Use of Prophylactic Iron Salts Supplementation During Gestation and Development of Gestational Diabetes Mellitus in Women From 2015 Pelotas (Brazil) Birth Cohort Study

Use of Prophylactic Iron Salts Supplementation During Gestation and Development of Gestational Diabetes Mellitus in Women From 2015 Pelotas (Brazil) Birth 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 Use of Prophylactic Iron Salts Supplementation During Gestation and Development of Gestational Diabetes Mellitus in Women From 2015 Pelotas (Brazil) Birth Cohort Study Vanessa Iribarrem Avena Miranda, Tatiane da Silva Dal Pizzol, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-862873/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study aims to evaluate the association between the use of iron salts during the first two trimesters in non-anemic women and the development of gestational diabetes mellitus (GDM). Methods The study used maternal data from 2015 Pelotas Birth Cohort. All non-anemic women at 24th week (N = 2463) were eligible for this study. GDM was self-reported by women. Crude and adjusted logistic regression were performed considering level of significance = 0.05. Results Among the women studied, 69.7% were exposed to prophylactic iron supplementation in the two first trimesters of gestation. The prevalence of GDM among those exposed was 8.7% (95%CI 7.4–10.1) and among those who were not exposed was 9.3% (CI95% 7.4–11.6). Iron supplementation was not associated with increased risk of GDM in crude (OR = 0.9; 95%CI 0,7–1,3) and adjusted analysis (OR = 1.1; 95% CI 0,8–1,6). Conclusions The results suggested that routine iron use in non-anemic pregnant women does not increase the risk of developing gestational diabetes. This evidence supports the existing national and international guidelines, whose recommendation is prophylactic iron supplementation for all pregnant women as soon as they initiate antenatal care in order to prevent iron deficiency anemia. Maternal & Fetal Medicine Pharmacoepidemiology drug utilization birth cohort study gestational diabetes mellitus supplementation. Figures Figure 1 Background Gestational Diabetes Mellitus (GDM) is a temporary condition, characterized by hyperglycemia, which occurs due to carbohydrate and glucose intolerance ( 1 , 2 ). It begins for the first time during pregnancy and it usually, disappears shortly after delivery ( 1 ). Population estimates of hyperglycemia frequency in pregnancy are conflicting, because there are different criteria for GDM diagnosis, with prevalence varying from 1 to 18% of pregnant women in different populations and differences between guidelines ( 2 , 3 ). In Latin America, for example, the 75 g 2-hour glucose test > 7.8 mmol / L or > 140 mg / dL is a diagnosis of GDM. In China,> 5.1 mmol / L or > 92 mg / dL sets GDM diagnosis( 4 ). GDM is responsible for many consequences in maternal-fetal health in the short and long term ( 3 ). The most common consequences among children are the increased risk of fetal macrosomia, neonatal hypoglycemia, shoulder dystocia, and hyperinsulinemia at birth. Mothers with GDM are at increased risk of preeclampsia, gestational hypertension, cesarean section, and polyhydramnios. In addition, there is an increased risk of fetal malformations, abortion, neonatal and perinatal mortality, as well as increased risk of maternal mortality ( 5 – 8 ). In the long term, the maternal effect of GDM is the elevated risk for the development of metabolic syndrome and type 2 diabetes( 9 ). For the child, there is almost double the risk of developing childhood obesity and metabolic syndrome, compared to children born from non-diabetic mothers ( 9 ). Another very prevalent problem during pregnancy is iron deficiency anemia, reaching 42.0% of all pregnant women ( 10 ). In this sense, current guidelines from World Health Organization (WHO) and Brazilian Ministry of Health recommend, in addition to adequate diet, prophylactic (routine) iron supplementation for all pregnant women, in order to satisfy the physiological needs of this mineral ( 11 , 12 ). However, this universal prophylactic supplementation has been questioned, because according to some authors, high iron intake may increase the risk of GDM, especially for those women with normal hemoglobin levels in early pregnancy( 13 , 14 ), which has been reported as an independent risk factor for DMG ( 15 ). Findings regarding the association between the use of iron salts and the development of gestational diabetes are new and still inconclusive, therefore, further studies are necessary to disentangle the possible relationship between the use of iron salts and GDM. In this study we aimed to evaluate the association between the use of iron salts in non-anemic women in early pregnancy and the development of GDM in a cohort of births whose mothers were followed up since the antenatal period. Methods This paper uses data from antenatal and perinatal studies from Pelotas’ Birth Cohort of 2015 (C2015), which was conducted in the city of Pelotas in southern Brazil. The study invited all women living in the urban area of Pelotas who gave birth, including stillbirths, in the five maternity hospitals of the city, between January 1 and December 31, 2015. Mothers were interviewed at the maternity hospital a few hours after delivery and answered a standardized questionnaire. They answered questions about antenatal period: demographic, socioeconomic, biological and behavioural issues, along with characteristics of pregnancy, delivery and medication use, including folic acid, iron salts and other vitamins and minerals. Furthermore, 75% of mothers who participated in the perinatal study were followed since the antenatal period by this cohort. More details of the study can be found in the cohort profile paper ( 16 ). The analyses in this article were performed with all mothers from a perinatal follow-up who were eligible for this study (N = 2463) (Fig. 1). Anaemic pregnant women before 24th week (with record of at least one hemoglobin test < 11g / dL in the pregnant woman's antenatal card), were not included in the analyses. For the outcome “gestational diabetes mellitus” self-reports were considered. The mothers answered the following question: “Did you have diabetes during pregnancy?”, followed by other question: “Did you have diabetes before pregnancy?”. Pregnant women who already had diabetes before becoming pregnant (n = 44) were excluded. Self-reported information about mother's knowledge of GDM, in the immediate postpartum, was validated through a study previously carried out in Pelotas' maternity, with high specificity (99.0%, 95%CI: 98.1; 99.6) and good sensitivity 73.0% (95%CI: 55.9; 86.2)( 17 ). The variables used in the analysis as possible confounding factors were: maternal age (collected in complete years and categorized as ≤ 19, 20–29, 30–46); ethnicity (self-reported by mothers as white, black or other); parity (total number of deliveries, including stillbirths and current pregnancy; later categorized as 1, 2, 3 or 4 or more); mother’s schooling (number of years of study, later categorized into four groups: 0–4, 5–8, 9–11 and 12 or more years) and family income expressed in local currency and converted into a multiple of minimum wage at the time of the perinatal interview (categorized as ≤ 1, 1.1 to 3.0, 3.1 to 6.0, 6.1 to 10 and > 10). A ‘minimum wage’ is a measure of the legal minimum monthly salary for formal employees in Brazil. Family history of diabetes mellitus was reported by the mother at the 24-month follow-up, pre-pregnancy body mass index (BMI) was calculated by dividing pre-pregnancy weight by the square of maternal height, and categorised according to WHO criteria( 18 ): underweight (< 18.5 kg/m 2 ); normal (18.5–24.9 kg/m 2 ); overweight (25.0–29.9 kg/m 2 ); and obese(≥ 30 kg/m 2 ) and smoking in pregnancy was considered “yes” when the mother reported smoking at least one cigarette a day, for at least 30 days. Information regarding supplement use was taken from the following questions: " Have you used or are you using any vitamin, calcium, folic acid or iron salts since you became pregnant ?”