Volume 15

Background

Assessing the generalizability of a study population—also referred to as external validity—is essential in epidemiologic research because it determines the extent to which findings from a specific sample can be applied to broader populations. While internal validity refers to the accuracy of a study’s results within the sample studied (i.e., whether the observed associations are free from bias, confounding, or measurement error), external validity addresses whether those findings hold true across different groups, settings, or times.¹ Without careful attention to generalizability, interventions or policy recommendations may be ineffective or even harmful when applied outside the study context, especially in populations with differing sociodemographic or clinical characteristics.² In studies of maternal and reproductive health, this is particularly important given the wide variability in risk factors, access to care, and outcomes across geographic and racial/ethnic populations. Preterm birth (PTB), a leading cause of infant morbidity and mortality in the United States³, serves as an especially important lens for examining maternal health equity and risk factors.

To better understand the commonalities and differences among Utah women of reproductive age compared to the national population, we leveraged the Pregnancy Risk Assessment Monitoring System (PRAMS), a population-based surveillance project conducted by the Centers for Disease Control and Prevention (CDC) and state health departments.⁴ Specifically, the objective of our study was to use the PRAMs Phase 8 questionnaire to compare Utah state versus United States (US) national population characteristics overall, and by preterm birth status, among women who participated in PRAMs between 2016 and 2022.

Methods

Study Population

We utilized data from the US national PRAMs Phase 8 questionnaire (2016–2022). A detailed description of the PRAMS surveillance system methodology and protocols can be found elsewhere.⁴ In brief, the PRAMS sample is stratified so that subpopulations of particular public health interest can be oversampled. Stratification variables vary by state and may include Medicaid status, birth weight, maternal race/ethnicity, geographic area, and smoking status. Utah oversamples women of lower education levels and infant birth weight to purposely

capture data on a known high-risk population. Each participating site draws a stratified random sample of 100 to 250 new mothers (2–6 months postpartum) every month from a frame of eligible birth certificates. New mothers are contacted via mailed questionnaire (available in English and Spanish) multiple times and telephone follow-up. The expected response rate according to the CDC is 50% nationwide. An informed consent document is included within each survey packet. Consent is implied if the survey is completed. A total of 249,970 women, reflecting an estimated population of 12,275,282 women, completed the PRAMs questionnaire 2016–2022 and were included in the present study.

For the questionnaire, women report on various health, lifestyle, psychosocial, and reproductive related factors that occurred before, during, and after their index birth. Sociodemographic and birth outcome information is captured via linked birth records

Statistical Analysis

Descriptive statistics (frequencies for categorical variables and means [standard error] for continuous variables) were used to explore differences in PRAMs participant characteristics, overall and by preterm birth status (<37 weeks vs ≥37 weeks), between the Utah and US national study populations. Stata (StataCorp, College Station, TX) was used for the analyses. All analyses accounted for the complex sampling designs.⁴

Ethics Approval

The University of Utah Institutional Review Board deemed the survey and administration procedures as surveillance and hence not human research.

Results

Utah’s maternal population, while sharing some similarities with national trends, also displayed notable demographic and behavioral differences. For example, women giving birth in Utah, compared to the US population, were more likely to be white (88.9% vs. 69.7%), privately insured (59.3% vs. 49.6), have received infertility treatment (6.9% vs 2.3%), wanted their pregnancy then or sooner (67.6% vs 60.6%), and have depression (19.6% vs 15.0%) or anxiety (30.2% vs 24.3%). Women giving birth in Utah, compared to the US population, were less likely to live in a rural area (9.5% vs 15.6%), be nulliparous (35.1% vs. 39.0%), smoke (7.2% vs. 15.0%) or consume alcohol (28.2% vs. 57.5% nationally) prior to pregnancy (Table 1). Utah women, compared to the nation, also tended to have higher educational attainment (72.1% vs 63.9% with some college or above) and household income levels (63.5% vs 55.1% at $40,000 or above annually) compared to the national average.

Nationally, PTB affected approximately 9% of births between 2016 and 2022, which was slightly less prevalent in Utah (8%). Subgroup analyses suggest that many of the risk factors for PTB are similarly associated with PTB in both Utah and the broader U.S. population (Table 2). For example, women who have a preterm labor, compared to those without preterm labor, are more likely to be older, black, Hispanic, of lower income and education, and more likely to have an unintended pregnancy. However, a few notable differences between the PRAMs national and Utah samples were observed. Among women diagnosed with diabetes or hypertension, 17.1% and 21.3%, respectively, had a preterm birth for PRAMs index pregnancy in the nation, compared to 20.6% and 25.5% respectively in Utah. Among women who experienced physical abuse in the year prior to pregnancy, 13.2% had a preterm birth for PRAMs index pregnancy in the nation, compared to 18.8% in Utah. Finally, among women with a prior preterm birth, 27.5% had a preterm birth reported for the PRAMs pregnancy, compared to 23.9% in Utah.

Conclusions

Overall, we found that while the relationship between population characteristics and prevalence of preterm birth was consistent in direction and magnitude between Utah and the US population of women of reproductive age, there are notable differences in socio-demographics and lifestyle factors that could impact external validity of Utah-based studies.  Specifically, Utah’s relatively low prevalence of Black birthing individuals limits the state’s capacity to explore racial disparities in maternal and perinatal outcomes—one of the most pressing public health challenges nationwide.⁵ For instance, while prevalence of preterm labor was similar in Utah compared to the US, our and prior research has shown that Black women experience a significantly higher rate of PTB compared to white women, a disparity that may be largely driven by structural racism and chronic stress.⁶ In Utah, the small proportion of Black births (1.6%) precludes robust stratified analyses, necessitating cautious interpretation of generalizability in racially diverse contexts.

Moreover, Utah’s higher rates of infertility treatment, depression, and anxiety, may signal differences in access to reproductive care and psychological distress that can influence maternal outcomes. These unique aspects position Utah as an important, albeit non-representative, case study in maternal health—a state where certain protective factors (e.g., higher SES, lower smoking and alcohol rates) as well as certain risk factors (e.g., depression/anxiety) may be more prevalent—can still offer key insights into prevention and intervention strategies relevant across the U.S.

Finally, in our preterm birth-stratified analyses, we observed that in Utah, compared to the rest of the nation, women with a prior preterm birth were less likely to have a subsequent preterm birth reported in PRAMs. In contrast, Utah women—regardless of prior preterm birth status—who reported depression, anxiety, or physical abuse in the year prior to pregnancy were more likely to have a preterm birth reported in PRAMs.

In sum, leveraging PRAMS data from both Utah and the national sample allows researchers and policymakers to assess the degree to which Utah’s maternal health trends align with or diverge from broader patterns. This comparative approach strengthens the evidence base for tailoring public health interventions while ensuring they remain responsive to both local and national needs.

