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Abstract
Objective We aimed to estimate the distribution of health-related behaviours and dietary habits by sociodemographics among public workers in China.
Design Cross-sectional study.
Setting A representative sample was obtained from 10 government-run institutions in Hunan province of China.
Participants A total of 5029 public workers were included in this study.
Primary and secondary outcome measures Prevalence on their sociodemographic characteristics, health-related behaviours and dietary habits. Socioeconomic status (SES) scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income. Multivariate logistic regression analysis and categorical principal component analysis were used to estimate differences in health-related behaviours and dietary habits by sociodemographics.
Results The distribution of health-related behaviours and dietary habits was varied by sociodemographic groups. Middle-aged groups (41–60 years) were more likely to smoke (for men, 34.5%), use alcohol (for men, 22.5%), and have short sleep duration (for men, 36.3%; for women, 39.6%). Young participants (≤30 years) were more likely to have multiple unhealthy behaviours and dietary habits. Those in low-SES have a significant higher rate of smoking (ORadj=1.46, 95% CI: 1.15 to 1.85) and leisure-time physical inactivity (ORadj=1.18, 95% CI: 1.02 to 1.37), but a lower rate of late sleeping (ORadj=0.69, 95% CI: 0.57 to 0.83) than those in high-SES. Notably, older men (≥51 years) with low-SES preferred the ‘smoked and pickled foods and dessert’ and ‘fish and nut’ pattern. In high-SES groups, 41–50 year old people preferred the ‘traditional foods’ and ‘cereals and dairy product’ pattern. No difference in dietary patterns by sociodemographics was found among women (p<0.05).
Conclusions Our findings of the disparity distribution of health-related behaviours and dietary habits by specific gender, age and SES among Chinese public workers have important policy implications for developing targeted health interventions to facilitate health-related behaviours and dietary habits in this population.
- epidemiology
- public health
- preventive medicine
Data availability statement
Data are available upon reasonable request. The data analysed during this study are included in the article. The numerical data used to support the findings of this study are available from the corresponding author upon reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
This is the first study using a large sample from a representative urban public worker population.
This is also the first study to use the categorical principal components analysis method to study health-related behaviours and dietary habits by sociodemographic characteristics such as gender, age and socioeconomic status groups.
Many variables were self-reported, and the findings may be subject to recall bias.
Results and conclusions referred to dietary habits are based on a questionnaire that have not been validated in the population of interest so they cannot be made with confidence owing to the increased opportunity for measurement bias.
Many variables were self-reported, and the findings may be subject to recall bias.
Introduction
Globally, health-related behaviours and dietary habits play an essential role in shaping population health. Health-related behaviours can be defined as voluntary behaviours that relate to health or disease,1 some of which may lead to negative outcomes from a health perspective, such as smoking, alcohol drinking, physical inactivity and sedentary lifestyle. Health-related behaviours have been recognised as major determinants of morbidity and mortality,2 3 and their role extends to the development and progression of diseases, the effectiveness of treatments and quality of life.4 The most common diseases can be prevented with the adoption of healthier behaviours.5 6 Among various health-related behaviours, smoking is a chief contributor to morbidity and the leading cause of mortality.6 7 Dietary habits are the habitual decisions of individuals or group of people regarding what foods they eat.8 Some unhealthy dietary habits (eg, eating midnight snack and consuming pickled foods) have been shown to be associated with a higher risk of cancer.9–11 The importance of healthy behaviours and dietary habits is underscored by the US Affordable Health Care Act, which provides unprecedented universal coverage for preventive behavioural and dietary health services.12
The distributions of health-related behaviours and dietary habits usually differ by sociodemographic characteristics, such as gender, age and social class.13–15 Men (including male adolescents), for instance, are more likely than women to smoke, binge drink;16 17 women (including female adolescents), by contrast, are less likely to engage in physical activity.18 Younger people were more likely to get involved in risk behaviours and unhealthy dietary habits than older people.19 20 Those with high socioeconomic status (SES) were less likely to smoke, and have a low level of physical inactivity, but more likely to have high nutritional eating patterns.21–25 These sociodemographic factors shape social context and day-to-day routines, which in turn influence health behaviours and dietary habits, as well as people’s ability to change. Knowledge of sociodemographic-specific behavioural characteristics and their interrelationships can help pinpoint intervention targets and guide for the development of efficacious interventions.
