Are you threatened? The size of the waist, not weight, can affect fertility in women

In the last study published in the journal Scientists examined the relationship between relative fat (RFM) and women’s infertility.

Infertility is the inability to achieve pregnancy after a regular year, without sex protection. It affects about 10% to 15% of couples around the world and significantly affects mental and physical health. The etiology of infertility is varied and complex, including abnormalities of the reproductive system, lifestyle factors, immunological diseases and hormonal disorders. The relationship between infertility and obesity has aroused significant interest in recent years.

Women’s infertility may result from egg disease, ovarian dysfunction, polycystic ovary syndrome (PCOS) and endometriosis. PCOS is characterized by hyperandrogenism, insulin resistance and an impaired function of ovarian follicles; These irregularities are particularly clear in women with obesity. Evidence suggests that obesity is positively correlated with the risk of infertility.

RFM is a more effective measure of visceral fat than the body mass index (BMI). RFM is calculated using the formula: RFM = 64 – (20 × height/waist circumference) + 12 (for women). RFM integrates the waist circuit (toilet), more precisely reflecting the distribution of visceral fat. Unlike BMI, which may not identify women with normal weight, but excessive visceral fat, RFM offers better screening for metabolic and reproductive risk.

In addition, the visceral fat directly affects the fertility and function of the ovaries, affecting chronic inflammation and insulin resistance, which is better captured by RFM. While RFM correlates with metabolic diseases, the way it refers to the female reproductive system, especially infertility, is poorly defined.

The study also notes that infertility and obesity are associated with psychosocial interaction, such as stress, anxiety and depression, emphasizing the need for a comprehensive approach to reproductive health.

About the study

In this study, scientists have examined the connections between RFM and infertility in women. The current analyzes used national data examination of health and nutritional tests from 2017 and 2020. Women aged 20–44 were included; People with the history of ovarian or hysterectomy or missing information about RFM or infertility were excluded. The basic exhibition was RFM, calculated on the basis of the height of the unit and toilet.

The basic result was infertility, determined using the elements of the questionnaire, asking if the participants tried to achieve pregnancy for a year without success, or whether they consulted with a doctor so as not to be able to understand. Accompanying variables included age, ethnic origin, marital status, level of education, BMI, alcohol -consumption, menstrual cycle regularity, sleep disturbance, smoking and prior treatment for pelvic infection or pelvic inflammatory disease.

The relationship between infertility and RFM was assessed by means of multidimensional logistic regression models. One model was adapted to sociodemographic variables, and the other was adapted to all accompanying variables. In addition, RFM was stratified in quarter to test line trends. The study also uses limited flexible cubic analysis to assess the shape of the association, confirming the linear compound.

Finally, subgroup analyzes were carried out to assess the stability of the Association (Association) in various demographic factors, including ethnic origin, education, income, BMI, alcohol consumption, smoking, smoking, sleep patterns, the regularity of the menstrual cycle and the history of pelvic infection or pelvic infection.

Arrangements

The study included 1487 women with an average age of 31.9 years and RFM 41.2. Of these, 200 people were infertile. Most of the participants were white non-Latin (29%), followed by non-Polish black (28%) and Mexican American (14%). About 56% of participants were married or living, and 36% was not married. Most participants did not smoke (70%) or have no sleep problems (77%) and had regular menstrual cycles (93%).

Infertile women were older, marital or common and had higher RFM than those without infertility. The average RFM was 42.8 for the infertile group and 40.9 for people without infertility. Scientists have recorded a significant correlation between RFM and infertility. The oil model (uncorrected) showed that the risk of infertility increased by 4% for each unit growth in RFM.

In the fully corrected model, after taking into account all accompanying variables, each RFM increase was associated with a 6% higher risk of infertility (quotient opportunities (opportunities [OR] = 1.06, 95% confidence interval [CI]: 1,01-1.12, p = 0.019).

The RFM relationship with infertility remained after adapting to sociodemographic variables or all accompanying variables. In addition, the highest quarter of RFM had a much higher risk of infertility than the lowest quarter. In particular, the risk of infertility in the highest quarter was 2.38 times higher than in the lowest quarter (OR = 2.38, 95% CI: 0.99-5.70), although the confidence interval included 1.00, which indicates the statistical significance of the limit for this discovery. T

Here is a significant and linear compound, with the risk of infertility continuously as RFM increases. Limited cubic analysis of the splajn confirmed that this association was rather linear than non -linear.

The results were stable in subgroups. The study showed consistent associations in the main demographic and clinical subgroups, including ethnicity, education, income, BMI categories, alcohol and smoking status, sleep disorders, regular menstrual cycle and pelvic infection history.

Conclusions

To sum up, discoveries indicate a significant relationship between RFM and women’s infertility, with similar results in various subgroups. The restrictions on the study include its cross -sectional project, which excludes causal inference and poor generalization due to the limited representation of the United States population by the sample.

In addition, unchanged disturbing factors could not be completely excluded. In general, RFM can be used as a potential indicator of screening, especially in women who may have normal BMI, but increased vanal fat.

Future research should assess its clinical significance, including through prospective and multi -level research relating to genetic factors, lifestyle and environment.