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Katherine VanHise, Jessica L Chan, Sahar Wertheimer, Roy G Handelsman, Ekaterina Clark, Rae Buttle, Erica T Wang, Ricardo Azziz, Margareta D Pisarska, Regional Variation in Hormonal and Metabolic Parameters of White and Black Women With PCOS in the United States, The Journal of Clinical Endocrinology & Metabolism, Volume 108, Issue 3, March 2023, Pages 706–712, https://doi.org/10.1210/clinem/dgac515
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Abstract
Ongoing research is needed to determine geo-epidemiologic differences of polycystic ovary syndrome (PCOS).
Determine hormonal and metabolic parameters of women with PCOS in 2 environments.
Prospective cohort study.
Tertiary-care based specialty clinics in Alabama and California.
A total of 1610 women with PCOS by National Institutes of Health Criteria from 1987 to 2010.
Interview, physical examination, laboratory studies.
Demographic data, menstrual cycle history, and hormonal and metabolic parameters were collected. Hirsutism was defined as modified Ferriman-Gallwey scores ≥4. Androgen values greater than laboratory reference ranges or >95th percentile of all values were considered elevated (hyperandrogenemia). Metabolic parameters included body mass index (BMI), waist-hip-ratio (WHR), glucose tolerance test, and homeostatic model assessment for insulin resistance (HOMA-IR) scores.
Alabama women with PCOS were younger with a higher BMI. After adjustment for age and BMI, Alabama women with PCOS were more likely hirsute (adjusted odds ratio [aOR], 1.8; 95% CI, 1.4-2.4; P < 0.001), with elevated HOMA-IR scores (adjusted beta coefficient 3.6; 95% CI, 1.61-5.5; P < 0.001). California women with PCOS were more likely to have hyperandrogenemia (free testosterone aOR, 0.14; 95% CI, 0.11-0.18; P < 0.001; total testosterone aOR, 0.41; 95% CI, 0.33-0.51). Results were similar when stratified by White race. In Black women with PCOS, BMI and WHR did not differ between locations, yet differences in androgen profiles and metabolic dysfunction remained.
Alabama women with PCOS, regardless of Black or White race, were more likely hirsute with metabolic dysfunction, whereas California women with PCOS were more likely to demonstrate hyperandrogenemia, highlighting potential environmental impacts on PCOS.
Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women and female adolescents worldwide. The hallmark features of the disorder include ovulatory dysfunction, hyperandrogenism, and polycystic ovarian morphology. These criteria in various combinations are required to establish a diagnosis of PCOS. The most recent 2018 International Guidelines endorse using modified 2003 Rotterdam criteria (requiring at least 2 of the following: ovulatory dysfunction, hyperandrogenism, and/or polycystic ovarian morphology) for establishing the diagnosis of PCOS after exclusion of related disorders (1).
Several cross-sectional studies have examined global variations in phenotypic presentation and metabolic dysfunction associated with PCOS (2–4). Results of these studies show differences in the prevalence and degree of hirsutism and hyperandrogenemia among women with PCOS residing in different countries. For example, hirsutism is more prevalent among Middle Eastern, Mediterranean, and Indian women with PCOS (3–5). Hyperandrogenemia is less common and/or less severe in Asian, Norwegian, and Finnish women with PCOS (3, 5). Additionally, there are important global differences in metabolic risk associated with PCOS. South Asian, African, and Hispanic women with PCOS are at the highest risk of developing metabolic syndrome and insulin resistance (2, 3, 5). The 2012 Amsterdam European Society of Human Reproduction and Embryology/American Society of Reproductive Medicine (ASRM) PCOS Workshop summarized these findings in their consensus statement, and additionally suggested an area of ongoing investigation to identify the “best management for manifestations by ethnicity, and the role of genetic and environmental factors to explain ethnic variances (5).”
An effective way to assess the impact of the environment on PCOS is to study groups of racially similar women across different geographical locations using the same protocols (6). Results of such studies would highlight possible determinants of PCOS that are less likely attributable to race/genetics, and more likely attributable to environment. In this study, we aim to address the proposition put forth by the European Society of Human Reproduction and Embryology/American Society of Reproductive Medicine Consensus Workshop by comparing hormonal and metabolic parameters in White and Black women with PCOS in 2 unique locations of the United States: Birmingham, Alabama, and Los Angeles, California, evaluated by the same investigator using similar approaches and tools. Our objective is to determine if women of the same race will have distinct hormonal and metabolic traits of PCOS in 2 geographical locations, suggesting geo-epidemiologic contributors of the disease.
Materials and Methods
Subjects
This prospective study included women and adolescents, aged ≥14 years, who presented for evaluation of androgen excess at reproductive endocrinology clinics at University of Alabama at Birmingham (UAB) in Birmingham, Alabama, or Cedars-Sinai Medical Center (CSMC) in Los Angeles, California, between 1987 and 2010. Participants who were pregnant or were unable to provide consent were excluded. This study was approved by the institutional review board at both UAB and CSMC. Written informed consent was obtained from each participant. All participants were evaluated by a single investigator (R.A.) using similar tools and approaches (7).
