Dietary minerals, reproductive hormone levels, and sporadic anovulation: associations in healthy women with regular menstrual cycles

Abstract

Although minerals are linked to several reproductive outcomes, it is unknown whether dietary minerals are associated with ovulatory function. We hypothesized that low intakes of minerals would be associated with an increased risk of anovulation. We investigated associations between dietary mineral intake and both reproductive hormones and anovulation in healthy women in the BioCycle Study, which prospectively followed 259 regularly menstruating women, aged 18–44 years who were not taking mineral supplements for 2 menstrual cycles. Intakes of 10 selected minerals were assessed via 24-hour dietary recalls at up to 4 times per cycle in each participant. Estradiol, progesterone, luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone-binding globulin, and testosterone were measured in serum up to 8 times per cycle. We used weighted linear mixed models to evaluate associations between minerals and hormones and generalized linear models for risk of anovulation. Compared to sodium intake ≥1,500mg, sodium intake <1,500mg was associated with higher levels of FSH (21.3%, 95% CI 7.5, 36.9), LH (36.8%, 95% CI 16.5, 60.5), and lower progesterone (−36.9%, 95% CI −56.5, −8.5). Sodium intake <1,500mg (risk ratio [RR] 2.70, 95% confidence interval [CI] 1.00, 7.31) and manganese intake <1.8mg (RR 2.00, 95% CI 1.02, 3.94) were associated with an increased risk of anovulation, compared to higher intakes respectively. Other measured dietary minerals were not associated with ovulatory function. As essential minerals are mostly obtained via diet, our results comparing insufficient to sufficient levels highlight the need for future research on dietary nutrients and their associations with ovulatory cycles.

Introduction

Minerals are inorganic elements that are essential for normal physiologic function and are widely involved in a broad range of processes including cellular metabolism and anti-oxidant and anti-inflammatory defenses ^{(1, 2)}. They play critical roles in enzyme activity as cofactors or catalysts ^{(3, 4)}, and contribute to protein synthesis ⁽⁵⁾ and the regulation of gene expression ⁽⁶⁾. Mineral homeostasis in the body system is tightly regulated and deficiencies in essential minerals may in turn impact a wide range of physiological processes ^{(7, 8)}.

There is ample evidence showing that minerals are important for reproductive function in women. In particular, minerals may be associated with ovulation, as demonstrated by induced ovulation upon administration of copper (Cu) in animals following stimulation of the hypothalamus ⁽⁹⁾, or by acting as antioxidants in controlling oxidative stress which has been shown to promote ovulation ⁽¹⁰⁾. In maturing mammalian oocytes, zinc (Zn) accumulates as oocytes grow and regulates meiosis ^{(11, 12)}, and as such may also be important for reproductive health. Higher levels of Cu, Zn ⁽¹³⁾, calcium (Ca), and manganese (Mn) ⁽¹⁴⁾ were measured in women with polycystic ovary syndrome (PCOS) and an inverse association between iron (Fe) intake and ovulatory infertility was suggested ⁽¹⁵⁾, all pointing to possible relations between essential minerals and reproductive health outcomes.

To date, most studies on minerals and reproductive function, particularly reproductive hormones, have been done using serum mineral concentrations ^{(16, 17, 18)} or animal models ^{(19, 20)}. Although diet is a major source of essential minerals in the general population, there are very few studies using dietary assessments to explore associations between minerals and reproductive function. Therefore, our objective was to investigate associations between the dietary intakes of 10 minerals and two primary outcomes including 1) reproductive hormones and 2) anovulation in healthy, regularly menstruating women who were not taking dietary supplements. We hypothesized that intake of dietary minerals below the recommended levels would be associated with changes in reproductive hormone concentrations and an increased risk of anovulation. While exploratory, our study provides a comprehensive examination of the influence of dietary minerals among healthy women.

Materials and Methods

Study design and sample collection

The BioCycle Study is a prospective cohort study that recruited 259 healthy regularly menstruating women from western New York in 2005–2007. Details of the study design and sample collection are described elsewhere ⁽²¹⁾. In brief, women aged 18–44 years with self-reported menstrual cycle lengths of 21–35 days for at least six months prior to recruitment and self-reported body mass index (BMI) of >18 or <35 kg/m² at screening were eligible for the study. Women were excluded if they used hormonal contraceptives in the past three months prior to screening, were pregnant or breastfeeding in the past six months, had a history of ovulatory disorders or uterine abnormalities, or were taking vitamin or mineral supplements during the study period. Participants provided information on age, race, lifestyle, and reproductive and health history via questionnaires at baseline. Each participant also completed the International Physical Activity Questionnaire (IPAQ) long form 2002, and we estimated their physical activity as high, moderate, and low based on standard IPAQ cutoffs. Trained research staff measured weight and height according to standardized protocols at baseline.

