Author’s Accepted Manuscript Modifiable cardiometabolic risk factors in youth with at-risk mental states: A cross-sectional study Oscar Lederman, Simon Rosenbaum, Chris Maloney, Jackie Curtis, Philip B Ward www.elsevier.com/locate/psychres
PII: DOI: Reference:
S0165-1781(16)32006-6 http://dx.doi.org/10.1016/j.psychres.2017.08.034 PSY10750
To appear in: Psychiatry Research Received date: 5 January 2017 Revised date: 4 August 2017 Accepted date: 15 August 2017 Cite this article as: Oscar Lederman, Simon Rosenbaum, Chris Maloney, Jackie Curtis and Philip B Ward, Modifiable cardiometabolic risk factors in youth with at-risk mental states: A cross-sectional study, Psychiatry Research, http://dx.doi.org/10.1016/j.psychres.2017.08.034 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
PSYCHIATRY RESEARCH Modifiable cardiometabolic risk factors in youth with at-risk mental states: A cross-sectional study Oscar Ledermana, c*, Simon Rosenbauma, b, Chris Maloneya, Jackie Curtisb, c, Philip B Wardb, d a
School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
b
School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
c
Keeping the Body in Mind Program, South Eastern Sydney Local Health District, Sydney, NSW,
Australia d
Schizophrenia Research Unit, South Western Sydney Local Health District & Ingham Institute of
Applied Medical Research, Liverpool, NSW, Australia
*Corresponding author: Oscar Lederman, Keeping the Body in Mind Program, 26 Llandaff St Bondi Junction, 2022 Australia. Email:
[email protected]
Highlights
·
Individuals with at-risk mental states (ARMS) reported lower levels of physical activity, were more sedentary and expended less energy than healthy volunteers.
·
ARMS participants reported significantly worse sleep quality than those with a first-episode psychosis (FEP) or healthy volunteers.
·
A strong association between physical activity, energy expenditure and self-reported sleep quality suggested that increased physical activity and better quality sleep were linked,
·
No differences were evident in anthropometric measures or blood glucose levels between ARMS, FEP and healthy volunteers.
·
Identifying lifestyle-related risk factors in the prodromal phases of illness may provide an opportunity for early intervention to reduce negative physical health outcomes
Abstract Young people experiencing psychotic illness engage in low amounts of physical activity have poor fitness levels and poor sleep quality. This study aimed to determine the prevalence of these modifiable cardiometabolic risk factors among individuals with at-risk mental states (ARMS), who are at increased risk of developing psychosis. A cross-sectional study was conducted in a communitybased youth mental health service. Thirty participants (23%♀, 21.3 ± 1.7 years old) were recruited, 10 with ARMS, 10 with first-episode psychosis (FEP) and 10 healthy volunteers. Physical activity levels were assessed using self-report and objective measures. Aerobic capacity, upper body strength, hamstring flexibility, forearm grip strength and core endurance were assessed. Sleep quality, depression and anxiety were measured by self-report questionnaire. The ARMS group did not differ significantly on anthropometric measures from FEP or healthy volunteers. They engaged in significantly less physical activity (p < 0.05) and had poorer sleep quality (p < 0.05) than healthy volunteers. Our results are consistent with other studies that found that youth with ARMS are at greater cardiometabolic risk. Interventions aimed at improving these modifiable risk factors may assist with preventing the decline in physical health associated with the development of psychiatric illness. Key words; physical activity, exercise, sleep, mental illness, psychosis, cardiovascular disease, diabetes, UHR, ARMS
1. Introduction Seventy-five percent of severe mental illness (SMI) develops before the age of 24, making youth (ages 12-25) the population with the highest incidence of mental illness of any age group (Australian Bureau of Statistics 2012). Psychotic disorders like schizophrenia and schizoaffective disorder are SMIs that affect how individuals perceive reality and behave. Among those who experience psychotic symptoms, impairments in social and occupational functioning and reduced quality of life have been frequently reported (Kalucy et al., 2013; Okely AD, 2012). Delays in diagnosis and treatment of psychosis are associated with poorer long-term outcomes (Rosen et al., 2002), hence there is a need to identify early manifestations of symptoms and ensure access to early intervention. Advances in early identification strategies led to the recognition and description of at-risk mental states (ARMS) (Yung and McGorry, 1996). These