Although health-related behaviours and dietary habits have been found to be associated with sociodemographics such as gender, age and SES, these factors are usually studied separately. There is a lack of comprehensive study on health-related behaviours and dietary habits by taking into account of all sociodemographic factors together, for instance, by combining age and gender. Also, most of the study were conducted in developed countries, it is also important to learn about the situation in developing countries such as China. The current study was conducted to understand the distribution of health-related behaviours and dietary habits by sociodemographics among public workers in urban area of China.
Methods
Study design and setting
This cross-sectional study was conducted between January 2018 and December 2018 in Changsha city, Hunan province of China which has been described in our previous study.26 Briefly, a multistage sampling design was carried out to obtain a representative sample. First, 10 institutions were randomly sampled from the government-run institutions that volunteered to participate in the study in Changsha city. Second, in each sampled institution, all the workers were selected to take part in our study using cluster sampling. In China, public workers are those working in the national legislative branch, judicial branch, administrative organs, the Party organs of the Communist Party of China and the democratic parties, people’s organisations and public institutions, who perform public duties according to law, such as civil servants, regular employee at university or hospital. After obtaining informed consent, eligible participants were asked to complete a digital self-reported questionnaire. The eligibility criteria for participants included: (1) being able to speak and understand Chinese, (2) being 18–60 years old, (3) working at the selected institution and (4) having no serious limb diseases. We invited 9149 public workers, and 7181 agreed to participate in, representing a response rate of 78.5%. Finally, a total of 5029 public workers that meet the criterion were include in this study.
Sociodemographic characteristics
The collected sociodemographic data included information on demographic (age, gender, marital status) and socioeconomic characteristics (education and annual household income). SES scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income.27 Educational attainment was divided into six groups, and annual household income was divided into seven groups. The SES score ranged from 1 to 42. According to the tertile values of the SES score distribution, study participants were further divided into three groups: low-SES (L-SES, 1–12 points), medium-SES (M-SES, 13–18 points) and high-SES (H-SES, 19–42 points).
Health-related behaviours
Data on health-related behaviours were collected using standardised questionnaires (see in online supplemental appendix 1), which included smoking, alcohol drinking, leisure‐time physical inactivity, sedentary behaviour, late sleeping and short sleep duration. Smoking was defined as smoking at least one cigarette a day for more than half a year, which can be further classified into three status: never, former or current smoking. Alcohol drinking was defined as drinking at least once a week for more than half a year, and can be further classified into three status: never, former or current smoking. Leisure‐time physical inactivity was defined as 30 min/day of physical activity at a frequency of once per week or less. Sedentary behaviour was defined as >2 hours/day sitting (such as watching TV and surfing the internet) apart from work and study. Late sleeping was defined as sleeping after midnight, and short sleep duration was defined as sleeping time <7 hours per night.
Supplemental material
Dietary habits
Dietary habits included four eating behaviour habits and 15 kinds of food consumption. Eating behaviour habits included irregular meals habit (yes or no), eating midnight snack habit (yes or no), eating gluttony habit (yes or no) and salty taste habit (yes or no). Food consumption was assessed by asking whether consuming each of the following food groups for more than three times/week: (1) rice, (2) wheat, (3) grains, (4) fish, (5) vegetables, (6) poultry meat, (7) livestock meat (pork, beef/lamb), (8) soybean and products, (9) fruits, (10) eggs, (11) dairy products, (12) nuts, (13) desserts, (14) pickle food and (15) smoked fish or meat.
Data analysis
Crude frequencies and weighted percentages were calculated for the distribution of sociodemographic characteristics. Among these sociodemographic variables, gender, age and SES were considered as important factors for health-related behaviours and dietary habits. Thus, analyses of health-related behaviours and dietary habits were stratified by these three variables. Participants were grouped into eight categories based on gender (male/female) and four age subgroups (≤30, 31–40, 41–50 and ≥51), and three categories based on SES. Weighted percentage of the six health-related behaviours and four eating habits were calculated by these categories. Multivariate logistic regression analysis was used to determine frequencies (health-related behaviours and eating habits) in L-SES and H-SES.
Categorical principal components analysis (CATPCA) was used to examine the different consumption patterns for the 15 food groups mentioned previously (table 1). The analysis allowed for simultaneous evaluation of the relationships between various variables. The analysis was considered reliable for Cronbach’s alpha coefficient >0.7. All the statistical analyses were performed using SPSS V.19.0 software. A two-sided p value <0.05 was considered as being of statistical significance.
Discretisation criteria used in the principal components analysis of categorical data
Patient and public involvement
No patients were involved in the design of the study.