Study Protocol
Participants self-identified as White, Black, Asian, Mixed, or Other race. All participants underwent a physical examination. Age, height, and weight were obtained. Waist circumference was measured at the narrowest portion of the torso approximately midway between the lower costal margin and the iliac crest, and the hip circumference was measured over the widest portion of the gluteal and greater trochanteric region. Body mass index (BMI) and waist to hip ratio (WHR) were then calculated. Clinical hyperandrogenism was assessed using the modified Ferriman-Gallwey score (mFG) (8). Hirsutism was defined as mFG ≥4 as per the 2018 International Guidelines (1). A detailed menstrual history was obtained. Participants were considered to have oligomenorrhea if they reported >35-day cycles, <10 bleeds per year, or reported being eumenorrheic but were confirmed nonovulatory with a luteal phase (cycle days 22-24) progesterone <4 ng/mL, as per the 2018 International Guidelines (1).
Participants underwent serum studies to assess for hyperandrogenemia if they had not received hormonal therapies in the preceding 3 months (7). Fasting blood samples were obtained on cycle days 3 through 8 of a spontaneous or progesterone-induced vaginal bleed (ie, the follicular phase) for measurement of circulating total testosterone, free testosterone, and dehydroepiandrosterone sulfate (DHEA-S). At UAB, all serum total testosterone levels were measured with an in-house column chromatography and radioimmunoassay, and serum free testosterone levels were calculated from an equilibrium dialysis-based assay of serum SHBG activity levels, as previously described (9, 10). At CSMC, serum levels of total testosterone were determined by liquid chromatography-tandem mass spectrometry (performed at either ARUP Laboratories, Salt Lake City, UT; Quest Diagnostics, San Juan Capistrano, CA; or LabCorp, Calabasas, CA). At CSMC, free testosterone levels were determined using equilibrium dialysis (performed at either ARUP Laboratories, Quest Diagnostics, or LabCorp). Measurements of testosterone using extraction chromatography and radioimmunoassay and radioimmunoassay have similar performance for differentiating PCOS from healthy controls at the 2 institutions included in this study, as previously described (11). At UAB, DHEA-S was measured by direct radioimmunoassay using a commercially available kit (Diagnostic Products Corporation, Los Angeles, CA). At CSMC, DHEA-S was determined by quantitative electrochemiluminescent immunoassay (performed at either ARUP Laboratories or LabCorp). Serum androgens collected at CSMC were processed at external laboratories (ARUP Laboratories, Quest Diagnostics, or LabCorp) with similar assays depending on the date of specimen collection and patient insurance authorization. For normalization of androgen levels across different assays, elevated serum androgens were defined as a dichotomous variable and considered elevated based on the laboratory's specific reference range, when available. When reference ranges were unavailable or could not be validated, values were considered elevated if they exceeded the 95th percentile of all reported values. Other causes of hyperandrogenism, such as nonclassic congenital adrenal hyperplasia, were excluded, as previously reported (7). We used the 1990 National Institutes of Health (NIH) criteria to define PCOS because ultrasound data were not readily available for most participants (12).
Participants underwent a 2-hour, 75-g oral glucose tolerance test (OGTT). Serum glucose and insulin values were measured at times 0, 60, and 120 minutes during the OGTT. Glucose values were determined by quantitative enzymatic assay (performed in-house at UAB or CSMC), and insulin values were determined by quantitative chemiluminescent assay (performed in-house at UAB or at ARUP Laboratories for CSMC specimens). Glucose and insulin values were considered elevated if they exceeded the reference range specific to the laboratory. Fasting glucose and fasting insulin values were used to compute a homeostatic model of insulin resistance (HOMA-IR) score with the following equation: [fasting glucose (mmol/L) × fasting insulin(mIU/L)]/22.5. An elevated HOMA-IR value is indicative of insulin resistance, with prior studies suggesting that values ranging from 1.55 to 3.8 can be considered cutoffs for insulin resistance (13, 14). In the present study, we used HOMA-IR as a continuous variable, with higher values indicating lesser degrees of insulin sensitivity.
Statistical Analysis
Descriptive statistics were performed using Student t tests, Wilcoxon rank sum, or χ2 tests, as appropriate. Logistic and linear regression was performed to adjust for age and BMI. Analyses were first conducted for all women with PCOS in Alabama compared with all women with PCOS in California. Analyses were then stratified by race for White women and Black women. All P values were 2-sided, with a set statistical significance level alpha of 0.05. Analyses were performed using the software STATA (version 13.0, StataCorp, College Station, TX).