occur in those who may be at increased risk for development of a first episode of psychosis (FEP) linked to a family history of psychosis, the presence of attenuated psychotic symptoms or periods when brief limited intermittent psychotic symptoms occur (BLIPS) (Yung et al., 2005b). Clinical tools such as the Comprehensive Assessment of at Risk Mental States (CAARMS) are used to identify individuals who meet these criteria, in the context of psychosocial impairment. For individuals living with psychosis, life expectancy is reduced by 15-20 years compared to healthy populations (Lawrence et al., 2013). This premature mortality is primarily attributed to cardiovascular and metabolic disease. Physical comorbidities including cardiovascular disease (CVD), metabolic syndrome (MetS), obesity and type two diabetes (T2D) are two to three times more prevalent in this population (Stubbs et al., 2015; Vancampfort et al., 2015). Side-effects of psychotropic medication are a contributing factor, with mean weight gain following exposure to antipsychotic medication of approximately 12kg during the first two years of treatment with second-generation antipsychotics (Alvarez-Jimenez et al., 2008). Sedentary lifestyles (Adair et
al., 2014), poor physical fitness (Shuval et al., 2014) and poor sleep quality (Grandner et al., 2014) are modifiable risk factors for CVD and MetS, and are common among people living with severe mental illness (Gretchen-Doorly et al., 2012; Vancampfort et al., 2013; Waters and Manoach, 2012). Reduced physical activity levels and fitness are independent risk factors for premature mortality (Kodama et al., 2009). Individuals with SMI engage in significantly less physical activity (Vancampfort et al.) and display lower levels of fitness then the general population (Vancampfort et al., 2016) . Modifiable risk factors such as smoking, drug abuse, and poor diet further contribute to the high prevalence of cardiometabolic diseases in individuals with SMI (De Hert et al., 2009). When considering interventions to address physical health, sleep behavior may be overlooked. Sleep has a significant impact on a person’s ability to engage in activity, and has a direct relationship to metabolic health (Anothaisintawee et al., 2016). Sleep occupies nearly one third of a lifespan and is essential for a healthy mind and body (Rechtschaffen, 1998). Lack of sleep or insomnia may constitute a prodromal symptom and often precedes acute exacerbation of psychotic symptoms (Tan and Ang, 2001). Insufficient sleep or poor sleep quality has also been associated with weight gain and increased risk of diabetes (Mallon et al., 2005). The cause of such changes include (1) alterations in glucose metabolism; (2) up-regulation of appetite (due to hormones leptin and ghrelin); and (3) decreased energy expenditure (Knutson et al., 2007). Identifying and addressing the poor physical health and adverse lifestyle-related behaviors of patients in the earliest phases could prevent the development of chronic diseases (Hennekens, 2007), and decrease the cost of treatment (Herman et al., 2013; Lehnert et al., 2011). A recent meta-analysis examined lifestyle-related cardiometabolic risk factors (CMRF) in youth with ARMS. Higher rates of sedentary behavior, poor fitness along with higher rates of smoking and alcohol abuse were found among individuals with ARMS compared to healthy volunteers (Carney et al., 2016). No differences were found in anthropometric measures including weight and body mass index (BMI). Another study reported modest increases in metabolic risk factors in anti-psychotic
drug-naïve youth with ARMS, specifically blood pressure, waist circumference and fasting blood glucose (Cordes et al., 2016). Recent evidence suggests that poor sleep quality is prevalent in ARMS populations (Lunsford-Avery et al., 2013), contributing to increased risk for metabolic disorders including diabetes and obesity (Keith et al., 2006; Yaggi, 2006 ). Few studies have examined the association between lifestyle-related CMRF, i.e. the relationship between fitness, physical activity and sleep quality, amongst youth with ARMS. Additionally, monitoring of cardiometabolic risk factors in specialized ARMS services occurs sporadically and there are currently no clear monitoring guidelines specific to this population (Carney et al., 2015). The aim of this cross-sectional study was to firstly, examine the prevalence of modifiable CMRF; physical activity, fitness and sleep quality, in individuals with ARMS compared to those with FEP, and healthy volunteers. Secondly, we examined the relationship between these CMRF and how they may contribute to an increased risk of physical health conditions like CVD and diabetes. We