About

Erica C Jansen, PhD, MPH, is an Assistant Professor in the Department of Nutritional Sciences and a Research Assistant Professor in Neurology at the University of Michigan School of Public Health. She is a nutritional epidemiologist whose research focuses on diet and sleep in relation to health across the lifespan, with particular emphasis on adolescence. Her work explores how early nutritional environments influence childhood obesity and the timing of puberty, as well as how various aspects of sleep—including duration, timing, and quality—affect the development of cardiometabolic risk. Dr. Jansen investigates the bidirectional relationships between sleep and diet, the role of toxicants in sleep and cardiometabolic outcomes, and the epigenetic markers that underlie these relationships. She conducts her research primarily within the ELEMENT cohort, a Mexican birth cohort followed for over 25 years, and her work is supported by multiple grants including a K01 award. Her research aims to elucidate the complex interactions between sleep, nutrition, toxicants, and epigenetics to better understand their impact on health during critical developmental periods.

Research topics

• Medicine
• Psychiatry
• Internal medicine
• Gerontology
• Demography
• Statistics
• Machine Learning
• Artificial Intelligence
• Mathematics
• Computer Science
• Environmental health
• Chemistry
• Algorithm
• Endocrinology
• Psychology
• Food science
• Clinical psychology
• Physiology

Selected publications

• 0111 Later Circadian Timing of the Onset of Eating is Linked to Worse Inflammatory Bowel Disease Outcomes

  SLEEP · 2026-05-01

  article

  Abstract Introduction Circadian disruption related to misalignment between food-intake timing and endogenous circadian rhythms may contribute to the onset and exacerbation of Inflammatory Bowel Disease (IBD) symptoms. Here, we investigated whether circadian meal timing, regularity, and eating window were associated with intestinal inflammation, clinician-rated disease severity, and self-reported quality of life among patients with IBD. Methods We leveraged baseline data from a randomized clinical trial of adults with active Crohn’s disease or ulcerative colitis (N=39). Participants completed seven days of food-timing logs and wore a Fitbit Charge 5TM to monitor sleep and activity at baseline. Circadian meal timing was calculated as the difference between the timing of each meal and sleep midpoint corrected for the sleep-debt accumulated over the week (MSFsc). Additional exposures of interest included day-to-day variability in meal timing, eating window duration, and breakfast skipping. Outcomes were measured at day 8 following the baseline assessment of sleep and food-timing logs. Outcomes included fecal calprotectin (intestinal inflammation), quality of life assessed by self-reported Short Inflammatory Bowel Disease Questionnaire (SIBDQ), and clinician-rated disease activity (active vs. inactive). We used linear and logistic regression models adjusted for age, sex, IBD type, and disease duration. Results Later circadian timing of the first meal was significantly associated with higher intestinal inflammation (β: 0.427; 95%CI: 0.159, 0.694) in the adjusted model. Similarly, greater day-to-day variability in the circadian timing of the first meal was significantly associated with lower quality of life scores (β: –4.99; 95% CI: –8.59, –1.39). A longer eating window was significantly associated with lower intestinal inflammation (β: -0.244; 95%CI: -0.486, -0.001) and was also associated with better quality of life and lower disease activity, though not statistically significant. Breakfast skipping showed unfavorable but non-significant associations across all outcomes. Conclusion Circadian misaligned eating patterns—particularly a later circadian onset of eating and greater irregularity in meal timing—was associated with higher intestinal inflammation and poorer quality of life in adults with IBD. These findings highlight circadian-aligned eating behaviors as a potential avenue for adjunctive, non-pharmacologic therapeutic strategies in IBD. Support (if any) Supported by R01 DK136520

  PublisherDOI

• Epigenetic age acceleration in adolescence: cross-sectional associations with dietary intake and prospective associations with cardiometabolic risk indicators in a Mexico City cohort

  Nutrition Metabolism and Cardiovascular Diseases · 2026-01-23

  articleOpen accessSenior author

  BACKGROUND AND AIMS: To examine the cross-sectional relationship between dietary intake and epigenetic age acceleration, as well as the prospective relationship between epigenetic age acceleration and cardiometabolic parameters measured two years later. METHODS AND RESULTS: ), fasting insulin (β = 0.86 μIU/mL), and insulin resistance (β = 0.21). Skin-Blood acceleration was associated with decreased HDL in males, and PedBE acceleration was associated with triglycerides in both sexes, though in opposing directions. CONCLUSION: Adolescent diet was not strongly associated with baseline epigenetic age acceleration. However, epigenetic age acceleration was associated prospectively with fat distribution and insulin resistance.

