Association between visceral adiposity index and infertility in reproductive-aged women in the United States.

Of the 1,231 participants, 127 were infertile women between the ages of 18 and 45, and 116 of the infertile women had regular menstruation over a 12 month period. The range of VAI for tertiles 1–3 were 0.1–0.65(≤ 0.65),0.65–1.75(≤ 1.75),and 1.75–19.69(≤ 19.69).Table 1 displays the characteristics of the study participants, categorized based on whether they were infertile or not. Women who were older, married or living together, drank alcohol, had a higher body mass index, and had a larger waist circumference were more likely to self-report being infertile. Furthermore, women with a higher VAI also had a higher prevalence of self-reported infertility, with a mean of 1.72 ± 1.91. Table 1 Baseline characteristics of study participants (N = 1231). Infertility Control p-value N = 127 1104 Age, mean ± SD (years) 33.33 ± 6.89 30.62 ± 7.84  < 0.001 poverty income ratio (PIR) 2.37 ± 1.58 2.27 ± 1.58 0.412 Race [n (%)]  Mexican American 22 (17.32%) 172 (15.58%) 0.813  Other Hispanic 10 (7.87%) 118 (10.69%)  Non-Hispanic White 40 (31.50%) 317 (28.71%)  Non-Hispanic Black 30 (23.62%) 283 (25.63%)  Other race—including multi-racial 25 (19.69%) 214 (19.38%) Education level [n (%)] 0.887  Below highschool 18 (14.52%) 146 (14.61%)  Highschool grad/GED/equivalent 22 (17.74%) 195 (19.52%)  Above highschool 84 (67.74%) 658 (65.87%) Marital status [n (%)]  < 0.001  Married 90 (72.58%) 490 (49.05%)  Widowed 9 (7.26%) 56 (5.61%)  Divorced 13 (10.48%) 264 (26.43%)  Separated 0 (0.00%) 11 (1.10%)  Never married 7 (5.65%) 125 (12.51%)  Living with partner 5 (4.03%) 53 (5.31%) Smoking status [n (%)] 0.926  Now 20 (42.55%) 126 (44.37%)  Former 6 (12.77%) 31 (10.92%)  Never 21 (44.68%) 127 (44.72%) Alcohol drinking [n (%)] 0.008  Yes 15 (13.51%) 60 (6.59%)  No 96 (86.49%) 851 (93.41%) Hypertension [n (%)] 0.001  Yes 29 (22.83%) 137 (12.41%)  No 98 (77.17%) 967 (87.59%) Diabetes [n (%)] 0.001  Yes 15 (11.81%) 39 (3.53%)  No 112 (88.19%) 1065 (96.47%) TG (mmol/L) 1.02 ± 0.73 0.94 ± 0.62 0.016 HDL (mmol/L) 1.35 ± 0.38 1.47 ± 0.40  < 0.001 BMI (kg/m 2 ) 32.69 ± 8.60 29.42 ± 8.53  < 0.001 WC (cm) 103.61 ± 20.52 94.92 ± 19.12  < 0.001 VAI 1.72 ± 1.91 1.44 ± 1.30  < 0.001 Mean ± SD for continuous variables: p value was calculated by the weighted linear regression model. % for Categorical variables: p value was calculated by the weighted chi-square test. Baseline characteristics of study participants (N = 1231). Mean ± SD for continuous variables: p value was calculated by the weighted linear regression model. % for Categorical variables: p value was calculated by the weighted chi-square test. The correlation between VAI and infertility is shown in Table 2 . Our results imply that a higher risk of infertility is linked to a higher VAI. There was a positive correlation between VAI and infertility in Models 1, 2, and 3. According to the fully adjusted model (Model 3: OR = 1.22, 95% CI:1.03–1.45), there was a 22% increase in the probability of being infertile for every unit increase in VAI. The statistical significance of this link persisted even after dividing VAI into thirds. Those in the highest VAI tertile were at a 252% higher risk than those in the lowest VAI tertile (OR = 3.52, 95% CI:1.18–10.49; p  = 0.02) (Table 2 ). Additionally, we used smoothed curve fitting to further examine the relationship between VAI and the risk of infertility, and the results indicated a positive nonlinear relationship (Fig.  2 ). Table 2 Associations between weight-adjusted-waist index and the risk of infertility. OR (95% CI), P-value Crude model Minimally adjusted model Fully adjusted model (Model 1) 1 (Model 2) 2 (Model 3) 3 N (infertility)  Continuous 127 1.12 (1.00, 1.25) 0.04 1.12 (1.00, 1.25) 0.04 1.22 (1.03, 1.45) 0.02 Categories  Tertile1 23 Reference Reference Reference  Tertile2 46 2.10 (1.25, 3.53)  < 0.01 2.00 (1.19, 3.39)  < 0.01 2.72 (0.90, 8.26) 0.07  Tertile3 58 2.71 (1.64, 4.49)  < 0.01 2.41 (1.43, 4.06)  < 0.01 3.52 (1.18, 10.49) 0.02 Insensitivity analysis, the visceral adiposity index was converted from a continuous variable to a categorical variable (tertiles). 