ABSTRACT
Aim and Introduction
Diabetes and prediabetes pose significant global public health challenges. Sex steroids, particularly testosterone and estradiol, play crucial roles in various metabolic processes. This study investigates the relationship between sex hormone levels and long‐term mortality in adults with prediabetes and diabetes, as well as those without glucose intolerance.
Material and Methods
This retrospective cohort study utilized data from the NHANES 2013–2016, including adults aged 50–79 across prediabetic, diabetic, and non‐diabetic groups. Serum testosterone, estradiol, and their ratios (T/E) were analyzed. The primary outcomes were all‐cause mortality and CVD mortality tracked until December 2019. Cox regression models estimated the associations between hormone levels and mortality risks.
Results
The study included 3,665 participants (male: 2,140; female: 1,775). In males with prediabetes, higher estradiol (adjusted hazard ratio [aHR] = 0.17, 95% confidence interval [CI]: 0.07–0.43) or testosterone (aHR = 0.39, 95% CI: 0.31–0.50) was significantly associated with lower risk of all‐cause mortality. Higher estradiol (aHR = 0.12, 95% CI: 0.04–0.32) or testosterone (aHR = 0.36, 95% CI: 0.27–0.48) was significantly associated with lower CVD mortality risk. In females with diabetes, there was a significant association between higher estradiol levels (aHR = 0.22, 95% CI: 0.06–0.83) or T/E ratio (aHR = 0.18, 95% CI: 0.04–0.73) with a reduced all‐cause mortality risk.
Conclusions
This study identifies some novel associations between estradiol, testosterone, and their ratios with long‐term mortality in men and women across different glycemic statuses. These findings suggest a potential protective role of sex hormones in individuals with altered glucose metabolism, with gender difference, warranting further investigation.
Keywords: Diabetes, Estradiol, Mortality
Higher levels of testosterone and estradiol predict lower CVD mortality in males with prediabetes and diabetes, while a higher T/E ratio predicts lower all‐cause mortality in females.
INTRODUCTION
Diabetes mellitus (DM) and prediabetes represent a significant public health challenge globally. Prediabetes is defined by an HbA1c ranging from 5.7% to 6.4%, by a fasting blood glucose of 100–125 mg/dL, or by a 2‐h oral glucose tolerance test of 140–199 mg/dL 1 , 2 . As of 2021, diabetes affects 529 million people globally, and over 1.31 billion people will have diabetes by 2050 3 . Prediabetes is present in approximately 720 million individuals worldwide as of 2021 and is projected to affect an estimated 1 billion people by 2045 4 . The progression from prediabetes to diabetes is influenced by genetic predisposition, diet, physical activity, and overall lifestyle 5 . Exacerbated insulin resistance leads to an accumulation of glucose in the blood, facilitating the transition from prediabetes to type 2 diabetes 6 , 7 .
Sex steroids, particularly testosterone and estradiol, are pivotal in regulating reproductive functions. However, their influence extends beyond reproduction, impacting various metabolic processes 8 , 9 . Associated with increased adipose mass, low testosterone is a phenomenon that places men at increased risk of developing insulin resistance 10 . Estradiol also affects glucose metabolism and insulin sensitivity, especially in women 11 . The association between endogenous levels of these hormones and metabolic dysfunctions is key to the development of metabolic disorders 12 , 13 , 14 . Despite extensive research into the metabolic roles of testosterone and estradiol, less is known about how these hormones affect long‐term outcomes.
Understanding the correlation between endogenous sex steroid levels and mortality could revolutionize the predictive accuracy of diabetes progression models and refine therapeutic modalities. Therefore, this study aims to dissect the relationship between bioavailable estradiol and testosterone levels and mortality in adults with prediabetes and diabetes. The assessment rests on a hypothesis that variations in these hormone levels impact survival outcomes significantly in this population.
METHODS
Data source
The study utilized data from the 2013–2014 and 2015–2016 National Health and Nutrition Examination Survey (NHANES) cycles. NHANES is a continuous, stratified multistage probability cluster survey that assesses the health and nutritional status of non‐institutionalized civilian US population. The survey includes both an in‐home interview and a physical examination at a mobile examination center (MEC). The data collected provide a wealth of information on the prevalence of major diseases and risk factors, nutritional status, and population health behaviors. The data generated and analyzed in the current study are publicly available on the official NHANES website (https://www.cdc.gov/nchs/nhanes/index.html).
Study design and participants
This population‐based, retrospective cohort study included on male and female adults aged 50–79 years from the NHANES. Participants were excluded, if they had end‐stage kidney disease (eGFR < 15 mL/min/1.73 m2), with both ovaries removed, or if complete data on sex, hemoglobin A1c (HbA1c), mortality status at follow‐up, serum estradiol or testosterone levels, or sample weights were absent. Additionally, female participants who were pregnant or had undergone bilateral oophorectomy were also excluded from the cohort.
Ascertainment of prediabetes and diabetes
Participants were confirmed as having diabetes, if they met any of the following criteria: self‐reported diagnosis of diabetes by a doctor, use of anti‐diabetic medication including insulin or oral pills, a HbA1c level of 6.5% or higher, a fasting plasma glucose (FPG) level of 126 mg/dL or higher, or an oral glucose tolerance test (OGTT) result of 200 mg/dL or higher.
Prediabetes was defined based on a self‐reported diagnosis of prediabetes by a doctor, an HbA1c level between 5.7% and 6.4% (39–46 mmol/mol), or an FPG level between 100 and 125 mg/dL.
Participants who did not fulfill the above criteria were classified into ‘non‐diabetes’ group.
These definitions aligned with previous studies using the NHANES database 15 , 16 .
Ethics statement
The NHANES program is conducted by the National Center for Health Statistics (NCHS) under the Centers for Disease Control and Prevention (CDC) and follows strict ethical guidelines to ensure the protection of participants. The data were publicly available and de‐identified, which safeguarded the privacy of all participants. The NCHS ensures that all data used for research purposes meet the highest standards of privacy and confidentiality. As this study involves only the analysis of secondary data from the NHANES, no additional ethical approval or informed consent was required.
