Status of unintended pregnancy (UP) and contraceptive needs of childbearing age women in Chengdu city

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Methods We conducted a questionnaire survey in five main urban areas of Chengdu. The survey employed a stratified two-stage sampling technique. Descriptive analysis and univariate and multivariate logistic regression analyses were performed to analyze the relationship between the UP and independent variables. In the multivariable analysis, an adjusted odds ratio(aOR) with a 95% confidence interval(CI) was reported to indicate statistical association. Results 1289 women aged 15–44 years were randomly selected and 1230 women completed the survey. Among the respondents, 24.1% had experienced UP. Married women had a 1.665 times higher odds of UP but the risk of UP was 0.528 times lower for 21-25-year-old women. Women with a university or higher level of education were less likely to report UP whereas those with a male partner from a rural area were more likely to report UP. Women with a male partner having a junior college, university or higher education background were less likely to report UP. More than half of the respondents had never received contraceptive education. Almost three in five of the respondents did not receive adequate contraceptive education, 70.41% of the respondents were very willing to accept professional contraceptive guidance. Conclusions Age, marital status, education level of females, and education level and birthplace of their sexual partners are influencing factors for UP among childbearing-aged women in Chengdu. Reproductive health guidance and policies are warranted to reduce the rate of UP in Chengdu. Health sciences/Health care Health sciences/Risk factors Reproductive age Contraception Pregnancy Unintended pregnancy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Unintended pregnancy (UP) is the term used when women did not desire to become pregnant at that time, or ever in the future [ 1 ]. It is usually the outcome of non-use, inconsistent use or incorrect use of effective family planning methods. According to World Health Organization reports, 75 million out of 175 million registered pregnancies were unwanted worldwide [ 2 ]. Approximately 58 UPs per 1000 women occurred each year in East Asia and 61% ended in abortion [ 3 ]. UP is considered one of the most important public health risks. It is a threat for both mother and child health due to the lack of family support, it is among the causes that increase mothers’ mortality and it is a major obstacle to the improvement of reproductive and sexual health [ 4 , 5 ]. Nowadays, there is a broad range of effective contraceptive methods available; however, misunderstandings regarding the availability and safety of emergency contraception cause a small proportion of people not to use them [ 6 ]. Therefore, despite the availability of multiple, effective contraceptive methods, there remains a high rate of UP globally [ 7 , 8 ]. Women need access to accurate information about these different methods in order to choose an option that matches their individual needs regarding lifestyle, family planning, risk factors and non-contraceptive benefits [ 9 , 10 ]. As a city blending tradition with modernity, Chengdu retains the traditional culture that values family and opinions from elders, while also being influenced by the younger generation's pursuit of personal development and diversified lifestyles, creating a complex impact on fertility decisions among childbearing-age women. Additionally, as one of China's new first-tier cities undergoing rapid urbanization, the increasing life pressures and changing social concepts brought about by urbanization may also become significant background factors contributing to unintended pregnancies. To the best of our knowledge, there are no studies investigating the prevalence and associated factors of UP in this region. Therefore, the main objectives of this study were to: (i) identify the prevalence of UP among women aged 15–44 years in five main urban area of Chengdu; (ii) examine the association between socio-demographic/behavioral characteristics and UP; and (iii) understand the contraceptive guidance needs of women of childbearing age and raise suggestions for the further development and provision of high-quality family planning services༎ Methods Study design and setting By using of multi-stage stratified cluster sampling, women of childbearing age were selected from five main urban areas of Chengdu (Jinjiang district, Qingyang district, Chenghua district, Jinniu district and Wuhou district) from April 2023 to February 2024. With the help of community staff, the respondents completed the online questionnaire. Study population Sample size According to the average contraceptive compliance rate 58.07% [ 11 ], the sample size is calculated as 364 people. Considering the non-response rate of 10% and questionnaire inefficiency of 10%, the minimum sample size was 437. A total of 1289 questionnaires were sent out in this time, and 1230 valid questionnaires (95.4%) were finally included after missing items, inconsistent answers and vague answers of key variable values were excluded. Therefore, the sample size of this study meets the requirements. Inclusion and exclusion criteria The inclusion criteria was women of childbearing age (15–44 years) who are sexually active and must be participate voluntarily and living in the five main urban areas of Chengdu mentioned above. The exclusion criteria was women who are less than 14 years or greater than 44 years, or women with no previous sexual activity, or women who are unwilling to participate in this survey. The study was approved by Ethics Committee of the Chengdu Second People's Hospital and performed in accordance with the Declaration of Helsinki, and all participants in the survey have signed an informed consent form. Randomization The survey employed a stratified two-stage sampling technique in order to ensure regional representativeness. First we conducted in five main urban areas of Chengdu. Taking all women of childbearing age (15–44 years old) in the above areas as the survey subjects. And there are more than 8,700 communities with a total population of approximately 6 million. Among them, there are about 860,000 married women of childbearing age (excluding unmarried individuals who are sexually active).Then computer-generated random numbers. A cluster sampling method was used to randomly select target communities. From each selected community residents' committee, simple random sampling was conducted using ID numbers to select 10 individuals as survey subjects, with an additional 3–5 as alternates. When the randomly sampled population does not meet the inclusion criteria, alternates are used to fill in. With the help of the community residents' committee, we contacted the selected individuals by phone. Questionnaire As none of the previously existing questionnaires addressed all of the items needed for our study, we developed a study-specific questionnaire after a thorough review of similarly published reports. Pilot tests on a group of 250 reproductive-aged women who presented for treatment at the gynecology outpatient clinic of Chengdu Second People's Hospital, with participants randomly selected to determine whether the concepts and expressions used in the questionnaire could be easily comprehended. The modified questionnaire consisted of two parts: UP and contraceptive demand. The self-administered questionnaire was programmed online ( https://www.wjx.cn/ ) by scanning a predetermined QR code. We used a secure questionnaire survey platform and limited the scope of data access through access permissions to reduce the risk of information leakage. Additionally, all participants in the survey have signed confidentiality agreements. Statistical analysis Simple descriptive analysis and bivariate and multivariate statistical analyses were performed in this study. Descriptive analysis was commenced to describe the frequency and percentage distribution. Logistic regression was employed because our dependent variable (UP) was measured as a binary factor. Results for the regression analysis have been presented as odds ratio (OR) values, with the corresponding 95% confidence interval (CI) signifying the precision and significance of the reported OR. Any OR of 1 indicates higher odds of UP. The inherent sample weight was applied and all analyses were carried out using STATA version 13.0 software. Results Basic subject information A total of 1289 women aged 15–44 years were randomly selected and 1230 women completed the survey (response rate = 95.4%). Among the 1230 women, 596 (48.5%) were married and 513 (41.7%) were from city areas. More than two-fifths (507; 41.2%) of participants were in the age group between 21 and 25 years. Over half the population (716; 58.2%) had a college degree or higher. Regarding occupation, the largest proportion of respondents (553; 45%) was from service industries, with industries such as managerial, technical and others accounting for 17.8%, 20.8% and 16.4%, respectively (Fig. 1 ). Demographic distribution of UP Figure 2 summarizes the proportion of UP across the included socio-demographic characteristics. More than half of UPs occurred among married women (175; 58.9%), whereas the rate of UP among unmarried, divorced and widowed women gradually decreased: 32.7%, 7.1% and 1.3%, respectively. Women in the 40–44-year age category had a higher proportion of UP (44.6%), whereas the lowest proportion was recorded among women aged 21–25 years (17.6%). Urban residents had 21.4% UP whereas 26.6% occurred among women from rural areas. Approximately 45% UP occurred among women with a primary level of education, whereas women with a higher educational level reported a lower prevalence. Women with a secondary education recorded 31.1% UP whereas only 19.3% occurred among women with a college or higher level of education. About four in ten of UPs (42%) occurred among women from the service industry. Reasons and outcomes of UP The most common reason for UP was unprotected intercourse, followed by incorrect use and having no idea how to use contraception. Approximately half of UPs were terminated by means of abortion; the main reason being that they had no family planning in the short term or because of economic pressure. Less than 8% chose to give birth and three in five had given birth because of external pressure (parents or partners) (Fig. 3 ). Logistic regression results of UP Figure 4 shows the outcome of univariate logistic regression analysis. Divorced and widowed (others) women had significantly higher odds of UP (OR = 2.491; 95% CI = 1.449–4.204), followed by married women (OR = 1.998; 95% CI = 1.504–2.64), compared with the unmarried reference marital status. Higher odds of UP occurred among women aged > 40 years (OR = 1.990; 95% CI = 1.010–4.006), whereas 21–25-year-olds had less risk of UP (OR = 0.527; 95% CI = 0.299–0.959). Compared with women educated to below junior high school level, those with a junior college (OR = 0.524; 95% CI = 0.329–0.834) or university and above level of education (OR = 0.358; 95% CI = 0.240–0.538) had a lower risk of UP. Women in others (agriculture and forestry personnel) were 1.64 times more likely to report UP compared with those in the managerial personal (OR = 1.640; 95% CI = 1.068–2.533). Higher odds occurred among women whose male partners were from urban (OR = 1.465; 95% CI = 1.060–2.021) and rural (OR = 1.848; 95% CI = 1.351–2.527) areas compared with partners from the city. Women of male partners with a junior college (OR = 0.553; 95% CI = 0.347–0.877) or university and above (OR = 0.293; 95% CI = 0.197–0.436) level of education had a significantly lower risk of UP compared with women of partners educated to below junior high school level (Fig. 4 ). Multivariate logistic regression analysis was used to exclude the influence of all the above factors on the results. After adjusting for relevant factors, similar values were found. The results indicated that married women had significantly higher odds of UP (aOR = 1.665; 95% CI = 1.133–2.456) compared with unmarried women; women aged 21–25 years had a lower risk of UP compared with women aged < 20 years (aOR = 0.528; 95% CI = 0.291–0.987); and women educated to university level or above were less likely to experience UP compared with those educated to below junior high school level (aOR = 0.555; 95% CI = 0.352–0.881). Highest odds occurred among women with male partners from a rural area compared with male partners from the city (aOR = 1.455; 95% CI = 1.042–2.027). It was also interesting to find that women whose male partners were educated to junior college (aOR = 0.603; 95% CI = 0.370–0.984) or university level and above (aOR = 0.384; 95% CI = 0.67–0.78) were less likely to have a UP than women of partners educated to below junior high school level (Table 1 ). Table 1 Multivariate hierarchical Logistic regression analysis of UP Variables Groups Unintended pregnancy(Yes/No) β S.E. Z value P value OR(95%CI) Marital status Unmarried 97 1 Married 175 0.510 0.197 2.588 0.010 1.665(1.133–2.456) Others 25 0.388 0.320 1.215 0.224 1.474(0.780–2.737) Female age(years) 40 37 0.132 0.394 0.335 0.738 1.141(0.530–2.493) Female Birthplace City 110 1 Urban 71 0.216 0.183 1.181 0.238 1.241(0.865–1.772) Rural 116 0.244 0.161 1.517 0.129 1.276(0.931–1.748) Female level of education Below junior high school 50 1 Senior high school 50 -0.292 0.258 -1.133 0.257 0.747(0.450–1.238) Junior college 59 -0.367 0.255 -1.442 1.149 0.693(0.421–1.143) University or above 138 -0.589 0.233 -2.522 0.012 0.555(0.352–0.881) Female occupation Managerial 50 1 technicist 56 0.186 0.229 0.811 0.417 1.204(0.770–1.615) Services 125 0.074 0.204 0.365 0.715 1.077(0.726–1.615) Production personal or others 66 0.408 0.232 1.758 0.079 1.503(0.956–2.375) Male Age(years) 40 45 0.593 0.385 1.540 0.124 1.809(0.866–3.950) Male Birthplace City 111 1 Urban 85 0.330 0.175 1.891 0.059 1.391(0.987–1.958) Rural 101 0.375 0.170 2.210 0.027 1.455(1.042–2.027) Male level of education Below junior high school 55 1 Senior high school 55 -0.280 0.252 -1.110 0.267 0.756(0.461–1.238) Junior college 58 -0.505 0.249 -2.026 0.043 0.603(0.370–0.984) University or above 129 -0.957 0.223 -4.287 < 0.001 0.384(0.248–0.596) Male occupation Managerial 57 1 technicist 45 -0.059 0.237 -0.248 0.804 0.943(0.592–1.499) Services 111 -0.130 0.201 -0.648 0.517 0.878(0.593–1.307) Production personal or others 84 0.084 0.212 0.398 0.691 1.088(0.719–1.652) Contraceptive needs Figure 5 shows the contraceptive needs of the respondents. Among the 1230 women, almost 61% did not receive adequate contraceptive education. When grouped by age, the 21–25-year age group accounted for the smallest proportion. In terms of education level, the proportions decreased with the gradual increase in level of education. With regard to marital status, unmarried people had the highest proportion. The main three reasons for the lack of contraceptive education were embarrassment (53.1%), lack of time (43.7%) and ‘do not care’ (22.3%) (Fig. 5 A). The Internet was the most common means of access to contraceptive education (65.6%; 392/598), followed by hospitals (60.4%; 391/598) and schools (57.2%; 342/598); however, 70.41% (866/1230) of respondents were very willing to accept professional contraceptive guidance. Unmarried women, those aged 21–30 years and those with a college education or above were more likely to receive contraceptive guidance. The most acceptable way to access contraceptive guidance was by the use of science manuals (67.48%; 830/1230), followed by gynecological specialist clinics (40%; 492/1230) and community lectures (37.24%; 458/1230) (Fig. 5 B). Discussion UP remains a significant public health concern worldwide. Although evidence suggests that rates of UP have declined worldwide due to increasing access to and use of contraception, there were 121 million UP annually [ 12 ]. Chengdu is a young and new first-tier city in China with a large number of young residents. At present, the aim in this city is to improve post-abortion care services in hospitals. However, this means that those who have sex but have not yet