Physical Health in Clinical High Risk for Psychosis Individuals: A Cross-Sectional Study

Background: The clinical high risk for psychosis (CHR-P) phase represents an opportunity for prevention and early intervention in young adults, which also could focus on improving physical health trajectories. Methods: We conducted a RECORD-compliant clinical register-based cohort study. The primary outcome was to describe the physical health of assessed CHR-P individuals, obtained via Electronic Health Records at the South London and Maudsley (SLaM) NHS Foundation Trust, UK (January 2013–October 2020). Results: The final database included 194 CHR-P subjects (46% female). Mean age was 23.70 ± 5.12 years. Percentage of tobacco smokers was 41% (significantly higher than in the age-matched general population [24%]). We found that 49% of subjects who consumed alcohol had an AUDIT-C (Alcohol Use Disorder Identification Test) score above 5 (hazardous drinking), with an average score of 4.94 (significantly higher than in the general population [2.75]). Investigating diet revealed low fiber intake in most subjects and high saturated fat intake in 10% of the individuals. We found that 47% of CHR-P subjects met the UK recommended physical activity guidelines (significantly lower than in the general population [66%]). Physical parameters (e.g., weight, heart rate, blood pressure) were not significantly different from the general population. Conclusions: This evidence corroborates the need for monitoring physical health parameters in CHR-P subjects, to implement tailored interventions that target daily habits.


Introduction
The clinical high risk for psychosis (CHR-P) construct enables the identification of individuals who have a greatly increased risk of developing a first episode of psychosis within 1-2 years compared to the general population [1,2]. The prevalence of CHR-P individuals in the community is still undefined [3] and there is scarce knowledge about the outcomes of individuals who do not transition to psychosis [4], who might remain at a lower level of functioning compared to non-psychiatric subjects [5]. In those individuals who will transition to psychosis, most will develop a schizophrenia spectrum disorder according to the DSM/ICD [6]. A 15-year follow-up study found that CHR-P individuals develop a psychotic disorder up to 10 years after initial presentation [7], in line with a risk of transition ranging from 65 to 79% at 10 years, reported by other studies [8]. In addition to attenuated psychotic symptoms (APS), brief limited intermittent psychotic symptoms (BLIPS) and genetic risk and deterioration syndrome (GRD) that define the construct [9], many CHR-P individuals often present other psychiatric comorbidities (i.e., anxiety, depres-

1.
Fagerström Test for Nicotine Dependence (FTND) [44] is a standardized instrument consisting of 6 questions exploring daily cigarette consumption, compulsive use, and dependence. The score ranges from 0 to 10 (with higher scores indicating a most severe level of dependence to nicotine). More precisely, scorings from 0 to 2 indicate a low level of dependence, from 3 to 4 low-moderate dependence, from 5 to 7 moderate dependence, and more than 8 a high level of dependence. For people that use other types of nicotine consumption other than cigarette smoking (e.g., e-cigarette, nicotine gum, or nicotine patches), we have investigated habits and reported information in adapted versions of FTND already used in the literature (i.e., equivalence of 10 vape nicotine puffs for a cigarette [45] or a re-worded test for gum users [46]). 2.
AUDIT (Alcohol Use Disorder Identification Test) [47] consists of 10 self-administered questions to investigate alcohol use disorder. When AUDIT-C score, which includes core questions regarding alcohol units consumed and frequency of drinking, is equal or above 4, it might indicate hazardous drinking. Regarding the AUDIT total score, a low level of risk is identified with an overall score between 0 and 7, the range from 8 to 15 is the most appropriate for simple advice focused on the reduction of drinking. Higher scores (up to 19) suggest the need for brief counselling and continuous monitoring, while a complete diagnostic evaluation for alcoholic dependence is warranted  for scores 20 and over.  3. DINE (Dietary Instrument for Nutritional Education) [48] is a structured interview investigating the intake of dietary fiber and fat (unsaturated and saturated). Scores for fibers and fat are rated into 3 different categories: low (under 30), medium (between 30 and 40), and high intake (more than 40). Scores for unsaturated fat are rated as low (less than 6), medium (6 to 9), and high (more than 9) 4.
IPAQ (International Physical Health Questionnaire) [49] rates the level of physical activity. This tool comprises 3 different categories of physical activity based on the intensity (vigorous, moderate, and walking) and quantifies the amount of time spent sitting.