hypothesized a gradient of physical/mental health whereby, those with more severe illness i.e. FEP would display lower levels of physical activity, fitness and sleep quality to youth with ARMS, with healthy volunteers display the lowest levels of modifiable CMRF. 2. Methods 2.1. Participants Twenty individuals (10 ARMS, 10 FEP) were recruited from the youth mental health service at Bondi Community Health Centre, South Eastern Sydney Local Health District, Sydney, Australia. Ten healthy age-matched- volunteers were recruited from within the same metropolitan catchment area. Participants were aged between 18-25 years and were recruited between September, 2014 to June, 2016. The clinical sample of ARMS and FEP participants had access to a physical health program (Keeping the Body in Mind), which provides exercise and nutritional services and encourages engagement in healthy lifestyle habits (Curtis et al., 2016). This program, facilitated by an Accredited
Exercise Physiologist (AEP) (Lederman et al., 2016) and Accredited Practising Dietitian (APD), includes access to supervised, individual and group exercise sessions in a fully-equipped gym located in the centre, and individual consultations and group cooking classes (Teasdale et al., 2016). Inclusion criteria for ARMS were assessed by the Comprehensive Assessment of At-risk Mental States (CAARMS) instrument. Those with previous or current psychosis were excluded (Yung et al., 2005a). All healthy volunteer participants were screened using the CAARMS interview and were excluded if they met the CAARMS criteria for ARMS. The CAARMS interview was administered by a qualified mental health professional, trained in delivering the CAARMS tool. If participants screened for ARMS met criteria for FEP, they would be referred to the early psychosis program (EPP) and could then be invited to participate in the study as part of the FEP group. FEP participants were excluded if they had been diagnosed with FEP for greater than 2 years. Diagnosis was made by clinician consensus including the treating psychiatrist. Women who were lactating or pregnant and those with a physical disability inhibiting them from completing the required physical assessments were also excluded from the study. Ethics approval was obtained from the South Eastern Sydney Local Health District (SESLHD) (HREC ref 14/027) 2.2. Procedures All ARMS and FEP participants were outpatients being treated by a multidisciplinary team including psychiatric nurses, psychologists, psychiatrists, occupational therapists who work collaboratively to identify individuals with ARMS or a first episode psychosis and provide evidence-based early intervention treatments. ARMS and FEP patients who met the inclusion criteria were referred to the project by the treating mental health practitioners to obtain written informed consent. Experimental measures were obtained over two sessions, spaced one week apart, with each session lasting no more than an hour. In Session 1 participants completed the Physical Activity Readiness
Questionnaire (PAR-Q) which determined whether participants required a more detailed medical examination prior to fitness testing (Griffin, 2006). Participants were guided through a comprehensive fitness test (detailed in section 2.3.3), and provided with an ActiGraph GT3x accelerometer that they were asked to wear for a one week period. Follow up sessions were scheduled one week later, and participants were requested to attend the clinic fasted. Session two included a point-of-care finger prick test to assess blood sugar levels (either fasting or random) and total cholesterol. Additionally, participants completed questionnaires, assessing physical activity, sleep quality and mood. Following session two, participants returned the accelerometers. Healthy volunteer participants were recruited through various community organizations such as local universities and other tertiary education providers. 2.3. Outcome measures Demographic information - including gender, age, ethnicity and employment status, was collected from each participant at the initial session. Psychotropic medication use was obtained via the electronic medical record system. 2.3.1. Metabolic Cardiometabolic risk factors were recorded on a metabolic monitoring form, a tool used for screening and monitoring in routine care. Anthropometric measures included; body weight (kg), height (m), body mass index, waist circumference (cm) and resting blood pressure (mmHg). Body weight was measured with light clothing using a SECA scale and height using a wall-mounted stadiometer. Waist circumference was measured at the point of the umbilicus and blood pressure from a seated position after a 10-minute period of rest.
