Data for these analyses were drawn from the Sleep Health Foundation 2019 web-based Insomnia survey. The primary aim of this cross-sectional survey was to investigate prevalence of sleep disorders and sleep problems in the Australian population. The survey additionally included self-reported diagnoses of diverse chronic health conditions, including gout. Characteristics of the sample surveyed have been reported elsewhere(9). Briefly, the sample incorporated Australian adults (≥ 18 years, n = 2044) recruited from an online survey panel by Dynata. The online panel comprises > 500,000 Australians, and allows for recruitment of a representative sample of Australian adults using a three-step randomisation process aimed at reducing recruitment bias(3, 9). Participants were naïve to the content and aims of the survey during initial recruitment and screening to reduce bias. The CHERRIES checklist has previously been reported for this study, see Appleton et al. for details (9).
Obstructive sleep apnoea (OSA)
Diagnosed OSA was determined by an affirmative response to the question ‘Have you ever been told by a doctor that you have any of the following conditions? Obstructive Sleep Apnoea’ (response items: yes, no, refused, don’t know). Possible undiagnosed OSA (henceforth possible OSA) was determined based on the frequency in the past month of symptoms including observed frequent/loud snoring, and observed pauses in breathing/stopping breathing during sleep. Possible OSA was categorised as self-report of witnessed breathing pauses (i.e apnoeas).
Doctor diagnosed medical conditions were determined with the question ‘Have you ever been told by a doctor that you have any of the following conditions?...’ for gout, arthritis, high blood pressure, obesity, and heart disease. Response options were yes, no, refused or don’t know; participants were included in analyses if they provided either a yes or no response to the question on gout.
Patient reported outcome measures for sleep
Doctor diagnosed restless leg syndrome (RLS) or periodic leg movements during sleep (PLMS) were assessed using the question ‘Have you been diagnosed with restless legs or periodic leg movements of sleep? (yes/no)’.
Worry about getting to or maintaining sleep (yes/no) was established from the question ‘How often have each of the following things disturbed your sleep or kept you up at night in the past month? Worry about getting to sleep or getting back to sleep after waking during the night’. Response items included rarely or never, a few nights a month, a few nights a week, and every or almost every night. Participants who indicated a few nights a week or every/almost every night were coded as worried about either getting to sleep, or maintaining sleep, > 3 nights/week.
Discussing sleep with a health professional
participants were asked ‘During the last 12 months have you discussed your sleep with any of the following health professionals?’ Responses included general practitioner, physiotherapist, chiropractor, specialist in private practice, hospital physician (with or without admission), other physician, psychologist, psychiatrist, pharmacist or other (specify). Participants who indicated they had spoken with at least one health professional were coded as a yes response.
Pain which disturbs sleep (yes/no) was defined as a response of ‘most nights (4–6 nights/week)’ or ‘every night’ to either of the following questions: ‘How often does pain stop you from going to sleep at night?’ or ‘How often does pain wake you up at night?’
Adequate sleep
participants were asked ‘In the past month, how often have you experienced feeling you got adequate or satisfactory sleep’? Response options were ‘rarely or never, a few nights a month, a few nights a week, every/almost every night’. Participants were coded as feeling they receive adequate sleep if they responded with either ‘a few nights a week, or every/almost every night’.
An inadequate opportunity to sleep as a consequence of their typical routine (yes/no) was coded yes if their response to the question ‘Does your current work schedule or typical weekday routine, including your duties at home, allow you to get enough sleep?’ was ‘sometimes’, ‘rarely or never’ or ‘don’t know’.
Covariates
Age (years), sex (categories: male, female and other) and Body Mass Index from self-reported height and weight were included as covariates. Standard alcoholic drinks were self-reported, using the question: “Thinking about alcoholic beverages such as beer, wine, liquor or mixed drinks, how many alcoholic beverages do you typically drink each week?”. Responses were categorised to allow comparison to the Australian guidelines to reduce health risks from drinking alcohol (10) as ‘none’, ‘≤1 standard drink/day’, ‘>1 to ≤ 2 standard drinks/day’, and ‘>2 standard drinks/day’.
Data Analysis
Data were analysed using IBM SPSS version 26.0 (IBM Corporation). Significant differences in sociodemographic and health characteristics of respondents by gout (yes or no) were examined using Mantel-Haenszel test of trend or Pearson χ2 statistic. Multivariable logistic regression analysis was used to examine associations between OSA (predictor) and gout (outcome) for Objective 1, adjusting for known correlates of gout (age, sex, BMI, alcohol consumption and arthritis).
Multivariable logistic regression analyses were used to examine associations between gout (predictor) and each of the patient reported sleep outcomes (summarised in Fig. 1), with each model adjusted for age, sex and BMI, selected based on established relationships with sleep problems in community samples(3, 9). Significance values for all models reported are based on the Wald statistic.