studies in developed countries reveal that poor lifestyle choices triggering noncommunicable diseases typically co - occur or  cluster  among children and adolescents .
. however , there is insufficient evidence on the clustering of risk behaviors among children in developing countries .
meanwhile , developing countries contend with the burden of infectious and chronic diseases less so than risk behaviors for infectious diseases ( rbid ) among children and adolescents . social variables , such as family socioeconomic status ( ses ) and family structure , are known to contribute toward risk behaviors ; therefore , they contribute to risk behavior clustering
. a low ses , which incorporates a low income and mothers educational levels , is associated with the clustering of risk behaviors .
therefore , interventions for risk behaviors must focus on disadvantaged children . rapid development in china is continuing to increase the number of rural - urban migrants .
china 's rural - urban migrant population ( henceforth ,  migrant population  ) is defined as individuals leaving their rural residences for urban cities for a certain period ( more than 6 months ) without changing household registration . in 2012 ,
the migrant population was approximately 236 million . according to 2010 data , 20.8% of the migrant population were children under 14 years old with living conditions characterized by instability , overcrowded housing , poor sanitation , children attending disadvantaged schools , and social and cultural isolation .
. however , the clustering of risk behaviors and their determinants among children in china is under - researched .
this study examined the clustering of risk behaviors for infectious and chronic diseases , and the accompanying influence of social determinants among learners in the high grades in primary schools enrolling migrants and residents in beijing .
first , we stratified schools into urban districts , inner suburbs , and outer suburbs .
beijing comprises 16 districts , including 6 urban districts , 6 inner suburbs , and 4 outer suburbs .
second , we randomly selected two medium - scale ( 8001200 ) primary schools from each district , which enrolled migrant and resident learners .
we selected two grade 4 and 5 classes from each school randomly , with all learners in those classes invited to participate . among the 1021 learners recruited , 41 declined to participate , and
the data were collected from february to may 2011 by trained fieldworkers . in this study , migrants were those whose household registration records ( hukou ) were not in beijing . given their different hukou statuses , learners were divided into two groups : migrants and residents .
this study was approved by the institutional review board at peking university ( irb00001052 - 11025 ) .
the questionnaires were self - completed , and the research assistants were available to clarify arising questions .
self - reported risk rbid included six items , namely :  do you wash hands before eating ?  
do you wash hands after defecation ?   do you wash fruit before eating ? 
 do you spit in public ?   do you drink tap water that is not boiled ?  and  do you share towels with others ? 
  sometimes  or  never  were risk behaviors for the first three questions , whereas  always  was a risk behavior for the latter three .
related risk behavior interventions for infectious diseases are recommended in health education courses in chinese primary schools , particularly public schools .
risk behaviors for chronic diseases ( rbcd ) and growth included : smoking ; passive smoking ( ps ) ( 4 days / week ) ; breakfast ( 3 days / week ) ; and consumption of vegetables ( 3 days / week ) , fruits ( 3 days / week ) , and milk ( 3 days / week ) .
we defined  smoking  as having ever smoked or tried and ps as exposure to other people 's tobacco smoke for more than 15 min / day .
the frequency method was used to measure risk behaviors , and arbitrary cut - offs were adopted to identify whether behaviors posed health risks .
clustering of risk behaviors was demonstrated by number of risk behaviors and clustering patterns of individual risk behaviors as previous studies .
descriptive analysis summarized the outcome of demographic characteristics and prevalence of risk behaviors with the percentage for categorical variables and mean for continuous variables .
chi - square tests were used to compare prevalence and clustering for the number of risk behaviors among the different groups , with a significance threshold of 0.05 .
the main effects model would be a priority , assuming that the risk behaviors were mutually independent of one another .
if it did not adequately fit , interactions between variables would be considered to establish an appropriate model .
the test of parallel lines was used to judge whether the data fit the ordinal logistic regression model ( p > 0.05 ) .
goodness of fit was tested using  2 log likelihood ( 2 ll ) ( p < 0.05 ) and pearson 's chi - square test ( p > 0.05 ) .
first , we stratified schools into urban districts , inner suburbs , and outer suburbs .
beijing comprises 16 districts , including 6 urban districts , 6 inner suburbs , and 4 outer suburbs .
second , we randomly selected two medium - scale ( 8001200 ) primary schools from each district , which enrolled migrant and resident learners .
we selected two grade 4 and 5 classes from each school randomly , with all learners in those classes invited to participate . among the 1021 learners recruited , 41 declined to participate , and
the data were collected from february to may 2011 by trained fieldworkers . in this study , migrants were those whose household registration records ( hukou ) were not in beijing . given their different hukou statuses , learners were divided into two groups : migrants and residents .