Acknowledgements

We acknowledge PRAMS Working Group and the Centers for Disease Control and Prevention (CDC). Research reported in this publication was also supported by the National Institutes of Health, National Institute of Aging (K01AG058781 [Dr Schliep]). The content is solely the responsibility of the authors and does not necessarily represent the official views of the CDC or the National Institutes of Health.

References

1. TL Lash TV, S Haneuse, KJ Rothman. . Modern Epidemiology. 3rd ed. vol 4th Edition. Wolters Kluwer; 2021.

2. Stuart EA, Bradshaw CP, Leaf PJ. Assessing the generalizability of randomized trial results to target populations. Prev Sci. Apr 2015;16(3):475-85. doi:10.1007/s11121-014-0513-z

3. Blencowe H, Cousens S, Chou D, et al. Born too soon: the global epidemiology of 15 million preterm births. Reproductive health. 2013;10:1-14.

4.  Shulman HB, D’Angelo DV, Harrison L, Smith RA, Warner L. The Pregnancy Risk Assessment Monitoring System (PRAMS): Overview of Design and Methodology. Am J Public Health. Oct 2018;108(10):1305-1313. doi:10.2105/AJPH.2018.304563

5. Petersen EE. Racial/ethnic disparities in pregnancy-related deaths—United States, 2007–2016. MMWR Morbidity and mortality weekly report. 2019;68

6. Alhusen JL, Bower KM, Epstein E, Sharps P. Racial discrimination and adverse birth outcomes: an integrative review. Journal of midwifery & women’s health. 2016;61(6):707-720.

Citation

Avondet E, Bah H, Hernandez-Nietling A, Ladd S, Toro J, Schliep K, Silva G, Vallejo-Riveros S, & Yeaman J. (2026). Can Utah Tell a National Story? Evaluating External Validity in Maternal Health Research. Utah Women’s Health Review. doi: 10.26055/d-f3b8-y628

PDF

View / download

Abstract

Background: While plausible mechanisms exist for an association between endometriosis and hypertriglyceridemia, prior studies have shown inconsistent findings, possibly due to the inability to assess endometriosis severity or subtypes.

Objectives: Among 473 premenopausal individuals undergoing gynecologic laparoscopy, the present study assessed the association between incident endometriosis and non-fasting serum triglycerides.

Methods: Participants were recruited (2007–2009) among women undergoing diagnostic or therapeutic laparoscopy or laparotomy (for any indication) and who had no prior endometriosis diagnosis. Endometriosis was categorized using American Society for Reproductive Medicine staging (I−IV). Typology was defined as superficial endometriosis [SE], ovarian endometrioma [OE], and deep infiltrating endometriosis [DE]. We collected biospecimens, anthropometrics, and self-reported sociodemographics at enrollment, prior to surgery. We evaluated the association between endometriosis diagnosis, stage, typology, and triglyceride concentrations using non-fasting female cutpoints (normal <175mg/dL vs hypertriglyceridemia ≥175mg/dL) via generalized linear models. We also evaluated whether the association differed by menstrual cycle phase.

Results: Among the cohort, 108 women (23%) had hypertriglyceridemia > 175 mg/dL. Overall, endometriosis was not associated with prevalence of hypertriglyceridemia (adjusted prevalence ratio (aPR): 1.24, 95% CI: 0.87, 1.77), after accounting for baseline age, race/ethnicity, marital status, BMI, income, and serum cotinine. However, this varied by stage and type. Women with moderate to severe stage endometriosis had a higher aPR for hypertriglyceridemia, 1.74 (95% CI: 1.03, 2.95), compared to those without endometriosis. DE combined with OE was associated with a 3.59 higher aPR (95% CI: 2.33, 5.54) for hypertriglyceridemia. A pattern emerged showing stronger associations in the follicular phase compared to the luteal phase.

Conclusions: In summary, while no association was observed for overall endometriosis and hypertriglyceridemia, we observed moderate to severe stage endometriosis as well as DE and OE endometriosis was associated with prevalence of hypertriglyceridemia.

Background

Endometriosis is a chronic gynecologic condition without an established causal pathway.¹ It is considered a major reproductive health concern in the US, severely impacting more than 6.5 million women ages 15–44.^2,3 Endometriosis may also lead to debilitating symptoms that can severely impact quality of life such as chronic pelvic pain, dysmenorrhea, and infertility.^4,5

Prior research has suggested that endometriosis may be linked to cardiovascular disease event. In particular, women with endometriosis are at an increased risk of coronary heart disease, cerebrovascular disease, and stroke.⁶ Therefore, the impact of endometriosis on lipid profiles such as triglycerides is of great interest. This is partly due to conditions such as elevated triglycerides also regarded as a risk factor for heart disease and stroke.⁷

Research on the associations between endometriosis and elevated triglyceride levels is currently limited, with very few studies exploring hypertriglyceridemia (defined as triglyceride levels of 150 mg/dl or higher). In the limited existing research, studies have  been inconsistent.^8-13 Melo et al. ⁸ observed that triglyceride levels were higher in women with endometriosis (105.3 mg/dl) compared to women without endometriosis (83 mg/dl). Similarly, }¹²¹² reported higher mean triglyceride levels in women with endometriosis (1.87 mmol/L) compared to a control group (1.38 mmol/L).

In contrast to Melo et al. ⁸  and Li et al. ¹² research, Zheng et al. ⁹ observed higher triglycerides levels in women with no endometriosis (1.23 mmol/L) compared to 1.12 mmol/L in women with endometriosis. This conflict could be attributed to its use of a study sample from a single health center, having a predominantly Asian participant demographic, and study participants with no endometriosis being older and having a higher Body Mass Index (BMI).

However, Zheng et al. ⁹ did observe in women with endometriosis, higher staging was associated with higher triglyceride concentrations (moderate 0.96 mmol/L vs severe endometriosis 1.26 mmol/L).⁸ The pattern of higher concentrations among higher staged endometriosis was also observed by Verit et al. ¹¹ However, most studies have not been able to include data on stage and no prior studies we are aware of have considered endometriosis typology.

In addition to not assessing severity or type of endometriosis, prior studies have not accounted for triglyceride fasting status and phase of menstrual cycle (follicular vs luteal). Epidemiological research has suggested that non-fasting vs fasting triglycerides better predict health outcomes, such as cardiovascular disease.¹⁴ Additionally, detailed within-in woman assessments have shown high variability in lipid levels by menstrual cycle phase, with higher levels documented in the follicular phase.¹⁵ Further, current research has not accounted for multiple confounding factors that can impact the relationship between endometriosis and hypertriglyceridemia. In particular, the role of physical activity, alcohol and caffeine consumption, and smoking. The present study aims to address prior gaps in the literature by assessing the association between endometriosis diagnosis, staging or severity, typology, and the occurrence of hypertriglyceridemia, considering fasting status, menstrual cycle phase, and multiple confounding factors assessed prior to incident endometriosis diagnosis.