Ascertainment of mortality status
The primary outcomes were all‐cause mortality and cardiovascular disease (CVD) mortality, both of which were obtained from the data followed through to the end of 2019. The National Center for Health Statistics (NCHS) provided the NHANES Public‐Use Linked Mortality File, which was linked to the National Death Index (a centralized NCHS database of all deaths in the US) through December 31, 2019. This enabled the ascertainment of mortality status for the NHANES participants. Additionally, the Linked Mortality File provided underlying cause of death for participants, classified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD‐10). Accordingly, CVD mortality was defined as death resulting from cardiovascular disease (codes I00–I09, I11, I13, and I20–I51).
Measurement of estradiol and testosterone
The main study variables were serum estradiol and testosterone levels, along with the testosterone‐estradiol (T/E) ratio. Serum testosterone and estradiol levels were obtained from the ‘sex steroid hormone’ data file of NHANES. In NHANES, participants' blood samples were collected only once during recruitment. Participants were initially interviewed at home and then instructed to visit a mobile examination center (MEC) within a few weeks for blood draws and other physical examinations. With regard to the laboratory methodology, simultaneous measurements of total testosterone and estradiol in serum were performed using the isotope dilution liquid chromatography tandem mass spectrometry (ID‐LC–MS/MS) method developed by the CDC for routine analysis. This method is certified by the CDC Hormone Standardization Program (HoSt) and traceable to certified reference materials from the National Metrology Institute of Japan (NMIJ CRM 6004‐a for estradiol) and the Australian National Measurement Institute (ANMI M914 for testosterone). Details of the data collection process can be found at: https://wwwn.cdc.gov/Nchs/Nhanes/2015‐2016/TST_I.htm.
Other study variables
Demographic data, including age, sex, poverty–income ratio, race, and education level, were collected by trained enumerators using household and sample demographic questionnaires, as well as the Computer‐Assisted Individual Investigation (CAPI) system (Confirmit Corp., New York, US).
Body mass index (BMI) values are obtained from NHANES examination measurements. Smoking status was categorized into three groups: non‐smoker, former smoker, and current smoker. Non‐smokers had smoked fewer than 100 cigarettes in their lifetime. Former smokers had smoked more than 100 cigarettes in their lifetime but did not currently smoke. Current smokers had smoked more than 100 cigarettes in their lifetime and answered “Yes” to the question “Do you smoke now?”
Physical activity was quantified using the MET‐h index, calculated as the sum of the products of the time spent weekly on each activity reported by the participant and the metabolic equivalent of task (MET) value for that activity. Activity levels were categorized as follows: Optimal (≥1,000 MET‐h), Active (500–1,000 MET‐h), and Inactive (<500 MET‐h) 17 .
CVD, which includes coronary heart disease, angina, congestive heart failure, myocardial infarction, and stroke, was defined based on the question, “Has a doctor or other health professional ever told you that you have this disease?”
Glomerular filtration rate (GFR) was estimated from re‐calibrated serum creatinine levels using the 4‐variable Modification of Diet in Renal Disease (MDRD) Study equation. We use the IDMS‐traceable MDRD Study equation that uses standardized creatinine: GFR = 175 × (standardized serum creatinine)−1.154 × (age)−0.203 × 0.742 (if the subject is a woman) × 1.212 (if the subject is black). Estimated GFR is reported in mL/min/1.73 m2. Participants with an eGFR <60 mL/min/1.73 m2 were considered having chronic kidney disease (CKD).
The presence of cancer was determined by the question, “Have you ever been told you had cancer or malignancy?” Chronic respiratory diseases were identified by answering “yes” to the questions, “Have you ever been told you have asthma, emphysema, or chronic bronchitis?” The number of comorbidities was calculated by summing the presence of CVD, CKD, cancer, and chronic respiratory disease for each participant. Insulin use was confirmed by the response to the question, “Are you currently using insulin?” Menopause status was determined by the response to the question, “About how old were you when you had your last menstrual period?”
Laboratory measurements, including total cholesterol, triglycerides, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), albumin, glycated hemoglobin (HbA1c), and fasting glucose, were obtained from the NHANES laboratory data files.
Statistical analysis
NHANES uses a complex, multistage, probability sampling design to assure national representation, wherein sampling weights (WTMEC2YR), pseudo‐stratum (SDMVSTRA), and pseudo‐cluster (SDMVPSU) provided by NHANES were applied in all analyses as guided by the NCHS. The weighted mean and standard error were presented for continuous variables; unweighted number and weighted proportion were presented for categorical variables. Differences in means between groups were compared by using the SURVEYREG procedure for continuous variables, while the Rao‐Scott chi‐square test was performed to examine the difference in the proportions between groups by using the SURVEYFREQ procedure for categorical variables.
Cox proportional hazards regression was performed by using the SURVEYPHREG procedure to calculate the hazard ratio (HR) and 95% confidence interval (CI) in estimating the associations between estradiol level, testosterone level, T/E ratio, and all‐cause mortality, and CVD mortality. Multivariable regression was adjusted for age (continuous), race, education, cigarette smoking, physical activity, diabetes status, insulin use, and number of comorbidities. A two‐sided P‐value of <0.05 was regarded as statistically significant. All statistical analyses were performed using SAS statistical software (version 9.4, SAS Inc., Cary, NC, USA).
RESULTS
Study population selection
A total of 20,146 NHANES participants in the 2013–2014 and 2015–2016 study cycles were identified. Only 4,877 participants aged 50–79 years were eligible for inclusion. Women who had both ovaries removed (n = 442) or participants with end‐stage kidney disease (n = 22) were excluded. After further excluding 498 participants with missing information on HbA1c, mortality status, and estradiol and testosterone, 3,915 individuals were included in the analysis. This study sample represents a total of 79,333,364 community‐dwelling individuals in the whole US (Figure 1).
Figure 1.