A CardioChek® (pts Diagnostics, Indiana, USA) finger-prick point-of-care testing kit was used to assess blood glucose levels (BSL) (fasting or random) and total cholesterol. 2.3.2. Physical activity Self-reported physical activity levels and sedentary behavior was measured via the 9-item International Physical Activity Questionnaire- short form (IPAQ- SF; Craig et al., 2003). The IPAQ has been validated in people with schizophrenia (Faulkner et al., 2006), and provides estimates of selfreported; vigorous-intensity activity, moderate intensity activity, walking and sedentary or sittingtime over a seven-day period. The metabolic equivalent (MET) refers to the metabolic cost of physical activity. Total MET-min/week was calculated... Objective physical activity levels were measured using ActiGraph wGT3X-BT wrist-worn accelerometers and ActiLife version 6.10.2 software. These devices provide objective 24 hour physical activity measurements including physical activity intensity, and duration of physical activity (Kelly et al., 2013). Participants were instructed to wear the device for a 7-day period at all times except for when showering or swimming. Activity data was collected over a one week period. Non-wear period was defined as a minimum length of 60 mins without any detectable activity. Cut point sets for determining intensity of exercise were determined using criteria validated against measures of oxygen consumption in the adult population (Troiano 2008). 2.3.3. Fitness Assessments were adapted from the YMCA fitness assessment manual (Lawrence and Coldin, 2000). Maximal oxygen consumption (VO2max) or aerobic capacity was estimated via a sub maximal aerobic exercise test using a Monark cycle ergometer. The YMCA protocol provides a validated estimate of maximal aerobic capacity (VO2max) in both clinical and non-clinical groups (Beekley et al., 2004; Rosenbaum et al., 2015). This test consisted of five stages including; a 3-minute warm up,
three 3-minute stages and a cool down. Resistance (watts) was increased at each stage in response to changes in heart rate (HR) and rate of perceived exertion (RPE). 2.3.3.2 Muscular strength/ endurance The push-up test protocol described by Jackson, Fromme, Plitt and Mercer (1994) was employed (Baumgartner et al., 2002). To accurately assess upper body strength, participants were asked to complete as many push-ups as possible until failure of technique or having to stop due to fatigue. Push-up technique varied from full push-ups to modified push-ups (on knees), depending on individual ability. Other exercise assessments included a forearm grip strength test using a handgrip dynamometer, a 1 minute crunch test for abdominal endurance and a sit and reach test to assess hamstring flexibility. All fitness tests were conducted by an Accredited Exercise Physiologist (Lederman et al., 2016). 2.3.4. Sleep behaviour Sleep behaviour was assessed via the Pittsburgh Sleep Quality Index questionnaire (PSQI). The Pittsburgh Sleep Quality Index (PSQI) is a 19-item self-report questionnaire that measures components of sleep including; sleep latency, duration, efficiency disturbances/continuity, and overall sleep quality (Buysse et al., 1989). Scores on the PSQI range from 0 to 21, with greater scores reflecting poorer sleep. The PSQI has been validated against gold standard laboratory-based sleep assessments and has been used extensively in schizophrenia (Afonso et al., 2011; Hofstetter et al., 2005), ARMS (Lunsford-Avery et al., 2013) samples and adolescent clinical groups (Kaneita et al., 2009). 2.3.5. Mood Self-reported symptoms of depression and anxiety were measured using the Beck Depression Inventory version II (BDI-II) and Beck Anxiety Inventory (BAI). These tools have been validated in both clinical and non-clinical populations (Beck et al., 1988; Fydrich et al., 1992).
