Pre-pregnancy intrauterine device use is associated with a reduced risk of subsequent preterm birth: a large population-based cohort study

Pre-pregnancy intrauterine device use is associated with a reduced risk of subsequent preterm birth: a large population-based cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pre-pregnancy intrauterine device use is associated with a reduced risk of subsequent preterm birth: a large population-based cohort study Xing Chen, Tao Wang, Yan Zhang, Zhengyuan Xie, Cai Kong, Binxue Wu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4149452/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Feb, 2025 Read the published version in BMC Public Health → Version 1 posted 4 You are reading this latest preprint version Abstract Background The effect of pre-pregnancy intrauterine device (IUD) use on subsequent preterm birth (PTB) remains unclear. To investigate the association between IUD use before pregnancy and subsequent PTB. Methods A total of 242,009 women who participated in the National Free Preconception Health Examination Project (NFPHEP) in Yunnan from 2013 to 2019 were included in the study. All study participants were classified into three groups according to their use of pre-pregnancy contraceptive methods: non-method users, IUD users, and other method users. We used multivariable Poisson regression model to investigate the association between the use of an IUD before pregnancy and subsequent PTB. Further models analyzed the multiplicative and additive interactions between pre-pregnancy IUD use and county deprivation. Results Of all the participants, 45,772 (18.9%) used IUDs before pregnancy, 39,627 (16.4%) used other contraceptive methods, and 156,506 (64.7%) were non-method users. The overall PTB rate was 4.8% (95% confidence interval [95% CI], 4.7–4.9%), and women in the IUD group had a significantly lower PTB rate (4.3%, 95% CI 4.1–4.5%) than women in the non-method users (4.9%, 95% CI 4.8–5.1%) and other method groups (4.7%, 95% CI 4.5–4.9%). IUD use before pregnancy was associated with a reduced risk of subsequent PTB (model 1: adjusted relative risk [aRR] 0.84, 95% CI 0.79 to 0.88; model 2: aRR 0.84, 95% CI 0.79 to 0.90). In counties with a normal level of development, IUD users had a 30% lower risk of subsequent PTB than non-users (aRR 0.70, 95% CI 0.63 to 0.77). Compared with non-IUD users from the least developed counties, those from counties with a normal level of socioeconomic development had the lowest risk of subsequent PTB (aRR 0.72, 0.62 to 0.83). The additive interaction between pre-pregnancy IUD use and low level of county development was statistically significant (relative excess risk due to interaction [RERI] -0.27, -0.40 to -0.13). Conclusion Pre-pregnancy IUD use is associated with a reduced risk of subsequent PTB. Pre-pregnancy IUD users in counties with a normal level of development were associated with a lower risk of subsequent PTB than their counterparts in the least developed countries. Intrauterine devices preterm birth contraception pre-pregnancy examination interaction Figures Figure 1 Figure 2 Background Preterm birth (PTB) is one of the primary causes of death in children under five[ 1 , 2 ]. It was also one of the leading causes of most neonatal deaths in 2018[ 3 ]. In addition, babies born preterm are at greater risk of developing a range of short- and long-term conditions, such as attention deficit disorder[ 4 ], emotional problems[ 5 ], and respiratory and gastrointestinal complications[ 6 ]. PTB affects nearly 15 million births, approximately 11.1% of all births worldwide, with significant regional variations: 12%-13% in the USA, 5%-9% in Europe, and 18% in Africa[ 7 ]. In China, the incidence of PTB is estimated to have risen from 5–10% in recent years, at around 1.5 million per year[ 8 ]. Copper-bearing intrauterine devices (IUDs) are the most widely used contraceptive method in China and the second most widely used method worldwide[ 9 ]. Approximately 120 million women (accounting for more than 50% of married contraceptive users) in China, and 14.3% of women of reproductive age in the world used this method[ 10 , 11 ]. IUDs are long-acting, easy to use, and highly effective - the Pearl Index is less than 1 in 100 women in the first year of use[ 12 ]. In addition to preventing unwanted pregnancy, copper IUDs have some non-contraceptive health benefits. Results from several case-control studies indicated that copper IUD use was associated with a decreased risk of endometrial cancer[ 13 – 15 ]. Systematic reviews also reported that prior copper IUD use was associated with a reduced risk of endometrial cancer, endometriosis, and cervical cancer[ 16 , 17 ]. The reason for these findings may be that the copper IUD may interfere with local hormone response and/or alter hormone production[ 16 ]. A clinical intervention study found that short-term copper IUD placement improved the embryo transfer placement and pregnancy rates[ 18 ]. However, there are a number of side effects associated with the use of copper IUDs, including prolonged and heavy monthly bleeding, irregular bleeding, more cramps and pain during monthly bleeding, pelvic inflammatory disease, and miscarriage, preterm birth, or infection in the rare case that the woman becomes pregnant with the IUD in place[ 19 ]. China stands out as one of the few countries where IUDs serve as the primary contraceptive method. Concerns surrounding the long-term benefits and potential side effects of IUDs are prevalent among both Chinese users and healthcare providers. A study carried out at a single center in Dongguan, China, revealed that women with a history of IUD use demonstrated a lower likelihood of PTB than the control group, which comprised users of other contraceptive method and non-users[ 20 ]. Likewise, an ecological study conducted in the USA indicated that women using long-acting reversible contraceptives, including IUDs and implants, exhibited a notably reduced risk of PTB[ 21 ]. Despite these findings, there remains a scarcity of robust evidence establishing the association between IUD use and subsequent PTB. Notably lacking are studies based on large population data. Leveraging information from the National Free Preconception Health Examination Project (NFPHEP) in Yunnan Province, involving over 242,000 participants, we sought to explore the relationship between pre-pregnancy IUD utilization and subsequent PTB. Additionally, we investigated how IUD usage interacts with the level of socioeconomic development in the counties where women reside concerning PTB risk. Methods Study design and population The data for this study were derived from the NFPHEP in Yunnan province, China. This project was launched by the National Health and Family Planning Commission and the Ministry of Finance of China to provide free health examination and birth planning counseling for couples who planning to have a child within the next six months, with the aim of reducing the potential risk factors for birth defects and preventing adverse pregnancy outcomes[ 22 ]. This project was initiated in Yunnan Province in 2010 and expanded to all 129 counties/districts in the province in 2013. The detailed study design, management, and implementation have been published elsewhere[ 22 – 24 ]. We extracted Yunnan data from all the 248,830 subjects who participated in the NFPHEP and gave a live birth between January 1, 2013, and December 31, 2019. At the initial enrolment and follow-up visits, participants underwent a preconception interview, physical examination, and laboratory tests. Standard questionnaires were used for data collection by trained local health workers in face-to-face interviews, including couples' socio-demographic information, lifestyle, disease history, fertility history, and current contraceptive use or the methods used immediately before enrolment for current non-users. Early pregnancy follow-up was conducted within 12 weeks of pregnancy, and pregnancy information of the subjects was collected timely and accurately, including date of last menstrual period, urine pregnancy test, and ultrasound to determine intrauterine pregnancy. Healthcare personnel provided eugenics-related guidance and advised participants to receive regular pregnancy care. Women were followed up for pregnancy outcomes within 6 weeks postpartum or 2 weeks following the conclusion of other pregnancy events. Since 6,821 (2.7%) women were missing information on contraceptive method before pregnancy, they were excluded from this analysis, resulting in a final cohort of 242,009 women who had a live birth included in this analysis (Fig. 1 ). This study was reviewed and approved by the Ethics Committee of Yunnan Population and Family Planning Research Institute (Approval number: 2017101702). Written informed consent forms were obtained from all participants before data collection. Exposure and Outcomes Contraceptive use before pregnancy is the main exposure factor we are interested in. We categorized all participants into three groups according to the methods they used immediately before pregnancy: (1) non-method users, including women who reported not using any contraceptive method before pregnancy; (2) IUDs users, including women who reported that the method used before pregnancy was IUDs. The type of IUD was almost exclusively copper-bearing ones, as levonorgestrel-releasing IUDs were rarely used in China. If used, it was usually not for contraception but mainly to treat conditions such as unexplained excessive menstrual bleeding; (3) other method users, including those who used a method other than an IUD before pregnancy, mostly condoms. If women used more than one contraceptive method before pregnancy, those who used another method (e.g. condom) in addition to an IUD were included in the IUD group. Otherwise, they were included in the other method group. The primary outcome of interest in this study was PTB occurring during the follow-up period after the preconception health examination. We defined PTB as all births delivered at a gestational age of less than 37 weeks or 259 days[ 25 ]. Gestational age was defined as the time between the woman's last menstrual period and the date of delivery[ 25 ]. Covariates A considerable number of potential confounding factors of PTB have been investigated in previous studies[ 26 – 28 ]. We selected them using directed acyclic graphs (see Supplementary Figure S1 ), including age (< 20 years, 20–24 years, 25–29 years, 30–34 years, and ≥ 35 years), occupation (farmer, other), education level (primary school or below, junior high school, senior high school, college or above), ethnicity (Han, Yi, other), socioeconomic development level of the county where the women lived (county development status: normal, low, very low), pre-pregnancy body mass index (BMI) (underweight: <18.5, normal: 18.5–23.9, overweight or obese: ≥24), anemia (yes, no), smoking status (yes, no), and alcohol consumption (yes, no). County development status was measured according to the national poverty-stricken county standard[ 29 , 30 ]. Anemia was defined as hemoglobin (Hb) less than 110 g/L for pregnant women as recommended by the WHO[ 31 ]. To deal with missing values, we used a fully conditional multiple imputation procedure to impute 10 replications (greater than the percentage of missing data). Supplementary Appendix 1 describes the covariates and multiple imputation methods in detail. Statistical analyses The proportions of women's baseline characteristics by pre-pregnancy contraceptive method were grouped and calculated. Pearson χ 2 tests were used to compare differences in the distributions of categorical characteristics between groups of pre-pregnancy contraceptive use. We performed univariate and multivariable Poisson regression models to explore the association between contraceptive method use and subsequent PTB, and calculated relative risk (RR) with corresponding 95% confidence intervals (CIs). In model 1, we used non-method users as the control, and in model 2, we used the other method users as the control. In both models, we controlled for women's age, occupation, education level, ethnicity, county development status, BMI, anemia, smoking, and alcohol consumption to calculate adjusted relative risk (aRRs). We also calculated PTB rates, rate differences, and rate ratios between users of different contraceptive methods. In subgroup analyses, based on the results of the χ 2 test and regression model, we performed the stratified Poisson regression on selected baseline characteristics and examined the aRRs and 95% CIs. In addition, we examined the interaction between pre-pregnancy IUD use and county development status on both additive and multiplicative scales. The product term was included in the Poisson regression model to assess the multiplicative interaction, which