Flow diagram of the study population selection. A total of 20,146 NHANES participants in the 2013–2014 and 2015–2016 cycles were included. Only 4,877 adults aged 50–79 years were eligible. Women who had both ovaries removed (n = 442) or participants with end‐stage kidney disease (n = 22) were excluded. After further excluding participants with missing information on HbA1c, mortality status, and estradiol or testosterone, 3,915 participants were included in the analysis. This study sample represents a total of 79,333,364 community‐dwelling individuals in the whole US.
Characteristics of the NHANES participants with prediabetes and diabetes
The characteristics of 2,140 male participants are summarized in Table 1. The mean age was 61.6 years and 73.4% were non‐Hispanic White males. Mean estradiol level (22.9 pg/mL vs 25.5 pg/mL, P = 0.034) and testosterone level (339.6 ng/dL vs 414.7 ng/dL, P = 0.006) were different between the groups categorized by CVD mortality status. However, no significant difference in estradiol, testosterone, or T/E ratio was observed between the groups categorized by all‐cause mortality status (Table 1).
Table 1.
Characteristics of male participants by all‐cause and CVD mortality status at follow‐up (n = 2,140)
| Total (n = 2,140) | All‐cause mortality | CVD mortality | |||||
|---|---|---|---|---|---|---|---|
| Died (n = 185) | Alive (n = 1,955) | P‐value | Died (n = 52) | Alive (n = 2,088) | P‐value | ||
| Estradiol level, pg/mL | 25.5 ± 0.3 | 25.9 ± 2.2 | 25.4 ± 0.3 | 0.823 | 22.9 ± 1.1 | 25.5 ± 0.3 | 0.034 |
| Testosterone level, ng/dL | 413.1 ± 5.4 | 386.4 ± 22.8 | 415.1 ± 5.7 | 0.237 | 339.6 ± 24.8 | 414.7 ± 5.6 | 0.006 |
| T/E ratio | 17.4 ± 0.3 | 16.3 ± 0.9 | 17.5 ± 0.4 | 0.205 | 16.0 ± 1.5 | 17.5 ± 0.3 | 0.359 |
| Age, years | 61.6 ± 0.3 | 66.1 ± 0.7 | 61.3 ± 0.3 | <0.001 | 67.0 ± 1.3 | 61.5 ± 0.3 | <0.001 |
| 50–59 | 812 (45.5) | 27 (22.8) | 785 (47.2) | <0.001 | 9 (19.2) | 803 (46.1) | <0.001 |
| 60–69 | 829 (35.9) | 69 (39.8) | 760 (35.6) | 15 (33.7) | 814 (35.9) | ||
| 70–79 | 499 (18.6) | 89 (37.4) | 410 (17.2) | 28 (47.1) | 471 (18.0) | ||
| Race | |||||||
| Non‐Hispanic White | 817 (73.4) | 84 (73.4) | 733 (73.4) | 0.537 | 26 (80.3) | 791 (73.2) | 0.165 |
| Non‐Hispanic Black | 462 (9.0) | 45 (11.3) | 417 (8.8) | 12 (10.4) | 450 (8.9) | ||
| Hispanic/other/unknown | 861 (17.6) | 56 (15.3) | 805 (17.8) | 14 (9.3) | 847 (17.8) | ||
| Poverty income ratio | |||||||
| Not poor | 1,554 (88.3) | 124 (78.3) | 1,430 (89.1) | 0.002 | 34 (66.4) | 1,520 (88.8) | <0.001 |
| Poor | 398 (11.7) | 49 (21.7) | 349 (10.9) | 16 (33.6) | 382 (11.2) | ||
| Missing | 188 | 12 | 176 | 2 | 186 | ||
| Education | |||||||
| High school and above | 1,536 (84.4) | 128 (82.2) | 1,408 (84.6) | 0.427 | 38 (85.8) | 1,498 (84.4) | 0.785 |
| Never attended high school | 603 (15.6) | 57 (17.8) | 546 (15.4) | 14 (14.2) | 589 (15.6) | ||
| Missing | 1 | 0 | 1 | 0 | 1 | ||
| BMI, kg/m2 | |||||||
| Normal | 491 (20.3) | 45 (20.1) | 446 (20.3) | <0.001 | 9 (13.4) | 482 (20.5) | <0.001 |
| Underweight | 56 (2.6) | 14 (9.6) | 42 (2.1) | 6 (17.0) | 50 (2.3) | ||
| Overweight | 829 (38.3) | 63 (26.3) | 766 (39.2) | 19 (29.3) | 810 (38.5) | ||
| Obese | 764 (38.8) | 63 (44.0) | 701 (38.4) | 18 (40.3) | 746 (38.8) | ||
| Cigarette smoking | |||||||
| Never | 816 (41.3) | 34 (15.0) | 782 (43.2) | <0.001 | 14 (24.1) | 802 (41.7) | 0.005 |
| Former | 842 (40.3) | 91 (47.3) | 751 (39.8) | 21 (36.1) | 821 (40.4) | ||
| Current | 479 (18.4) | 59 (37.7) | 420 (17.0) | 17 (39.9) | 462 (17.9) | ||