Results
A total of 1610 women with PCOS by NIH Criteria were included in this study, 889 from UAB and 721 from CSMC. Table 1 summarizes the combinations of clinical and laboratory criteria used to establish a PCOS diagnosis. Of all women who were included, 1300 (80.7%) self-identified as White, 201 (12.5%) self-identified as Black, and 86 (5.3%) self-identified as either Asian, Mixed, or Other race, and 23 (1.4%) did not specify their race. Women with PCOS in Alabama were younger (28.0 ± 7.6 years vs 29.5 ± 7.3 years, P = 0.0001) and had a higher BMI (33.1 ± 9.3 kg/m2 vs 30.1 ± 8.3 kg/m2, P < 0.001) than women with PCOS in California (Table 2). Women with PCOS in Alabama were more likely to be hirsute (84.6% vs 72.8%, P < 0.001) and have a higher mean mFG score (7.9 ± 4.9 vs 6.7 ± 5.1, P < 0.001) than women with PCOS in California (Table 2). After adjusting for age and BMI, women with PCOS in Alabama were still more likely to be hirsute (adjusted odds ratio [aOR], 1.8; 95% CI, 1.4-2.4; P < 0.001). On the contrary, women with PCOS in California were more likely to have elevated free testosterone, total testosterone, and DHEA-S values than women with PCOS in Alabama (Table 2). These findings persisted after adjusting for age and BMI: elevated free testosterone (aOR, 0.14; 95% CI, 0.11-9.18; P < 0.001), elevated total testosterone (aOR, 0.41; 95% CI, 0.33-0.51; P < 0.001), and elevated DHEA-S (aOR, 0.07; 95% CI, 0.05-0.09; P < 0.001).
Combinations of clinical and laboratory criteria used to establish PCOS diagnosis
Ovulatory dysfunction . | Hirsutism . | Elevated total T . | Elevated free T . | Elevated DHEA-S . | n (total n = 1610) . |
---|---|---|---|---|---|
+ | + | + | + | + | 270 |
+ | + | − | + | + | 8 |
+ | + | + | − | + | 10 |
+ | + | + | + | − | 130 |
+ | + | − | − | + | 10 |
+ | + | − | + | − | 130 |
+ | + | + | − | − | 297 |
+ | + | − | − | − | 384 |
+ | − | + | + | + | 147 |
+ | − | − | + | + | 5 |
+ | − | + | − | + | 3 |
+ | − | + | + | − | 51 |
+ | − | − | − | + | 7 |
+ | − | − | + | − | 38 |
+ | − | + | − | − | 68 |
+ | NA | + | + | + | 41 |
+ | NA | − | + | + | 0 |
+ | NA | + | − | + | 0 |
+ | NA | + | + | − | 4 |
+ | NA | − | − | + | 0 |
+ | NA | − | + | − | 1 |
+ | NA | + | − | − | 6 |
Ovulatory dysfunction . | Hirsutism . | Elevated total T . | Elevated free T . | Elevated DHEA-S . | n (total n = 1610) . |
---|---|---|---|---|---|
+ | + | + | + | + | 270 |
+ | + | − | + | + | 8 |
+ | + | + | − | + | 10 |
+ | + | + | + | − | 130 |
+ | + | − | − | + | 10 |
+ | + | − | + | − | 130 |
+ | + | + | − | − | 297 |
+ | + | − | − | − | 384 |
+ | − | + | + | + | 147 |
+ | − | − | + | + | 5 |
+ | − | + | − | + | 3 |
+ | − | + | + | − | 51 |
+ | − | − | − | + | 7 |
+ | − | − | + | − | 38 |
+ | − | + | − | − | 68 |
+ | NA | + | + | + | 41 |
+ | NA | − | + | + | 0 |
+ | NA | + | − | + | 0 |
+ | NA | + | + | − | 4 |
+ | NA | − | − | + | 0 |
+ | NA | − | + | − | 1 |
+ | NA | + | − | − | 6 |
Abbreviations: +, presence of; −, absence of; DHEA-S, dehydroepiandrosterone sulfate; NA, not available; PCOS, polycystic ovary syndrome; T, testosterone.