Each participant provided fasting blood specimens up to eight times per cycle during her visits at specific phases of the menstrual cycle, including menstruation, mid- and late follicular phase, luteinizing hormone (LH) surge, estimated day of ovulation, and early-, mid-, and late luteal phase. Fertility monitors (Clearblue Easy Fertility Monitor; Inverness Medical, Waltham, MA) and personal cycle length histories were used to determine the timing of visits ⁽²²⁾. In total, we collected data for two cycles from 250 women and one cycle from nine women; 94% of the participants completed at least seven clinic visits per cycle. The University at Buffalo Health Sciences Institutional Review Board (IRB) served as the IRB designated by the National Institutes of Health under a reliance agreement and approved the study. All study participants provided written informed consent.

Dietary assessment

We obtained dietary data via 24-hour dietary recalls completed by study participants when they visited the clinic during the menstruation, mid-follicular, ovulation, and mid-luteal phases of each cycle. Approximately 87% of participants completed four dietary recalls per cycle; 13% of women completed three recalls per cycle and 0.4% of women completed only two. We used the Nutrition Data System for Research software version 2005 (the Nutrition Coordinating Center, University Minnesota, Minneapolis, MN) to estimate intakes of dietary minerals, including calcium (Ca, mg), phosphorus (P, mg), magnesium (Mg, mg), iron (Fe, mg), zinc (Zn, mg), copper (Cu, mg), manganese (Mn, mg), selenium (Se, Mg), sodium (Na, mg), and potassium (K, mg) from food and beverage intakes. Na intake captures amounts that were naturally occurring in foods and those that were added during food processing; however, it does not include Na from any added table salt. We categorized daily intakes of dietary minerals by their recommended daily allowance (RDA). The RDAs for each mineral are: 1,000 mg for Ca, 700 mg for P, 310 mg for Mg, 18 mg for Fe, 8 mg for Zn, 0.9 mg for Cu, 1.8 mg for Mn, 55 Mg for Se, and 1,500 mg for Na ⁽²³⁾. Mean levels of K intake were below the RDA (4,700 mg) in all of our participants, as such K intake was categorized by the US average of 2,227 mg per day ⁽²⁴⁾. As intakes were not observed to change over the cycle, except for Zn which showed minimal variability ⁽²⁵⁾, we averaged the intake of dietary minerals per cycle for these analyses. Total energy intake was also averaged per cycle given that we did not observe changes across the cycle ⁽²⁵⁾, though another study has noted fluctuations ⁽²⁶⁾.

Reproductive hormone measurement

Details of hormonal analyses were previously reported ⁽²⁷⁾. Concentrations of total estradiol, follicle stimulating hormone (FSH), LH, progesterone, and sex hormone-binding globulin (SHBG) were measured using solid-phase competitive chemiluminescent enzymatic immunoassays (Specialty Laboratories Inc., Valencia, CA) on a DPC Immulite 2000 analyzer (Siemens Medical Solutions Diagnostics, Deerfield, IL) at the Kaleida Health Center for Laboratory Medicine, Buffalo, NY. Total testosterone concentrations (ng/dL) were measured by liquid chromatography/tandem mass spectrometry employing a Shimadzu Prominence Liquid Chromatograph (Shimadzu Scientific Instruments, Inc., Columbia, MD) with an ABSceix 5500 tandem mass spectrometer (AB SCIEX, Framingham, MA) at the University of Minnesota, Minneapolis, MN. Increased sensitivity was obtained using Mobile Phase B (100% acetonitrile) with a low standard of 4 ng/dL added to the standard curve. Free (i.e., bioavailable) estradiol and testosterone and free androgen index were calculated based on standardized methods ⁽²⁸⁾. The coefficient of variation (CV) was <10% for estradiol and SHBG, <5% for LH and FSH, <14% for progesterone, and <7% for total testosterone. We defined sporadic anovulatory cycles as cycles with peak progesterone concentrations ≤5 ng/mL and no observed serum LH peak during the mid or late luteal phase cycle visit (in the event that timing of progesterone measurement was too early) ⁽²⁹⁾. In total, 42 of the 509 cycles (8.3%) in the study were considered anovulatory.

Statistical analysis

Distributions of demographic variables were characterized by intakes of dietary minerals below or above the RDA or the US average intake for K. We used Fisher’s exact test, Chi-square tests, or Student’s t-test to compare the demographic variables as appropriate. We calculated Pearson correlation coefficients among person-averaged dietary mineral intakes.

