Susan Malone


Susan Malone headshot

Susan Malone


Assistant Professor

1 212 992 7047

433 First Avenue
Room 412
New York, NY 10010
United States

Accepting PhD students

Susan Malone's additional information

Susan Kohl Malone is a registered nurse with a focus on chronic disease prevention and management. This work inspired her research interests into the roles that modifiable lifestyle behaviors (sleep, physical activity, eating habits) and environmental factors (light exposure) play on cardio-metabolic disease risk. Of special interest are the timing and rhythmicity of these behaviors and exposures. 

Rhythms are the rule, not the exception, underlying almost all physiological functions. Thus, the rhythmicity and timing of behaviors and biology need to be measured and managed to move towards greater wellness. The goal of Prof. Malone’s research team is to incorporate timing and rhythmicity into behavioral interventions to ameliorate chronic disease. Prof. Malone has been the principle investigator on several funded sleep intervention studies. She has led a sleep health intervention to reverse metabolic syndrome in middle-aged adults as part of NYU’s P20 Exploratory Center for Precision Health in Diverse Populations. She also leads a randomized controlled trial to determine whether improving sleep improves glycemic control in adults with prediabetes. Prof. Malone has led several population-based studies examining the relationships between multiple dimensions of sleep, such as duration, timing, regularity, quality with cardio-metabolic risk behaviors, and cardio-metabolic outcomes.

Prof. Malone holds an undergraduate degree in nursing with a theology minor from Georgetown University and a MSN and PhD from the University of Pennsylvania. She completed postdoctoral fellowship training in the Center for Sleep and Circadian Neurobiology at the University of Pennsylvania under the mentorship of Dr. Allan Pack.


Postdoctoral Fellowship - University of Pennsylvania
PhD - University of Pennsylvania
MSN - University of Pennsylvania
BSN - Georgetown University

Community/population health

American Academy of Nursing
Eastern Nursing Research Society
National Association of School Nurses
Sigma Theta Tau Nursing Honor Society
Sleep Research Society
Society for Research in Biological Rhythms

Faculty Honors Awards

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


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). Journal of Diabetes Research, 2021. 10.1155/2021/6611064
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<0.01), shorter sleep duration (d=0.79), fewer total activity counts (d=1.32), shorter average awakening length (d=0.46), and delays in sleep onset (d=1.06) and sleep midpoint (d=0.72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with (NCT03215914).

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). Chronobiology International, 38(4), 543-556. 10.1080/07420528.2020.1868490
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.

Efficacy of a sleep health intervention to optimize standard smoking cessation treatment response: Results from a pilot randomized controlled trial

Patterson, F., Grandner, M. A., Malone, S. K., Pohlig, R. T., Ashare, R. L., & Edwards, D. G. (2020). Journal of Smoking Cessation. 10.1017/jsc.2020.8
BackgroundWe tested if an adjunctive sleep health (SH) intervention improved smoking cessation treatment response by increasing quit rates. We also examined if baseline sleep, and improvements in sleep in the first weeks of quitting, were associated with quitting at the end of treatment.MethodsTreatment-seeking smokers (N = 29) aged 21-65 years were randomized to a SH intervention (n = 16), or general health (GH) control (n = 13) condition. Participants received six counseling sessions across 15-weeks: SH received smoking cessation + SH counseling; GH received smoking cessation + GH counseling. Counseling began 4-weeks before the target quit date (TQD), and varenicline treatment began 1-week prior to TQD. Smoking status and SH were assessed at baseline (week 1), TQD (week 4), 3 weeks after cessation (week 7), week 12, and at the end of treatment (EOT; week 15).ResultsSH versus GH participants had higher Carbon Monoxide (CO) -verified, 7-day point prevalence abstinence at EOT (69% vs. 54%, respectively; adjusted odds ratio (aOR) = 2.10, 95% confidence interval (CI) = 0.40-10.69, P = 0.77). Higher baseline sleep efficiency (aOR = 1.42, 95% CI = 1.03-1.96, P = 0.03), predicted higher EOT cessation. Models were adjusted for age, sex, education, and baseline nicotine dependence.ConclusionsImproving SH in treatment-seeking smokers prior to cessation warrants further examination as a viable strategy to promote cessation.