. If yes, the drug names were then questioned and for each drug reported a question about the trimester of use was asked: “In which trimester of pregnancy did you use this medicine?” ( 1st trimester / 2nd trimester, 3rd trimester). From these questions, it was possible to generate the main exposure used in our analyses: “use of prophylactic iron in the first and / or second trimester of pregnancy”, which has been formulated using all iron compounds alone or in combination with other active substances, provided that iron was the main compound present. All analyses were performed in Stata software 15.0. Sample description was performed according to exposure and outcome (GDM) using the chi-square test. The association of iron supplements use with development of GDM was evaluated using logistic regression The regression followed a previously established hierarchical conceptual model, which comprises three levels. The distal level included the sociodemographic variables and family history of diabetes; the second level included pre-gestational BMI, parity and smoke; and the proximal level included the use of iron salts. Variables with p < 0.20 were kept in the model to control confounding factors. For all statistical analyses, the significance threshold was set at p < 0.05. The Federal University of Pelotas, School of Physical Education Ethics Committee, approved the study protocol (522.064). All mothers signed an informed consent form before being interviewed. Results Of the 2463 mothers who participated in this study, about half were between 20 and 29 years old (48.0%), most white skin colour (75.8%) and with more than nine years of schooling (72.1%). The predominant family income was 1.1 to 3 minimum wages (46.0%) and 47.0% of the mothers had pre-gestational BMI considered normal by WHO criteria ( 18 ). More than half of women were in their first pregnancy (52.7%), had no family history of gestational diabetes (55.5%) and most were non-smokers (86.6%) (Table 1 ). Table 1 'Baseline characteristics of mothers participating in the perinatal cohort study (n = 4270) and eligible mothers (n = 2463). 2015 Pelotas (Brazil) Birth Cohort. Variables Perinatal sample Eligible mothers N (%) 95% CI N (%) 95% CI Age ≤ 19 630 (14.8) 13.7–15.8 282 (11.5) 10.2–12.7 20–29 2021 (47.3) 45.8–48.8 1182 (48.0) 46.0–50.0 30–46 1618 (37.9) 36.4–39.4 998 (40.5) 38.5–42.4 Skin colour White 3005 (70.5) 69.1–71.8 1864 (75.8) 74.1–77.4 Black 680 (16.0) 14.8–17.1 305 (12.4) 11.1–13.7 Others 578 (13.5) 12.5–14.5 291 (11.8) 10.5–13.1 Schooling (years) ≤ 4 394 (9.3) 8.3–10.1 168 (6.8) 5.8–7.8 5–8 1098 (25.7) 24.4–27.0 520 (21.1) 19.5–22.7 9–11 1463 (34.3) 32.8–35.7 894 (36.3) 34.4–38.2 ≥ 12 1314 (30.7) 29.4–32.1 881 (35.8) 33.9–37.6 Family income (minimum wages) a ≤ 1 512 (12.6) 11.6–13.6 222 (9.5) 8.3–10.6 1.1–3.0 1906 (47.0) 45.4–48.5 1077 (46.1) 44.0–48.0 3.1–6.0 1077 (26.5) 25.2–27.9 684 (29.2) 27.4–31.1 6.1–10.0 307 (7.5) 6.6–8.2 191 (8.2) 7.0–9.2 > 10.0 257 (6.4) 5.5–7.0 164 (7.0) 5.9–8.1 Pre-pregnancy body mass index (kg/m²) < 18.5 155 (3.8) 0.3–4.3 62 (2.5) 1.2–3.1 18.5 - < 25.0 1037 (49.3) 47.8–50.8 1150 (47.5) 45.5–49.5 25.0 - < 30.0 1160 (28.1) 26.7–29.4 717 (29.6) 27.8–31.4 ≥ 30.0 778 (18.8) 17.6–20.0 490 (20.2) 18.6–21.8 Parity 1 2114 (49.6) 48.0–51.0 1298 (52.7) 50.7–54.6 2 1315 (30.8) 29.4–32.2 780 (31.7) 29.8–33.5 3 472 (11.0) 10.1–12.0 242 (9.8) 8.6–11.0 ≥ 4 367 (8.6) 7.7–9.4 142 (5.8) 4.8–6.6 Family History of GDM b No 1707 (55.9) 54.2–57.8 993 (55.5) 53.2–57.8 Yes 1345 (44.1) 42.2–45.8 795 (44.4) 42.2–46.7 Smoke No 3553 (83.3) 82.1–84.3 2132 (86.6) 85.2–87.9 Yes 714 (16.7) 15.6–17.8 330 (13.4) 12.1–14.8 CI: confidence interval a Family income expressed in local currency and converted into a multiple of minimum wage (R$788,00). b Family history of diabetes mellitus. Variable with highest values of missing information (n = 675). Women eligible for this study did not differ from women participating in the perinatal study of C2015 regarding the characteristics analysed (Table 1 ). Of all women in the analysed sample (N = 2463), 69.7% were exposed to iron supplementation in the first and / or second trimester of pregnancy. The prevalence of GDM was higher among older pregnant women (12.8%), less educated (13.7%), with family income between 1.1 and 3.0 minimum / monthly salaries (10.2%). Pre-pregnancy BMI > = 30 (16.9%), who had 4 or more children (12.6%) and with a family history of diabetes (12.5%) (Table 2 ). Table 2 Prevalence of gestational diabetes mellitus (GDM) according to independent variables (N = 2463). 2015 Pelotas (Brazil) Birth Cohort. Variables Prevalence of DMG N % 95%CI p-value a Age < 0.001 ≤ 19 6 2,1 0.9–4.6 20–29 84 7.1 5.7–8.7 30–46 128 12.8 10.8–15.1 Skin colour 0.202 White 156 8.4 7.1–9.7 Black 35 11.4 8.3–15.6 Others 27 9.2 6.4–13.2 Schooling (years) 0.004 ≤ 4 23 13.7 9.2–19.8 5–8 37 7.1 5.1–9.6 9–11 95 10.6 8.7–12.8 ≥ 12 63 7.2 5.6–9.1 Family income (minimum wages) b 0.002 ≤ 1 19 8.5 5.5–13.0 1.1–3.0 110 10.2 8.6–12.2 3.1–6.0 68 9.9 7.9–12.4 6.1–10.0 8 4.2 2.1–8.1 > 10.0 4 2.4 0.9–6.3 Pre-pregnancy body mass index (kg/m²) < 0.001 < 18.5 1 1.6 0.2–11.1 18.5 - <25.0 61 5.3 4.1–6.7 25.0 - <30.0 70 9.7 7.7–12.1 ≥ 30.0 83 16.9 13.8–20.5 Parity < 0.001 1 83 6.4 5.1–7.8 2 87 11.2 9.1–13.5 3 30 12.4 8.7–17.2 ≥ 4 18 12.6 8.0–19.3 Family History of GDM c < 0.001 No 77 7.8 6.2–9.6 Yes 100 12.5 10.4–15.1 Smoke 0.644 No 191 8.9 7.8–10.2 Yes 27 8.1 5.6–11.6 Iron supplementation 0.626 No 68 9.3 7.4–11.5 Yes 146 8.7 7.4–10.1 Total 214 8.8 7.7–10.0 CI: confidence interval a p value of chi-square test b Family income expressed in local currency and converted into a multiple of minimum wage (R$788,00) c Family history of diabetes mellitus gestational. Variable with highest values of missing information (n = 675). The prevalence of self-reported GDM in the entire cohort (N = 4270) was 8.5% (95% CI 7.6; 9.3) and among those eligible for this study was 8.8% (95% CI 7.7 ; 10.0), being 8.6% (95% CI 7.3 ; 10.0) among exposed and 9.2% (95% CI 8.9 ; 9.2) among those not exposed to iron supplements (Table 2 ). The use of iron salts in the first or second gestational trimester showed no positive association with GDM both in the crude analysis (OR = 0.9 95% CI 0.6; 1.3) and in the adjusted analysis for skin colour, age, education, family income, pre-gestational BMI, parity, family history of diabetes mellitus and smoking during pregnancy (OR = 1.1 95% CI 0.8; 1.5) (Table 3 ). Table 3 Association between iron salt supplementation and gestational diabetes mellitus among non-anemic women. 2015 Pelotas (Brazil) Birth Cohort. Iron supplementation Crude Adjusted a OR (95% CI) p-value OR (95% CI) p-value Non-anaemic pregnant women up to 24th weeks (N = 2463) 0.509 0.420 No Reference (1.0) Reference (1.0) Yes 0.9 (0.7–1.3) 1.1 (0.8–1.6) Non-anaemic pregnant women up to 12th weeks (N = 2559) 0.631 0.405 No Reference (1.0) Reference (1.0) Yes 1.1 (0.8–1.6) 1.2 (0.8–1.7) OR: odds ratio a Model adjusted for skin color, age, education, family income in minimum wages, pre-gestational BMI, parity, smoking during pregnancy, family history of diabetes mellitus. A subset of analyses was performed for data corresponding to the first trimester of pregnancy (up to 12th weeks). Results were similar from those derived from the main analyses (including the first and/or second trimester (adjusted OR = 1.2 95% CI 0.8; 1.7) (Table 3 ). Discussion This study showed that, among non-anemic women, prophylactic use of iron in the first and/or second trimester of pregnancy was not an independent risk factor for the development of GDM Published evidence on this subject is controversial. Previous observational studies have suggested that higher stores of iron might be associated with glucose metabolism disorders and an increase in the risk of GDM( 19 – 24 ). This relation is biologically plausible, because iron has a high capacity of oxirreduction and its free form can catalyze the formation of free radicals, causing cell damage, also known as oxidative stress. Therefore, other suggested mechanism involves the formation of hidroxil radical which can damage the cell membranes of pancreatic ß cells, affecting insulin synthesis and secretion associated with pregnancy-induced insulin resistance( 25 , 26 ). Also, the excess of iron deposition in the muscle may decrease glucose uptake ( 26 ). However, three randomized controlled trials, performed in hospitals and primary care services in China (N = 1164)( 27 ), Finland (N = 2912)( 28 ) and United Arab Emirates (N = 960)( 29 ), found no significant difference in the incidence of GDM between control and experimental women. The daily iron dose in the experimental group ranged from 30mg to 60mg administered during the first and second gestational trimesters ( 28 – 30 ). In the control group two studies used placebo ( 28 , 30 ) and one used a lower dosage of iron and a frequency of use lower than the experimental group ( 29 ). It should be noted that one of the randomized clinical trials cited ( 27 ) reported poor adherence to supplementation, which is a reality among pregnant women, mainly due to the undesirable adverse effects of iron supplementation ( 31 ), a fact that may alter the results of this and other researches, underestimating the real effect of this compound. In our study no differences were found in the prevalence of GDM between women exposed and not exposed to the supplement, as in the study of Chan et al., 2009( 27 ), who did not find increased incidence of GDM in the exposed group. The analysis of the study association may be limited due to lack of information regarding dosage, adherence, frequency of use and exposure time. Dosage information would be useful for qualifying the exposure variable (use of iron salts), considering "yes" only those compounds with prophylactic dosage. Knowledge of adherence to iron salt compounds would allow a better selection of women eligible for the study, and exposure time would be useful for estimating dose-response effect. Regardless of the findings concerning the occurrence of GDM and iron use, it is a fact that GDM has been increasing in several countries as a result of population growth, increased maternal age, lack of physical activity and, especially, the increased prevalence of obesity ( 3 , 32 ), and our findings confirm this trend, presenting prevalence of self-reported gestational diabetes almost three times higher than (8.5%; IC = 7.8 ; 9.6) another birth cohort study conducted in the year 2004, also in the city of Pelotas, with 4231 pregnant women, which found a self-reported prevalence of 3.0% gestational diabetes (95% CI: 2.53 ; 3.64)( 33 ). It is known that there are many divergences between the diagnostic criteria used for GDM, but between 2004 and 2015 there were no changes in the diagnostic test cut-offs in the recommendations from Brazilian Ministry of Health ( 12 , 34 ). Among the limitations of this study, it should be noted that many pregnant women had only one or two hemoglobin results in the antenatal card, thus, pregnant women who had only one recorded hemoglobin test whose result was normal (non-anaemic), were eligible for our study. However, they may have developed anaemia later and such information was not registered in the card. On the other hand, the use of information from antenatal records completed by health professionals who followed this pregnant women was a positive aspect and considered indispensable for the definition of women eligible for the study, since these results enabled the identification of non-anemic pregnant women according to the gestational trimester, which guaranteed the temporality of the study association. Information on GDM diagnostic and iron use was self-reported only, which can be considered other limitations of this study. Furthermore, the control variable “family history of diabetes”, was collected only from the third month of the 24-month follow-up of the children, which resulted in a high number of missing information (27.4%). Among the positive aspects, we highlight the fact that all pregnant women who had a hospital delivery in the municipality were interviewed within one year, and the small number of refusals, which allows the generalization of the results to other pregnant women under the same conditions of our sample. Conclusions Our study showed that the use of iron supplementation in non-anaemic pregnant women was not related with the development of GDM, which meets current national and international guidelines, whose recommendation is the routine supplementation to all pregnant women as soon as they start antenatal care to prevent iron deficiency anaemia. List Of Abbreviations Gestational diabetes mellitus (GDM) World Health Organization (WHO) Body mass index (BMI) Declarations Ethics approval and consent to participate: The Federal University of Pelotas, School of Physical Education Ethics Committee, approved the study protocol (approval number 522.064). All mothers signed an informed consent form before being interviewed. All methods were carried out in accordance with relevant guidelines and regulations. Consent for publication : Not applicable. Availability of data and materials: Due to confidentiality restrictions related to the ethics approval for this study, no identifying information about participants may be released. Dataset without identification used during the current study are available from the corresponding author on reasonable request. Competing interests: none to declare Funding: This article is based on data from the study "Pelotas Birth Cohort, 2015" conducted by Postgraduate Program in Epidemiology at Federal University of Pelotas, with the collaboration of the Brazilian Public Health Association (ABRASCO). The 2015 Pelotas (Brazil) Birth Cohort is funded by the Wellcome Trust (095582). Funding for specific follow-up visits was also received from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Author Contributions: conceptualization, VIAM, MPTS, TSDP and ADB; methodology, VIAM, MPTS, SSM, BHL and ADB; formal analysis, VIAM, MPTS, RB and ADB; writing—original draft preparation, VIAM; writing—review and editing, VIAM, MPTS, TSDP, MSF, SSM, BHL, RB and ADB; supervision, MPTS, TSDP and ADB; project administration, ADB and MFS. All authors have read and approved the manuscript. Acknowledgements: We are grateful to all the families who took part in the Pelotas birth cohorts, and the Pelotas teams, including research scientists, interviewers, workers and volunteers. References World Health Organization. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy: a World Health Organization Guideline. Diabetes Res Clin Pract. 2013. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2012. Diabetes OP-AdSMdSFBdAdGeOSBd. Rastreamento e diagnóstico de diabetes mellitus gestacional no Brasil. 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Dode MA, Santos Ida S. [Risk factors for gestational diabetes mellitus in the birth cohort in Pelotas, Rio Grande do Sul State, Brazil, 2004]. Cad Saude Publica. 2009;25(5):1141–52. Assistência pré-natal: normas e manuais técnicos., (1998). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-862873","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":53961550,"identity":"2cdab87d-c97b-4524-ad23-ad57dfd21c9b","order_by":0,"name":"Vanessa Iribarrem Avena Miranda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBADHgZm5gNAWkKGFC1sCSAtPCRZZADRSwgYHD978OGPP3Yy5u08n1/dqLHgYWA/fHQDXi1n8pKNeduSeWQO826zzjkGdBhPWtoNfFokG3LMpBkbmHkkmHm3GeewAbVI8Jjh19L/xvznjz/1QC08z4xz/hGhhV8ix4yBh+0wSAvz49w2orS8MZbmbTsO1MJmxpzbJ8HDRsgvbPw5hh9//Km2l+A//Phzzrc6OX72w8fwakHRLgEmiVUOAswfSFE9CkbBKBgFIwcAACF+O5T5pMznAAAAAElFTkSuQmCC","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Vanessa","middleName":"Iribarrem Avena","lastName":"Miranda","suffix":""},{"id":53961552,"identity":"df57bd02-2c6c-4dc9-98cb-73968243617b","order_by":1,"name":"Tatiane da Silva Dal Pizzol","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tatiane","middleName":"da Silva Dal","lastName":"Pizzol","suffix":""},{"id":53961554,"identity":"494aeba8-559e-4c71-a552-1aab7a6a6a31","order_by":2,"name":"Marysabel Pinto Telis Silveira","email":"","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marysabel","middleName":"Pinto Telis","lastName":"Silveira","suffix":""},{"id":53961555,"identity":"387ec7e9-b4e6-42e7-a40e-2c6ff32b758b","order_by":3,"name":"Sotero Serrate