2.4. Data Analysis Data analysis was conducted using SPSS (IBM: version 23). One-way ANOVAs, t-tests and chi-square tests were used to compare outcomes between the ARMS, FEP and healthy volunteer participants. Least Significant Difference (LSD) post-hoc tests were used to identify significant between-group differences. Partial η2 (ηp2) effect sizes were calculated for mean differences between groups. Spearman’s rho correlations were used to determine the relationship between variables. Correlations were considered significant if p ≤ 0.05 (2-tailed). The rules of thumb to interpret the effect sizes values are as follows (Gray & and Kinnear 2012); 0.01 5.5 mmol/L or random BSL > 7 mmol/L)
1 (11)
116.6 (9.3)
107.7 (9.7)
Systolic Blood Pressure (mmHg)
0 (0)
24.0 (4.6)
22.2 (2.8)
Body Mass Index
2 (22)
3.4 (0.8)
90.4 (14.2)
71.2 (5.9)
112.3 (8.8)
25.1 (5.0)
71.6 (11.2)
74.4 (16.6)
Weight (kg)
FEP (n=10)
ARMS (n=10)
Healthy volunteers (n=10) 69.6 (9.8)
Table 2. Mean (SD) for anthropometric and metabolic outcomes
p = 0.77 p = 0.35
x2= 2.25
p = 0.22
p = 0.93
p = 0.12
p = 0.31
p = 0.71
p
F(2,24) = 2.85
F(2,27) = 1.6
F(2,27) = 0.71
F(2,27) = 2.29
F(2,27) =1.2
F(2,27) = 0.34
Statistical test
ηp2 = 0.08
ηp2 = 0.19
ηp2 = 0.11
ηp2 = 0.01
ηp2 = 0.15
ηp2 = 0.08
ηp2 = 0.03
ηp2
IPAQ – International Physical Activity Questionnaire *p < 0.05, ARMS vs Healthy Volunteers **p < 0.05, ARMS vs FEP *** p < 0.05, FEP vs Healthy Volunteers
Table 3. Mean (SD) for subjective physical activity measures between groups, measured by the International Physical Activity Questionnaire Healthy ARMS FEP Statistical test P ηp2 volunteers (n=10) (n=10) (n=10) IPAQ vigorous physical 119 (156) 66 (70) 47.5 (75) F(2,27) =1.18 p = 0.32 ηp2 = 0.08 activity (mins/week) IPAQ moderate physical 378 (510) 65 (48) 201 (308) F(2,27) =2.07 p = 0.15 ηp2 = 0.13 activity (mins/week) IPAQ moderate to vigorous 497 (511) 130 (93) 260 (365) F(2,27) =2.57 p = 0.10 ηp2 = 0.16 physical activity (mins/week) IPAQ walking activity 1414 (802) 552 (351) 734.5 (455) F(2,27) =6.36 p < 0.05*,*** ηp2 = 0.32 (mins/week) IPAQ sedentary activity 2086 (822) 2709 (1359) 3108 (2155) F(2,27) =1.11 p = 0.34 ηp2 = 0.08 (mins/week) IPAQ MET mins 7130.2 2609 (1334) 3607.9 (1658) F(2,27) = 15.75 p < 0.001*,*** ηp2 = 0.54 (2494)
Moderate activity (mins/week) Light activity (mins/week) Sedentary activity (mins/week) % of time spent in moderate activity week % of time spent in light activity week % of time spent in sedentary activity week
Wear time (%) 632 (270) 1613(710) 5893 (1576) 7.7 (2.4)
19.2 (5.9) 73.1 (6.6)
1599 (1179)
5580 (2145) 12.3 (6.5)
17.5 (9.1)
70.23 (15.0)
81.5 (21.5)
ARMS (n=9)
1163 (777)