had a UP remain hidden. In addition, women who go to public hospitals for induced abortion are the target population for post-abortion care but there are also many who undergo self-induced drug abortion or spontaneous abortion in private clinics, meaning that some abortions occurring outside of the health sector cannot be captured. With the statistical data missing for these groups, we cannot fully understand the status of UP or the contraceptive needs of women of childbearing age in our city. In this study, by taking the community as the unit and all women of childbearing age in the five main urban areas as the object, we used a self-administered questionnaire survey to understand the current situation of UP, carry out an intervention, prevent UP at an early stage and reduce the incidence of UP in our city. Our study indicated that being married was associated with an increased risk of UP. This result corroborates the results of previous studies by Nyarko et al. [ 13 ]. Who found that married women are more likely to be at risk of UP than those who never married or those who were previously married. They thought that this may be due to the non-use of contraceptives or contraceptive failure, as some married women may believe that contraceptive use has serious side effects while others may believe that it is a sin. Another important explanatory factor for this may be gender inequality among couples: when women are in union, condom use is rarely under their control [ 14 ]. Additionally, male partners hold economic sway and refuse to use condom [ 15 ]. In our opinion, UP can easily occur due to improper or no use of contraception. Consistent and effective use of contraception during each act of intercourse is necessary for married couples to avoid unintended pregnancy (UP). However, it seems that many couples find it difficult to ensure correct use of contraception during every sexual encounter. Therefore, it is necessary to further strengthen the awareness of contraception in couples and family planning should play a greater role. According to the findings of this study, age plays a significant role in the risk of UP among women. In our study, women in other age categories were more likely to experience UP compared to those aged 21–25 years. This finding is in contradiction with previous studies that found women aged 20–34 years to have the highest proportion of UP [ 16 ] and studies that found 15–19 years were more likely to experience UP compared to women in other age categories [ 17 ]. In their opinion, younger women have higher fertility, higher frequency of sexual intercourse, feel shy to take advice about family planning from relatives or family care organizations and have higher contraceptive failure, all of which contributes to UP. From our perspective, education is a powerful individual predictor of human actions; most women in the 21–25-year age group are in school and they are more willing and able to obtain contraceptive knowledge, which may lead to a low rate of UP. Moreover, most of the women aged 21–25 are unmarried and their partner is their boyfriend (but not living together), this also aligns with the findings as mentioned above, that married women have a higher rate of UP. Additionally, the risk of UP is found to be predicted by the education level of the woman. Data in the present study showed that, compared with the women who have no formal education, women who have a college degree or above or have a male partner with a college degree or above are at relatively low risk for UP. Our results are consistent with those of other studies that found women having a husband with no education and primary education were significantly associated with UP [ 18 , 19 ]. Education has the potential to raise women’s consciousness about the implications of UP and possible contraceptive methods that educated women are probably taking advantage of [ 20 ]. Font-Ribera L et al. [ 21 ] also explained that women with some formal education are more empowered to take charge of their sexual and reproductive health matters than women who have no formal education. On the other hand, education has been shown to empower women through career opportunities that often translate into higher socioeconomic status, which, in turn, may increase women’s autonomy and ability to negotiate safer sex practices, including condom use [ 22 ]. Moreover, male partners’ birthplace is significantly associated with the UP of Chengdu women. Data indicated that women whose male partners were from rural areas were 1.5 times odds to have a UP than their urban counterparts. Male partners from rural areas may have low socioeconomic status and perceive a pregnancy as unintended if they feel that they cannot cater for the unborn child with their current socioeconomic standing. The desire to avoid pregnancy did not translate into contraceptive use [ 23 ]. High rates of UP may also be attributable to limited reproductive health education and knowledge. Gaps in contraceptive knowledge directly affect the choice of contraceptive method and the effect of contraception [ 24 ]. Data in our study showed that more than half of the women had never received contraceptive guidance and related education. Furthermore, as the level of education decreases, the unmet need for contraception increases. Additionally, about 70% of the respondents obtained contraceptive education from the Internet rather than from family planning consultation clinics or gynecology-related clinics. It should be pointed out that more than two-thirds said yes when were asked if they would be willing to receive contraceptive education, with the largest groups being unmarried, aged 21–30 years and educated to college level or above. Meanwhile, popular science handbooks, gynecological clinics and community publicity are the most acceptable ways to access contraceptive information. Based on the above situation, the following points are important, from the policy level: (1) establish dedicated reproductive health consultation windows at community health service centers to provide free consultations for women of childbearing age; (2) build an efficient family planning service network covering the entire city; (3) increase supply points for free or low-cost contraceptives (e.g., condoms and short-term oral contraceptives); (4) promote scientific contraception knowledge through multiple channels to change traditional concepts. In terms of specific intervention measures, our suggestions are as follows: (1) create easy-to-understand manuals that include information on contraceptive principles, common contraceptive methods, and their advantages and disadvantages, and distribute them in places where women of childbearing age gather; (2) for economically disadvantaged families, the government can provide subsidies or coupons to reduce the cost of accessing contraceptive resources; (3) design a specialized application to help users understand suitable contraceptive methods for themselves; (4) conduct family planning knowledge training sessions involving both partners to enhance mutual understanding and support. We believe that through the above methods, the situation of UP among women of childbearing age in Chengdu can be improved, and the reproductive and fertility health can be safeguarded. Conclusion The current situation of UP among women of childbearing age in Chengdu is concerning. Age, marital status, education level of females, and education level and birthplace of their sexual partners are influencing factors.There is an urgent need to address the demand for contraceptive guidance among these women. The first step is to popularize contraceptive knowledge in our city. Additionally, it is crucial to emphasize that contraception is not only the responsibility of women, but men also need to participate actively. Limitations Several limitations to our study should be acknowledged. First, there are many urban areas in Chengdu and we only focused on the five major urban areas, which may lead to the survey results failing to accurately reflect the entire population, thus a larger sample size is required. Second, our