Mengue","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sotero","middleName":"Serrate","lastName":"Mengue","suffix":""},{"id":53961556,"identity":"a67364fa-8e2a-4de6-acb6-18b9127ffd8e","order_by":4,"name":"Mariângela Freitas Silveira","email":"","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mariângela","middleName":"Freitas","lastName":"Silveira","suffix":""},{"id":53961557,"identity":"c2b8f2d4-c1de-41f5-b5a8-ce43f77f4fb0","order_by":5,"name":"Bárbara H Lutz","email":"","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bárbara","middleName":"H","lastName":"Lutz","suffix":""},{"id":53961558,"identity":"79a6e6b5-aa02-41f5-99d2-1b77879cb585","order_by":6,"name":"Romina Buffarini","email":"","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Romina","middleName":"","lastName":"Buffarini","suffix":""},{"id":53961559,"identity":"42bb2a67-1253-4aaf-864a-9651d242b6d5","order_by":7,"name":"Andréa Dâmaso Bertoldi","email":"","orcid":"","institution":"Federal University of Pelotas","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Andréa","middleName":"Dâmaso","lastName":"Bertoldi","suffix":""}],"badges":[],"createdAt":"2021-08-31 20:44:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-862873/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-862873/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14016856,"identity":"470557c5-d872-42c2-b9b7-d1685015e9cc","added_by":"auto","created_at":"2021-09-27 14:21:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70354,"visible":true,"origin":"","legend":"Flowchart of the study population of eligible women. 2015 Pelotas (Brazil) Birth Cohort.","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-862873/v1/4387185009f669b5799c788b.jpg"},{"id":16169296,"identity":"2afc8944-fe0b-498b-ae9b-1f7f59e59eba","added_by":"auto","created_at":"2021-12-04 09:14:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":474590,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-862873/v1/29cd6321-bad0-4c79-89a8-398bcd84da27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eUse of Prophylactic Iron Salts Supplementation During Gestation and Development of Gestational Diabetes Mellitus in Women From 2015 Pelotas (Brazil) Birth Cohort Study\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eGestational Diabetes Mellitus (GDM) is a temporary condition, characterized by hyperglycemia, which occurs due to carbohydrate and glucose intolerance (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It begins for the first time during pregnancy and it usually, disappears shortly after delivery (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Population estimates of hyperglycemia frequency in pregnancy are conflicting, because there are different criteria for GDM diagnosis, with prevalence varying from 1 to 18% of pregnant women in different populations and differences between guidelines (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Latin America, for example, the 75 g 2-hour glucose test\u0026thinsp;\u0026gt;\u0026thinsp;7.8 mmol / L or \u0026gt;\u0026thinsp;140 mg / dL is a diagnosis of GDM. In China,\u0026gt; 5.1 mmol / L or \u0026gt;\u0026thinsp;92 mg / dL sets GDM diagnosis(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGDM is responsible for many consequences in maternal-fetal health in the short and long term (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The most common consequences among children are the increased risk of fetal macrosomia, neonatal hypoglycemia, shoulder dystocia, and hyperinsulinemia at birth. Mothers with GDM are at increased risk of preeclampsia, gestational hypertension, cesarean section, and polyhydramnios. In addition, there is an increased risk of fetal malformations, abortion, neonatal and perinatal mortality, as well as increased risk of maternal mortality (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In the long term, the maternal effect of GDM is the elevated risk for the development of metabolic syndrome and type 2 diabetes(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). For the child, there is almost double the risk of developing childhood obesity and metabolic syndrome, compared to children born from non-diabetic mothers (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother very prevalent problem during pregnancy is iron deficiency anemia, reaching 42.0% of all pregnant women (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In this sense, current guidelines from World Health Organization (WHO) and Brazilian Ministry of Health recommend, in addition to adequate diet, prophylactic (routine) iron supplementation for all pregnant women, in order to satisfy the physiological needs of this mineral (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, this universal prophylactic supplementation has been questioned, because according to some authors, high iron intake may increase the risk of GDM, especially for those women with normal hemoglobin levels in early pregnancy(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), which has been reported as an independent risk factor for DMG (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFindings regarding the association between the use of iron salts and the development of gestational diabetes are new and still inconclusive, therefore, further studies are necessary to disentangle the possible relationship between the use of iron salts and GDM. In this study we aimed to evaluate the association between the use of iron salts in non-anemic women in early pregnancy and the development of GDM in a cohort of births whose mothers were followed up since the antenatal period.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis paper uses data from antenatal and perinatal studies from Pelotas\u0026rsquo; Birth Cohort of 2015 (C2015), which was conducted in the city of Pelotas in southern Brazil. The study invited all women living in the urban area of Pelotas who gave birth, including stillbirths, in the five maternity hospitals of the city, between January 1 and December 31, 2015.\u003c/p\u003e\n\u003cp\u003eMothers were interviewed at the maternity hospital a few hours after delivery and answered a standardized questionnaire. They answered questions about antenatal period: demographic, socioeconomic, biological and behavioural issues, along with characteristics of pregnancy, delivery and medication use, including folic acid, iron salts and other vitamins and minerals. Furthermore, 75% of mothers who participated in the perinatal study were followed since the antenatal period by this cohort. More details of the study can be found in the cohort profile paper (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe analyses in this article were performed with all mothers from a perinatal follow-up who were eligible for this study (N\u0026thinsp;=\u0026thinsp;2463) (Fig. 1). Anaemic pregnant women before 24th week (with record of at least one hemoglobin test\u0026thinsp;\u0026lt;\u0026thinsp;11g / dL in the pregnant woman\u0026apos;s antenatal card), were not included in the analyses.\u003c/p\u003e\n\u003cp\u003eFor the outcome \u0026ldquo;gestational diabetes mellitus\u0026rdquo; self-reports were considered. The mothers answered the following question: \u0026ldquo;Did you have diabetes during pregnancy?\u0026rdquo;, followed by other question: \u0026ldquo;Did you have diabetes before pregnancy?\u0026rdquo;. Pregnant women who already had diabetes before becoming pregnant (n\u0026thinsp;=\u0026thinsp;44) were excluded. Self-reported information about mother\u0026apos;s knowledge of GDM, in the immediate postpartum, was validated through a study previously carried out in Pelotas\u0026apos; maternity, with high specificity (99.0%, 95%CI: 98.1; 99.6) and good sensitivity 73.0% (95%CI: 55.9; 86.2)(\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe variables used in the analysis as possible confounding factors were: maternal age (collected in complete years and categorized as \u0026le;\u0026thinsp;19, 20\u0026ndash;29, 30\u0026ndash;46); ethnicity (self-reported by mothers as white, black or other); parity (total number of deliveries, including stillbirths and current pregnancy; later categorized as 1, 2, 3 or 4 or more); mother\u0026rsquo;s schooling (number of years of study, later categorized into four groups: 0\u0026ndash;4, 5\u0026ndash;8, 9\u0026ndash;11 and 12 or more years) and family income expressed in local currency and converted into a multiple of minimum wage at the time of the perinatal interview (categorized as \u0026le;\u0026thinsp;1, 1.1 to 3.0, 3.1 to 6.0, 6.1 to 10 and \u0026gt;\u0026thinsp;10). A \u0026lsquo;minimum wage\u0026rsquo; is a measure of the legal minimum monthly salary for formal employees in Brazil.