Susan Malone

Faculty

Susan Malone headshot

Susan Kohl Malone

PhD RN

Assistant Professor

1 212 992 7047

433 First Ave
New York, NY 10010
United States

Accepting PhD students

Susan Kohl Malone, PhD, RN, is an Assistant Professor at NYU Rory Meyers College of Nursing. Her research focuses on understanding how sleep patterns and circadian rhythms impact metabolic health, with particular emphasis on preventing type 2 diabetes through personalized sleep interventions. She investigates how improving sleep health can reverse metabolic syndrome in diverse populations and addresses critical health disparities in sleep and cardiometabolic outcomes. Prof. Malone also teaches courses on lifestyle approaches to wellness and mentors doctoral students in sleep health research.

Malone has led multiple NIH-funded research projects, and is currently investigating metabolically-relevant hormonal rhythms in adults with prediabetes and short sleep duration, as well as multimodal dynamic biosensing for quantifying long COVID symptom progression. Her work combines nursing science, behavioral science, and circadian biology to develop evidence-based interventions that improve health outcomes across the lifespan.

Prior to joining the faculty at NYU Meyers, Malone served as a Senior Research Scientist at the college and completed postdoctoral training at the University of Pennsylvania's Center for Sleep and Circadian Neurobiology. She brings extensive clinical experience as a certified school nurse and diabetes educator, having worked in various healthcare settings including diabetes treatment centers and school health programs. This clinical background informs her translational research approach to making sleep science accessible and applicable to real-world health challenges.

Among her many honors, Malone had the unique honor of having the annual Susan Kohl Award established in her name at Georgetown University.

She completed postdoctoral training as a Senior Research Scientist at New York University Rory Meyers College of Nursing and as a Postdoctoral Fellow at the University of Pennsylvania Perelman School of Medicine's Center for Sleep and Circadian Neurobiology, where she developed expertise in sleep and circadian health research. Her doctoral dissertation examined whether chronotype modifies the relationship between sleep duration and body mass index in adolescents, establishing her foundation in sleep health across the lifespan.

PhD in Nursing, University of Pennsylvania School of Nursing
MSN in Nursing, University of Pennsylvania School of Nursing
BSN in Nursing, Georgetown University School of Nursing
Cardiometabolic Health
Circadian Rhythms
Diabetes Prevention
Health Disparities
School Health
Sleep Research
American Academy of Nursing
Eastern Nursing Research Society
International Association of Circadian Health Clinics
Sigma Theta Tau Nursing Honor Society
Sleep Research Society
Society for Research in Biological Rhythms
Society of Behavioral Medicine
Marion R. Gregory Award for distinguished completed doctoral dissertation, University of Pennsylvania School of Nursing (2015)
Heilbrunn Nurse Scholar Award, Rockefeller University (2014)
Research Poster Winner, National Association of School Nurses Annual Conference (2013)
Leadership Identification Scholarship, University of Pennsylvania School of Nursing (1985)
Susan Kohl Award, Georgetown University (1985)
Sigma Theta Tau, Nursing Honor Society (1984)

Short Sleep Duration, Late Sleep Timing, and Late Eating Timing: A Trilogy of Behavioral Risk Factors for High Blood Pressure

Hoopes, E. K., Wittman, M., D’Agata, M., Brookstein-Burke, T., Robson, S., Malone, S. K., Goel, N., & Patterson, F. (2022). In Circulation (Vols. 145, Issue S1).
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Social Isolation, Sleep Disturbance, and Cognitive Health:  A Longitudinal Mediation Study

Qi, X., Pei, S., Malone, S. K., & Wu, B. (2022). In Innovation in Aging (Vols. 6).
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Use of a Hybrid Closed Loop Insulin Delivery System Improves Sleep and Glycemic Control in Adults with Long-standing Type 1 Diabetes and Hypoglycemia Unawareness

