Abstract
Accumulated evidence has shown that the antioxidant diet exhibits protective effects on women’s reproductive health. The Composite Dietary Antioxidant Index (CDAI) serves as a crucial indicator for assessing antioxidant-rich diets. However, the relationship between CDAI and menopause age as well as reproductive lifespan remains unclear. In this cross-sectional analysis, we investigated these associations using data from 4514 post-menopausal women who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. Analyses incorporated sampling weights and design variables to address its complex survey structure, ensuring nationally representative results Information on age at menopause and reproductive lifespan was derived from questionnaire data. The CDAI was calculated based on the intake of selenium, zinc, carotenoid, Vitamin A, C and E. Multiple linear regression, smooth curve fitting, threshold effect analysis, and subgroup analysis were used to investigate the association between the CDAI and age at menopause as well as reproductive lifespan. After adjusting for age, race, BMI and other confounding factors, our findings revealed that higher CDAI was associated with a later age at menopause (β = 0.09, 95% CI = 0.02–0.15, P = 0.013) and longer reproductive lifespan (β = 0.11, 95% CI = 0.04–0.18, P = 0.001). A nonlinear threshold effect was identified, with an inflection point at CDAI = 1.05. Below this threshold, each unit increase in CDAI was associated with a 0.24-year delay in menopause (β = 0.24, 95% CI = 0.09–0.39, P = 0.002), but this effect was not observed above this point. Additionally, each standard deviation increase in CDAI was associated with a 4% decrease in early menopause risk (OR = 0.96, 95% CI = 0.92-1.00, P = 0.048). The use of oral contraceptives and female hormones modified these relationships. Our research highlighted a positive non-linear association between CDAI and age at menopause, as well as reproductive lifespan, emphasizing the potential clinical relevance of dietary antioxidant optimization within specific thresholds.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-23666-9.
Keywords: Composite dietary antioxidant index, Menopause, Reproductive lifespan, Cross-sectional study
Subject terms: Nutrition, Endocrine reproductive disorders
Introduction
Menopause is an irreversible stage that women will eventually face in their lifetime, which is defined as the permanent cessation of menstruation due to the loss of ovarian follicular activity1, marking the end of reproductive capability. The timing of menopause and reproductive lifespan (defined as the duration from menarche to menopause) are not merely physiological milestones but critical determinants of long-term health outcomes. Early menopause (before 45 years) is associated with an increased risk of overall mortality, cardiovascular diseases, neurological disorders, mental illnesses, osteoporosis, and other related health sequelae in women, and the risk intensifies as the age at menopause advances2. Similarly, a shorter reproductive lifespan is significantly associated with an increased risk of cardiovascular diseases3, mood disorders4, chronic kidney disease5, and pulmonary dysfunction6. Given these profound impacts, identifying modifiable factors that influence menopause timing and reproductive lifespan is of substantial clinical and public health importance.
The menopause age and reproductive lifespan can be influenced by various factors including race, geographical region, genetics and levels of oxidative stress7,8. Among these, oxidative stress has emerged as a key mechanistic driver of ovarian aging. Oxidative stress is defined as the condition arising from an imbalance between free radicals and antioxidants in the body, which can lead to cellular damage, accelerated aging9, and a decline in female reproductive capacity. A direct link between oxidative stress and ovarian function has been firmly established in substantial animal models10. Notably, recent clinical studies have also demonstrated that human ovarian aging is characterized by oxidative damage and mitochondrial dysfunction, with women exhibiting decreased ovarian reserve showing increased reactive oxygen species (ROS) level and reduced antioxidant status11. These findings collectively highlight oxidative stress as a critical target for preserving reproductive function.
In addition, adjusting the diet structure has been regarded as an effective way to influence reproductive lifespan12. More importantly, daily dietary intake of antioxidants can serve as a practical and sustainable means to combat oxidative stress13,14, with growing evidence supporting their role in protecting ovarian function. Furthermore, the antioxidant capacity of food is now being evaluated more objectively. The Composite Dietary Antioxidant Index (CDAI) is an effective and robust nutritional tool to measure of dietary antioxidant characteristics, which is calculated based on several dietary antioxidants including selenium, zinc, carotenoid, Vitamin A, C and E15. Unlike single-nutrient assessments, CDAI captures the synergistic effects of multiple antioxidants, providing a comprehensive measure of overall dietary antioxidant capacity—a key advantage given that antioxidants often act in concert to neutralize oxidative stress. This definition is first proposed by Wright in 2003, and has been progressively and extensively used as an indicator to measure an individual’s antioxidant capacity. Now various diseases have been found to be closely related to CDAI16. For instance, Liu et al. found that higher CDAI levels in postmenopausal women are associated with a lower risk of atherosclerotic cardiovascular disease17. Similarly, Wang et al. found that the CDAI was positively associated with a lower prevalence of chronic kidney disease in adults in the United States18. Notably, He et al. (2024) recently reported a significant negative correlation between CDAI and biological phenotypic age, suggesting its potential role in delaying aging processes19—a finding that indirectly supports its relevance to reproductive lifespan. However, the relationship between CDAI and menopause age as well as reproductive lifespan remains unknown. In this study, we hypothesize that higher CDAI—indicating greater overall dietary antioxidant intake—is associated with a later age at menopause and a longer reproductive lifespan.
The National Health and Nutrition Examination Survey (NHANES) is a population-based cross-sectional survey designed to gather information about the health and nutritional status of individuals across the United States. This database uses a complex stratified, multistage probability cluster sampling design to represent the entire US population. To date, researchers have used the NHANES database to unveil the negative association between CDAI and a likelihood of hypertension20, stroke21, and depression22. However, the relationship between the CDAI, age at menopause, and reproductive lifespan has not been evaluated. To address this gap, we utilized data involving 4514 participants with natural post menopause from the NHANES database spanning 1999–2018 to investigate these associations.
Materials and methods
Survey description
NHANES is conducted by the National Center for Health Statistics (NCHS), a part of the Centers for Disease Control and Prevention (CDC), to assess the health and nutritional status of the U.S. population. The survey uses a stratified multistage probability sampling method to ensure that the included samples are representative23,24. The study was approved by the National Center for Health Statistics Research Ethics Review Board, and written informed consent was obtained from each participant25.