measures the relative change in risk[ 32 ]. Additive interactions were evaluated using three indicators: relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S), which measure the absolute change in risk[ 33 ]. Pre-pregnancy IUD use was recoded in the additive interaction calculation, as it acts as a preventive factor[ 34 ]. In sensitivity analyses, we restricted our analysis to singletons, and additionally adjusted for adverse pregnancy history, including preterm birth, overdue birth, spontaneous abortion, induced abortion, and stillbirth. To avoid the influence of chronic disease on the association between pre-pregnancy contraceptive method use and subsequent PTB, further sensitivity analyses were conducted by excluding individuals with a history of chronic diseases, including hypertension, diabetes, heart disease, epilepsy, hepatitis B, tuberculosis, thyroid disease, and cancers. All statistical inferences were 2-sided, and P values < 0.05 were considered statistically significant. All analyses were performed using R, version 4.2.1. Results Baseline characteristics of participants Of the 242,009 women included in the analysis, 45,772 (18.9%) had used an IUD before pregnancy and were classified in the IUD group, 156,506 (64.7%) in the non-use group, and 39,627 (16.4%) in the other method group, with > 95% of the other methods being condoms. The mean age of all participants was 26.3 years (SD 4.8); 116,353 (48.1%) were primiparas and 1,368 (0.6%) were twins or multiple births. Compared to women in the non-use and other method groups, those in the IUD group were older (≥ 35 years: 12.8% vs 5.1% and 6.1%, respectively), less educated (college or higher: 4.8% vs 14.2% and 25.0%, respectively), and more likely to be farmers (93.3% vs 88.4% and 75.4%, respectively) and multiparas (96.7% vs 38.1% and 55.0%, respectively) (Table 1 ). Table 1 Baseline characteristics of participants, by pre-pregnancy contraceptive methods. Characteristics Non-use IUDs Other methods Total P No. subjects 156602 45777 39630 242009 Age (years) < 0.001 < 20 8682 (5.5) 242 (0.5) 564 (1.4) 9488 (3.9) 20–24 65360 (41.8) 7138 (15.8) 7138 (30.3) 84485 (34.9) 25–29 55800 (35.6) 20681 (45.2) 17759 (44.8) 94240 (39.0) 30–34 18742 (12.0) 11856 (25.9) 6891 (17.4) 37489 (15.5) >=35 7922 (5.1) 5855 (12.8) 2426 (6.1) 16203 (6.7) Unclear 96 (0.06) 5 (0.01) 3 (0.01) 104 (0.04) Ethnicity < 0.001 Han 96060 (61.3) 27075 (59.1) 26759 (67.5) 149894 (61.9) Yi 23201 (14.8) 7461 (16.3) 5601 (14.1) 36263 (15.0) Others 37341 (23.8) 11241 (24.6) 7270 (18.3) 55852 (23.1) Occupation < 0.001 Farmer 138488 (88.4) 42706 (93.3) 29895 (75.4) 211089 (87.2) Others 18114 (11.6) 3071 (6.7) 9735 (24.6) 30920 (12.8) Education level < 0.001 Primary School or below 26637 (17.0) 12427 (27.1) 3898 (9.8) 42962 (17.8) Junior high school 80312 (51.2) 26723 (58.4) 17291 (43.6) 124326 (51.4) Senior high school 24772 (15.8) 3790 (8.3) 7794 (19.7) 36356 (15.0) College or above 22181 (14.2) 2181 (4.8) 9913 (25.0) 34275 (14.2) Unclear 2700 (1.7) 656 (1.4) 734 (1.9) 4090 (1.7) County development status < 0.001 Normal 60323 (38.5) 16793 (36.7) 22465 (56.7) 99581 (41.1) Low 58576 (37.4) 21613 (47.2) 13572 (34.2) 93761 (38.7) Very low 37703 (24.1) 7371 (16.1) 3593 (9.1) 48667 (20.1) BMI before pregnancy < 0.001 =24 24812 (15.8) 9659 (21.1) 6996 (17.1) 41467 (17.1) Unclear 149 (0.1) 23 (0.05) 20 (0.05) 192 (0.08) Parity One 96976 (61.9) 1542 (3.3) 17835 (45.0) 116353 (48.1) Two or above 59626 (38.1) 44235 (96.7) 21795 (55.0) 125656 (51.9) Anemia < 0.001 No 149765 (95.6) 43849 (95.8) 38258 (96.5) 231872 (95.8) Yes 5846 (3.8) 1608 (3.5) 1092 (2.8) 8546 (3.5) Unclear 991 (0.6) 320 (0.7) 280 (0.7) 1591 (0.7) Adverse pregnancy history < 0.001 No 50290 (32.1) 27563 (60.2) 15344 (38.7) 93197 (38.5) Yes 32913 (21.0) 17268 (37.7) 15495 (39.1) 65676 (27.1) Unclear 73399 (46.9) 946 (2.1) 8791 (22.2) 83136 (34.4) Alcohol consumption < 0.001 No 153067 (98.2) 44665 (97.6) 37278 (94.1) 235010 (97.1) Yes 2813 (1.8) 883 (1.9) 2203 (5.5) 5899 (2.4) Unclear 722 (0.5) 229 (0.5) 149 (0.4) 1100 (0.5) Smoking status < 0.001 No 155516 (99.4) 45426 (99.2) 39228 (99.1) 240170 (99.3) Yes 543 (0.3) 198 (0.4) 276 (0.6) 1017 (0.4) Unclear 543 (0.3) 153 (0.3) 126 (0.3) 822 (0.3) Abbreviation: IUDs: intrauterine devices; BMI: Body Mass Index. Non-use: including women who reported not using any contraceptive method before pregnancy. IUDs: including women who reported that the method used before pregnancy was IUDs. Other methods: including women who used a method other than an IUD before pregnancy. Adverse pregnancy history: including preterm birth, overdue birth, spontaneous abortion, induced abortion, and stillbirth. Incidence of PTB Overall, 4.8% (11,587/242,009) of study participants had a PTB. This rate was 4.3% (95% CI 4.1–4.5%) among women who had used an IUD before pregnancy, which was significantly lower (rate difference, -0.62% [-0.84% to -0.41%]; rate ratio, 0.87 [0.83 to 0.92]) than non-users (4.9%, 95%CI 4.8–5.1%) and also significantly lower (rate difference, 0.39% [-0.76% to -0.11%)]; rate ratio, 0.92 [0.86 to 0.98]) than users of other methods (4.7%, 4.5–4.9%). The difference in the rate of PTB between the non-use and other method groups was not statistically significant (rate difference, 0.24% [0.00–0.47%]; rate ratio, 0.95 [0.91 to 1.00]) (Table 2 ). Table 2 The PTB rates among contraceptive users, by pre-pregnancy contraceptive methods. Contraceptives No. of PTB PTB rate, % (95% CI) PTB rate comparisons (95% CI) PTB rate comparisons (95% CI) Rate difference, % Rate ratio Rate difference, % Rate ratio Total 11587 4.8 (4.7 to 4.9) Non-use 7743 4.9 (4.8 to 5.1) (reference) 1.00 (reference) 0.24 (0.00 to 0.47) 1.05 (1.00 to 1.11) IUDs 1978 4.3 (4.1 to 4.5) -0.62 (-0.84 to -0.41) 0.87 (0.83 to 0.92) -0.39 (-0.67 to -0.11) 0.92 (0.86 to 0.98) Other methods 1866 4.7 (4.5 to 4.9) -0.24 (-0.47 to 0.00) 0.95 (0.91 to 1.00) (reference) 1.00 (reference) Abbreviation: PTB: preterm birth; IUDs: intrauterine devices. Non-use: including women who reported not using any contraceptive method before pregnancy. IUDs: including women who reported that the method used before pregnancy was IUDs. Other methods: including women who used a method other than an IUD before pregnancy. Association of pre-pregnancy IUD use with the risk of subsequent PTB We performed both the univariate and multivariate Poisson regression models to estimate the association between pre-pregnancy contraceptive use and the risk of subsequent PTB. The results of the analyses showed that the risk of subsequent PTB was significantly lower in women who used an IUD before pregnancy compared with their counterparts who did not use any method (cRR 0.87 [0.83–0.92], aRR 0.84 [0.79–0.88]) and those who used other methods before pregnancy (cRR 0.92 [0.86–0.98], aRR 0.84 [0.79–0.90]) (Table 3 ). We further stratified the data by women's age, ethnicity, occupation, education level, county development status, pre-pregnancy BMI, parity, anemia, and adverse pregnancy history. Pre-pregnancy IUD users were 10–31% less likely than their counterparts to have a subsequent PTB in most of the subgroup analyses. In counties with a normal level of development, the risk of subsequent PTB among IUD users was only 0.7 times that of non-users and other methods users (aRR 0.70 [0.63–0.77] compared to Non-use; aRR 0.69 [0.62–0.77] compared to Others) (Fig. 2 ). Table 3 Association between pre-pregnancy contraceptive methods and PTB. Contraceptives Model 1 (95%CI) Model 2 (95%CI) Crude RR Adjusted RR Crude RR Adjusted RR Non-use 1.00 (reference) 1.00 (reference) 1.05 (0.99 to 1.10) 1.00 (0.95 to 1.06) IUDs 0.87 (0.83 to 0.92) 0.84 (0.79 to 0.88) 0.92 (0.86 to 0.98) 0.84 (0.79 to 0.90) Other methods 0.95 (0.91 to 1.00) 0.99 (0.94 to 1.05) 1.00 (reference) 1.00 (reference) Abbreviation: PTB: preterm birth; IUDs: intrauterine devices. Non-use: including women who reported not using any contraceptive method before pregnancy. IUDs: including women who reported that the method used before pregnancy was IUDs. Other methods: including women who used a method other than an IUD before pregnancy. Model 1: Non-use is the control. Model 2: Other methods is the control. Table 4 presents the results of the interaction between pre-pregnancy IUD use and county development status on both additive and multiplicative scales. The risk of subsequent PTB was significantly lower among IUD users living in counties categorized as normal (aRR 0.72, 0.62 to 0.83) and low (aRR 0.87, 0.76 to 0.98) levels of development compared to non-users living in the least developed counties. Notably, a significant negative additive interaction was observed between pre-pregnancy IUD use and low county development status, with RERI, AP, and S being − 0.27 (-0.40 to -0.13), -0.20 (-0.29 to -0.11) and 0.55 (0.46 to 0.65). Table 4 The interaction of pre-pregnancy IUD use and county development status on both additive and multiplicative scales. No. of PTB No. of Total PTB rate, % (95% CI) Estimate 95% confidence interval Lower limit Upper limit Risk ratios for joint effects Main effect No IUDs and very low development 2004 41296 4.9 (4.6–5.1) 1.00 (reference) No IUDs and low development 3660 72148 5.1 (4.9–5.2) 1.06 1.01 1.13 No IUDs and normal development 3945 82788 4.8 (4.6–4.9) 1.09 1.03 1.15 IUDs and very low development 366 7371 5.0 (4.5–5.5) 1.00 0.89 1.12 Joint effect IUDs and low development 999 21613 4.6 (4.3–4.9) 0.87 0.76 0.98 IUDs and normal development 613 16793 3.7 (3.4-4.0) 0.72 0.62 0.83 Measures of additive interaction* RERI -0.27 -0.40 -0.13 AP -0.20 -0.29 -0.11 S 0.55 0.46 0.65 Abbreviation: PTB: preterm birth; IUDs: intrauterine devices; RERI: relative excess risk due to interaction; AP: attributable proportion due to interaction; S: synergy index. *Pre-pregnancy IUD use was recoded in the calculation of additive interaction. Sensitive analyses In the analysis of data from singletons, IUD use before pregnancy was associated with a reduced risk of subsequent PTB after controlling for baseline characteristics (aRR 0.83 [0.79–0.88] in model 1; aRR 0.85 [0.76–0.91] in model 2). Several sensitivity analyses were performed, in which we additionally included adverse pregnancy history as a covariate, excluded women exposed to chronic disease, and excluded those using more than one type of contraceptive method (including IUDs) before pregnancy. And IUD users before pregnancy was also associated with lower risk of subsequent PTB in all the analyses (see Supplementary Table 1). Discussion Among the 242,009 women who participated in the National Free Preconception Health Examination Project in Yunnan Province in 2013–2019, 4.8% (4.7%-4.9%) had a PTB. The rates were 4.3% (4.1%-4.5%), 4.7% (4.5%-4.9%), and 4.9% (4.8%-5.1%) among IUD users, other method users, and non-users, respectively. After adjusting for potential confounding using Poisson regression models, we found a 16% reduction in the risk of PTB in the offspring of women who used IUDs before pregnancy compared with other method users and non-users. Our conclusion remained unchanged in a number of subgroups of women with different characteristics and in several sensitivity analyses. Our results are consistent with a cohort study[ 20 ] by Jiang and colleagues in Dongguan, China, which recruited 12,508 multiparas aged 19–48 years and found a 26% (aRR 0.74, 95% CI 0.59–0.91) reduction in the risk of PTB in a subsequent pregnancy in women with a history of IUD use compared with their counterparts. However, the control group in the Jiang’s study included both other method users and non-method users, and it was not possible to determine the relative risk of IUD users compared with other method users and non-method users. In our study, the risk of PTB in women using other methods was largely similar to that of non-method users (aOR 0.99, 95% CI 0.94–1.05). Other methods could be considered as a negative control exposure, and this result strengthens the reliability of the association of pre-pregnancy IUD use with a reduced risk of PTB[ 35 ]. The underlying mechanisms of the effect of IUDs in reducing the risk of PTB in the offspring are unclear. Early studies have shown that PTB is influenced by a combination of socio-demographic, nutritional, medical, obstetric, and environmental factors, and the etiology was not completely understood[ 26 , 36 ]. The type of IUDs used in this study were predominantly copper IUDs (> 99%). Mao and colleagues reported that copper IUDs may cause local mechanical injury to the endometrium and stimulate the immune system to produce an inflammatory response to increase endometrial receptivity[ 18 , 37 ]. Since Increased endometrial receptivity can facilitate embryo implantation[ 38 ], copper IUDs may therefore reduce the risk of PTB by promoting easier and firmer implantation of the embryo. In addition, several