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Socio-Environmental Determinants of the Disparities in Health Behaviors among Minority Youth
Submitted:
03 February 2024
Posted:
08 February 2024
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Studies including only children and/or adolescents <18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Nicholson 2012 [46] | All Australia | Infants 0-1 year Children 4-5 years |
10090 | 2-years longitudinal study | Composite variable (family annual income, years of parental education, parental occupational status) divided in quintiles | Sleep disturbances | Two or more parent-reported sleep problems (difficulty getting to sleep, not happy sleeping alone, waking during the night, and restless sleep), four or more nights per week | Lower SES was associated with increased odds for parent-reported sleep problems |
Biggs 2013 [44] | Adélaïde | Children 5-10 years from 32 primary schools | 1845 | Cross-sectional study | Area SES index based on postal code (low, mid, high) | Sleep duration | Parent-reported sleep duration | Children from low SES areas reported later bedtimes and reduced sleep opportunity than children from higher SES areas |
Hardy 2017 [40] | New South Wales | Children aged 5-16 years | 7555 | Cross-sectional study |
Area index (based on post codes and divided in tertiles) | Sleep duration | Self-reported sleep duration (adherence to recommendation according to age) | There was no difference in adherence between high and low SES children |
Williamson 2019 [36] | All Australia | Infants from general population aged 0-1 year | 4517 | 10-year longitudinal cohort study |
Socioeconomic risk index (average of financial hardship score and composite SES score [derived from income, education, and occupational prestige]) | Sleep disturbances | Parent-reported sleep problems trajectories (single question; no sleep problems, mild sleep problems over time, increased middle childhood sleep problems, limited infant/preschool sleep problems, persistent sleep problems through middle childhood) | Higher socioeconomic risks increased the odds for all sleep problem trajectories compared to no sleep problems |
Studies including adult participants ≥ 18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Moffitt 1991 [48] | South Australia | Adults from the general population | 1765 | Cross-sectional study | Annual household income | Sleep disturbances | Sleep subscale of the Nottingham health profile | Low income was associated with more sleep problems |
Adams 2012 [47] | South Australia | Adults from the general population | 3007 | Cross-sectional study | Education (high school or less, still studying, trade/diploma, university degree or higher) Household income ($<30000, 30–60000, 60–100000, >100000) |
OSA | High risk OSA (STOP-BANG questionnaire) | High risk for OSA was associated with less education and lower income |
Soltani 2012 [45] | Queensland | Adults women from an established cohort | 3655 | Cross-sectional study | Family income per week (>$1,000, $700-$1000, $400-$700, <$400) Highest level of education (tertiary, complete high school, incomplete high school) Housing tenure (own, rent) Employment status (employed, home duties, unemployed/economically inactive) |
Sleep quality | PSQI global score (0-5, 5-10, >10) | Women with poor sleep quality were more likely to have not completed high school, to be either unemployed or to be undertaking home duties and to be renting their current home |
Liviya NG 2014 [43] | Melbourne | Adults from general population | 707 | Cross-sectional study | Education (nontertiary vs tertiary) Occupation (manager, professional, associate professional, clerical, or service) Income per week (≥$2000, $1600–$1999, $1000–$1599, $0–$999) |
EDS | Excessive daytime sleepiness (ESS score >10) | There was no association between SES and EDS |
Studies including adult participants ≥ 18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Seib 2014 [42] | South-East Queensland | Women from general population aged 60-70 years | 322 | Cross-sectional study |
Employment status (employed, domestic duties, unemployed/disability pension, retired) Income (<20000 AUD, 20000-80000 AUD, >80000 AUD) |
Sleep disturbances | Sleep disturbance (General Sleep Disturbance Scale) | Women who were unemployed or on a disability support pension reported more sleep disturbance |
Clark 2017 [41] | All Australia | Women from one cohort aged 31-36 years. Women from another cohort aged 59-64 years |
7835 | Cross-sectional study |
Occupation (manager/professional, clerical/sales, trades/production/labourer) | Sleep duration | Sleep duration Short sleep (≤6h/day vs >6h/day) Long sleep (≥8h/day vs <8h/day) |
In the young cohort, trades/production/labourers slept less than other occupational categories |
Perales 2017 [39] | All Australia | Adults from general population aged 20-70 years | 9181 | Cross-sectional study |
Education (degree or higher, professional qualification or secondary school, below secondary school) Employment status (full-time, part-time, self-employed, unemployed, full-time student) House tenure (owned outright, mortgage, rental) Material deprivation (yes vs no) Lack of prosperity (poor/very poor vs other) Financial worsening (one of last year's major life events) Income poverty (annual income below 60% of the sample median) |
Sleep duration | Sleep duration | Lower education, material deprivation and lack of prosperity were associated with shorter sleep duration, while unemployment with longer sleep duration |
