Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting.
Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting.
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DOI：
10.1371/journal.pone.0242186
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Bauni E
中科院分区：
文献类型：
--
作者：
Ssewanyana D;Abubakar A;Newton CRJC;Otiende M;Mochamah G;Nyundo C;Walumbe D;Nyutu G;Amadi D;Doyle AM;Ross DA;Nyaguara A;Williams TN;Bauni E
青少年往往更容易受到危险和鲁莽行为的伤害。生活在农村环境中的青少年可能经常经历贫困和一系列风险因素，这可能会增加他们对各种形式的健康风险行为（HRB）的脆弱性。了解青少年HRB的聚集性及其影响因素对制定干预措施和促进健康具有重要意义。本研究探讨在肯尼亚海岸的农村环境中的青少年的伤害和暴力，物质使用，卫生，体育活动和饮食相关的风险行为的共同发生。具体而言，本研究的目的是确定集群的HRB;基于五类健康风险行为，并确定与HRB集群相关的因素。对生活在基利菲健康和人口监测系统所覆盖地区的1 060名13-19岁青少年进行了随机抽样调查。参与者完成了一份关于健康行为的问卷，该问卷是通过音频计算机辅助自我访谈进行的。对13个行为因素（伤害和暴力，卫生，烟酒和药物使用，体力活动，饮食相关行为）进行潜类分析，以确定聚类和逐步有序logistic回归与非参数bootstrapping确定与聚类相关的因素。将年龄、性别、文化程度、就学率、心理健康、居住方式和父母监护水平等变量纳入初始逐步回归模型。我们确定了3个行为集群（集群1：低风险承担者（22.9%）;集群2：中等风险承担者（67.8%）;集群3：高风险承担者（9.3%））。相对于第一组，高风险组的成员（即中度或高度风险承担者）与年龄较大（p <0.001），男性（p<0.001），抑郁症状（p = 0.005），不上学（p = 0.001）和父母监督水平低（p<0.001）密切相关。肯尼亚沿海农村地区青少年中存在导致传染性和非传染性疾病的健康风险行为聚集现象。这表明迫切需要有针对性的多成分健康行为干预措施，同时解决青少年健康和福祉的各个方面，包括青少年的心理健康需求。
Adolescents tend to experience heightened vulnerability to risky and reckless behavior. Adolescents living in rural settings may often experience poverty and a host of risk factors which can increase their vulnerability to various forms of health risk behavior (HRB). Understanding HRB clustering and its underlying factors among adolescents is important for intervention planning and health promotion. This study examines the co-occurrence of injury and violence, substance use, hygiene, physical activity, and diet-related risk behaviors among adolescents in a rural setting on the Kenyan coast. Specifically, the study objectives were to identify clusters of HRB; based on five categories of health risk behavior, and to identify the factors associated with HRB clustering. A cross-sectional survey was conducted of a random sample of 1060 adolescents aged 13–19 years living within the area covered by the Kilifi Health and Demographic Surveillance System. Participants completed a questionnaire on health behaviors which was administered via an Audio Computer-Assisted Self–Interview. Latent class analysis on 13 behavioral factors (injury and violence, hygiene, alcohol tobacco and drug use, physical activity, and dietary related behavior) was used to identify clustering and stepwise ordinal logistic regression with nonparametric bootstrapping identified the factors associated with clustering. The variables of age, sex, education level, school attendance, mental health, form of residence and level of parental monitoring were included in the initial stepwise regression model. We identified 3 behavioral clusters (Cluster 1: Low-risk takers (22.9%); Cluster 2: Moderate risk-takers (67.8%); Cluster 3: High risk-takers (9.3%)). Relative to the cluster 1, membership of higher risk clusters (i.e. moderate or high risk-takers) was strongly associated with older age (p<0.001), being male (p<0.001), depressive symptoms (p = 0.005), school non-attendance (p = 0.001) and a low level of parental monitoring (p<0.001). There is clustering of health risk behaviors that underlies communicable and non-communicable diseases among adolescents in rural coastal Kenya. This suggests the urgent need for targeted multi-component health behavior interventions that simultaneously address all aspects of adolescent health and well-being, including the mental health needs of adolescents.
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