Association between vitamin C deficiency and pelvic organ prolapse in young women in the eastern Democratic Republic of Congo: a case-control study
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Abstract Background: Pelvic organ prolapse (POP), which is the descent of one or more organs into the vagina, is a complex condition resulting from weakness and defects in pelvic floor structures. It has a high incidence in young women in resource-limited settings, and its etiology is multifactorial. The termini of all etiological factors are associated with abnormalities in connective tissue, whose main component is collagen. In addition to its role as a potent antioxidant, vitamin C is involved in collagen synthesis. The objective of this study was to describe the association between serum vitamin C concentrations and prolapse in young women in a resource-limited setting. Methods: We conducted a matched case‒control study in a tertiary hospital. Multivariate logistic regression was used to examine the possible association between serum vitamin C concentration and pelvic organ prolapse. Participants were divided into three groups according to tertiles of their serum vitamin C concentration. Variables were selected for our logistic regression models using a directed and hierarchical approach. Model I was used to establish the unadjusted association. The other variables were sequentially incorporated into subsequent models (Models II, III, and IV). A restricted cubic spline regression curve was used to visualize the dose-response relationship for Model IV. Results: A total of 285 patients were included. Serum vitamin C concentration remained significantly and inversely associated with the risk of pelvic organ prolapse (aOR = 9.06; 95% CI: 4.55–18.86). Model IV showed a strong and significant inverse association: 85% risk reduction for the 2nd tertile (OR = 0.15; 95% CI: 0.07–0.33) and 89% for the 3rd tertile (OR = 0.11; 95% CI: 0.05–0.25). The restricted cubic spline curve demonstrated a statistically significant nonlinear relationship (p < 0.001). Conclusions: This study revealed a link between serum vitamin C levels and POP in young women.
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Association between vitamin C deficiency and pelvic organ prolapse in young women in the eastern Democratic Republic of Congo: a case-control 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 Association between vitamin C deficiency and pelvic organ prolapse in young women in the eastern Democratic Republic of Congo: a case-control study Eloge Ilunga-Mbaya¹, Denis Mukwege², Renaud de Tayrac³, Mbongi Moke Destin⁴, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7784162/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Pelvic organ prolapse (POP), which is the descent of one or more organs into the vagina, is a complex condition resulting from weakness and defects in pelvic floor structures. It has a high incidence in young women in resource-limited settings, and its etiology is multifactorial. The termini of all etiological factors are associated with abnormalities in connective tissue, whose main component is collagen. In addition to its role as a potent antioxidant, vitamin C is involved in collagen synthesis. The objective of this study was to describe the association between serum vitamin C concentrations and prolapse in young women in a resource-limited setting. Methods: We conducted a matched case‒control study in a tertiary hospital. Multivariate logistic regression was used to examine the possible association between serum vitamin C concentration and pelvic organ prolapse. Participants were divided into three groups according to tertiles of their serum vitamin C concentration. Variables were selected for our logistic regression models using a directed and hierarchical approach. Model I was used to establish the unadjusted association. The other variables were sequentially incorporated into subsequent models (Models II, III, and IV). A restricted cubic spline regression curve was used to visualize the dose-response relationship for Model IV. Results: A total of 285 patients were included. Serum vitamin C concentration remained significantly and inversely associated with the risk of pelvic organ prolapse (aOR = 9.06; 95% CI: 4.55–18.86). Model IV showed a strong and significant inverse association: 85% risk reduction for the 2nd tertile (OR = 0.15; 95% CI: 0.07–0.33) and 89% for the 3rd tertile (OR = 0.11; 95% CI: 0.05–0.25). The restricted cubic spline curve demonstrated a statistically significant nonlinear relationship (p < 0.001). Conclusions: This study revealed a link between serum vitamin C levels and POP in young women. association pelvic organ prolapse vitamin C deficiency young woman Figures Figure 1 Figure 2 BACKGROUND Pelvic organ prolapse (POP) is a complex condition resulting from weakness and defects in pelvic floor structures [1 ]. It contributes to morbidity, reduces quality of life, and causes serious social and economic problems [2, 3 ]. Its prevalence varies among studies depending on the population and methodology studied [4, 5, 6 ]. It is among the most frequent reasons for gynecologic consultations and represents 19.9% of all indications for gynecological surgeries [7 ]. However, its etiology is difficult to determine [8 ]. Pelvic floor trauma during childbirth leading to elongation of the pudendal and sacral nerves seems to be the most commonly implicated event. However, POP most often develops several years after this obstetric trauma and, in addition, is also observed in women with no obstetric history [9, 10, 11 ]. Ultimately, this multifactorial disease occurs because of the complex interaction of several factors, including genetic susceptibility, advanced age, and obstetric, environmental and nutritional factors [12, 13 ]. The common denominator of all these etiological factors is the weakening of the support structures of the pelvic floor and therefore the abnormalities of the connective tissue whose main component is collagen. In addition to its role in collagen synthesis, vitamin C acts as a potent antioxidant and improves soft tissue healing [14, 15 ]. A poor nutritional status predisposes populations in resource-limited countries to vitamin C deficiency [16, 17, 18 ]. Hypovitaminosis C has previously been associated with several pathological conditions [19, 20, 21, 22 ]. In developed countries, the likelihood of developing POP increases with age, and the incidence of prolapse in the young female population is high in resource-limited countries [8,23 ] . The objective of this study was to describe the association between serum vitamin C concentration and POP in young women in a resource-limited setting. METHODS Method We conducted a matched case‒control study from January 2023 to January 2024 in the urogynecology unit of Panzi Hospital, a tertiary hospital in the eastern Democratic Republic of Congo. This study was approved by the National Ethics Committee of the School of Public Health of the University of Kinshasa on 30/01/2021 (reference number: ESP/CE/20/2021), and informed consent was obtained from all participants. Study participants The population of interest consisted of patients who presented with POP and those who presented with other gynecological conditions. The participants included patients aged 18 to 45 years who had clinical and symptomatic POP stage III-IV according to their POP-Q results (cases), and patients in the same age group who presented to the gynecology department for a condition other than pelvic floor disorders and for whom a physical examination did not note pelvic static disorders (controls). The original groups were age-matched by matching controls to women already enrolled as cases. Pregnant, breastfeeding, and postmenopausal women, smokers, alcoholics, those with chronic or cardiovascular diseases such as high blood pressure or diabetes, those taking vitamin C or multivitamin supplements in the past 6 months, and those with fibroids, endometriosis, cancers, or HIV were excluded. Participants completed a questionnaire explained by a 4th-year resident physician in a language they understood. Afterward, the participants were examined by one of two experienced gynecologists. Patients were asked to have an empty bladder prior to examination, which was performed both at rest and on Valsalva using a Simm's speculum. Participants with stage III–IV POP according to the POP-Q were considered cases, and those classified as having stage 0–I POP according to the POP-Q were considered controls. The sample size was calculated using Epi Info version 7. The frequency of cases exhibiting a decrease in vitamin C was previously reported to be 62% [17 ]. On the basis of a power of 90%, a 95% confidence interval, a case‒control ratio of 2.0 and an odds ratio representing the association between exposure and outcome (POP) of 1.93, we estimated that a total of 285 patients (95 cases and 190 controls) would be needed. Study variables The study variables included age, parity, body mass index (BMI) ( 30 kg/m2), provenance (residence), occupation, history of macrosomia, POP stage, serum vitamin C level, and ferritin level. The parity considered was vaginal delivery, and it was categorized as low-parity (1–2 births), multiparous (3–4 births), and grand multiparous (≥ 5 births); residence was categorized as rural for those who lived in the countryside or villages, urban–rural for those living in remote areas adjoining large cities, and urban for those coming from large cities. Vitamin C dosage Blood samples were obtained in the morning from participants with an empty stomach using a standard venipuncture procedure. The samples were protected from light and frozen. After standard preanalysis procedures (centrifugation and aliquoting), the obtained serum was frozen at -20 degrees and shipped to the Molecular Medicine Laboratory of the Biomedical Research Institute (IRB) of the Health Training and Support Center (CEFA/MONKOLE) for serum Vitamin C analysis. We used the ELISA (Enzyme-Linked Immunosorbent Assay) chain with three Human Vitamin C Kits supplied by Abbexa Ltd. (Cambridge, UK) with reference number: abx156668 and lot numbers E2406416T, E2406417T and E2406418T. The ELISA Kit was used for in vitro quantitative measurement of vitamin C (ascorbic acid) concentration in serum, plasma, and other biological fluids. Serum vitamin C levels were determined using a sandwich enzyme immunoassay method (Mybiosource Ltd., USA) and an Inqaba Biotechnical Industries (Pty Ltd., Pretoria, South Africa) Micro Plate Reader Elisa analyzer according to the manufacturer's instructions. The spectrophotometric optical density was measured at a wavelength of 450 nm. We used 493.8 ng/ml to 4000 ng/ml as the reference range, in contrast to the supplier's recommendations. Any concentration less than 493.8 ng/ml was considered hypovitaminosis. Statistical analysis Statistical analyses were performed using R software (version 4.4.2). Quantitative variables are presented as medians and interquartile ranges (IQRs) if