Methods

Cohort Selection

The present study utilized data from the Endometriosis, Natural History, Diagnosis and Outcomes (ENDO) study (2007–2009). ²  The ENDO study was designed to 1) examine the scope and magnitude of endometriosis by diagnostic method and choice of comparison group; and 2) investigate the relationship between endocrine disrupting chemicals (EDCs) and occurrence of gynecologic pathology, including endometriosis. Eligibility criteria for enrollment in the ENDO study includes: 18–44 years of age, currently menstruating, no breast feeding ≥ 6 months, no cancer history other than nonmelanoma skin cancer, and no injectable hormonal treatment within the past 2 years.

Participants included 473 premenopausal women undergoing diagnostic or therapeutic laparoscopy or laparotomy regardless of clinical indication (pelvic pain, pelvic mass, menstrual irregularities, suspected fibroids, tubal ligation, and infertility) from clinical centers in Salt Lake City, UT and San Francisco, CA. The University of Utah Institutional Review Board (IRB) approved the study (IRB #00021614), and all participants gave written informed consent before enrollment and data collection.

Data Collection

Standardized data collection included a baseline personal interview, collection of biospecimens (blood, urine, peritoneal fluid, omental fat, and endometriosis implants when available), and in-person anthropometric assessment. ²   The baseline questionnaire, anthropometric assessment, and specimen collection occurred before surgery. Socio-demographics, reproductive and medical history, and lifestyle information were self-reported. For the anthropometric assessment, height was measured with a portable stadiometer and weight with electronic scales. Body Mass Index (BMI) was calculated from height and weight measurements (weight [kg] / height [m²]). BMI was categorized according to the Centers for Disease Control and Prevention classification <18.5 kg/m²; 8.5-24.99 kg/m²; 25.0-29.99 kg/m²; and ≥ 30.0 kg/m²). Serum cotinine (ng/mL) was measured and used to evaluate smoking.

Outcome: hypertriglyceridemia

Hypertriglyceridemia was defined as non-fasting triglyceride concentration level ≥175mg/dL, as this has been determined in prior research to be the optimal non-fasting cut-point for mid-life women.¹⁶ A sensitivity analysis was conducted using the standard cut-point of ≥150 mg/dL.¹⁷

Exposure: endometriosis diagnosis, staging, and typology

The exposure of interest was visualized endometriosis diagnosis (yes/no) along with endometriosis stage and typology. For endometriosis, all surgeons participating in the ENDO study were trained in the diagnosis and staging of endometriosis. The surgeons completed a standardized operative report immediately after surgery to capture the degree of endometriosis and gynecologic and pelvic pathology.^2,18    Endometriosis staging was categorized using the revised American Society for Reproductive Medicine (rASRM) disease stage. The rASRM uses a weighted point score to categorize endometriosis staging: stage I, minimal (scores 1-5); stage II, mild (scores 6-15); stage III, moderate (scores 16-40); and stage IV, severe (scores >40).¹⁹ Endometriosis typology was assessed using the rASRM form. Women with only superficial lesions on the ovary or peritoneum were considered to have superficial endometriosis (SE), women with deep lesions (>5mm invasion) noted in the peritoneum or with obliteration of the posterior cul-de-sac were considered to have deep infiltrating endometriosis (DE), and women with deep lesion of any size noted in the ovary were considered to have ovarian endometrioma (OE). Women who had deep ovarian and peritoneal lesions were considered to have OE and DE.^20,21

Due to sample size limitations, endometriosis staging was reclassified into minimal to mild (stage I/II) and moderate to severe (stage III/IV) endometriosis. Typology was also classified into SE only, OE or DE, and OE and DE. “No endometriosis” served as the comparison for diagnosis, staging, and typology. Women with “No endometriosis” is also defined as women with no endometriosis but with other gynecological conditions and women with no endometriosis with normal pelvis.

Covariates

Confounders were determined via literature review and the use of directed acyclic graphs.²² Our primary models adjusted for baseline age (continuous), race and ethnicity (Hispanic vs non-Hispanic; non-white vs white), marital status (not-married vs married), BMI (continuous, kg/m²), income (Below poverty Line,  ≤180% of poverty Line, vs > 180% of poverty line) and serum cotinine (continuous, ng/ml). Additional covariates considered included level of physical activity (low, moderate, high), history of alcohol consumption (yes, no), and average daily caffeine consumption (continuous). We also include models adjusted for self-reported parity, prior to laparoscopy/laparotomy. While endometriosis impacts infertility and consequently parity, parity is known to impact endometriosis.

Statistical Analysis

We used modified Poisson regression with robust standard errors to calculate adjusted prevalence ratios (aPRs) and 95% CIs for the association between endometriosis diagnosis, staging, and typology and hypertriglyceridemia.^23,24 Given that triglyceride levels have been shown to vary by stage of menstrual cycle (follicular and luteal),²⁵ stratified results were presented. Geometric mean concentrations of triglycerides by endometriosis diagnosis, stage, and typology were generated overall and by menstrual cycle phase. We formally assessed whether the association between endometriosis and hypertriglyceridemia may be modified by menstrual cycle phase via the Wald test.

Sensitivity Analysis

We assessed potential non-linearity of triglycerides in relation to endometriosis using restricted cubic splines, adjusting for age, race/ethnicity, marital, categorical BMI, and log serum cotinine variables. Tests for nonlinearity used the likelihood ratio test, comparing the adjusted model with only the linear term to the adjusted model with the linear and the cubic spline terms. Further, we conducted an additional analysis using  the standard hypertriglyceridemia cutpoint of ≥150 mg/dL vs less for comparability with past and future studies.¹⁷ Finally, we considered alternative models adjusting for additional potential confounders including physical activity, caffeine and alcohol consumption, and parity.

ethics Approval

Study participants were remunerated for their time and travel. Full human subjects approval was obtained for the conduct of this study; each of the women provided informed consent before any data collection.²

Results

Descriptive Analyses

Among 473 women in the study, 108 (22.8%) had hypertriglyceridemia (≥175mg/dL) and 190 (40.2%) had endometriosis. Women with endometriosis were more likely to be younger, >180% of the poverty line, and have a lower BMI compared to women without endometriosis (Table 1). Women with hypertriglyceridemia had a higher BMI compared to those without hypertriglyceridemia. Further, women with moderate to severe endometriosis had a higher prevalence of hypertriglyceridemia (35.2%) than women with minimal to mild endometriosis (18.7%) and those with no endometriosis diagnosis (22.6%). Differences were also observed by endometriosis subtype, and women with combined OE and DE endometriosis had the highest prevalence of hypertriglyceridemia (50.0%) (Table 1). In addition, women with combined OE and DE endometriosis had higher mean (169 ± 81 mg/dl) and median [25%, 75%] (179 [99, 215] mg/dl) triglycerides compared to women with no endometriosis (mean=147 ± 101; median [25%, 75%] 121 [90, 166] mg/dl).