| Missing | 3 | 1 | 2 | 0 | 3 | ||
| Physical activity | |||||||
| Optimal | 598 (50.2) | 29 (42.8) | 569 (50.6) | 0.259 | 8 (30.4) | 590 (50.7) | 0.186 |
| Active | 235 (21.8) | 20 (33.2) | 215 (21.2) | 7 (43.2) | 228 (21.4) | ||
| Inactive | 354 (27.9) | 26 (24.0) | 328 (28.2) | 9 (26.4) | 345 (28.0) | ||
| Missing | 953 | 110 | 843 | 28 | 925 | ||
| Diabetes status | |||||||
| Non‐diabetes | 573 (32.0) | 55 (31.3) | 518 (32.1) | 0.012 | 11 (15.2) | 562 (32.4) | 0.050 |
| Prediabetes | 842 (39.7) | 48 (28.2) | 794 (40.5) | 19 (46.7) | 823 (39.5) | ||
| Diabetes | 725 (28.3) | 82 (40.5) | 643 (27.4) | 22 (38.1) | 703 (28.1) | ||
| Insulin use | |||||||
| No | 1,987 (94.4) | 167 (91.8) | 1,820 (94.6) | 0.177 | 46 (87.8) | 1,941 (94.6) | 0.181 |
| Yes | 153 (5.6) | 18 (8.2) | 135 (5.4) | 6 (12.2) | 147 (5.4) | ||
| CVD | |||||||
| No | 1,719 (82.9) | 102 (56.4) | 1,617 (84.9) | <0.001 | 18 (40.6) | 1,701 (83.8) | <0.001 |
| Yes | 421 (17.1) | 83 (43.6) | 338 (15.1) | 34 (59.4) | 387 (16.2) | ||
| CKD | |||||||
| No | 1,862 (89.0) | 130 (76.9) | 1,732 (89.9) | <0.001 | 31 (66.8) | 1,831 (89.5) | <0.001 |
| Yes | 278 (11.0) | 55 (23.1) | 223 (10.1) | 21 (33.2) | 257 (10.5) | ||
| Cancer history | |||||||
| No | 1,842 (82.1) | 133 (62.8) | 1,709 (83.5) | <0.001 | 39 (63.5) | 1,803 (82.5) | 0.021 |
| Yes | 298 (17.9) | 52 (37.2) | 246 (16.5) | 13 (36.5) | 285 (17.5) | ||
| Chronic respiratory disease | |||||||
| No | 1,917 (90.3) | 144 (75.7) | 1,773 (91.4) | <0.001 | 40 (69.7) | 1,877 (90.8) | 0.003 |
| Yes | 223 (9.7) | 41 (24.3) | 182 (8.6) | 12 (30.3) | 211 (9.2) | ||
| Number of comorbidities | |||||||
| 0 | 1,258 (58.9) | 52 (26.0) | 1,206 (61.3) | <0.001 | 12 (20.6) | 1,246 (59.7) | <0.001 |
| 1 | 604 (28.7) | 56 (29.0) | 548 (28.7) | 9 (14.8) | 595 (29.0) | ||
| 2 | 222 (10.4) | 58 (36.5) | 164 (8.5) | 22 (49.3) | 200 (9.6) | ||
| 3–4 | 56 (2.0) | 19 (8.5) | 37 (1.5) | 9 (15.3) | 47 (1.7) | ||
| Laboratory measures | |||||||
| Total cholesterol, mg/dL | 188.6 ± 1.6 | 175.4 ± 3.7 | 189.6 ± 1.7 | 0.002 | 181.8 ± 8.0 | 188.8 ± 1.6 | 0.388 |
| Triglyceride, mg/dL (n = 1,098) | 122.8 ± 3.3 | 123.9 ± 8.0 | 122.8 ± 3.3 | 0.876 | 151.1 ± 18.7 | 122.3 ± 3.4 | 0.158 |
| HDL‐C, mg/dL | 49.6 ± 0.6 | 47.5 ± 0.8 | 49.8 ± 0.6 | 0.012 | 46.4 ± 1.8 | 49.7 ± 0.6 | 0.111 |
| LDL‐C, mg/dL (n = 1,072) | 110.1 ± 1.8 | 99.0 ± 3.8 | 110.8 ± 1.9 | 0.012 | 114.8 ± 6.0 | 110.0 ± 1.8 | 0.426 |
| Albumin, g/dL | 43.1 ± 0.1 | 41.0 ± 0.4 | 43.2 ± 0.1 | <0.001 | 40.5 ± 0.6 | 43.1 ± 0.1 | <0.001 |
| HbA1c, % | 6.0 ± 0.0 | 6.2 ± 0.1 | 6.0 ± 0.0 | 0.015 | 6.6 ± 0.2 | 6.0 ± 0.0 | <0.001 |
| Fasting glucose, mg/dL (n = 1,138) | 119.2 ± 1.4 | 133.7 ± 4.5 | 118.4 ± 1.4 | 0.002 | 169.0 ± 13.9 | 118.3 ± 1.4 | <0.001 |
Continuous variables are presented as mean ± SE. Categorical variables are presented as unweighted counts (weighted percentages). P‐values <0.05 are shown in bold. BMI, body mass index; CKD, chronic kidney disease; CVD, cardiovascular disease; HbA1c, glycated hemoglobin; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol.
The characteristics of 1,775 female patients are summarized in Table 2. The mean age was 61.2 years and 71.2% were non‐Hispanic White females. Mean estradiol (7.6 pg/mL vs 19.5 pg/mL, P < 0.001) and testosterone level (20.3 ng/dL vs 24.2 ng/dL, P = 0.044) were significantly different between the groups categorized by all‐cause mortality status. In addition, estradiol level (7.6 pg/mL vs 18.9 pg/mL, P < 0.001) was significantly different between the groups categorized by CVD mortality status (Table 2).
Table 2.