  PublisherDOI

• Meal Timing Patterns and Associations with Fat Mass in Adolescents

  medRxiv · 2026-04-23

  articleOpen access

  Background: The timing of energy intake could be important in the development of obesity. However, most observational evidence stems from adults, anthropometric defined obesity outcomes, single meal timing phenotyping, and traditional regression modeling. Objective: We aimed to describe meal timing patterns in adolescents and determine if they associated with fat mass by modeling the median and all other percentiles of the frequency distribution. Methods: We analyzed data from the Sleep and Growth Study 2 (S-Grow2, N=286, 12-13y). Participants completed 3-day 24-hour dietary recalls and time stamped eating occasions were used to define 8 meal timing traits, with aide from self-reported wake and bed timing. Principal component analysis (PCA) identified multi-dimensional meal timing patterns. Fat mass index (FMI) was estimated using dual energy X-ray absorptiometry. Quantile regression assessed if there were associations between meal timing traits and FMI across the entire FMI frequency distribution. Results: The typical first and last eating occasions were 8:00am (40 minutes after waking) and 8:00pm (2.7 hours before sleep), respectively, thus the eating period typically lasted 11.5 hours per day. The typical eating period midpoint was 2:15pm, and the timing when 50% of energy intake was consumed typically occurred at 3:15pm. PCA revealed three meal timing patterns: 1) "Delayed Start, Condensed Eating Period" (43% of variance; shorter eating period and delayed timing of first eating); 2) "Late, Sleep Proximal Eating" (30% of variance; later timing of last eating and extended eating period), and 3) "Later Energy Intake" (10% of variance; delayed energy intake midpoint). Higher scores for the "Delayed Start, Condensed Eating Period" pattern associated with higher body mass index and FMI at the upper tails of their distributions. Conclusions: Distinct multidimensional meal timing patterns emerged in early adolescence, with the delayed start, condensed eating period pattern potentially associated with higher adiposity.

  PublisherOA PDFDOI

• Adherence to the Alternate Mediterranean Diet and Multidimensional Sleep Health Among US Adults from the 2017-2018 National Health and Nutrition Examination Survey: Exploring Racial/Ethnic Disparities