Self-care in People with Type 2 Diabetes Mellitus Research Protocol of a Multicenter Mixed Methods Study (SCUDO)

Luciani, M., Fabrizi, D., Rebora, P., Rossi, E., Di Mauro, S., Kohl Malone, S., & Ausili, D. (2019). Professioni Infermieristiche, 72(3), 203-212.
About 11% of the adult global populations is estimated to be living with type 2 diabetes mellitus (T2DM) by 2040. T2DM requires people to make decisions regarding complex therapeutic regimes, to maintain their well-being and quality of life, to manage symptoms and to reduce disease complications. All these behaviours, requiring knowledge, motivation, experience, and skills, have been referred to the concept of self-care. The intricacy and multidimensionality of T2DM self-care requires a complex approach to its overall comprehension. This Embedded Mixed Method study aims to investigate the experience of self-care in Type 2 Diabetes Mellitus adult patients. It comprises a prospective observational design, and an interpretive description. Quantitative data will be collected with validated questionnaires from 300 patients at baseline and once a year for two years on: diabetes self-care, quality of life, diabetes related distress, and sleep quality. Socio-demographic and clinical data will be collected from medical records. Qualitative data will be collected using semi-structured interviews on circa 10-20 patients, at baseline and once a year for two years, analysed according to interpretive description. Quantitative and qualitative data will be analysed separately and then merged and interpreted. This study will expand our understanding of self-care in people with T2DM. The expected outcome will be a better understanding of the effect of self-care on glycaemic control and therefore clinical outcomes and costs.

Shift Workers Have Higher Blood Pressure Medicine Use, But Only When They Are Short Sleepers: A Longitudinal UK Biobank Study

Riegel, B., Daus, M., Lozano, A. J., Malone, S. K., Patterson, F., & Hanlon, A. L. (2019). Journal of the American Heart Association, 8(20). 10.1161/JAHA.119.013269
Background: Some, but not all, studies report associations between shift work and hypertension, suggesting that particular subgroups may be at risk. We examined moderating effects of sleep duration and circadian preference on the relationship between shift work and new blood pressure (BP) medicine use at follow-up. Methods and Results: Baseline and 5-year follow-up data from the UK Biobank cohort (N=9200) were used to generate logistic regression models for shift workers and nonshift workers. The moderating effects of sleep duration (short ≤6 hours; adequate 7–8 hours; long ≥9 hours) and circadian preference (morning “larks;” intermediate; evening “owls”) at baseline were examined with new BP medicine use at follow-up, adjusting for age, sex, race, education, employment, urban/rural, cardiovascular disease family history, depression, alcohol intake, physical activity, diet, smoking, and body mass index. The sample was predominately middle aged (55.3±7.4), female (57.3%), and white (97.9%). Most reported adequate sleep duration (7–8 hours, 73.7%) and were intermediate type (65.3%); 8.0% were shift workers at baseline. Only 6.5% reported new BP medicine use at follow-up. Short sleep duration was a significant moderator of new BP medicine use in shift workers. Among short sleepers, shift workers had a 2.1-fold increased odds of new BP medicine use compared with nonshift workers (odds ratio=2.08, 95% CI=1.21–3.58, P=0.008). In those reporting adequate (odds ratio=0.82, 95% CI=0.54–1.25, P=0.35) and long sleep (odds ratio=0.64, 95% CI=0.11–3.54, P=0.60), this relationship was protective but nonsignificant. Interaction between circadian preference and shift work on BP medicine use was nonsignificant. Conclusions: Shift workers with short sleep duration may be at risk for hypertension.

Sleep and alertness in a duty-hour flexibility trial in internal medicine

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BACKGROUND A purpose of duty-hour regulations is to reduce sleep deprivation in medical trainees, but their effects on sleep, sleepiness, and alertness are largely unknown. METHODS We randomly assigned 63 internal-medicine residency programs in the United States to follow either standard 2011 duty-hour policies or flexible policies that maintained an 80-hour workweek without limits on shift length or mandatory time off between shifts. Sleep duration and morning sleepiness and alertness were compared between the two groups by means of a noninferiority design, with outcome measures including sleep duration measured with actigraphy, the Karolinska Sleepiness Scale (with scores ranging from 1 [extremely alert] to 9 [extremely sleepy, fighting sleep]), and a brief computerized Psychomotor Vigilance Test (PVT-B), with long response times (lapses) indicating reduced alertness. RESULTS Data were obtained over a period of 14 days for 205 interns at six flexible programs and 193 interns at six standard programs. The average sleep time per 24 hours was 6.85 hours (95% confidence interval [CI], 6.61 to 7.10) among those in flexible programs and 7.03 hours (95% CI, 6.78 to 7.27) among those in standard programs. Sleep duration in flexible programs was noninferior to that in standard programs (between-group difference, −0.17 hours per 24 hours; one-sided lower limit of the 95% confidence interval, −0.45 hours; noninferiority margin, −0.5 hours; P=0.02 for noninferiority), as was the score on the Karolinska Sleepiness Scale (between-group difference, 0.12 points; one-sided upper limit of the 95% confidence interval, 0.31 points; noninferiority margin, 1 point; P<0.001). Noninferiority was not established for alertness according to the PVT-B (between-group difference, −0.3 lapses; one-sided upper limit of the 95% confidence interval, 1.6 lapses; noninferiority margin, 1 lapse; P=0.10). CONCLUSIONS This noninferiority trial showed no more chronic sleep loss or sleepiness across trial days among interns in flexible programs than among those in standard programs. Noninferiority of the flexible group for alertness was not established.