Study population
From the participants of ten NHANES cycles between 1999 and 2018 (N = 101,316), we initially identified 10,598 women who had reached menopause due to natural causes or hysterectomy. These cycles were selected because they represent the earliest to latest surveys with standardized assessment of age at menarche and natural menopause in the reproductive health questionnaire module. We first excluded those with a history of hysterectomy or oophorectomy (N = 3,907), resulting in 6,691 individuals. Subsequently, we excluded participants with missing data on the Composite Dietary Antioxidant Index (CDAI), age at menarche, or age at menopause (N = 1,386). Additionally, participants with incomplete covariate information were removed (N = 791), including missing data on oral contraceptive or female hormone use (N = 339), marital status (N = 227), BMI (N = 179), and educational level (N = 46). Finally, a total of 4,514 postmenopausal women were included in the final analysis. The detailed selection process is presented in Fig. 1.
Fig. 1.
Flowchart of the participant selection from NHANES 1999–2018.
Exposure and outcomes
In the NHANES dataset, each participant’s food and nutrient intake was recorded using a 24-hour dietary recall interview. The initial dietary recall was conducted in person, followed by a telephone interview three to ten days later. The intake of antioxidants, micronutrients, and total energy was calculated using the Food and Nutrient Database for Dietary Studies provided by the United States Department of Agriculture26. From the questionnaire interview, we assessed the intake of dietary supplements over the past month, detailing dosage, frequency, and duration of consumption27. CDAI was calculated as the sum of the daily average intakes of zinc, selenium, carotenoids, vitamin A, vitamin C, and vitamin E. Each nutrient was first normalized by subtracting the mean and then dividing by its standard deviation (SD)16,17. Reproductive lifespan was defined as the duration from the age at menarche to the age at menopause. Menarche age was assessed using NHANES question code RHQ020. Menopause was identified based on responses to “Had regular periods in the past 12 months?” (RHQ30) for 1999–2002, and “At least 1 period in the past 12 months?” (RHQ031) and “Reason didn’t have a period” (RHD042/RHD43) for 2003–2018, with surgical menopause cases excluded using codes RHD280 (hysterectomy) and RHD310 (oophorectomy). Age at menopause was self-reported (RHQ060/RHQ067).
Covariates
In our study, we identified several potential factors that could influence the relationship between the CDAI and both age at menopause and reproductive lifespan, including race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Races), BMI, educational status (less than high school, high school or GED, above high school), poverty-income ratio (PIR), marital status (married/living with partner, never married, divorced/separated/widowed), alcohol consumption, smoking habits, and the use of oral contraceptives or female hormones. All these factors were incorporated into our multivariate adjustment model. BMI was calculated by dividing weight in kilograms by the square of height in meters. Following WHO recommendations, we used BMI cutoffs of 25 kg/m² and 30 kg/m² to classify overweight and obesity28. PIR was calculated as the household income divided by the federal poverty threshold, adjusted for family size and geographic location, following the U.S. Department of Health and Human Services Poverty Guidelines and NHANES analytic protocols29,30. Alcohol consumption was classified as none, moderate (1 drink/day), heavy (2–3 drinks/day) or binge (≥ 4 drinks/day) according to definitions from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) in the National Institute of Health. The smoking habits involved in the questionnaire data was ascribed as “never/former” (100 cigarettes in lifetime) or “now” (lifetime smoking). The detailed processes for measuring all variables in the study can be found at www.cdc.gov/nchs/nhanes/. We constructed three multivariate linear regression models to evaluate the association between CDAI and reproductive outcomes. Model 1 was unadjusted. Model 2 adjusted for age and race. Model 3 further included socioeconomic, lifestyle, and medical factors, as these variables may confound the antioxidant-reproductive outcome relationship. This progressive adjustment enhances the robustness of our findings.
Statistical analysis
Continuous variables are represented by mean ± standard deviation based on their distribution. The associations between different reproductive lifespans or groups due to age at menopause are analyzed using either the Chi-square test or the Kruskal-Wallis H test. Multivariate linear regression analysis is employed to investigate the relationships between CDAI and age at menarche, age at menopause, and reproductive age range. Model 1 remains unadjusted; Model 2 is adjusted for age and race; and Model 3 additionally adjusts for BMI, PIR, educational level, marital status, alcohol consumption, smoking status, and the use of oral contraceptives or female hormones. Subgroup analyses were conducted based on age, race, BMI, educational level, smoking habits, and use of oral contraceptives or female hormones to identify potential variations within these specific populations. Our study utilizes smooth curve fitting to thoroughly examine the potential nonlinear relationships between CDAI and both age at menopause and reproductive lifespan. Threshold effect analysis is utilized to examine the saturation effect of CDAI. Additionally, multivariate linear regression equations were applied to analyze the relationships between the components of CDAI and both age at menopause and reproductive lifespan.
All analyses were conducted in accordance with NHANES analytic guidelines, utilizing the R survey package to apply sampling weights, account for clustering and stratification, and generate nationally representative estimates. The weighted baseline characteristics of participants according to menarche age, menopause age, reproductive lifespan, and CDAI tertiles are provided in Supplementary Tables S1 and S2. Analyses were performed using Empower software (www.empowerstats.com; X&Y Solutions, Inc., Boston, MA, USA) and R version 3.4.3 (http://www.R-project.org, The R Foundation). P < 0.05 was considered statistically significant.
Results
Baseline characteristics of participants according to menarche age, menopause age and reproduction lifespan tertile
The study included 4514 participants. After applying sampling weights to account for the complex survey design, the weighted mean of the CDAI was 0.31 ± 0.07. Participants’ ethnic backgrounds were as follows: 5.56% Mexican American, 4.95% other Hispanic, 74.02% non-Hispanic White, 8.93% non-Hispanic Black, and 6.54% other races. The median age at menarche was 12.87 ± 0.04 years, and the median reproductive lifespan was 36.50 ± 0.16 years.
Then, participants were stratified into tertiles based on their age at menarche, age at menopause and reproductive lifespan, as shown in Table 1. Accordingly, age at menarche was categorized into three groups: earlier than 11 years, 12–13 years, and later than 14 years. There were significant differences among different menarche age groups in the following indicators, including BMI (P < 0.001), educational level (P = 0.004), use of oral contraceptives (OC) (P = 0.009) and reproductive lifespan (P < 0.001). Based on age at menopause, T1 represented participants under 47 years old, T2 represented those aged 48 to 51 years, and T3 represented those aged 52 and above. Age at menopause was significantly associated with age (P < 0.001), race (P < 0.001), educational level (P < 0.001), PIR (P < 0.001), marital status (P = 0.001), alcohol consumption (P < 0.001), smoking habits (P < 0.001), reproductive lifespan (P < 0.001) and CDAI (P < 0.001) across tertiles. In a separate column, participants were categorized based on reproductive lifespan, with T1 representing below 33 years, T2 representing 34 to 38 years, and T3 representing 39 years and above. Reproductive lifespan was significantly associated with race (P < 0.001), educational level (P < 0.001), PIR (P < 0.001), marital status (P = 0.004), alcohol consumption (P < 0.001), smoking habits and use of OC (P < 0.001), as well as the CDAI (P < 0.001). We found that CDAI showed an overall upward trend as both age at menopause and reproductive lifespan increased.