Healthy volunteers (n=9) 78.8 (29.6)
76.1 (3.9)
15.8 (2.7)
8.1 (1.8)
6933 (1251)
1439 (312)
728 (157)
88.6 (12.6)
FEP (n=9)
p = 0.07 p = 0.88 p = 0.23 p = 0.05
p = 0.55 p = 0.46
F(2,24) =0.13 F(2,24) =1.57 F(2,24) = 3.47
F(2,24) = 0.62 F(2,24) = 0.81
p = 0.64
P
F(2,24) =3.06
F(2,24) =0.46
Statistical test
Table 4. Means (SD) for objectively assessed physical activity (Actigraph accelerometer)
ηp2 = 0.06
ηp2 = 0.05
ηp2 = 0.22
ηp2 = 0.12
ηp2 = 0.01
ηp2 = 0.20
ηp2 = 0.04
ηp2
5.5 (9.1)
Hamstring Flexibility (cm) -6.3 (11.3)
25.2 (17.9)
Statistical test
-3.8 (19.3) F(2,26) = 1.92
p = 0.17
p = 0.24
p = 0.33
34.9 (10.2) F(2,26) = 1.15 16.4 (12.7) F(2,26) = 1.53
p = 0.61
p = 0.18
p = 0.35
P
43.3 (13.9) F(2,26) = 0.51
32.9 (13.8) F(2,25) = 1.86
2.5 (0.5) F(2,25) = 1.10
FEP (n=10)
VO2max – Volume of oxygen consumption (representing of cardiovascular fitness)
26.8 (11.9)
39.8 (9.0)
41.1 (9.6)
Push up test (repetitions)
39.8 (13.9)
45.5 (10.0)
Abdominal crunch test (repetitions) Grip Strength (kg)
34.1 (9.4)
42.0 (9.8)
2.5 (0.7)
ARMS (n=10)
VO2max (ml/kg/min)
VO2max (L/min)
Healthy volunteers (n=10) 2.9 (0.6)
Table 5. Mean (SD) for cardio-respiratory fitness, strength and flexibility measures between groups
ηp2 = 0.13
ηp2 = 0.11
ηp2 = 0.08
ηp2 = 0.04
ηp2 = 0.13
ηp2 = 0.08
ηp2
3.9 (1.5)
Pittsburgh Sleep Quality Index (PSQI) 8.0 (3.3)
1.4 (1.1)
0.9 (1.1)
1.9 (1.2)
1.3 (0.5)
0 (0)
FEP (n=10)
5.5 (3.4)
0.4 (1.0)
0.6 (1.3)
0.5 (0.7)
1.2 (0.8)
1.9 (1.1)
0.9 (0.6)
*p < 0.05, ARMS vs Healthy volunteer **p < 0.05, ARMS vs FEP
0.3 (0.5)
0 (0)
Need Meds to Sleep
0.9 (0.6)
Day Dysfunction Due to Sleepiness Sleep Efficiency 0.2 (0.6)
0.2 (0.4)
1.2 (0.6)
PSQI latency
Overall Sleep Quality
2.0 (0.8)
1.1 (0.6)
PSQI disturbance
0.3 (0.7)
PSQI duration
ARMS (n=10)
Healthy volunteers (n=10) 0.2 (0.4)
F(2,27) = 5.12
F(2,27) = 4.78
p = 0.01*
p = 0.02*,**
p = 0.33
p = 0.08
F(2,27) = 2.80 F(2,27) = 1.15
p = 0.01*,**
p = 0.22
p = 0.27
p = 0.35
P
F(2,27) = 6.02
F(2,27) = 1.61
F(2,27) = 1.37
F(2,27) = 1.12
Statistical test
ηp2 = 0.28
ηp2 = 0.26
ηp2 = 0.08
ηp2 = 0.17
ηp2 = 0.31
ηp2 = 0.11
ηp2 = 0.09
ηp2 = 0.08
ηp2
Table 6. Mean (SD) for subjective sleep measures between groups, measured by the Pittsburgh Sleep Quality Index (PSQI)
Table 7. Mean (SD) for self-reported psychiatric symptom ratings between groups Healthy ARMS FEP Statistical P volunteers (n=9) (n=10) test (n=10) Beck Depression 18.2 6.1 F(2,26) = p= 4.8 (6.2) Inventory 6.69 0.005*,** (12.6) (6.4) (BDI) Beck Anxiety 13.2 8.1 F(2,27) = p = 0.05 4.7 (5.7) Inventory 3.45 (7.3) (8.6) (BAI)
ηp2
ηp2 = 0.34
ηp2 = 0.20
*p < 0.05, ARMS vs Healthy volunteer **p < 0.05, ARMS vs FEP *** p < 0.05, FEP vs Healthy volunteer