this study was approved by the institutional review board at peking university ( irb00001052 - 11025 ) .
the questionnaires were self - completed , and the research assistants were available to clarify arising questions .
self - reported risk rbid included six items , namely :  do you wash hands before eating ?  
do you wash hands after defecation ?   do you wash fruit before eating ? 
 do you spit in public ?   do you drink tap water that is not boiled ?  and  do you share towels with others ?  response choices were  always ,   sometimes ,  and  never .   sometimes  or  never  were risk behaviors for the first three questions , whereas  always  was a risk behavior for the latter three .
related risk behavior interventions for infectious diseases are recommended in health education courses in chinese primary schools , particularly public schools .
risk behaviors for chronic diseases ( rbcd ) and growth included : smoking ; passive smoking ( ps ) ( 4 days / week ) ; breakfast ( 3 days / week ) ; and consumption of vegetables ( 3 days / week ) , fruits ( 3 days / week ) , and milk ( 3 days / week ) .
we defined  smoking  as having ever smoked or tried and ps as exposure to other people 's tobacco smoke for more than 15 min / day .
the frequency method was used to measure risk behaviors , and arbitrary cut - offs were adopted to identify whether behaviors posed health risks .
clustering of risk behaviors was demonstrated by number of risk behaviors and clustering patterns of individual risk behaviors as previous studies .
descriptive analysis summarized the outcome of demographic characteristics and prevalence of risk behaviors with the percentage for categorical variables and mean for continuous variables .
chi - square tests were used to compare prevalence and clustering for the number of risk behaviors among the different groups , with a significance threshold of 0.05 .
the main effects model would be a priority , assuming that the risk behaviors were mutually independent of one another .
if it did not adequately fit , interactions between variables would be considered to establish an appropriate model .
the test of parallel lines was used to judge whether the data fit the ordinal logistic regression model ( p > 0.05 ) .
goodness of fit was tested using  2 log likelihood ( 2 ll ) ( p < 0.05 ) and pearson 's chi - square test ( p > 0.05 ) .
as can be seen in table 1 , boys outnumbered girls in all the districts .
two - thirds of the learners ( age range : 914 years ; mean = 11.25 years ) were in public schools ; 70.2% of the subjects were migrants .
the education level of guardians in the outer suburbs was the lowest ; only 13.5% had attended high school .
the percentage of ownership of <3 household appliances increased with distance from an urban area , with 21.6% in an urban district , 54.9% in an inner suburb , and 62.2% in an outer suburb .
the most prevalent rbid and rbcd were  not washing hands after defecation ( whad )  and  consuming milk 3 days / week ,  respectively .
the prevalence of none , one , two , and three or more rbid was 61.2% , 20.0% , 10.8% , and 8.1% , respectively , and for rbcd it was 46.0% , 30.6% , 15.4% , and 8.0% , respectively .
multiple risk behaviors and their clustering by district rbid : risk behaviors for infectious diseases ; rbcd : risk behaviors for chronic diseases ; whbe : not washing hands before eating ; whad : not washing hands after defecation ; wfbe : not washing fruit before eating ; sip : spitting in public .
the main effects in the log - linear model showed inadequate fit for the data and interactions between two of the variables demonstrated an appropriate model .
as shown in table 3 , this was deemed to have a better fit to the data (  = 45.42 , p = 0.538 ;  = 61.64 , p = 0.125 ) . in rbid , not washing hands before eating with whad ( odds ratio [ or ] = 6.06 , 95% ci 4.009.17 ) , spitting in public ( sip ) with drinking unboiled tap water ( dutw ) ( or = 4.57 , 95% ci 2.109.98 ) , and whad with not washing fruit before eating ( or = 4.09 , 95% ci 2.486.75 ) were behaviors more likely to be observed together . in rbcd ,
fc with mc ( or = 5.49 , 95% ci 3.758.03 ) , hb with vc ( or = 2.64 , 95% ci 1.235.69 ) , and ps with fc ( or = 2.58 , 95% ci 1.773.77 ) were more likely to occur dependently .
clustering patterns for risk behaviors rbid : likelihood ratio goodness - of - fit tests  = 45.42 , p = 0.538 ; rbcd : likelihood ratio goodness - of - fit tests  = 61.64 , p = 0.125 .
