Study population

In the present cross-sectional, multicenter study, we enrolled clinically stable, adult patients (≥ 18 years old) who underwent LT, followed-up in seven different Italian Hepatology Units. Inclusion criteria were LT performed at least 12 months before enrolment and absence of clinical events during the last 6 months. Exclusion criteria were multiorgan transplant, re-transplant, vascular or biliary complications, systemic disorders (e.g., CV disease, cancer, infection, recurrence of pre-LT liver disease), unstable clinical conditions, or hospital admission in the last 6 months. Human Immunodeficiency Virus infection, deafness, or inability to carry out a telephone interview in full understanding, or holidays in the last 4 weeks represented further exclusion criteria. Patients were enrolled between June 1stand September 30th, 2021.

All patients gave their consent before participating. Trained professional staff scheduled a telephone interview, during which patients answered to the composite questionnaire. Subjects were invited to be alone in a soundless setting. We recorded demographic data including gender, age, transplant date, referral centre, region of residence, education degree, presence of caregiver, alcohol, and tobacco habits. Afterwards, patients completed four questionnaires in an estimated total time of 10–15 min.

QuestionnairesThe international physical activity questionnaire

The International Physical Activity Questionnaire (IPAQ) was developed by the World Health Organization in 1998 for the surveillance of PA [12]. Two forms are available. The 27-item long version and the IPAQ-short form (SF) have been validated against accelerometer measurements as a gold standard in 12 countries including Italy [12]. The IPAQ-SF includes 11 items about time spent on walking, vigorous and moderate intensity activity, sedentary activity, and demographic information, including education, and other items concerning comprehension of the questionnaire. Information about PA is reported in minutes per day and/or days per week [13].

The IPAQ-SF investigates three types of activity organized in the three domains. The specific types of activity are walking, moderate-intensity activities and vigorous intensity activities. Frequency (measured in days per week) and duration (time per day) are recorded separately for each activity. The items were structured to provide separate scores on walking, moderate-intensity, and vigorous-intensity activity as well as a combined total score to describe global level of activity.

Another measure of volume of activity can be computed by weighting each type of activity by its energy requirements defined in Metabolic Equivalent Task (MET, multiples of the resting metabolic rate) to yield a score in MET-minutes. A MET-minute is computed by multiplying the MET score by the minutes of activity performed. MET-minute scores are equivalent to kilocalories for a 60-kg person. An average MET score was derived for each type of activity. There are three possible levels of PA suggested for classifying populations which take account of the concept of total PA of all domains. The proposed levels are: (i) inactive; (ii) minimally active; (iii) high active category.

We considered a further sub classification: patients with MET = 0 were considered as totally inactive.

The IPAQ also provides an indicator of sedentary activity, measuring time spent sitting on a typical week expressed in ‘minutes’ (Sitting Total Minutes/week = weekday sitting minutes × 5 weekdays + weekend day sitting minutes × 2 weekend days) [12]. The IPAQ sitting question is an additional indicator variable and is not included as part of any summary score of PA.

We also conducted a qualitative analysis of PA since in the questionnaire patients indicated the prevalent activity. We organized data according to three subgroups: non-structured activity (any bodily movement produced by skeletal muscles that requires energy expenditure), structured (a subset of PA that is planned and repetitive and has as a final or an intermediate objective the improvement or maintenance of physical fitness) and sport activity (it involve PA and exercise but differ in that they also have a set of rules, or goals to train and excel in specific athletic skills) [14, 15].

Other questionnaires

Data to calculate the Medi-Lite score were recorded. Medi-Lite represents a validated tool to measure the adherence to MD [16], and consists of nine items about daily consumption of fruit, vegetables, cereals, meat and meat products, dairy products, alcohol, and olive oil, and the weekly intake of legumes and fish [16]. The final score ranges from 0 (low adherence) to 18 (highest adherence).

The QoL was evaluated with the Short Form Health Survey (SF-12), which consists of twelve questions exploring eight health domains to evaluate physical and mental health [17]. We computed two summary scores of physical (Physical Component Summary, PCS-12) and mental (Mental Component Summary, MCS-12) health, using the weighted means of the eight domains.

Finally, we assessed the return to work with both closed and open ad hoc questions, using a specialized employment questionnaire as reported in our recently published study focused on MD [18].

Statistical analysis

All analyses were conducted with SPSS (version 28.0), after analysing the missing values. Pairwise deletion was used when a case had missing answers.

Study population description and analysis of physical activity patterns

Descriptive statistics, such as frequencies, percentages, median, mean [± standard deviation (SD)] were used to describe the sample’s characteristics.

Analyses of IPAQ score variables

We investigated the relationships between the IPAQ variables and personal data, life-style patterns, Medi-Lite score and QoL. We computed independent samples χ2 tests and t tests comparing totally inactive (MET = 0) versus active (MET > 0) patients. Specifically, χ2 tests were used to compare genders, educational levels (primary school, secondary school, high school, and university), place of stay (northern, central, southern Italy), occupation (blue collar, white collar, unemployed/retired), caregiver (yes, no), smoking (yes, no), alcohol habit (none, occasional, continuous). The t tests were used for age, time from LT, Medi-Lite, IPAQ, and the PCS-12 and MCS-12 scores. As measures of effect size, Cramer’s V was computed for χ2 tests.

Mann–Whitney and Kruskal–Wallis non-parametric tests (for two or more groups, respectively) were used to examine the continuous variables such as PA expressed as MET.

Multivariate analysis to identify predictors of total inactivity

A multivariable logistic regression analysis was developed to describe and test hypotheses about relationships between the categorical outcome variable (inactive vs. active) and some continuous predictor variables. As indicators of overall model evaluation, we referred to Hosmer–Lemeshow inferential goodness-of-fit test [19] (lower values and non-significance indicate a good fit to the data)and Nagelkerke R2 [20] (values range from 0 to 1). Statistical significance of individual predictors was tested using the Wald chi-square statistic (p < 0.05). The resultant predicted probabilities (odds ratios) can be used to determine if higher or lower probabilities are indeed associated with an event (i.e. inactive patient) given the different levels of the predictor variables (e.g. age). Odds ratios are expressed together with 95% confidence interval.

Sample size determination

For observational studies that include logistic regression, a minimum sample size of 500 is conventionally needed to infer the statistics that represent the parameters [21]. The other recommended rules of thumb include the following: n = 100 + 50i, where i refers to number of independent variables in the final [21]. Coherently with the aims of the current study, we hypothesized that at least eight predictors (gender, age, educational level, smoking and alcohol habits, adherence to MD, physical and mental health) will account for the outcome variable. As such, we calculated to enrol at least 500 patients (i.e. 100 + [50 × 8] = 500).

Ethical approval

The local Independent Ethics Committee approved the study (CEAVC, Tuscany, Italy, approval number 20659) that was developed according to the ethical parameters established in the Declaration of Helsinki (1964) and its later amendments [22].