Association between endometriosis and hypertriglyceridemia

Overall, women with diagnosed endometriosis had a 1.24 (95% CI 0.87, 1.77) higher prevalence of hypertriglyceridemia after adjusting for age at baseline, race/ethnicity, marital status, BMI, income, and serum cotinine compared to women without endometriosis (Table 2). This pattern varied by endometriosis severity and typology. Compared to women with no endometriosis, women with moderate to severe endometriosis had a 1.74 (95% CI 1.03, 2.95) higher adjusted prevalence of hypertriglyceridemia; while there was no association observed with minimal to mild (Stage I/II) endometriosis (aPR: 1.06, 95% CI: 0.70, 1.59). When we investigated endometriosis typology, we observed that women with combined OE and DE experienced a 3.59 (95% CI 2.33, 5.54) higher adjusted prevalence of hypertriglyceridemia compared to those without endometriosis.

Role of menstrual cycle

On average, among everyone in the cohort, there was little difference in hypertriglyceridemia prevalence between women assessed in the follicular phase (22.0%) versus the luteal phase (21.9%) (Table 1). However, among women diagnosed with endometriosis, hypertriglyceridemia prevalence was higher in the follicular phase (26.7%) versus the luteal phase (20.6%). (Table 3). While there was no clear pattern for staging (Table 3), we found the highest prevalence of hypertriglyceridemia among women with OE and DE in the follicular phase (70.0%) versus the luteal phase (33.3%) (Table 3). Indeed, after adjustment, women with OE and DE were 4.38 times more likely to have hypertriglyceridemia (95% CI: 2.36, 8.12) in the follicular phase compared to 2.92 (95% CI: 1.06, 8.04) in the luteal phase (Table 3). Continuous assessment of geometric mean concentrations of serum triglyceride indicated a pattern of higher concentrations in the follicular phase, versus luteal phases, for women with endometriosis, severe staging, and most notably typology as evidenced by the non-overlapping 95% CIs (Supplementary Table 2). Restricted cubic splines revealed a linear relationship between endometriosis and serum triglycerides; however, precision was low due to limited power in our study (Supplementary Figure 1).  Results were slightly attenuated when evaluating hypertriglyceridemia at the level of ≥150 mg/dL vs less (Supplementary Table 1). Results did not appreciably change when considering other confounding factors (Supplementary Table 3).

Commentary

Principal Findings

In this study, we observed a higher prevalence of hypertriglyceridemia among women with moderate to severe (III/IV) endometriosis and women with combined OE and DE endometriosis typology, compared to women with no endometriosis diagnosis, after taking into account multiple confounding factors. The results also showed that triglyceride levels and hypertriglyceridemia risk estimates were higher in the follicular phase compared to the luteal phase among women with endometriosis but no difference in women without endometriosis.

Strengths of the study

The present study is novel in that it is one of a few studies that directly assessed the associations between endometriosis diagnosis, staging, typology, and risk of hypertriglyceridemia. The ENDO study had very few exclusion criteria, making our results generalizable to other women undergoing laparoscopy/laparotomy for multiple indications.

Limitations of the data

A limitation of this study is that it does not include fasting blood draws. This limitation may impact the strength of the association of hypertriglyceridemia. However, research has shown that non-fasting triglyceride levels are a better predictor of cardiovascular risk than fasting triglycerides.²⁶ Further, due to the small sample sizes, we lacked precision in some of our estimates, notably when looking at typology and in our spline analyses assessing potential non-linear relationships. Finally, while our study had few exclusion criteria, our sample was made up predominately of white non-Hispanic women of higher socioeconomic status. Future studies assessing the relationship between endometriosis and triglycerides should make sure to include women of underrepresented minorities and of varying socioeconomic classes for more generalizability.

Interpretation

Endometriosis staging and hypertriglyceridemia

We observed that moderate to severe (III/IV) endometriosis was more strongly associated with hypertriglyceridemia than minimal to mild (I/II) endometriosis. Prior studies have reported associations between elevated triglyceride levels and endometriosis staging. ^8,9,11,12 To illustrate, Verit et al. ¹¹ and Zheng et al. ⁹ both reported increasing triglycerides levels by increasing endometriosis severity. In the Verit et al. study, mean triglyceride levels were 135.0 mg/dL in women with no endometriosis, 157.3 mg/dL in women with minimal to mild endometriosis, and 189.0 mg/dL in women with moderate to severe endometriosis. Importantly, our study is also unique in that it is the only one that includes a multivariable assessment on the risk of hypertriglyceridemia or triglyceride levels ≥ 175 mg/dL.

Poor lipid metabolism in women with endometriosis is a potential clinical pathway for hypertriglyceridemia occurrence.¹² Sphingomyelin, a class of phospholipids and a critical component of the plasma membranes, is an important determinant of lipoprotein metabolism.^27,28 While sphingomyelin is essential for cellular integrity, its accumulation—potentially exacerbated by endometriosis—can disrupt lipid metabolism and signaling pathways, contributing to elevated lipid levels in the bloodstream and tissues. Beyond lipid handling, sphingolipids more broadly are implicated in generalized inflammatory processes, which may explain why chronic inflammation from endometriosis, or indeed from other conditions, can contribute to increased cardiovascular risk.²⁷ Notably, research has associated higher-stage endometriosis with elevated sphingomyelin levels, supporting our finding that hypertriglyceridemia risk was highest in women with moderate to severe endometriosis compared to those with minimal to mild disease or no endometriosis. Thus, both lipid-specific and inflammation-mediated pathways may be relevant in linking endometriosis to cardiometabolic risk.^27,28

Endometriosis typology and hypertriglyceridemia

The present study also showed an association between endometriosis typology and hypertriglyceridemia. We observed that combined ovarian and deep infiltrating endometriosis (OE and DE) had a higher risk of hypertriglyceridemia than SE or OE alone. Importantly, we found no study that has directly assessed hypertriglyceridemia risk by endometriosis typology. The study of Vouk et al.,²⁹ however, documented elevated concentrations of sphingomyelins in women with ovarian endometriosis. As previously described, elevated levels of sphingomyelin disrupt lipid metabolism, which likely results in an abnormal increase in lipid uptake in the cells and tissue. Further, the study of Bedin et al.³⁰ examined lipid nanoparticle concentrations, an analogue to low density lipoprotein (LDL) receptors, in deep endometriotic tissues. The results suggest increased LDL uptake by endometriotic tissue. Although the study focuses on LDL, it is worth noting that LDL and triglycerides share similar clinical implications.