Table 1.
The baseline characteristics according to age of menarche, age of menopause and reproductive lifespan tertiles.
| Total | Age of menarche, years | Age of menopause, years | Reproductive lifespan, years | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T1(≤ 11) | T2(12 ~ 13) | T3(≥ 14) | P- value | T1(≤ 47) | T2(48 ~ 51) | T3(≥ 52) | P-value | T1(≤ 33) | T2(34 ~ 38) | T3(≥ 39) |
P- value |
||
| Age | 63.14 ± 0.22 | 61.83 ± 0.49 | 62.71 ± 0.48 | 63.77 ± 0.28 | 0.006 | 61.65 ± 0.45 | 62.47 ± 0.36 | 64.65 ± 0.31 | < 0.001 | 61.99 ± 0.56 | 62.20 ± 0.36 | 64.27 ± 0.30 | < 0.001 |
| Race, n(%) | 0.124 | < 0.001 | < 0.001 | ||||||||||
| Mexican American | 755(5.56) | 158(7.05) | 169(5.15) | 428(5.25) | 269(7.30) | 259(6.67) | 227(3.57) | 192(6.35) | 278(7.17) | 285(4.14) | |||
| Other Hispanic | 476(4.95) | 108(6.31) | 100(4.48) | 268(4.70) | 293(10.86) | 229(9.06) | 315(7.48) | 214(10.58) | 265(9.45) | 358(7.85) | |||
| Non-Hispanic White | 2072(74.02) | 370(72.31) | 526(77.16) | 1176(73.20) | 598(69.99) | 584(72.70) | 890(77.77) | 422(69.16) | 642(72.64) | 1008(77.08) | |||
| Non-Hispanic Black | 837(8.93) | 158(9.28) | 186(8.34) | 493(9.07) | 167(5.66) | 137(5.20) | 172(4.27) | 118(5.80) | 155(5.20) | 203(4.40) | |||
| Other Races | 374(6.54) | 32(5.04) | 74(4.86) | 268(7.78) | 96(6.18) | 128(6.37) | 150(6.91) | 92(8.11) | 122(5.54) | 160(6.53) | |||
| BMI category, n(%) | < 0.001 | 0.449 | 0.149 | ||||||||||
| Normal weight | 1216(30.49) | 160(21.47) | 244(27.04) | 812(35.02) | 385(32.43) | 349(27.54) | 482(31.20) | 302(34.98) | 409(30.54) | 505(28.49) | |||
| Overweight | 1394(31.05) | 238(30.00) | 319(29.83) | 837(31.93) | 592(37.26) | 563(39.69) | 749(38.45) | 403(34.58) | 602(38.45) | 899(40.18) | |||
| Obese | 1904(38.47) | 428(48.52) | 492(43.12) | 984(33.05) | 446(30.31) | 425(32.77) | 523(30.35) | 333(30.44) | 451(31.02) | 610(31.33) | |||
| Education level, n(%) | 0.004 | < 0.001 | < 0.001 | ||||||||||
| Less than high school | 1381(18.03) | 213(14.61) | 276(15.13) | 892(20.45) | 536(47.20) | 605(55.09) | 890(61.15) | 364(44.64) | 623(52.35) | 1044(61.98) | |||
| High school or GED | 1102(26.66) | 190(24.54) | 258(26.68) | 654(27.35) | 382(29.63) | 312(27.26) | 408(24.16) | 272(30.68) | 364(27.52) | 466(24.32) | |||
| Abovehighschool | 2031(55.32) | 423(60.85) | 521(58.18) | 1087(52.20) | 505(23.18) | 420(17.65) | 456(14.69) | 402(24.67) | 475(20.14) | 504(13.70) | |||
| Income to poverty ratio(%) | 0.107 | < 0.001 | < 0.001 | ||||||||||
| < 1.5 | 1683(23.33) | 310(24.66) | 358(19.87) | 1015(24.42) | 625(31.04) | 524(23.93) | 534(17.52) | 486(32.41) | 587(26.44) | 610(17.27) | |||
| 1.5 ~ 3.5 | 1510(32.60) | 258(29.37) | 376(35.30) | 876(32.47) | 327(36.24) | 381(42.53) | 613(50.63) | 218(35.58) | 405(41.34) | 698(49.62) | |||
| ≥ 3.5 | 1321(44.07) | 258(45.97) | 321(44.83) | 742(43.10) | 471(32.72) | 432(33.54) | 607(31.85) | 334(32.01) | 470(32.22) | 706(33.12) | |||
| Maritalstatus, n(%) | 0.195 | 0.001 | 0.004 | ||||||||||
| Married/living with partner | 2308(59.70) | 403(57.03) | 539(62.14) | 1366(59.50) | 87(3.72) | 71(3.55) | 61(1.94) | 63(3.87) | 73(3.34) | 83(2.24) | |||
| Never married | 219(2.93) | 49(3.90) | 50(1.96) | 120(3.04) | 668(42.02) | 582(35.35) | 737(35.54) | 480(41.29) | 657(38.71) | 850(34.75) | |||
| Divorced/separated/widowed | 1987(37.37) | 374(39.07) | 466(35.90) | 1147(37.46) | 668(54.26) | 684(61.10) | 956(62.51) | 495(54.84) | 732(57.95) | 1081(63.00) | |||
| Alcohol consumption, n(%) | 0.258 | < 0.001 | < 0.001 | ||||||||||
| None | 1276(23.33) | 220(23.58) | 268(20.55) | 788(24.48) | 95(7.40) | 58(4.33) | 53(1.94) | 68(7.96) | 76(4.49) | 62(2.42) | |||
| Moderate | 1898(44.22) | 346(41.23) | 476(48.77) | 1076(43.19) | 366(30.56) | 340(25.24) | 428(28.69) | 269(31.58) | 359(26.09) | 506(28.20) | |||
| Heavy | 1134(28.23) | 225(31.16) | 264(26.40) | 645(28.06) | 541(37.12) | 572(47.25) | 785(47.05) | 370(32.93) | 626(47.16) | 902(47.17) | |||
| Binge | 206(4.23) | 35(4.02) | 47(4.28) | 124(4.27) | 421(24.92) | 367(23.18) | 488(22.32) | 331(27.54) | 401(22.26) | 544(22.21) | |||
| Smoking habits, n(%) | 0.689 | < 0.001 | 0.015 | ||||||||||
| Never/former | 2727(57.60) | 467(55.79) | 645(57.43) | 1615(58.27) | 817(53.69) | 812(54.44) | 1098(62.54) | 622(54.87) | 854(54.67) | 1251(60.76) | |||
| Now | 1787(42.40) | 359(44.21) | 410(42.57) | 1018(41.73) | 606(46.31) | 525(45.56) | 656(37.46) | 416(45.13) | 608(45.33) | 763(39.24) | |||
| Ever OC use, n(%) | 0.009 | 0.106 | < 0.001 | ||||||||||