whbe : not washing hands before eating ; whad : not washing hands after defecation ; wfbe : not washing fruit before eating ; sip : spitting in public ; dutw : drinking unboiled tap water ; stwo : sharing towel with others ; es : ever smoking ; ps : passive smoking ; hb : having breakfast ; vc : vegetables consumption ; fc : fruits consumption ; mc : milk consumption ; or : odds ratio ; ci : confidence interval ; rbid : risk behaviors for infectious diseases ; rbcd : risk behaviors for chronic diseases .
ordinal logistic analysis results showed that no matter the model for rbid or rbcd , the data fit the ordinal logistic regression model well , with p > 0.05 in the test of parallel lines ; the goodness of fit was also fine with p < 0.05 in  2 ll and p > 0.05 in pearson 's chi - square test [ tables 4 and 5 ] .
results of r showed the explanatory power was lowest in model 1 and highest in model 4 .
r in model 2 was greater than it was in model 3 , whether in rbid or rbcd , and disclosed the important role of the school .
once all variables were included in model 4 , more rbid was exhibited by boys , migrants , those living in the outer suburbs , private school learners , learners with less educated guardians , and those from families with fewer household appliances .
the three most influential factors were school type ( or = 4.47 , 95% ci 3.006.66 ) , school located in an inner suburb ( or = 0.27 , 95% ci 0.180.38 ) , and gender ( or = 0.56 , 95% ci 0.420.74 ) .
regarding rbcd , behavioral clustering was not associated with household registration status and number of appliances , but was significantly associated with school type ( or = 5.36 , 95% ci 3.727.73 ) , school located in an inner suburb ( or = 0.59 , 95% ci 0.430.81 ) , and gender ( or = 0.61 , 95% ci 0.470.78 ) .
ordinal logistic regression by number of rbid ( reference : no risk behaviors ) or : odds ratio ; ci : confidence interval ; rbid : risk behaviors for infectious diseases .
ordinal logistic regression by number of rbcd and growth ( reference : no risk behaviors ) or : odds ratio ; ci : confidence interval ; rbcd : risk behaviors for chronic diseases ; 2 ll : 2 log likelihood .
as can be seen in table 1 , boys outnumbered girls in all the districts .
two - thirds of the learners ( age range : 914 years ; mean = 11.25 years ) were in public schools ; 70.2% of the subjects were migrants .
the education level of guardians in the outer suburbs was the lowest ; only 13.5% had attended high school .
the percentage of ownership of <3 household appliances increased with distance from an urban area , with 21.6% in an urban district , 54.9% in an inner suburb , and 62.2% in an outer suburb .
the most prevalent rbid and rbcd were  not washing hands after defecation ( whad )  and  consuming milk 3 days / week ,  respectively . the prevalence of none , one , two , and three or more rbid was 61.2% , 20.0% , 10.8% , and 8.1% , respectively , and for rbcd it was 46.0% , 30.6% , 15.4% , and 8.0% , respectively .
multiple risk behaviors and their clustering by district rbid : risk behaviors for infectious diseases ; rbcd : risk behaviors for chronic diseases ; whbe : not washing hands before eating ; whad : not washing hands after defecation ; wfbe : not washing fruit before eating ; sip : spitting in public .
the main effects in the log - linear model showed inadequate fit for the data and interactions between two of the variables demonstrated an appropriate model .
as shown in table 3 , this was deemed to have a better fit to the data (  = 45.42 , p = 0.538 ;  = 61.64 , p = 0.125 ) . in rbid ,
not washing hands before eating with whad ( odds ratio [ or ] = 6.06 , 95% ci 4.009.17 ) , spitting in public ( sip ) with drinking unboiled tap water ( dutw ) ( or = 4.57 , 95% ci 2.109.98 ) , and whad with not washing fruit before eating ( or = 4.09 , 95% ci 2.486.75 ) were behaviors more likely to be observed together . in rbcd ,
fc with mc ( or = 5.49 , 95% ci 3.758.03 ) , hb with vc ( or = 2.64 , 95% ci 1.235.69 ) , and ps with fc ( or = 2.58 , 95% ci 1.773.77 ) were more likely to occur dependently .
clustering patterns for risk behaviors rbid : likelihood ratio goodness - of - fit tests  = 45.42 , p = 0.538 ; rbcd : likelihood ratio goodness - of - fit tests  = 61.64 , p = 0.125 .
whbe : not washing hands before eating ; whad : not washing hands after defecation ; wfbe : not washing fruit before eating ; sip : spitting in public ; dutw : drinking unboiled tap water ; stwo : sharing towel with others ; es : ever smoking ; ps : passive smoking ; hb : having breakfast ; vc : vegetables consumption ; fc : fruits consumption ; mc : milk consumption ; or : odds ratio ; ci : confidence interval ; rbid : risk behaviors for infectious diseases ; rbcd : risk behaviors for chronic diseases .