Role of the menstrual cycle phase

When we investigated whether cycle phase influenced the association between endometriosis and triglycerides, we found that the prevalence of hypertriglyceridemia and geometric mean triglyceride concentrations in women with endometriosis was higher in the follicular phase than in the luteal phase. Estrogen concentration, also associated with lipid metabolism, is known to rise with ovulation, possibly leading to higher lipid levels.¹⁵ The effect is more pronounced in the follicular phase as estrogen levels peak. The fact that we only found triglycerides to be higher in the follicular versus luteal phase among women with endometriosis may be related to women with endometriosis having higher estrogen levels,³¹ however further research is needed to confirm these novel findings. Additionally, while our findings collaborate the positive association between estrogen and lipoprotein cholesterol,^15,32 more research looking specifically at triglycerides is needed.

Conclusions

Hypertriglyceridemia has far-reaching consequences for women’s health, requiring increased attention. The condition is associated with an increased risk of all-cause mortality and incident cardiovascular disease events.³² There are also documented associations with pregnancy-related complications such as preeclampsia, gestational diabetes, and fetal macrosomia.^33,34 It may also be important for health professionals to inquire about the menstrual cycle phase during routine metabolic panels, as there is variability in triglyceride levels observed across different phases of the menstrual cycle, which can impact the interpretation of the test results. More research is also needed on the impact of endometriosis severity and localization endometriosis (staging vs typology) on triglycerides across the menstrual cycle phase.

In summary, while overall we found that women with, compared to without endometriosis, had a null association with hypertriglyceridemia, when looking at typology, we found women with ovarian endometrioma combined with deep infiltrating had a four-fold higher prevalence of hypertriglyceridemia. Additionally, women with moderate to severe staging had a two-fold higher prevalence. We also observed differences by menstrual cycle phase. Although research is extensive on the effects of endometriosis on women’s health, few studies exist assessing hypertriglyceridemia risk as an outcome, and even fewer studies specifically focusing on endometriosis staging and typology.

References

1.   Shafrir AL, Farland LV, Shah DK, et al. Risk for and consequences of endometriosis: A critical epidemiologic review. Best Pract Res Clin Obstet Gynaecol. Jul 3 2018;doi:10.1016/j.bpobgyn.2018.06.001

2.   Buck Louis GM, Hediger ML, Peterson CM, et al. Incidence of endometriosis by study population and diagnostic method: the ENDO study. Research Support, N.I.H., Intramural. Fertility and sterility. Aug 2011;96(2):360-5. doi:10.1016/j.fertnstert.2011.05.087

3.   Zondervan KT, Becker CM, Missmer SA. Endometriosis. N Engl J Med. Mar 26 2020;382(13):1244-1256. doi:10.1056/NEJMra1810764

4.   Bulletti C, Coccia ME, Battistoni S, Borini A. Endometriosis and infertility. J Assist Reprod Genet. Aug 2010;27(8):441-7. doi:10.1007/s10815-010-9436-1

5.   Kvaskoff M, Mu F, Terry KL, et al. Endometriosis: a high-risk population for major chronic diseases? Hum Reprod Update. Mar 11 2015;doi:dmv013 [pii]10.1093/humupd/dmv013 [doi]

6.   Marchandot B, Curtiaud A, Matsushita K, et al. Endometriosis and cardiovascular disease. Eur Heart J Open. Jan 2022;2(1):oeac001. doi:10.1093/ehjopen/oeac001

7.   Lee JS, Chang PY, Zhang Y, Kizer JR, Best LG, Howard BV. Triglyceride and HDL-C Dyslipidemia and Risks of Coronary Heart Disease and Ischemic Stroke by Glycemic Dysregulation Status: The Strong Heart Study. Diabetes Care. Apr 2017;40(4):529-537. doi:10.2337/dc16-1958

8.   Melo AS, Rosa-e-Silva JC, Rosa-e-Silva AC, Poli-Neto OB, Ferriani RA, Vieira CS. Unfavorable lipid profile in women with endometriosis. Fertility and sterility. May 01 2010;93(7):2433-6. doi:10.1016/j.fertnstert.2009.08.043

9.   Zheng R, Du X, Lei Y. Correlations between endometriosis, lipid profile, and estrogen levels. Medicine (Baltimore). Jul 21 2023;102(29):e34348. doi:10.1097/MD.0000000000034348

10. Kinugasa S, Shinohara K, Wakatsuki A. Increased asymmetric dimethylarginine and enhanced inflammation are associated with impaired vascular reactivity in women with endometriosis. Atherosclerosis. Dec 2011;219(2):784-8. doi:10.1016/j.atherosclerosis.2011.08.005

11. Verit FF, Erel O, Celik N. Serum paraoxonase-1 activity in women with endometriosis and its relationship with the stage of the disease. Human Reproduction. 2008;23(1):100-104.

12. Li B, Zhang Y, Zhang L, Zhang L. Association between endometriosis and metabolic syndrome: a cross-sectional study based on the National Health and Nutrition Examination Survey data. Gynecol Endocrinol. Dec 2023;39(1):2254844. doi:10.1080/09513590.2023.2254844

13. Santoro L, D’Onofrio F, Campo S, et al. Endothelial dysfunction but not increased carotid intima-media thickness in young European women with endometriosis. Human reproduction (Oxford, England). May 2012;27(5):1320-6. doi:10.1093/humrep/des062

14. Keirns BH, Sciarrillo CM, Koemel NA, Emerson SR. Fasting, non-fasting and postprandial triglycerides for screening cardiometabolic risk. J Nutr Sci. 2021;10:e75. doi:10.1017/jns.2021.73

15. Mumford SL, Dasharathy S, Pollack AZ, Schisterman EF. Variations in lipid levels according to menstrual cycle phase: clinical implications. Clin Lipidol. Apr 1 2011;6(2):225-234. doi:10.2217/clp.11.9

16. White KT, Moorthy MV, Akinkuolie AO, et al. Identifying an Optimal Cutpoint for the Diagnosis of Hypertriglyceridemia in the Nonfasting State. Clin Chem. Sep 2015;61(9):1156-63. doi:10.1373/clinchem.2015.241752

17. Oh RC, Trivette ET, Westerfield KL. Management of Hypertriglyceridemia: Common Questions and Answers. Am Fam Physician. Sep 15 2020;102(6):347-354.