| NO | 1767(31.06) | 268(25.21) | 395(30.78) | 1104(33.14) | 836(66.28) | 819(68.82) | 1092(70.88) | 556(62.02) | 911(70.11) | 1280(71.17) | |||
| Yes | 2747(68.94) | 558(74.79) | 660(69.22) | 1529(66.86) | 587(33.72) | 518(31.18) | 662(29.12) | 482(37.98) | 551(29.89) | 734(28.83) | |||
| Ever Female Hormones use, n(%) | 0.722 | 0.006 | 0.090 | ||||||||||
| NO | 3346(67.26) | 602(65.84) | 791(68.43) | 1953(67.22) | 337(30.14) | 313(29.20) | 518(37.03) | 222(28.12) | 371(33.21) | 575(34.44) | |||
| Yes | 1168(32.74) | 224(34.16) | 264(31.57) | 680(32.78) | 1086(69.86) | 1024(70.80) | 1236(62.97) | 816(71.88) | 1091(66.79) | 1439(65.56) | |||
| Age of menarche | 12.87 ± 0.04 | 10.53 ± 0.03 | 12.00 ± 0.00 | 14.03 ± 0.04 | < 0.001 | 12.91 ± 0.07 | 12.74 ± 0.07 | 12.92 ± 0.06 | 0.057 | 13.58 ± 0.08 | 13.12 ± 0.06 | 12.39 ± 0.06 | < 0.001 |
| Age of menopause | 49.36 ± 0.15 | 49.41 ± 0.30 | 48.93 ± 0.27 | 49.54 ± 0.20 | 0.120 | 42.82 ± 0.18 | 49.33 ± 0.03 | 53.96 ± 0.07 | < 0.001 | 41.68 ± 0.23 | 48.51 ± 0.08 | 53.29 ± 0.09 | < 0.001 |
| Reproductive lifespan | 36.50 ± 0.16 | 38.87 ± 0.30 | 36.93 ± 0.27 | 35.51 ± 0.20 | < 0.001 | 29.91 ± 0.21 | 36.58 ± 0.07 | 41.04 ± 0.09 | < 0.001 | 28.10 ± 0.21 | 35.39 ± 0.05 | 40.91 ± 0.08 | < 0.001 |
| CDAI | 0.31 ± 0.07 | 0.48 ± 0.18 | 0.37 ± 0.17 | 0.22 ± 0.09 | 0.400 | −0.11 ± 0.13 | 0.29 ± 0.13 | 0.60 ± 0.11 | < 0.001 | −0.18 ± 0.17 | 0.10 ± 0.11 | 0.66 ± 0.10 | < 0.001 |
Baseline characteristics according to the CDAI tertile
To better illustrate the impact of the CDAI, Table 2 trisected the CDAI values into three distinct groups: T1 ranged from − 7.06 to −1.80, T2 from − 1.80 to 0.96, and T3 from 0.96 to 12.32. Among different CDAI groups, there were significant differences in race (P < 0.001), BMI (P < 0.001), educational level (P < 0.001), PIR (P < 0.001), marital status (P = 0.007), alcohol consumption (P = 0.021), and use of female hormones (P = 0.002). Similar to Table 1, participants with higher CDAI tended to experience later ages at menopause and longer reproductive lifespans.
Table 2.
The baseline characteristics according to the CDAI tertiles.
| Tertile1(−7.06~−1.80) | Tertile2(−1.80 ~ 0.96) | Tertile3(0.96 ~ 12.32) | P-value | |
|---|---|---|---|---|
| Age, years | 63.42 ± 0.40 | 63.17 ± 0.35 | 62.89 ± 0.37 | 0.622 |
| Race, n (%) | < 0.001 | |||
| Mexican American | 280(6.78) | 268(6.38) | 207(3.88) | |
| Other Hispanic | 338(12.05) | 254(8.40) | 245(6.89) | |
| Non-Hispanic White | 614(69.47) | 696(74.92) | 762(76.88) | |
| Non-Hispanic Black | 159(5.24) | 182(5.31) | 135(4.40) | |
| Other Races | 115(6.46) | 104(4.98) | 155(7.96) | |
| BMI category, n (%) | < 0.001 | |||
| Normal weight | 373(27.30) | 357(26.97) | 486(36.08) | |
| Overweight | 671(40.89) | 663(41.02) | 570(34.32) | |
| Obese | 462(31.81) | 484(32.01) | 448(29.60) | |
| Education level, n (%) | < 0.001 | |||
| Less than high school | 552(46.41) | 660(54.01) | 819(63.56) | |
| High school or GED | 375(29.57) | 402(27.71) | 325(23.42) | |
| Above high school | 579(24.02) | 442(18.29) | 360(13.02) | |
| Income to poverty ratio (%) | < 0.001 | |||
| < 1.5 | 684(30.65) | 523(22.13) | 476(18.52) | |
| 1.5 ~ 3.5 | 340(36.94) | 435(42.54) | 546(51.09) | |
| ≥ 3.5 | 482(32.42) | 546(35.32) | 482(30.38) | |
| Marital status, n (%) | 0.007 | |||
| Married/living with partner | 88(3.42) | 69(3.00) | 62(2.49) | |
| Never married | 720(41.87) | 658(37.17) | 609(33.95) | |
| Divorced/separated/widowed | 698(54.72) | 777(59.83) | 833(63.56) | |
| Alcohol consumption, n (%) | 0.021 | |||
| None | 66(4.25) | 75(4.28) | 65(4.15) | |
| Moderate | 368(26.99) | 376(28.83) | 390(28.69) | |
| Heavy | 581(40.16) | 657(45.79) | 660(46.09) | |
| Binge | 491(28.60) | 396(21.10) | 389(21.06) | |
| Smoking habits, n (%) | 0.613 | |||
| Never/former | 919(57.92) | 894(56.02) | 914(58.71) | |
| Now | 587(42.08) | 610(43.98) | 590(41.29) | |
| Ever OC use, n (%) | 0.708 | |||
| NO | 897(67.59) | 920(69.33) | 930(69.67) | |
| Yes | 609(32.41) | 584(30.67) | 574(30.33) | |
| Ever Female Hormones use, n (%) | 0.002 | |||
| NO | 316(27.42) | 387(31.97) | 465(37.64) | |
| Yes | 1190(72.58) | 1117(68.03) | 1039(62.36) | |
| Age of menarche, years | 12.95 ± 0.07 | 12.90 ± 0.07 | 12.77 ± 0.07 | 0.185 |
| Age of menopause, years | 48.60 ± 0.27 | 49.61 ± 0.19 | 49.76 ± 0.20 | < 0.001 |
| Reproductive lifespan, years | 35.65 ± 0.28 | 36.71 ± 0.19 | 36.98 ± 0.21 | < 0.001 |
| CDAI | −3.21 ± 0.04 | −0.44 ± 0.03 | 3.76 ± 0.07 | < 0.001 |