95% CI 95% confidence interval. OR odds ratio. 1 Model 1: Covariates were not adjusted at all. 2 Model 2: Adjusted forage, and race. 3 Model 3: Adjusted forage, ratio of family income to poverty, race, education level, marital status, Smoking status, Alcohol drinking, Hypertension, Diabetes. Figure 2 Smoothing curve fitting of AVI index and infertility. Associations between weight-adjusted-waist index and the risk of infertility. 1.12 (1.00, 1.25) 0.04 1.12 (1.00, 1.25) 0.04 1.22 (1.03, 1.45) 0.02 2.10 (1.25, 3.53) < 0.01 2.00 (1.19, 3.39) < 0.01 2.72 (0.90, 8.26) 0.07 2.71 (1.64, 4.49) < 0.01 2.41 (1.43, 4.06) < 0.01 3.52 (1.18, 10.49) 0.02 Insensitivity analysis, the visceral adiposity index was converted from a continuous variable to a categorical variable (tertiles). 95% CI 95% confidence interval. OR odds ratio. 1 Model 1: Covariates were not adjusted at all. 2 Model 2: Adjusted forage, and race. 3 Model 3: Adjusted forage, ratio of family income to poverty, race, education level, marital status, Smoking status, Alcohol drinking, Hypertension, Diabetes. Smoothing curve fitting of AVI index and infertility. We performed subgroup analyses to determine whether other factors altered the association between VAI and infertility. The results indicated that there was no dependence and that the subgroup between VAI and infertility was stable. The positive correlation between VAI and infertility was not significantly impacted by stratified factors such as age, ethnicity, education level, marital status, smoking at least 100 cigarettes, drinking alcohol at least 12 times a year, diabetes, and hypertension ( p  > 0.05), as shown in Table 3 . Table 3 Subgroups analyses of the effect of VAI on infertility. Subgroups N OR (95% CI) P for interaction Total Infertility Age 0.2049  Tertile1 408 21 1.28 (0.68, 2.43)  Tertile2 378 43 1.86 (1.06, 3.26)  Tertile3 445 63 1.28 (1.03, 1.60) Race 0.3855  Mexican American 194 22 1.15 (0.71, 1.86)  Other Hispanic 128 10 1.69 (0.88, 3.24)  Non-Hispanic White 357 40 1.27 (1.01, 1.59)  Non-Hispanic Black 313 30 1.29 (0.74, 2.25)  Other race 239 25 0.64 (0.26, 1.57) Education level 0.2534  Below high school 164 18 1.63 (0.93, 2.85)  High school grad/GED/equivalent 217 22 1.00 (0.56, 1.77)  Above high school 742 84 1.12 (0.82, 1.51) Marital status 0.5472  Married 580 90 1.20 (0.90, 1.60)  Widowed 65 9 1.37 (0.99, 1.90)  Divorced and separated 288 13 0.67 (0.26, 1.71)  Never married 132 7 1.06 (0.49, 2.31)  Living with partner 58 5 1.08 (0.33, 3.54) Smoking status 0.5515  Now 146 20 1.09 (0.66, 1.81)  Former 37 6 1.34 (0.72, 2.48)  Never 148 21 1.10 (0.82, 1.47) Alcohol drinking 0.8586  Yes 75 15 1.22 (1.02, 1.45)  No 947 96 1.15 (0.59, 2.22) Hypertension 0.2074  Yes 166 29 1.26 (0.86, 1.83)  No 1065 98 0.97 (0.73, 1.29) Diabetes 0.8003  Yes 54 15 1.16 (0.85, 1.59)  No 1177 112 1.10 (0.81, 1.48) Subgroup analysis of the correlation between visceral obesity index and infertility. Factors such as age, race, education level, marital status, smoking, alcohol consumption, diabetes, and hypertension did not affect the positive correlation between visceral obesity index and infertility. Subgroups analyses of the effect of VAI on infertility. Subgroup analysis of the correlation between visceral obesity index and infertility. Factors such as age, race, education level, marital status, smoking, alcohol consumption, diabetes, and hypertension did not affect the positive correlation between visceral obesity index and infertility.

