A 70-day diary study reveals why activity, sleep, socializing, nature, diet, and mood may not follow the same pattern for everyone.
Study: Examining the clustering of lifestyle factors and affect in daily life: An idiographic approach. Image Credit: MMD Creative / Shutterstock
In a recent study published in the journal Applied Psychology: Health and Well-Being, researchers examined the clustering of lifestyle behaviors and emotional experiences in daily life.
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Healthy lifestyle factors, such as adequate physical activity, limited alcohol use, good sleep quality, a healthy diet, and tobacco avoidance, have received increasing attention in recent years. Adherence to these healthy lifestyle factors is associated with a higher life expectancy and reduced mortality. Studies have demonstrated clustering of lifestyle factors, though limited data exist on how emotional health and lifestyle factors cluster differently across individuals.
The clustering of lifestyle factors has been commonly examined in cross-sectional analyses. For instance, one study reported that people who eat better tend to exercise more, while those with higher alcohol intake tend to use more tobacco. Other studies have investigated longitudinal changes in lifestyle factors; one study found that increases in physical activity over time may be accompanied by reductions in smoking or increases in social interactions.
Further, research indicates that lifestyle fluctuations co-occur daily, leading to within-person contemporaneous associations in which changes in one lifestyle on a given day are accompanied by fluctuations in others on the same day. Of late, studies have focused on within-person temporal associations, wherein fluctuations in a given lifestyle at one time point are accompanied by changes in another at a later time point.
About the study
In the present study, researchers evaluated the clustering of affect and lifestyle factors in daily life among a non-clinical convenience sample of adults in the United States. Participants were recruited to complete daily surveys for 70 days. The Brief Pittsburgh Sleep Quality Index, modified to collect past-night data, was administered to assess sleep quality. Participants also specified their daily nap duration.
The Godin Leisure-Time Exercise questionnaire, modified for daily use, was administered to measure physical activity. To assess dietary intake, participants reported daily fruit and vegetable servings, which the researchers used as a brief dietary indicator, as well as the number of alcoholic and caffeinated beverages consumed per day.
The Scale of Positive and Negative Experiences was used to measure negative and positive affect. Participants also reported their time spent relaxing, enjoying nature (nature engagement), socializing with others (social engagement), engaging in hobbies, and watching movies or television. The clustering of affect and lifestyle factors was assessed using network modeling.
Specifically, graphical vector autoregression (GVAR) models assessed associations at the between-person and within-person (contemporaneous and temporal) levels. One set of GVAR models included only lifestyle factors, while another set also included negative and positive affect. Person-specific idiographic network models were also analyzed.
Findings
In total, 79 individuals aged 18 to 80 years were included. Most participants were male (53%), and White (72%), and about 57% reported some form of employment. The lifestyle factors-only GVAR model showed associations at the between-person and both within-person contemporaneous and temporal levels. Physical activity was correlated with nature engagement and vegetable and fruit intake at the between-person level.
At the within-person contemporaneous level, alcohol use was associated with social engagement, nature engagement was associated with social engagement and physical activity, and physical activity was associated with vegetable and fruit intake. At the within-person temporal level, autocorrelations were observed for all lifestyle factors but sleep duration.
This meant that spending more time on hobbies than usual on one day was associated with more hobby time the next day. In the within-person contemporaneous model that also included affect, daily positive affect showed same-day partial associations with vegetable and fruit intake, social engagement, sleep duration, time spent relaxing, nature engagement, alcohol intake, and time spent on hobbies.
Further, daily negative affect was positively associated with sleep distress and negatively associated with time spent on hobbies and time spent watching movies or television. Person-specific idiographic models showed wide variations in clustering across participants. For instance, physical activity was associated with nature engagement only for one participant, whereas it was more central to the network for another subject.
Conclusions
In sum, the study explored clustering of emotional health and lifestyle factors in daily life. The findings illustrate clustering in the entire sample at multiple levels. Moreover, personalized networks highlighted between-person differences in how these factors covaried in daily life.
Overall, recognizing that these associations vary across individuals represents a preliminary step to the development and evaluation of personalized lifestyle interventions. However, the findings are associational and come from a non-clinical, non-representative convenience sample using brief self-reported measures, so they should be interpreted as preliminary rather than as clinical guidance.
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