their distribution was not normal and as means and standard deviations (SDs) otherwise. Qualitative variables are presented as frequencies (N) and percentages (%). Bivariate analyses were used to compare sociodemographic and clinical characteristics between cases and controls. Depending on the nature of the variables and the data distribution, the chi-square test (χ²), the Mann-Whitney U test, or the Kruskal-Wallis test was used. A statistical significance level of 5% (p < 0.05) was used. Bivariate logistic regression allowed us to calculate crude odds ratios (ORb) and their 95% confidence intervals (95% CI). The selection of variables in our logistic regression models followed a directed and hierarchical approach, based on biological plausibility and evidence from the literature. This strategy allowed us to assess the robustness of the primary association between serum vitamin C levels and POP by progressively introducing confounders. Model I established the unadjusted association. Subsequent models (Models II, III, and IV) sequentially incorporated body mass index (BMI), parity, origin, and history of macrosomia. This block approach highlights the impact of each group of variables on risk estimation. A final multivariate logistic regression model was constructed by including all variables with a p value less than 0.05 in the preliminary bivariate analyses. This model provided adjusted odds ratios (aORs) and their 95% CIs. In addition, a restricted cubic spline (RCS) regression curve was used to visualize the dose-response relationship between serum vitamin C levels and POP in Model IV. RESULTS BASIC CHARACTERISTICS OF THE PARTICIPANTS Table 1 Basic characteristics of the participants N Prolapse No Prolapse P Total Participant 285 95 190 Age median (EIQ) 39(6.5) 40(10) 0.193 Occupation Shopkeeper 55 21(22.1) 34(17.9) 0.402 Farmer 178 57(60.0) 121(63.7) Employee 20 9(9.5) 11(5.8) Student 9 1(1.1) 8(4.2) Housewife 23 7(7.4) 16(8.4) Origin Rural 256 182(71.1) 74(28.9) < 0.001 Urban 29 8(27.6) 21(72.4) Parity Pauciparous 48 21(22.1) 27(14.3) 0.008 Multiparous 104 42(44.2) 62(32.8) Large Multiparous 132 32(33.7) 100(52.9) Macrosomia No 233 62(26.6) 171(73.4) < 0.001 Yes 52 33(63.5) 19(36.5) Ferritin Low 77 59(62.1) 18(9.5) < 0.001 Normal 208 36(37.9) 172(90.5) BMI Normal 183 96(50.5) 87(91.6) < 0.001 High 102 94(49.5) 8(8.4) Vitamin C < 449 ng/ml 95 64(67.4) 31(16.3) 2148 ng/ml 95 14(14.7) 81(42.6) BMI : body mass index IQR : interquartile range A total of 285 patients were included in the study, including 95 cases and 190 controls. Bivariate analyses revealed that age matching was successful (p = 0.193). Several variables were significantly different between the cases and controls. Histories of macrosomia (p < 0.001), ferritin deficiency (p < 0.001), low body mass index (p < 0.001), and low serum vitamin C levels (p < 0.001) were significantly more common in the cases. Parity was also associated with prolapse (p = 0.008) (Table 1 ). CHARACTERISTICS OF PARTICIPANTS ACCORDING TO THEIR SERUM VITAMIN C LEVEL Table 2 Characteristics of the participants according to serum vitamin C level Serum vitamin C Variables Down Normal p Age median (IQR) 39(8) 39(9) 0.211 Occupation 0.264 Shopkeeper 14 (15.9%) 41(20.8%) Farmer 54 (61.4%) 124(62.9%) Employee 10 (11.4%) 10 (5.1%) Student 4 (4.5%) 5 (2.5%) Housewife 6 (6.8%) 17 (8.6%) Origin < 0.001 Rural 186 (94.4%) 70(79.5%) Urban 11 (5.6%) 18 (20.5%) BMI < 0.001 Normal 111(56.3%) 72(81.8%) High 86(43.7%) 16(18.2%) Parity Pauciparous 21 (23.9%) 27 (15.8%) 0.068 Multiparous 33 (37.5%) 71 (36.0%) Large multiparous woman 34 (38.6%) 46 (49.7%) Macrosomia < 0.001 No 61 (69.3%) 172 (87.3%) Yes 27 (30.7%) 25 (12.7%) BMI : body mass index IQR : interquartile range Analysis of baseline characteristics by serum vitamin C status revealed several statistically significant differences. Women with a low vitamin C status were more frequently from rural areas (94.4% vs. 79.5%, p < 0.001), had a high BMI (43.7% vs. 18.2%, p < 0.001), and reported a greater prevalence of macrosomia (30.7% vs. 12.7%, p < 0.001) (Table 2 ). PARTICIPANT CHARACTERISTICS ACCORDING TO SERUM VITAMIN C LEVEL DIVIDED INTO TERTILES Table 3 Distribution of participants according to serum vitamin C level divided into tertiles Serum vitamin C Variables T 1 (≤ 448 ng/ml) T 2 (449 ng/ml − 2147 ng/ml) T 3 (> 2148 ng/ml) P Age median (IQR) 39(7.5) 40(8.5) 39(10) 0.444 Occupation 0.368 Shopkeeper 15 (15.8%) 16 (16.8%) 24 (25.3%) Farmer 59 (62.1%) 63 (66.3%) 56 (58.9%) Employee 10 (10.5%) 5 (5.3%) 5 (5.3%) Student 4 (4.2%) 1 (1.1%) 4 (4.2%) Housewife 7 (7.4%) 10 (10.5%) 6 (6.3%) Origin 0.002 Rural 77 (81.1%) 89 (93.7%) 90 (94.7%) Urban 18 (18.9%) 6 (6.3%) 5 (5.3%) BMI Normal 78(82.1%) 49 (51.6%) 56 (58.9%) < 0.001 Down 17 (17.9%) 46 (48.4%) 39 (41.1%) Parity Pauciparous 22 (23.2%) 11 (11.7%) 15 (15.8%) 0.271 Multiparous 35 (36.8%) 35 (37.2%) 34 (35.8%) Large multiparous woman 38 (40%) 48 (51.1%) 46 (48.4%) Macrosomia < 0.001 No 66 (69.5%) 82 (86.3%) 85 (89.5%) Yes 29 (30.5%) 13 (13.7%) 10 (10.5%) BMI : body mass index IQR : interquartile range T1 : 1st tertile T2: 2nd tertile T3 : 3rd tertile Participants were divided into three groups according to tertiles of their serum vitamin C concentration: T1 (≤ 448 ng/ml), T2 (449–2147 ng/ml), and T3 (> 2148 ng/ml). The median age was comparable between the groups (39 years [IQR: 7.5] at T1, 40 years [8.5] at T2, and 39 years [ 10 ] at T3; p = 0.444). Rural origin was predominant and increased with increasing vitamin C levels, from 81.1% at T1 to 94.7% at T3 (p = 0.002). Conversely, the proportion of women living in urban areas decreased with increasing serum vitamin C levels. BMI varied significantly across tertiles (p < 0.001). The proportion of women with a normal BMI was greater in T1 (82.1%) than in T3 (58.9%), whereas those with a low BMI were greater in T2 (48.4%) and T3 (41.1%). Finally, a history of macrosomia was significantly more frequent in the group with the lowest vitamin C concentration (30.5% in T1) than in the T2 (13.7%) and T3 (10.5%) groups (p < 0.001). Table 3 . Association between vitamin C level and prolapse Table 4 Association between serum vitamin C level and pelvic organ prolapse Model 1 OR (95% CI) Model 2 (95% CI) Model 3 (95% CI) Model 4 (95% CI) Vitamin C (continuous) 0.999(0.998–0.999) 0.999(0.998–0.999) 0.999(0.998–0.999) 0.999(0.998–0.999) Vitamin C (categorical) T1( 2148) 0.08(0.04–0.17) 0.09(0.04–0.19) 0.09(0.04–0.21) 0.11(0.05–0.25) p value < 0.001 < 0.001 < 0.001 < 0.001 OR: odds ratio, CI: confidence interval, T: tertile In Model I, serum vitamin C concentration was entered as a quantitative variable in a multiple logistic regression, with POP as the dependent variable. A 1 ng/ml increase in vitamin C was associated with a significant reduction in the probability of prolapse (OR = 0.999; 95% CI: 0.998–0.999). When vitamin C concentration was categorized into tertiles (T), a strong and significant inverse association was observed. Compared with participants in the first tertile ( 2148 ng/ml) had an 89% (OR = 0.11) and a 92% (OR = 0.08) lower risk of prolapse, respectively (p < 0.001). In Model II, adjustment for body mass index did not affect the observed association between vitamin C concentration and prolapse. Vitamin C concentration, introduced in tertiles, remained strongly and inversely associated with the probability of prolapse. Participants in T2 had an OR of 0.14 (95% CI: 0.06–0.28), and those in T3 had an OR of 0.09 (95% CI: 0.04–0.19), with highly significant values (p < 0.001). Model III, adjusted for BMI, parity, and origin, confirmed this inverse association. T2 participants had an 85.5% reduced risk (OR = 0.145; 95% CI: 0.065–0.306), whereas T3 participants had a 90.5% reduced risk (OR = 0.095; 95% CI: 0.041–0.206), with p values < 0.001. Model IV, which also includes the macrosomia variable, shows similar results: an 85% reduction in risk for participants in T2 (OR = 0.15; 95% CI: 0.07–0.33) and an 89% reduction for those in T3 (OR = 0.11; 95% CI: 0.05–0.25). Table 4 Dose-response relationship between serum vitamin C concentration and the risk of genital prolapse A restricted spline (RCS) analysis was performed to explore the dose–response relationship between serum vitamin C concentration and POP risk, adjusting for BMI, parity, origin, and history of macrosomia. The resulting curve shows a statistically significant nonlinear relationship (p < 0.001), which is confirmed by the significance of the coefficients of the vitamin C spline terms. The model shows good predictive performance, with a C-index of 0.918, a Brier score of 0.109, and an R² of 0.63, indicating a satisfactory fit to the data. Figure 1 . Factors associated with pelvic organ prolapse The aORs and 95% CIs for factors associated with POP according to the final logistic regression model are shown in Fig. 2 . Notably, for each significant factor, the 95% confidence interval did not overlap the value of 1, indicating a statistically significant association. Participants with a history of macrosomia had a significantly greater probability of prolapse (aOR = 4.93; 95% CI: 2.16–11.89). Similarly, compared with pauciparous women, multiparous women had a significantly elevated risk of prolapse (aOR = 2.61; 95% CI: 1.05–6.77). The adjusted aOR for grand multiparous women compared with that for pauciparous women was 1.42 (95% CI: 0.56–3.71), indicating that there was no statistically significant association with POP. On the other hand, compared with rural origin, urban origin was also linked to an increased risk of prolapse (ORa = 7.48; 95% CI: 2.27–29.13). Finally, participants with a low serum vitamin C concentration also had a very high prolapse rate (ORa = 9.06; 95% CI: 4.55–18.86). Conversely, overweight and obesity appeared to be protective factors, significantly reducing the risk of POP (aOR = 0.06; 95% CI: 0.02–0.15). DISCUSSION In this study, we revealed an association between serum vitamin C concentration and pelvic organ prolapse (POP). A 1 ng/ml increase in vitamin C concentration was associated with a significant reduction in the probability of POP even after adjustment for BMI, parity, origin, and history of macrosomia. The RCS model also revealed a statistically significant nonlinear relationship (p < 0.001), indicating that the risk of POP decreased nonlinearly with increasing vitamin C concentration. Visually, the curve revealed a risk of prolapse for very low vitamin C concentrations (< 900 ng/ml), for which the odds ratio (OR) exceeded 1. A rapid decrease in risk is observed between 900 and 1200 ng/ml, where the OR becomes less than 1, suggesting an optimal zone of protection. Between approximately 900 and 2000 ng/ml, serum vitamin C concentration remains associated with a marked reduction in the risk of prolapse, with apparent stability of the protective effect. Beyond 2500–3000 ng/ml, the curve gradually increased to an OR close to or greater than 1, but this increase was not statistically significant. (Fig. 1 ) This inverted U-shaped profile suggests that excess vitamin C may no longer