The National Center for Health Statistics (NCHS) is the publishing organization for the National Health and Nutrition Examination Survey (NHANES), a national survey that evaluates Americans’ health and nutrition. To ensure that the sample was representative, a complicated, multistage probability design was used to perform the NHANES 22 . To gather information on the participants’ socioeconomic situation, health, and other aspects, a household interview was conducted. Both laboratory and physical examinations were conducted in a mobile examination center. The NCHS study Ethics Review Board authorized all NHANES study procedures, and all survey participants gave written informed consent. The public can access all the information regarding the NHANES study design and data at www.cdc.gov/nchs/nhanes/ . This cross-sectional study followed the STROBE reporting standards 23 . Data from the National Health and Nutrition Examination Survey (NHANES) covering the years 2015–2020 was utilized. We included in our research participants who provided comprehensive information on their visceral obesity index (VAI) and infertility. A total of 25,531 people were initially enrolled. After excluding male participants (n = 12,613), individuals without information on waist circumference (n = 143), triglycerides (n = 9141), BMI (n = 50), individuals without information on infertility (n = 1580), and female participants over 45 and under 18 (n = 773), our final analysis comprised 1231 eligible participants (Fig.  1 ). Figure 1 Flow chart of the inclusion and exclusion of study participants. Flow chart of the inclusion and exclusion of study participants. Amato et al. developed the gender-specific visceral obesity index (VAI) to account for physiological variations in visceral obesity between men and women 24 . VAI is a measure of anthropometric and metabolic characteristics, such as high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), waist circumference (WC), and body mass index (BMI). It is thought to be a sign of malfunction and buildup of visceral adipose tissue. The VAI for each participant was calculated by using the following formulas. For males: VAI = WC/(39.68 + (1.88*BMI))*(TG/1.03)*(1.31/HDL-C); For females: VAI = WC/(36.58 + (1.89*BMI))*(TG/0.81)*(1.52/HDL-C). TG and HDL-C were calculated in mmol/L, and WC was calculated in cm in the formulas. The dependent variable for infertility was each woman’s self-report from the Reproductive Health Questionnaire (questionnaire variable name: RHQ074). Researchers prodded participants with questions like, “Have you tried to get pregnant for one year?” 25 . A “infertile” situation was indicated if the response was “yes,” and a “fertile” situation was indicated if it was no. Based on similar literature and practice 26 – 28 , factors included age, ethnicity, education level, marital status, poverty income ratio (PIR), diabetes, hypertension, alcohol and smoking patterns, waist circumference, BMI, triglycerides, and HDL cholesterol. There were five racial and ethnic groupings among the participants. Mexican Americans, Blacks, Whites, non-Hispanics, Hispanics, and Others (including Multiracial). Waist circumference, body mass index, triglycerides, HDL cholesterol, age in years, and poverty income ratio (PIR) were among the continuous variables that were measured. The definitions of the three degrees of education were as follows: high school graduate/GED or equivalent, above high school, and below high school 29 . The NHANES maintained its classification of marital status into five categories: cohabiting, single, widowed, divorced, married, and unmarried. Diabetes was described as a diagnosed illness 30 . Additionally, the measure of hypertension was self-reported 31 . Those who never smoked (less than 100 cigarettes in their lifetime), those who smoked in the past (at least 100 cigarettes in their lifetime, smokers, and no smokers at all), and those who now smoke (more than 100 cigarettes in their lifetime or smoked daily) were the three categories depending on their smoking status. A person's drinking status was ascertained by asking if they had more than 12 drinks in a year. Those who answered "yes" were deemed to be drinkers, while those who answered “no” were not. All statistical analyses were performed with consideration for the intricate, multistage clustered surveys and with the appropriate NHANES sampling weights, following the recommendations of the Centers for Disease Control and Prevention. In descriptive analyses, a weighted Student’s t -test (for continuous variables) or a weighted Chi-square test (for categorical data) was used to evaluate the two comparison groups based on their infertility status. For continuous data, proportions were utilized to represent categorical parameters, while averages and standard deviations were employed to describe them. Multivariate regression models using the NHANES complex sample design (sampling weights) were used to examine the link between VAI and infertility. In Model 1, covariates were left unchanged. Model 2 adjusted for age and race. Model 3 took into consideration the following variables: age, race, education level, marital status, number of cigarettes smoked in the past 100 days, number of beverages consumed annually, diabetes (yes/no), and hypertension (yes/no). We used smoothed curve fitting in addition to subgroup analyses to look at the nonlinear relationship between VAI and infertility. We used R ( http://www.r-project.org ) and Empower software ( http://www.empowerstats.com ) for all statistical analyses, following the Centers for Disease Control and Prevention’s (CDC) instructions. The statistical significance criterion was established at p  < 0.05.