Associations between dietary minerals and serum reproductive hormones were assessed by weighted linear mixed models with random intercepts. Cycle-averaged dietary minerals were evaluated in quintiles (comparing lower intakes to the highest intake quintile) and as dichotomized by the RDA or US average. Models were adjusted for age, BMI, race, physical activity, Mediterranean diet score, intakes of total energy, fiber, and protein, and other hormone concentrations. Inverse probability weights were used to account for the complex feedback mechanisms between changing reproductive hormones levels over the menstrual cycle ^{(30, 31)}. The results are presented as percent difference in hormone levels with 95% confidence intervals (CIs). We adjusted all models of dietary mineral intake and reproductive hormones for the false discovery rate using the Benjamini-Hochberg procedure within each dietary mineral group (i.e., Ca, P, Mg, etc.) to account for multiple comparisons.

We used Poisson regression with robust error variance estimates to investigate risk of sporadic anovulation with dietary mineral intakes by quintiles and RDA. All sporadic anovulation models were adjusted for age, BMI, race, physical activity, Mediterranean diet score, and intakes of energy, fiber, and protein. We report estimates as risk ratios (RR) and 95% CIs. SAS version 9.4 (SAS Institute, Cary, NC, USA) was used for all statistical analyses.

Results

Average daily intake of minerals, including P, Cu, Mn, Se, and Na, were above the RDA in more than half of our participants, whereas intakes of Ca, Mg, and Fe above the RDA were observed in only about 10% of women (Table 1). The mean age (± standard deviation) of our participants was significantly higher among women whose intakes of dietary P (27.7 ± 8.3 years) and Zn (28.8 ± 8.7 years) were greater than the RDA and whose K was greater than the US average (30.0 ± 8.8 years), compared to those who consumed less (24.8 ± 7.1 for P, 25.9 ± 7.5 for Zn, and 26.4 ± 7.8 for K). Intakes of dietary Ca, P, Mg, Zn, Cu, and K were significantly different by race. Dietary minerals assessed in our study were all significantly correlated to each other (P<0.0001; Table 2). The highest correlations were detected between Mg and Mn (r = 0.85), whereas the least correlated minerals were Ca and Cu (r = 0.33), and Zn and Mn (r = 0.33).

Table 1.

Characteristics of the study cohort by dietary mineral intakes less or greater than daily recommended dietary allowance.

	Calcium, Ca (mg)		Phosphorus, P (mg)		Magnesium, Mg (mg)		Iron, Fe (mg)		Zinc, Zn (mg)
Demographics (%)	<1,000	≥1,000	<700	≥700	<310	≥310	<18	≥18	<8	≥8
N (%)	226(87.3)	33(12.7)	36(13.9)	223(86.1)	231(89.2)	28(10.8)	233(90.0)	26(10.0)	136(52.5)	123(47.5)
Age, years: mean ± SD	27.0±8.1	29.6±8.7	24.8±7.1	27.7±8.3	27.2±8.1	27.7±9.2	27.1±8.0	28.9±9.6	25.9±7.5	28.8±8.7
BMI, kg/m2: mean ± SD	24.0±3.8	24.6±4.3	24.6±4.0	24.0±3.8	24.2±3.8	23.4±4.3	24.1±3.9	24.2±3.5	23.8±3.6	24.3±4.1
Race
White	55.3	87.9	22.2	65.5	56.3	85.7	57.9	73.1	45.6	74.8
Black	22.6	0.0	41.7	16.1	20.8	10.7	21.0	7.7	25.0	13.8
Other	22.1	12.1	36.1	18.4	22.9	3.6	21.0	19.2	29.4	11.4
Physical Activity
Low	10.6	3.0	11.1	9.4	10.0	7.1	10.3	3.9	11.8	7.3
Moderate	35.0	39.4	44.4	34.1	34.6	42.9	34.8	42.3	39.7	30.9
High	54.4	57.6	44.4	56.5	55.4	50.0	54.9	53.9	48.5	61.8
≤ High school education	13.3	9.1	16.7	12.1	13.9	3.6	13.3	7.7	11.0	14.6
Current smoker	4.4	0.0	0.0	4.5	4.3	0.0	3.9	3.9	2.9	4.9
Married	23.9	36.4	5.6	28.7	24.2	35.7	25.8	23.1	22.8	28.5
Nulliparous	74.3	57.6	83.3	70.4	72.7	67.9	72.1	73.1	80.9	62.6
Past OC Use	52.7	63.6	27.8	58.3	53.7	57.1	53.7	57.7	49.3	59.4
N (%)	(39.0)	(61.0)	(15.4)	(84.6)	(6.2)	(93.8)	(1.9)	(98.1)	(74.9)	(25.1)
Age, years: mean ± SD	26.8±8.4	27.6±8.1	25.8±8.2	27.6±8.2	26.2±7.1	27.4±8.3	25±5.1	27.3±8.3	26.4±7.8	30.0±8.8
BMI, kg/m2: mean ± SD	24.3±3.8	23.9±3.9	24.6±3.9	24.0±3.9	24.3±4.2	24.1±3.8	24±4.4	24.1±3.9	24±3.8	24±4.1
Race
White	42.6	70.3	50.0	61.2	50.0	60.1	40.0	59.8	51.0	84.6
Black	34.7	10.1	32.5	17.4	18.8	19.8	20.0	19.7	25.3	3.1
Other	22.8	19.6	17.5	21.5	31.3	20.2	40.0	20.5	23.7	12.3
Physical Activity
Low	14.9	6.3	17.5	8.2	6.3	9.9	0.0	9.8	11.3	4.6
Moderate	32.7	37.3	30.0	36.5	50.0	34.6	20.0	35.8	35.1	36.9
High	52.5	56.3	52.5	55.3	43.8	55.6	80.0	54.3	53.6	58.5
≤ High school education	17.8	9.5	12.5	12.8	12.5	12.8	20.0	12.6	16.0	3.1
Current smoker	2.0	5.1	0.0	4.6	0.0	4.1	0.0	3.9	3.6	4.6
Married	19.8	29.1	17.5	26.9	12.5	26.3	20.0	25.6	21.1	38.5
Nulliparous	75.3	70.3	75.0	71.7	75.0	72.0	80.0	72.1	75.8	61.5
Past OC Use	47.5	58.2	37.5	57.1	37.5	55.1	60.0	53.9	49.5	67.7