Characteristics of female participants by all‐cause and CVD mortality status at follow‐up (n = 1,775)
| Total (n = 1,775) | All‐cause mortality | CVD mortality | |||||
|---|---|---|---|---|---|---|---|
| Died (n = 103) | Alive (n = 1,672) | P‐value | Died (n = 25) | Alive (n = 1,750) | P‐value | ||
| Estradiol, pg/mL | 18.8 ± 1.7 | 7.6 ± 0.7 | 19.5 ± 1.9 | <0.001 | 7.6 ± 0.8 | 18.9 ± 1.8 | <0.001 |
| Testosterone level, ng/dL | 24.0 ± 1.3 | 20.3 ± 1.5 | 24.2 ± 1.4 | 0.044 | 19.7 ± 3.0 | 24.0 ± 1.3 | 0.196 |
| T/E ratio | 3.7 ± 0.1 | 3.3 ± 0.3 | 3.7 ± 0.1 | 0.244 | 3.0 ± 0.5 | 3.7 ± 0.1 | 0.193 |
| Age, years | 61.2 ± 0.2 | 65.8 ± 1.0 | 60.9 ± 0.3 | <0.001 | 65.8 ± 1.2 | 61.1 ± 0.3 | <0.001 |
| 50–59 | 742 (47.6) | 18 (29.0) | 724 (48.6) | 0.004 | 4 (26.4) | 738 (47.8) | 0.122 |
| 60–69 | 673 (34.4) | 40 (37.0) | 633 (34.2) | 11 (37.5) | 662 (34.4) | ||
| 70–79 | 360 (18.0) | 45 (34.0) | 315 (17.1) | 10 (36.2) | 350 (17.8) | ||
| Race | |||||||
| Non‐Hispanic White | 633 (71.2) | 51 (74.9) | 582 (71.0) | 0.495 | 12 (70.1) | 621 (71.3) | 0.450 |
| Non‐Hispanic Black | 353 (10.4) | 21 (10.9) | 332 (10.4) | 6 (17.8) | 347 (10.4) | ||
| Hispanic/other/unknown | 789 (18.3) | 31 (14.2) | 758 (18.5) | 7 (12.1) | 782 (18.4) | ||
| Poverty income ratio | |||||||
| Not poor | 1,218 (87.1) | 55 (66.7) | 1,163 (88.3) | <0.001 | 10 (45.7) | 1,208 (87.6) | <0.001 |
| Poor | 377 (12.9) | 42 (33.3) | 335 (11.7) | 15 (54.3) | 362 (12.4) | ||
| Missing | 180 | 6 | 174 | 0 | 180 | ||
| Education | |||||||
| High school and above | 1,303 (85.6) | 70 (81.9) | 1,233 (85.8) | 0.301 | 15 (72.0) | 1,288 (85.7) | <0.001 |
| Never attended high school | 472 (14.4) | 33 (18.1) | 439 (14.2) | 10 (28.0) | 462 (14.3) | ||
| BMI, kg/m2 | |||||||
| Normal | 409 (25.4) | 17 (16.3) | 392 (25.9) | <0.001 | 4 (16.1) | 405 (25.5) | 0.212 |
| Underweight | 43 (2.1) | 11 (13.1) | 32 (1.5) | 3 (7.6) | 40 (2.0) | ||
| Overweight | 484 (27.4) | 27 (26.1) | 457 (27.4) | 6 (18.0) | 478 (27.5) | ||
| Obese | 839 (45.1) | 48 (44.5) | 791 (45.2) | 12 (58.2) | 827 (45.0) | ||
| Cigarette smoking | |||||||
| Never | 1,097 (58.7) | 36 (27.9) | 1,061 (60.5) | <0.001 | 9 (25.9) | 1,088 (59.1) | 0.002 |
| Former | 397 (25.1) | 43 (44.0) | 354 (24.1) | 13 (62.8) | 384 (24.7) | ||
| Current | 280 (16.1) | 24 (28.1) | 256 (15.5) | 3 (11.3) | 277 (16.2) | ||
| Missing | 1 | 0 | 1 | 0 | 1 | ||
| Physical activity | |||||||
| Optimal | 386 (43.5) | 9 (36.9) | 377 (43.7) | 0.588 | 1 (33.7) | 385 (43.6) | 0.422 |
| Active | 234 (24.1) | 11 (33.4) | 223 (23.9) | 4 (46.3) | 230 (24.0) | ||
| Inactive | 314 (32.4) | 13 (29.7) | 301 (32.5) | 2 (20.0) | 312 (32.4) | ||
| Missing | 841 | 70 | 771 | 18 | 823 | ||
| Menopaused | |||||||
| No | 271 (15.3) | 10 (11.9) | 261 (15.5) | 0.428 | 4 (17.9) | 267 (15.3) | 0.706 |
| Yes | 1,504 (84.7) | 93 (88.1) | 1,411 (84.5) | 21 (82.1) | 1,483 (84.7) | ||
| Diabetes status | |||||||
| Non‐diabetes | 543 (37.9) | 28 (25.6) | 515 (38.6) | <0.001 | 9 (32.8) | 534 (38.0) | <0.001 |
| Prediabetes | 743 (41.0) | 28 (24.3) | 715 (42.0) | 2 (6.2) | 741 (41.4) | ||
| Diabetes | 489 (21.1) | 47 (50.1) | 442 (19.4) | 14 (61.0) | 475 (20.6) | ||
| Insulin use | |||||||
| No | 1,673 (96.1) | 89 (88.1) | 1,584 (96.6) | 0.007 | 20 (67.1) | 1,653 (96.4) | <0.001 |
| Yes | 102 (3.9) | 14 (11.9) | 88 (3.4) | 5 (32.9) | 97 (3.6) | ||
| CVD | |||||||
| No | 1,553 (90.0) | 76 (77.3) | 1,477 (90.7) | 0.002 | 19 (76.7) | 1,534 (90.1) | 0.041 |
| Yes | 222 (10.0) | 27 (22.7) | 195 (9.3) | 6 (23.3) | 216 (9.9) | ||
| CKD | |||||||
| No | 1,516 (84.1) | 72 (75.7) | 1,444 (84.6) | 0.048 | 17 (65.3) | 1,499 (84.3) | 0.025 |
| Yes | 259 (15.9) | 31 (24.3) | 228 (15.4) | 8 (34.7) | 251 (15.7) | ||
| Cancer history | |||||||
| No | 1,561 (84.9) | 80 (75.3) | 1,481 (85.5) | 0.061 | 20 (79.3) | 1,541 (85.0) | 0.502 |