understanding of men's knowledge of contraception was mainly obtained through questionnaires distributed to women, however, women may not be able to fully understand men's true opinions on contraception, which may lead to information distortion, we should use separate questionnaires for men in order to fully reflect the role of men in UP. Third, in online surveys, respondents may deliberately provide false answers in order to quickly complete the questionnaire, which can lead to bias in data integrity. Declarations Author contributions LMW, FX, and DNS contributed to conception and design of this study. JL and ZLW conducted the data analysis. LMW, LS and TQW contributed to writing and revising the final manuscript. All authors read and approved the final manuscript. Data availability Raw data are not publicly available to preserve individuals’ privacy. The datasets used during the current study available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Participate declaration Informed consent was obtained from all participants. References Grindlay, K., Seymour, J., Fix, L. & Grossman, D. Unintended Pregnancy and Abortion in the US Navy, 2016. J. Gen. Intern. Med. 37 (Suppl 3), 679–684 (2022). Jalali, R., Mohammadi, M., Vaisi-Raygani, A., Ghobadi, A. & Salari, N. Prevalence of unwanted pregnancy in Iranian women: a systematic review and meta-analysis. Reprod. Health . 16 (1), 133 (2019). Li, C., Gao, J. & Liu, J. Repeat abortion and associated factors among women seeking abortion services in northwestern China: a cross-sectional study. BMC Public. Health . 21 (1), 1626 (2021). Schwarz, E. B., Smith, R., Steinauer, J., Reeves, M. F. & Caughey, A. B. Measuring the effects of unintended pregnancy on women's quality of life. Contraception 78 (3), 204–210 (2008). Khajehpour, M., Simbar, M., Jannesari, S., Ramezani-Tehrani, F. & Majd, H. A. 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Socioeconomic inequalities in unintended pregnancy and abortion decision. J. Urban Health . 85 (1), 125–135 (2008). Exavery, A. et al. Role of condom negotiation on condom use among women of reproductive age in three districts in Tanzania. BMC Public. Health . 12 , 1097 (2012). Machiyama, K. et al. Reasons for unmet need for family planning, with attention to the measurement of fertility preferences: protocol for a multi-site cohort study. Reprod. Health . 14 (1), 23 (2017). Pazol, K. et al. Impact of Contraceptive Education on Knowledge and Decision Making: An Updated Systematic Review. Am. J. Prev. Med. 55 (5), 703–715 (2018). Table 1 Multivariate hierarchical Logistic regression analysis of UP. Additional Declarations No competing interests reported. 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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-5130692","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":447084194,"identity":"f3b41eef-a935-401f-ac06-83bf158de0a0","order_by":0,"name":"limei Wu","email":"","orcid":"","institution":"Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"limei","middleName":"","lastName":"Wu","suffix":""},{"id":447084195,"identity":"22564ddf-7851-410d-8317-6df94d4a93db","order_by":1,"name":"Jiang Li","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiang","middleName":"","lastName":"Li","suffix":""},{"id":447084196,"identity":"a36e586d-292f-4a23-8475-f30f97272d43","order_by":2,"name":"Zhanglu Wang","email":"","orcid":"","institution":"Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhanglu","middleName":"","lastName":"Wang","suffix":""},{"id":447084198,"identity":"e3312f77-ef18-4f02-b788-cb3132dffc7c","order_by":3,"name":"Ling Song","email":"","orcid":"","institution":"Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Song","suffix":""},{"id":447084201,"identity":"f900ce75-9f0e-405c-92d2-05ca90e5b149","order_by":4,"name":"Tianqin Wei","email":"","orcid":"","institution":"Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tianqin","middleName":"","lastName":"Wei","suffix":""},{"id":447084204,"identity":"963bf232-e80c-49d2-9dbf-b7af937675e1","order_by":5,"name":"Fan Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYFACxgcMDBUQpgSRWpgNGBjOkKyFsY0ULQY3khk/F86zi+ZvYD54m4fBLo+gFskZyczSM7cl5844wJZszcOQXExQC79E/gFp3m0Hcjcw8JhJ8zAcSGwgpIVNIpn5N+8ckBb+b8Rp4ZdIZpPmbQDbwkacFsmex2zWPMeAfjnMZmw5xyCZsBaD48nMt3lq7HL725sf3nhTYUdYCwIwg00gXv0oGAWjYBSMAjwAAPAnMw5iZNLSAAAAAElFTkSuQmCC","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":true,"prefix":"","firstName":"Fan","middleName":"","lastName":"Xu","suffix":""},{"id":447084208,"identity":"63bf76cc-36eb-419a-93ea-46185133728d","order_by":6,"name":"Dina Sun","email":"","orcid":"","institution":"Second Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dina","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2024-09-22 03:37:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5130692/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5130692/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81308317,"identity":"066ee822-66b2-4855-8012-51ac6e78177a","added_by":"auto","created_at":"2025-04-24 15:05:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":389834,"visible":true,"origin":"","legend":"\u003cp\u003eBasic subject information\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/90525b356908b6a6d2b93db4.png"},{"id":81308323,"identity":"c67dcefd-937a-4697-a26d-5a2ef96e202c","added_by":"auto","created_at":"2025-04-24 15:05:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":607176,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between socio-demographic variables and unintended pregnancy\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/eb97ddd49c4bc38c010d4aa8.png"},{"id":81309736,"identity":"c5ce3849-b50d-4036-8f5f-21e08dce365f","added_by":"auto","created_at":"2025-04-24 15:13:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":435718,"visible":true,"origin":"","legend":"\u003cp\u003eReasons and outcomes of unintended pregnancy\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/469228815b6ccd824d282b0c.png"},{"id":81309733,"identity":"2e75b8c2-ff87-4f01-8749-cfc12c15a717","added_by":"auto","created_at":"2025-04-24 15:13:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":607674,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariate hierarchical logistic regression analysis of unintended pregnancy (*\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/715abaed743660222397f6d2.png"},{"id":81309735,"identity":"1b270b48-de42-4e72-acce-bee9d61460f0","added_by":"auto","created_at":"2025-04-24 15:13:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1012195,"visible":true,"origin":"","legend":"\u003cp\u003eA Number of women receiving adequate/inadequate contraceptive education:\u003c/p\u003e\n\u003cp\u003e(a) total; (b, c, d) proportions according to marital status, age and education, respectively. B Number of women willing/not willing to receive contraceptive instructions:\u003c/p\u003e\n\u003cp\u003e(a) total; (b, c, d) proportions according to marital status, age and education, respectively.