Studies including adult participants ≥ 18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Gordon 2019 [38] | All Australia | Adults from general population | 2211 | Cross-sectional study |
Education (primary/secondary school, TAFE/technical college, university) Occupation (manager/professional, white collar, blue collar, retired/pension, unemployed/student) |
Sleep duration | Perceived sleep insufficiency frequency in past month (0-13 vs 14-30 days) | There were no statistically significant associations between frequent perceived insufficient sleep and education or occupation |
Hartescu 2019 [37] | Australia, South Africa, China, South Korea, and UK | Adults from South Africa, Australia, China, South Korea and UK recruited through social media and websites | 9238 | Multi-site Cross-sectional study |
Education (less than primary/primary/lower secondary; upper secondary/post-secondary nontertiary; tertiary) Employment status (yes vs no) |
Insomnia | Insomnia (DSM-5 criteria) | Lower education and unemployment were associated with insomnia diagnosis |
Metse 2020 [2] | All Australia | Adults from general population | 1265 | Cross-sectional study |
Education (up to secondary school vs technical/tertiary) Employment status (employed vs unemployed) |
Sleep duration Sleep latency Sleep efficiency |
Self-reported sleep duration, sleep onset latency, number of awakenings, WASO, and sleep efficiency (suboptimal vs appropriate according to age-related cut-offs) | Lower education was associated with higher odds of suboptimal sleep duration and sleep onset latency. Unemployment was associated with an increased likelihood of suboptimal sleep efficiency. |
Studies including only children and/or adolescents <18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
McDowall 2017 [49] | Wellington | children 2-12y attending inpatient or day wards of a children's hospital | 115 | Cross-sectional study |
Parental education (6 levels) Household income (5 levels) |
Sleep duration Sleep latency Sleep problems |
Parent-reported sleep latency, sleep duration, and sleep problems (Children’s Sleep Habits Questionnaire score) | Parents from homes with higher annual income were more likely to report shorter sleep latencies and fewer sleep problems. Parents with higher education reported shorter weekday sleep latencies. |
Muller 2019 [30] | All the country | Preschoolers 3-4y from a birth cohort | 910 | Cross-sectional study |
Maternal socioeconomic deprivation (composite score from yes/no responses to various deprivation characteristics) | Sleep duration | Mother-reported sleep duration (<10h vs 10-13h) | Preschoolers whose mothers experienced high individual deprivation were twice as likely as children of mothers reporting no deprivation characteristics to have short sleep on the weekend but not on weekdays |
Harding 2020 [50] | All the country | Children 6-10y whose parents completed an online survey | 1205 | Cross-sectional Study |
Parental education (secondary or below vs tertiary or above) | Sleep Related Breathing Disorder | High risk for SDB (Sleep Related Breathing Disorder Scale of the Pediatric Sleep Questionnaire score ≥0.33) |
Parental education was not associated with high risk for SDB |
Studies including adult participants ≥ 18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Paine 2004 [51] | All the country | Adults 20-59 y from the general population | 2670 | Cross-sectional Study |
Employment status (unemployed vs employed) | Insomnia | Insomnia symptoms (difficulty falling asleep, frequency of nocturnal awakenings, difficulty getting back to sleep, waking too early, wake feeling refreshed) | Being unemployed increased the risk of reporting having difficulty falling asleep and waking 3 or more times during the night. |
Studies including adult participants ≥ 18 years old | ||||||||
Study | Location | Participants | Sample size | Type of study | SES determinant | Type of sleep disturbances | Sleep measurement tool | Author’s conclusions |
Gander 2005 [52] | All the country | Adults 30-60 y from the general population | 5441 | Cross-sectional study |
Eligibility for community services card (yes vs no) | Excessive Daytime Sleepiness | EDS (Epworth Sleepiness Scale score >10) | Eligibility for a community services card was not associated with EDS |
Paine 2016a [53] | All the country | Adults 20-59 y from the general population | 4330 | Cross-sectional study |
Employment status (employed with no night work, employed with night work, unemployed) | Sleep duration | Self-reported sleep duration: short sleep (<7 h), long sleep (>8 h), insufficient sleep (extension of sleep duration by >2 hours on free days compared with scheduled days) | The odds of reporting insufficient sleep were higher for those employed in night work and lower for the unemployed. The odds of reporting short sleep were higher for night workers and unemployed. The likelihood of reporting long sleep was higher for unemployed. |
Paine 2016b [54] | All the country | Adults from the general population | 10369 | Cross-sectional study |
Education (tertiary, some secondary, no secondary qualification) Equivalized household income (low, middle, high tertiles) |
Insomnia | Difficulty falling asleep, frequent nocturnal awakenings, early morning awakenings (all/most of the time vs a good bit/some/a little/none of the time) | Difficulty falling asleep and frequent nocturnal awakenings were more likely among those with less than a secondary school education. Being in the highest household income tertile was associated with a lower likelihood of reporting early morning awakenings. |
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