to developing successful fertility programs and policies specifically designed for different populations, keeping in mind determinants such as age, education level, and religious affiliation. Education about reproductive rights and family planning alternatives should be prioritized, particularly for young women and members of underprivileged communities. Adopting interventions that support women's autonomy in making reproductive decisions and gender equality will help solve the problem of forced pregnancy. Everyone's access to and use of family planning options increase, especially for those who would rather have fewer children. Interventions and messaging that speak to a range of religious and cultural groups should be created. Accordingly, these determinants should be critically taken into account by specific public health interventions to control fertility, as well as those aimed at designing and strengthening existing fertility programs at the regional and national levels.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAkaike information criterion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBayesian Information Criteria\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentral Statistical Agency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDemographic and Health Survey\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnumeration areas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFamily Planning\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHSTP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Sector Transformation Plan\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntracluster correlation coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePMA-ET\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePerformance Monitoring for Action Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReproductive Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSustainable Development Goal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSub-Saharan Africa\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVariance Inflation Factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study involved a secondary analysis of deidentified data from the PMA in Ethiopia. The PMA Ethiopia survey was conducted strictly under the ethical rules and regulations of the World Health Organization and IIRB of the Ethiopian Health and Nutrition Research Institute (EHNRI). Informed consent was obtained from the respondents. PMA was also administered after ethical approval was obtained from the Bloomberg School of Public Health at Johns Hopkins University in Baltimore, USA.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;N/A not applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during the study are publicly available from the PMA website.\u003c/p\u003e\n\u003cp\u003ehttps://www.pmadata.org/data/request-access-datasets.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing\u0026nbsp;interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors did not obtain any funding.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eFT\u0026nbsp;conceptualized the study, obtained and analyzed the data, wrote the original and final drafts of the manuscript, interpreted the results and critically revised the final manuscript. SA contributed to the conceptualization of the study, analyzed and interpretation of the results and critically reviewed the final manuscript. FT and SA also participated in field work implementation and project facilitation. KM contributed to the conception of the idea and critically reviewed the final manuscript, including language and grammar corrections and editions. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe authors express gratitude to the PMA project for granting permission and supplying the data for further analysis. We acknowledge\u0026nbsp;the PMA Ethiopia project data-collecting\u0026nbsp;team members and research participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePopulation Division of the United Nations Department of Economic and Social Affairs (UN DESA). 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Politics. \u0026lsquo;Motherhood in childhood\u0026rsquo;. Generational change Ethiopia. 2019;3:1\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAriho P, Kabagenyi A. Age at first marriage, age at first sex, family size preferences, contraception and change in fertility among women in Uganda: analysis of the 2006\u0026ndash;2016 period. BMC Womens Health. 2020;20(1):8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNdahindwa V, Kamanzi C, Semakula M, Abalikumwe F, Hedt-Gauthier B, Thomson DRJR. Determinants of fertility in Rwanda in the context of a fertility transition: a secondary analysis of the 2010. Demographic Health Surv. 2014;11(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarber JS, Miller W, Kusunoki Y, Hayford SR, Guzzo KBJPS, Health R. Intimate relationship dynamics and changing desire for pregnancy among young women. 2019;51(3):143\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFantaye FT, Damtew SAJP. Women decision making on use of modern family planning methods and associated factors. Evid PMA Ethiopia. 2024;19(2):e0298516.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"fertility desire, desire for more children, fertility intention, PMA, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-4142531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4142531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn Ethiopia, although many activities have been performed to control rapid population growth and reduce the average number of births per woman, in the last ten years, it has not been feasible to achieve the desired level of change, as was planned and intended in the National Health Sector Transformation Plan (HSTP) and reproductive health (RH) strategies. The annual growth of the population and fertility rates continue to increase at 2.7 and 4.6, respectively. Fertility is one of the fundamental aspects affecting population dynamics, while the fertility desire of women to have children is one of the key elements of fertility and can be a precursor to actual fertility performance, a useful tool for understanding aggregate fertility trends, and important for understanding future reproductive behavior. Women's fertility desire is the number of children they want to have in the next few years, based on their assessment of the costs and benefits of childbearing.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis analysis used cross-sectional data from Performance Monitoring for Action Ethiopia (PMA-ET) 2021. A total of 4138 married or cohabiting individual women between the ages of 15 and 49 who were not pregnant were included in this analysis. Sampling weighting factors and design were applied in this analysis, and chi-square test statistics were computed to determine the overall association and used to assess the adequacy of the cell sample size. Multilevel binary logistic regression was used to identify important predictors of women\u0026rsquo;s fertility desire. The results are presented as percentages and odds ratios with 95% confidence intervals (CIs). Statistical significance was declared at a significance level of 0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eApproximately three-quarters (74.1%, 95% CI; 71.5% \u0026minus;\u0026thinsp;76.6%) of reproductive-aged married/cohabiting women in Ethiopia desired to have a child. Women who reported having a forced pregnancy by their spouse, being of the Muslim religion, being aged 19 and above at first sex, and having attained secondary or higher education were found to be positively and significantly associated with the likelihood of fertility desire to have a child. However, women who reported 40 years of age or older, partner\u0026rsquo;s age 45 years of or older, who had three or more live births, who had a family size of five or more members, and who had ever used FPs were found to have lower odds of having a fertile desire to have a child.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe prevalent high-fertility desire to have a child in Ethiopia hinders the quick reduction of fertility rates and calls for the implementation of multifaceted strategies that preserve this high-fertility desire. Accordingly, sociocultural and demographic variables were determined to influence the desire for children. Understanding these determinants is vital to developing successful fertility programs and policies specifically designed for different populations, prioritizing and adopting interventions that increase everyone's access to and use of family planning options, and messaging that speaks to a range of religious and cultural groups.\u003c/p\u003e","manuscriptTitle":"Determinants of fertility desire among reproductive-aged married/cohabiting women in Ethiopia: an analysis of PMA-ET 2021 data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 21:40:37","doi":"10.21203/rs.3.rs-4142531/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d24c1d98-6859-436c-9a67-b80fcbffd9d9","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-25T21:40:40+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-25 21:40:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4142531","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4142531","identity":"rs-4142531","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}