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/cfcecbc8adb44de8cc09effa.png"},{"id":85463903,"identity":"ac456cbe-6b5c-4490-a863-7e6f2f4a684c","added_by":"auto","created_at":"2025-06-26 08:02:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4152788,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5130692/v1/1c798b1f-df3d-49ca-ad26-2ef475fad3bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Status of unintended pregnancy (UP) and contraceptive needs of childbearing age women in Chengdu city","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUnintended pregnancy (UP) is the term used when women did not desire to become pregnant at that time, or ever in the future [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is usually the outcome of non-use, inconsistent use or incorrect use of effective family planning methods. According to World Health Organization reports, 75\u0026nbsp;million out of 175\u0026nbsp;million registered pregnancies were unwanted worldwide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Approximately 58 UPs per 1000 women occurred each year in East Asia and 61% ended in abortion [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUP is considered one of the most important public health risks. It is a threat for both mother and child health due to the lack of family support, it is among the causes that increase mothers\u0026rsquo; mortality and it is a major obstacle to the improvement of reproductive and sexual health [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Nowadays, there is a broad range of effective contraceptive methods available; however, misunderstandings regarding the availability and safety of emergency contraception cause a small proportion of people not to use them [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, despite the availability of multiple, effective contraceptive methods, there remains a high rate of UP globally [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Women need access to accurate information about these different methods in order to choose an option that matches their individual needs regarding lifestyle, family planning, risk factors and non-contraceptive benefits [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs a city blending tradition with modernity, Chengdu retains the traditional culture that values family and opinions from elders, while also being influenced by the younger generation's pursuit of personal development and diversified lifestyles, creating a complex impact on fertility decisions among childbearing-age women. Additionally, as one of China's new first-tier cities undergoing rapid urbanization, the increasing life pressures and changing social concepts brought about by urbanization may also become significant background factors contributing to unintended pregnancies. To the best of our knowledge, there are no studies investigating the prevalence and associated factors of UP in this region. Therefore, the main objectives of this study were to: (i) identify the prevalence of UP among women aged 15\u0026ndash;44 years in five main urban area of Chengdu; (ii) examine the association between socio-demographic/behavioral characteristics and UP; and (iii) understand the contraceptive guidance needs of women of childbearing age and raise suggestions for the further development and provision of high-quality family planning services༎\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eBy using of multi-stage stratified cluster sampling, women of childbearing age were selected from five main urban areas of Chengdu (Jinjiang district, Qingyang district, Chenghua district, Jinniu district and Wuhou district) from April 2023 to February 2024. With the help of community staff, the respondents completed the online questionnaire.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eSample size\u003c/b\u003e According to the average contraceptive compliance rate 58.07% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], the sample size is calculated as 364 people. Considering the non-response rate of 10% and questionnaire inefficiency of 10%, the minimum sample size was 437. A total of 1289 questionnaires were sent out in this time, and 1230 valid questionnaires (95.4%) were finally included after missing items, inconsistent answers and vague answers of key variable values were excluded. Therefore, the sample size of this study meets the requirements.\u003c/p\u003e \u003cp\u003e\u003cb\u003eInclusion and exclusion criteria\u003c/b\u003e The inclusion criteria was women of childbearing age (15\u0026ndash;44 years) who are sexually active and must be participate voluntarily and living in the five main urban areas of Chengdu mentioned above. The exclusion criteria was women who are less than 14 years or greater than 44 years, or women with no previous sexual activity, or women who are unwilling to participate in this survey. The study was approved by Ethics Committee of the Chengdu Second People's Hospital and performed in accordance with the Declaration of Helsinki, and all participants in the survey have signed an informed consent form.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRandomization\u003c/b\u003e The survey employed a stratified two-stage sampling technique in order to ensure regional representativeness. First we conducted in five main urban areas of Chengdu. Taking all women of childbearing age (15\u0026ndash;44 years old) in the above areas as the survey subjects. And there are more than 8,700 communities with a total population of approximately 6\u0026nbsp;million. Among them, there are about 860,000 married women of childbearing age (excluding unmarried individuals who are sexually active).Then computer-generated random numbers. A cluster sampling method was used to randomly select target communities. From each selected community residents' committee, simple random sampling was conducted using ID numbers to select 10 individuals as survey subjects, with an additional 3\u0026ndash;5 as alternates. When the randomly sampled population does not meet the inclusion criteria, alternates are used to fill in. With the help of the community residents' committee, we contacted the selected individuals by phone.\u003c/p\u003e\n\u003ch3\u003eQuestionnaire\u003c/h3\u003e\n\u003cp\u003eAs none of the previously existing questionnaires addressed all of the items needed for our study, we developed a study-specific questionnaire after a thorough review of similarly published reports. Pilot tests on a group of 250 reproductive-aged women who presented for treatment at the gynecology outpatient clinic of Chengdu Second People's Hospital, with participants randomly selected to determine whether the concepts and expressions used in the questionnaire could be easily comprehended. The modified questionnaire consisted of two parts: UP and contraceptive demand. The self-administered questionnaire was programmed online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wjx.cn/\u003c/span\u003e\u003cspan address=\"https://www.wjx.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) by scanning a predetermined QR code. We used a secure questionnaire survey platform and limited the scope of data access through access permissions to reduce the risk of information leakage. Additionally, all participants in the survey have signed confidentiality agreements.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSimple descriptive analysis and bivariate and multivariate statistical analyses were performed in this study. Descriptive analysis was commenced to describe the frequency and percentage distribution. Logistic regression was employed because our dependent variable (UP) was measured as a binary factor. Results for the regression analysis have been presented as odds ratio (OR) values, with the corresponding 95% confidence interval (CI) signifying the precision and significance of the reported OR. Any OR of \u0026lt;\u0026thinsp;1 denotes less odds of UP, whereas an OR of \u0026gt;\u0026thinsp;1 indicates higher odds of UP. The inherent sample weight was applied and all analyses were carried out using STATA version 13.0 software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBasic subject information\u003c/h2\u003e \u003cp\u003eA total of 1289 women aged 15\u0026ndash;44 years were randomly selected and 1230 women completed the survey (response rate\u0026thinsp;=\u0026thinsp;95.4%). Among the 1230 women, 596 (48.5%) were married and 513 (41.7%) were from city areas. More than two-fifths (507; 41.2%) of participants were in the age group between 21 and 25 years. Over half the population (716; 58.2%) had a college degree or higher. Regarding occupation, the largest proportion of respondents (553; 45%) was from service industries, with industries such as managerial, technical and others accounting for 17.8%, 20.8% and 16.4%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDemographic distribution of UP\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the proportion of UP across the included socio-demographic characteristics. More than half of UPs occurred among married women (175; 58.9%), whereas the rate of UP among unmarried, divorced and widowed women gradually decreased: 32.7%, 7.1% and 1.3%, respectively. Women in the 40\u0026ndash;44-year age category had a higher proportion of UP (44.6%), whereas the lowest proportion was recorded among women aged 21\u0026ndash;25 years (17.6%). Urban residents had 21.4% UP whereas 26.6% occurred among women from rural areas. Approximately 45% UP occurred among women with a primary level of education, whereas women with a higher educational level reported a lower prevalence. Women with a secondary education recorded 31.1% UP whereas only 19.3% occurred among women with a college or higher level of education. About four in ten of UPs (42%) occurred among women from the service industry.