ordinal logistic analysis results showed that no matter the model for rbid or rbcd , the data fit the ordinal logistic regression model well , with p > 0.05 in the test of parallel lines ; the goodness of fit was also fine with p < 0.05 in  2 ll and p > 0.05 in pearson 's chi - square test [ tables 4 and 5 ] .
results of r showed the explanatory power was lowest in model 1 and highest in model 4 .
r in model 2 was greater than it was in model 3 , whether in rbid or rbcd , and disclosed the important role of the school .
once all variables were included in model 4 , more rbid was exhibited by boys , migrants , those living in the outer suburbs , private school learners , learners with less educated guardians , and those from families with fewer household appliances .
the three most influential factors were school type ( or = 4.47 , 95% ci 3.006.66 ) , school located in an inner suburb ( or = 0.27 , 95% ci 0.180.38 ) , and gender ( or = 0.56 , 95% ci 0.420.74 ) .
regarding rbcd , behavioral clustering was not associated with household registration status and number of appliances , but was significantly associated with school type ( or = 5.36 , 95% ci 3.727.73 ) , school located in an inner suburb ( or = 0.59 , 95% ci 0.430.81 ) , and gender ( or = 0.61 , 95% ci 0.470.78 ) .
ordinal logistic regression by number of rbid ( reference : no risk behaviors ) or : odds ratio ; ci : confidence interval ; rbid : risk behaviors for infectious diseases .
ordinal logistic regression by number of rbcd and growth ( reference : no risk behaviors ) or : odds ratio ; ci : confidence interval ; rbcd : risk behaviors for chronic diseases ; 2 ll : 2 log likelihood .
this study assessed the clustering of multiple risk behaviors for infectious and chronic diseases and their social determinants among learners in schools enrolling migrants and residents in beijing , china .
the prevalence of none , one , two , and three or more risk factors was 61.2% , 20.0% , 10.8% , and 8.1% , respectively , for infectious diseases , and 46.0% , 30.6% , 15.4% , and 8.0% , respectively , for chronic diseases . regarding some rbid , the participants engaged in more healthy behaviors than those in a nationwide , representative chinese survey conducted in 2005 , wherein elementary school learners washed their hands 72.5% ( before eating ) and 75.4% ( after defecation ) of the time .
the survey showed that , regarding some rbcd , daily breakfast and vegetable consumption was at 84.0% and 67.0% , respectively , among the learners ; this was 79.4% and 81.2% in our study .
as most beijing schools provide lunch in recent years , vegetable intake was boosted in students .
children who begin smoking earlier are more likely to develop severe nicotine addiction . in a longitudinal canadian study , the prevalence among 1011-year - old children of having
ever smoked was 6% from 2000 to 2001 , compared to 7.9% in our study .
data from the united kingdom showed that 1216-year - old children 's breakfast intake 5 days a week was at 76.7% .
however , these studies are not comparable with the current one because of differences in the survey periods , regions , and population .
although few studies have focused on behaviors for infectious diseases , there are a number of studies that have examined the clustering of rbcd .
our results from the log - linear models showed clear evidence that risk behaviors for infectious and chronic diseases were not independent , but were instead clustered together , such as washing hands before eating and after defecation , sip and dutw , fruit consumption and milk intake , and breakfast and vegetable consumption . although the analytic techniques used to define clustering differed across studies , it was clear that some risk behaviors clustered .
multiple behavior interventions ( i.e. , targeting more than one health behavior simultaneously ) would have the potential for a much greater public health impact compared to single behavior interventions .
the limited clustering of smoking with the other factors was very different from the other studies .
a possible reason for this was that the risk behaviors we investigated were more about diet and nutrition , and less about physical activity and alcohol consumption , which were observed clustering with smoking by other researchers .
in addition , the population we studied was primary school students , among whom the smoking rate is comparatively low .
however , our results also showed that interventions for smoking and fruit consumption together would be good for primary school students .
the literature shows that many factors  including gender , ethnicity , grade level , family , schooling , and community contexts  influence risk behaviors . in our study , we considered demographic characteristics ( i.e. , gender and age ) , school environment ( i.e. , school type : private or public ; location : urban district or suburb ) , and family context as determinants of the clustering of risk behaviors .
the family context in our study referred to ses , including place of household registration ( beijing or other ) , number of household appliances , and guardians education levels . here ,
household appliances ( i.e. , television , washing machine , air conditioner , refrigerator , and personal computer ) were considered a measure of wealth because collecting data on income and savings is a sensitive issue in china and learners may not give accurate income - related information .