Note: Cycle-averaged daily intake of dietary potassium was categorized by the US average intake (e.g., 2,227 mg). P-values for continuous variables were calculated using Student’s t-test, and for categorical variables using Fisher’s exact test. Statistically significant differences are in bold (p<0.05).

BMI, body mass index; OC, oral contraceptive; SD, standard deviation.

Table 2.

Correlations among average dietary mineral intakes across both cycles (n=259).

	Calcium, Ca	Phosphorus, P	Magnesium, Mg	Iron, Fe	Zinc, Zn	Copper, Cu	Manganese, Mn	Selenium, Se	Sodium, Na	Potassium, K
Calcium	1.00	0.81	0.57	0.51	0.41	0.33	0.38	0.38	0.47	0.60
Phosphorus		1.00	0.78	0.57	0.48	0.52	0.56	0.70	0.71	0.80
Magnesium			1.00	0.61	0.42	0.60	0.85	0.51	0.47	0.83
Iron				1.00	0.59	0.44	0.58	0.46	0.51	0.52
Zinc					1.00	0.48	0.33	0.36	0.38	0.42
Copper						1.00	0.48	0.34	0.38	0.56
Manganese							1.00	0.41	0.34	0.58
Selenium								1.00	0.70	0.51
Sodium									1.00	0.57
Potassium										1.00

Note: All were statistically significant (P<0.0001).

Compared to Ca intake above the RDA (≥1,000 mg), intake of Ca <RDA was associated with lower progesterone concentrations (−20.0% difference, 95% CI -34.9, –1.9; Table 3), adjusted for age, BMI, race, physical activity, intakes of energy, Mediterranean diet score, fiber, and protein, and other hormones. Intake of Mg below the RDA (<310 mg) was inversely associated with testosterone (−4.7% difference, 95% CI −9.2, 0.0), relative to above the RDA. However, these results did not persist after adjusting for false discovery rate. We found that intake of Na below the RDA (<1,500 mg) was associated with higher concentrations of FSH (21.3% change, 95% CI 7.5, 36.9) and LH (36.8% change, 95% CI 16.5, 60.5), and lower concentrations of progesterone (−36.9% change, 95% CI −56.5, −8.5), compared to Na intake above the RDA (≥1,500 mg). Stratified by the US average intake, we detected inverse associations between K intake <2,227 mg and free androgen index (5.7% change, 95% CI −0.1, 11.9), relative to intake of K ≥2,227 mg, though the result was no longer significant after adjusting for false discovery rate. Compared to the highest quintile, the lowest quintiles of Fe and Zn were associated with lower progesterone (−36.4% difference, 95% CI −53.4, −13.4) and LH (−14.0% difference, 95% CI −24.1, −2.6), respectively (Supplemental Table 1).

Table 3.