\u003c/p\u003e\n\u003cp\u003eFamily history of diabetes mellitus was reported by the mother at the 24-month follow-up, pre-pregnancy body mass index (BMI) was calculated by dividing pre-pregnancy weight by the square of maternal height, and categorised according to WHO criteria(\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e): underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e); normal (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e); overweight (25.0\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e); and obese(\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) and smoking in pregnancy was considered \u0026ldquo;yes\u0026rdquo; when the mother reported smoking at least one cigarette a day, for at least 30 days.\u003c/p\u003e\n\u003cp\u003eInformation regarding supplement use was taken from the following questions: \u003cem\u003e\u0026quot; Have you used or are you using any vitamin, calcium, folic acid or iron salts since you became pregnant\u003c/em\u003e?\u0026rdquo;. If yes, the drug names were then questioned and for each drug reported a question about the trimester of use was asked: \u003cem\u003e\u0026ldquo;In which trimester of pregnancy did you use this medicine?\u0026rdquo; (\u003c/em\u003e1st trimester / 2nd trimester, 3rd trimester).\u003c/p\u003e\n\u003cp\u003eFrom these questions, it was possible to generate the main exposure used in our analyses: \u0026ldquo;use of prophylactic iron in the first and / or second trimester of pregnancy\u0026rdquo;, which has been formulated using all iron compounds alone or in combination with other active substances, provided that iron was the main compound present. All analyses were performed in Stata \u003cem\u003esoftware\u003c/em\u003e 15.0. Sample description was performed according to exposure and outcome (GDM) using the chi-square test. The association of iron supplements use with development of GDM was evaluated using logistic regression\u003c/p\u003e\n\u003cp\u003eThe regression followed a previously established hierarchical conceptual model, which comprises three levels. The distal level included the sociodemographic variables and family history of diabetes; the second level included pre-gestational BMI, parity and smoke; and the proximal level included the use of iron salts. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 were kept in the model to control confounding factors. For all statistical analyses, the significance threshold was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003cp\u003eThe Federal University of Pelotas, School of Physical Education Ethics Committee, approved the study protocol (522.064). All mothers signed an informed consent form before being interviewed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 2463 mothers who participated in this study, about half were between 20 and 29 years old (48.0%), most white skin colour (75.8%) and with more than nine years of schooling (72.1%). The predominant family income was 1.1 to 3 minimum wages (46.0%) and 47.0% of the mothers had pre-gestational BMI considered normal by WHO criteria (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). More than half of women were in their first pregnancy (52.7%), had no family history of gestational diabetes (55.5%) and most were non-smokers (86.6%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e'Baseline characteristics of mothers participating in the perinatal cohort study (n\u0026thinsp;=\u0026thinsp;4270) and eligible mothers (n\u0026thinsp;=\u0026thinsp;2463). 2015 Pelotas (Brazil) Birth Cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePerinatal sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEligible mothers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e630 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.7\u0026ndash;15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u0026ndash;12.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.8\u0026ndash;48.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1182 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.0\u0026ndash;50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1618 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.4\u0026ndash;39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e998 (40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.5\u0026ndash;42.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSkin colour\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3005 (70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.1\u0026ndash;71.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1864 (75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.1\u0026ndash;77.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e680 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.8\u0026ndash;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e305 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.1\u0026ndash;13.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e578 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u0026ndash;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e291 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.5\u0026ndash;13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchooling (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e394 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3\u0026ndash;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.8\u0026ndash;7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1098 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.4\u0026ndash;27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e520 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.5\u0026ndash;22.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1463 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.8\u0026ndash;35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e894 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.4\u0026ndash;38.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1314 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.4\u0026ndash;32.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e881 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.9\u0026ndash;37.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily income (minimum wages)\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e512 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u0026ndash;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u0026ndash;10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.1\u0026ndash;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1906 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.4\u0026ndash;48.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1077 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.0\u0026ndash;48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.1\u0026ndash;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1077 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.2\u0026ndash;27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e684 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.4\u0026ndash;31.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.1\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6\u0026ndash;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.0\u0026ndash;9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e257 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5\u0026ndash;7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e164 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.9\u0026ndash;8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePre-pregnancy body mass index (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u0026ndash;4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u0026ndash;3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5 - \u0026lt; 25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1037 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.8\u0026ndash;50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1150 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.5\u0026ndash;49.