According to our research, higher VAI is associated with a higher incidence of infertility. Therefore, high VAI levels may be associated with an increased risk of infertility, and VAI provides a practical and easily accessible method to assess metabolic and reproductive problems in infertile women. However, more large-scale prospective studies are needed in the future to confirm the results of this study.

We recruited 1231 female patients for this cross-sectional study, and the results showed a positive correlation between VAI and infertility, independent of age, race, education level, marital status, smoking, alcohol intake, diabetes, or hypertension. According to the findings of the investigation, lowering VAI levels may help decrease the likelihood of infertility. This is the only study that we are aware of that assesses the correlation between VAI and female infertility. Obese women often experience irregular menstruation with poor ovulation, endometriosis, and infertility, which highlights the detrimental consequences of obesity on reproduction 32 , 33 . Numerous studies have demonstrated that obesity not only deteriorates metabolic status but also causes ovulatory dysfunction, increasing the incidence of infertility in obese women by three times compared to non-obese women 34 . Especially two investigations including sizable cohorts of Danish women who were considering becoming pregnant revealed an unfavorable relationship between higher BMI and fertility 25 . Notably, obese women still have low fertility even in the absence of ovulatory dysfunction. Gesink and colleagues examined a large American cohort of over 7000 women and discovered that the probability of spontaneous conception declined linearly with BMI > 29 kg/m 2 . Similar findings were found in a comparable study that involved over 3000 women in the Netherlands who had regular menstrual cycles 35 . Furthermore, it seems that participation in assisted conception programs reduces the fertility of obese women 36 . In fact, poor oocyte quality and reduced preimplantation have been linked to poor results in individuals undergoing in vitro fertilization (IVF) who are overweight or obese 37 . Losing weight is therefore highly advised in these women in order to enhance reproductive function 38 . Our latest research supports and validates the detrimental effect of visceral fat on infertility in women. There is a connection between declining metabolism and visceral adiposity. In Yu Kang et al.’s study, patients who were metabolically unwell and obese (MUO) had a considerably greater VAI than patients who were healthy and obese (MHO). Furthermore, VAI and the frequency of conversion to the MUO phenotype correlated positively 39 . Insulin sensitivity did not correlate with waist circumference or BMI in a study by Amato et al., but there was a positive connection between VAI and cardiometabolic risk as well as visceral adipose tissue measured by magnetic resonance imaging 19 . An elevated VAI was linked to an increased cardiometabolic risk in a research involving 1764 hospitalized patients 24 . Studies have shown that TG/HDL-C is a strong predictor of metabolic syndrome and insulin resistance, playing a crucial role in the development of infertility 40 . The development of infertility and metabolic disorders is complex and diverse, and lipid metabolism disorders may play a key role in follicular development, egg maturation, and hormone secretion 41 . A large number of animal studies have confirmed that dyslipidemia can lead to a decrease in female reproductive capacity 42 . Therefore, VAI is able to indicate abnormal metabolic status in the body, thereby predicting infertility risk and serving as a basis for health promotion. VAI has been shown to be a predictor of clinical severity and treatment outcome in patients with polycystic ovary syndrome 21 . The association between VAI and infertility is not well understood, but our findings suggest that increased VAI is associated with an increased risk of potential infertility, primarily because of neuroendocrine mechanisms that interfere with ovarian function and can affect ovulation rates and endometrial tolerance 33 . The circulating levels of gonadotropins, estradiol, and estradiol during the follicular phase are lower in obese women, even with normal menstrual cycles and apparently normal fertility. This suggests that the obesity condition itself has an inhibitory influence on the production of these