be beneficial, although these high concentrations were infrequent in the sample. The entire curve highlights the existence of an optimal range of vitamin C concentrations to reduce the risk of POP. Several studies have demonstrated an association between vitamin C level and many chronic diseases, including sleep disorders, Alzheimer's disease, osteoporosis and periodontitis [19, 20, 21, 22 ]. However, studies on the association between serum vitamin C levels and POP are lacking. Several risk factors contribute to the pathogenesis of POP, including menopause, a history of hysterectomy, estrogen levels, parity, advanced age, BMI and sustained high intra-abdominal pressure, including obesity, chronic cough, constipation, and repeated weight bearing [6, 10 ]. Notably, these aforementioned macroscopic factors cannot completely clarify the pathogenesis of POP, which may not occur in all women who are exposed to these risk factors and may also affect women who do not have these conditions. It is therefore imperative to thoroughly investigate the causes of the molecular mechanism of POP to offer new perspectives to elucidate its pathogenesis, identify prevention methods, and improve diagnostic and treatment methods. Indeed, vitamin C plays a vital role in the synthesis of collagen (an essential component of the extracellular matrix), which is a cofactor of prolyl hydroxylase and lyxyl hydroxylase. These enzymes catalyze the hydroxylation of connective tissue. The proline and lysine residues of procollagen promote the correct folding of the stable triple helix conformation of collagen. Studies on cell cultures have also revealed that vitamin C can induce the mobilization of tendon-derived stem cells, the growth and differentiation of osteoblasts and the stimulation of fibroblasts [14,21 ] . Our multivariate analysis revealed that the factors associated with POP in young women are a history of macrosomia (aOR = 4.93; 95% CI: 2.16–11.89), urban origin (aOR = 7.48; 95% CI: 2.27–29.13), and a low serum vitamin C concentration (aOR = 9.06; 95% CI: 4.55–18.86). Overall, our results suggest that different factors may promote the occurrence of POP in young women. Indeed, a more complete picture of factors associated with POP in young women would include not only demographic (macrosomia, origin) but also molecular (serum vitamin C concentration) and probably genetic factors. These findings on serum vitamin C concentration should prompt immunohistochemical studies on collagen from these women. Several studies conducted in resource-limited countries and on young populations have confirmed that macrosomia is a risk factor for POP [7, 24 ]. In this study, compared with women from rural areas, women from urban areas had a 7-fold greater risk (ORa = 7.48; 95% CI: 2.27–29.13) of developing POP. These findings are striking when we consider that POP risk factors (multiple vaginal births, home births, heavy labor, etc.) are more likely to be found in rural areas than in urban areas. However, these results may be related to lifestyle. These findings are similar to the results of a study by Aljerry Dias do Rêgo [25 ], who compared a riverine population of indigenous origin in the Amazon, whose members maintain their traditional habits, with an urban population in northern Brazil to more precisely analyze the effects of lifestyle on pelvic floor disorders. Indeed, compared with city dwellers, people of rural origin have different lifestyles. Their eating habits are healthier. They often consume fresh fruits and vegetables that are not contaminated by chemicals. In summary, a more in-depth analysis of these findings should be conducted in a comparative dietary survey. Multiparity (3–4 vaginal deliveries) was associated with a significantly elevated risk of prolapse compared with pauciparous women with 1 to 2 vaginal deliveries (aOR = 2.61; 95% CI: 1.05–6.77). On the other hand, the aOR for grand multiparous women (≥ 5 vaginal deliveries) compared with that for pauciparous women was 1.42 (95% CI: 0.56–3.71), indicating a lack of a statistically significant association. These results suggest that women who have had more than 5 vaginal deliveries are not at greater risk of developing POP than those who have had 1 to 2 vaginal deliveries. These findings corroborate the results presented in our previous article, where the number of deliveries did not in itself explain the risk of POP but rather the obstetric conditions did (home delivery, perineal tear, macrosomia, etc.) [26 ]. These data corroborate those presented by Eddie HM in the USA, who concluded that POP was mainly associated with the first two vaginal deliveries. Subsequent deliveries are associated with minimal modification of pelvic floor structures. Indeed, in his series, the frequency and severity of POP were associated with increasing age rather than parity [27 ]. On the other hand, overweight and obesity appeared to be protective factors, significantly reducing the risk of POP (aOR = 0.06; 95% CI: 0.02–0.15) compared with women with normal and low BMIs. Interestingly, our results are not consistent with most related research [2, 28 ], which demonstrated an association between obesity, overweight status, and POP. However, most studies revealing a positive correlation between obesity and POP have focused on the theory that increased intra-abdominal pressure would stress the pelvic floor and lead to structural damage and/or neurological dysfunction that predisposes patients to POP without necessarily evaluating the intrinsic molecular mechanisms related to the connective tissue supporting the pelvic floor. Our previous study also revealed a significant association between low BMI and POP. A plausible explanation could be that women with a low BMI may have nutritional deficiencies affecting the intrinsic molecular composition of the supporting collagen of the pelvic floor structures. More elaborate research analyzing the molecular structure of collagen in these patient groups is needed. Limitations and strengths of the study There are several limitations to our study. Its cross-sectional nature (only 1 vitamin C assay) may make it difficult to confirm the causal relationship between serum vitamin C levels and POP. Therefore, our results need to be further confirmed by interventional studies. Our study is the first to highlight the relationship between hypovitaminosis C and POP in a prospective case‒control study that strives to reduce potential biases related to a micronutrient study (meticulous sample handling, use of more sensitive biological tests, etc.). This finding paves the way for several avenues of research on the intrinsic molecular mechanisms that may underlie the pathophysiology of POP. Indeed, future studies should analyze the quality of collagen underlying the pelvic floor structures in these young women as well as the enzymatic markers of oxidative stress in these tissues. Thus, other researchers could study the potential preventive action of vitamin C supplementation in population categories in resource-limited countries in randomized trials. CONCLUSION This study revealed a link between serum vitamin C levels and POP in young women. This study highlights a statistically significant nonlinear relationship, demonstrating that the risk of POP decreases in a nonlinear manner with increasing vitamin C concentration, highlighting the importance of nutrition in the occurrence of early POP in young women. Further prospective studies with repeated measurements of serum vitamin C concentrations and immunohistochemical studies on collagens in these women are needed to clarify the link between vitamin C and POP in young women. Abbreviations POP: pelvic organ prolapse POP-Q : pelvic organ prolapse quantification HIV: human immunodeficiency virus BMI: body mass index ELISA: Enzyme-Linked Immunosorbent Assay aOR: adjusted odds ratios OR: Odds Ratios Declarations Acknowledgements The authors would like to thank Dr. Jun Manda, MD.MSc for his help in translating. Author contributions EI: study design, data collection, documentary research, manuscript writing; DM: design of the study, criticism and correction of the manuscript, analysis of the relevance; RT: review of the manuscript, analysis of relevance; MM: samples analyses, RM: manuscript review, IA: analysis of relevance, correction of the manuscript, MB: data collection, BM: statistical analyzes and criticism of the manuscript, MB: review of the manuscript; SM: Design of the study, critique and correction of the manuscript. All authors read and approved the final manuscript. Funding The author did not receive any external funding support for this study. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate The study was approved by the national ethics committee of the School of Public Health of the University of Kinshasa on 30 January 2021 (reference number: ESP/CE/20/2021). All study participants provided a valid written informed consent for participation in the study and agreed to the use of their data for research purposes prior to recruitment, respecting the safety of participants and consent according to the Declaration of Helsinki.. Consent for publication not applicable. Competing interests The authors declare no competing interests. Author Information EIM: MD. Obstetrician-gynecologist specializing in urogynecology, PhD student DM: PhD, Head of Department of Gynecology and Obstetrics at Panzi Hospital and specialist in urogynecology RT: PhD, Urogynecologist, head of the mother and child unit at the university hospital of Nîmes/France MM: MD.MSc.PhD student biomedical research institute/MONKOLE IA: MD. PhD, Professor of gynecology. RM: MD. Obstetrician-gynecologist, specialist in Urogynecology, PhD student. BM: MD. PhD, Professor of Nutrition at the Kinshasa School of Public Health. MB: MD. PhD. Obstetrician-gynecologist SM: MD. PhD. Obstetrician-gynecologist, head of the department of gynecology and obstetrics at the university clinics of Kinshasa. References Gedefaw G. Burden of pelvic organ prolapse in Ethiopia: a systematic review and meta-analysis. BMC Women's Health. 2020; 20:16. https://doi.org/10.1186/s12905-020-01039-w. Friedman T, Eslick GD, Dietz HP. Risk factors for prolapse recurrence: systematic review and meta-analysis. Int Urogynecol J. 2018;29(1):13–21. Cooper J, Annappa M, Dracocardos D, Cooper W, Muller S, Mallen C. Prevalence of genital prolapse symptoms in primary care: a cross-sectional survey. Int Urogynecol J. 2015;26(4):505–10. Li Z, Xu T, Li Z, Gong J, Liu Q, Zhu L. An epidemiologic study of pelvic organ prolapse in rural Chinese women: a population-based sample in China. Int Urogynecol J. 2019;30(11):1925–32. Ballard K, Ayenachew F, Wright J, Atnafu H. Prevalence of obstetric fistula and symptomatic pelvic organ prolapse in rural Ethiopia. Int Urogynecol J. 2016;27(7):1063–7. Islam RM, Oldroyd J, Karim MN, Hossain SM, Md Emdadul Hoque D, Romero L, et al. Systematic review and meta-analysis of prevalence of, and risk factors for, pelvic floor disorders in community-dwelling women in low and middle-income countries : A protocol study. BMJ Open. 2017;7(6):1–6. Walker GJA, Gunasekera P. Pelvic organ prolapse and incontinence in developing countries: Review of prevalence and risk factors. Int Urogynecol J. 2011;22(2):127–35. Dheresa M, Worku A, Oljira L, Mengiste B, Assefa N, Berhane Y. One in five women suffer from pelvic floor disorders in Kersa district Eastern Ethiopia: a community-based study . BMC Womens Health. 