Associations between dietary mineral intakes and reproductive hormone concentrations by daily recommended dietary allowance (RDA).

			<RDA vs. ≥RDA [ref]
	<RDA	≥RDA	%Difference	95% CI		Raw P-value	P-value adjusted for false discovery rate
Calcium, Ca (mg)	150.0–999.1	1005.3–1963.7
Estradiol, pg/mL			−3.4	−10.8	4.7	0.397	0.921
Free Estradiol, pg/mL			−4.0	−11.2	3.8	0.301	0.921
FSH, mIU/mL			0.6	−5.9	7.7	0.855	0.962
LH, ng/mL			−2.3	−10.5	6.8	0.612	0.921
Progesterone, ng/mL			−20.1	−34.9	−1.9	0.032	0.288
SHBG, nmol/L			1.4	−2.5	5.6	0.484	0.921
Testosterone, ng/dL			0.0	−3.9	4.0	0.994	0.994
Free testosterone, ng/dL			−0.5	−4.6	3.8	0.818	0.962
Free androgen index			−1.6	−7.5	4.7	0.614	0.921
Phosphorus, P (mg)	296.3–698.3	700.1–1843.2
Estradiol, pg/mL			0.5	−8.2	10.1	0.907	0.961
Free Estradiol, pg/mL			0.2	−8.3	9.5	0.961	0.961
FSH, mIU/mL			5.5	−2.1	13.7	0.163	0.511
LH, ng/mL			2.5	−7.0	13.1	0.616	0.924
Progesterone, ng/mL			−1.0	−21.9	25.4	0.933	0.961
SHBG, nmol/L			2.9	−2.4	8.5	0.284	0.511
Testosterone, ng/dL			−2.7	−6.9	1.8	0.233	0.511
Free testosterone, ng/dL			−2.8	−7.3	1.9	0.233	0.511
Free androgen index			−4.1	−10.6	2.8	0.239	0.511
Magnesium, Mg (mg)	65.1–307.9	310.5–539.3
Estradiol, pg/mL			−2.7	−12.2	7.9	0.605	0.908
Free Estradiol, pg/mL			−1.3	−10.8	9.3	0.805	0.969
FSH, mIU/mL			−5.1	−13.0	3.4	0.229	0.515
LH, ng/mL			5.3	−6.0	17.9	0.372	0.670
Progesterone, ng/mL			0.5	−23.4	32.0	0.969	0.969
SHBG, nmol/L			−4.5	−9.9	1.2	0.117	0.515
Testosterone, ng/dL			−4.7	−9.2	0.0	0.049	0.441
Free testosterone, ng/dL			−3.4	−8.3	1.7	0.192	0.515
Free androgen index			−0.6	−8.1	7.5	0.881	0.969
Iron, Fe (mg)	3.9–18.0	18.1–52.4
Estradiol, pg/mL			−5.0	−13.2	4.0	0.265	0.646
Free Estradiol, pg/mL			−3.9	−12.0	4.9	0.372	0.646
FSH, mIU/mL			−2.0	−9.1	5.7	0.601	0.646
LH, ng/mL			−3.7	−12.7	6.2	0.445	0.646
Progesterone, ng/mL			−12.9	−31.4	10.6	0.257	0.646
SHBG, nmol/L			−1.2	−5.6	3.4	0.595	0.646
Testosterone, ng/dL			−2.1	−6.2	2.1	0.324	0.646
Free testosterone, ng/dL			−1.9	−6.3	2.7	0.419	0.646
Free androgen index			−1.6	−8.2	5.4	0.646	0.646
Zinc, Zn (mg)	2.9–8.0	8.0–113.2
Estradiol, pg/mL			3.6	−3.1	10.8	0.297	0.828
Free Estradiol, pg/mL			4.5	−2.1	11.5	0.184	0.828
FSH, mIU/mL			2.1	−3.4	8.0	0.460	0.828
LH, ng/mL			−2.9	−9.7	4.5	0.431	0.828
Progesterone, ng/mL			−0.2	−16.3	19.1	0.987	0.987
SHBG, nmol/L			2.2	−1.6	6.2	0.264	0.828
Testosterone, ng/dL			0.7	−2.5	4.0	0.659	0.867