Combinations of clinical and laboratory criteria used to establish PCOS diagnosis
Ovulatory dysfunction . | Hirsutism . | Elevated total T . | Elevated free T . | Elevated DHEA-S . | n (total n = 1610) . |
---|---|---|---|---|---|
+ | + | + | + | + | 270 |
+ | + | − | + | + | 8 |
+ | + | + | − | + | 10 |
+ | + | + | + | − | 130 |
+ | + | − | − | + | 10 |
+ | + | − | + | − | 130 |
+ | + | + | − | − | 297 |
+ | + | − | − | − | 384 |
+ | − | + | + | + | 147 |
+ | − | − | + | + | 5 |
+ | − | + | − | + | 3 |
+ | − | + | + | − | 51 |
+ | − | − | − | + | 7 |
+ | − | − | + | − | 38 |
+ | − | + | − | − | 68 |
+ | NA | + | + | + | 41 |
+ | NA | − | + | + | 0 |
+ | NA | + | − | + | 0 |
+ | NA | + | + | − | 4 |
+ | NA | − | − | + | 0 |
+ | NA | − | + | − | 1 |
+ | NA | + | − | − | 6 |
Ovulatory dysfunction . | Hirsutism . | Elevated total T . | Elevated free T . | Elevated DHEA-S . | n (total n = 1610) . |
---|---|---|---|---|---|
+ | + | + | + | + | 270 |
+ | + | − | + | + | 8 |
+ | + | + | − | + | 10 |
+ | + | + | + | − | 130 |
+ | + | − | − | + | 10 |
+ | + | − | + | − | 130 |
+ | + | + | − | − | 297 |
+ | + | − | − | − | 384 |
+ | − | + | + | + | 147 |
+ | − | − | + | + | 5 |
+ | − | + | − | + | 3 |
+ | − | + | + | − | 51 |
+ | − | − | − | + | 7 |
+ | − | − | + | − | 38 |
+ | − | + | − | − | 68 |
+ | NA | + | + | + | 41 |
+ | NA | − | + | + | 0 |
+ | NA | + | − | + | 0 |
+ | NA | + | + | − | 4 |
+ | NA | − | − | + | 0 |
+ | NA | − | + | − | 1 |
+ | NA | + | − | − | 6 |
Abbreviations: +, presence of; −, absence of; DHEA-S, dehydroepiandrosterone sulfate; NA, not available; PCOS, polycystic ovary syndrome; T, testosterone.
Baseline characteristics of all women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1610 . | (n = 889) . | (n = 721) . | |
Age (SD), y | 28 (7.6) | 29.5 (7.3) | 0.0001 |
BMI (SD), kg/m2 | 33.1 (9.3) | 30.1 (8.3) | <0.001 |
Waist-hip ratio (SD) | 0.8 (0.1) | 0.9 (0.1) | 0.0012 |
% Hirsute | 84.6% | 72.8% | <0.001 |
Mean mFG score (SD) | 7.9 (4.9) | 6.7 (5.1) | <0.001 |
% Elevated free T | 30.6% | 76.7% | <0.001 |
% Elevated total T | 55.5% | 74.1% | <0.001 |
% Elevated DHEA-S | 8.9% | 58.5% | <0.001 |
Mean HOMA-IR score (SD) | 8.25 (8.15) | 3.37 (8.60) | <0.001 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1610 . | (n = 889) . | (n = 721) . | |
Age (SD), y | 28 (7.6) | 29.5 (7.3) | 0.0001 |
BMI (SD), kg/m2 | 33.1 (9.3) | 30.1 (8.3) | <0.001 |
Waist-hip ratio (SD) | 0.8 (0.1) | 0.9 (0.1) | 0.0012 |
% Hirsute | 84.6% | 72.8% | <0.001 |
Mean mFG score (SD) | 7.9 (4.9) | 6.7 (5.1) | <0.001 |
% Elevated free T | 30.6% | 76.7% | <0.001 |
% Elevated total T | 55.5% | 74.1% | <0.001 |
% Elevated DHEA-S | 8.9% | 58.5% | <0.001 |
Mean HOMA-IR score (SD) | 8.25 (8.15) | 3.37 (8.60) | <0.001 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; mFG, modified Ferriman-Gallwey score; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
Baseline characteristics of all women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1610 . | (n = 889) . | (n = 721) . | |
Age (SD), y | 28 (7.6) | 29.5 (7.3) | 0.0001 |
BMI (SD), kg/m2 | 33.1 (9.3) | 30.1 (8.3) | <0.001 |
Waist-hip ratio (SD) | 0.8 (0.1) | 0.9 (0.1) | 0.0012 |
% Hirsute | 84.6% | 72.8% | <0.001 |
Mean mFG score (SD) | 7.9 (4.9) | 6.7 (5.1) | <0.001 |
% Elevated free T | 30.6% | 76.7% | <0.001 |
% Elevated total T | 55.5% | 74.1% | <0.001 |
% Elevated DHEA-S | 8.9% | 58.5% | <0.001 |
Mean HOMA-IR score (SD) | 8.25 (8.15) | 3.37 (8.60) | <0.001 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1610 . | (n = 889) . | (n = 721) . | |
Age (SD), y | 28 (7.6) | 29.5 (7.3) | 0.0001 |
BMI (SD), kg/m2 | 33.1 (9.3) | 30.1 (8.3) | <0.001 |
Waist-hip ratio (SD) | 0.8 (0.1) | 0.9 (0.1) | 0.0012 |
% Hirsute | 84.6% | 72.8% | <0.001 |
Mean mFG score (SD) | 7.9 (4.9) | 6.7 (5.1) | <0.001 |
% Elevated free T | 30.6% | 76.7% | <0.001 |
% Elevated total T | 55.5% | 74.1% | <0.001 |
% Elevated DHEA-S | 8.9% | 58.5% | <0.001 |
Mean HOMA-IR score (SD) | 8.25 (8.15) | 3.37 (8.60) | <0.001 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; mFG, modified Ferriman-Gallwey score; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
Women with PCOS in Alabama were more likely to have elevated glucose and insulin values at each time point in a 2-hour OGTT than women in California (Fig. 1A). These findings remained significant after adjustment for age and BMI (data not shown). Additionally, women with PCOS in Alabama had a higher mean HOMA-IR score than women with PCOS in California (8.25 ± 8.15 vs 3.37 ± 8.60; P < 0.001). This finding remained even after adjusting for age and BMI (adjusted beta coefficient, 3.6; 95% CI, 1.61-5.5; P < 0.001).