18. Schliep KC, Stanford JB, Chen Z, et al. Interrater and intrarater reliability in the diagnosis and staging of endometriosis. Obstet Gynecol. Jul 2012;120(1):104-12. doi:10.1097/AOG.0b013e31825bc6cf

19. Revised American Society for Reproductive Medicine classification of endometriosis: 1996. Fertility and sterility. May 1997;67(5):817-21. doi:S001502829781391X [pii]

20. Byun J, Peterson CM, Backonja U, et al. Adiposity and endometriosis severity and typology. Journal of minimally invasive gynecology. 2020;27(7):1516-1523.

21. Johnson NP, Hummelshoj L, Adamson GD, et al. World Endometriosis Society consensus on the classification of endometriosis. Human reproduction. 2017;32(2):315-324.

22. Correia KF, Dodge LE, Farland LV, et al. Confounding and effect measure modification in reproductive medicine research. Human Reproduction. 2020;35(5):1013-1018.

23. Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratio and differences Am J Epidemiol 2005;162: 199–200.

24. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. Apr 2004;159(7):702-6.

25. Mumford SL, Schisterman EF, Siega-Riz AM, et al. A longitudinal study of serum lipoproteins in relation to endogenous reproductive hormones during the menstrual cycle: findings from the BioCycle study. J Clin Endocrinol Metab. Sep 2010;95(9):E80-5. doi:10.1210/jc.2010-0109.

26. Bansal, S., Buring JE, Rifai, N. et al. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women.” 2007:JAMA 298(3): 309-316.

27. Jiang X-C, Yeang C, Li Z, et al. Sphingomyelin biosynthesis: its impact on lipid metabolism and atherosclerosis. Clinical Lipidology. 2009;4(5):595-609.

28. Lu J, Ling X, Liu L, et al. Emerging hallmarks of endometriosis metabolism: a promising target for the treatment of endometriosis. Biochimica et Biophysica Acta (BBA)-molecular Cell Research. 2023;1870(1):119381.

29. Vouk K, Hevir N, Ribič-Pucelj M, et al. Discovery of phosphatidylcholines and sphingomyelins as biomarkers for ovarian endometriosis. Human reproduction. 2012;27(10):2955-2965.

30. Bedin A, Maranhão RC, Tavares ER, Carvalho PO, Baracat EC, Podgaec S. Nanotechnology for the treatment of deep endometriosis: uptake of lipid core nanoparticles by LDL receptors in endometriotic foci. Clinics. 2019;74:e989.

31. Chantalat E, Valera MC, Vaysse C, et al. Estrogen Receptors and Endometriosis. Int J Mol Sci. Apr 17 2020;21(8)doi:10.3390/ijms21082815

32. MacGregor KA, Ho FK, Celis-Morales CA, Pell JP, Gallagher IJ, Moran CN. Association between menstrual cycle phase and metabolites in healthy, regularly menstruating women in UK Biobank, and effect modification by inflammatory markers and risk factors for metabolic disease. BMC medicine. 2023;21(1):488.

33. Arca M, Veronesi C, D’Erasmo L, et al. Association of hypertriglyceridemia with all‐cause mortality and atherosclerotic cardiovascular events in a low‐risk Italian Population: the TG‐REAL retrospective cohort analysis. Journal of the American Heart Association. 2020;9(19):e015801.

34. Eppel D, Feichtinger M, Lindner T, et al. Association between maternal triglycerides and disturbed glucose metabolism in pregnancy. Acta Diabetologica. 2021;58(4):459-465.

Supplementary Material

Citation

Adediran E, Farland L, Pollack A, Yan B, Peterson C, Rexrode K, Varner M, Brown B, Spiess S, Stanford J, Myrer R, & Schliep K. (2025). Endometriosis and hypertriglyceridemia, why we care about severity and typology?. Utah Women’s Health Review. doi: 10.26055/d-wycr-2hjm

PDF

View / download

Abstract

Human papillomavirus (HPV) is the most common sexually transmitted infection, with nearly all sexually active individuals exposed to it at some point in their lives. While most HPV infections resolve on their own, persistent infections with high-risk strains, particularly HPV-16 and HPV-18, can lead to cervical cancer. The HPV vaccine is highly effective in preventing infections from the most dangerous strains of the virus and can reduce the risk of cervical cancer by up to 90%. Despite such convincing evidence for cancer prevention, the uptake of HPV vaccination in the US and Utah still lags behind other vaccines. As of 2023, in Utah teens ages 13-17, 61.2% of males and females are up-to-date with their HPV vaccination, increased substantially from 30.5% in 2016. Utah now matches the average percentage of up-to-date in teens in the US (61.4%). While this improvement in up-to-date status of HPV vaccination in Utah adolescents is encouraging uptake still significantly lags behind when compared to other common childhood vaccinations which have an estimated coverage percentage of >90%. Utah has many resources and initiatives aimed at improving our HPV vaccination rate.

Background

Human papillomavirus (HPV) is the most common sexually transmitted infection, with nearly all sexually active individuals exposed to it at some point in their lives. While most HPV infections resolve on their own, persistent infections with high-risk strains, particularly HPV-16 and HPV-18, can lead to cervical cancer. HPV is responsible for more than 90% of cervical cancer cases in the US ¹. Cervical cancer is the fourth most common cancer among women, with an estimated 600,000 new cases and 340,000 deaths globally each year ². The HPV vaccine is highly effective in preventing infections from the most dangerous strains of the virus and can reduce the risk of cervical cancer by up to 90%. First available in 2006, it has been administered over 270 million times globally and has been proven to be safe and effective. The first version of the vaccine, Gardasil 4, provided protection against 4 strains of HPV. In 2014, Gardasil 9 was approved by the FDA and now covers 9 major strains of HPV and the trials leading to its approval found it to be nearly 100% effective in preventing the 6 HPV cancers ³. A recent retrospective analysis of cervical cancer mortality found an overall 62% reduction in cervical cancer mortality among women under the age of 25, corresponding with the first cohort of women for whom HPV vaccination was available ⁴. Despite such convincing evidence for cancer prevention, the uptake of HPV vaccination in the US and Utah still lags behind other vaccines. The HPV vaccine is currently recommended for all children and teens between the ages of 9 and 29, with the typical practice to start the vaccination at age 11, The vaccine is given in a 2 or 3 shot series depending on the age at which the first dose was given⁵. This data snapshot will compare Utah’s HPV vaccine rate among adolescents to that of the US as well as look at cervical cancer rates in Utah and the US.