Free testosterone, ng/dL			0.1	−3.3	3.6	0.972	0.987
Free androgen index			−1.1	−6.1	4.2	0.674	0.867
Copper, Cu (mg)	0.3–0.9	0.9–12.3
Estradiol, pg/mL			−4.1	−10.4	2.5	0.217	0.663
Free Estradiol, pg/mL			−4.0	−10.2	2.5	0.221	0.663
FSH, mIU/mL			4.7	−1.0	10.8	0.109	0.663
LH, ng/mL			3.4	−4.0	11.4	0.377	0.729
Progesterone, ng/mL			−3.6	−19.5	15.3	0.684	0.843
SHBG, nmol/L			−0.6	−4.4	3.3	0.749	0.843
Testosterone, ng/dL			−1.3	−4.5	1.9	0.405	0.729
Free testosterone, ng/dL			−0.9	−4.2	2.6	0.614	0.843
Free androgen index			0.2	−4.9	5.5	0.950	0.950
Manganese, Mn (mg)	0.4–1.8	1.8–10.6
Estradiol, pg/mL			4.8	−3.3	13.6	0.251	0.619
Free Estradiol, pg/mL			3.7	−4.0	12.1	0.355	0.619
FSH, mIU/mL			1.8	−4.8	8.8	0.608	0.619
LH, ng/mL			3.1	−5.5	12.5	0.488	0.619
Progesterone, ng/mL			−5.1	−22.9	16.7	0.619	0.619
SHBG, nmol/L			1.4	−2.5	5.6	0.484	0.619
Testosterone, ng/dL			−3.0	−6.8	1.0	0.139	0.619
Free testosterone, ng/dL			−3.3	−7.4	0.9	0.118	0.619
Free androgen index			−2.8	−8.8	3.6	0.380	0.619
Selenium, Se (Mg)	33.0–54.9	55.2–211.5
Estradiol, pg/mL			−4.2	−13.9	6.7	0.437	0.919
Free Estradiol, pg/mL			−2.4	−12.1	8.3	0.644	0.919
FSH, mIU/mL			6.1	−2.9	16.0	0.191	0.825
LH, ng/mL			8.7	−3.3	22.2	0.163	0.825
Progesterone, ng/mL			−14.5	−35.6	13.3	0.275	0.825
SHBG, nmol/L			0.3	−5.9	6.8	0.931	0.972
Testosterone, ng/dL			−1.3	−6.3	4.0	0.620	0.919
Free testosterone, ng/dL			−1.0	−6.4	4.7	0.715	0.919
Free androgen index			−0.2	−8.2	8.6	0.972	0.972
Sodium, Na (mg)	931.2–1462.1	1561.0–6553.3
Estradiol, pg/mL			−3.2	−16.4	12.1	0.667	0.750
Free Estradiol, pg/mL			−3.1	−16.1	11.8	0.663	0.750
FSH, mIU/mL			21.3	7.5	36.9	0.002	0.009
LH, ng/mL			36.8	16.5	60.5	0.0001	<.0001
Progesterone, ng/mL			−36.9	−56.5	−8.5	0.015	0.045
SHBG, nmol/L			−2.4	−10.5	6.5	0.585	0.750
Testosterone, ng/dL			−3.3	−10.0	4.0	0.365	0.750
Free testosterone, ng/dL			−2.8	−10.0	5.1	0.479	0.750
Free androgen index			−0.2	−11.2	12.2	0.976	0.976
Potassium, K (mg)	493.8–2222.3	2230.9–4242.5
Estradiol, pg/mL			−1.2	−8.4	6.6	0.759	0.854
Free Estradiol, pg/mL			0.5	−6.7	8.2	0.897	0.897
FSH, mIU/mL			−4.0	−9.8	2.2	0.202	0.455
LH, ng/mL			−2.1	−9.8	6.3	0.616	0.792
Progesterone, ng/mL			8.3	−11.2	32.1	0.430	0.645
SHBG, nmol/L			−2.5	−6.6	1.7	0.262	0.472
Testosterone, ng/dL			2.5	−1.0	6.2	0.167	0.455
Free testosterone, ng/dL			3.5	−0.3	7.5	0.073	0.329
Free androgen index			5.7	−0.1	11.9	0.055	0.329