Results of a 2-hour OGTT differ in women with PCOS in Alabama (UAB) compared with California (CSMC). (A) White and Black women with PCOS. (B) White women with PCOS only. (C) Black women with PCOS only. *P < 0.05.
In a subset analysis of White women with PCOS (n = 1300), the results were similar to the entire cohort (Table 3 and Fig. 1B), and all findings remained true after adjustment for age and BMI (data not shown). In a subset analysis of Black women with PCOS (n = 201), there were some differences compared with the total cohort. There was no statistically significant difference in BMI or WHR in Black women with PCOS between California and Alabama (Table 4). Although Black women with PCOS in Alabama had a higher mean mFG compared with Black women with PCOS in California (9.1 ± 5.1 vs 7.7 ± 0.4.7 in CA; P = 0.03), there was no difference in the percentage of hirsutism (88.4% in Alabama vs 83.3% in California; P = 0.31).
Baseline characteristics of White women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1300 . | (n = 749) . | (n = 551) . | |
Age (SD), y | 28.1 (7.6) | 29.1 (7.4) | 0.02 |
BMI (SD), kg/m2 | 32.9 (9.5) | 29.7 (8.2) | <0.001 |
Waist-hip ratio (SD) | 0.83 (0.09) | 0.85 (0.08) | 0.0012 |
% Hirsute | 83.7% | 72.1% | <0.001 |
Mean mFG score (SD) | 7.7 (4.9) | 6.7 (5.2) | <0.001 |
% Elevated free T | 31.5% | 76.0% | <0.001 |
% Elevated total T | 53.9% | 72.4% | <0.001 |
% Elevated DHEA-S | 9.4% | 58.1% | <0.001 |
Mean HOMA-IR score (SD) | 7.61 (6.48) | 2.95 (3.32) | <0.001 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1300 . | (n = 749) . | (n = 551) . | |
Age (SD), y | 28.1 (7.6) | 29.1 (7.4) | 0.02 |
BMI (SD), kg/m2 | 32.9 (9.5) | 29.7 (8.2) | <0.001 |
Waist-hip ratio (SD) | 0.83 (0.09) | 0.85 (0.08) | 0.0012 |
% Hirsute | 83.7% | 72.1% | <0.001 |
Mean mFG score (SD) | 7.7 (4.9) | 6.7 (5.2) | <0.001 |
% Elevated free T | 31.5% | 76.0% | <0.001 |
% Elevated total T | 53.9% | 72.4% | <0.001 |
% Elevated DHEA-S | 9.4% | 58.1% | <0.001 |
Mean HOMA-IR score (SD) | 7.61 (6.48) | 2.95 (3.32) | <0.001 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; mFG, modified Ferriman-Gallwey score; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
Baseline characteristics of White women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1300 . | (n = 749) . | (n = 551) . | |
Age (SD), y | 28.1 (7.6) | 29.1 (7.4) | 0.02 |
BMI (SD), kg/m2 | 32.9 (9.5) | 29.7 (8.2) | <0.001 |
Waist-hip ratio (SD) | 0.83 (0.09) | 0.85 (0.08) | 0.0012 |
% Hirsute | 83.7% | 72.1% | <0.001 |
Mean mFG score (SD) | 7.7 (4.9) | 6.7 (5.2) | <0.001 |
% Elevated free T | 31.5% | 76.0% | <0.001 |
% Elevated total T | 53.9% | 72.4% | <0.001 |
% Elevated DHEA-S | 9.4% | 58.1% | <0.001 |
Mean HOMA-IR score (SD) | 7.61 (6.48) | 2.95 (3.32) | <0.001 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 1300 . | (n = 749) . | (n = 551) . | |
Age (SD), y | 28.1 (7.6) | 29.1 (7.4) | 0.02 |
BMI (SD), kg/m2 | 32.9 (9.5) | 29.7 (8.2) | <0.001 |
Waist-hip ratio (SD) | 0.83 (0.09) | 0.85 (0.08) | 0.0012 |
% Hirsute | 83.7% | 72.1% | <0.001 |
Mean mFG score (SD) | 7.7 (4.9) | 6.7 (5.2) | <0.001 |
% Elevated free T | 31.5% | 76.0% | <0.001 |
% Elevated total T | 53.9% | 72.4% | <0.001 |
% Elevated DHEA-S | 9.4% | 58.1% | <0.001 |
Mean HOMA-IR score (SD) | 7.61 (6.48) | 2.95 (3.32) | <0.001 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; mFG, modified Ferriman-Gallwey score; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
Baseline characteristics of Black women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 201 . | (n = 121) . | (n = 80) . | |
