Sleep, Dietary, and Exercise Behavioral Clusters Among Truck Drivers With Obesity

Abstract

Objective Our objectives were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health and psychosocial factors. Methods Participants’ (n=452, BMI M=37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior co-variation. Cluster differences were tested with generalized estimating equations. Results Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in BMI. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. Conclusions Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.

Does stress influence sleep patterns, food intake, weight gain, abdominal obesity and weight loss interventions and vice versa?

“…They did Effect of stress on food intake N. R. W. Geiker et al 89 obesity reviews not report, however, the proportion of very short and very long sleepers, which might be of relevance to health. Studies specifically assessing poor and short sleep and very long sleep found both associated with increased levels of mental stress and obesity (83)(84)(85)(86). Among children and adolescents, results are more consistent and show a decline in sleep duration of more than 1 h per night (87), most prevalent among children and adolescents of racial/ethnic minorities and those with low socioeconomic status (88).…”

Obesity in the Workplace

“…Diet, calorie expenditure, diabetes, stress, and quality and quantity of sleep all appear clustered around obesity. 68–70 Workers with obesity are over-represented vs the general population in certain occupations. 32,70,71 For example, one study found that non-Hispanic white males who worked in health care support (36.3%), protective service (34.3%), and transportation and material moving (33.7%) had the highest prevalence of obesity while among non-Hispanic white female workers, the highest prevalence of obesity was in farming/fishing/forestry (35.9%), transportation and material moving (31.5%), and production (30.4%).…”

Perspectivas do uso de mineração de dados e aprendizado de máquina em saúde e segurança no trabalho

“…Cabe citar que existem outras técnicas de comparação entre vetores com outras medidas de similaridade, como distância de cossenos (cosine similarity) e similaridade de Jaccard, entre outras 16,17 . Alguns estudos na área da saúde, como o estudo realizado por Olson et al 18 , utilizaram o algoritmo k-means para agrupamento de perfis. Nesse estudo 18 , foram agrupados perfis de caminhoneiros de acordo com atributos comuns, como duração do sono, prática de exercícios e hábitos alimentares.…”

“…Alguns estudos na área da saúde, como o estudo realizado por Olson et al 18 , utilizaram o algoritmo k-means para agrupamento de perfis. Nesse estudo 18 , foram agrupados perfis de caminhoneiros de acordo com atributos comuns, como duração do sono, prática de exercícios e hábitos alimentares. Outro estudo, realizado por Lee et al 19 , utilizou uma variação do algoritmo k-means para agrupar perfis de equipes médicas de acordo com um questionário que avaliou a incidência e grau da síndrome de burnout.…”

“…Gao et al 22 Olson et al 18 Lee et al 19 Quadro Com os resultados obtidos na pesquisa realizada na Biblioteca Virtual em Saúde e nos demais estudos citados neste ensaio, elaborou-se uma relação de finalidades, aplicações e estudos exemplificativos (Quadro 2).…”