A systematic review of lifestyle patterns and their association with adiposity in children aged 5–12 years

Abstract

SummaryDiet, physical activity, sedentary behaviour and sleep are typically examined independently with childhood adiposity; however, their combined influence remains uncertain. This review aims to systematically summarize evidence on the clustering of these behaviours through lifestyle patterns and evaluate associations with adiposity in children aged 5–12 years. Search strategies were run in six databases. Twenty‐eight papers met the inclusion criteria, six of which included all four behaviours. A range of lifestyle patterns were identified (healthy, unhealthy and mixed). Mixed patterns were most frequently reported. Unhealthy patterns comprising low physical activity and high sedentary behaviour were also frequently observed. Mixed patterns comprising healthy diets, low physical activity and high sedentary behaviour were more commonly seen in girls, whereas boys were more physically active, similarly sedentary and had unhealthier diets. Children from lower socio‐economic backgrounds tended to more frequently display unhealthy patterns. Unhealthy lifestyle patterns were more often associated with adiposity risk than healthy and mixed patterns. With few studies including all four behaviours, it is difficult to establish a clear picture of their interplay and associations with adiposity. Nonetheless, reliance on lifestyle patterns is likely more beneficial than individual behaviours in targeting adiposity and improving understanding of how these behaviours influence health.

MINISTOP 2.0: a smartphone app integrated in primary child health care to promote healthy diet and physical activity behaviours and prevent obesity in preschool-aged children: protocol for a hybrid design effectiveness-implementation study

“…We will, however, analyse whether there are any differences in intervention effect depending on socioeconomic status or migration background. We use self-reported data for some outcomes, which is common in large studies measuring lifestyle changes [53]. However, the combination of selfreporting and the lack of blinding of participants and nurses, who are responsible for data collection, increases the risk of differential social desirability bias between arms, and research participation effects more generally.…”

Association between Leisure Screen Time and Junk Food Intake in a Nationwide Representative Sample of Spanish Children (1–14 Years): A Cross-Sectional Study

“…However, we hypothesize that screen time may be associated with junk food consumption in our study through different pathways. First, evidence shows that children belonging to low-income families are more likely to spend longer periods using screens and follow worse dietary patterns [ 10 ] as parents have longer working hours, less time to look after their children, and are less informed on the harmful effects of low-quality diets. In this sense, parents having longer working hours may offer their children more readily available options requiring less of their time, such as mobile devices to entertain them and junk food to feed them.…”

“…Based on literature [ 10 , 20 , 32 , 33 , 34 , 35 , 36 , 37 ], we used the following variables as potential confounders: (1) sex (male and female) and (2) age of the child in years (1–2, 3–5, 6–11, and 12–14), categorized according to the Spanish school system, as we assume that children in different school stages have different routines, screen time usages, and dietary patterns; (3) education level of the parents (low, medium, and high); (4) relationship between who answered the questionnaire and the child (parents and others); (5) family structure (couple-parent, single-parent, couple-parent or single-parent living with other family members, and others); (6) sleep duration (proper sleep duration and short sleep duration), dichotomized according to the recommendations of the National Sleep Foundation (NSF) [ 38 , 39 ]; (7) physical activity in their leisure time (no exercise, physical or sports activity occasionally, physical activity several times a month, sports or physical training several times a week); (8) Body Mass Index for age (BMI-for-age) z-score, which is the standardized measure through weight and height reported by person who answered the questionnaire, calculated according to the child growth standards of the World Health Organization (WHO) [ 40 ]. We treated as missing data those z-scores classified as Biologically Implausible value (BIV) [ 41 , 42 , 43 ] for weight-for-age, height-for-age, and BMI-for-age; and (9) proxy of parent frequency of sweet, soft drink, fast food, and snack intake (high and low).…”

“…Childhood overweight and obesity are associated with a combination of some genetic, behavioral, and environmental factors [ 9 ], which cause an energy imbalance between calories consumed and calories expended [ 1 ]. A systematic review published in 2020 shows that unhealthy lifestyle behaviors, including higher patterns of screen time, unhealthy dietary habits, and lower levels of physical activity during childhood are associated with adiposity risk [ 10 ]. In this sense, dietary patterns have become of poorer quality over the last years mainly due to a reduction in the adherence to the Mediterranean Diet, which evidence shows is a protective factor for adiposity [ 11 ], and an increase in the intake of junk food, defined as food that is unhealthy but is easy to eat [ 12 ], which might be due to Western influences [ 13 , 14 , 15 ].…”

Associations between contextual and compositional characteristics of early childcare facilities with health, health behaviours and well-being among young children aged 06 years: protocol for a scoping review

“…26 It is well known from previous research that health inequalities already exist among young children. For instance, children whose parents have a lower socioeconomic position are more likely to be physically inactive, 27 consume unhealthy meals and snacks [27][28][29] and to show worse health outcomes [30][31][32] than those coming from families with a higher socioeconomic position. However, it still remains unclear whether compositional and contextual factors mediate or moderate emerging health inequalities.…”