Variables
Baseline descriptive variables included: ( Physical parameters: weight in kilograms, height in meters, Body Mass Index (BMI), waist circumference in centimeters, heart rate in beats per minute (bpm), respiratory rate in acts per minute (apm), systolic and diastolic pressure in mmHg.

Statistical Analysis
This clinical register-based cohort study was conducted according to the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) Statement [50] (Table S1, Supplementary Materials). The primary outcome was to describe physical health data (see "variables") in the sample. Sociodemographic parameters and physical health data (including missing data) were described with mean and SD for continuous variables, and absolute and relative frequencies for categorical variables. We employed the use of Student's t-test for independent samples of numerical variables (i.e., number of cigarettes smoked, FTND score in smokers, AUDIT-C and AUDIT total score in drinkers, DINE total score, IPAQ score, weight, height, Body Mass Index, waist circumference, heart rate, respiratory rate, systolic pressure, diastolic pressure). Fisher's exact test was employed for categorical variables (i.e., number of tobacco smokers and alcohol drinkers). A secondary aim was to compare the physical health data with the national average in the general population: we compared data from our sample with values taken from UK Office for National Statistics census data, referring to the same age-span (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35) and the same period (2013-2019). The 95% confidence intervals were computed for our sample data using bootstrapping (10,000 samples). Differences were considered to be statistically significant if the census value did not fall within the bootstrapped 95% confidence intervals. Another secondary aim was to detect differences between male and female CHR-P subjects. For all analyses, statistical tests were two-sided and statistical significance was defined as p < 0.05, except for multiple t-test comparisons where we adjusted statistical significance using Bonferroni correction (p values are reported unadjusted). All analyses were conducted in IBM SPSS 28.0.

Sample Characteristics
The final database included 194 CHR-P subjects, 90 (46%) females and 104 (54 males. Mean age was 23.70 ± 5.12 years. The majority of the sample comprised white (41 and black British (21%) subjects. Sociodemographic parameters are described in Table   Table 1

Tobacco Use
Tobacco smokers in the sample were 80 (41%, bootstrapped 95%CI 35-48%). Amo the subjects who smoked, the mean number of cigarettes smoked every day was 9 ± (bootstrapped 95%CI 7-11), the mean FTND score was 2.51 ± 2.54 (bootstrapped 95% 1.95-3.06). Overall, 64 subjects (33%) had a low to moderate level of dependence (FTN score ≤ 5), 12 subjects (6%) had a moderate level of dependence (FTND score between and 7), and 4 subjects (2%) had a high level dependence (FTND score ≥ 7) ( Figure 1).  UK government statistics published in 2018 [51] concerning smoking habits in the general population reported that 24% of the subjects were smokers in the same age group (16)(17)(18)(19)(20)(21)(22)(23)(24), with an average consumption of 11 cigarettes a day. Average FTND score in UK, for the general population, has been reported as 3.00 [52]. Therefore, our sample reported a percentage of smokers that was significantly higher and almost double compared to the general population, while the number of cigarettes smoked daily and average FTND score in smokers were comparable.
UK government statistics published in 2017 [53] reported a higher proportion of drinkers (80%) in the same age-group (16)(17)(18)(19)(20)(21)(22)(23)(24) in the general population. However, proportions of hazardous drinking were lower: 1.5% were drinking more than 5 days a week and 30% were drinking more than 4 units on the heaviest drinking day. Also, recent evidence reports an average AUDIT-C score in the general population of 2.75 [54], which is significantly lower than the score in our sample.
UK government statistics published in 2017 [53] reported a higher proportion drinkers (80%) in the same age-group (16)(17)(18)(19)(20)(21)(22)(23)(24) in the general population. However, p portions of hazardous drinking were lower: 1.5% were drinking more than 5 days a we and 30% were drinking more than 4 units on the heaviest drinking day. Also, recent e dence reports an average AUDIT-C score in the general population of 2.75 [54], which significantly lower than the score in our sample.
We did not find comparable values for DINE scores in government statistics.    (Figure 3).
Government statistics published in 2015 [55] showed that 66% of young adults (19-34 years) in England met the recommended physical activity guidelines (75 min of vigorous or 150 min of moderate activity, see discussion) for vigorous or moderate activity, compared to the significantly lower proportion of 47% (bootstrapped 95%CI 41-53%) in our sample. Detailed physical health data of the sample are described in Table 2.  Government statistics published in 2015 [55] showed that 66% of young adults (19-34 years) in England met the recommended physical activity guidelines (75 min of vigorous or 150 min of moderate activity, see discussion) for vigorous or moderate activity, compared to the significantly lower proportion of 47% (bootstrapped 95%CI 41-53%) in our sample.
Detailed physical health data of the sample are described in Table 2 This evidence is in line with average parameters collected in the general UK population (i.e., BMI = 24.6 [56], waist circumference = 82.5 cm [57]). Detailed physical parameters of the sample are reported in Table 3.