Association between CDAI and the age at menopause as well as reproductive lifespan
Table 3 displayed the results of multivariate linear regression analyzing the association of CDAI with age at menarche, age at menopause and reproductive lifespan. In the unadjusted model, there is a significant positive correlation between CDAI and both age at menopause (β = 0.13, 95%CI = 0.06–0.20, P < 0.001) and reproductive lifespan (β = 0.15, 95% CI = 0.08–0.22, P < 0.001). After adjusting for age and race in model 2, the significant positive effects of age at menopause (β = 0.13, 95% CI = 0.06–0.19, P < 0.001) and reproductive lifespan (β = 0.15, 95%CI = 0.08–0.22, P < 0.001) persist. In model 3, adjustments were incorporated for additional variables including BMI, educational status, PIR, marital status, alcohol consumption, smoking habits, use of oral contraceptives or female hormones. The fully adjusted model revealed that increased CDAI was correlated with increased age at menopause (β = 0.09, 95%CI = 0.02–0.15, P = 0.013) and increased reproductive lifespan (β = 0.11, 95%CI = 0.04–0.18, P = 0.001). Additionally, after full adjustment for confounding factors, the analysis showed that T3, compared to T1, had a significant positive correlation with age at menopause (β = 0.86, 95%CI = 0.30–1.42, P = 0.003) and reproductive lifespan (β = 1.01, 95%CI = 0.42–1.60, P < 0.001).
Table 3.
The association of CDAI with the age of menopause and reproductive lifespan.
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| β (95%CI) | P-value | β (95%CI) | P-value | β (95%CI) | P-value | |
| Age of menarche, years | ||||||
| CDAI | −0.02(−0.05, 0.00) | 0.062 | −0.02(−0.05, 0.00) | 0.064 | −0.02(−0.05, 0.00) | 0.062 |
| CDAI group | ||||||
| Tertile 1 | Reference | Reference | Reference | Reference | Reference | Reference |
| Tertile 2 | −0.05(−0.24, 0.13) | 0.582 | −0.03(−0.21, 0.15) | 0.727 | 0(−0.18, 0.19) | 0.979 |
| Tertile 3 | −0.18(−0.37, 0.02) | 0.079 | −0.17(−0.37, 0.03) | 0.088 | −0.15(−0.35, 0.04) | 0.116 |
| P for trend | 0.154 | 0.119 | 0.081 | |||
| Age of menopause, years | ||||||
| CDAI | 0.13(0.06, 0.20) | < 0.001 | 0.13(0.06, 0.19) | < 0.001 | 0.09(0.02, 0.15) | 0.013 |
| CDAI group | ||||||
| Tertile 1 | Reference | Reference | Reference | Reference | Reference | Reference |
| Tertile 2 | 1.01(0.42, 1.60) | < 0.001 | 1.02(0.43, 1.60) | < 0.001 | 0.85(0.28, 1.41) | 0.004 |
| Tertile 3 | 1.16(0.60, 1.71) | < 0.001 | 1.13(0.57, 1.70) | < 0.001 | 0.86(0.30, 1.42) | 0.003 |
| P for trend | 0.455 | 0.528 | 0.895 | |||
| Reproductive lifespan, years | ||||||
| CDAI | 0.15(0.08, 0.22) | < 0.001 | 0.15(0.08, 0.22) | < 0.001 | 0.11(0.04, 0.18) | 0.001 |
| CDAI group | ||||||
| Tertile 1 | Reference | Reference | Reference | Reference | Reference | Reference |
| Tertile 2 | 1.06(0.45, 1.68) | < 0.001 | 1.05(0.42, 1.67) | 0.001 | 0.84(0.24, 1.45) | 0.006 |
| Tertile 3 | 1.33(0.76, 1.91) | < 0.001 | 1.30(0.71, 1.90) | < 0.001 | 1.01(0.42, 1.60) | < 0.001 |
| P for trend | 0.214 | 0.242 | 0.445 | |||
Model 1: No covariates were adjusted.
Model 2: Adjusted for age and race.
Model 3: Adjusted for age, race, BMI, education level, PIR, marital status, alcohol consumption, smoking habits, use of oral contraceptives or female hormones.
Next, multivariate regression was employed to evaluate the impact of CDAI on early (under 45 years) and late (over 55 years) menopause. According to Table 4, across all models, an increased CDAI significantly reduced the risk of early menopause. In Model 1, without adjusting for variables, each standard deviation increase in CDAI was associated with a 5% reduction in the risk of early menopause (OR = 0.94, P = 0.007). In Model 2, after adjusting for age and race, each standard deviation increase in CDAI was associated with a 6% reduction in the risk of early menopause (OR = 0.94, P = 0.007). In Model 3, after adjusting for age, race, BMI, educational level, PIR, marital status, alcohol consumption, smoking habits, and use of oral contraceptives or female hormones, CDAI remained negatively associated with the risk of early menopause (OR = 0.96, P = 0.048). After dividing CDAI into tertiles, in Model 1, the risk of early menopause in T3 compared to T1 is reduced by 33% (OR = 0.67, P = 0.004); in Model 2, it was reduced by 34% (OR = 0.66, P = 0.004); and in Model 3, it was reduced by 27% (OR = 0.73, P = 0.034). In contrast to the findings for early menopause, no significant association was observed between CDAI and late menopause (≥ 55 years) across all models.
