Clustering of multiple health risk factors among a sample of adolescents in Liberia: a latent class analysis

被引:6
作者
Atorkey, Prince [1 ,2 ,3 ,4 ]
Asante, Kwaku Oppong [5 ,6 ]
机构
[1] Univ Newcastle, Sch Med & Publ Hlth, Univ Dr, Callaghan, NSW 2308, Australia
[2] Hunter New England Local Hlth Dist, Hunter New England Populat Hlth, Locked Mail Bag 10, Wallsend, NSW 2287, Australia
[3] Univ Newcastle, Prior Res Ctr Hlth Behav, Callaghan, NSW, Australia
[4] Hunter Med Res Inst, Newcastle, NSW, Australia
[5] Univ Ghana, Dept Psychol, Legon, Accra, Ghana
[6] Univ Free State, Dept Psychol, Bloemfontein, South Africa
来源
JOURNAL OF PUBLIC HEALTH-HEIDELBERG | 2022年 / 30卷 / 06期
关键词
Cluster analysis; Multiple health risk factors; Adolescents; Liberia; LIFE-STYLE BEHAVIORS; PHYSICAL-ACTIVITY; SUBSTANCE USE; ALCOHOL; ASSOCIATIONS; FRUIT; DIET;
D O I
10.1007/s10389-020-01465-y
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Aim Non-communicable diseases (NCDs) are associated with modifiable health risk factors. There is a lack of evidence regarding clusters of health-related behaviours among school-going adolescents from sub-Saharan Africa. This study was conducted to identify clustering patterns of health risk factors (i.e. smoking tobacco, inadequate fruit intake, inadequate vegetable intake, physical inactivity, sedentary behaviour, anxiety and depression) and association with sociodemographic factors among school-going adolescents in Liberia. Subject and methods The 2017 Liberian Global School-based Student Health Survey on 2774 adolescents aged 11 years and above (52.5% females) sampled with a two-stage cluster sample design was used. Latent class analysis was used to generate the clusters and latent class regression assessed the associations between sociodemographic factors and the clusters. Results We identified three clusters labelled as (1) 'low substance use, moderately active cluster' (34.8%); (2) 'inadequate fruit and vegetable cluster' (48.9%) and (3) 'risk taking cluster' (16.3%)'. Compared to cluster 1, adolescent boys [AOR = 1.71, 1.29-2.27, p < 0.001], and those in grade 10-12 [AOR = 1.51, 1.13-2.02, p < 0.001] were more likely to belong to cluster 2. Participants aged 15 years and above [AOR = 0.60, 0.39-0.91, p = 0.018] were less likely to belong to cluster 2. Compared to cluster 1, adolescents aged 15 years and above [AOR = 3.58, 1.33-9.62, p = 0.011] and those with low socio-economic status [AOR = 1.83, 1.22-2.73, p = 0.003] were more likely to belong to cluster 3. Conclusion These results underscore the need for interventions that address adolescent multiple health risk factors, especially considering sociodemographic differences.
引用
收藏
页码:1389 / 1397
页数:9
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