| Yes | 214 (15.1) | 23 (24.7) | 191 (14.5) | 5 (20.7) | 209 (15.0) | ||
| Chronic respiratory disease | |||||||
| No | 1,540 (87.5) | 82 (78.0) | 1,458 (88.1) | 0.017 | 20 (79.4) | 1,520 (87.6) | 0.128 |
| Yes | 235 (12.5) | 21 (22.0) | 214 (11.9) | 5 (20.6) | 230 (12.4) | ||
| Number of comorbidities | |||||||
| 0 | 1,090 (60.3) | 39 (42.5) | 1,051 (61.3) | <0.001 | 9 (26.9) | 1,081 (60.7) | 0.009 |
| 1 | 483 (28.5) | 36 (32.6) | 447 (28.2) | 10 (54.1) | 473 (28.2) | ||
| 2 | 161 (8.8) | 18 (13.6) | 143 (8.5) | 4 (12.0) | 157 (8.8) | ||
| 3–4 | 41 (2.4) | 10 (11.3) | 31 (1.9) | 2 (7.1) | 39 (2.3) | ||
| Laboratory measures | |||||||
| Total cholesterol, mg/dL (n = 1,645) | 209.4 ± 1.3 | 200.8 ± 5.8 | 209.9 ± 1.3 | 0.140 | 211.6 ± 11.6 | 209.4 ± 1.3 | 0.853 |
| Triglyceride, mg/dL (n = 886) | 116.5 ± 2.8 | 149.7 ± 25.0 | 114.8 ± 2.6 | 0.174 | 136.8 ± 18.9 | 116.4 ± 2.8 | 0.296 |
| HDL‐C, mg/dL (n = 1,645) | 62.6 ± 0.9 | 62.1 ± 7.6 | 62.7 ± 0.7 | 0.938 | 54.9 ± 3.3 | 62.7 ± 0.9 | 0.033 |
| LDL‐C, mg/dL (n = 878) | 120.4 ± 1.5 | 100.4 ± 6.9 | 121.4 ± 1.8 | 0.015 | 91.8 ± 6.4 | 120.5 ± 1.5 | <0.001 |
| Albumin, g/dL | 42.4 ± 0.1 | 40.7 ± 0.7 | 42.5 ± 0.1 | 0.014 | 40.8 ± 0.6 | 42.5 ± 0.1 | 0.007 |
| HbA1c, % | 5.8 ± 0.0 | 6.1 ± 0.1 | 5.8 ± 0.0 | 0.067 | 6.4 ± 0.2 | 5.8 ± 0.0 | 0.028 |
| Fasting glucose, mg/dL (n = 913) | 108.7 ± 1.2 | 124.0 ± 7.3 | 107.8 ± 1.3 | 0.038 | 134.6 ± 19.6 | 108.5 ± 1.2 | 0.194 |
Continuous variables are presented as mean ± SE. Categorical variables are presented as unweighted counts (weighted percentages). P‐values <0.05 were shown in bold. BMI, body mass index; CKD, chronic kidney disease; CVD, cardiovascular disease; HbA1c, glycated hemoglobin; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol.
Associations between estradiol, testosterone level, T/E ratio, and mortality, stratified by diabetes status and sex
The associations between mortality, estradiol, testosterone level, and T/E ratio stratified by diabetes status and sex are demonstrated in Table 3.
Table 3.
Associations between estradiol level, testosterone level, T/E ratio, and mortality outcomes, stratified by diabetes status
| Subgroup | Male | Female | ||||||
|---|---|---|---|---|---|---|---|---|
| All‐cause mortality | CVD mortality | All‐cause mortality | CVD mortality | |||||
| aHR (95% CI) † | P‐value | aHR (95% CI) † | P‐value | aHR (95% CI) † | P‐value | aHR (95% CI) † | P‐value | |
| Non‐diabetes (Male: n = 359; Female: n = 325) | ||||||||
| Estradiol, pg/mL ‡ | 0.65 (0.10–4.09) | 0.639 | 0.23 (0.05–1.11) | 0.066 | 1.86 (0.99–3.47) | 0.052 | 1.25 (0.64–2.46) | 0.504 |
| Testosterone, ng/dL ‡ | 1.37 (0.37–5.08) | 0.625 | 0.50 (0.18–2.33) | 0.495 | 2.59 (0.81–8.23) | 0.104 | 0.55 (0.07–4.37) | 0.563 |
| T/E ratio ‡ , § | 5.23 (0.24–114.20) | 0.282 | NE | – | 0.35 (0.11–1.10) | 0.070 | 0.38 (0.09–1.49) | 0.157 |
| Prediabetes (Male: n = 458; Female: n = 406) | ||||||||
| Estradiol, pg/mL ‡ | 0.17 (0.07–0.43) | <0.001 | 0.12 (0.04–0.32) | <0.001 | 1.45 (0.84–2.50) | 0.170 | NA | – |
| Testosterone, ng/dL ‡ | 0.39 (0.31–0.50) | <0.001 | 0.36 (0.27–0.48) | <0.001 | 1.00 (0.34–2.96) | 0.998 | NA | – |
| T/E ratio ‡ , § | 1.93 (0.03–123.84) | 0.750 | 3.48 (0.01–2,112.13) | 0.694 | 0.54 (0.26–1.10) | 0.086 | NA | – |
| Diabetes (Male: n = 367; Female: n = 202) | ||||||||
| Estradiol, pg/mL ‡ | 1.69 (0.35–8.14) | 0.501 | 1.26 (0.18–8.62) | 0.809 | 1.04 (0.50–2.16) | 0.924 | 0.79 (0.37–1.67) | 0.522 |
| Testosterone, ng/dL ‡ | 0.92 (0.28–3.00) | 0.886 | 1.21 (0.22–6.77) | 0.827 | 0.22 (0.06–0.83) | 0.027 | 0.81 (0.25–2.63) | 0.712 |
| T/E ratio ‡ , § | 0.24 (0.02–3.20) | 0.270 | 0.50 (0.03–10.01) | 0.637 | 0.18 (0.04–0.73) | 0.018 | 0.81 (0.47–1.40) | 0.442 |
P‐values <0.05 are shown in bold.
