Role of lifestyle behaviours in the ethnic pattern of poor health outcomes in Leicester, England: analysis of a survey data set

The association of smoking with different eating and dietary behaviours: A cross-sectional analysis of 80 296 United Kingdom adults

BACKGROUND AND AIMS

Smokers typically have a lower body mass index (BMI) than non-smokers, while smoking cessation is associated with weight gain. In pre-clinical research, nicotine in tobacco smoking suppresses appetite and influences subsequent eating behaviour; however, this relationship is unclear in humans. This study measured the associations of smoking with different eating and dietary behaviours.

DESIGN

A cross-sectional analysis of data from health assessments conducted between 2004 and 2022.

SETTING

An independent healthcare-based charity within the United Kingdom.

PARTICIPANTS

A total of 80 296 men and women (mean ± standard deviation [SD]: age, 43.0 ± 10.4 years; BMI, 25.7 ± 4.2 kg/m2; 62.5% male) stratified into two groups based on their status as a smoker (n = 6042; 7.5%) or non-smoker (n = 74 254; 92.5%).

MEASUREMENTS

Smoking status (self-report) was the main exposure, while the primary outcomes were selected eating and dietary behaviours. Age, sex and socioeconomic status (index of multiple deprivation [IMD]) were included as covariates and interaction terms, while moderate-to-vigorous exercise and sleep quality were included as covariates only.

FINDINGS

Smokers had lower odds of snacking between meals and eating food as a reward or out of boredom versus non-smokers (all odds ratio [OR] ≤ 0.82; P < 0.001). Furthermore, smokers had higher odds of skipping meals, going more than 3 h without food, adding salt and sugar to their food, overeating and finding it hard to leave something on their plate versus non-smokers (all OR ≥ 1.06; P ≤ 0.030). Additionally, compared with non-smokers, smoking was associated with eating fried food more times per week (rate ratio [RR] = 1.08; P < 0.001), eating fewer meals per day, eating sweet foods between meals and eating dessert on fewer days per week (all RR ≤ 0.93; P < 0.001). Several of these relationships were modified by age, sex and IMD.

CONCLUSIONS

Smoking appears to be associated with eating and dietary behaviours consistent with inhibited food intake, low diet quality and altered food preference. Several of these relationships are moderated by age, sex and socioeconomic status.

Associations of environment and lifestyle factors with suboptimal health status: a population-based cross-sectional study in urban China

INTRODUCTION

Suboptimal health status (SHS), an intermediate state between chronic disease and health, is characterized by chronic fatigue, non-specific pain, headaches, dizziness, anxiety, depression, and functional system disorders with a high prevalence worldwide. Although some lifestyle factors (e.g. smoking, alcohol consumption, physical exercise) and environmental factors (e.g. air quality, noise, living conditions) have already been studied, few studies can comprehensively illustrate the associations of lifestyle and environment factors with general, physical, mental, and social SHS.

METHODS

A cross-sectional study was conducted among 6750 urban residents aged 14 years or over in five random cities from September 2017 to September 2018 through face-to-face questionnaires. There were 5881 valid questionnaires with a response rate of 87%. A general linear model and structural equation model were developed to quantify the effects of lifestyle behaviors and environment factors on SHS.

RESULTS

The detection rates of general, physical, mental, and social SHS were 66.7, 67.0, 65.5, and 70.0%, respectively. Good lifestyle behaviors and favorable environment factors positively affected SHS (P < 0.001). Lifestyle behaviors had the largest effect on physical SHS (β = - 0.418), but the least on social SHS (β = - 0.274). Environment factors had the largest effect on mental SHS (β = 0.286), but the least on physical SHS (β = 0.225).

CONCLUSIONS

Lifestyle behaviors and environment factors were important influencing factors of SHS. Physical SHS was more associated with lifestyle. Lifestyle and environment were similarly associated with mental and social SHS.