Note: Models were adjusted for age, body mass index, race, physical activity, Mediterranean diet score, intakes of energy, fiber, and protein, and other hormones. For progesterone, only measurements during the luteal phase were included. Intakes of potassium were categorized by the US average intakes (e.g., 2,227 mg/day). Statistically significant estimates and intervals are in bold.

CI, confidence interval; FSH, follicle-stimulating hormone; LH, luteinizing hormone; %Difference, percent difference in hormone concentrations; SHBG, sex hormone-binding globulin.

Compared to intakes of minerals above the RDA, intakes of Mn <1.8 mg (RR 2.00, 95% CI 1.02, 3.94) and Na <1,500 mg (RR 2.70, 95% CI 1.00, 7.31) were associated with increased risk of sporadic anovulation, adjusted for age, BMI, race, physical activity, Mediterranean diet score, and intakes of energy, fiber, and protein (Table 4). Intakes of Se <55 Mg were associated with increased risk for sporadic anovulation (RR 2.66, 95% CI 0.96, 7.36), relative to Se intake ≥55 Mg. In general, no significant associations were detected when dietary minerals were assessed in quintiles (Supplemental Table 2).

Table 4.

Dietary mineral intake by recommended dietary allowance (RDA) and risk of sporadic anovulation.

	≥RDA (reference)	<RDA
Dietary minerals (/day)		RR	95% CI
Calcium, Ca (<1,000 mg)		1.82	0.62	5.34
Phosphorus, P (<700 mg)		1.99	0.72	4.96
Magnesium, Mg (<310 mg)		1.58	0.46	5.39
Iron, Fe (<18 mg)		1.39	0.58	3.37
Zinc, Zn (< 8mg)		0.94	0.48	1.85
Copper, Cu (<0.9 mg)		1.12	0.58	2.17
Manganese, Mn (<1.8 mg)		2.00	1.02	3.94
Selenium, Se (<55 Mg)		2.66	0.96	7.36
Sodium, Na (<1,500 mg)		2.70	1.00	7.31
Potassium, K (<2,227 mg)		1.13	0.48	2.64

Note: All models were adjusted for age, body mass index, race, physical activity, Mediterranean diet score, and intakes of energy, fiber, and protein. Intakes of dietary potassium were categorized by the US average intakes (e.g., 2,227 mg/day). Statistically significant estimates and intervals are in bold.

CI, confidence interval; RR, risk ratio.

Discussion

Overall, our data suggest associations between intakes of specific dietary minerals, particularly Na intake, and reproductive hormones in normally menstruating women of reproductive age. Our data also indicate associations between insufficient intakes of Mn and Na and an increased risk of sporadic anovulation, though the majority of dietary minerals that we evaluated were not associated with the risk of anovulation. As our assessed minerals are abundant in easily accessible food items, our data suggest that specific dietary factors may influence reproductive hormones and ovulation among healthy women.

We observed associations between dietary Na intake below the RDA and higher FSH and LH concentrations, lower progesterone levels, and an increased risk of sporadic anovulation. High intake of Na has been associated with increased levels of steroid hormones, such as glucocorticoids, in 370 adults ⁽³²⁾; however, studies evaluating the potential role of dietary Na on changes of other hormone levels are scarce, limiting comparison with our work. One experimental study conducted in male rats reported increased levels of FSH and testosterone and decreased levels of LH in high-salt fed rats compared to controls fed a low-salt diet ⁽³³⁾. Sufficient levels of Na intake might be important for mammalian reproduction, as suggested in an animal study which detected significantly lower mating and fewer litters in mice fed low-Na foods, compared to mice fed high-Na foods ⁽³⁴⁾. Specific biological mechanisms linking Na intake and ovulatory function are limited, though could be perhaps similar to a relationship between Na and inflammation. Positive associations between Na and inflammation were suggested in a cross-sectional analysis of 1,597 individuals where 24-h Na excretion was associated with increases in serum C-reactive protein concentration, a global marker of inflammation ⁽³⁵⁾. As ovulation is considered an acute inflammatory process ⁽³⁶⁾, our finding on the association between Na intake below the RDA and increased risk of anovulation could be in part related to this mechanism. Nonetheless, because Na intake assessed in our study does not reflect Na from salt added at the table, exposure misclassification is possible. Despite the fact that Na is an essential mineral, excessive consumption is related to adverse health conditions such as high blood pressure and cardiovascular disease ⁽³⁷⁾, and thus our result should be interpreted carefully.

An association between Mn intake below the RDA and an increased risk for sporadic anovulation was indicated in our study, although we did not detect any associated changes in hormones. The impact of Mn on women’s reproductive health has been investigated in relation to pubertal development in prior work. Specifically, in animal studies using prepubertal female rats, a significant increase in serum LH levels was detected upon MnCl₂ treatment ^{(17, 38)}. Given that Mn is abundant in easily obtainable foods (e.g., teas, nuts, legumes, and whole grains), further investigation into the particular sources of dietary Mn and improved ovulatory function could be beneficial for reproductive age women.