Sleep and Alertness Outcomes in a Duty-Hour Flexibility Trial in Internal Medicine

Malone, S. (2019). New England Journal of Medicine, 915-923.

Sleep as atarget for optimized response to smoking cessationtreatment

Patterson, F., Grandner, M. A., Malone, S. K., Rizzo, A., Davey, A., & Edwards, D. G. (2019). Nicotine and Tobacco Research, 21(2), 139-148. 10.1093/ntr/ntx236
Declining national rates of current tobacco use to an all-time low of 15.1% represents a public health victory. Undermining this progress, however, are smoking rates of up to 50% among high-risk, low-income populations. Current FDA-approved treatments for nicotine dependence are ineffective with between 70-95% of treatment-seekers relapsing within the first year of attempted abstinence. Thus, identification of novel intervention targets to optimize response to currently available treatments for nicotine dependence is a critical next step. One such target may be sleep insomnia. Insomnia is a clinically verified nicotine withdrawal symptom but, to date, addressing insomnia or other sleep disturbance symptoms as an adjunctive smoking cessation therapy has yet to be fully considered.To this end, this manuscript presents a narrative review of: (1) sleep continuity and architecture in smokers versus nonsmokers; (2) effects of nicotine abstinence on sleep; (3) possible mechanisms linking sleep with smoking cessation outcomes; (4) plausible adjunctive sleep therapies to promote smoking cessation; (5) possible treatments for unhealthy sleep in smokers; and (6) directions for future research.Taken together, this will provide conceptual support for sleep therapy as an adjunctive treatment for smoking cessation. Implications:This narrative literature review presents a comprehensive discussion of the relationship between habitual sleep and cigarette smoking.The extent to which unhealthy sleep in smokers may be a viable intervention target for promoting response to smoking cessation treatment is considered. Ultimately, this review provides conceptual support for sleep therapy as an adjunctive treatment for smoking cessation.

Social jetlag, circadian disruption, and cardiometabolic disease risk

Malone, S. K., Mendoza, M. A., & Patterson, F. (2019). In Sleep and Health (pp. 227-240). Elsevier. 10.1016/B978-0-12-815373-4.00018-6
The sun rises and sets over the earth in a predictable pattern. This pattern has existed for billions of years and has influenced the behavior of all living things. Behavioral rhythms have aligned with these light-dark rhythms and conferred an evolutionary advantage. Humans have adapted to the light-dark cycle so that activity occurs during the day and rest occurs during the night. Increased visibility afforded by daylight optimizes foraging and safety while being active. Reduced visibility during the night optimizes sleeping and fasting. Daily rhythms, such as light-dark, are known as circadian rhythms from the Latin words “circa,” for about, and “dias,” for a day. Physiological processes rely on predictable circadian rhythms. These processes include sleeping and waking, cardiac function, such as heart rate and blood pressure, and metabolic processes, such as glucose, lipid, and energy metabolism. Disrupting circadian rhythms can profoundly impact cardiometabolic health and well-being. Poor cardiometabolic health can also disrupt the circadian system. This chapter will briefly introduce the cardiometabolic syndrome, the circadian system, circadian disruption, and social jetlag as a form of circadian disruption.

Addressing the Social Determinants of Health: A Call to Action for School Nurses

Schroeder, K., Malone, S. K., McCabe, E., & Lipman, T. (2018). Journal of School Nursing, 34(3), 182-191. 10.1177/1059840517750733
Social determinants of health (SDOH), the conditions in which children are born, grow, live, work or attend school, and age, impact child health and contribute to health disparities. School nurses must consider these factors as part of their clinical practice because they significantly and directly influence child well-being. We provide clinical guidance for addressing the SDOH when caring for children with three common health problems (obesity, insufficient sleep, and asthma). Given their unique role as school-based clinical experts, care coordinators, and student advocates, school nurses are well suited to serve as leaders in addressing SDOH.