2018;18(1):95. https://doi.org/10.1186/s12905-018-0585-1 Woodman PJ, Swift SE, O'Boyle AL, Valley MT, Bland DR, Kahn MA, et al. Prevalence of severe pelvic organ prolapse in relation to job description and socioeconomic status: A multicenter cross-sectional study. Int Urogynecol J. 2006;17(4):340–5. Weintraub AY, Glinter H, Marcus-Braun N. Narrative review of the epidemiology, diagnosis and pathophysiology of pelvic organ prolapse. Int Braz J Urol. 2020;46(1):5–14. Dietz HP. Genetics of pelvic organ prolapse: as nt. Int Urogynecol J. 2012;23(4):509–10. https://doi.org/10.1007/s00192-011-1638-2 Devkota HR, Sijali TR, Harris C, Ghimire DJ, Prata N, Bates MN. Bio-mechanical risk factors for uterine prolapse among women living in the hills of western Nepal: A case-control study. Women's Health. 2020;16:1-9. Teixeira FH, Fernandes CE, do Souto RP, de Oliveira E. Polymorphism rs1800255 from COL3A1 gene and the risk for pelvic organ prolapse. Int Urogynecol J. 2020;31(1):73–8. DePhillipo NN, Aman ZS, Kennedy MI, Begley JP, Moatshe G, LaPrade RF. Efficacy of Vitamin C Supplementation on Collagen Synthesis and Oxidative Stress After Musculoskeletal Injuries: A Systematic Review. Orthop J Sport Med. 2018;6(10). doi:10.1177/2325967118804544 Lis DM, Jordan M, Lipuma T, Smith T, Schaal K, Baar K. Collagen and Vitamin C Supplementation Increases Lower Limb Rate of Force Development . Int J Sport Nutr. 2022;32(2):65–73. Carr AC, Rowe S. Factors Affecting Vitamin C Status and Prevalence of Deficiency: A Global Health Perspective. Nutrients. 2020;12(7). doi:10.3390/nu12071963 Rowe S, Carr AC. Global Vitamin C Status and Prevalence of Deficiency: A Cause for Concern? Nutrients. 2020;12(7). doi:10.3390/nu12072008 Mayne ST. Antioxidant nutrients and chronic disease: use of biomarkers of exposure and oxidative stress status in epidemiologic research. J Nutr. 2003;133(3):933-940. doi : 10.1093/jn/133.3.933S. Simon JA, Hudes ES, Browner WS. Serum ascorbic acid and cardiovascular disease prevalence in US adults. Epidemiology. 1998;9(3):316–21. Appiah D, Ingabire-Gasana E, Appiah L, Yang J. The Relation of Serum Vitamin C Concentrations with Alzheimer's Disease Mortality in a National Cohort of Community-Dwelling Elderly Adults. Nutrients. 2024;16(11). https://doi.org/10.3390/nu16111672 Ratajczak AE, Szymczak-Tomczak A, Skrzypczak-Zielińska M, Rychter AM, Zawada A, Dobrowolska A, et al. Vitamin C Deficiency and the Risk of Osteoporosis in Patients with an Inflammatory Bowel Disease. Nutrients. 2020;12(8). doi:10.3390/nu12082263 Wang S, Lai F, Zhao L, Zhou J, Kong D, Yu H, et al. Association between vitamin C in serum and sleeping disorder based on NHANES 2017-2018. SciRep. 2024;14(1):9727. https://doi.org/10.1038/s41598-024-56703-0 Masenga GG, Shayo BC, Rasch V. Prevalence and risk factors for pelvic organ prolapse in Kilimanjaro, Tanzania: A population based study in Tanzanian rural community. PLoS One. 2018;13(4):1–13. Elbiss HM, Osman N, Hammad FT. Prevalence, risk factors and severity of symptoms of pelvic organ prolapse among Emirati women. BMC Urol. 2015;15(1):1–5. D o Rêgo AD, Peterson TV, Bernardo WM, Baracat EC, Haddad JM. Comparison of stress urinary incontinence between urban women and women of indigenous origin in the Brazilian Amazon. Int Urogynecol J. 2021;32(2):395–402. Ilunga-Mbaya E, Mukwege D, De Tayrac R, Mbunga B, Maroyi R, Ntakwinja M, et al. Exploring risk factors of pelvic organ prolapse at eastern of Democratic Republic of Congo: a case- control study. BMC Womens Health. 2024;24(1):1–6. SZE EHM, HOBBS G. Relationship between vaginal birth and pelvic organ prolapse. Acta Obstet Gynecol Scand. 2009;88(2):200–3. https://doi.org/10.1080/00016340802596033 Rogowski A, Bienkowski P, Tarwacki D, Dziech E, Samochowiec J, Jerzak M, et al. Association between metabolic syndrome and pelvic organ prolapse severity. Int Uro gynecol J Pelvic Floor Dysfunct. 2015;26(4):563–8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 11 Nov, 2025 Editor invited by journal 14 Oct, 2025 Editor assigned by journal 07 Oct, 2025 Submission checks completed at journal 07 Oct, 2025 First submitted to journal 05 Oct, 2025 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. 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1","display":"","copyAsset":false,"role":"figure","size":14358,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNonlinear dose-response relationship between serum vitamin C concentration and the risk of genital prolapse (adjusted RCS model)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7784162/v1/aa9fa92efdab7d8ba5e30e4e.png"},{"id":96492787,"identity":"4f72984f-f1a5-4f1d-aff7-3da8f3e2eda0","added_by":"auto","created_at":"2025-11-21 18:11:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":85636,"visible":true,"origin":"","legend":"\u003cp\u003eForecast plot showing factors associated with prolapse and their adjusted ORs\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7784162/v1/a45bf8fa37853bed60bf3cb0.png"},{"id":96913121,"identity":"42048a98-777b-4fae-b67f-29b5471d42db","added_by":"auto","created_at":"2025-11-27 13:52:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1180485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7784162/v1/fe69d155-c154-4386-b4bc-95c9d529fc10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between vitamin C deficiency and pelvic organ prolapse in young women in the eastern Democratic Republic of Congo: a case-control study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003ePelvic organ prolapse (POP) is a complex condition resulting from weakness and defects in pelvic floor structures [1 ]. It contributes to morbidity, reduces quality of life, and causes serious social and economic problems [2, 3 ]. Its prevalence varies among studies depending on the population and methodology studied [4, 5, 6 ]. It is among the most frequent reasons for gynecologic consultations and represents 19.9% of all indications for gynecological surgeries [7 ].\u003c/p\u003e\u003cp\u003eHowever, its etiology is difficult to determine [8 ]. Pelvic floor trauma during childbirth leading to elongation of the pudendal and sacral nerves seems to be the most commonly implicated event. However, POP most often develops several years after this obstetric trauma and, in addition, is also observed in women with no obstetric history [9, 10, 11 ].\u003c/p\u003e\u003cp\u003eUltimately, this multifactorial disease occurs because of the complex interaction of several factors, including genetic susceptibility, advanced age, and obstetric, environmental and nutritional factors [12, 13 ]. The common denominator of all these etiological factors is the weakening of the support structures of the pelvic floor and therefore the abnormalities of the connective tissue whose main component is collagen. In addition to its role in collagen synthesis, vitamin C acts as a potent antioxidant and improves soft tissue healing [14, 15 ]. A poor nutritional status predisposes populations in resource-limited countries to vitamin C deficiency [16, 17, 18 ]. Hypovitaminosis C has previously been associated with several pathological conditions [19, 20, 21, 22 ]. In developed countries, the likelihood of developing POP increases with age, and the incidence of prolapse in the young female population is high in resource-limited countries [8,23 ] .\u003c/p\u003e\u003cp\u003eThe objective of this study was to describe the association between serum vitamin C concentration and POP in young women in a resource-limited setting.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eWe conducted a matched case‒control study from January 2023 to January 2024 in the urogynecology unit of Panzi Hospital, a tertiary hospital in the eastern Democratic Republic of Congo. This study was approved by the National Ethics Committee of the School of Public Health of the University of Kinshasa on 30/01/2021 (reference number: ESP/CE/20/2021), and informed consent was obtained from all participants.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy participants\u003c/h3\u003e\n\u003cp\u003eThe population of interest consisted of patients who presented with POP and those who presented with other gynecological conditions. The participants included patients aged 18 to 45 years who had clinical and symptomatic POP stage III-IV according to their POP-Q results (cases), and patients in the same age group who presented to the gynecology department for a condition other than pelvic floor disorders and for whom a physical examination did not note pelvic static disorders (controls). The original groups were age-matched by matching controls to women already enrolled as cases.\u003c/p\u003e\u003cp\u003ePregnant, breastfeeding, and postmenopausal women, smokers, alcoholics, those with chronic or cardiovascular diseases such as high blood pressure or diabetes, those taking vitamin C or multivitamin supplements in the past 6 months, and those with fibroids, endometriosis, cancers, or HIV were excluded.\u003c/p\u003e\u003cp\u003eParticipants completed a questionnaire explained by a 4th-year resident physician in a language they understood. Afterward, the participants were examined by one of two experienced gynecologists. Patients were asked to have an empty bladder prior to examination, which was performed both at rest and on Valsalva using a Simm's speculum. Participants with stage III\u0026ndash;IV POP according to the POP-Q were considered cases, and those classified as having stage 0\u0026ndash;I POP according to the POP-Q were considered controls.\u003c/p\u003e\u003cp\u003eThe sample size was calculated using Epi Info version 7. The frequency of cases exhibiting a decrease in vitamin C was previously reported to be 62% [17 ]. On the basis of a power of 90%, a 95% confidence interval, a case‒control ratio of 2.0 and an odds ratio representing the association between exposure and outcome (POP) of 1.93, we estimated that a total of 285 patients (95 cases and 190 controls) would be needed.\u003c/p\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eThe study variables included age, parity, body mass index (BMI) (\u0026lt;\u0026thinsp;18.5 kg/m2 and \u0026gt;\u0026thinsp;30 kg/m2), provenance (residence), occupation, history of macrosomia, POP stage, serum vitamin C level, and ferritin level. The parity considered was vaginal delivery, and it was categorized as low-parity (1\u0026ndash;2 births), multiparous (3\u0026ndash;4 births), and grand multiparous (\u0026ge;\u0026thinsp;5 births); residence was categorized as rural for those who lived in the countryside or villages, urban\u0026ndash;rural for those living in remote areas adjoining large cities, and urban for those coming from large cities.