Table 4.
Associations between CDAI and age at menopause.
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| OR (95%CI) | P-value | OR (95%CI) | P-value | OR (95%CI) | P-value | |
| Early menopause (< 45 years) | ||||||
| CDAI | 0.94 (0.91,0.98) | 0.007 | 0.94(0.91,0.98) | 0.007 | 0.96(0.92, 1.00) | 0.048 |
| CDAI group | ||||||
| Tertile 1 | Reference | Reference | Reference | Reference | Reference | Reference |
| Tertile 2 | 0.68(0.50, 0.92) | 0.013 | 0.67(0.50, 0.91) | 0.012 | 0.71(0.53, 0.97) | 0.033 |
| Tertile 3 | 0.67(0.51, 0.88) | 0.004 | 0.66(0.50, 0.88) | 0.004 | 0.73(0.55, 0.98) | 0.034 |
| P for trend | 0.846 | 0.868 | 0.892 | |||
| Late menopause (≥ 55 years) | ||||||
| CDAI | 1.01(0.98, 1.05) | 0.399 | 1.02(0.98, 1.05) | 0.372 | 1.01(0.97, 1.04) | 0.757 |
| CDAI group | ||||||
| Tertile 1 | Reference | Reference | Reference | Reference | Reference | Reference |
| Tertile 2 | 1.06(0.76, 1.47) | 0.749 | 1.08(0.77, 1.52) | 0.652 | −0.23(−0.67,0.22) | 0.747 |
| Tertile 3 | 1.21(0.92, 1.60) | 0.166 | 1.25(0.93, 1.67) | 0.140 | −0.25(−0.74,0.25) | 0.300 |
| P for trend | 0.312 | 0.316 | 0.419 | |||
Model 1: No covariates were adjusted.
Model 2: Adjusted for age and race.
Model 3: Adjusted for age, race, BMI, education level, PIR, marital status, alcohol consumption, smoking habits, use of oral contraceptives or female hormones.
To investigate whether the effects of the CDAI on menopause age and reproductive lifespan continue to persist with increasing levels, we used CDAI to create smooth curves for age at menopause and reproductive lifespan. Figure 2 revealed an inverted U-shaped curve between CDAI and age at menopause, and an L-shaped curve for CDAI and reproductive lifespan. Therefore, we further conducted a threshold effect analysis as presented in Table 5, which indicated that below an inflection point of 1.05, there was a positive correlation between CDAI and menopause age (β = 0.24, 95% CI = 0.09–0.39, P = 0.002) as well as reproductive lifespan (β = 0.24, 95% CI = 0.08–0.41, P = 0.003), with log-likelihood ratios of 0.003 and 0.002, respectively. Above this point, the influence of CDAI ceased to be statistically significant. This may indicate that a reasonable increase in the CDAI up to 1.05 could be a clinical strategy to mitigate the risk of early menopause and prolong the reproductive age interval.
Fig. 2.
Smooth curve fitting for the association between CDAI and the age at menopause (a) and reproductive lifespan (b).
Table 5.
Threshold effect analysis of CDAI on age at menopause and reproductive lifespan by the two-piecewise linear regression.
| Inflection point | Adjusted β (95% CI), P-value | |
|---|---|---|
| Age at menopause, years | Reproductive lifespan, years | |
| < 1.05 | 0.24 (0.09, 0.39) 0.002 | 0.24 (0.08, 0.41) 0.003 |
| ≥ 1.05 | −0.07 (−0.21, 0.07) 0.327 | −0.03 (−0.16, 0.11) 0.716 |
| Log-likelihood ratio | 0.003 | 0.002 |
Subgroup analysis
As shown in Fig. 3, a subgroup analysis was conducted to assess the robustness of the correlation between CDAI and age at menopause as well as reproductive lifespan. Age was categorized into two groups based on threshold of 60. The variables considered included age, race, BMI, educational level, smoking status, marital status, and use of oral contraceptives and female hormones. It was observed that in populations who had used oral contraceptives and female hormones, the correlations between CDAI and age at menopause as well as reproductive lifespan were more pronounced. Specifically, in the subgroup using oral contraceptives, each standard deviation increase in CDAI was associated with a delay in age at menopause by 0.11 years (β = 0.11, 95%CI = 0.04–0.17, P < 0.01) and an increase in the reproductive age range by 0.16 years (β = 0.16, 95%CI = 0.04–0.17, P < 0.01). Similarly, in the subgroup using female hormones, each standard deviation increasing in CDAI resulted in a delay in age at menopause by 0.12 years (β = 0.12, 95% CI = 0.06–0.19, P < 0.01) and an increase in the reproductive lifespan by 0.17 years (β = 0.17, 95% CI = 0.07–0.26, P < 0.01). In participants that did not use oral contraceptives or female hormones, no significant correlation was observed between CDAI and age at menopause as well as reproductive lifespan. Interaction tests within subgroups for age, race, BMI, educational level, smoking status, and marital status were all not significant, indicating that the relationships between CDAI and age at menopause as well as reproductive lifespan were consistent across these factors.
Fig. 3.
Subgroup analyses of the association between CDAI and age at menopause as well as reproductive lifespan stratified by age, race, BMI, smoking status, marital status, ever use OC or female hormones.
Association between components of CDAI and the age at menopause and reproductive lifespan
In Table 6, a multivariate linear regression equation was used to explore the relationship between the six components of CDAI and age at menopause as well as reproductive lifespan. In the fully adjusted Model 3, only Vitamin C and carotenoids showed a significant positive correlation.
Table 6.
Association of six components of CDAI (mg) with age at menopause and reproductive lifespan.