Results
Sample characteristics
A total of 5029 participants were included in the study (3006 for women; 2023 for men), and their characteristics were shown in table 2. The age distribution of the sample was as follows: 19.6% of participants were ≤30 years, 40.1% were 31–40 years, 24.8% were 41–50 years and 15.6% were ≥51 years old. Most participants were married/cohabited (84.8%), with an education level of undergraduate/college or above (94.6%), and with a family income level of 1 10 000–200 000 (36.2%). According to the definition of SES for the current study, 35.3% were in L-SES group, 36.6% were in M-SES group and 28.1% were in H-SES group. The rate of current smoking, current alcohol drinking, leisure‐time physical inactivity, sedentary behaviour, late sleeping and short sleep duration among the participants was 12.0%, 6.7%, 54.8%, 74.8%, 16.6% and 34.4%, respectively. Additionally, the rate of four eating behaviour habits was 38.3% for irregular meals habit, 26.1% for salty taste habit, 4.8% for eating gluttony and 2.0% for eating midnight snack, respectively (table 2).
Characteristics of study participants
Distribution of health-related behaviours and eating behaviour habits by gender and age
We further examined distribution of health-related behaviours and eating behaviour habits by age for men and women separately (table 3). Smoking and alcohol drinking behaviours were observed for men, but hardly for women. For men, the age of ≥51 years group had the highest rate of current smoking (36.2%, p<0.001), current alcohol drinking (25.7%, p<0.001) and short sleep duration (39.0%, p=0.001). Younger men (age ≤40 years, p<0.001) had a high rate of leisure‐time physical inactivity (age ≤30 years: 52.8%; age 31–40 years: 59.6%). The youngest age group (age ≤30 years, p<0.001) had the highest rate of sedentary behaviour (80.4%) and late sleeping (30.1%). As for eating behaviour habits, the youngest age group (age ≤30 years, p<0.001) had the highest rate of irregular meals habit (50.4%), eating midnight snack habit (3.5%), eating gluttony habit (10.3%) and salty taste habit (35.8%).
Distribution of health-related behaviours and eating behaviour habits by age and gender
For women, the youngest age group (age ≤30 years, p<0.001) had the highest rate of sedentary behaviour (81.7%), leisure-time physical inactivity (69.4%) and late sleeping (20.7%). The ≥51 years age group had the highest rate of short sleep duration (45.4%, p=0.001). As for eating behaviour habits, the youngest age group (age ≤30 years, p<0.001) had the highest rate of irregular meals habit (61.1%), eating midnight snack habit (3.9 %), eating gluttony habit (7.0%) and salty taste habit (25.6%). A negative dose–response trend increasing age was found in irregular meals habit, eating midnight snack habit and salty taste habit (p<0.001).
Distribution of health-related behaviours and eating behaviour habits by SES
Table 4 presented the distribution of health-related behaviours and eating behaviour habits among different SES groups after adjusting for age, gender and marital status. For health-related behaviours, compared with the H-SES group, the L-SES group demonstrated a significantly higher rate of current smoking (adjusted OR (ORadj)=1.46, 95% CI: 1.15 to 1.85) and leisure-time physical inactivity (ORadj=1.18, 95% CI: 1.02 to 1.37), but a significantly lower rate of late sleeping (ORadj=0.69, 95% CI: 0.57 to 0.83). No significant differences were found in the rate of current alcohol drinking, sedentary behaviour and short sleep duration (p>0.05). Additionally, the rate of the four dietary behaviours were similar in the three different SES groups (p>0.05).
Distribution of health-related behaviours and eating behaviour habits by SES
Food consumption patterns by gender, age and SES
CATPCA was performed to identify the patterns of food consumption for 15 food groups by gender, age and SES (figure 1). The Cronbach’s alpha was 0.887 and the total eigenvalue was 5.812, indicating good reliability for assessment of simultaneous relationships among the selected variables. Among the 15 food groups, rice consumption habit was located at the centroid. Four food consumption patterns were identified. Pattern 1 named ‘traditional foods’ pattern was characterised by more consumption of vegetables, livestock and poultry meat, fruits and eggs. Pattern 2 named ‘cereals and dairy product’ pattern was characterised by more consumption of grain, wheat, soybean and products and dairy product. Pattern 3 named ‘fish and nut’ pattern was characterised by more consumption of fish and nut. Pattern 4 named ‘smoked and pickled foods, and dessert’ pattern was characterised by more consumption of smoked fish or meat, pickle food and dessert.CATPCA indicated the ‘traditional foods’ and ‘cereals and dairy product’ patterns were mainly observed in the 41–50 years age group with H-SES. ‘Fish and nut’ and ‘smoked and pickled foods, and dessert’ patterns were mainly observed among the ≥51 years old men in L-SES group. There is an absence of difference in four food consumption patterns among young women (aged ≤40 years old) in the M-SES group.
