Configural path of obesity: linkage of physical activity and lifestyle based on fuzzy-set qualitative comparative analysis

Abstract

Obesity plays a significant role in the burden of various health conditions, it is not only a global health issue but challenges the national public health system. Some regions of China still face a high prevalence of obesity, and it is broadly recognized that physical activities interact with lifestyle in different pathways would affect obesity. We aim to capture different configurational paths that lead to obesity, using the fuzzy set Qualitative Comparative Analysis. Eight obesity-related variables were involved, and data were collected between January 1, 2021, and January 31, 2022. The study shows six configurational paths result in obesity, in which the necessary condition is "educational status," and core conditions of "the time of exercise" and "weekly sitting time*sleeping time less than 6 h*second hand smoking exposure on average of 4-6 days per week *keep excising on average of 4 times per week* exercise intensity on the shortness of breath, markedly increased heart rate, heavy sweating" play an important role in the obesity outcome, and the solution exhibits acceptable consistency is 0.50. The six configurational paths solution consistency is 0.76, and the solution coverage is 0.31. Besides the necessary condition and core factors that play(s) an important role in the development of obesity, we have to consider the multiple factors of physical activity and lifestyle have a cross-cutting effect on obesity. This can offer a better understanding of the mechanisms that cause obesity by identifying and characterizing the regional population, which would help develop an effective protective measure for obesity.

Keywords: fsQCA; lifestyle; obesity; physical activity; qualitative comparative analysis of fuzzy sets.

Figure 1

Logistic diagram of antecedent conditions.

Figure 2

Distribution of body mass index by age. Explanation: The < 18.5, >18.5 and < 24, >28, ≧25 and < 28, are all the BMI indicators, the unite is kg/m². Numbers on the vertical axis represent the number of cases.

Figure 3

Relationship between BMI and influences. Explanation: × represents p > 0.05, in which no significant relationship between variables. The size of the bubble indicates the strength of the correlation between the two variables. The lighter the color, the lower the correlation (because some variables’ colors are so light, they can not be read, so turn it to black).

Figure 4

The outcome of regression analysis.