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eReasons and outcomes of UP\u003c/h3\u003e\n\u003cp\u003eThe most common reason for UP was unprotected intercourse, followed by incorrect use and having no idea how to use contraception. Approximately half of UPs were terminated by means of abortion; the main reason being that they had no family planning in the short term or because of economic pressure. Less than 8% chose to give birth and three in five had given birth because of external pressure (parents or partners) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLogistic regression results of UP\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the outcome of univariate logistic regression analysis. Divorced and widowed (others) women had significantly higher odds of UP (OR\u0026thinsp;=\u0026thinsp;2.491; 95% CI\u0026thinsp;=\u0026thinsp;1.449\u0026ndash;4.204), followed by married women (OR\u0026thinsp;=\u0026thinsp;1.998; 95% CI\u0026thinsp;=\u0026thinsp;1.504\u0026ndash;2.64), compared with the unmarried reference marital status. Higher odds of UP occurred among women aged\u0026thinsp;\u0026gt;\u0026thinsp;40 years (OR\u0026thinsp;=\u0026thinsp;1.990; 95% CI\u0026thinsp;=\u0026thinsp;1.010\u0026ndash;4.006), whereas 21\u0026ndash;25-year-olds had less risk of UP (OR\u0026thinsp;=\u0026thinsp;0.527; 95% CI\u0026thinsp;=\u0026thinsp;0.299\u0026ndash;0.959). Compared with women educated to below junior high school level, those with a junior college (OR\u0026thinsp;=\u0026thinsp;0.524; 95% CI\u0026thinsp;=\u0026thinsp;0.329\u0026ndash;0.834) or university and above level of education (OR\u0026thinsp;=\u0026thinsp;0.358; 95% CI\u0026thinsp;=\u0026thinsp;0.240\u0026ndash;0.538) had a lower risk of UP. Women in others (agriculture and forestry personnel) were 1.64 times more likely to report UP compared with those in the managerial personal (OR\u0026thinsp;=\u0026thinsp;1.640; 95% CI\u0026thinsp;=\u0026thinsp;1.068\u0026ndash;2.533). Higher odds occurred among women whose male partners were from urban (OR\u0026thinsp;=\u0026thinsp;1.465; 95% CI\u0026thinsp;=\u0026thinsp;1.060\u0026ndash;2.021) and rural (OR\u0026thinsp;=\u0026thinsp;1.848; 95% CI\u0026thinsp;=\u0026thinsp;1.351\u0026ndash;2.527) areas compared with partners from the city. Women of male partners with a junior college (OR\u0026thinsp;=\u0026thinsp;0.553; 95% CI\u0026thinsp;=\u0026thinsp;0.347\u0026ndash;0.877) or university and above (OR\u0026thinsp;=\u0026thinsp;0.293; 95% CI\u0026thinsp;=\u0026thinsp;0.197\u0026ndash;0.436) level of education had a significantly lower risk of UP compared with women of partners educated to below junior high school level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis was used to exclude the influence of all the above factors on the results. After adjusting for relevant factors, similar values were found. The results indicated that married women had significantly higher odds of UP (aOR\u0026thinsp;=\u0026thinsp;1.665; 95% CI\u0026thinsp;=\u0026thinsp;1.133\u0026ndash;2.456) compared with unmarried women; women aged 21\u0026ndash;25 years had a lower risk of UP compared with women aged\u0026thinsp;\u0026lt;\u0026thinsp;20 years (aOR\u0026thinsp;=\u0026thinsp;0.528; 95% CI\u0026thinsp;=\u0026thinsp;0.291\u0026ndash;0.987); and women educated to university level or above were less likely to experience UP compared with those educated to below junior high school level (aOR\u0026thinsp;=\u0026thinsp;0.555; 95% CI\u0026thinsp;=\u0026thinsp;0.352\u0026ndash;0.881). Highest odds occurred among women with male partners from a rural area compared with male partners from the city (aOR\u0026thinsp;=\u0026thinsp;1.455; 95% CI\u0026thinsp;=\u0026thinsp;1.042\u0026ndash;2.027). It was also interesting to find that women whose male partners were educated to junior college (aOR\u0026thinsp;=\u0026thinsp;0.603; 95% CI\u0026thinsp;=\u0026thinsp;0.370\u0026ndash;0.984) or university level and above (aOR\u0026thinsp;=\u0026thinsp;0.384; 95% CI\u0026thinsp;=\u0026thinsp;0.67\u0026ndash;0.78) were less likely to have a UP than women of partners educated to below junior high school level (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate hierarchical Logistic regression analysis of UP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\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\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnintended pregnancy(Yes/No)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZ value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.510\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.197\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.588\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.665(1.133\u0026ndash;2.456)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.474(0.780\u0026ndash;2.737)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale age(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.639\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.310\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-2.060\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.528(0.291\u0026ndash;0.987)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.568(0.291\u0026ndash;1.133)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.695(0.350\u0026ndash;1.410)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.141(0.530\u0026ndash;2.493)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale Birthplace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.241(0.865\u0026ndash;1.772)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.276(0.931\u0026ndash;1.748)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale level of 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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow junior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.747(0.450\u0026ndash;1.238)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.693(0.421\u0026ndash;1.143)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.589\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.233\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-2.522\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.555(0.352\u0026ndash;0.881)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale occupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManagerial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etechnicist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.204(0.770\u0026ndash;1.615)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eServices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.077(0.726\u0026ndash;1.615)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProduction personal or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.503(0.956\u0026ndash;2.375)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale Age(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.773(0.390\u0026ndash;1.615)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.903(0.451\u0026ndash;1.901)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.740(0.884\u0026ndash;3.620)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.809(0.866\u0026ndash;3.950)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale Birthplace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.391(0.987\u0026ndash;1.958)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.375\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.210\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.455(1.042\u0026ndash;2.027)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale level of 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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow junior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-1.