Principal components analysis of categorical data (Cronbach’s alpha=0.887; eigenvalue=5.812). Variables in association: Pattern 1 named ‘traditional foods’ pattern was characterised by more consumption of vegetables, livestock and poultry meat, fruits and eggs. Pattern 2 named ‘cereals and dairy product’ pattern was characterised by more consumption of grain, wheat, soybean and products and dairy product. Pattern 3 named ‘fish and nut’ pattern was characterised by more consumption of fish and nut. Pattern 4 named ‘smoked and pickled foods, and dessert’ pattern was characterised by more consumption of smoked fish or meat, pickle food and dessert; H-SES, high-socioeconomic status; L-SES: low-socioeconomic status; M-SES, medium-socioeconomic status; SES, socioeconomic status.
Discussion
This cross-sectional study showed that the distributions of health-related behaviours and dietary habits varied by gender, age and SES among public workers in China. Men in the middle-aged group (41–60 years) were more likely to smoke, use alcohol and have short sleep duration, but men in the 31–40 years age group had the highest rate of leisure‐time physical inactivity (59.6%). Young women (age ≤30 years) were more likely to have leisure‐time physical inactivity, but women aged ≥51 years were more likely to have short sleep duration. Sedentary behaviour, late sleeping, as well as all four risk eating behaviour habits were more prevalent in the youngest age group (age ≤30 years), regardless of gender. In addition, we found that people in the H-SES group were less likely to be current smoker and have physical inactivity, but were more likely to have late sleeping. We also identified four food consumption patterns, which varied by gender, age and SES.
We found gender and age differences in the occurrence of health-related behaviours. For instance, the rate of smoking and alcohol drinking were much lower in women than men, which may be explained by sociocultural factors. The social gender role in culture considers it acceptable, appropriate or even desirable to engage in certain behaviours such as smoking and drinking for men, but almost not for women.28–30 In this study, a higher rate of smoking and alcohol drinking was found in middle-aged (41–60 years) men than that in younger men (≤40 years). In recent years, the Chinese government has been gradually strengthening the policies against tobacco use, and the group intervention on smoking cessation based on social cognitive theory could be effective to reduce smoking.31 32 Male smokers in the high age group lacking health knowledge and ignoring the proper health behaviours cannot sufficiently understand the need for preventive measures,33 34 even reduce the stress of social isolation, economic hardship, prior trauma and the loss of power and status by smoking.35 In addition, we found young women and men had a high rate of leisure‐time physical inactivity, late sleeping and sedentary behaviour, which was consistent with previous research.36 With the rapid socioeconomic development in China and changes in urbanisation, work stress emerged in the urban population, especially among the working young population due to a rise in living costs, which may result in long working time and lacking leisure time to participate in physical activity. Modern media use has also become intricately connected with our bedtime routine and sleep.37 Additionally, individuals in the ≥51 years age group were more likely to have a high level of short sleep duration. These findings strongly suggest that planning of effective health promotion programmes should target health-related behaviours that are modified by gender and age.