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.0 - \u0026lt; 30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1160 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.7\u0026ndash;29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e717 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.8\u0026ndash;31.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e778 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.6\u0026ndash;20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e490 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.6\u0026ndash;21.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2114 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.0\u0026ndash;51.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1298 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.7\u0026ndash;54.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1315 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.4\u0026ndash;32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e780 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.8\u0026ndash;33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e472 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1\u0026ndash;12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e242 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.6\u0026ndash;11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e367 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7\u0026ndash;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.8\u0026ndash;6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily History of GDM\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1707 (55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.2\u0026ndash;57.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e993 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.2\u0026ndash;57.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1345 (44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.2\u0026ndash;45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e795 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.2\u0026ndash;46.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3553 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.1\u0026ndash;84.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2132 (86.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85.2\u0026ndash;87.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e714 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6\u0026ndash;17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e330 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.1\u0026ndash;14.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Family income expressed in local currency and converted into a multiple of minimum wage (R$788,00).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e Family history of diabetes mellitus. Variable with highest values of missing information (n\u0026thinsp;=\u0026thinsp;675).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWomen eligible for this study did not differ from women participating in the perinatal study of C2015 regarding the characteristics analysed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOf all women in the analysed sample (N\u0026thinsp;=\u0026thinsp;2463), 69.7% were exposed to iron supplementation in the first and / or second trimester of pregnancy. The prevalence of GDM was higher among older pregnant women (12.8%), less educated (13.7%), with family income between 1.1 and 3.0 minimum / monthly salaries (10.2%). Pre-pregnancy BMI\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;30 (16.9%), who had 4 or more children (12.6%) and with a family history of diabetes (12.5%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of gestational diabetes mellitus (GDM) according to independent variables (N\u0026thinsp;=\u0026thinsp;2463). 2015 Pelotas (Brazil) Birth Cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePrevalence of DMG\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u0026ndash;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u0026ndash;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8\u0026ndash;15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSkin colour\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.1\u0026ndash;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.3\u0026ndash;15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.4\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchooling (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u0026ndash;19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u0026ndash;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7\u0026ndash;12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6\u0026ndash;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily income (minimum wages)\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.5\u0026ndash;13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.1\u0026ndash;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.6\u0026ndash;12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.1\u0026ndash;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.9\u0026ndash;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.1\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u0026ndash;8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u0026ndash;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePre-pregnancy body mass index (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u0026ndash;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5 - \u0026lt;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u0026ndash;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.0 - \u0026lt;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u0026ndash;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.8\u0026ndash;20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u0026ndash;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1\u0026ndash;13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7\u0026ndash;17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u0026ndash;19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily History of GDM\u003c/b\u003e\u003csup\u003e\u003cb\u003ec\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2\u0026ndash;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.4\u0026ndash;15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u0026ndash;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6\u0026ndash;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIron supplementation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u0026ndash;11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u0026ndash;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u0026ndash;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e p value of chi-square test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e Family income expressed in local currency and converted into a multiple of minimum wage (R$788,00)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ec\u003c/sup\u003e Family history of diabetes mellitus gestational. Variable with highest values of missing information (n\u0026thinsp;=\u0026thinsp;675).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe prevalence of self-reported GDM in the entire cohort (N\u0026thinsp;=\u0026thinsp;4270) was 8.5% (95% CI 7.6; 9.3) and among those eligible for this study was 8.8% (95% CI 7.7 ; 10.0), being 8.6% (95% CI 7.3 ; 10.0) among exposed and 9.2% (95% CI 8.9 ; 9.2) among those not exposed to iron supplements (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe use of iron salts in the first or second gestational trimester showed no positive association with GDM both in the crude analysis (OR\u0026thinsp;=\u0026thinsp;0.9 95% CI 0.6; 1.3) and in the adjusted analysis for skin colour, age, education, family income, pre-gestational BMI, parity, family history of diabetes mellitus and smoking during pregnancy (OR\u0026thinsp;=\u0026thinsp;1.1 95% CI 0.8; 1.5) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between iron salt supplementation and gestational diabetes mellitus among non-anemic women. 