studies have found that copper IUDs have a protective effect against endometrial hyperplasia[ 16 , 17 , 39 ], which may promote the growth of spiral arteries in the uterus, promote the proliferation and differentiation of epithelial and stromal cells, regulate the vasomotor activity of capillaries, increase endometrial blood flow, and promote cellular edema and decidualization of stromal cells, thereby facilitating embryo implantation[ 18 , 40 , 41 ], which affects PTB. Besides, some studies suggest that IUD placement helps to separate the opposing surfaces of the uterine cavity and subsequent IUD removal also helps to remove uterine adhesions[ 42 , 43 ], which may facilitate embryo implantation and thus reduce the risk of PTB[ 18 ]. We performed interaction analysis on both additive and multiplicative scales to examine the joint effect of IUD use and county-level socioeconomic development. Compared with non-IUD users in the least developed counties, IUD users in counties with a normal and low levels of development had a significantly reduced risk of subsequent PTB (normal level: aRR 0.72, 95% CI 0.62 to 0.83; low level: aRR 0.87, 95% CI 0.76 to 0.98). additionally, a significant negative additive interaction was observed between pre-pregnancy IUD use and low county development status (RERI − 0.27, 95 CI -0.40 to -0.13; AP -0.20, 95% CI -0.29 to -0.11; S 0.55, 95% CI 0.46 to 0.65). The reasons for these findings are unclear. One plausible explanation could be attributed to the substandard hygienic environment and limited medical resources in the least developed counties[ 44 ], potentially leading to IUD users in these areas facing a higher risk of pelvic inflammatory disease, consequently increasing the risk of subsequent PTB[ 36 , 43 ]. However, further studies are warranted for confirmation. Strengths and Limitations To our knowledge, this is the largest cohort study (> 200,000 women) to investigate the association of pre-pregnancy IUD use with the risk of subsequent PTB. We included all women who participated in the NFPHEP in Yunnan Province and had a live birth between 2013 and 2019 in this study, with a low risk of selection bias. We did stratified analyses and sensitivity analyses, and all the results are consistent, which makes our conclusions more reliable. However, this study has several limitations. First, because of data limitations, we did not include some important confounders in the data analysis, including pregnancy complications, folic acid supplementation, diet, and lifestyle during pregnancy. Second, misclassification bias may not be eliminated because we estimated women's gestational age from their last menstrual period rather than from the date measured by ultrasound. Third, we did not have information on the IUD type, duration of use, and time from termination of contraception to pregnancy, so our analysis cannot be more detailed. Conclusions IUD use may have a protective effect against subsequent PTB. Pre-pregnancy IUD users in counties with a normal level of development were associated with a lower risk of subsequent PTB than their counterparts in the least developed countries. IUD use in China has declined rapidly over the past decade. We recommend that the national free family planning programme and service providers promote the IUDs as a first-line of contraceptive method, not only due to its high efficacy, but also because of its potential to reduce the risk of PTB. Abbreviations IUD Intrauterine device PTB Preterm birth NFPHEP National Free Preconception Health Examination Project CI Confidence intervals aRR adjusted relative risk RERI relative excess risk due to interaction RR Relative risk AP Attributable proportion due to interaction S Synergy index Declarations Acknowledgements Not applicable. Author contributions YC and HY developed the concept, supervised the study, and reviewed the final version. XC performed the data analysis and wrote the first draft of the paper. TW, YZ, ZX, CK, BW, YL ZZ, and XS contributed to the design of the study. All authors reviewed the paper and interpreted the data and revised the manuscript. Final responsibility for the decision to submit for publication was shared by all the authors. Funding This study was supported by the Open Subjects of Key Laboratory of Preconception Health in Western China/Key Laboratory of Fertility Regulation and Minority Birth Health Research of Yunnan Province (ZDsys2021003) and Major Science and Technology Project of Yunnan (Biomedicine) (202002AA100007). Data availability The NFPHEP questionnaire is available on request from the corresponding author ( [email protected] ). NFPHEP data are not publicly available due to legislative or ethnical restrictions. This study is based on anonymized microdata available from the Yunnan NFPHEP project. Access to the data can only be permitted through an affiliation with Yunnan authorized environment. Ethical approval and consent to participate This study was reviewed and approved by the Ethics Committee of Yunnan Population and Family Planning Research Institute (Approval number: 2017101702). All participants gave informed consent. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Frey HA, Klebanoff MA: The epidemiology, etiology, and costs of preterm birth . Semin Fetal Neonatal Med 2016, 21 (2):68-73. Liu L, Oza S, Hogan D, Chu Y, Perin J, Zhu J, Lawn JE, Cousens S, Mathers C, Black RE: Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals . Lancet 2016, 388 (10063):3027-3035. Liu Y, Kang L, He C, Miao L, Qiu X, Xia W, Zhu J, Liang J, Li Q, Wang Y et al : Neonatal mortality and leading causes of deaths: a descriptive study in China, 2014-2018 . BMJ open 2021, 11 (2):e042654. Delobel-Ayoub M, Arnaud C, White-Koning M, Casper C, Pierrat V, Garel M, Burguet A, Roze JC, Matis J, Picaud JC et al : Behavioral problems and cognitive performance at 5 years of age after very preterm birth: the EPIPAGE Study . Pediatrics 2009, 123 (6):1485-1492. Van Lieshout RJ, Boyle MH, Saigal S, Morrison K, Schmidt LA: Mental health of extremely low birth weight survivors in their 30s . Pediatrics 2015, 135 (3):452-459. Goldenberg RL, Culhane JF, Iams JD, Romero R: Epidemiology and causes of preterm birth . Lancet 2008, 371 (9606):75-84. Chawanpaiboon S, Vogel JP, Moller AB, Lumbiganon P, Petzold M, Hogan D, Landoulsi S, Jampathong N, Kongwattanakul K, Laopaiboon M et al : Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis . Lancet Glob Health 2019, 7 (1):e37-e46. Hu Y, Wu Q, Han L, Zou Y, Hong D, Liu J, Zhu Y, Zhu Q, Chen D, Qi L et al : Association between maternal gestational weight gain and preterm birth according to body mass index and maternal age in Quzhou, China . Sci Rep 2020, 10 (1):15863. Tezcan S, Adali T: Marriage characteristics and reproductive health of adolescents in Turkey: findings from Demographic and Health Surveys 1998 and 2008 . Turk J Pediatr 2012, 54 (3):273-282. Buhling KJ, Zite NB, Lotke P, Black K: Worldwide use of intrauterine contraception: a review . Contraception 2014, 89 (3):162-173. Li J, Temmerman M, Chen Q, Xu J, Hu L, Zhang WH: A review of contraceptive practices among married and unmarried women in China from 1982 to 2010 . Eur J Contracept Reprod Health Care 2013, 18 (3):148-158. Hochmuller JT, Lopes KS, Guazzelli CAF, Gomes MKO, Araujo Júnior E, Peixoto AB: Expulsion rate of intrauterine device: mediate vs. immediate puerperium period . J Turk Ger Gynecol Assoc 2020, 21 (3):143-149. Salazar-Martinez E, Lazcano-Ponce EC, Gonzalez Lira-Lira G, Escudero-De los Rios P, Salmeron-Castro J, Hernandez-Avila M: Reproductive factors of ovarian and endometrial cancer risk in a high fertility population in Mexico . Cancer research 1999, 59 (15):3658-3662. Hill DA, Weiss NS, Voigt LF, Beresford SA: Endometrial cancer in relation to intra-uterine device use . International journal of cancer 1997, 70 (3):278-281. Castellsagué X, Thompson WD, Dubrow R: Intra-uterine contraception and the risk of endometrial cancer . International journal of cancer 1993, 54 (6):911-916. Hubacher D, Grimes DA: Noncontraceptive health benefits of intrauterine devices: a systematic review . Obstetrical & gynecological survey 2002, 57 (2):120-128. Johnson MJ, Morgan KW: Intrauterine contraception benefits extend beyond birth control . Nurse Pract 2005, 30 (2):50-55. Mao X, Zhang J, Chen Q, Kuang Y, Zhang S: Short-term copper intrauterine device placement improves the implantation and pregnancy rates in women with repeated implantation failure . Fertil Steril 2017, 108 (1):55-61.e51. World Health Organization Department of Sexual and Reproductive Health and Research (WHO/SRH) and Johns Hopkins Bloomberg School of Public Health/ Center for Communication Programs (CCP) KS: Family Planning: A Global Handbook for Providers (2022 update) : Baltimore and Geneva: CCP and WHO; 2022. Jiang B, He WC, Yu JY, Wei SS, Zhang XJ: History of IUD utilization and the risk of preterm birth: a cohort study . Arch Gynecol Obstet 2022, 305 (2):349-358. Goldthwaite LM, Duca L, Johnson RK, Ostendorf D, Sheeder J: Adverse Birth Outcomes in Colorado: Assessing the Impact of a Statewide Initiative to Prevent Unintended Pregnancy . Am J Public Health 2015, 105 (9):e60-66. Zhang S, Wang Q, Shen H: [Design of the national free proception health examination project in China] . Zhonghua Yi Xue Za Zhi 2015, 95 (3):162-165. Tang J, Zhu X, Li M, Huang D, Zhao Q: The impact of maternal prepregnancy impaired fasting glucose on preterm birth and large for gestational age: a large population-based cohort study . Am J Obstet Gynecol 2020, 222 (3):265.e261-265.e219. Zeng M, He Y, Li M, Yang L, Zhu Q, Liu J, Mao Y, Chen Q, Du J, Zhou W: Association between maternal pregestational glucose level and adverse pregnancy outcomes: a population-based retrospective cohort study . BMJ Open 2021, 11 (9):e048530. WHO: recommended definitions, terminology and format for statistical tables related to the perinatal period and use of a new certificate for cause of perinatal deaths. Modifications recommended by FIGO as amended October 14, 1976 . Acta Obstet Gynecol Scand 1977, 56 (3):247-253. Bryce E, Gurung S, Tong H, Katz J, Lee AC, Black RE, Walker N: Population attributable fractions for risk factors for spontaneous preterm births in 81 low- and middle-income countries: A systematic analysis . J Glob Health 2022, 12 :04013. Seyama R, Makino S, Nojiri S, Takeda J, Suzuki T, Maruyama Y, Takeda S, Itakura A: Retrospective study of the recurrence risk of preterm birth in Japan . J Matern Fetal Neonatal Med 2022, 35 (3):515-519. Tang J, Chen R, Yu Y, Bao W, Tiemeier H, Rodney A, Zhu X, Li M, Huang D, Zhao Q: Associations of pre-pregnancy impaired fasting glucose and body mass index among pregnant women without pre-existing diabetes with offspring being large for gestational age and preterm birth: a cohort study in China . BMJ Open Diabetes Res Care 2021, 9 (1). Park A, Wang S, Wu G: Regional poverty targeting in China . Journal of Public Economics 2002, 86 (1):123-153. Liu Y, Liu J, Zhou Y: Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies . Journal of Rural Studies 2017, 52 :66-75. WHO: Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System . In . , vol. (WHO/NMH/NHD/MNM/11.1). Geneva: World Health Organization; 2011. Andersson T, Alfredsson L, Källberg H, Zdravkovic S, Ahlbom A: Calculating measures of biological interaction . European journal of epidemiology 2005, 20 (7):575-579. VanderWeele TJ, Knol MJJEM: A Tutorial on Interaction . 2014, 3 :33 - 72. Knol MJ, VanderWeele TJ, Groenwold RH, Klungel OH, Rovers MM, Grobbee DE: Estimating measures of interaction on an additive scale for preventive exposures . European journal of epidemiology 2011, 26 (6):433-438. Shi X, Miao W, Tchetgen ET: A Selective Review of Negative Control Methods in Epidemiology . Current epidemiology reports 2020, 7 (4):190-202. Vogel JP, Chawanpaiboon S, Moller AB, Watananirun K, Bonet M, Lumbiganon P: The global epidemiology of preterm birth . Best Pract Res Clin Obstet Gynaecol 2018, 52 :3-12. Dekel N, Gnainsky Y, Granot I, Mor G: Inflammation and implantation . Am J Reprod Immunol 2010, 63 (1):17-21. Achache H, Revel A: Endometrial receptivity markers, the journey to successful embryo implantation . Human Reproduction Update 2006, 12 (6):731-746. Yoost J: Understanding benefits and addressing misperceptions and barriers to intrauterine device access among populations in the United States . Patient Prefer Adherence 2014, 8 :947-957. Gnainsky Y, Granot I, Aldo PB, Barash A, Or Y, Schechtman E, Mor G, Dekel N: Local injury of the endometrium induces an inflammatory response that promotes successful implantation . Fertil Steril 2010, 94 (6):2030-2036. Rama Raju GA, Shashi Kumari G, Krishna KM, Prakash GJ, Madan K: Assessment of uterine cavity by hysteroscopy in assisted reproduction programme and its influence on pregnancy outcome . Arch Gynecol Obstet 2006, 274 (3):160-164. Homer HA, Li TC, Cooke ID: The septate uterus: a review of management and reproductive outcome . Fertil Steril 2000, 73 (1):1-14. Salma U, Xue M, Md Sayed AS, Xu D: Efficacy of intrauterine device in the treatment of intrauterine adhesions . Biomed Res Int 2014, 2014 :589296. Li Z, Zhang L: Poverty and health-related quality of life: a cross-sectional study in rural China . Health Qual Life Outcomes 2020, 18 (1):153. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial2420322.docx Cite Share Download PDF Status: Published Journal Publication published 18 Feb, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 27 Mar, 2024 Submission checks completed at journal 25 Mar, 2024 Editor assigned by journal 25 Mar, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Province","correspondingAuthor":false,"prefix":"","firstName":"Cai","middleName":"","lastName":"Kong","suffix":""},{"id":284486828,"identity":"b04f1438-0bee-403c-84da-91f38b931559","order_by":5,"name":"Binxue Wu","email":"","orcid":"","institution":"NHC Key Lab of Reproduction Regulation, Shanghai Engineering Research Center of Reproductive Health Drug and Devices, Shanghai Institute for Biomedical and Pharmaceutical Technologies, School of Publi","correspondingAuthor":false,"prefix":"","firstName":"Binxue","middleName":"","lastName":"Wu","suffix":""},{"id":284486831,"identity":"aa45277f-fc91-44ec-90c0-cb5f286dbe9b","order_by":6,"name":"Yuzhi Lan","email":"","orcid":"","institution":"Department of Medical Genetics, NHC Key Laboratory of Healthy Birth and Birth Defect Prevention in Western China, First People's Hospital of Yunnan 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Che","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYDACCTBpw8PGcPjAgQ8/iNeSJsfPeCzx4Mwe4rUcNpZsPmN8mIONCB38s5uPSfzcwZy44diZD4cZeBjk+cUOELDkzrE0yd4zbIkbzpzdcLjAgsFw5uwE/FoMJHLMJHjbeBI33ABqmcHDkGBwm6CW/G+Sf9skEjfcf/PgMDDciNGSwybN22ZgLNlwhoE4LRI30oytZdsS5PgZjhkAA1mCsF/4ZyQ/vPm27T8oKh9/+PDDRp5fmoAWIGCRQLaVoHIQYP5AlLJRMApGwSgYuQAA7LlKUc1bVoQAAAAASUVORK5CYII=","orcid":"","institution":"NHC Key Lab of Reproduction Regulation, Shanghai Engineering Research Center of Reproductive Health Drug and Devices, Shanghai Institute for Biomedical and Pharmaceutical Technologies, School of Publi","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Che","suffix":""}],"badges":[],"createdAt":"2024-03-22 11:42:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4149452/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4149452/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-21766-9","type":"published","date":"2025-02-18T15:58:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53752091,"identity":"82ce8fa0-a055-4e2e-a733-38bf5739278c","added_by":"auto","created_at":"2024-03-29 18:49:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27034,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe flow chart of participants selection.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4149452/v1/5a971c9de80bc735daea2031.png"},{"id":53752094,"identity":"0b6935a0-b84e-4584-aa90-ddc8604a586e","added_by":"auto","created_at":"2024-03-29 18:49:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":842675,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation between pre-pregnancy contraceptive methods and PTB: findings of stratification analyses.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviation: PTB: preterm birth; IUDs: intrauterine devices; BMI: Body Mass Index.\u003c/p\u003e\n\u003cp\u003eNon-use: including women who reported not using any contraceptive method before pregnancy.\u003c/p\u003e\n\u003cp\u003eIUDs: including women who reported that the method used before pregnancy was IUDs.\u003c/p\u003e\n\u003cp\u003eOther methods: including women who used a method other than an IUD before pregnancy.\u003c/p\u003e\n\u003cp\u003eAdverse pregnancy history: including preterm birth, overdue birth, spontaneous abortion, induced abortion, and stillbirth.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4149452/v1/41bc752bcfb800fcd044d267.png"},{"id":77052690,"identity":"83ce41cf-d18f-46a1-b14a-827dcf2a2e00","added_by":"auto","created_at":"2025-02-24 16:23:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3873931,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4149452/v1/3473d738-9633-4f81-bf2b-8121a871c542.pdf"},{"id":53752093,"identity":"1c8876da-315e-4362-ab4c-0d7533f1dc55","added_by":"auto","created_at":"2024-03-29 18:49:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":211270,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial2420322.docx","url":"https://assets-eu.researchsquare.com/files/rs-4149452/v1/81ca578f49d486350f99f880.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pre-pregnancy intrauterine device use is associated with a reduced risk of subsequent preterm birth: a large population-based cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003ePreterm birth (PTB) is one of the primary causes of death in children under five[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It was also one of the leading causes of most neonatal deaths in 2018[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, babies born preterm are at greater risk of developing a range of short- and long-term conditions, such as attention deficit disorder[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], emotional problems[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and respiratory and gastrointestinal complications[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. PTB affects nearly 15\u0026nbsp;million births, approximately 11.1% of all births worldwide, with significant regional variations: 12%-13% in the USA, 5%-9% in Europe, and 18% in Africa[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In China, the incidence of PTB is estimated to have risen from 5\u0026ndash;10% in recent years, at around 1.5\u0026nbsp;million per year[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCopper-bearing intrauterine devices (IUDs) are the most widely used contraceptive method in China and the second most widely used method worldwide[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Approximately 120\u0026nbsp;million women (accounting for more than 50% of married contraceptive users) in China, and 14.3% of women of reproductive age in the world used this method[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. IUDs are long-acting, easy to use, and highly effective - the Pearl Index is less than 1 in 100 women in the first year of use[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition to preventing unwanted pregnancy, copper IUDs have some non-contraceptive health benefits. Results from several case-control studies indicated that copper IUD use was associated with a decreased risk of endometrial cancer[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Systematic reviews also reported that prior copper IUD use was associated with a reduced risk of endometrial cancer, endometriosis, and cervical cancer[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The reason for these findings may be that the copper IUD may interfere with local hormone response and/or alter hormone production[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A clinical intervention study found that short-term copper IUD placement improved the embryo transfer placement and pregnancy rates[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, there are a number of side effects associated with the use of copper IUDs, including prolonged and heavy monthly bleeding, irregular bleeding, more cramps and pain during monthly bleeding, pelvic inflammatory disease, and miscarriage, preterm birth, or infection in the rare case that the woman becomes pregnant with the IUD in place[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChina stands out as one of the few countries where IUDs serve as the primary contraceptive method. Concerns surrounding the long-term benefits and potential side effects of IUDs are prevalent among both Chinese users and healthcare providers. A study carried out at a single center in Dongguan, China, revealed that women with a history of IUD use demonstrated a lower likelihood of PTB than the control group, which comprised users of other contraceptive method and non-users[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Likewise, an ecological study conducted in the USA indicated that women using long-acting reversible contraceptives, including IUDs and implants, exhibited a notably reduced risk of PTB[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Despite these findings, there remains a scarcity of robust evidence establishing the association between IUD use and subsequent PTB. Notably lacking are studies based on large population data. Leveraging information from the National Free Preconception Health Examination Project (NFPHEP) in Yunnan Province, involving over 242,000 participants, we sought to explore the relationship between pre-pregnancy IUD utilization and subsequent PTB. Additionally, we investigated how IUD usage interacts with the level of socioeconomic development in the counties where women reside concerning PTB risk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThe data for this study were derived from the NFPHEP in Yunnan province, China. This project was launched by the National Health and Family Planning Commission and the Ministry of Finance of China to provide free health examination and birth planning counseling for couples who planning to have a child within the next six months, with the aim of reducing the potential risk factors for birth defects and preventing adverse pregnancy outcomes[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This project was initiated in Yunnan Province in 2010 and expanded to all 129 counties/districts in the province in 2013. The detailed study design, management, and implementation have been published elsewhere[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe extracted Yunnan data from all the 248,830 subjects who participated in the NFPHEP and gave a live birth between January 1, 2013, and December 31, 2019. At the initial enrolment and follow-up visits, participants underwent a preconception interview, physical examination, and laboratory tests. Standard questionnaires were used for data collection by trained local health workers in face-to-face interviews, including couples' socio-demographic information, lifestyle, disease history, fertility history, and current contraceptive use or the methods used immediately before enrolment for current non-users. Early pregnancy follow-up was conducted within 12 weeks of pregnancy, and pregnancy information of the subjects was collected timely and accurately, including date of last menstrual period, urine pregnancy test, and ultrasound to determine intrauterine pregnancy. Healthcare personnel provided eugenics-related guidance and advised participants to receive regular pregnancy care. Women were followed up for pregnancy outcomes within 6 weeks postpartum or 2 weeks following the conclusion of other pregnancy events. Since 6,821 (2.7%) women were missing information on contraceptive method before pregnancy, they were excluded from this analysis, resulting in a final cohort of 242,009 women who had a live birth included in this analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This study was reviewed and approved by the Ethics Committee of Yunnan Population and Family Planning Research Institute (Approval number: 2017101702). Written informed consent forms were obtained from all participants before data collection.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExposure and Outcomes\u003c/h2\u003e \u003cp\u003eContraceptive use before pregnancy is the main exposure factor we are interested in. We categorized all participants into three groups according to the methods they used immediately before pregnancy: (1) non-method users, including women who reported not using any contraceptive method before pregnancy; (2) IUDs users, including women who reported that the method used before pregnancy was IUDs. The type of IUD was almost exclusively copper-bearing ones, as levonorgestrel-releasing IUDs were rarely used in China. If used, it was usually not for contraception but mainly to treat conditions such as unexplained excessive menstrual bleeding; (3) other method users, including those who used a method other than an IUD before pregnancy, mostly condoms. If women used more than one contraceptive method before pregnancy, those who used another method (e.g. condom) in addition to an IUD were included in the IUD group. Otherwise, they were included in the other method group.