Age (SD), y | 28.0 (7.2) | 31.9 (7.3) | 0.0002 |
BMI (SD), kg/m2 | 35.0 (8.1) | 33.5 (8.1) | 0.2 |
Waist-hip ratio (SD) | 0.85 (0.99) | 0.87 (0.08) | 0.28 |
% Hirsute | 88.4% | 83.3% | 0.31 |
Mean mFG score (SD) | 9.1 (5.1) | 7.7 (4.7) | 0.03 |
% Elevated free T | 26.5% | 78.8% | <0.001 |
% Elevated total T | 64.5% | 81.3% | 0.010 |
% Elevated DHEA-S | 6.6% | 57.5% | <0.001 |
Mean HOMA-IR score (SD) | 10.40 (11.98) | 8.77 (28.78) | 0.0007 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 201 . | (n = 121) . | (n = 80) . | |
Age (SD), y | 28.0 (7.2) | 31.9 (7.3) | 0.0002 |
BMI (SD), kg/m2 | 35.0 (8.1) | 33.5 (8.1) | 0.2 |
Waist-hip ratio (SD) | 0.85 (0.99) | 0.87 (0.08) | 0.28 |
% Hirsute | 88.4% | 83.3% | 0.31 |
Mean mFG score (SD) | 9.1 (5.1) | 7.7 (4.7) | 0.03 |
% Elevated free T | 26.5% | 78.8% | <0.001 |
% Elevated total T | 64.5% | 81.3% | 0.010 |
% Elevated DHEA-S | 6.6% | 57.5% | <0.001 |
Mean HOMA-IR score (SD) | 10.40 (11.98) | 8.77 (28.78) | 0.0007 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
Baseline characteristics of Black women with PCOS in Alabama (UAB) and California (CSMC)
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 201 . | (n = 121) . | (n = 80) . | |
Age (SD), y | 28.0 (7.2) | 31.9 (7.3) | 0.0002 |
BMI (SD), kg/m2 | 35.0 (8.1) | 33.5 (8.1) | 0.2 |
Waist-hip ratio (SD) | 0.85 (0.99) | 0.87 (0.08) | 0.28 |
% Hirsute | 88.4% | 83.3% | 0.31 |
Mean mFG score (SD) | 9.1 (5.1) | 7.7 (4.7) | 0.03 |
% Elevated free T | 26.5% | 78.8% | <0.001 |
% Elevated total T | 64.5% | 81.3% | 0.010 |
% Elevated DHEA-S | 6.6% | 57.5% | <0.001 |
Mean HOMA-IR score (SD) | 10.40 (11.98) | 8.77 (28.78) | 0.0007 |
. | UAB . | CSMC . | P value . |
---|---|---|---|
Total n = 201 . | (n = 121) . | (n = 80) . | |
Age (SD), y | 28.0 (7.2) | 31.9 (7.3) | 0.0002 |
BMI (SD), kg/m2 | 35.0 (8.1) | 33.5 (8.1) | 0.2 |
Waist-hip ratio (SD) | 0.85 (0.99) | 0.87 (0.08) | 0.28 |
% Hirsute | 88.4% | 83.3% | 0.31 |
Mean mFG score (SD) | 9.1 (5.1) | 7.7 (4.7) | 0.03 |
% Elevated free T | 26.5% | 78.8% | <0.001 |
% Elevated total T | 64.5% | 81.3% | 0.010 |
% Elevated DHEA-S | 6.6% | 57.5% | <0.001 |
Mean HOMA-IR score (SD) | 10.40 (11.98) | 8.77 (28.78) | 0.0007 |
Abbreviations: BMI, body mass index; CSMC, Cedars-Sinai Medical Center; DHEA-S, dehydroepiandrosterone sulfate; HOMA-IR, homeostatic model of insulin resistance; PCOS, polycystic ovary syndrome; T, testosterone; UAB, University of Alabama at Birmingham.
After adjusting for age and BMI, the difference in mean mFG score was no longer significant (aOR, 0.8; 95% CI, −0.6 to 2.3; P = 0.27). Similar to the total cohort, Black women with PCOS in California were more likely to have elevated free testosterone, total testosterone, and DHEA-S values than Black women with PCOS in Alabama, even after adjusting for age and BMI (data not shown). Black women with PCOS in Alabama were more likely to have elevated glucose levels during the 2-hour OGTT (Fig. 1C); however, after adjustment for age and BMI, this was no longer statistically significant. Additionally, Black women with PCOS in Alabama were more likely to have elevated insulin values during the 2-hour OGTT (Fig. 1C); after adjusting for age and BMI, this was no longer significant at 60 minutes (aOR, 2.6; 95% CI, 0.6-11.0. P = 0.19) and 120 minutes (aOR, 17.3; 95% CI, 0.9-353; P = 0.06). As with the total cohort, Black women with PCOS in Alabama were more likely to have an elevated mean HOMA-IR score compared with Black women in California, even after adjustment for age and BMI (adjusted beta coefficient. 5.4; 95% CI, 0.3-10.8; P = 0.049).