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.756(0.461\u0026ndash;1.238)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.505\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.249\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-2.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.603(0.370\u0026ndash;0.984)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-0.957\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.223\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-4.287\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.384(0.248\u0026ndash;0.596)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale occupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManagerial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etechnicist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.943(0.592\u0026ndash;1.499)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eServices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.878(0.593\u0026ndash;1.307)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProduction personal or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.088(0.719\u0026ndash;1.652)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eContraceptive needs\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the contraceptive needs of the respondents. Among the 1230 women, almost 61% did not receive adequate contraceptive education. When grouped by age, the 21\u0026ndash;25-year age group accounted for the smallest proportion. In terms of education level, the proportions decreased with the gradual increase in level of education. With regard to marital status, unmarried people had the highest proportion. The main three reasons for the lack of contraceptive education were embarrassment (53.1%), lack of time (43.7%) and \u0026lsquo;do not care\u0026rsquo; (22.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Internet was the most common means of access to contraceptive education (65.6%; 392/598), followed by hospitals (60.4%; 391/598) and schools (57.2%; 342/598); however, 70.41% (866/1230) of respondents were very willing to accept professional contraceptive guidance. Unmarried women, those aged 21\u0026ndash;30 years and those with a college education or above were more likely to receive contraceptive guidance. The most acceptable way to access contraceptive guidance was by the use of science manuals (67.48%; 830/1230), followed by gynecological specialist clinics (40%; 492/1230) and community lectures (37.24%; 458/1230) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUP remains a significant public health concern worldwide. Although evidence suggests that rates of UP have declined worldwide due to increasing access to and use of contraception, there were 121\u0026nbsp;million UP annually [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Chengdu is a young and new first-tier city in China with a large number of young residents. At present, the aim in this city is to improve post-abortion care services in hospitals. However, this means that those who have sex but have not yet had a UP remain hidden. In addition, women who go to public hospitals for induced abortion are the target population for post-abortion care but there are also many who undergo self-induced drug abortion or spontaneous abortion in private clinics, meaning that some abortions occurring outside of the health sector cannot be captured. With the statistical data missing for these groups, we cannot fully understand the status of UP or the contraceptive needs of women of childbearing age in our city. In this study, by taking the community as the unit and all women of childbearing age in the five main urban areas as the object, we used a self-administered questionnaire survey to understand the current situation of UP, carry out an intervention, prevent UP at an early stage and reduce the incidence of UP in our city.\u003c/p\u003e \u003cp\u003eOur study indicated that being married was associated with an increased risk of UP. This result corroborates the results of previous studies by Nyarko et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Who found that married women are more likely to be at risk of UP than those who never married or those who were previously married. They thought that this may be due to the non-use of contraceptives or contraceptive failure, as some married women may believe that contraceptive use has serious side effects while others may believe that it is a sin. Another important explanatory factor for this may be gender inequality among couples: when women are in union, condom use is rarely under their control [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Additionally, male partners hold economic sway and refuse to use condom [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In our opinion, UP can easily occur due to improper or no use of contraception. Consistent and effective use of contraception during each act of intercourse is necessary for married couples to avoid unintended pregnancy (UP). However, it seems that many couples find it difficult to ensure correct use of contraception during every sexual encounter. Therefore, it is necessary to further strengthen the awareness of contraception in couples and family planning should play a greater role.\u003c/p\u003e \u003cp\u003eAccording to the findings of this study, age plays a significant role in the risk of UP among women. In our study, women in other age categories were more likely to experience UP compared to those aged 21\u0026ndash;25 years. This finding is in contradiction with previous studies that found women aged 20\u0026ndash;34 years to have the highest proportion of UP [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and studies that found 15\u0026ndash;19 years were more likely to experience UP compared to women in other age categories [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In their opinion, younger women have higher fertility, higher frequency of sexual intercourse, feel shy to take advice about family planning from relatives or family care organizations and have higher contraceptive failure, all of which contributes to UP. From our perspective, education is a powerful individual predictor of human actions; most women in the 21\u0026ndash;25-year age group are in school and they are more willing and able to obtain contraceptive knowledge, which may lead to a low rate of UP. Moreover, most of the women aged 21\u0026ndash;25 are unmarried and their partner is their boyfriend (but not living together), this also aligns with the findings as mentioned above, that married women have a higher rate of UP.\u003c/p\u003e \u003cp\u003eAdditionally, the risk of UP is found to be predicted by the education level of the woman. Data in the present study showed that, compared with the women who have no formal education, women who have a college degree or above or have a male partner with a college degree or above are at relatively low risk for UP. Our results are consistent with those of other studies that found women having a husband with no education and primary education were significantly associated with UP [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Education has the potential to raise women\u0026rsquo;s consciousness about the implications of UP and possible contraceptive methods that educated women are probably taking advantage of [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Font-Ribera L et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] also explained that women with some formal education are more empowered to take charge of their sexual and reproductive health matters than women who have no formal education. On the other hand, education has been shown to empower women through career opportunities that often translate into higher socioeconomic status, which, in turn, may increase women\u0026rsquo;s autonomy and ability to negotiate safer sex practices, including condom use [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, male partners\u0026rsquo; birthplace is significantly associated with the UP of Chengdu women. Data indicated that women whose male partners were from rural areas were 1.5 times odds to have a UP than their urban counterparts. Male partners from rural areas may have low socioeconomic status and perceive a pregnancy as unintended if they feel that they cannot cater for the unborn child with their current socioeconomic standing.