  Journal of the Academy of Nutrition and Dietetics · 2026-01-01 · 1 citations

  articleOpen accessSenior author

  BACKGROUND: Adherence to the Mediterranean diet has been linked to better sleep health. However, the relationship between adherence to the alternate Mediterranean diet (aMED) and specific sleep health dimensions remains understudied, particularly among racial/ethnic minority adult populations in the United States (US). OBJECTIVE: The objective was to examine associations between aMED adherence and multiple dimensions of sleep health in US adults and assess differences by race/ethnicity. DESIGN: A cross-sectional analysis using data from the 2017-2018 National Health and Nutrition Examination Survey (NHANES), a nationally representative survey of the noninstitutionalized US population, was conducted. Dietary intake was assessed via two 24-hour recalls to calculate a modified aMED score, and sleep health was measured using self-reported dimensions summarized into a composite score. PARTICIPANTS/SETTING: The analytic study sample included 3005 adults (aged 18 years and older) from the 2017-2018 NHANES cycle. Analyses were survey-weighted to yield estimates representative of US adults who completed two 24-hour dietary recalls. MAIN OUTCOME MEASURES: Sleep health was assessed using 5 self-reported dimensions (ie, regularity, timing, duration, satisfaction, and alertness) summarized into a composite multidimensional sleep health score, with a score ≥3 indicating overall "good" sleep health. STATISTICAL ANALYSES PERFORMED: Survey-weighted logistic regression models were used to examine the associations between aMED adherence and sleep health dimensions as well as the overall multidimensional sleep health score, while adjusting for confounding variables. All models incorporated NHANES strata, clusters, and the 2-day dietary recall weight (WTDR2D) to account for the complex survey design and obtain nationally representative estimates. Effect modification by race/ethnicity was assessed using both interaction terms and stratified models. RESULTS: In survey-weighted analyses, the mean (SE) age was 47.1 (0.6) years; 51.3% were male. The weighted mean aMED score was 4.0, and 71% of adults were classified as having good sleep health. Higher aMED scores were significantly associated with greater odds of achieving recommended sleep duration (odds ratio [OR] per 1-point increase 1.1; 95% CI, 1.0 to 1.2; P = .03). Stratified analyses revealed that moderate/high aMED adherence was significantly associated with a greater odds of achieving recommended sleep duration among racial/ethnic minority adults (OR, 1.3; 95%, CI 1.1 to 1.7; P = .01), but not among non-Hispanic White adults (OR 1.1; 95% CI, 0.7 to 1.9; P = .68). No significant associations were observed for other sleep domains or the overall multidimensional sleep health score. CONCLUSIONS: Higher aMED adherence was associated with greater odds of achieving recommended sleep duration, with this association observed among racial/ethnic minority adults, but not among non-Hispanic White adults. Given the cross-sectional design, temporality cannot be established. Longitudinal studies incorporating objective sleep measures are needed to further evaluate these associations.

  PublisherDOI

• Diet and sleep among college student populations: a systematic review

  Sleep Medicine Reviews · 2026-05-01

  articleSenior author
  PublisherDOI

• Circadian gene expression in adolescents: Associations with concurrent circadian disruption and subsequent changes in cardiometabolic risk measures

  Sleep Medicine · 2026-02-05

  articleOpen accessSenior author

  OBJECTIVES: Circadian disruption has been linked to adverse metabolic health. Adolescents are particularly susceptible to circadian disruptors, such as delayed sleep onset and social jetlag, which may have sex-specific effects. However, evidence linking these disruptors with circadian gene expression and subsequent cardiometabolic risk remains limited. METHODS: Our study included 203 adolescents (53% females, median age 13.6 years) from the ELEMENT cohort in Mexico City. Sleep was assessed via 7-day wrist actigraphy. A fasting venipuncture blood sample was collected between 8:00 a.m. and 12:00 p.m. RNA was isolated from blood leukocytes and sequenced to determine the relative expression of genes. We conducted differential gene expression analysis for 12 core clock genes in relation to sleep midpoint and social jetlag, adjusting for sleep duration and other potential confounders. We further evaluated how circadian gene expression associated with changes in adiposity, glucose metabolism, blood pressure, and lipid profiles over two years using linear regression. RESULTS: Later sleep midpoint (per 1-h increase) was associated with reduced mid-morning expression of four circadian genes: RORA (log2 fold change [LFC]: -0.190; P value: 0.001), RORC (LFC: -0.147; P value: 0.039), CLOCK (LFC: -0.141; P value: 0.019), and NR1D2 (LFC: -0.093; P value: 0.029). Additionally, expression levels of several clock genes (CRY1, NR1D2, BMAL1, and PER1-3) were associated with changes in metabolic biomarkers over two years in sex-specific patterns. For instance, NR1D2 showed a negative association with fasting glucose among females (β: -0.0012; P value: 0.020), while demonstrating positive associations with LDL cholesterol (β: 0.0023; P value: 0.002) and total cholesterol (β: 0.0016; P value: 0.028) among males. CONCLUSIONS: Expression of core clock genes was linked to circadian disruption and changes in cardiometabolic risk factors in a sex-specific manner among adolescents. Our findings provide novel insights into potential biological mechanisms underlying associations of circadian disruption with cardiometabolic health.