\u003c/p\u003e \u003cp\u003eThe primary outcome of interest in this study was PTB occurring during the follow-up period after the preconception health examination. We defined PTB as all births delivered at a gestational age of less than 37 weeks or 259 days[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Gestational age was defined as the time between the woman's last menstrual period and the date of delivery[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eA considerable number of potential confounding factors of PTB have been investigated in previous studies[\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. We selected them using directed acyclic graphs (see Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), including age (\u0026lt;\u0026thinsp;20 years, 20\u0026ndash;24 years, 25\u0026ndash;29 years, 30\u0026ndash;34 years, and \u0026ge;\u0026thinsp;35 years), occupation (farmer, other), education level (primary school or below, junior high school, senior high school, college or above), ethnicity (Han, Yi, other), socioeconomic development level of the county where the women lived (county development status: normal, low, very low), pre-pregnancy body mass index (BMI) (underweight: \u0026lt;18.5, normal: 18.5\u0026ndash;23.9, overweight or obese: \u0026ge;24), anemia (yes, no), smoking status (yes, no), and alcohol consumption (yes, no). County development status was measured according to the national poverty-stricken county standard[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Anemia was defined as hemoglobin (Hb) less than 110 g/L for pregnant women as recommended by the WHO[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. To deal with missing values, we used a fully conditional multiple imputation procedure to impute 10 replications (greater than the percentage of missing data). Supplementary Appendix 1 describes the covariates and multiple imputation methods in detail.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eThe proportions of women's baseline characteristics by pre-pregnancy contraceptive method were grouped and calculated. Pearson χ\u003csup\u003e2\u003c/sup\u003e tests were used to compare differences in the distributions of categorical characteristics between groups of pre-pregnancy contraceptive use. We performed univariate and multivariable Poisson regression models to explore the association between contraceptive method use and subsequent PTB, and calculated relative risk (RR) with corresponding 95% confidence intervals (CIs). In model 1, we used non-method users as the control, and in model 2, we used the other method users as the control. In both models, we controlled for women's age, occupation, education level, ethnicity, county development status, BMI, anemia, smoking, and alcohol consumption to calculate adjusted relative risk (aRRs). We also calculated PTB rates, rate differences, and rate ratios between users of different contraceptive methods.\u003c/p\u003e \u003cp\u003eIn subgroup analyses, based on the results of the χ\u003csup\u003e2\u003c/sup\u003e test and regression model, we performed the stratified Poisson regression on selected baseline characteristics and examined the aRRs and 95% CIs. In addition, we examined the interaction between pre-pregnancy IUD use and county development status on both additive and multiplicative scales. The product term was included in the Poisson regression model to assess the multiplicative interaction, which measures the relative change in risk[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additive interactions were evaluated using three indicators: relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S), which measure the absolute change in risk[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Pre-pregnancy IUD use was recoded in the additive interaction calculation, as it acts as a preventive factor[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn sensitivity analyses, we restricted our analysis to singletons, and additionally adjusted for adverse pregnancy history, including preterm birth, overdue birth, spontaneous abortion, induced abortion, and stillbirth. To avoid the influence of chronic disease on the association between pre-pregnancy contraceptive method use and subsequent PTB, further sensitivity analyses were conducted by excluding individuals with a history of chronic diseases, including hypertension, diabetes, heart disease, epilepsy, hepatitis B, tuberculosis, thyroid disease, and cancers. All statistical inferences were 2-sided, and P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. All analyses were performed using R, version 4.2.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eBaseline characteristics of participants\u003c/h2\u003e\n \u003cp\u003eOf the 242,009 women included in the analysis, 45,772 (18.9%) had used an IUD before pregnancy and were classified in the IUD group, 156,506 (64.7%) in the non-use group, and 39,627 (16.4%) in the other method group, with \u0026gt;\u0026thinsp;95% of the other methods being condoms. The mean age of all participants was 26.3 years (SD 4.8); 116,353 (48.1%) were primiparas and 1,368 (0.6%) were twins or multiple births. Compared to women in the non-use and other method groups, those in the IUD group were older (\u0026ge;\u0026thinsp;35 years: 12.8% vs 5.1% and 6.1%, respectively), less educated (college or higher: 4.8% vs 14.2% and 25.0%, respectively), and more likely to be farmers (93.3% vs 88.4% and 75.4%, respectively) and multiparas (96.7% vs 38.1% and 55.0%, respectively) (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBaseline characteristics of participants, by pre-pregnancy contraceptive methods.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-use\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIUDs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOther methods\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. subjects\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e242009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8682 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e242 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e564 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9488 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65360 (41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7138 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7138 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84485 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55800 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20681 (45.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17759 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94240 (39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18742 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11856 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6891 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37489 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;=35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7922 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5855 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2426 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16203 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104 (0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96060 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27075 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26759 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149894 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23201 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7461 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5601 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36263 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37341 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11241 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7270 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55852 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138488 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42706 (93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29895 (75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e211089 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18114 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3071 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9735 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30920 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary School or below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26637 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12427 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3898 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42962 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80312 (51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26723 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17291 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124326 (51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24772 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3790 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7794 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36356 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCollege or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22181 (14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2181 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9913 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34275 (14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2700 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e656 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e734 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4090 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCounty development status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60323 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16793 (36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22465 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99581 (41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58576 (37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21613 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13572 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93761 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37703 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7371 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3593 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48667 (20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI before pregnancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20555 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4786 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6238 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31579 (79.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.5\u0026ndash;23.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111086 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31309 (68.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26376 (66.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e168771 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;=24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24812 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9659 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6996 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41467 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e192 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96976 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1542 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17835 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116353 (48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwo or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59626 (38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44235 (96.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21795 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125656 (51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnemia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149765 (95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43849 (95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38258 (96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e231872 (95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5846 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1608 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1092 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8546 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e991 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e320 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e280 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1591 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdverse pregnancy history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50290 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27563 (60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15344 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93197 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32913 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17268 (37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15495 (39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65676 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73399 (46.