\u003c/p\u003e\n\u003ch3\u003eVitamin C dosage\u003c/h3\u003e\n\u003cp\u003eBlood samples were obtained in the morning from participants with an empty stomach using a standard venipuncture procedure. The samples were protected from light and frozen. After standard preanalysis procedures (centrifugation and aliquoting), the obtained serum was frozen at -20 degrees and shipped to the Molecular Medicine Laboratory of the Biomedical Research Institute (IRB) of the Health Training and Support Center (CEFA/MONKOLE) for serum Vitamin C analysis. We used the ELISA (Enzyme-Linked Immunosorbent Assay) chain with three Human Vitamin C Kits supplied by Abbexa Ltd. (Cambridge, UK) with reference number: abx156668 and lot numbers E2406416T, E2406417T and E2406418T. The ELISA Kit was used for in vitro quantitative measurement of vitamin C (ascorbic acid) concentration in serum, plasma, and other biological fluids. Serum vitamin C levels were determined using a sandwich enzyme immunoassay method (Mybiosource Ltd., USA) and an Inqaba Biotechnical Industries (Pty Ltd., Pretoria, South Africa) Micro Plate Reader Elisa analyzer according to the manufacturer's instructions. The spectrophotometric optical density was measured at a wavelength of 450 nm.\u003c/p\u003e\u003cp\u003eWe used 493.8 ng/ml to 4000 ng/ml as the reference range, in contrast to the supplier's recommendations. Any concentration less than 493.8 ng/ml was considered hypovitaminosis.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using R software (version 4.4.2). Quantitative variables are presented as medians and interquartile ranges (IQRs) if their distribution was not normal and as means and standard deviations (SDs) otherwise. Qualitative variables are presented as frequencies (N) and percentages (%).\u003c/p\u003e\u003cp\u003eBivariate analyses were used to compare sociodemographic and clinical characteristics between cases and controls. Depending on the nature of the variables and the data distribution, the chi-square test (χ\u0026sup2;), the Mann-Whitney U test, or the Kruskal-Wallis test was used. A statistical significance level of 5% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was used. Bivariate logistic regression allowed us to calculate crude odds ratios (ORb) and their 95% confidence intervals (95% CI). The selection of variables in our logistic regression models followed a directed and hierarchical approach, based on biological plausibility and evidence from the literature. This strategy allowed us to assess the robustness of the primary association between serum vitamin C levels and POP by progressively introducing confounders. Model I established the unadjusted association. Subsequent models (Models II, III, and IV) sequentially incorporated body mass index (BMI), parity, origin, and history of macrosomia. This block approach highlights the impact of each group of variables on risk estimation. A final multivariate logistic regression model was constructed by including all variables with a p value less than 0.05 in the preliminary bivariate analyses. This model provided adjusted odds ratios (aORs) and their 95% CIs. In addition, a restricted cubic spline (RCS) regression curve was used to visualize the dose-response relationship between serum vitamin C levels and POP in Model IV.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eBASIC CHARACTERISTICS OF THE PARTICIPANTS\u003c/h2\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\u003eBasic characteristics of the participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProlapse\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo Prolapse\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTotal Participant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emedian (EIQ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39(6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40(10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.193\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShopkeeper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21(22.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34(17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.402\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFarmer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57(60.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e121(63.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9(9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11(5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8(4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousewife\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrigin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e182(71.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74(28.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8(27.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21(72.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePauciparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21(22.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27(14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42(44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62(32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge Multiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32(33.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100(52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMacrosomia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62(26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e171(73.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33(63.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19(36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFerritin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59(62.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18(9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36(37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e172(90.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96(50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87(91.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94(49.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitamin C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;449 ng/ml\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64(67.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31(16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e449\u0026ndash;2148 ng/ml\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17(17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78(41.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2148 ng/ml\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14(14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81(42.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eBMI\u003c/b\u003e: body mass index \u003cb\u003eIQR\u003c/b\u003e: interquartile range\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA total of 285 patients were included in the study, including 95 cases and 190 controls. Bivariate analyses revealed that age matching was successful (p\u0026thinsp;=\u0026thinsp;0.193). Several variables were significantly different between the cases and controls. Histories of macrosomia (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ferritin deficiency (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), low body mass index (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and low serum vitamin C levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly more common in the cases. Parity was also associated with prolapse (p\u0026thinsp;=\u0026thinsp;0.008) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCHARACTERISTICS OF PARTICIPANTS ACCORDING TO THEIR SERUM VITAMIN C LEVEL\u003c/h3\u003e\n\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\u003eCharacteristics of the participants according to serum vitamin C level\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSerum vitamin C\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDown\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emedian (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39(8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39(9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupation\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\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShopkeeper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (15.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41(20.8%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFarmer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (61.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124(62.9%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (11.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (5.1%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (2.5%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousewife\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (6.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (8.6%)\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\u003eOrigin\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e186 (94.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70(79.5%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (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\u003eBMI\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111(56.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72(81.8%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86(43.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16(18.2%)\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\u003eParity\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePauciparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (23.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (15.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71 (36.0%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge multiparous woman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (38.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (49.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMacrosomia\u003c/p\u003e\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (69.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e172 (87.3%)\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (30.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (12.7%)\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\"\u003e\u003cb\u003eBMI\u003c/b\u003e: body mass index \u003cb\u003eIQR\u003c/b\u003e: interquartile range\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of baseline characteristics by serum vitamin C status revealed several statistically significant differences. Women with a low vitamin C status were more frequently from rural areas (94.4% vs. 79.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had a high BMI (43.7% vs. 18.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and reported a greater prevalence of macrosomia (30.7% vs. 12.