Malone, S. K., Matus, A. M., Peleckis, A., Flatt, A. J., Grunin, L., Yu, G., Jang, S., Weimer, J., Lee, I., Rickels, M., & Goel, N. (2022). In Sleep.
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Accelerometer-derived Sleep and Circadian Domains and Sociodemographic Correlates in the UK Biobank

Gehrman, P., Malone, S. K., Patterson, F., Mitchell, J., & Mazzotti, D. (2021). In Sleep.
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Actigraphy-derived rest--activity rhythms are associated with nocturnal blood pressure in young women

Hoopes, E. K., Patterson, F., Berube, F. R., D'Agata, M. N., Brewer, B., Malone, S. K., Farquhar, W. B., & Witman, M. A. (2021). In Journal of Hypertension (Vols. 39, Issues 12, pp. 2413-2421). 10.1097/HJH.0000000000002966
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INTRODUCTION: Misalignment between lifestyle behaviors and endogenous circadian rhythms is associated with elevated nocturnal blood pressure (BP) in experimental studies; however, less is known about free-living (i.e. nonlaboratory) circadian disruption and nocturnal BP. Additionally, sex-specific cardiovascular implications of circadian disruption are unclear. OBJECTIVE: To examine the associations between rest--activity rhythms (RAR), a field-based estimate of circadian disruption, and nocturnal BP characteristics in young men and women. METHODS: Fifty participants (20 ± 1 years; 20 men/30 women) underwent 24-h ambulatory BP monitoring following 14 days of wrist actigraphy. RAR variables of interdaily stability (day-to-day consistency in RAR), intradaily variability (within-day fragmentation of RAR), and relative amplitude (difference between peak vs. trough activity) were derived from actigraphy. Multivariable regression models of mean nocturnal SBP, DBP, and SBP dipping were generated to test main associations with RAR variables, and sex × RAR interactions. Daytime BP, race, BMI, physical activity, sleep duration, alcohol, caffeine, and sodium intake were considered as covariates. RESULTS: In the full sample, no main associations between RAR and nocturnal BP characteristics were found. Sex interacted with RAR such that in women, higher interdaily stability (β = -5.39, 95% CI = -10.04 to -0.73, P = 0.024) and relative amplitude (β = -4.78, 95% CI = -9.22 to -0.34, P = 0.036) were both associated with lower nocturnal SBP. Sex-stratified multivariable models of nocturnal BP also revealed associations between interdaily stability and relative amplitude with SBP dipping in women (all P ≤ 0.01). No associations were apparent in men. CONCLUSION: Consistent and high-amplitude RAR are favorably associated with nocturnal BP characteristics in young women.

Associations Between Rest-Activity and Nocturnal Blood Pressure are Sex Dependent in Apparently Health Emerging Adults

Hoopes, E. K., Patterson, F., Berube, F., D’Agata, M., Brewer, B., Malone, S. K., Farquhar, W., & Wittman, M. (2021). In Sleep.
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Bedtime habits in adults with and without type 2 diabetes

Malone, S. K., Di, J., Leroux, A., Riegel, B., Melkus, G., Rickels, M., Punjabi, N., Pack, A., Crainiceanu, C., & Urbaneck, J. (2021). In Journal of Articles in Support of the Null Hypotheses (Issues 18, pp. 33-40).
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Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery

Malone, S. K., Peleckis, A. J., Grunin, L., Yu, G., Jang, S., Weimer, J., Lee, I., Rickels, M. R., & Goel, N. (2021). In Journal of Diabetes Research (Vols. 2021). 10.1155/2021/6611064
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Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age=58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen's d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d=0.47-0.79), reduced basal insulin requirements (d=0.48), and a smaller glucose coefficient of variation (d=0.47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d=0.60), lability index (d=0.50), HYPO score (d=1.06)). Shorter sleep onset latency (d=1.53; p

Habitual physical activity patterns in a nationally representative sample of U.S. adults