The association between SES and various health-related behaviours are multiple and complex.38 Past studies have consistently shown SES as the strongest predictor of tobacco use.39–41 In the current study, we found higher rate of smoking and leisure‐time physical inactivity in the L-SES group than H-SES group, which was consistent with previous research.42 43 Our study, for the first time, found a higher rate of late sleeping in H-SES group than L-SES group among public workers in China. Tobacco control policies, leisure‐time physical inactivity and late sleeping interventions in China should be increasingly focused on populations with low-SES in order to break the link between socioeconomic disadvantage and these unhealthy behaviours. Education, one of the components of SES, remained the strongest predictor of these unhealthy behaviors,39–41 43 suggesting future intervention programmes to take targeted measures to reduce unhealthy behaviours, according to education attainment status. Although no significant differences in short sleep duration and sedentary behaviours were observed by SES in this study, we found much higher rate of short sleep duration and sedentary behaviours in our study population than the general population in southeast of China in other studies, 42 44 drawing our attention to the impact of short sleep duration and sedentary behaviours on health among this special population.9
We found differences in dietary habits including eating behaviour habits and food consumption patterns by gender, age and SES. For eating behaviour habits, both women and men in the younger age group (≤30 years) have the highest rate of these four unhealthy dietary habits. Younger individuals may get involved easily in unhealthy eating behaviours due to poor control awareness and health literacy.19 20 45 Although there were no differences in four eating behaviours among three SES groups, combination of some other studies, SES remained an important factor to impact unhealthy eating behaviours.46–48
We also explored food consumption patterns by sociodemographics using CATPCAanalysis, which is the first study of its kind among public workers in China. We found the ‘traditional foods’ and ‘cereals and dairy product’ patterns were mainly observed in the 41–50 years age group with H-SES. In China, traditional foods such as vegetables, fruits, meats and eggs were considered as healthy food pattern in line with Chinese traditions. Research has consistently shown that high intake of vegetables and fruits, whole grains and eggs may decrease the risk of chronic diseases, even cancer.49 50 In addition, we found ‘fish and nut’ and ‘smoked and pickled foods, and dessert’ patterns were mainly observed among the ≥51 years men in L-SES group. High intake of sugars, and pickled or smoked foods may increase such risk,9 22 51 52 but fish consumption was associated with a reduced risk of all-cause mortality.53 Available study has pointed out that men have a higher liking for sweets than women.54 Younger age, low education and low family income were associated with a poor health literacy status, which may result in a low nutrient food consumption.45 The findings have implications for future intervention programmes to take targeted measures to reduce unhealthy food consumption habits, according to specific sociodemographic characteristics.
Strengths and limitations
To the best of our knowledge, this is the first study using a large sample from a representative urban public worker population. This is also the first study to use the CATPCA method to study health-related behaviours and dietary habits by sociodemographic characteristics such as gender, age and SES groups. CATPCA was applied: a multivariate analysis for varying discrete systems which builds a mathematical space where the variables are projected. The sociodemographic factors, health-related behaviours and dietary habits were discrete values, so we had to discretise them for analysis by CATPCA. Additionally, CATPCA has standard provisions for the graphical representation of the non-linear principal component analysis output, including the biplots and triplots.55 As can be seen in figure 1, such a biplot provides a clear and comprehensive view of the relationships between persons and variables. It is possible to enrich this view even further, as CATPCA can label persons by the categories of a particular variable to help determine how specific groups of persons can be distinguished on the basis of that particular variable. However, some limitations should be considered when interpreting our results. First, many variables were self-reported, and the findings may subject to recall bias. Meanwhile, results and conclusions referring to dietary habits were based on a questionnaire that have not been validated in the population of interest so they cannot be made with confidence owing to the increased opportunity for measurement bias. Second, the study participants came from Hunan province and China, and the generalisability of the study findings may not be able to generalise to other parts of China despite its large sample size. Future multiprovince or multinational surveillance studies are needed to further test findings in our study. Third, the cross-sectional study design may preclude any observation of behaviours and dietary habits changes over time. Future longitudinal studies may overcome such a limitation.
Conclusions
This study confirmed the various distribution of health-related behaviours and dietary habits by sociodemographic characteristics among public workers. Notably, this study found that middle-aged group (41–60 years) had the highest rate of smoking and alcohol drinking, and young-aged group (≤40 years) with L-SES were more likely to have multiple unhealthy behaviours and dietary habits. We also identified four food consumption patterns, which varied by gender, age and SES. Our findings of the disparity distribution of health-related behaviours and dietary habits by specific gender, age and SES among Chinese public workers have important policy implications for developing targeted health interventions to facilitate health-related behaviours and dietary habits in this population.
Data availability statement
Data are available upon reasonable request. The data analysed during this study are included in the article. The numerical data used to support the findings of this study are available from the corresponding author upon reasonable request.
Ethics statements
Ethics approval
Ethics approval for this study was granted by the Ethics Committee of Xiangya School of Public Health, Central South University, China (No. XYGW-2016-10).
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors LL was responsible for the study design, data analyses and interpretation, manuscript writing and revision. JH, FO, DQ and YL were responsible for the data acquisition, interpretation and manuscript revision. YY and DL were responsible for the manuscript revision. SX was responsible for the study conceptualisation, data acquisition and interpretation and manuscript revision. All of the authors approved the final content of this manuscript.
Funding This work was supported by the Ministry of Science and Technology of China (Grant No. 2016YFC0900802).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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