Study On Distribution And Clustering Of Health-related Behaviors Among Residents

BackgroundsHealth-related behaviors,such as smoking,excessive drinking,lack of exercise,and insufficient intake of vegetables and fruits,have significant impacts on the health of the population.WHO estimated that 3.3 million deaths worldwide were attributable to alcohol consumption each year,6 million deaths were attributable to smoking each year,3.2 million people died due to lack of exercise and 1.7 million deaths were attributable to excessive salt intake each year.A large number of studies have also proved that health-risk behaviors are important causes of chronic non-communicable diseases,including cardiovascular and cerebrovascular diseases,type Ⅱ diabetes and some cancers.To effectively modify the health-related behavior of the population,several studies have explored the risk factors of health-related behavior.They found that some of the health-related behaviors were closely related to age,sex,educational level,and economic level.In addition,a number of studies have found that health-related behaviors are not randomly distributed in the population,but appear to clustering in certain population.Some health-risk behaviors often co-occur and their negative effect on health is higher than the sum of the effect of exposure to each factor alone.Most of the previous studies have been carried out in developed countries such as Europe and America,and the large sample research aimed at Chinese mainland residents is inadequate.Therefore,this study used the baseline data of Air pollution and Health cohort study to analyze the prevalence of health-related behaviors of local residents(smoking,drinking,diet and exercise),explore the clustering of health-risk behaviors and socio-demographic variables associated with health-risk clusters.The aim of this study was to provide scientific evidence for local government to develop effective public health interventions,especially preventive policy and measures of chronic diseases.MethodsFrom June 2015 to December 2016,we collected a total of 32291 qualified questionnaires in Yinzhou,the biggest district of Ningbo.The investigation stations were set up in the community health service centers and health-related information from subjects was collected by face-to-face interviews and physical examination by the trained investigators.The composition ratio(%)was used to describe the distribution of categorical variables.Mean and standard deviation were described for continuous variables.We tested the differences of health-related behavior between different social demographic characteristics using the Chi Square Test.Associations between socio-demographic variables and health-risk behaviors were estimated by binary logistic regression models.To evaluate the most frequent clusters of risk behaviors,ratio between the observed and expected(O/E)prevalence was calculated for each possible combination of risk behaviors.We calculated the adjusted odds ratios and 95%confidence intervals(95%CIs)using multinomial logistic regression models for the associations between socio-demographic factors and the number of accumulated health-risk behaviors with no health-risk behavior as a reference level.ResultsA total of 32291 subjects were included in this study,of which 13851 were male and 18440 were female.The smoking rate in this survey was 15.20%,and the probability of smoking in men,young and middle-aged people and those with lower levels of education was higher.The rate of excessive drinking was 17.36%,and the high-risk people for excessive drinking were male,middle-aged and manual workers.For consumption of fruits,bean products,milk and eggs,the frequency is relatively low among local residents.The rate of insufficient intake of vegetables and fruits was 85.65%.Men,the elderly,unaccompanied people,unemployed or retired people,people with low education levels and high family income were more likely to have inadequate intake of fruit and vegetables.The rate of physical inactivity was 66.97%.Men,the elderly,individuals who had no partners or were unemployed or retired were more often lack of exercise.More than half of respondents(66.90%)had two or more health-risk behaviors,4.88%of the respondents had all four health-risk behaviors,including smoking,excessive drinking,intake of fruits and vegetables and physical inactivity.Only 3.83%of respondents had no health-risk behaviors.Our results indicated that the clustering of intake of fruits and vegetables and physical inactivity was the most common combination among women.The co-occurrence of smoking and excessive drinking had the strongest clustering effect(O/E=11.21 95%CI:1.18,1.25)among men.The clustering of smoking,excessive drinking and inadequate intake of fruits and vegetables and the clustering of smoking,excessive drinking and physical inactivity occurred more frequently than expected.The clustering of four harmful health behaviors was also common and its observed prevalence was higher than the expected prevalence.With no health-risk behaviors as a reference group,results from multivariate analyses suggested that risk factors of multiple health-risk behaviors among men were 45-64 years old,no partner,low educational level and high family income.Risk factors of multiple health-risk behaviors among women were unemployment or retirement and high family income.ConclusionsThis study found that the prevalence of smoking and excessive drinking are relatively high among men.Inadequate intake of vegetables and fruits was common.More than half of the residents lacked physical activity.The clustering of inadequate intake of fruits and vegetables and physical inactivity was the most common combination among women.Smoking and excessive drinking presented the highpotential for clustering among men.Among men,middle-aged adults,unaccompanied persons,people with lower educational attainment and higher household income are at high risk of multiple health-risk behaviors.Among women,unemployed or retired people and those with higher household incomes are at high risk of multiple health-risk behaviors.Therefore,local public health intervention policies should focus on this part of the population.