  PublisherDOI

• 0018 Prospective Associations Between Rest-Activity Rhythms and Changes in Blood Pressure Across Mid to Late Adolescence

  SLEEP · 2026-05-01

  articleSenior author

  Abstract Introduction Delayed sleep timing has been associated with higher blood pressure among adolescents. However, rest-activity rhythms (RAR), which incorporate both sleep and physical activity, have been rarely explored. Methods The dataset included 558 adolescents (mean age 13.98, SD = 2.15) from the Mexico City-based ELEMENT cohort. Participants completed 7-day wrist actigraphy at the adolescent baseline (T1) visit. R package GGIR was used to derive RAR variables (Amplitude, IS, IV, Up Mesor, Down Mesor, Mesor, L5, L5 time, M10, M10 time, Acrotime, and Relative Amplitude). Blood pressure (systolic, SBP; and diastolic, DBP) was measured at two time-points approximately two years apart (T1 and T2). Linear regression models with RAR variables as continuous exposures and changes in SBP/DBP as outcomes, were adjusted for confounders. Sex stratified models were also tested. False detection rates (FDR) were controlled with the Benjamini Hochberg method. Results We found several associations related to timing of activity. Later L5 (“least active 5 hours”) starting time was associated with positive two year increases in DBP (Beta = 0.265 with SE 0.07 and P < 0.001) and higher SBP (Beta = 0.191, SE 0.08; P = 0.017). In contrast, later Up Mesor (transition from lower to higher activity) was associated with negative two-year changes in SBP and DBP (Beta=-0.37, SE 0.16; P=0.02; and Beta=-0.40, SE 0.14; P=0.003, respectively). Similarly, later M10 (most active 10 hours) was associated with negative two-year changes in SBP (Beta = -0.727, SE 0.20; P < 0.001) and DBP (Beta = -0.709, SE0.23; P = 0.002). All DBP associations remained significant with FDR adjustment. Finally, there were sex differences, such that the M10 association was more prominent in males and the L5 and Up Mesor associations were more prominent in females. Conclusion We found associations between timing of activity throughout the 24-hour day, but not other RAR metrics, with prospective changes in blood pressure. In line with prior research, later low activity periods (i.e., sleep) associated with higher blood pressure. In contrast to expectation, later timing of higher activity periods associated with relative reductions in blood pressure over time in a sex-specific manner. Support (if any) R01HL169893

  PublisherDOI

• 0340 The Sleep-Wake Classification Performance of Pediatric-Trained Machine Learning Algorithms for Actigraphy Data

  SLEEP · 2026-05-01

  article

  Abstract Introduction Increasingly, actigraphy methods seek to leverage raw acceleration data and machine-learning scoring classification. However, much of the progress has been made in adults. We therefore trained machine-learning sleep-wake classifiers using pediatric data. We aimed to assess their sleep-wake scoring ability and benchmarked against an adult-trained classifier and algorithms in GGIR. Methods Sixty children (26 female, ages 5.3–17.7 years) completed in-lab overnight polysomnography at the Children’s Hospital of Philadelphia and wore a GENEActiv device (3-axis accelerometer, 50 Hz) on their non-dominant wrist. The acceleration data were converted into 30-second epochs and aligned with physician-scored sleep-wake data from electroencephalography. Six machine-learning models were trained using leave-one-subject-out cross-validation. Epoch-by-epoch analyses generated performance metrics: sensitivity and specificity, with balanced accuracy (BA) used to rank. Discrepancy analyses compared the overall sleep duration estimated. Results Overall, 560.1 hours of data were collected; 74.4% of epochs were scored as sleep with an average sleep duration of 7.1 hours (SD = 1.9). Of the six pediatric-trained machine learning models, the top two were random forest (BA = 0.78; Sensitivity = 0.87; Specificity = 0.69) and neural network (BA = 0.77; Sensitivity = 0.83; Specificity = 0.73). These performance metrics exceeded that of an adult-trained neural net classifier applied to our data (BA = 0.71; Sensitivity = 0.93; Specificity = 0.49), but were comparable to the GGIR Cole-Kripke (GGIR-CK: BA = 0.79; Sensitivity = 0.75; Specificity = 0.85) and GGIR van Hees algorithms (GGIR-vH: BA = 0.78; Sensitivity = 0.84; Specificity = 0.73). Overall, sleep duration was underestimated by an average of 15 minutes using the random forest classifier and by an average of 37 minutes using the neural network classifier. For comparison, both GGIR-CK and GGIR-vH underestimated sleep duration by an average of 33 minutes. Conclusion We trained pediatric sleep-wake classifiers that had a strong ability to detect sleep and a moderate-to-strong ability to detect wake. Based on epoch-by-epoch and discrepancy analyses, the random forest classifier was the most optimal, outperforming GGIR-CK, GGIR-vH, and an adult-trained neural network classifier. With larger samples used for training and validation, we may reduce variability and further improve pediatric sleep-wake classification using actigraphy. Support (if any)