Gender Differences of Physical Health Data in CHR-P Samples
• Tobacco use: differences in the number of smokers were nearly significant (p = 0.08) between male and female subjects (47% vs. 34% respectively). • Alcohol use: differences were not significant for the number of drinkers (p = 0.60), AUDIT-C score (p = 0.63) and AUDIT total score (p = 0.63) between male and female subjects. • Type of diet: differences between male and female subjects were non-significant for DINE total (p = 0.28), DINE fiber (p = 0.09), DINE fat (p = 0.10), DINE unsaturated fat (p = 0.69). • Physical activity: difference between male and female subjects were significant (p < 0.001) for both days (1.80 ± 2.03 vs. 0.66 ± 1.37) and minutes-per-day of vigorous physical activity (70.20 ± 96.35 vs. 18.66 ± 39.34). There were no significant differences between male and female subjects regarding moderate activity, walking, and time spent sitting. • Physical parameters: significative differences between male and female subjects were detected for weight (p < 0.001), height (p = 0.002), heart rate (p = 0.002), systolic pressure (p < 0.001), and diastolic pressure (p = 0.002). These differences reflect physiological differences that are also present in the general population [58].

Discussion
To our knowledge, the present study includes one of the largest CHR-P samples to date (n = 194) that has been investigated on physical health and lifestyle outcomes. We reported 41% of CHR-P individuals were tobacco smokers, almost double compared to the percentage in the UK general population of the same age. Overall, 49% of the subjects who consumed alcohol had an AUDIT-C score above 5 (hazardous drinking), with an average AUDIT-C score of 4.94, which is almost double of the average AUDIT-C score in the UK general population (2.75). Investigation of diet revealed low fiber intake in the majority of the sample and high saturated fat intake in 10% of the individuals. The results for physical activity showed a low proportion of subjects meeting the recommended physical activity guidelines (47% vs. 66% of young adults of the same age in UK).
Prevalence of tobacco smoking in individuals with schizophrenia is four to five times higher than the healthy population and over 60% of the patients are smokers [59], but smoking becomes a habit before the onset of schizophrenia in 77% of the cases [60] with an average anticipation of 11 years [61]. Hence, the onset of the smoking habit might coincide with the period in which the first symptoms of psychosis appear [62,63]. Our results of increased smoking habit in CHR-P individuals confirm this evidence and are in line with previous research from our team [2,[64][65][66]. This CHR-P state thus provides an interesting framework to examine this association [67], constituting not only a phase in which smoking habit and attenuated psychotic symptoms coexist and influence each other, but also a window of opportunity to investigate specific reasons for initiating tobacco use and provide effective smoking cessation support [68]. In fact, on average, tobacco dependence was low-moderate (average FTND was 2.5), suggesting the CHR-P stage may be an optimal period for smoking cessation strategies to be effective, since they could be implemented before the development of a higher level of dependence, as shown in recent schizophrenic samples where FTND score was around 5 [69].
Regarding alcohol use in our sample, even if the proportion of individuals not consuming alcohol is comparable to the same age group in the UK general population, it is important to underline how both AUDIT-C and AUDIT total average scores in drinkers were almost coincident with the threshold score for hazardous alcohol use. If we also take into account the long-known issue of inconsistency related to self-reports of alcohol use in young adults [70], these averages may also be undervalued. This evidence confirms previous reports about higher alcohol consumption in CHR-P individuals and that an at-risk status is associated with alcohol involvement [71,72]. Of note, alcohol was also found as an important confounder between cannabis misuse and psychosis conversion in a high-risk sample [72]. These observations underline the importance of implementing specific alcohol abuse monitoring and prevention interventions in the CHR-P phase.