2015 Pelotas (Brazil) Birth Cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIron supplementation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-anaemic pregnant women up to 24th weeks (N\u0026thinsp;=\u0026thinsp;2463)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.7\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.8\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-anaemic pregnant women up to 12th weeks (N\u0026thinsp;=\u0026thinsp;2559)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1 (0.8\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2 (0.8\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR: odds ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Model adjusted for skin color, age, education, family income in minimum wages, pre-gestational BMI, parity, smoking during pregnancy, family history of diabetes mellitus.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA subset of analyses was performed for data corresponding to the first trimester of pregnancy (up to 12th weeks). Results were similar from those derived from the main analyses (including the first and/or second trimester (adjusted OR\u0026thinsp;=\u0026thinsp;1.2 95% CI 0.8; 1.7) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study showed that, among non-anemic women, prophylactic use of iron in the first and/or second trimester of pregnancy was not an independent risk factor for the development of GDM\u003c/p\u003e \u003cp\u003ePublished evidence on this subject is controversial. Previous observational studies have suggested that higher stores of iron might be associated with glucose metabolism disorders and an increase in the risk of GDM(\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This relation is biologically plausible, because iron has a high capacity of oxirreduction and its free form can catalyze the formation of free radicals, causing cell damage, also known as oxidative stress. Therefore, other suggested mechanism involves the formation of hidroxil radical which can damage the cell membranes of pancreatic \u0026szlig; cells, affecting insulin synthesis and secretion associated with pregnancy-induced insulin resistance(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Also, the excess of iron deposition in the muscle may decrease glucose uptake (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). However, three randomized controlled trials, performed in hospitals and primary care services in China (N\u0026thinsp;=\u0026thinsp;1164)(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), Finland (N\u0026thinsp;=\u0026thinsp;2912)(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) and United Arab Emirates (N\u0026thinsp;=\u0026thinsp;960)(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), found no significant difference in the incidence of GDM between control and experimental women. The daily iron dose in the experimental group ranged from 30mg to 60mg administered during the first and second gestational trimesters (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). In the control group two studies used placebo (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) and one used a lower dosage of iron and a frequency of use lower than the experimental group (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). It should be noted that one of the randomized clinical trials cited (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) reported poor adherence to supplementation, which is a reality among pregnant women, mainly due to the undesirable adverse effects of iron supplementation (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), a fact that may alter the results of this and other researches, underestimating the real effect of this compound.\u003c/p\u003e \u003cp\u003eIn our study no differences were found in the prevalence of GDM between women exposed and not exposed to the supplement, as in the study of Chan et al., 2009(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), who did not find increased incidence of GDM in the exposed group. The analysis of the study association may be limited due to lack of information regarding dosage, adherence, frequency of use and exposure time. Dosage information would be useful for qualifying the exposure variable (use of iron salts), considering \"yes\" only those compounds with prophylactic dosage. Knowledge of adherence to iron salt compounds would allow a better selection of women eligible for the study, and exposure time would be useful for estimating dose-response effect.\u003c/p\u003e \u003cp\u003eRegardless of the findings concerning the occurrence of GDM and iron use, it is a fact that GDM has been increasing in several countries as a result of population growth, increased maternal age, lack of physical activity and, especially, the increased prevalence of obesity (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and our findings confirm this trend, presenting prevalence of self-reported gestational diabetes almost three times higher than (8.5%; IC\u0026thinsp;=\u0026thinsp;7.8 ; 9.6) another birth cohort study conducted in the year 2004, also in the city of Pelotas, with 4231 pregnant women, which found a self-reported prevalence of 3.0% gestational diabetes (95% CI: 2.53 ; 3.64)(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). It is known that there are many divergences between the diagnostic criteria used for GDM, but between 2004 and 2015 there were no changes in the diagnostic test cut-offs in the recommendations from Brazilian Ministry of Health (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the limitations of this study, it should be noted that many pregnant women had only one or two hemoglobin results in the antenatal card, thus, pregnant women who had only one recorded hemoglobin test whose result was normal (non-anaemic), were eligible for our study. However, they may have developed anaemia later and such information was not registered in the card. On the other hand, the use of information from antenatal records completed by health professionals who followed this pregnant women was a positive aspect and considered indispensable for the definition of women eligible for the study, since these results enabled the identification of non-anemic pregnant women according to the gestational trimester, which guaranteed the temporality of the study association.\u003c/p\u003e \u003cp\u003eInformation on GDM diagnostic and iron use was self-reported only, which can be considered other limitations of this study. Furthermore, the control variable \u0026ldquo;family history of diabetes\u0026rdquo;, was collected only from the third month of the 24-month follow-up of the children, which resulted in a high number of missing information (27.4%).\u003c/p\u003e \u003cp\u003eAmong the positive aspects, we highlight the fact that all pregnant women who had a hospital delivery in the municipality were interviewed within one year, and the small number of refusals, which allows the generalization of the results to other pregnant women under the same conditions of our sample.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e Our study showed that the use of iron supplementation in non-anaemic pregnant women was not related with the development of GDM, which meets current national and international guidelines, whose recommendation is the routine supplementation to all pregnant women as soon as they start antenatal care to prevent iron deficiency anaemia.\u003c/p\u003e "},{"header":"List Of Abbreviations","content":" \u003cp\u003eGestational diabetes mellitus (GDM)\u003c/p\u003e \u003cp\u003eWorld Health Organization (WHO)\u003c/p\u003e \u003cp\u003eBody mass index (BMI)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e The Federal University of Pelotas, School of Physical Education Ethics Committee, approved the study protocol (approval number 522.064). All mothers signed an informed consent form before being interviewed.