Adjusted for age (in years), race, education, cigarette smoking, physical activity, insulin use, CKD, CVD, albumin, and HbA1c (no correction for insulin use in the non‐diabetes group). For non‐diabetic males, associations between estradiol, testosterone level, and CVD mortality were adjusted for age (in years), race, poverty income ratio, education, cigarette smoking, physical activity, CKD, CVD, cancer history, chronic respiratory disease, albumin, and HbA1c.
Data is logarithmically transformed.
Testosterone/estradiol.
P‐values <0.05 are shown in bold. aHR, adjusted hazard ratio; CI, confidence interval; CVD, cardiovascular disease; NA, not applicable; NE, too few events occurred in one group.
In males with prediabetes, higher estradiol (adjusted HR [aHR] = 0.17, 95% CI: 0.07–0.43) or testosterone (aHR = 0.39, 95% CI: 0.31–0.50) was significantly associated with lower risk of all‐cause mortality. Similarly, higher estradiol (aHR = 0.12, 95% CI: 0.04–0.32) or testosterone (aHR = 0.36, 95% CI: 0.27–0.48) was significantly associated with lower CVD mortality risk.
In females with diabetes, we observed a significant association between higher estradiol levels (aHR = 0.22, 95% CI: 0.06–0.83) or T/E ratio (aHR = 0.18, 95% CI: 0.04–0.73) with a reduced risk of all‐cause mortality. A similar trend was noted for CVD mortality risk, though it did not reach statistical significance.
Among non‐diabetic participants, no significant associations were observed between hormone levels and mortality.
DISCUSSION
In our study, we found that for non‐diabetic individuals, there was no relationship between estradiol, testosterone, or the T/E ratio and mortality outcomes, regardless of gender. However, in prediabetic men, both estradiol and testosterone levels were associated with a lower risk of all‐cause and cardiovascular mortality. In diabetic women, higher testosterone levels and the T/E ratio were associated with significantly lower all‐cause mortality, with the increase in T/E ratio showing a slightly stronger protective association. A similar trend was observed for cardiovascular mortality, although it did not reach statistical significance.
The pathogenesis and evolution of type 2 diabetes mellitus depends on interactions between genetic factors and lifestyle factors, such as diet and exercise, and overall lifestyle 5 , 6 , 7 . However, a range of studies and reviews in the literature also supports the idea that sex hormones, particularly testosterone and estradiol, also play a pivotal role in processes that affect the development of metabolic disease, such as diabetes and metabolic syndrome 8 , 9 . Since elucidation of such “gonadal‐metabolic axis” could contribute to the understanding of diabetes progression and refine therapeutic approaches, the present study, based on data from the NHANES, investigated the association between endogenous levels of estradiol and testosterone and mortality rates among adults diagnosed with prediabetes and diabetes, as well as those without glucose intolerance. The findings expand our current understanding of the links between sex steroid hormones and survival outcomes, specifically among individuals with prediabetes and diabetes in a real‐world setting, with observed sex‐specific differences.
Although the pathophysiology of the observed phenomena cannot be fully elucidated in this study, the findings of this study can be viewed in the context of existing reports in the medical literature. Presenting results of a sub‐study of the TRAVERSE Randomized Clinical Trial, for instance, one very recent paper reported that low testosterone levels in men predicted a higher risk of developing insulin resistance 10 .
The effects of testosterone on health outcomes and mortality have been well‐documented in the medical literature. One meta‐analysis, published in 2018, suggested that low testosterone predicted elevated CVD mortality, albeit with marked heterogeneity among included studies 18 . A more recent study based in Europe reported a link between elevated testosterone level and lower risk of conversion from prediabetes to manifest diabetes in males 19 . That study revealed that males with higher testosterone experienced more favorable glucose metabolism, as evidenced by reduced HbA1c levels, lower stimulated glucose levels, and higher insulin sensitivity, although no connection between testosterone levels and glucose metabolism was elucidated in prediabetic females 19 .
Another research group reported testosterone level to be reduced in diabetic men, while also being inversely related to blood glucose and cortisol levels, plus the study found that low testosterone placed diabetic men at risk for a hypercoagulable state 20 . Meanwhile, a systematic review and meta‐analysis published in 2018 revealed that higher testosterone level could decrease the risk of type 2 diabetes significantly in men 21 , while an eariler study found low testosterone to be associated with worsened atherosclerotic disease markers in middle‐aged patients with type 2 diabetes 22 . More recently, a Taiwan‐based retrospective cohort study found reduced total serum testosterone to be associated with a higher 10‐year risk of cardiovascular events in young men aged 30–49 years 23 , while studies published back in a decade ago have already elucidated a correlation between low testosterone incident metabolic syndrome 24 .
As for therapeutic implications of the aforementioned studies on testosterone and diabetes, although one study published in 2017 suggested that testosterone replacement, along with phosphodiesterase 5‐inhibitors and statin treatment could reduce mortality in diabetic, hypogonadic men, it is difficult to distinguish between the contributions of these three interventions 25 . Other studies have failed to establish a benefit of such treatments 10 , 26 .
Relevant to the estradiol aspect of the findings of the present study, one analysis published in 2022 elucidated an association between low estrogen and elevated cardiovascular disease mortality in men 27 . While other published studies also seem to corroborate such an estrogenic phenomenon in men, including implications of the T/E ratio, women have often been excluded from the analysis 12 , 28 . One notable exception, however, is a 2022 study showing that, in both men and women with ischemic heart disease, higher T/E ratio was associated with a lower long‐term risk of fatal events 29 . The present study adds additional female data to the knowledgebase.