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| β (95%CI) | P-value | β (95%CI) | P-value | β (95%CI) | P-value | |
| Age of menopause | ||||||
| Vitamin A | 0.001(0.000,0.001) | 0.030 | 0(0.000,0.001) | 0.108 | 0(0.000,0.001) | 0.416 |
| Vitamin C | 0.006(0.003,0.009) | < 0.001 | 0.005(0.002,0.008) | < 0.001 | 0.004(0.001,0.007) | 0.018 |
| Vitamin E | 0.038(−0.028,0.103) | 0.257 | 0.046(−0.015,0.107) | 0.14 | 0.018(−0.046,0.082) | 0.574 |
| Selenium | 0.003(−0.003,0.009) | 0.311 | 0.004(−0.002,0.010) | 0.159 | 0.003(−0.002,0.008) | 0.278 |
| Zinc | 0.04(−0.005,0.085) | 0.079 | 0.041(−0.004,0.086) | 0.072 | 0.033(−0.009,0.075) | 0.127 |
| Carotenoid | 0.000(0.000,0.000) | < 0.001 | 0.000(0.000,0.000) | < 0.001 | 0.000(0.000,0.000) | 0.001 |
| Reproductive lifespan | ||||||
| Vitamin A | 0.001(0.000,0.001) | 0.005 | 0.001(0.000,0.001) | 0.023 | 0(0.000,0.001) | 0.117 |
| Vitamin C | 0.005(0.002,0.008) | < 0.001 | 0.005(0.002,0.008) | < 0.001 | 0.004(0.001,0.007) | 0.021 |
| Vitamin E | 0.056(−0.006,0.118) | 0.078 | 0.062(0.003,0.122) | 0.041 | 0.034(−0.026,0.094) | 0.267 |
| Selenium | 0.005(−0.001,0.010) | 0.134 | 0.006(0.000,0.011) | 0.071 | 0.004(−0.001,0.010) | 0.146 |
| Zinc | 0.045(−0.001,0.091) | 0.056 | 0.044(−0.003,0.091) | 0.065 | 0.035(−0.008,0.079) | 0.112 |
| Carotenoid | 0.000(0.000,0.000) | < 0.001 | 0.000(0.000,0.000) | < 0.001 | 0.000(0.000,0.000) | < 0.001 |
Model 1: No covariates were adjusted.
Model 2: Adjusted for age and race.
Model 3: Adjusted for age, race, BMI, education level, PIR, marital status, alcohol consumption, smoking habits, use of oral contraceptives or female hormones.
Discussion
Our study found that an increase in the CDAI was positively correlated with an increase in the age at menopause and reproductive lifespan. Higher CDAI significantly reduced the risk of early menopause (under 45 years) and there was a threshold effect on menopausal age and reproductive interval. Subgroup analysis indicated that the use of oral contraceptives or female hormones impacted the relationship between CDAI and reproductive metrics. Further, Vitamin C and carotenoids, key components of CDAI, appear to extend reproductive lifespan significantly. This study is the first to explore these relationships in naturally menopausal women, suggesting that dietary antioxidants may delay menopause onset and extend reproductive lifespan, with significant implications for improving women’s reproductive health.
Currently, the use of dietary antioxidant properties to regulate ovarian function has been a hot topic of research today31. For instance, dietary flaxseed, due to its antioxidant components, has been proven to potentially improve menopausal symptoms such as hot flashes and sweating32,33. Additionally, a cross-sectional study conducted by Alina et al. using NHANES data from 2001 to 2018 also found that an increased intake of Vitamin D, a promoter of gene expression for antioxidant effects by binding to Vitamin D response elements (VDRE), could reduce the risk of early menopause and shortened reproductive lifespan34. In addition, calculating based on the intake of various antioxidant micronutrients (selenium, zinc, carotenoids, and vitamins A, C, E), CDAI is frequently employed to assess dietary antioxidant levels and has been linked to various health outcomes. Liu et al. reported that postmenopausal women with high CDAI scores often exhibit a lower incidence of atherosclerotic cardiovascular disease17. Moreover, research by He et al. has shown a significant negative correlation between CDAI and biological phenotypic age34, which aligns with our findings that a higher CDAI is associated with a delayed onset of menopause in women. Although the effect size is modest—translating to a 0.09-year delay per CDAI unit—population-wide dietary shifts toward antioxidant-rich patterns could yield clinically meaningful impacts. For example, a 3-unit CDAI increase, achievable through feasible interventions such as daily fruit or vegetable intake, might delay menopause by approximately 3 months. Such delays could reduce early menopause prevalence and attenuate its sequelae, including cardiovascular and osteoporosis risks, at the population level. Additionally, combining dietary improvements with other modifiable factors (e.g. smoking cessation, physical activity) may amplify these benefits.
To date, no study has considered the impact of CDAI on reproductive lifespan. Our results revealed that CDAI, especially the components of Vitamin C and carotenoids, contribute to menopause delay. Vitamin C is a hydrophilic compound that acts as a cofactor for the hydroxylation of proline and lysine during collagen formation. Threshold analysis identified an inflection point at CDAI = 1.05, below which each unit increase in CDAI was associated with a 0.24-year delay in menopause onset. This threshold corresponds to achievable dietary targets, such as: Vitamin C: ≥90 mg/day (e.g., 1 orange + 1 cup broccoli), Carotenoids: ≥6 mg/day (e.g., 1 medium carrot + 1 cup spinach), Zinc: ≥11 mg/day (e.g., 3 oz oysters + 1 serving almonds). These values align with the Dietary Reference Intakes (DRIs) for adults35, emphasizing that modest dietary improvements (e.g., adding 1–2 daily servings of fruits/vegetables) may suffice to reach this threshold. Our findings suggest that for individuals at risk of early menopause, prioritizing antioxidant-rich foods within this range was associated with a longer reproductive lifespan and mitigating health risks.
Available results indicate its multi-directional cellular effect, especially its role in scavenging free radicals. A randomized, triple-blind placebo-controlled clinical trial revealed that Vitamin C combined with Vitamin E could significantly reduce the level of MDA and ROS in patients with endometriosis and improved dyspareunia and severity of pelvic pain36. In female mice, a diet rich in vitamin C can prevent age-related declines in both the quantity and quality of oocytes37.Our findings may further advance clinical studies exploring the antioxidant stress role of vitamin C in ovarian hypofunction. In addition, Carotenoids, another compound in CDAI are 40-carbon isoprenoid molecules that produce the red, yellow, and orange pigmentation found in nature. Various plants, microalgae, bacteria, and fungi are natural sources of carotenoids. Among the 50 kinds of carotenes present in nature, the best known are α-carotene and β-carotene. These natural antioxidants could aid in quenching free radicals produced by complex physiological reactions and, consequently, protect the tissue from oxidative stress, apoptosis, mitochondrial dysfunction, and inflammation38. Clinical studies suggest that carotenoid consumption is associated with lower risk of cardiovascular disease, cancer, and eye disease. This substantial evidence supports its protective effect on female reproductive function due to oxidative stress damage. However, clinical evidence of a direct link between CDAI composition and reproductive lifespan is relatively scarce. Our findings may suggest that for people with risk factors for early menopause, an adequate intake of a diet with a high CDAI, especially within the threshold range we have provided, may be beneficial in prolonging reproductive life and reducing other health problems. Of course, prospective large cohort studies are needed to further verify the scientific nature of this hypothesis.