Data

As of 2023, in Utah teens ages 13-17, 61.2% of males and females are up-to-date with their HPV vaccination. This has increased substantially from 30.5% in 2016. Utah now matches the average percentage of up-to-date in teens in the US (61.4%)⁶ (Figure 1a). While this improvement in up-to-date status of HPV vaccination in Utah adolescents is encouraging, as shown in Figure 1b, HPV vaccine uptake still significantly lags behind when compared to other common childhood vaccinations, including meningococcal conjugate (MenACWY), tetanus, diphtheria, pertussis (Tdap), measles, mumps, rubella (MMR), varicella, hepatitis A and hepatitis B, all of which have an estimated coverage percentage of >90%⁶.

Figure 1.

Given that HPV is the primary cause of cervical cancer and recent retrospective studies demonstrating an overall decrease in cervical cancer mortality in the population for whom HPV vaccination has been available⁴, it makes sense to compare cervical cancer incidence in Utah and across the United States as compared to HPV vaccination coverage. As seen in the heat maps in Figure 2, there is generally a higher incidence of cervical cancer (darker blue) in states in which HPV vaccination coverage is lower (lighter blue). Though Utah is near the national average for HPV vaccination coverage (61.2%), it has a low incidence of rate of cervical cancer (6 cases per 100,000)^6,7.

Figure 2.

What is Being Done?

Utah has implemented several initiatives to improve HPV vaccination rates among adolescents.  Below you will find resources shared in the “Complete Health Indicator Report of Immunizations: HPV, adolescents” from the Utah Department of Health and Human Services⁸, as well as some additional resources and research currently being done in Utah.

• Public Media Campaigns: The state has launched extensive media campaigns to educate the public about the benefits of HPV vaccination and its role in cancer prevention. https://cancer.utah.gov/cancers/hpv/
• Intermountain West HPV Vaccination Coalition: This coalition, encompassing members from 20 states, meets regularly to identify barriers to HPV vaccination, build partnerships, and discuss related policy priorities and research efforts. https://healthcare.utah.edu/huntsmancancerinstitute/about-us/hpv-coalition
• Healthcare Provider Education: The Utah Department of Health and Human Services, in collaboration with organizations like Utah Area Health Education Centers (AHEC), the American Cancer Society, and the Huntsman Cancer Institute, has formed a statewide workgroup focused on educating physicians about HPV vaccination and associated diseases. https://immunize.utah.gov/hpv-information-for-the-public/ The CDC also provides toolkits and resources for physicians on talking to parents about HPV vaccinations, encouraging healthcare providers to discuss it similar to all other routine childhood vaccinations – https://www.cdc.gov/vaccines/vpd/hpv/hcp/index.html
• Targeted Pilot Programs: From July 2021 to May 2022, efforts were made to increase HPV vaccination rates in Utah’s lowest-performing health districts. Primary care clinics in regions such as Bear River, Southeast, Southwest, Tri County, and Utah County participated in tailored, evidence-based interventions to boost vaccination rates. https://utahafp.org/how-you-can-help-increase-hpv-vaccination-rates-in-utah/
• Research and Grants: The Huntsman Cancer Institute, in partnership with the American Cancer Society North Region, has been involved in initiatives aimed at increasing adolescent HPV vaccination rates across five Mountain West states, including Utah. https://uofuhealth.utah.edu/huntsman/labs/kepka/research/grants

Now more than ever, it is important for medical providers, public health students and employees, and defenders of women and children’s health to arm themselves with evidence-backed data to share with family, friends, and representatives to keep increasing the rate of this life-saving vaccine.

References

1. CDC. Cancers Linked With HPV Each Year. Cancer. February 3, 2025. Accessed March 18, 2025. https://www.cdc.gov/cancer/hpv/cases.html

2. Cervical cancer | Knowledge Action Portal on NCDs. Accessed March 18, 2025. https://www.knowledge-action-portal.com/en/content/cervical-cancer

3. History of HPV Vaccination. Accessed March 2, 2025. https://sjr-redesign.stjude.org/content/dam/research-redesign/centers-initiatives/hpv-cancer-prevention-program/hpv-advocacy-campaign/history-hpv-vaccination.pdf

4. Dorali P, Damgacioglu H, Clarke MA, et al. Cervical Cancer Mortality Among US Women Younger Than 25 Years, 1992-2021. JAMA. 2025;333(2):165-166. doi:10.1001/jama.2024.22169

5. HPV Vaccination Recommendations | CDC. February 10, 2025. Accessed March 18, 2025. https://www.cdc.gov/vaccines/vpd/hpv/hcp/recommendations.html

6. CDC. Vaccination Coverage among Adolescents (13 – 17 Years). TeenVaxView. December 20, 2024. Accessed March 18, 2025. https://www.cdc.gov/teenvaxview/interactive/index.html

7. State Cancer Profiles > Incidence Rates Table. Accessed March 18, 2025. https://statecancerprofiles.cancer.gov/incidencerates/index.php?stateFIPS=00&areatype=state&cancer=057&stage=999&race=00&sex=2&age=001&year=0&type=incd&sortVariableName=rate&sortOrder=desc#results

8. IBIS-PH – Complete Health Indicator Report – Immunizations: HPV, adolescents. Accessed September 10, 2025. https://ibis.utah.gov/ibisph-view/indicator/complete_profile/ImmHPV.html

Citation

Dryden S. (2025). HPV Vaccination and Cervical Cancer Rates – How Utah is doing compared to the rest of the US. Utah Women’s Health Review. doi: 10.26055/d-g813-rkcs

PDF

View / download

More than 30 million Americans are currently living with diabetes—approximately 1 in every 10 people.¹ Of these cases, over 90% are classified as type 2 diabetes. ² Diabetes is more prevalent within certain populations and age groups, with risk generally increasing with age. While about 10% of the overall adult population has diabetes, this figure rises to over 25% among adults aged 65 years and older. ³ Historically, type 2 diabetes was most commonly diagnosed in individuals aged 45 and older. However, in recent years, it has become increasingly common among children, teens, and young adults. ⁴

Type 2 diabetes is a chronic condition that affects the way the body processes glucose, the main source of energy from food. It develops when the body’s cells become resistant to insulin—a  hormone made by the pancreas that helps glucose enter cells to be used for energy. ⁵ In response to insulin resistance, the pancreas initially produces more insulin to compensate. However, over time, the pancreas cannot keep up with the increased demand, leading to elevated blood sugar levels. Persistently high blood sugar can damage various organs and systems in the body, increasing risk of serious health problems such as heart disease, vision loss, and kidney disease. ⁵

Symptoms of type 2 diabetes often develop gradually over several years and may go unnoticed for a long time. Because these symptoms can be subtle or easily mistaken for other conditions, it is important to be aware of your risk factors and consult a healthcare provider about getting your blood sugar tested. Common signs of type 2 diabetes include frequent urination, frequent and unsatisfied thirst, unexpected weight loss, uncontrolled hunger, blurry vision, numb or tingling hands or feet, unexplained fatigue, dry skin, sores that heal slowly, and frequent infections. ⁶

Type 2 diabetes is preventable through early identification of impaired glucose tolerance, healthy eating, and physical exercise. ³ Better health outcomes are often achieved through close supervision and coordination of a multidisciplinary healthcare team and strong family and social support.⁷ Individuals with diabetes must also learn new habits to regulate their diabetes, including checking blood sugar regularly, injecting insulin (as needed), and monitoring blood pressure and cholesterol.