Though our data do not support hormonal differences in relation to dietary Se, intake of Se below the RDA was associated with an increased risk for sporadic anovulation. Due to its antioxidant properties, greater attention has been given to Se in relation to fertility. A significantly higher level of glutathione peroxidase activity, an enzyme containing Se, was observed in menstruating women compared to women without regular menstruation ⁽³⁹⁾ and plasma Se was related to estradiol concentrations across the menstrual cycle ⁽⁴⁰⁾. Additionally, Se was positively associated with progesterone concentrations in adolescent girls, a marker of ovulatory function, in research specifically investigating Se status, sex hormone secretion, and thyroid metabolism ⁽⁴¹⁾. Combined with previous studies using Se measured in blood, our data using dietary Se may also perhaps underscore a potential role of Se in ovulatory function in healthy women.

Our data suggested an association between dietary Ca and progesterone, though the result was no longer significant after adjusting for false discovery rate. Nevertheless, this association is in line with an experimental study, which demonstrated an association between Ca and progesterone in ovarian follicle cells ⁽⁴²⁾. Although we did not detect any associations between Ca and estradiol, prior studies reported a relation between Ca and estrogen metabolism in women ^{(43, 44, 45)}, suggesting a possible interaction between Ca and estrogen and link with other estrogen-dependent conditions, such as endometriosis ⁽⁴⁶⁾. We recently reported no association between Ca consumption via dairy intake and sporadic anovulation ⁽⁴⁷⁾ and our findings regarding overall dietary Ca intake in this analysis were similar. In a separate analysis, we did not detect any significant changes in Ca measured in diet across the cycle overall and by anovulation status. Therefore, our null results might be due to the fact that any changes in dietary Ca over the cycle are very small and are not subsequently associated with reproductive hormones and ovulation measured in our study.

We further observed that insufficient dietary intakes of Mg were associated with lower testosterone levels, though the association did not remain after adjustment for multiple comparisons. Influence of Mg on hormonal change has been suggested in an experimental study that showed that changes in Mg status were associated with changes in testosterone and SHBG ⁽⁴⁸⁾. Previously, a study of 25 post-menopausal women and 15 pre-menopausal women reported no association between serum Mg concentrations and testosterone, though an inverse association with estrogen was detected ⁽¹⁶⁾. Our measurement of Mg via dietary intake is different from the serum measurement, as the latter may reflect overall Mg status in the body system. Still, our data suggest the importance of Mg in maintaining the level of bioavailable testosterone for reproductive age women.

Consumption of K was lower than the RDA for all participants in our study, which is consistent with the US general population, where average intakes of dietary K are substantially lower than the RDA (4,700 mg) among both men and women ⁽²³⁾. Stratifying intake by the US average, we found that intake of K below the US average was associated with higher testosterone, free testosterone, and free androgen index, though the results were no longer significant after adjusting for false discovery rate. In an experimental study, K demonstrated a regulatory role in plasma testosterone levels ⁽¹⁹⁾, potentially supporting our observation between K and androgen levels. Though we observed associations with testosterone levels with consumption of K, this did not translate into associations with the risk of anovulation in healthy regularly menstruating women.

Our study has several limitations. In an animal study, a role of reproductive hormones on Na consumption has been suggested, possibly through the sympathetic nervous system which could be influenced by estradiol and drive Na intake in turn ⁽⁴⁹⁾. Therefore, it is possible that the intakes of certain dietary minerals, particularly Na, could be affected by hormonal changes specific to cycle phase. However, this might be of less concern as we employed longitudinal modeling with inverse probability weighting to account for changing levels of endogenous reproductive hormones over the menstrual cycle, and we did not observe changes in intakes over the cycle. As the women in our study were instructed not to take any mineral supplements or undergo any diet regimes during the study period ⁽²¹⁾, our data reflect the most common sources of minerals in a regular diet and the results are only generalizable to healthy regularly menstruating women not taking supplements. However, there are several strengths in our study as well. We used 24-hour dietary recalls collected multiple times throughout the menstrual cycles to estimate usual intakes. This approach was used to reduce potential measurement error ⁽⁵⁰⁾, though more recalls may have been necessary to more adequately assess intake for specific minerals such as Ca. Our data also capture a broad spectrum of the essential minerals via diet and there is greater public health utility and easy interpretation of measures of daily mineral consumption.

Overall, our analyses suggest that intakes of specific dietary minerals, particularly Na and Mn, may influence reproductive hormone concentrations and ovulatory function in premenopausal women with regular menstrual cycles. Minerals are mostly obtained via diet in the general population and a range of whole food diets will likely provide adequate micronutrients to support normal ovulatory function. Given that essential minerals are abundant in easily accessible food items, our data suggest that dietary factors likely have important influences on ovulation and fertility. Moreover, the reproductive hormones investigated in our study affect not only women’s reproductive health, but general health across the lifespan. Thus, the associations with dietary minerals suggested in our study may be also of significance for other health outcomes related to reproductive organs or hormone levels.