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e946 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8791 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83136 (34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153067 (98.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44665 (97.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37278 (94.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e235010 (97.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2813 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e883 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2203 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5899 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e722 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e229 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1100 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155516 (99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45426 (99.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39228 (99.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e240170 (99.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e543 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e198 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e276 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1017 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e543 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e153 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e822 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviation: IUDs: intrauterine devices; BMI: Body Mass Index.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNon-use: including women who reported not using any contraceptive method before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eIUDs: including women who reported that the method used before pregnancy was IUDs.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eOther methods: including women who used a method other than an IUD before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAdverse pregnancy history: including preterm birth, overdue birth, spontaneous abortion, induced abortion, and stillbirth.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eIncidence of PTB\u003c/h2\u003e\n \u003cp\u003eOverall, 4.8% (11,587/242,009) of study participants had a PTB. This rate was 4.3% (95% CI 4.1\u0026ndash;4.5%) among women who had used an IUD before pregnancy, which was significantly lower (rate difference, -0.62% [-0.84% to -0.41%]; rate ratio, 0.87 [0.83 to 0.92]) than non-users (4.9%, 95%CI 4.8\u0026ndash;5.1%) and also significantly lower (rate difference, 0.39% [-0.76% to -0.11%)]; rate ratio, 0.92 [0.86 to 0.98]) than users of other methods (4.7%, 4.5\u0026ndash;4.9%). The difference in the rate of PTB between the non-use and other method groups was not statistically significant (rate difference, 0.24% [0.00\u0026ndash;0.47%]; rate ratio, 0.95 [0.91 to 1.00]) (Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe PTB rates among contraceptive users, by pre-pregnancy contraceptive methods.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eContraceptives\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNo. of PTB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePTB rate, %\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePTB rate comparisons\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePTB rate comparisons\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate difference, %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate difference, %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRate ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8 (4.7 to 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 (4.8 to 5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24 (0.00 to 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05 (1.00 to 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIUDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 (4.1 to 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.62 (-0.84 to -0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87 (0.83 to 0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.39 (-0.67 to -0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.86 to 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 (4.5 to 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.24 (-0.47 to 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (0.91 to 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eAbbreviation: PTB: preterm birth; IUDs: intrauterine devices.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eNon-use: including women who reported not using any contraceptive method before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eIUDs: including women who reported that the method used before pregnancy was IUDs.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eOther methods: including women who used a method other than an IUD before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eAssociation of pre-pregnancy IUD use with the risk of subsequent PTB\u003c/h2\u003e\n \u003cp\u003eWe performed both the univariate and multivariate Poisson regression models to estimate the association between pre-pregnancy contraceptive use and the risk of subsequent PTB. The results of the analyses showed that the risk of subsequent PTB was significantly lower in women who used an IUD before pregnancy compared with their counterparts who did not use any method (cRR 0.87 [0.83\u0026ndash;0.92], aRR 0.84 [0.79\u0026ndash;0.88]) and those who used other methods before pregnancy (cRR 0.92 [0.86\u0026ndash;0.98], aRR 0.84 [0.79\u0026ndash;0.90]) (Table\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e). We further stratified the data by women\u0026apos;s age, ethnicity, occupation, education level, county development status, pre-pregnancy BMI, parity, anemia, and adverse pregnancy history. Pre-pregnancy IUD users were 10\u0026ndash;31% less likely than their counterparts to have a subsequent PTB in most of the subgroup analyses. In counties with a normal level of development, the risk of subsequent PTB among IUD users was only 0.7 times that of non-users and other methods users (aRR 0.70 [0.63\u0026ndash;0.77] compared to Non-use; aRR 0.69 [0.62\u0026ndash;0.77] compared to Others) (Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAssociation between pre-pregnancy contraceptive methods and PTB.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eContraceptives\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel 1 (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel 2 (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude RR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted RR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude RR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted RR\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05 (0.99 to 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (0.95 to 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIUDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87 (0.83 to 0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84 (0.79 to 0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.86 to 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84 (0.79 to 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (0.91 to 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99 (0.94 to 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviation: PTB: preterm birth; IUDs: intrauterine devices.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNon-use: including women who reported not using any contraceptive method before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eIUDs: including women who reported that the method used before pregnancy was IUDs.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eOther methods: including women who used a method other than an IUD before pregnancy.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eModel 1: Non-use is the control.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eModel 2: Other methods is the control.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e presents the results of the interaction between pre-pregnancy IUD use and county development status on both additive and multiplicative scales. The risk of subsequent PTB was significantly lower among IUD users living in counties categorized as normal (aRR 0.72, 0.62 to 0.83) and low (aRR 0.87, 0.76 to 0.98) levels of development compared to non-users living in the least developed counties. Notably, a significant negative additive interaction was observed between pre-pregnancy IUD use and low county development status, with RERI, AP, and S being \u0026minus;\u0026thinsp;0.27 (-0.40 to -0.13), -0.20 (-0.29 to -0.11) and 0.55 (0.46 to 0.65).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe interaction of pre-pregnancy IUD use and county development status on both additive and multiplicative scales.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNo. of PTB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNo. of Total\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePTB rate, % (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% confidence interval\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower limit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper limit\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk ratios for joint effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMain effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo IUDs and very low development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.9 (4.6\u0026ndash;5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo IUDs and low development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.1 (4.9\u0026ndash;5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo IUDs and normal development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.8 (4.6\u0026ndash;4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIUDs and very low development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0 (4.5\u0026ndash;5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJoint effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIUDs and low development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.6 (4.3\u0026ndash;4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.98\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIUDs and normal development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.7 (3.4-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeasures of additive interaction*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRERI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eAbbreviation: PTB: preterm birth; IUDs: intrauterine devices; RERI: relative excess risk due to interaction; AP: attributable proportion due to interaction; S: synergy index.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e*Pre-pregnancy IUD use was recoded in the calculation of additive interaction.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eSensitive analyses\u003c/h2\u003e\n \u003cp\u003eIn the analysis of data from singletons, IUD use before pregnancy was associated with a reduced risk of subsequent PTB after controlling for baseline characteristics (aRR 0.83 [0.79\u0026ndash;0.88] in model 1; aRR 0.85 [0.76\u0026ndash;0.91] in model 2). Several sensitivity analyses were performed, in which we additionally included adverse pregnancy history as a covariate, excluded women exposed to chronic disease, and excluded those using more than one type of contraceptive method (including IUDs) before pregnancy. And IUD users before pregnancy was also associated with lower risk of subsequent PTB in all the analyses (see Supplementary Table\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e Among the 242,009 women who participated in the National Free Preconception Health Examination Project in Yunnan Province in 2013\u0026ndash;2019, 4.8% (4.7%-4.9%) had a PTB. The rates were 4.3% (4.1%-4.5%), 4.7% (4.5%-4.9%), and 4.9% (4.8%-5.1%) among IUD users, other method users, and non-users, respectively. After adjusting for potential confounding using Poisson regression models, we found a 16% reduction in the risk of PTB in the offspring of women who used IUDs before pregnancy compared with other method users and non-users.