Results from the investigation on the type of diet revealed that more than 60% of individuals in the sample had a low intake of fiber, while almost 10% of the sample had a high saturated fat intake. Since there is still scarce evidence in the literature about the use of the DINE questionnaire in the general population, our study is one of the first in the CHR-P literature to show standardized scores for specific types of diet intake. Also, our data show how diet could be targeted in these individuals to prevent other cardio-metabolic risk factors that are well known in psychosis and at-risk individuals [21,73].
UK national guidelines about physical activity published in 2021 [74] recommend at least 75 min of vigorous or 150 min of moderate activity every week; in our sample, averages were far below these values, with around 52 min of vigorous activity and 75 min of moderate activity. Of note, average vigorous physical activity was significantly different between male and female subjects (126 vs. 13 min), but also differences in moderate physical activity (174 vs. 70 min) were relevant, even if the difference was not statistically significant. Among the limitations of our study, the lack of a control group was addressed by comparing our results with data from the UK census using bootstrapping. However, individuals participating in national surveys might not be help-seeking for mental health problems, like CHR-P individuals presenting to OASIS. Also, data from national surveys might not be collected in clinical examinations by doctors or other healthcare professionals. Finally, the cross-sectional design of our study does not explain causality (or lack of) between unhealthy lifestyles in CHR-P individuals and other important outcomes (i.e., risk of transition).

Conclusions
Our study, through the investigation of physical health and lifestyle outcomes in a large sample size of CHR-P individuals, showed that the percentage of smokers is 41% (twice as high as the general population) and those who consume alcohol have drinking behaviors that might be more dangerous and possibly lead to abuse and addiction. Diet was unbalanced, with high proportions of low fiber intake and high saturated fat intake, while subjects meeting the recommended physical activity guidelines were a low proportion (47% vs. 66% of young adults of the same age in UK). This evidence corroborates the need for monitoring physical health parameters and lifestyle in CHR-P subjects to increase our knowledge about their causes and implement tailored interventions for targeting daily habits. Even if high-quality research focused on physical health in young people with CHR-P is still scarce [29], interventions aimed at reducing alcohol and tobacco use, instead of promoting a balanced diet and physical activity that adheres to national guidelines, would constitute favorable and generalizable treatments in CHR-P, as they are effective towards comorbidities (i.e., depression) and not only for the individuals who will develop psychosis.
Supplementary Materials: The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/brainsci13010128/s1, Table S1: The RECORD statement -checklist of items, extended from the STROBE statement, that should be reported in observational studies using routinely collected health data.

Informed Consent Statement:
Consent is not required to analyze the deidentified dataset for approved research studies. Patients may opt-out of inclusion in the deidentified dataset.

Data Availability Statement:
The authors give no permission to share raw data.

Conflicts of Interest:
PFP received honoraria or grant fees from Lundbeck, Angelini and Menarini in the past 36 months outside of the current work.