Type 2 diabetes has been a serious public health problem among American Indians and Alaska Natives for almost 40 years. ⁸ Type 2 diabetes is a major cause of morbidity (such as blindness, kidney failure, lower-extremity amputation, and cardiovascular disease) among American Indian and Alaska Natives (AI/AN) adults. Since the early 1960s, AI/ANs have been disproportionately affected by diabetes compared with other US populations.⁸

In the United States, 9.7% of adult women have been diagnosed with diabetes. ¹ According to the most recent reports from the Utah Department of Health, more than 16.7% of Utah’s AI/AN population has diabetes, compared to 8.5% of all Utahns.⁹ In 2017, the Indian Health Service reported that 14.8% of AI/AN women have diabetes. ¹⁰ From 2015 through 2019, about 7.2% of female adults in Utah reported having diabetes (Table 1).¹¹ Utah AI/AN die from complications of type 2 diabetes at twice the rate of the general Utah Population (147.4 diabetes deaths per 100,000 Utah AI/ANs compared to 73.0 deaths per 100,000 Utah general Population).¹² Many of the poor health conditions that disproportionately affect the AI/AN population are attributed to poverty, lifestyle, genetics, and an inadequate healthcare delivery system.¹³

Utah public health agencies and local health departments partner with the National Diabetes Prevention Program (NDPP) to support diabetes prevention and management efforts across the state. NDPP offers evidence-based, low-cost community interventions designed for individuals with prediabetes, helping them reduce their risk of developing type 2 diabetes through lifestyle changes¹⁴ In addition to NDPP classes, agencies also work with primary care clinics to promote the Diabetes Self-Management Program (DSMP), known as “Living Well with Diabetes,” which provides education and support for individuals already diagnosed with diabetes. The NDPP’s mission is to help people with prediabetes to participate in affordable, high-quality lifestyle change programs to reduce their risk of type 2 diabetes and improve their overall health.

DSMP classes teach participants skills to manage their diabetes and other chronic conditions. Physical and emotional symptoms come with diabetes; this program aims to help participants effectively communicate with their healthcare providers and make healthy day-to-day decisions. DSMP has been shown to improve hypoglycemia, depression, diet, communication with physicians, and diabetes management self-efficacy. ¹⁵

Local DSMP workshops provide two trained instructors and meet once a week for six weeks. During the workshop, the topics covered include pain, fatigue, and stress management; monitoring blood sugar and managing hyper/hypoglycemia; creating an action plan to set and achieve attainable goals; problem-solving; dealing with difficult emotions and complications; physical activity and exercise; healthy eating; communication skills and working with your health care professional; and foot care. ¹⁶ In conclusion, type 2 diabetes remains a major public health concern in the United States and disproportionately affecting AI/AN women. NDPP and DSMP programs play a crucial role in helping individuals to delay or properly manage their diabetes. These programs provide tools and support to educate participants about healthy lifestyle changes. It is critical to address the social of determinants health in this population. Addressing what is known about social determinants of health can help reduce the burden of type 2 diabetes and improve the quality life among AI/AN women.

References

1. CDC. Prevalence of Total, Diagnosed, and Undiagnosed Diabetes in Adults: United States, August 2021–August 2023. https://www.cdc.gov/nchs/products/databriefs/db516.htm

2. Insulin Resistance & Prediabetes. 2025. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance

3. Fonseca VA, Kirkman MS, Darsow T, Ratner RE. The American Diabetes Association diabetes research perspective. Diabetes Care. Jun 2012;35(6):1380-7. doi:10.2337/dc12-9001

4. Fagot-Campagna A, Pettitt DJ, Engelgau MM, et al. Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective. J Pediatr. May 2000;136(5):664-72. doi:10.1067/mpd.2000.105141

5. Diabetes Overview: Prediabetes and Insulin Resistance. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance

6. Diabetes Overview: Type 2 Diabetes. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/type-2-diabetes

7. Standards of medical care in diabetes–2014. Diabetes Care. Jan 2014;37 Suppl 1:S14-80. doi:10.2337/dc14-S014

8. Acton KJ, Burrows NR, Moore K, Querec L, Geiss LS, Engelgau MM. Trends in diabetes prevalence among American Indian and Alaska Native children, adolescents, and young adults. Am J Public Health. Sep 2002;92(9):1485-90. doi:10.2105/ajph.92.9.1485

9. Services UDoHH. Health Indicator Report of Diabetes Prevalence. https://ibis.utah.gov/ibisph-view/indicator/view/DiabPrev.Race.html

10. Lucero JE, Roubideaux Y. Advancing Diabetes Prevention and Control in American Indians and Alaska Natives. Annu Rev Public Health. Apr 5, 2022;43:461-475. doi:10.1146/annual-publhealth-093019-010011

11. Health UDo. A Utah Health Disparities Profile Diabetes and Gestational Diabetes among Racial and Ethnic Minority Women in Utah. 2021;

12. Health UDo. Utah Health Disparities Summary 2009 American Indians Chronic Conditions, Reproductive Health, Injury and Lifestyle Risk. 2009;

13. Hoover E, Cook K, Plain R, et al. Indigenous peoples of North America: environmental exposures and reproductive justice. Environ Health Perspect. Dec 2012;120(12):1645-9. doi:10.1289/ehp.1205422

14. Prevention CfDCa. What Is the National DPP? https://www.cdc.gov/diabetes-prevention/programs/what-is-the-national-dpp.html

15. Lorig K, Ritter PL, Villa FJ, Armas J. Community-based peer-led diabetes self-management: a randomized trial. Diabetes Educ. Jul-Aug 2009;35(4):641-51. doi:10.1177/0145721709335006

16. Health UDo. Linking Utahns to Quality Self-Management Education. 2018.

Citation

Dorsan E. (2025). Diabetes among American Indian/Alaska Native Utah Women. Utah Women’s Health Review. doi: 10.26055/d-4swc-a8xw

PDF

View / download