Discussion
This study supports regional differences in hormonal and metabolic parameters in women with PCOS in the United States, highlighting the impact of the environment on PCOS phenotype. Women with PCOS in Alabama were more likely to demonstrate clinical hyperandrogenism and metabolic dysfunction with evidence of insulin resistance, whereas women with PCOS in California were more likely to demonstrate biochemical hyperandrogenemia. The results were similar when considering only women of White race. When assessing only women of Black race, the results overall were similar, with Black women with PCOS in Alabama demonstrating higher mean mFG scores and Black women with PCOS in California more likely to have elevated androgen values. Notable differences within the Black PCOS cohort were that the mean BMI and WHR did not differ significantly between the 2 locations, and that the total percentage of Black women with PCOS with hirsutism did not differ significantly, but differences in androgen profiles and metabolic dysfunction remained.
When considering our results, several genetic and environmental factors may be contributing to the differences in PCOS presentation and outcomes. In a genetically predisposed individual, various environmental exposures may initiate the development of clinically evident PCOS. The literature suggests that the environmental impact may begin as early as in utero (6, 15). Throughout an individual's lifetime, factors such as geography, diet and nutrition, socioeconomic status, and environmental toxins have also been identified as environmental modulators of PCOS development and progression (6, 16).
Genetic ancestry of individuals of the same race in the United States has been shown to vary per region (17–20). This is thought to be a consequence of several historical events that resulted in various degrees of admixture of Native American, European, and African gene pools in America. For example, African Americans in the Southern United States have a higher percentage of African ancestry than African Americans in the Northeast or West regions (17, 18). This has been interpreted as being a result of the African slave trade (18). One study from 2015 of more than 150 000 Americans found that self-reported African Americans in Alabama had a mean genetic makeup consisting of 81% African ancestry, 0.7% Native American ancestry, and 17% European ancestry, whereas self-reported African Americans in California had a mean genetic makeup consisting of 73% African ancestry, 0.85% Native American ancestry, and 24% European ancestry (18). In self-reported European American men and women, there is less genetic variation across the country. European Americans from Alabama were found to have 98.9% European ancestry and European Americans from California were found to have 98.1% European ancestry (18). Thus, individuals of the same race in different geographical locations of the United States may have differing genetic predispositions for developing diseases such as PCOS.
One example of how variation in genetic material may impact our results is the gene SRD5A1, which encodes the 5α-reductase type 1 enzyme. 5α-reductase converts testosterone to dihydrotestosterone, a more potent androgen that is implicated in PCOS pathogenesis. In 1 study of White women with PCOS at UAB, specific haplotypes of SRD5A1 were associated with increasing degrees of hirsutism, suggesting a genetic basis for the severity of hirsutism in this population (21). Given our findings that women in Alabama were more likely to be hirsute than women in California despite less hyperandrogenemia, it is interesting to consider the potential impact of genes such as SRD5A1 between the 2 locations.
When considering the impact of the environment on chronic diseases like PCOS, diet and nutrition is a highly studied environmental modulator. In the PCOS literature, starch-based foods, dairy products, and whey protein have all been found to have negative impacts on the metabolic sequelae of the disease (6, 22, 23). Food-purchasing habits and normative diets differ in California and Alabama. The Food Acquisition and Purchase Survey database records food purchases over a 7-day period (24–26) using the Healthy Eating Index (HEI) score in relation to US dietary guidelines, with scores ranging 0 to 100; higher scores suggest greater concordance with dietary guidelines (27). A 2019 study found that HEI scores vary in different geographical regions of the United States, with the highest HEI scores reported in the West (57.0 ± 0.8), and lowest HEI scores reported in the South (53.1 ± 0.8), P < 0.05 (25). The specific food decisions that contributed to these findings were found to also vary by race (25).
The HEI scores of foods available at different types of food retailers also varies, with mean composite HEI scores lowest at convenience stores (43.0) and highest at natural/gourmet food retailers (56.0) (24). The accessibility of natural/gourmet food retailers vs convenience stores differs by geographical locations in the country. In Alabama, convenience stores made up approximately 70% of the food retailers in the 9 counties surrounding UAB in 1 study spanning 2013 through 2015, and convenience stores had significantly less healthy food options when compared with traditional grocery stores in this region (28). In Los Angeles County, the accessibility of traditional supermarkets was not impacted by the number of convenience stores or fast-food restaurants, and the convenience stores offered more fresh fruits and vegetables when compared with convenience stores in the rural Southern United States (29–31).