\u0026nbsp;All methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eDue to confidentiality restrictions related to the ethics approval for this study, no identifying information about participants may be released. Dataset without identification used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003enone to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis article is based on data from the study \u0026quot;Pelotas Birth Cohort, 2015\u0026quot; conducted by Postgraduate Program in Epidemiology at Federal University of Pelotas, with the collaboration of the Brazilian Public Health Association (ABRASCO). The 2015 Pelotas (Brazil) Birth Cohort is funded by the Wellcome Trust (095582).\u0026nbsp;Funding for specific follow-up visits was also received from the Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) and Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa do Estado do Rio Grande do Sul (FAPERGS). \u0026nbsp;This study was financed in part by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - Brasil (CAPES) - Finance Code 001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003econceptualization, VIAM, MPTS, TSDP and ADB; methodology, VIAM, MPTS, SSM, BHL and ADB; formal analysis, VIAM, MPTS, RB and ADB; writing\u0026mdash;original draft preparation, VIAM; writing\u0026mdash;review and editing, VIAM, MPTS, TSDP, MSF, SSM, BHL, RB and ADB; supervision, MPTS, TSDP and ADB; project administration, ADB and MFS. All\u0026nbsp;authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe are grateful to all the families who took part in the Pelotas birth cohorts, and the Pelotas teams, including research scientists, interviewers, workers and volunteers.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy: a World Health Organization Guideline. Diabetes Res Clin Pract. 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmerican Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiabetes OP-AdSMdSFBdAdGeOSBd. Rastreamento e diagn\u0026oacute;stico de diabetes mellitus gestacional no Brasil. 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Maternal hemoglobin and risk of gestational diabetes mellitus in chinese women. Obstet Gynecol. 2002;99(5):807\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJavadian P, Alimohamadi S, Gharedaghi MH, Hantoushzadeh S. Gestational diabetes mellitus and iron supplement; effects on pregnancy outcome. Acta Medica Iranica. 2014;52(5):385.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOzyigit EA, Ugur M, Unlu S, Ozaksit G, Avsar F. The Effect of Oral Iron Supplementation on the Glucose Metabolism in Non-Anemic Pregnant Women: A Prospective Case-Control Study. Uhod-Uluslararasi Hematoloji-Onkoloji Dergisi. 2008;18(3):155\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRawal S, Hinkle SN, Bao W, Zhu Y, Grewal J, Albert PS, et al. A longitudinal study of iron status during pregnancy and the risk of gestational diabetes: findings from a prospective, multiracial cohort. Diabetologia. 2017;60(2):249\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandez-Cao JC, Aranda N, Ribot B, Tous M, Arija V. Elevated iron status and risk of gestational diabetes mellitus: A systematic review and meta-analysis. Matern Child Nutr. 2017;13(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasanueva E, Viteri FE. Iron and oxidative stress in pregnancy. J Nutr. 2003;133(5 Suppl 2):1700s-8s.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Q, Sun L, Tan Y, Wang G, Lin X, Cai L. Role of iron deficiency and overload in the pathogenesis of diabetes and diabetic complications. Curr Med Chem. 2009;16(1):113\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan K, Chan B, Lam K, Tam S, Lao T. Iron supplement in pregnancy and development of gestational diabetes\u0026mdash;a randomised placebo-controlled trial. BJOG: An International Journal of Obstetrics \u0026amp; Gynaecology. 2009;116(6):789\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKinnunen TI, Luoto R, Helin A, Hemminki E. Supplemental iron intake and the risk of glucose intolerance in pregnancy: re-analysis of a randomised controlled trial in Finland. Maternal and Child Nutrition. 2016;12(1):74\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuladsahebmadarek E, Sayyah-Melli M, SiminTaghavi, Abbasalizadeh S, Seyedhejazie M. The effect of supplemental iron elimination on pregnancy outcome. Pak J Med Sci. 2011;27(3):641\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan KKL, Chan BCP, Lam KF, Tam S, Lao TT. Iron supplement in pregnancy and development of gestational diabetes-a randomised placebo-controlled trial. Bjog-an International Journal of Obstetrics and Gynaecology. 2009;116(6):789\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTitilayo A, Palamuleni ME, Omisakin O. Sociodemographic factors influencing adherence to antenatal iron supplementation recommendations among pregnant women in Malawi: Analysis of data from the 2010 Malawi Demographic and Health Survey. Malawi medical journal: the journal of Medical Association of Malawi. 2016;28(1):1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGestacional SBdDD. Diretrizes da Sociedade Brasileira de Diabetes. 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDode MA, Santos Ida S. [Risk factors for gestational diabetes mellitus in the birth cohort in Pelotas, Rio Grande do Sul State, Brazil, 2004]. Cad Saude Publica. 2009;25(5):1141\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssist\u0026ecirc;ncia pr\u0026eacute;-natal: normas e manuais t\u0026eacute;cnicos., (1998).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pharmacoepidemiology, drug utilization, birth cohort study, gestational diabetes mellitus, supplementation.","lastPublishedDoi":"10.21203/rs.3.rs-862873/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-862873/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aims to evaluate the association between the use of iron salts during the first two trimesters in non-anemic women and the development of gestational diabetes mellitus (GDM).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study used maternal data from 2015 Pelotas Birth Cohort. All non-anemic women at 24th week (N\u0026thinsp;=\u0026thinsp;2463) were eligible for this study. GDM was self-reported by women. Crude and adjusted logistic regression were performed considering level of significance\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the women studied, 69.7% were exposed to prophylactic iron supplementation in the two first trimesters of gestation. The prevalence of GDM among those exposed was 8.7% (95%CI 7.4\u0026ndash;10.1) and among those who were not exposed was 9.3% (CI95% 7.4\u0026ndash;11.6). Iron supplementation was not associated with increased risk of GDM in crude (OR\u0026thinsp;=\u0026thinsp;0.9; 95%CI 0,7\u0026ndash;1,3) and adjusted analysis (OR\u0026thinsp;=\u0026thinsp;1.1; 95% CI 0,8\u0026ndash;1,6).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe results suggested that routine iron use in non-anemic pregnant women does not increase the risk of developing gestational diabetes. This evidence supports the existing national and international guidelines, whose recommendation is prophylactic iron supplementation for all pregnant women as soon as they initiate antenatal care in order to prevent iron deficiency anemia.\u003c/p\u003e","manuscriptTitle":"Use of Prophylactic Iron Salts Supplementation During Gestation and Development of Gestational Diabetes Mellitus in Women From 2015 Pelotas (Brazil) Birth Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-27 14:21:24","doi":"10.21203/rs.3.rs-862873/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8b72e7bc-9083-4833-8569-a92f0346e396","owner":[],"postedDate":"September 27th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":7459185,"name":"Maternal \u0026 Fetal Medicine"}],"tags":[],"updatedAt":"2021-12-04T09:14:06+00:00","versionOfRecord":[],"versionCreatedAt":"2021-09-27 14:21:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-862873","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-862873","identity":"rs-862873","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}