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePARTICIPANT CHARACTERISTICS ACCORDING TO SERUM VITAMIN C LEVEL DIVIDED INTO TERTILES\u003c/h2\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\u003eDistribution of participants according to serum vitamin C level divided into tertiles\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSerum vitamin C\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eT 1 (\u0026le;\u0026thinsp;448 ng/ml)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eT 2 (449 ng/ml \u0026minus;\u0026thinsp;2147 ng/ml)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eT 3 (\u0026gt;\u0026thinsp;2148 ng/ml)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emedian (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39(7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40(8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39(10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.368\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShopkeeper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (15.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16 (16.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (25.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFarmer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59 (62.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63 (66.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56 (58.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (10.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1 (1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousewife\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (7.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10 (10.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrigin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77 (81.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e89 (93.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90 (94.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (18.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78(82.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49 (51.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56 (58.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (17.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46 (48.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39 (41.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePauciparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (23.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11 (11.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15 (15.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.271\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultiparous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (36.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35 (37.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34 (35.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge multiparous woman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e48 (51.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 (48.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMacrosomia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66 (69.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e82 (86.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85 (89.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (30.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13 (13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (10.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e: body mass index \u003cb\u003eIQR\u003c/b\u003e: interquartile range \u003cb\u003eT1\u003c/b\u003e: 1st \u003csup\u003etertile\u003c/sup\u003e T2: 2nd tertile \u003cb\u003eT3\u003c/b\u003e: 3rd tertile\u003c/p\u003e\u003cp\u003eParticipants were divided into three groups according to tertiles of their serum vitamin C concentration: T1 (\u0026le;\u0026thinsp;448 ng/ml), T2 (449\u0026ndash;2147 ng/ml), and T3 (\u0026gt;\u0026thinsp;2148 ng/ml). The median age was comparable between the groups (39 years [IQR: 7.5] at T1, 40 years [8.5] at T2, and 39 years [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] at T3; p\u0026thinsp;=\u0026thinsp;0.444). Rural origin was predominant and increased with increasing vitamin C levels, from 81.1% at T1 to 94.7% at T3 (p\u0026thinsp;=\u0026thinsp;0.002). Conversely, the proportion of women living in urban areas decreased with increasing serum vitamin C levels.\u003c/p\u003e\u003cp\u003eBMI varied significantly across tertiles (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The proportion of women with a normal BMI was greater in T1 (82.1%) than in T3 (58.9%), whereas those with a low BMI were greater in T2 (48.4%) and T3 (41.1%). Finally, a history of macrosomia was significantly more frequent in the group with the lowest vitamin C concentration (30.5% in T1) than in the T2 (13.7%) and T3 (10.5%) groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAssociation between vitamin C level and prolapse\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between serum vitamin C level and pelvic organ prolapse\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1 OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2 (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3 (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4 (95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitamin C (continuous)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.999(0.998\u0026ndash;0.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.999(0.998\u0026ndash;0.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.999(0.998\u0026ndash;0.999)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.999(0.998\u0026ndash;0.999)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitamin C (categorical)\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\u003eT1(\u0026lt;\u0026thinsp;449)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT2 (449\u0026ndash;2148)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.11(0.05\u0026ndash;0.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14(0.06\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.14(0.07\u0026ndash;0.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.15(0.07\u0026ndash;0.33)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3(\u0026gt;\u0026thinsp;2148)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.08(0.04\u0026ndash;0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09(0.04\u0026ndash;0.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.09(0.04\u0026ndash;0.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11(0.05\u0026ndash;0.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR: odds ratio, CI: confidence interval, T: tertile\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn Model I, serum vitamin C concentration was entered as a quantitative variable in a multiple logistic regression, with POP as the dependent variable. A 1 ng/ml increase in vitamin C was associated with a significant reduction in the probability of prolapse (OR\u0026thinsp;=\u0026thinsp;0.999; 95% CI: 0.998\u0026ndash;0.999). When vitamin C concentration was categorized into tertiles (T), a strong and significant inverse association was observed. Compared with participants in the first tertile (\u0026lt;\u0026thinsp;449 ng/ml), participants in T2 (449\u0026ndash;2148 ng/ml) and T3 (\u0026gt;\u0026thinsp;2148 ng/ml) had an 89% (OR\u0026thinsp;=\u0026thinsp;0.11) and a 92% (OR\u0026thinsp;=\u0026thinsp;0.08) lower risk of prolapse, respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In Model II, adjustment for body mass index did not affect the observed association between vitamin C concentration and prolapse. Vitamin C concentration, introduced in tertiles, remained strongly and inversely associated with the probability of prolapse. Participants in T2 had an OR of 0.14 (95% CI: 0.06\u0026ndash;0.28), and those in T3 had an OR of 0.09 (95% CI: 0.04\u0026ndash;0.19), with highly significant values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eModel III, adjusted for BMI, parity, and origin, confirmed this inverse association. T2 participants had an 85.5% reduced risk (OR\u0026thinsp;=\u0026thinsp;0.145; 95% CI: 0.065\u0026ndash;0.306), whereas T3 participants had a 90.5% reduced risk (OR\u0026thinsp;=\u0026thinsp;0.095; 95% CI: 0.041\u0026ndash;0.206), with p values\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003cp\u003eModel IV, which also includes the macrosomia variable, shows similar results: an 85% reduction in risk for participants in T2 (OR\u0026thinsp;=\u0026thinsp;0.15; 95% CI: 0.07\u0026ndash;0.33) and an 89% reduction for those in T3 (OR\u0026thinsp;=\u0026thinsp;0.11; 95% CI: 0.05\u0026ndash;0.25). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDose-response relationship between serum vitamin C concentration and the risk of genital prolapse\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA restricted spline (RCS) analysis was performed to explore the dose\u0026ndash;response relationship between serum vitamin C concentration and POP risk, adjusting for BMI, parity, origin, and history of macrosomia. The resulting curve shows a statistically significant nonlinear relationship (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which is confirmed by the significance of the coefficients of the vitamin C spline terms. The model shows good predictive performance, with a C-index of 0.918, a Brier score of 0.109, and an R\u0026sup2; of 0.63, indicating a satisfactory fit to the data. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eFactors associated with pelvic organ prolapse\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe aORs and 95% CIs for factors associated with POP according to the final logistic regression model are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Notably, for each significant factor, the 95% confidence interval did not overlap the value of 1, indicating a statistically significant association. Participants with a history of macrosomia had a significantly greater probability of prolapse (aOR\u0026thinsp;=\u0026thinsp;4.93; 95% CI: 2.16\u0026ndash;11.89). Similarly, compared with pauciparous women, multiparous women had a significantly elevated risk of prolapse (aOR\u0026thinsp;=\u0026thinsp;2.61; 95% CI: 1.05\u0026ndash;6.77). The adjusted aOR for grand multiparous women compared with that for pauciparous women was 1.42 (95% CI: 0.56\u0026ndash;3.71), indicating that there was no statistically significant association with POP.\u003c/p\u003e\u003cp\u003eOn the other hand, compared with rural origin, urban origin was also linked to an increased risk of prolapse (ORa\u0026thinsp;=\u0026thinsp;7.48; 95% CI: 2.27\u0026ndash;29.13). Finally, participants with a low serum vitamin C concentration also had a very high prolapse rate (ORa\u0026thinsp;=\u0026thinsp;9.06; 95% CI: 4.55\u0026ndash;18.86).\u003c/p\u003e\u003cp\u003eConversely, overweight and obesity appeared to be protective factors, significantly reducing the risk of POP (aOR\u0026thinsp;=\u0026thinsp;0.06; 95% CI: 0.02\u0026ndash;0.15).