\u003c/p\u003e \u003cp\u003eOur conclusion remained unchanged in a number of subgroups of women with different characteristics and in several sensitivity analyses. Our results are consistent with a cohort study[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] by Jiang and colleagues in Dongguan, China, which recruited 12,508 multiparas aged 19\u0026ndash;48 years and found a 26% (aRR 0.74, 95% CI 0.59\u0026ndash;0.91) reduction in the risk of PTB in a subsequent pregnancy in women with a history of IUD use compared with their counterparts. However, the control group in the Jiang\u0026rsquo;s study included both other method users and non-method users, and it was not possible to determine the relative risk of IUD users compared with other method users and non-method users. In our study, the risk of PTB in women using other methods was largely similar to that of non-method users (aOR 0.99, 95% CI 0.94\u0026ndash;1.05). Other methods could be considered as a negative control exposure, and this result strengthens the reliability of the association of pre-pregnancy IUD use with a reduced risk of PTB[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe underlying mechanisms of the effect of IUDs in reducing the risk of PTB in the offspring are unclear. Early studies have shown that PTB is influenced by a combination of socio-demographic, nutritional, medical, obstetric, and environmental factors, and the etiology was not completely understood[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The type of IUDs used in this study were predominantly copper IUDs (\u0026gt;\u0026thinsp;99%). Mao and colleagues reported that copper IUDs may cause local mechanical injury to the endometrium and stimulate the immune system to produce an inflammatory response to increase endometrial receptivity[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Since Increased endometrial receptivity can facilitate embryo implantation[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], copper IUDs may therefore reduce the risk of PTB by promoting easier and firmer implantation of the embryo. In addition, several studies have found that copper IUDs have a protective effect against endometrial hyperplasia[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which may promote the growth of spiral arteries in the uterus, promote the proliferation and differentiation of epithelial and stromal cells, regulate the vasomotor activity of capillaries, increase endometrial blood flow, and promote cellular edema and decidualization of stromal cells, thereby facilitating embryo implantation[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which affects PTB. Besides, some studies suggest that IUD placement helps to separate the opposing surfaces of the uterine cavity and subsequent IUD removal also helps to remove uterine adhesions[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which may facilitate embryo implantation and thus reduce the risk of PTB[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe performed interaction analysis on both additive and multiplicative scales to examine the joint effect of IUD use and county-level socioeconomic development. Compared with non-IUD users in the least developed counties, IUD users in counties with a normal and low levels of development had a significantly reduced risk of subsequent PTB (normal level: aRR 0.72, 95% CI 0.62 to 0.83; low level: aRR 0.87, 95% CI 0.76 to 0.98). additionally, a significant negative additive interaction was observed between pre-pregnancy IUD use and low county development status (RERI \u0026minus;\u0026thinsp;0.27, 95 CI -0.40 to -0.13; AP -0.20, 95% CI -0.29 to -0.11; S 0.55, 95% CI 0.46 to 0.65). The reasons for these findings are unclear. One plausible explanation could be attributed to the substandard hygienic environment and limited medical resources in the least developed counties[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], potentially leading to IUD users in these areas facing a higher risk of pelvic inflammatory disease, consequently increasing the risk of subsequent PTB[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, further studies are warranted for confirmation.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eTo our knowledge, this is the largest cohort study (\u0026gt;\u0026thinsp;200,000 women) to investigate the association of pre-pregnancy IUD use with the risk of subsequent PTB. We included all women who participated in the NFPHEP in Yunnan Province and had a live birth between 2013 and 2019 in this study, with a low risk of selection bias. We did stratified analyses and sensitivity analyses, and all the results are consistent, which makes our conclusions more reliable.\u003c/p\u003e \u003cp\u003eHowever, this study has several limitations. First, because of data limitations, we did not include some important confounders in the data analysis, including pregnancy complications, folic acid supplementation, diet, and lifestyle during pregnancy. Second, misclassification bias may not be eliminated because we estimated women's gestational age from their last menstrual period rather than from the date measured by ultrasound. Third, we did not have information on the IUD type, duration of use, and time from termination of contraception to pregnancy, so our analysis cannot be more detailed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIUD use may have a protective effect against subsequent PTB. Pre-pregnancy IUD users in counties with a normal level of development were associated with a lower risk of subsequent PTB than their counterparts in the least developed countries. IUD use in China has declined rapidly over the past decade. We recommend that the national free family planning programme and service providers promote the IUDs as a first-line of contraceptive method, not only due to its high efficacy, but also because of its potential to reduce the risk of PTB.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIUD Intrauterine device\u003c/p\u003e\n\u003cp\u003ePTB Preterm birth\u003c/p\u003e\n\u003cp\u003eNFPHEP National Free Preconception Health Examination Project\u003c/p\u003e\n\u003cp\u003eCI Confidence intervals\u003c/p\u003e\n\u003cp\u003eaRR adjusted relative risk\u003c/p\u003e\n\u003cp\u003eRERI relative excess risk due to interaction\u003c/p\u003e\n\u003cp\u003eRR Relative risk\u003c/p\u003e\n\u003cp\u003eAP Attributable proportion due to interaction\u003c/p\u003e\n\u003cp\u003eS Synergy index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYC and HY developed the concept, supervised the study, and reviewed the final version. XC performed the data analysis and wrote the first draft of the paper. TW, YZ, ZX, CK, BW, YL ZZ, and XS contributed to the design of the study. All authors reviewed the paper and interpreted the data and revised the manuscript. Final responsibility for the decision to submit for publication was shared by all the authors.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Open Subjects of Key Laboratory of Preconception Health in Western China/Key Laboratory of Fertility Regulation and Minority Birth Health Research of Yunnan Province (ZDsys2021003) and Major Science and Technology Project of Yunnan (Biomedicine) (202002AA100007).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NFPHEP questionnaire is available on request from the corresponding author ([email protected]). NFPHEP data are not publicly available due to legislative or ethnical restrictions. This study is based on anonymized microdata available from the Yunnan NFPHEP project. Access to the data can only be permitted through an affiliation with Yunnan authorized environment.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of Yunnan Population and Family Planning Research Institute (Approval number: 2017101702). All participants gave informed consent.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFrey HA, Klebanoff MA: \u003cstrong\u003eThe epidemiology, etiology, and costs of preterm birth\u003c/strong\u003e. \u003cem\u003eSemin Fetal Neonatal Med \u003c/em\u003e2016, \u003cstrong\u003e21\u003c/strong\u003e(2):68-73.\u003c/li\u003e\n\u003cli\u003eLiu L, Oza S, Hogan D, Chu Y, Perin J, Zhu J, Lawn JE, Cousens S, Mathers C, Black RE: \u003cstrong\u003eGlobal, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals\u003c/strong\u003e. \u003cem\u003eLancet \u003c/em\u003e2016, \u003cstrong\u003e388\u003c/strong\u003e(10063):3027-3035.\u003c/li\u003e\n\u003cli\u003eLiu Y, Kang L, He C, Miao L, Qiu X, Xia W, Zhu J, Liang J, Li Q, Wang Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eNeonatal mortality and leading causes of deaths: a descriptive study in China, 2014-2018\u003c/strong\u003e. \u003cem\u003eBMJ open \u003c/em\u003e2021, \u003cstrong\u003e11\u003c/strong\u003e(2):e042654.\u003c/li\u003e\n\u003cli\u003eDelobel-Ayoub M, Arnaud C, White-Koning M, Casper C, Pierrat V, Garel M, Burguet A, Roze JC, Matis J, Picaud JC\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eBehavioral problems and cognitive performance at 5 years of age after very preterm birth: the EPIPAGE Study\u003c/strong\u003e. \u003cem\u003ePediatrics \u003c/em\u003e2009, \u003cstrong\u003e123\u003c/strong\u003e(6):1485-1492.\u003c/li\u003e\n\u003cli\u003eVan Lieshout RJ, Boyle MH, Saigal S, Morrison K, Schmidt LA: \u003cstrong\u003eMental health of extremely low birth weight survivors in their 30s\u003c/strong\u003e. \u003cem\u003ePediatrics \u003c/em\u003e2015, \u003cstrong\u003e135\u003c/strong\u003e(3):452-459.\u003c/li\u003e\n\u003cli\u003eGoldenberg RL, Culhane JF, Iams JD, Romero R: \u003cstrong\u003eEpidemiology and causes of preterm birth\u003c/strong\u003e. \u003cem\u003eLancet \u003c/em\u003e2008, \u003cstrong\u003e371\u003c/strong\u003e(9606):75-84.\u003c/li\u003e\n\u003cli\u003eChawanpaiboon S, Vogel JP, Moller AB, Lumbiganon P, Petzold M, Hogan D, Landoulsi S, Jampathong N, Kongwattanakul K, Laopaiboon M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGlobal, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis\u003c/strong\u003e. \u003cem\u003eLancet Glob Health \u003c/em\u003e2019, \u003cstrong\u003e7\u003c/strong\u003e(1):e37-e46.\u003c/li\u003e\n\u003cli\u003eHu Y, Wu Q, Han L, Zou Y, Hong D, Liu J, Zhu Y, Zhu Q, Chen D, Qi L\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAssociation between maternal gestational weight gain and preterm birth according to body mass index and maternal age in Quzhou, China\u003c/strong\u003e. \u003cem\u003eSci Rep \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(1):15863.\u003c/li\u003e\n\u003cli\u003eTezcan S, Adali T: \u003cstrong\u003eMarriage characteristics and reproductive health of adolescents in Turkey: findings from Demographic and Health Surveys 1998 and 2008\u003c/strong\u003e. \u003cem\u003eTurk J Pediatr \u003c/em\u003e2012, \u003cstrong\u003e54\u003c/strong\u003e(3):273-282.\u003c/li\u003e\n\u003cli\u003eBuhling KJ, Zite NB, Lotke P, Black K: \u003cstrong\u003eWorldwide use of intrauterine contraception: a review\u003c/strong\u003e. \u003cem\u003eContraception \u003c/em\u003e2014, \u003cstrong\u003e89\u003c/strong\u003e(3):162-173.\u003c/li\u003e\n\u003cli\u003eLi J, Temmerman M, Chen Q, Xu J, Hu L, Zhang WH: \u003cstrong\u003eA review of contraceptive practices among married and unmarried women in China from 1982 to 2010\u003c/strong\u003e. \u003cem\u003eEur J Contracept Reprod Health Care \u003c/em\u003e2013, \u003cstrong\u003e18\u003c/strong\u003e(3):148-158.\u003c/li\u003e\n\u003cli\u003eHochmuller JT, Lopes KS, Guazzelli CAF, Gomes MKO, Araujo J\u0026uacute;nior E, Peixoto AB: \u003cstrong\u003eExpulsion rate of intrauterine device: mediate vs. immediate puerperium period\u003c/strong\u003e. \u003cem\u003eJ Turk Ger Gynecol Assoc \u003c/em\u003e2020, \u003cstrong\u003e21\u003c/strong\u003e(3):143-149.\u003c/li\u003e\n\u003cli\u003eSalazar-Martinez E, Lazcano-Ponce EC, Gonzalez Lira-Lira G, Escudero-De los Rios P, Salmeron-Castro J, Hernandez-Avila M: \u003cstrong\u003eReproductive factors of ovarian and endometrial cancer risk in a high fertility population in Mexico\u003c/strong\u003e. \u003cem\u003eCancer research \u003c/em\u003e1999, \u003cstrong\u003e59\u003c/strong\u003e(15):3658-3662.\u003c/li\u003e\n\u003cli\u003eHill DA, Weiss NS, Voigt LF, Beresford SA: \u003cstrong\u003eEndometrial cancer in relation to intra-uterine device use\u003c/strong\u003e. \u003cem\u003eInternational journal of cancer \u003c/em\u003e1997, \u003cstrong\u003e70\u003c/strong\u003e(3):278-281.\u003c/li\u003e\n\u003cli\u003eCastellsagu\u0026eacute; X, Thompson WD, Dubrow R: \u003cstrong\u003eIntra-uterine contraception and the risk of endometrial cancer\u003c/strong\u003e. \u003cem\u003eInternational journal of cancer \u003c/em\u003e1993, \u003cstrong\u003e54\u003c/strong\u003e(6):911-916.