hormones 43 . All systems involved in oocyte differentiation and maturation (including hormones, proteins, and soluble substances secreted by adipocytes) are dysregulated and impacted in their physiology because obesity is pathologically related to inflammation 44 . The reduction of women's fertility potential due to adipose tissue is therefore directly caused by malfunctioning of the primary molecular mechanisms that control the normal biological activity of the cellular components of their reproductive organs, which are also regulated by the hypothalamic-pituitary-ovarian axis 11 . There are various benefits to our study. Initially, the NHANES database served as the foundation for our investigation, and every analysis considered the use of suitable NHANES sampling weights to increase the representativeness of the findings. Second, we investigated the nonlinear link between infertility and VAI by sensitivity analysis. This is the first study to look at the relationship between VAI and female infertility. Third, VAI is a quick and uncomplicated clinical tool that should be used to advise women of reproductive age about their higher risk of infertility at medical reviews. Our study is not without limits, though. First, we were unable to clearly determine a causal association among VAI and infertility because of the cross-sectional nature of our study. Secondly, an in-depth examination of additional markers was not feasible due to the restricted data present in the NHANES database.

Infertility is a medical condition usually defined as the failure to conceive after 12 months of regular sexual intercourse 1 . About 7 to 15.5% of women in the US who are of reproductive age have infertility, and 8 out of 12 couples struggle with conception 2 . Infertility affects a sizable percentage of people worldwide (9.0%), in rich countries (3.5–16.6%), and in developing countries (6.9–9.3%) 3 . Even though infertility has gained international attention recently as a public health concern, the factors that contribute to it still need to be further investigated. One prevalent issue among women who are fertile is obesity. It is generally regarded as an excessive build-up of body fat that has a detrimental impact on one’s health 4 , 5 . It is predicted that by 2025, more than 21% of women worldwide will be obese. This tendency may be linked to both rapid changes in lifestyle and economic development 6 . More gynecological disorders in women, such as excessive menstruation 7 , endometriosis and uterine fibroids (UF) 8 , 9 , polycystic ovary syndrome (PCOS) 10 , 11 , pregnancy complications like pre-eclampsia and eclampsia 12 , miscarriage 13 and infertility 14 , 15 , are linked to higher body mass indices (BMI). Despite being a conventional and cost-effective approach, using body mass index (BMI) to evaluate obesity (defined as a BMI exceeding 25 kg/m 2 ) lacks the ability to differentiate between lean and fat body mass 16 , 17 . Because BMI does not provide a good picture of obesity distribution, it is not appropriate to use it alone to assess obesity 18 . Waist circumference measures central obesity, but it may not adequately reflect the health hazards associated with abdominal obesity since it cannot distinguish between visceral and subcutaneous adipose tissue in the abdomen. A recently proposed mathematical model with a scientific design, the visceral obesity index (VAI) evaluates the quantity and function of visceral fat in a person’s body 19 . Increased visceral fat has been linked in studies to a number of diseases, including metabolic syndrome, diabetes, cardiovascular disease, and several forms of cancer 20 . Anthropometric information (waist circumference, BMI) and metabolic markers (triglycerides and HDL cholesterol) are combined in the VAI assessment approach. In essence, VAI offers a comprehensive evaluation of a person's visceral fat status and could be a helpful substitute for visceral CT scans due to its lower radiation risks and cost 21 . This study investigated the connection between infertility and the visceral obesity index in American women between the ages of 18 and 45. The National Health and Nutrition Examination Survey (NHANES) will provide the data for the study. The goal is to shed light on the complex relationship between visceral fat and infertility in order to aid in the clinical development of treatments aimed at reducing the risk of infertility.

Supplementary Information. Supplementary Information.