Preventive medicine reports · 2024
Moderating effects of socioeconomic status and geographical location on the Health4Life school-based intervention.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Egan Lyra, Gardner Lauren A, Newton Nicola C, O'Dean Siobhan, Champion Katrina E
Аннотация
OBJECTIVE: This study evaluated the moderating effects of socioeconomic status (SES) and geographical location on the efficacy of an eHealth school-based multiple health behaviour change intervention - Health4Life - in targeting alcohol and tobacco use, dietary intake, knowledge, behavioural intentions, and psychological distress over 24-months.
METHODS: Data from the Health4Life cluster-randomised controlled trial conducted from 2019 to 2021 in 71 Australian secondary schools were analysed (N=6639; baseline age 11-14yrs). Schools were from metropolitan (89%) and regional (11%) areas, and participants' SES was classified as low (15%), mid (37%), and high (48%) relative to the study population. Primary outcomes included alcohol and tobacco use, and a composite indicator of poor diet. Secondary outcomes were knowledge, behavioural intentions, and psychological distress. Latent growth models assessed moderating effects of SES and geographical location on between-group change over 24-months.
RESULTS: Geographical location moderated the intervention's effect on odds of reporting a poor diet (OR = 1.79, 95% CI = 1.32-2.43, p < 0.001) and diet-related behavioural intentions (OR = 0.71, 95% CI = 0.56-0.89, p = 0.024) over time. Subset analyses indicated that intervention participants in regional areas had higher odds of reporting a poor diet (OR = 1.61, 95% CI = 1.13-2.29, p = 0.008), while those in metropolitan areas had higher odds of improving diet-related behavioural intentions (OR = 1.13, 95% CI = 1.01-1.27, p = 0.041), compared to the control group. No other significant moderation effects were observed.
CONCLUSIONS: While significant disparities were generally not observed, the geographical differences in intervention effects on diet and diet-related intentions suggest that co-designed and tailored approaches may benefit disadvantaged adolescents to address the disproportionately high rates of lifestyle risk behaviours among these priority populations.
METHODS: Data from the Health4Life cluster-randomised controlled trial conducted from 2019 to 2021 in 71 Australian secondary schools were analysed (N=6639; baseline age 11-14yrs). Schools were from metropolitan (89%) and regional (11%) areas, and participants' SES was classified as low (15%), mid (37%), and high (48%) relative to the study population. Primary outcomes included alcohol and tobacco use, and a composite indicator of poor diet. Secondary outcomes were knowledge, behavioural intentions, and psychological distress. Latent growth models assessed moderating effects of SES and geographical location on between-group change over 24-months.
RESULTS: Geographical location moderated the intervention's effect on odds of reporting a poor diet (OR = 1.79, 95% CI = 1.32-2.43, p < 0.001) and diet-related behavioural intentions (OR = 0.71, 95% CI = 0.56-0.89, p = 0.024) over time. Subset analyses indicated that intervention participants in regional areas had higher odds of reporting a poor diet (OR = 1.61, 95% CI = 1.13-2.29, p = 0.008), while those in metropolitan areas had higher odds of improving diet-related behavioural intentions (OR = 1.13, 95% CI = 1.01-1.27, p = 0.041), compared to the control group. No other significant moderation effects were observed.
CONCLUSIONS: While significant disparities were generally not observed, the geographical differences in intervention effects on diet and diet-related intentions suggest that co-designed and tailored approaches may benefit disadvantaged adolescents to address the disproportionately high rates of lifestyle risk behaviours among these priority populations.