Our results indicate that higher testosterone levels and T/E ratio are both associated with a lower mortality risk in female with diabetes. These findings need further interpretation, particularly regarding the biological meaning of the T/E ratio, which is considered to reflect the balance between androgenic and estrogenic effects in the body. The observations can be explained through several potential mechanisms. First, testosterone at physiological levels improves insulin sensitivity and aids in glucose metabolism, which may counteract the metabolic dysfunctions often present in diabetic women, ultimately reducing mortality risk 30 . Estradiol, while protective against some health conditions, can also promote the storage of fat and affect metabolic processes when not balanced by testosterone. In postmenopausal women, where estradiol levels decrease significantly, a higher T/E ratio may indicate a relatively healthy androgen status and a hormonal balance that supports improved metabolic control, which is crucial for women with diabetes. Additionally, testosterone can promote vasodilation through nitric oxide production 31 , which is particularly relevant for diabetic women at elevated risk of CVD. A higher T/E ratio may reflect a healthier androgenic state that supports vascular health and reduces cardiovascular events. Further, testosterone also helps maintain muscle mass and strength, preventing frailty—a common issue in diabetic women that contributes to higher mortality 32 . A higher T/E ratio might thus indicate better muscle preservation, leading to improved overall health and survival.
Among men with established diabetes, due to their already higher baseline testosterone levels than women, the protective effects of testosterone may not be as pronounced, as shown in our analyses. In contrast, women start with lower testosterone levels, so even a slightly increase in testosterone levels or T/E ratio can have more profound protective effects.
Another aspect of our observations is that testosterone is associated with lower mortality risk in prediabetic men but not in diabetic men. This can be explained by the progression of metabolic dysfunction and hormonal balance as the disease advances. In the prediabetic stage, men still maintain relatively better insulin sensitivity and metabolic function, and testosterone plays a critical role in supporting these processes. This is supported by a recent study documented increase in testosterone levels is linked with a lower risk of conversion of prediabetes to manifest diabetes in prediabetic males 19 . The protective effect of testosterone on glucose metabolism, fat accumulation, and muscle mass may delay diabetes progression and help reduce mortality risk 33 . As men progress from prediabetes to diabetes, worsening metabolic dysfunction, including chronic hyperglycemia, insulin resistance, and inflammation, may outweigh the benefits of testosterone 34 . This explains why testosterone levels are no longer protective against mortality in diabetic men.
Similarly, estradiol levels are protective against mortality in prediabetic men but not in diabetic men due to the changing dynamics of metabolic health and hormone function as the disease progresses. In prediabetic men, estradiol, which is largely derived from testosterone via aromatization, plays a role in cardiovascular protection by promoting vasodilation, reducing inflammation, and maintaining vascular integrity 35 . These effects help counteract early cardiovascular risks and metabolic disturbances, which might contribute to a lower risk of mortality in prediabetic men. However, as men progress from prediabetes to diabetes, the benefits of estradiol may be diminished by the worsening of insulin resistance, chronic hyperglycemia, and increased inflammation associated with diabetes. These metabolic stressors can overwhelm the protective effects of estradiol on overall health. As a result, estradiol may no longer provide significant protection against mortality in men who have developed diabetes.
Given the state of knowledge in the literature, the findings of the present study expand the current understanding of the links between sex steroid hormones and survival outcomes. The results apply to individuals with prediabetes and diabetes in a real‐world setting and also reveals sex‐specific differences in how these hormones are linked to mortality risk. It should be noted that the above explanations are postulations due to the observational nature of our study, where the true pathways remain unclear. To be sure, more research is needed, particularly regarding how sex hormones affect long‐term outcomes. Additionally, studies are needed that investigate the underlying biological pathways to further elucidate these associations before targeted interventions can be developed. Further research into the relationships between sex steroids and mortality could enhance the development of personalized therapeutics for diabetes prevention and management.
STRENGTHS AND LIMITATIONS
The strength of this study lies in its utilization of the NHANES database, which provides a diverse and representative sample of the US population; this ensures that the findings are generalizable and robust. This comprehensive dataset allows for the examination of a wide range of demographic and health‐related variables, which enhances the validity and applicability of the study results. Additionally, the standardized methodology used in NHANES for data collection and hormone measurement ensures consistency and reliability across the study population. One notable limitation of the present study is the method of hormone level measurement. NHANES uses a single measurement of estradiol and testosterone levels, which may not accurately reflect long‐term hormonal status. Hormone levels can fluctuate, due to various factors such as time of day, recent physical activity, and stress. Potentially, these factors can introduce variability that a single measurement cannot capture. This limitation may affect the ability to draw conclusions regarding the chronic effects of hormone levels on mortality risk. Furthermore, while the NHANES database is extensive, it is observational in nature, which limits the ability to establish causality between hormone levels and mortality outcomes. Our study examines long‐term mortality, but due to the NHANES data collection protocol, only a single blood sample taken at baseline was available. As diabetes, prediabetes status, and hormone levels can fluctuate over extended observation periods, caution is necessary when interpreting the results. There also may be residual confounding factors that were not accounted for in the analysis, such as lifestyle factors, environmental exposures, and genetic predispositions, which could influence both hormone levels and mortality risk. To address these limitations, future research should include longitudinal studies that track hormone levels over time to better understand their long‐term effects on health outcomes. Future studies should explore the underlying biological pathways to clarify these associations before developing targeted interventions. Experimental studies and randomized controlled trials, in particular, could establish causative links and deepen understanding of the biological mechanisms involved.
In conclusion, our study highlights that hormone levels, specifically estradiol and testosterone, have varying associations with mortality outcomes depending on glycemic status and sex. While no significant correlations were found among non‐diabetic individuals, prediabetic men showed a protective relationship between higher estradiol and testosterone levels and both all‐cause and cardiovascular mortality. In diabetic women, higher testosterone levels and the testosterone‐to‐estradiol ratio were associated with lower all‐cause mortality, with a similar but statistically non‐significant trend observed for cardiovascular mortality. These findings suggest that hormone levels may play a role in mortality risk among individuals with altered glucose metabolism, warranting further investigation into the underlying mechanisms.
DISCLOSURE
The authors declare no conflict of interest.
Approval of the research protocol: N/A.
Informed consent: N/A.
Approval date of registry and the registration no. of the study/trial: N/A.
Animal studies: N/A.
FUNDING
This study was supported by the National Key R&D Program of China (2021YFA0910100).
ACKNOWLEDGMENTS
None.
DATA AVAILABILITY STATEMENT
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets analyzed during the current study are available from the corresponding author on reasonable request.