\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we revealed an association between serum vitamin C concentration and pelvic organ prolapse (POP). A 1 ng/ml increase in vitamin C concentration was associated with a significant reduction in the probability of POP even after adjustment for BMI, parity, origin, and history of macrosomia. The RCS model also revealed a statistically significant nonlinear relationship (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that the risk of POP decreased nonlinearly with increasing vitamin C concentration. Visually, the curve revealed a risk of prolapse for very low vitamin C concentrations (\u0026lt;\u0026thinsp;900 ng/ml), for which the odds ratio (OR) exceeded 1. A rapid decrease in risk is observed between 900 and 1200 ng/ml, where the OR becomes less than 1, suggesting an optimal zone of protection. Between approximately 900 and 2000 ng/ml, serum vitamin C concentration remains associated with a marked reduction in the risk of prolapse, with apparent stability of the protective effect. Beyond 2500\u0026ndash;3000 ng/ml, the curve gradually increased to an OR close to or greater than 1, but this increase was not statistically significant. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) This inverted U-shaped profile suggests that excess vitamin C may no longer be beneficial, although these high concentrations were infrequent in the sample. The entire curve highlights the existence of an optimal range of vitamin C concentrations to reduce the risk of POP.\u003c/p\u003e\u003cp\u003eSeveral studies have demonstrated an association between vitamin C level and many chronic diseases, including sleep disorders, Alzheimer's disease, osteoporosis and periodontitis [19, 20, 21, 22 ]. However, studies on the association between serum vitamin C levels and POP are lacking. Several risk factors contribute to the pathogenesis of POP, including menopause, a history of hysterectomy, estrogen levels, parity, advanced age, BMI and sustained high intra-abdominal pressure, including obesity, chronic cough, constipation, and repeated weight bearing [6, 10 ]. Notably, these aforementioned macroscopic factors cannot completely clarify the pathogenesis of POP, which may not occur in all women who are exposed to these risk factors and may also affect women who do not have these conditions. It is therefore imperative to thoroughly investigate the causes of the molecular mechanism of POP to offer new perspectives to elucidate its pathogenesis, identify prevention methods, and improve diagnostic and treatment methods. Indeed, vitamin C plays a vital role in the synthesis of collagen (an essential component of the extracellular matrix), which is a cofactor of prolyl hydroxylase and lyxyl hydroxylase. These enzymes catalyze the hydroxylation of connective tissue. The proline and lysine residues of procollagen promote the correct folding of the stable triple helix conformation of collagen. Studies on cell cultures have also revealed that vitamin C can induce the mobilization of tendon-derived stem cells, the growth and differentiation of osteoblasts and the stimulation of fibroblasts [14,21 ] .\u003c/p\u003e\u003cp\u003eOur multivariate analysis revealed that the factors associated with POP in young women are a history of macrosomia (aOR\u0026thinsp;=\u0026thinsp;4.93; 95% CI: 2.16\u0026ndash;11.89), urban origin (aOR\u0026thinsp;=\u0026thinsp;7.48; 95% CI: 2.27\u0026ndash;29.13), and a low serum vitamin C concentration (aOR\u0026thinsp;=\u0026thinsp;9.06; 95% CI: 4.55\u0026ndash;18.86). Overall, our results suggest that different factors may promote the occurrence of POP in young women. Indeed, a more complete picture of factors associated with POP in young women would include not only demographic (macrosomia, origin) but also molecular (serum vitamin C concentration) and probably genetic factors. These findings on serum vitamin C concentration should prompt immunohistochemical studies on collagen from these women. Several studies conducted in resource-limited countries and on young populations have confirmed that macrosomia is a risk factor for POP [7, 24 ].\u003c/p\u003e\u003cp\u003eIn this study, compared with women from rural areas, women from urban areas had a 7-fold greater risk (ORa\u0026thinsp;=\u0026thinsp;7.48; 95% CI: 2.27\u0026ndash;29.13) of developing POP. These findings are striking when we consider that POP risk factors (multiple vaginal births, home births, heavy labor, etc.) are more likely to be found in rural areas than in urban areas. However, these results may be related to lifestyle. These findings are similar to the results of a study by Aljerry Dias do R\u0026ecirc;go [25 ], who compared a riverine population of indigenous origin in the Amazon, whose members maintain their traditional habits, with an urban population in northern Brazil to more precisely analyze the effects of lifestyle on pelvic floor disorders. Indeed, compared with city dwellers, people of rural origin have different lifestyles. Their eating habits are healthier. They often consume fresh fruits and vegetables that are not contaminated by chemicals. In summary, a more in-depth analysis of these findings should be conducted in a comparative dietary survey. Multiparity (3\u0026ndash;4 vaginal deliveries) was associated with a significantly elevated risk of prolapse compared with pauciparous women with 1 to 2 vaginal deliveries (aOR\u0026thinsp;=\u0026thinsp;2.61; 95% CI: 1.05\u0026ndash;6.77). On the other hand, the aOR for grand multiparous women (\u0026ge;\u0026thinsp;5 vaginal deliveries) compared with that for pauciparous women was 1.42 (95% CI: 0.56\u0026ndash;3.71), indicating a lack of a statistically significant association. These results suggest that women who have had more than 5 vaginal deliveries are not at greater risk of developing POP than those who have had 1 to 2 vaginal deliveries. These findings corroborate the results presented in our previous article, where the number of deliveries did not in itself explain the risk of POP but rather the obstetric conditions did (home delivery, perineal tear, macrosomia, etc.) [26 ]. These data corroborate those presented by Eddie HM in the USA, who concluded that POP was mainly associated with the first two vaginal deliveries. Subsequent deliveries are associated with minimal modification of pelvic floor structures. Indeed, in his series, the frequency and severity of POP were associated with increasing age rather than parity [27 ].\u003c/p\u003e\u003cp\u003eOn the other hand, overweight and obesity appeared to be protective factors, significantly reducing the risk of POP (aOR\u0026thinsp;=\u0026thinsp;0.06; 95% CI: 0.02\u0026ndash;0.15) compared with women with normal and low BMIs. Interestingly, our results are not consistent with most related research [2, 28 ], which demonstrated an association between obesity, overweight status, and POP. However, most studies revealing a positive correlation between obesity and POP have focused on the theory that increased intra-abdominal pressure would stress the pelvic floor and lead to structural damage and/or neurological dysfunction that predisposes patients to POP without necessarily evaluating the intrinsic molecular mechanisms related to the connective tissue supporting the pelvic floor. Our previous study also revealed a significant association between low BMI and POP. A plausible explanation could be that women with a low BMI may have nutritional deficiencies affecting the intrinsic molecular composition of the supporting collagen of the pelvic floor structures. More elaborate research analyzing the molecular structure of collagen in these patient groups is needed.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and strengths of the study\u003c/h2\u003e\u003cp\u003eThere are several limitations to our study. Its cross-sectional nature (only 1 vitamin C assay) may make it difficult to confirm the causal relationship between serum vitamin C levels and POP. Therefore, our results need to be further confirmed by interventional studies. Our study is the first to highlight the relationship between hypovitaminosis C and POP in a prospective case‒control study that strives to reduce potential biases related to a micronutrient study (meticulous sample handling, use of more sensitive biological tests, etc.). This finding paves the way for several avenues of research on the intrinsic molecular mechanisms that may underlie the pathophysiology of POP. Indeed, future studies should analyze the quality of collagen underlying the pelvic floor structures in these young women as well as the enzymatic markers of oxidative stress in these tissues. Thus, other researchers could study the potential preventive action of vitamin C supplementation in population categories in resource-limited countries in randomized trials.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study revealed a link between serum vitamin C levels and POP in young women. This study highlights a statistically significant nonlinear relationship, demonstrating that the risk of POP decreases in a nonlinear manner with increasing vitamin C concentration, highlighting the importance of nutrition in the occurrence of early POP in young women. Further prospective studies with repeated measurements of serum vitamin C concentrations and immunohistochemical studies on collagens in these women are needed to clarify the link between vitamin C and POP in young women.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePOP: pelvic organ prolapse\u003c/p\u003e\n\u003cp\u003ePOP-Q : pelvic organ prolapse quantification\u003c/p\u003e\n\u003cp\u003eHIV: human immunodeficiency virus\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eELISA:\u0026nbsp;Enzyme-Linked Immunosorbent Assay\u003c/p\u003e\n\u003cp\u003eaOR: adjusted odds ratios\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratios\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Dr. Jun Manda, MD.MSc for his help in translating.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEI: study design, data collection, documentary research, manuscript writing; DM: design of the study, criticism and correction of the manuscript, analysis of the relevance; RT: review of the manuscript, analysis of relevance; MM: samples analyses, RM: manuscript review, IA: analysis of relevance, correction of the manuscript, MB: data collection, BM: statistical analyzes and criticism of the manuscript, MB: review of the manuscript; SM: Design of the study, critique and correction of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author did not receive any external funding support for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the national ethics committee of the School of Public Health of the University of Kinshasa on 30 January 2021 (reference number: ESP/CE/20/2021). All study participants provided a valid written informed consent for participation in the study and agreed to the use of their data for research purposes prior to recruitment, respecting the safety of participants and consent according to the Declaration of Helsinki..