Although the mechanism by which antioxidant foods prolong reproductive life is still being explored, it may be partly related to improving decreased ovarian function caused by oxidative stress. Oxidative stress occurs when the body’s antioxidant system is depleted owing to an excess of reactive oxygen species (ROS). Exuberant ROS in the ovary can dysregulate the dynamics of the ovarian reserve and/or impair the survival and competence of the oocytes39, thus potentially leading to an earlier onset of menopause and shorten the reproductive lifespan8. Besides, oxidative stress can mediate the onset of inflammation, which could facilitate apoptosis of granulosa cells and oocytes, resulting in the early loss of the ovaries’ role in maintaining menstruation40–42. On the contrary, antioxidant enzymes serve to neutralize ROS production, thereby protecting ovary function. For instance, quercetin, a dietary antioxidant, can enhance ARE binding activity and Nrf-2-mediated transcriptional activity, thus inducing the expression of antioxidant enzymes43, thereby preventing oxidative stress by inhibiting the NF-κB pathway44. Besides, oocytes cultured in media supplemented with quercetin exhibit improved capabilities of maturation and early embryonic development45. Similarly, dietary trace element zinc, which act as a transcriptional regulator of Nrf2, can upregulate downstream antioxidants through nuclear translocation, thereby responding to ROS-induced damage46. Zinc is also a cofactor for one of the most important antioxidant enzymes, Zn-SOD/SOD1, and play a crucial role in female reproduction by scavenging ROS47,48. Collectively, dietary antioxidants can improve ovarian function by mitigating oxidative stress through various mechanisms.
In addition, our research introduces a novel observation that the use of oral contraceptives or female hormones may influence the relationship between the CDAI and reproductive age. The primary components of oral contraceptives and female hormones include estrogens and progestogens. Existing research has demonstrated their antioxidant properties49. Estrogen replacement therapy, for instance, has been confirmed to induce antioxidant and protect various tissues from oxidative stress, including brain, bone and myocardial tissue50,51. Estrogen may amplify the protective effects of dietary antioxidants on ovarian follicular reserve by suppressing mitochondrial ROS generation and enhancing DNA repair mechanisms, such as PARP-1 activation52. Unlike estrogens, progesterone does not possess the characteristic chemical structure of antioxidants, but high levels of progesterone appear to reduce oxidative damage53. Adler et al. confirmed through real-time quantitative PCR that in vitro progesterone treatment significantly increased myeloperoxidase expression in isolated human neutrophils, while significantly reducing NADPH oxidase gene expression54. Progesterone exerts protective effects in various diseases by upregulating γ-aminobutyric acid inhibition, reducing lipid peroxidation and oxidative stress, decreasing the release of inflammatory cytokines, and minimizing apoptosis-induced cell death, thereby promoting cell survival and proliferation53. These mechanisms may create a microenvironment where dietary antioxidants more effectively counteract ovarian oxidative stress. Critically, our observations imply that hormonal supplementation and high-CDAI diets may act synergistically to delay ovarian aging. Notably, hormone replacement therapy is subject to strict indications and contra-indications, and how to combine it with high-CDAI foods to properly avoid premature menopause needs further research and discussion.
Taken together, our study is the first to explore the relationship between CDAI and both the age at menopause and reproductive lifespan, highlighting potential dietary strategies to improve women’s reproductive health. However, its cross-sectional nature introduces several limitations. First, its cross-sectional design precludes establishing causality, as we cannot determine the temporal direction between CDAI and reproductive outcomes (e.g., whether higher antioxidant intake delays menopause or longer reproductive lifespan correlates with healthier diets). Second, self-reported age at menarche and menopause—events often recalled decades later—may introduce recall bias, potentially distorting associations. Third, unadjusted confounders, including hormone replacement therapy (not explicitly incorporated) and broader dietary patterns beyond individual antioxidants, could influence results. Fourth, while the total sample size (4,514) is adequate, subgroup and threshold analyses may lack power due to smaller subsamples, weakening effect estimate precision. Finally, CDAI focused on six antioxidants, excluding others (e.g., polyphenols) that might impact ovarian health. These limitations highlight the need for longitudinal studies with larger cohorts, validated reproductive timing data, comprehensive confounder adjustment, and expanded antioxidant assessment to confirm our findings.
Conclusions
In summary, our cross-sectional analysis of 4514 postmenopausal women from NHANES 1999–2018 reveals that within a certain range, higher CDAI levels are associated witha reduced risk of early menopause, delayed menopause, and prolonged reproductive lifespan. Additionally, these associations appear to be modified by oral contraceptive and female hormone use, with vitamin C and carotenoids emerging as key contributors within the CDAI framework. These findings highlight the role of dietary guidance in improving reproductive health. Notably, the cross-sectional nature of this study limits causal inference. Future research is needed to validate these associations and explore their underlying mechanisms, which would strengthen the potential clinical relevance of dietary antioxidant optimization in the context of female reproductive aging.
Supplementary Information
Below is the link to the electronic supplementary material.
Author contributions
X.Z. and Z.H. conceptualized the study, conducted the research, wrote the main manuscript text, and prepared all figures and tables. N.S. and F.L. performed data validation, formal analysis, and meticulously reviewed and edited the manuscript for accuracy and clarity. Q.Z. secured funding, provided overall research supervision, and contributed to the study design and conceptualization. All authors reviewed and approved the final manuscript.
Funding
This research was funded by the National Natural Science Foundation of China (no. 82474563), the Major Project of Hangzhou Health Commission (no. Z20230103) and Zhejiang Provincial Clinical Research Center for Gynecological and Obstetrical Diseases (no. 2022E50002) to Q.Z; the Zhejiang Provincial Natural Science Foundation of China (no. LQ24H270019), the National Natural Science Foundation of China (no. 82305294), Zhejiang Traditional Medicine and Technology Program, China (no. 2025ZR173), Medical Scientific Research Foundation of Zhejiang Province, China (no. 2025KY158), and Research Project of Zhejiang Chinese Medical University (no. 2024JKZKTS37) to X.X.Z.
Data availability
The datasets analyzed during the current study are available in the NHANES repository at the following links: www.cdc.gov/nchs/nhanes/.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiaoxuan Zhao and Zanche Huang contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets analyzed during the current study are available in the NHANES repository at the following links: www.cdc.gov/nchs/nhanes/.