\u003c/li\u003e\n\u003cli\u003eHubacher D, Grimes DA: \u003cstrong\u003eNoncontraceptive health benefits of intrauterine devices: a systematic review\u003c/strong\u003e. \u003cem\u003eObstetrical \u0026amp; gynecological survey \u003c/em\u003e2002, \u003cstrong\u003e57\u003c/strong\u003e(2):120-128.\u003c/li\u003e\n\u003cli\u003eJohnson MJ, Morgan KW: \u003cstrong\u003eIntrauterine contraception benefits extend beyond birth control\u003c/strong\u003e. \u003cem\u003eNurse Pract \u003c/em\u003e2005, \u003cstrong\u003e30\u003c/strong\u003e(2):50-55.\u003c/li\u003e\n\u003cli\u003eMao X, Zhang J, Chen Q, Kuang Y, Zhang S: \u003cstrong\u003eShort-term copper intrauterine device placement improves the implantation and pregnancy rates in women with repeated implantation failure\u003c/strong\u003e. \u003cem\u003eFertil Steril \u003c/em\u003e2017, \u003cstrong\u003e108\u003c/strong\u003e(1):55-61.e51.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization Department of Sexual and Reproductive Health and Research (WHO/SRH) and Johns Hopkins Bloomberg School of Public Health/ Center for Communication Programs (CCP) KS: \u003cstrong\u003eFamily Planning: A Global Handbook for Providers (2022 update)\u003c/strong\u003e: Baltimore and Geneva: CCP and WHO; 2022.\u003c/li\u003e\n\u003cli\u003eJiang B, He WC, Yu JY, Wei SS, Zhang XJ: \u003cstrong\u003eHistory of IUD utilization and the risk of preterm birth: a cohort study\u003c/strong\u003e. \u003cem\u003eArch Gynecol Obstet \u003c/em\u003e2022, \u003cstrong\u003e305\u003c/strong\u003e(2):349-358.\u003c/li\u003e\n\u003cli\u003eGoldthwaite LM, Duca L, Johnson RK, Ostendorf D, Sheeder J: \u003cstrong\u003eAdverse Birth Outcomes in Colorado: Assessing the Impact of a Statewide Initiative to Prevent Unintended Pregnancy\u003c/strong\u003e. \u003cem\u003eAm J Public Health \u003c/em\u003e2015, \u003cstrong\u003e105\u003c/strong\u003e(9):e60-66.\u003c/li\u003e\n\u003cli\u003eZhang S, Wang Q, Shen H: \u003cstrong\u003e[Design of the national free proception health examination project in China]\u003c/strong\u003e. \u003cem\u003eZhonghua Yi Xue Za Zhi \u003c/em\u003e2015, \u003cstrong\u003e95\u003c/strong\u003e(3):162-165.\u003c/li\u003e\n\u003cli\u003eTang J, Zhu X, Li M, Huang D, Zhao Q: \u003cstrong\u003eThe impact of maternal prepregnancy impaired fasting glucose on preterm birth and large for gestational age: a large population-based cohort study\u003c/strong\u003e. \u003cem\u003eAm J Obstet Gynecol \u003c/em\u003e2020, \u003cstrong\u003e222\u003c/strong\u003e(3):265.e261-265.e219.\u003c/li\u003e\n\u003cli\u003eZeng M, He Y, Li M, Yang L, Zhu Q, Liu J, Mao Y, Chen Q, Du J, Zhou W: \u003cstrong\u003eAssociation between maternal pregestational glucose level and adverse pregnancy outcomes: a population-based retrospective cohort study\u003c/strong\u003e. \u003cem\u003eBMJ Open \u003c/em\u003e2021, \u003cstrong\u003e11\u003c/strong\u003e(9):e048530.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWHO: recommended definitions, terminology and format for statistical tables related to the perinatal period and use of a new certificate for cause of perinatal deaths. Modifications recommended by FIGO as amended October 14, 1976\u003c/strong\u003e. \u003cem\u003eActa Obstet Gynecol Scand \u003c/em\u003e1977, \u003cstrong\u003e56\u003c/strong\u003e(3):247-253.\u003c/li\u003e\n\u003cli\u003eBryce E, Gurung S, Tong H, Katz J, Lee AC, Black RE, Walker N: \u003cstrong\u003ePopulation attributable fractions for risk factors for spontaneous preterm births in 81 low- and middle-income countries: A systematic analysis\u003c/strong\u003e. \u003cem\u003eJ Glob Health \u003c/em\u003e2022, \u003cstrong\u003e12\u003c/strong\u003e:04013.\u003c/li\u003e\n\u003cli\u003eSeyama R, Makino S, Nojiri S, Takeda J, Suzuki T, Maruyama Y, Takeda S, Itakura A: \u003cstrong\u003eRetrospective study of the recurrence risk of preterm birth in Japan\u003c/strong\u003e. \u003cem\u003eJ Matern Fetal Neonatal Med \u003c/em\u003e2022, \u003cstrong\u003e35\u003c/strong\u003e(3):515-519.\u003c/li\u003e\n\u003cli\u003eTang J, Chen R, Yu Y, Bao W, Tiemeier H, Rodney A, Zhu X, Li M, Huang D, Zhao Q: \u003cstrong\u003eAssociations of pre-pregnancy impaired fasting glucose and body mass index among pregnant women without pre-existing diabetes with offspring being large for gestational age and preterm birth: a cohort study in China\u003c/strong\u003e. \u003cem\u003eBMJ Open Diabetes Res Care \u003c/em\u003e2021, \u003cstrong\u003e9\u003c/strong\u003e(1).\u003c/li\u003e\n\u003cli\u003ePark A, Wang S, Wu G: \u003cstrong\u003eRegional poverty targeting in China\u003c/strong\u003e. \u003cem\u003eJournal of Public Economics \u003c/em\u003e2002, \u003cstrong\u003e86\u003c/strong\u003e(1):123-153.\u003c/li\u003e\n\u003cli\u003eLiu Y, Liu J, Zhou Y: \u003cstrong\u003eSpatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies\u003c/strong\u003e. \u003cem\u003eJournal of Rural Studies \u003c/em\u003e2017, \u003cstrong\u003e52\u003c/strong\u003e:66-75.\u003c/li\u003e\n\u003cli\u003eWHO: \u003cstrong\u003e\u003cem\u003eHaemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System\u003c/em\u003e\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e, vol. (WHO/NMH/NHD/MNM/11.1). Geneva: World Health Organization; 2011.\u003c/li\u003e\n\u003cli\u003eAndersson T, Alfredsson L, K\u0026auml;llberg H, Zdravkovic S, Ahlbom A: \u003cstrong\u003eCalculating measures of biological interaction\u003c/strong\u003e. \u003cem\u003eEuropean journal of epidemiology \u003c/em\u003e2005, \u003cstrong\u003e20\u003c/strong\u003e(7):575-579.\u003c/li\u003e\n\u003cli\u003eVanderWeele TJ, Knol MJJEM: \u003cstrong\u003eA Tutorial on Interaction\u003c/strong\u003e. 2014, \u003cstrong\u003e3\u003c/strong\u003e:33 - 72.\u003c/li\u003e\n\u003cli\u003eKnol MJ, VanderWeele TJ, Groenwold RH, Klungel OH, Rovers MM, Grobbee DE: \u003cstrong\u003eEstimating measures of interaction on an additive scale for preventive exposures\u003c/strong\u003e. \u003cem\u003eEuropean journal of epidemiology \u003c/em\u003e2011, \u003cstrong\u003e26\u003c/strong\u003e(6):433-438.\u003c/li\u003e\n\u003cli\u003eShi X, Miao W, Tchetgen ET: \u003cstrong\u003eA Selective Review of Negative Control Methods in Epidemiology\u003c/strong\u003e. \u003cem\u003eCurrent epidemiology reports \u003c/em\u003e2020, \u003cstrong\u003e7\u003c/strong\u003e(4):190-202.\u003c/li\u003e\n\u003cli\u003eVogel JP, Chawanpaiboon S, Moller AB, Watananirun K, Bonet M, Lumbiganon P: \u003cstrong\u003eThe global epidemiology of preterm birth\u003c/strong\u003e. \u003cem\u003eBest Pract Res Clin Obstet Gynaecol \u003c/em\u003e2018, \u003cstrong\u003e52\u003c/strong\u003e:3-12.\u003c/li\u003e\n\u003cli\u003eDekel N, Gnainsky Y, Granot I, Mor G: \u003cstrong\u003eInflammation and implantation\u003c/strong\u003e. \u003cem\u003eAm J Reprod Immunol \u003c/em\u003e2010, \u003cstrong\u003e63\u003c/strong\u003e(1):17-21.\u003c/li\u003e\n\u003cli\u003eAchache H, Revel A: \u003cstrong\u003eEndometrial receptivity markers, the journey to successful embryo implantation\u003c/strong\u003e. \u003cem\u003eHuman Reproduction Update \u003c/em\u003e2006, \u003cstrong\u003e12\u003c/strong\u003e(6):731-746.\u003c/li\u003e\n\u003cli\u003eYoost J: \u003cstrong\u003eUnderstanding benefits and addressing misperceptions and barriers to intrauterine device access among populations in the United States\u003c/strong\u003e. \u003cem\u003ePatient Prefer Adherence \u003c/em\u003e2014, \u003cstrong\u003e8\u003c/strong\u003e:947-957.\u003c/li\u003e\n\u003cli\u003eGnainsky Y, Granot I, Aldo PB, Barash A, Or Y, Schechtman E, Mor G, Dekel N: \u003cstrong\u003eLocal injury of the endometrium induces an inflammatory response that promotes successful implantation\u003c/strong\u003e. \u003cem\u003eFertil Steril \u003c/em\u003e2010, \u003cstrong\u003e94\u003c/strong\u003e(6):2030-2036.\u003c/li\u003e\n\u003cli\u003eRama Raju GA, Shashi Kumari G, Krishna KM, Prakash GJ, Madan K: \u003cstrong\u003eAssessment of uterine cavity by hysteroscopy in assisted reproduction programme and its influence on pregnancy outcome\u003c/strong\u003e. \u003cem\u003eArch Gynecol Obstet \u003c/em\u003e2006, \u003cstrong\u003e274\u003c/strong\u003e(3):160-164.\u003c/li\u003e\n\u003cli\u003eHomer HA, Li TC, Cooke ID: \u003cstrong\u003eThe septate uterus: a review of management and reproductive outcome\u003c/strong\u003e. \u003cem\u003eFertil Steril \u003c/em\u003e2000, \u003cstrong\u003e73\u003c/strong\u003e(1):1-14.\u003c/li\u003e\n\u003cli\u003eSalma U, Xue M, Md Sayed AS, Xu D: \u003cstrong\u003eEfficacy of intrauterine device in the treatment of intrauterine adhesions\u003c/strong\u003e. \u003cem\u003eBiomed Res Int \u003c/em\u003e2014, \u003cstrong\u003e2014\u003c/strong\u003e:589296.\u003c/li\u003e\n\u003cli\u003eLi Z, Zhang L: \u003cstrong\u003ePoverty and health-related quality of life: a cross-sectional study in rural China\u003c/strong\u003e. \u003cem\u003eHealth Qual Life Outcomes \u003c/em\u003e2020, \u003cstrong\u003e18\u003c/strong\u003e(1):153.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Intrauterine devices, preterm birth, contraception, pre-pregnancy examination, interaction","lastPublishedDoi":"10.21203/rs.3.rs-4149452/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4149452/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe effect of pre-pregnancy intrauterine device (IUD) use on subsequent preterm birth (PTB) remains unclear. To investigate the association between IUD use before pregnancy and subsequent PTB.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e A total of 242,009 women who participated in the National Free Preconception Health Examination Project (NFPHEP) in Yunnan from 2013 to 2019 were included in the study. All study participants were classified into three groups according to their use of pre-pregnancy contraceptive methods: non-method users, IUD users, and other method users. We used multivariable Poisson regression model to investigate the association between the use of an IUD before pregnancy and subsequent PTB. Further models analyzed the multiplicative and additive interactions between pre-pregnancy IUD use and county deprivation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf all the participants, 45,772 (18.9%) used IUDs before pregnancy, 39,627 (16.4%) used other contraceptive methods, and 156,506 (64.7%) were non-method users. The overall PTB rate was 4.8% (95% confidence interval [95% CI], 4.7\u0026ndash;4.9%), and women in the IUD group had a significantly lower PTB rate (4.3%, 95% CI 4.1\u0026ndash;4.5%) than women in the non-method users (4.9%, 95% CI 4.8\u0026ndash;5.1%) and other method groups (4.7%, 95% CI 4.5\u0026ndash;4.9%). IUD use before pregnancy was associated with a reduced risk of subsequent PTB (model 1: adjusted relative risk [aRR] 0.84, 95% CI 0.79 to 0.88; model 2: aRR 0.84, 95% CI 0.79 to 0.90). In counties with a normal level of development, IUD users had a 30% lower risk of subsequent PTB than non-users (aRR 0.70, 95% CI 0.63 to 0.77). Compared with non-IUD users from the least developed counties, those from counties with a normal level of socioeconomic development had the lowest risk of subsequent PTB (aRR 0.72, 0.62 to 0.83). The additive interaction between pre-pregnancy IUD use and low level of county development was statistically significant (relative excess risk due to interaction [RERI] -0.27, -0.40 to -0.13).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePre-pregnancy IUD use is associated with a reduced risk of subsequent PTB. Pre-pregnancy IUD users in counties with a normal level of development were associated with a lower risk of subsequent PTB than their counterparts in the least developed countries.\u003c/p\u003e","manuscriptTitle":"Pre-pregnancy intrauterine device use is associated with a reduced risk of subsequent preterm birth: a large population-based cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-29 18:49:01","doi":"10.21203/rs.3.rs-4149452/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-27T10:57:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-25T15:18:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-25T15:18:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-03-22T11:39:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1529350b-ea81-4c58-b764-b422e6a66a69","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:04:34+00:00","versionOfRecord":{"articleIdentity":"rs-4149452","link":"https://doi.org/10.1186/s12889-025-21766-9","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-02-18 15:58:04","publishedOnDateReadable":"February 18th, 2025"},"versionCreatedAt":"2024-03-29 18:49:01","video":"","vorDoi":"10.1186/s12889-025-21766-9","vorDoiUrl":"https://doi.org/10.1186/s12889-025-21766-9","workflowStages":[]},"version":"v1","identity":"rs-4149452","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4149452","identity":"rs-4149452","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}