as expected , demographic characteristics , school environment , and family context variables contributed toward the number of risk behaviors , with the school environment variables being the most significant contributor .
as learners spend most of their time in school , school conditions , interventions , and teachers and peers support reportedly facilitate the formation of healthy behaviors . in china , urban schools physical conditions and health education capacity
are slightly better than those of suburban schools . however , while the conditions in urban schools are generally better , the gaps between urban and suburban schools are not qualitative but quantitative , and more differences exist between public and private schools enrolling migrant children . in public schools ,
health education courses are regularly offered by qualified teachers , and basic hygiene amenities ( sufficient taps , washrooms , and classroom lights ) , desks and chairs adjusted according to child height , and a balanced diet can be provided . in most public schools ,
learners annually undergo professional health checks , participate in vaccination programs , and receive counseling ; none of these is provided in most private schools recruiting migrant learners .
similarly , in our study , schools characteristics mattered more than the family context as r showed .
the family context , reflected by the ses , including household income , parents educational level , and occupation , was another important determinant of risk behaviors . in our study , number of appliances and guardians educational levels ( constituting the family context ) significantly influenced the number of rbid , possibly because of misinformation regarding these and related prevention measures among learners of a lower ses .
regarding rbcd , the guardians education level significantly influenced behavioral clustering but proved less significant than the school environment . according to many studies , teenagers from low ses backgrounds are likely to report inadequate fruit and vegetable consumption .
however , comparisons are limited because differences in estimates may be confounded by differences in the risk factors investigated , data - gathering instruments , and analysis
. the schools characteristics in our study could be particularly influential because urban public primary schools in beijing provide nutritional lunch  comprising fruit , vegetables , and milk  to learners .
however , demographic and social determinants can directly influence the number of unhealthy behaviors . since clustered risk behaviors may be particularly harmful to children 's health , public health interventions should target three or more risk behaviors according to socioeconomic conditions .
it was comprised of a cross - sectional survey , making it impossible to make causal inferences about risk behaviors .
moreover , the survey comprised self - reported data by the learners , increasing the possibility of misreporting .
further , we did not measure daily vegetable and fruit servings , but assessed the weekly frequency , with arbitrary cut - offs .
however , we did maximize the likelihood of honest reporting by ensuring the learners anonymity .
thus , despite the limitations , this study is one of the few to focus on social determinants of multiple health behaviors among learners in developing countries , particularly migrant learners .
. therefore , improved school conditions and integrated behavioral interventions are particularly important for health promotion .
 background : studies in developed countries reveal that poor lifestyle choices triggering diseases typically cluster among children 
 . however , there is insufficient evidence on the clustering of risk behaviors among children in developing countries . 
 this study aimed to determine the clustering of risk behaviors and their social determinants among 4th - and 5th -grade learners in beijing , china.methods:the sample comprised of 967 learners from six primary schools enrolled migrant and resident learners by two - stage stratified cluster sampling . 
 prevalence denoted the risk behaviors and their clustering . 
 a log - linear model was used to explore the clustering patterns . 
 ordinal logistic regression determined the influence of demographic characteristics , school environment , and family context on behavioral clustering.results:the prevalence of none , one , two , and three or more risk factors was 61.2% , 20.0% , 10.8% , and 8.1% for infectious diseases and 46.0% , 30.6% , 15.4% , and 8.0% for chronic diseases , respectively . 
 some behaviors appeared dependent and were more likely to be observed together . 
 the three most influential factors for infectious diseases were school type ( odds ratio [ or ] = 4.47 , 95% confidence interval [ ci ] 3.006.66 ) , school located in an inner suburb ( or = 0.27 , 95% ci 0.180.38 ) , and gender ( or = 0.56 , 95% ci 0.420.74 ) . regarding risk behaviors for chronic diseases , 
 clustering was not associated with household registration status and number of appliances , but was significantly associated with school type ( or = 5.36 , 95% ci 3.727.73 ) , school located in an inner suburb ( or = 0.59 , 95% ci 0.430.81 ) , and gender ( or = 0.61 , 95% ci 0.470.78 ) . 
 school environment variables were the most significant contributor to the number of risk behaviors.conclusions:the characteristics of schools enrolling migrants and residents influenced the number of risk behaviors . 
 therefore , improved school conditions and integrated behavioral interventions are particularly recommended for health promotion . 
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Sample
Measures
Data analysis
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Demographic characteristics
Multiple risk behaviors and clustering patterns
Social determinants of risk behavior clustering
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