Malone, S. K., Patterson, F., Grunin, L., Melkus, G. D., Riegel, B., Punjabi, N., Yu, G., Urbanek, J., Crainiceanu, C., & Pack, A. (2021). In Translational Behavioral Medicine (Vols. 11, Issues 2, pp. 332-341). 10.1093/tbm/ibaa002
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Physical inactivity is a leading determinant of noncommunicable diseases. Yet, many adults remain physically inactive. Physical activity guidelines do not account for the multidimensionality of physical activity, such as the type or variety of physical activity behaviors. This study identified patterns of physical activity across multiple dimensions (e.g., frequency, duration, and variety) using a nationally representative sample of adults. Sociodemographic characteristics, health behaviors, and clinical characteristics associated with each physical activity pattern were defined. Multivariate finite mixture modeling was used to identify patterns of physical activity among 2003-2004 and 2005-2006 adult National Health and Nutrition Examination Survey participants. Chi-square tests were used to identify sociodemographic differences within each physical activity cluster and test associations between the physical activity clusters with health behaviors and clinical characteristics. Five clusters of physical activity patterns were identified: (a) low frequency, short duration (n = 730, 13%); (b) low frequency, long duration (n = 392, 7%); (c) daily frequency, short duration (n = 3,011, 55%); (d) daily frequency, long duration (n = 373, 7%); and (e) high frequency, average duration (n = 964, 18%). Walking was the most common form of activity; highly active adults engaged in more varied types of activity. High-activity clusters were comprised of a greater proportion of younger, White, nonsmoking adult men reporting moderate alcohol use without mobility problems or chronic health conditions. Active females engaged in frequent short bouts of activity. Data-driven approaches are useful for identifying clusters of physical activity that encompass multiple dimensions of activity. These activity clusters vary across sociodemographic and clinical subgroups.

Rest-activity rhythms in emerging adults : implications for cardiometabolic health

Hoopes, E. K., Witman, M. A., D’Agata, M. N., Berube, F. R., Brewer, B., Malone, S. K., Grandner, M. A., & Patterson, F. (2021). In Chronobiology International (Vols. 38, Issues 4, pp. 543-556). 10.1080/07420528.2020.1868490
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Emerging adulthood (18–25 years) represents a window of opportunity to modify the trajectory of cardiometabolic disease risk into older adulthood. Not known is the extent to which rest-activity rhythms (RAR) may be related to biomarkers of cardiometabolic health in this population. In this cross-sectional, observational study, 52 healthy emerging adults wore wrist accelerometers (14 consecutive days; 24 h/day) for assessment of nonparametric RAR metrics, including interdaily stability (IS; day-to-day RAR consistency), intradaily variability (IV; within-day RAR fragmentation), and relative amplitude (RA; robustness of RAR), as well as autocorrelation (correlation of rest/activity levels at 24-h lag-times). Cardiometabolic biomarkers, including body mass index (BMI), body fat percentage, blood pressure (BP), fasting lipids, glucose, and C-reactive protein (CRP) were assessed. Additional measures including physical activity, sleep duration, and habitual caffeine and alcohol consumption were also evaluated. A series of multivariable regression models of cardiometabolic biomarkers were used to quantify associations with RAR metrics. On average, participants were 20 ± 1 years of age (21 males, 31 females), non-obese, and non-hypertensive. All were nonsmokers and free of major diseases or conditions. In separate models, which adjusted for sex, BMI, moderate-vigorous physical activity, sleep duration, caffeine, and alcohol consumption, IS was inversely associated with total cholesterol (p ≤ 0.01) and non-HDL cholesterol (p < .05), IV was positively associated with CRP (p < .05), and autocorrelation was inversely associated with total cholesterol (p < .05) and CRP (p < .05). Conversely, associations between RA and cardiometabolic biomarkers were nonsignificant after adjustment for BMI, alcohol, and caffeine consumption. In conclusion, RAR metrics, namely, a higher IS, lower IV, and higher autocorrelation, emerged as novel biomarkers associated with more favorable indices of cardiometabolic health in this sample of apparently healthy emerging adults.