Socioeconomic status (SES) has been shown to impact PCOS development and outcomes. Individuals who experienced low childhood SES despite obtaining a higher education and SES in adulthood were significantly at risk to develop PCOS (odds ratio, 2.5; 95% CI, 1.4-4.4) (16). The presence of individual components of PCOS (oligomenorrhea, hirsutism, and elevated testosterone) also differed based on the SES of an individual, suggesting that not all components of PCOS are impacted by SES (16). Although we were unable to assess the SES or income of individual participants in our study, US Census data from 1990 through 2010 shows a lower median income and higher percentage of people in poverty in Alabama compared with California and the national average (32, 33). These differences in income could be contributing to food purchasing decisions, which could have an independent impact on PCOS disease manifestation.
Environmental exposures are an area of ongoing public health concern given their potential to impact chronic disease, including PCOS (6). Several environmental exposures differ between the 2 geographical locations in this study. Los Angeles County, California, has a greater population density, greater number of unhealthy days per year (as assessed by the Air Quality Index), and larger amount of toxic releases per square mile, when compared with Jefferson County, Alabama (surrounding UAB) (34–36). Bisphenol A (BPA) and vitamin D are 2 specific environmental factors that are known to impact PCOS (37–39). BPA exposure can contribute to elevated androgen levels in women with PCOS; however, there are no studies directly comparing serum concentrations of BPA in women from diverse geographical regions of the United States that may be contributory to our findings (38, 39). Women with PCOS with vitamin D deficiency are more likely to have dysglycemia than women with normal vitamin D levels (37). Ongoing research is needed to compare the prevalence of vitamin D deficiency in women across different regions of the United States.
The prevalence of several metabolic disorders varies per US region and state. Data demonstrate that adults in Alabama had a higher prevalence of diabetes (11.8% vs 8.6%), elevated total cholesterol (42.7% vs 36.5%), and obesity (32.9% vs 25.1%) when compared with adults in California in the year 2011 (40). When stratified by sex and age, the prevalence of the diabetes, elevated total cholesterol, and obesity remained higher in Alabama. Additional data from the years 2000 through 2009 show that the prevalence of diabetes was higher in adults in Alabama compared with California throughout this decade (41). Thus, it is important to consider how the environment plays a role in these multifactorial metabolic disorders including PCOS.
One limitation to this study is that by including women with a PCOS diagnosis by NIH criteria, the results and conclusions are less generalizable to women with PCOS phenotypes reliant on ultrasound findings (1). Because participants presented for evaluation of their symptoms of androgen excess, selection bias may play a role. Access to specialty clinics for the evaluation of androgen excess may have differed between the 2 locations, thereby amplifying this selection bias. Additionally, SES, specific diet, environmental exposures, and an evaluation of exercise of the individual participants in the study were not directly assessed. A strength of our study was the standardization and consistency in data acquisition. All data were collected prospectively under the supervision of a single principal investigator, and the subjects were well-phenotyped and had consistent standardized androgenic data.
This study suggests there are regional differences in hormonal and metabolic parameters in women with PCOS in California and Alabama, highlighting the impact of differing genetic and environmental modulators on PCOS development. Even after adjusting for age and BMI, women with PCOS in Alabama were more likely to have clinical hyperandrogenism and insulin resistance, whereas women with PCOS in California were more likely to have biochemical hyperandrogenemia. Overall results were similar when stratified by race, with some exceptions including the lack of differences in BMI among Black women with PCOS based on geographic location yet continued variation in androgen profiles and metabolic dysfunction based on regional differences. Ongoing research is needed to identify modifiable environmental risk factors for PCOS that may be race and ethnic specific to bring precision medicine to the management of PCOS.
Acknowledgments
We would like to acknowledge Tania L Gonzalez, PhD, for her contribution toward Fig. 1. We would also like to acknowledge all participants willing to participate in research and our research studies.
Funding
This work was supported in part by grants R01-DK073632 and R01-HD29364 from the National Institutes of Health and an endowment of the Helping Hand of Los Angeles, Inc. (to R.A.).
Disclosures
R.A. serves as consultant to Core Access Surgical Technologies, Spruce Biosciences, Rani Therapeutics, and Fortress Biotech; as advisor to Arora Forge; and as equity holder in Martin Imaging. M.D.P. serves as a consultant for Ferring Pharmaceuticals and speaker for Natera. The remaining authors have nothing to disclose.
Data Availability
The datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.
References
Abbreviations
- aOR
adjusted odds ratio
- BMI
body mass index
- BPA
bisphenol A
- CSMC
Cedars-Sinai Medical Center
- DHEA-S
dehydroepiandrosterone sulfate
- HEI
Health Eating Index
- HOMA-IR
homeostatic model of insulin resistance
- mFG
modified Ferriman-Gallwey score
- NIH
National Institutes of Health
- OGTT
oral glucose tolerance test
- PCOS
polycystic ovary syndrome
- SES
socioeconomic status
- UAB
University of Alabama at Birmingham
- WHR
waist-to-hip ratio