  PublisherDOI

• Associations between repeated measures of exposure to phthalates, phenols, parabens, and their mixtures and metabolic syndrome in midlife women in Mexico city

  Environmental Research · 2026-03-25

  article
  PublisherDOI

• Hydrotherapy and acupressure for restless legs syndrome: results of a qualitative part of a randomized controlled exploratory study

  Frontiers in Medicine · 2025-09-01

  articleOpen accessSenior author

  Introduction: Restless legs syndrome (RLS) has a negative impact on quality of life and remains challenging to treat. This study explored the subjective experiences of individuals using two self-managed, non-pharmacological interventions-hydrotherapy and acupressure-for RLS, focusing on their perceived benefits, challenges, and feasibility in everyday life. Methods: Within a three-armed randomized study we conducted qualitative interviews in both intervention groups. The semi-structured interviews were coded and analyzed using reflexive thematic analysis. Coding followed both an inductive approach, grounded in the data, and a deductive approach, guided by the study objectives. Data analysis was carried out using MAXQDA® software. Results: A total of 12 telephone interviews (six per intervention group) were qualitatively analyzed. Participants had a mean age of 65 years (range 35-75). Six themes emerged: prior experiences, motivation, study document perception, treatment integration, perceived impact, and post-intervention use. Both groups reported symptom and sleep improvements. Increased mindfulness was more common in the acupressure group. Hydrotherapy participants noted sensory effects but also discomfort and time barriers. Both interventions were seen as practical, with acupressure being perceived as easier to apply. Conclusion: Participants of both groups reported varying degrees of RLS symptom improvement. High-quality confirmatory RCTs are needed to investigate the effectiveness of acupressure and hydrotherapy, with a focusing on practical implementation and the need for comprehensive, continuous guidance. Treatments in RLS should be location-independent to improve both participation and outcomes. Future research should further explore individualized adaptations and contextual factors influencing treatment experience and effectiveness. Trial registration: Identifier DRKS00029960.

  PublisherOA PDFDOI

Recent grants

• Sleep and Circadian Rhythms in Adolescence: Epigenetic Pathways of Cardiometabolic Risk

  NIH · $759k · 2020–2025

Frequent coauthors

• Alejandra Cantoral

  Ibero American University

  79 shared

• Karen E. Peterson

  University of Michigan–Ann Arbor

  78 shared

• Martha María Téllez‐Rojo

  Instituto Nacional de Salud Pública

  69 shared

• Galit Levi Dunietz

  Michigan Medicine

  51 shared

• Astrid N. Zamora

  Stanford University

  29 shared

• Peter X.‐K. Song

  University of Michigan–Ann Arbor

  27 shared

• Louise M. O’Brien

  University of Michigan–Ann Arbor

  27 shared

• Arturo Arrona‐Palacios

  Brigham and Women's Hospital

  24 shared

Labs

• Jansen LaboratoryPI

Education

• PhD, Epidemiology

  University of Michigan School of Public Health

  2016

• MPH, Epidemiology

  University of Michigan School of Public Health

  2014

• Bachelor of Science, Biology

  Hope College

  2012