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEIM: MD. Obstetrician-gynecologist specializing in urogynecology, PhD student\u003c/p\u003e\n\u003cp\u003eDM: PhD, Head of Department of Gynecology and Obstetrics at Panzi Hospital and specialist in urogynecology\u003c/p\u003e\n\u003cp\u003eRT: PhD, Urogynecologist, head of the mother and child unit at the university hospital of N\u0026icirc;mes/France\u003c/p\u003e\n\u003cp\u003eMM: MD.MSc.PhD student biomedical research institute/MONKOLE\u003c/p\u003e\n\u003cp\u003eIA: MD. PhD, Professor of gynecology.\u003c/p\u003e\n\u003cp\u003eRM: MD. Obstetrician-gynecologist, specialist in Urogynecology, PhD student.\u003c/p\u003e\n\u003cp\u003eBM: MD. PhD, Professor of Nutrition at the Kinshasa School of Public Health.\u003c/p\u003e\n\u003cp\u003eMB: MD. PhD. Obstetrician-gynecologist\u003c/p\u003e\n\u003cp\u003eSM: MD. PhD. Obstetrician-gynecologist, head of the department of gynecology and obstetrics at the university clinics of Kinshasa.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGedefaw G. Burden of pelvic organ prolapse in Ethiopia: a systematic review and meta-analysis. BMC Women\u0026apos;s Health. 2020; 20:16. https://doi.org/10.1186/s12905-020-01039-w.\u003c/li\u003e\n\u003cli\u003eFriedman T, Eslick GD, Dietz HP. Risk factors for prolapse recurrence: systematic review and meta-analysis. Int Urogynecol J. 2018;29(1):13\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eCooper J, Annappa M, Dracocardos D, Cooper W, Muller S, Mallen C. Prevalence of genital prolapse symptoms in primary care: a cross-sectional survey. Int Urogynecol J. 2015;26(4):505\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eLi Z, Xu T, Li Z, Gong J, Liu Q, Zhu L. An epidemiologic study of pelvic organ prolapse in rural Chinese women: a population-based sample in China. Int Urogynecol J. 2019;30(11):1925\u0026ndash;32.\u003c/li\u003e\n\u003cli\u003eBallard K, Ayenachew F, Wright J, Atnafu H. Prevalence of obstetric fistula and symptomatic pelvic organ prolapse in rural Ethiopia. Int Urogynecol J. 2016;27(7):1063\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eIslam RM, Oldroyd J, Karim MN, Hossain SM, Md Emdadul Hoque D, Romero L, et al. Systematic review and meta-analysis of prevalence of, and risk factors for, pelvic floor disorders in community-dwelling women in low and middle-income countries : A protocol study. BMJ Open. 2017;7(6):1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eWalker GJA, Gunasekera P. Pelvic organ prolapse and incontinence in developing countries: Review of prevalence and risk factors. Int Urogynecol J. 2011;22(2):127\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003eDheresa M, Worku A, Oljira L, Mengiste B, Assefa N, Berhane Y. One in five women suffer from pelvic floor disorders in Kersa district Eastern Ethiopia: a community-based study . BMC Womens Health. 2018;18(1):95. https://doi.org/10.1186/s12905-018-0585-1\u003c/li\u003e\n\u003cli\u003eWoodman PJ, Swift SE, O\u0026apos;Boyle AL, Valley MT, Bland DR, Kahn MA, et al. Prevalence of severe pelvic organ prolapse in relation to job description and socioeconomic status: A multicenter cross-sectional study. Int Urogynecol J. 2006;17(4):340\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eWeintraub AY, Glinter H, Marcus-Braun N. Narrative review of the epidemiology, diagnosis and pathophysiology of pelvic organ prolapse. Int Braz J Urol. 2020;46(1):5\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eDietz HP. Genetics of pelvic organ prolapse: as nt. Int Urogynecol J. 2012;23(4):509\u0026ndash;10. https://doi.org/10.1007/s00192-011-1638-2\u003c/li\u003e\n\u003cli\u003eDevkota HR, Sijali TR, Harris C, Ghimire DJ, Prata N, Bates MN. Bio-mechanical risk factors for uterine prolapse among women living in the hills of western Nepal: A case-control study. Women\u0026apos;s Health. 2020;16:1-9.\u003c/li\u003e\n\u003cli\u003eTeixeira FH, Fernandes CE, do Souto RP, de Oliveira E. Polymorphism rs1800255 from COL3A1 gene and the risk for pelvic organ prolapse. Int Urogynecol J. 2020;31(1):73\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eDePhillipo NN, Aman ZS, Kennedy MI, Begley JP, Moatshe G, LaPrade RF. Efficacy of Vitamin C Supplementation on Collagen Synthesis and Oxidative Stress After Musculoskeletal Injuries: A Systematic Review. Orthop J Sport Med. 2018;6(10). doi:10.1177/2325967118804544\u003c/li\u003e\n\u003cli\u003eLis DM, Jordan M, Lipuma T, Smith T, Schaal K, Baar K. Collagen and Vitamin C Supplementation Increases Lower Limb Rate of Force Development . Int J Sport Nutr. 2022;32(2):65\u0026ndash;73.\u003c/li\u003e\n\u003cli\u003eCarr AC, Rowe S. Factors Affecting Vitamin C Status and Prevalence of Deficiency: A Global Health Perspective. Nutrients. 2020;12(7). doi:10.3390/nu12071963 \u003c/li\u003e\n\u003cli\u003eRowe S, Carr AC. Global Vitamin C Status and Prevalence of Deficiency: A Cause for Concern? Nutrients. 2020;12(7). doi:10.3390/nu12072008\u003c/li\u003e\n\u003cli\u003eMayne ST. Antioxidant nutrients and chronic disease: use of biomarkers of exposure and oxidative stress status in epidemiologic research. J Nutr. 2003;133(3):933-940. doi : 10.1093/jn/133.3.933S.\u003c/li\u003e\n\u003cli\u003eSimon JA, Hudes ES, Browner WS. Serum ascorbic acid and cardiovascular disease prevalence in US adults. Epidemiology. 1998;9(3):316\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eAppiah D, Ingabire-Gasana E, Appiah L, Yang J. The Relation of Serum Vitamin C Concentrations with Alzheimer\u0026apos;s Disease Mortality in a National Cohort of Community-Dwelling Elderly Adults. Nutrients. 2024;16(11). https://doi.org/10.3390/nu16111672\u003c/li\u003e\n\u003cli\u003eRatajczak AE, Szymczak-Tomczak A, Skrzypczak-Zielińska M, Rychter AM, Zawada A, Dobrowolska A, et al. Vitamin C Deficiency and the Risk of Osteoporosis in Patients with an Inflammatory Bowel Disease. Nutrients. 2020;12(8). doi:10.3390/nu12082263\u003c/li\u003e\n\u003cli\u003eWang S, Lai F, Zhao L, Zhou J, Kong D, Yu H, et al. Association between vitamin C in serum and sleeping disorder based on NHANES 2017-2018. SciRep. 2024;14(1):9727. https://doi.org/10.1038/s41598-024-56703-0\u003c/li\u003e\n\u003cli\u003eMasenga GG, Shayo BC, Rasch V. Prevalence and risk factors for pelvic organ prolapse in Kilimanjaro, Tanzania: A population based study in Tanzanian rural community. PLoS One. 2018;13(4):1\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eElbiss HM, Osman N, Hammad FT. Prevalence, risk factors and severity of symptoms of pelvic organ prolapse among Emirati women. BMC Urol. 2015;15(1):1\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eD o R\u0026ecirc;go AD, Peterson TV, Bernardo WM, Baracat EC, Haddad JM. Comparison of stress urinary incontinence between urban women and women of indigenous origin in the Brazilian Amazon. Int Urogynecol J. 2021;32(2):395\u0026ndash;402.\u003c/li\u003e\n\u003cli\u003eIlunga-Mbaya E, Mukwege D, De Tayrac R, Mbunga B, Maroyi R, Ntakwinja M, et al. Exploring risk factors of pelvic organ prolapse at eastern of Democratic Republic of Congo: a case- control study. BMC Womens Health. 2024;24(1):1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eSZE EHM, HOBBS G. Relationship between vaginal birth and pelvic organ prolapse. Acta Obstet Gynecol Scand. 2009;88(2):200\u0026ndash;3. https://doi.org/10.1080/00016340802596033\u003c/li\u003e\n\u003cli\u003eRogowski A, Bienkowski P, Tarwacki D, Dziech E, Samochowiec J, Jerzak M, et al. Association between metabolic syndrome and pelvic organ prolapse severity. Int Uro gynecol J Pelvic Floor Dysfunct. 2015;26(4):563\u0026ndash;8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"association, pelvic organ prolapse, vitamin C, deficiency, young woman","lastPublishedDoi":"10.21203/rs.3.rs-7784162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7784162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003ePelvic organ prolapse (POP), which is the descent of one or more organs into the vagina, is a complex condition resulting from weakness and defects in pelvic floor structures. It has a high incidence in young women in resource-limited settings, and its etiology is multifactorial. The termini of all etiological factors are associated with abnormalities in connective tissue, whose main component is collagen. In addition to its role as a potent antioxidant, vitamin C is involved in collagen synthesis. The objective of this study was to describe the association between serum vitamin C concentrations and prolapse in young women in a resource-limited setting.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eWe conducted a matched case‒control study in a tertiary hospital. Multivariate logistic regression was used to examine the possible association between serum vitamin C concentration and pelvic organ prolapse. Participants were divided into three groups according to tertiles of their serum vitamin C concentration. Variables were selected for our logistic regression models using a directed and hierarchical approach. Model I was used to establish the unadjusted association. The other variables were sequentially incorporated into subsequent models (Models II, III, and IV). A restricted cubic spline regression curve was used to visualize the dose-response relationship for Model IV.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eA total of 285 patients were included. Serum vitamin C concentration remained significantly and inversely associated with the risk of pelvic organ prolapse (aOR\u0026thinsp;=\u0026thinsp;9.06; 95% CI: 4.55\u0026ndash;18.86). Model IV showed a strong and significant inverse association: 85% risk reduction for the 2nd tertile (OR\u0026thinsp;=\u0026thinsp;0.15; 95% CI: 0.07\u0026ndash;0.33) and 89% for the 3rd tertile (OR\u0026thinsp;=\u0026thinsp;0.11; 95% CI: 0.05\u0026ndash;0.25). The restricted cubic spline curve demonstrated a statistically significant nonlinear relationship (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eThis study revealed a link between serum vitamin C levels and POP in young women.\u003c/p\u003e","manuscriptTitle":"Association between vitamin C deficiency and pelvic organ prolapse in young women in the eastern Democratic Republic of Congo: a case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-21 18:11:51","doi":"10.21203/rs.3.rs-7784162/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-11-11T13:11:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-14T08:31:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-08T00:01:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-08T00:01:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2025-10-05T10:17:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79fa4ad8-2ce0-4f46-a3da-984ce5d863eb","owner":[],"postedDate":"November 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-21T18:11:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-21 18:11:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7784162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7784162","identity":"rs-7784162","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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