\u003c/p\u003e \u003cp\u003eThe desire to avoid pregnancy did not translate into contraceptive use [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. High rates of UP may also be attributable to limited reproductive health education and knowledge. Gaps in contraceptive knowledge directly affect the choice of contraceptive method and the effect of contraception [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Data in our study showed that more than half of the women had never received contraceptive guidance and related education. Furthermore, as the level of education decreases, the unmet need for contraception increases. Additionally, about 70% of the respondents obtained contraceptive education from the Internet rather than from family planning consultation clinics or gynecology-related clinics. It should be pointed out that more than two-thirds said yes when were asked if they would be willing to receive contraceptive education, with the largest groups being unmarried, aged 21\u0026ndash;30 years and educated to college level or above. Meanwhile, popular science handbooks, gynecological clinics and community publicity are the most acceptable ways to access contraceptive information.\u003c/p\u003e \u003cp\u003eBased on the above situation, the following points are important, from the policy level: (1) establish dedicated reproductive health consultation windows at community health service centers to provide free consultations for women of childbearing age; (2) build an efficient family planning service network covering the entire city; (3) increase supply points for free or low-cost contraceptives (e.g., condoms and short-term oral contraceptives); (4) promote scientific contraception knowledge through multiple channels to change traditional concepts. In terms of specific intervention measures, our suggestions are as follows: (1) create easy-to-understand manuals that include information on contraceptive principles, common contraceptive methods, and their advantages and disadvantages, and distribute them in places where women of childbearing age gather; (2) for economically disadvantaged families, the government can provide subsidies or coupons to reduce the cost of accessing contraceptive resources; (3) design a specialized application to help users understand suitable contraceptive methods for themselves; (4) conduct family planning knowledge training sessions involving both partners to enhance mutual understanding and support. We believe that through the above methods, the situation of UP among women of childbearing age in Chengdu can be improved, and the reproductive and fertility health can be safeguarded.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current situation of UP among women of childbearing age in Chengdu is concerning. Age, marital status, education level of females, and education level and birthplace of their sexual partners are influencing factors.There is an urgent need to address the demand for contraceptive guidance among these women. The first step is to popularize contraceptive knowledge in our city. Additionally, it is crucial to emphasize that contraception is not only the responsibility of women, but men also need to participate actively.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eSeveral limitations to our study should be acknowledged. First, there are many urban areas in Chengdu and we only focused on the five major urban areas, which may lead to the survey results failing to accurately reflect the entire population, thus a larger sample size is required. Second, our understanding of men's knowledge of contraception was mainly obtained through questionnaires distributed to women, however, women may not be able to fully understand men's true opinions on contraception, which may lead to information distortion, we should use separate questionnaires for men in order to fully reflect the role of men in UP. Third, in online surveys, respondents may deliberately provide false answers in order to quickly complete the questionnaire, which can lead to bias in data integrity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLMW, FX, and DNS contributed to conception and design of this study. JL and ZLW conducted the data analysis. LMW, LS and TQW contributed to writing and revising the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw data are not publicly available to preserve individuals’ privacy. The datasets used during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGrindlay, K., Seymour, J., Fix, L. \u0026amp; Grossman, D. 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Table 1 Multivariate hierarchical Logistic regression analysis of UP.\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":"Reproductive age, Contraception, Pregnancy, Unintended pregnancy","lastPublishedDoi":"10.21203/rs.3.rs-5130692/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5130692/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo assess the prevalence and associated factors of unintended pregnancy (UP) and explore the contraceptive needs among women of childbearing age in the main urban areas of Chengdu.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a questionnaire survey in five main urban areas of Chengdu. The survey employed a stratified two-stage sampling technique. Descriptive analysis and univariate and multivariate logistic regression analyses were performed to analyze the relationship between the UP and independent variables. In the multivariable analysis, an adjusted odds ratio(aOR) with a 95% confidence interval(CI) was reported to indicate statistical association.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e1289 women aged 15\u0026ndash;44 years were randomly selected and 1230 women completed the survey. Among the respondents, 24.1% had experienced UP. Married women had a 1.665 times higher odds of UP but the risk of UP was 0.528 times lower for 21-25-year-old women. Women with a university or higher level of education were less likely to report UP whereas those with a male partner from a rural area were more likely to report UP. Women with a male partner having a junior college, university or higher education background were less likely to report UP. More than half of the respondents had never received contraceptive education. Almost three in five of the respondents did not receive adequate contraceptive education, 70.41% of the respondents were very willing to accept professional contraceptive guidance.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAge, marital status, education level of females, and education level and birthplace of their sexual partners are influencing factors for UP among childbearing-aged women in Chengdu. Reproductive health guidance and policies are warranted to reduce the rate of UP in Chengdu.\u003c/p\u003e","manuscriptTitle":"Status of unintended pregnancy (UP) and contraceptive needs of childbearing age women in Chengdu city","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-24 15:05:49","doi":"10.21203/rs.3.rs-5130692/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":"6bb7f081-ef20-49f7-bd06-03d60090cc5d","owner":[],"postedDate":"April 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47589367,"name":"Health sciences/Health care"},{"id":47589368,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-06-26T07:54:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-24 15:05:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5130692","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5130692","identity":"rs-5130692","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}