chile , an upper middle - income country in south america , has seen increases in the prevalence of overweight and obesity , well - established risk factors for conditions such as cancer , cardiovascular disease , and diabetes [ 1 , 2 ] . in 1987 , the prevalence of excess weight among 6-year - olds in chile was 13% ; by 2000 , it had reached 27% . according to a 2012 report by the organization for economic cooperation and development ( oecd ) , 25.1% of chilean adults are obese and , among chilean children aged 517 years , 27.1% of girls and 28.6% of boys are overweight or obese . like excess weight , sleep disorders , particularly sleep apneas , have been associated with hypertension [ 5 , 6 ] , coronary artery disease , myocardial infarction [ 8 , 9 ] , heart failure , and diabetes . although reports have been published on the prevalence of obesity and of sleep apnea in chilean adults and young children [ 4 , 11 ] , few reports have focused attention on the prevalence of obesity and sleep apnea among young adults , particularly college students transitioning from adolescence into adulthood . moreover , the college years are often characterized by insufficient sleep , increased consumption of energy drinks and caffeinated beverages , and irregular meal and sleep patterns , which can have important consequences for overall health and wellbeing [ 1215 ] . to address the paucity of literature on the epidemiology of obstructive sleep apnea ( osa ) and adiposity indices among college students in chile , and to lay groundwork for developing health promotion and disease prevention strategies we investigated osa risk and the extent to which high risk for osa was associated with overweight , general obesity , and central obesity in this population . the study was conducted between december 2010 and june 2011 at four colleges in the magallanes region of chile : universidad tecnologica de chile , universidad del mar , universidad de magallanes , and universidad santo tomas . of the 994 full - time undergraduates who participated in the study , we excluded students who were above 35 years old or missing information on age , sleep apnea ( i.e. , the berlin questionnaire ) , or adiposity measures ( n = 78 ) . the final sample consisted of 916 students aged 18 to 35 who had complete exposure and outcome information . interested students were invited to meet in a large room or an auditorium where they were informed about the study purpose and procedures and invited to complete anonymous questionnaires requesting demographic , lifestyle , and sleep - related information . students who gave informed consent and completed the questionnaires were invited to participate in a brief physical examination during which trained research nurses took cardiometabolic and anthropometric measures including height , weight , blood pressure ( bp ) , pulse rate , waist circumference ( wc ) , and hip circumference ( hc ) . all study procedures were approved by the institutional review boards of centro de rehabilitacin club de leones cruz del sur , punta arenas , chile , and the university of washington , usa . the harvard school of public health office of human research administration , usa , granted approval to use the anonymized dataset for analyses . osa risk was evaluated using the berlin questionnaire . since it was first developed in 1996 , the berlin questionnaire has been validated and used extensively in clinical and epidemiologic research globally including latin america [ 1723 ] . numerous validation studies have reported moderate to high consistency between results of the berlin questionnaire and parameters of polysomnography , particularly respiratory disturbance index ( rdi ) > 5 and apnea - hypopnea index ( ahi )  5 , especially within clinical populations . category 2 assesses frequency of feelings of fatigue or tiredness after waking as well as sleepiness while driving . category 3 ascertains information about obesity and hypertension [ 17 , 19 ] . in the first two categories , a participant is given a positive score if he or she responds with yes  or experiences frequent symptoms ( more than 3 to 4 times per week ) in two or more questions within that category . for category 3 , a participant is given a positive score if he or she is obese ( bmi  30  kg / m ) or has a history of hypertension . participants with positive scores in two or more categories are classified as having a high risk for osa . body mass index ( bmi ) was calculated as weight in kilograms divided by height in square meters ( kg / m ) . categories of bmi were defined according to the world health organization ( who ) criteria ( underweight : < 18.5  kg / m ; normal : 18.524.9  kg / m ; overweight : 25.029.9  kg / m ; and obese : 30.0  kg / m ) . central obesity was evaluated using the international diabetes federation ( idf ) criteria for south american men and women , that is , wc  90  cm ( for men ) and wc  80  cm ( for women ) . waist - to - hip ratio ( whr ) was calculated by dividing wc by hc . whr was further categorized by quartile distribution and central obesity defined as whr in the top quartile . each anthropometric measurement was taken twice , and the average was used in data analyses . lifestyle and behavioral characteristics included moderate or vigorous physical activity ( yes versus no ) , cigarette smoking status ( never , former , or current ) , alcohol consumption within the past year ( no versus yes ) , and use of more than one energy or stimulant drink per week ( no versus yes ) . energy or stimulant drinks were defined as beverages used to boost energy levels , increase alertness , and enhance cognition and mood . examples of these beverages include coffee , yerba mate , cola , red bull , and dark dog . other variables included self - rated health ( good versus poor ) and systolic and diastolic bp . high risk for obstructive sleep apnea ( osa ) , defined as described above , was the exposure and the outcomes of interest were overweight , general obesity , central obesity , bmi , wc , hc , and whr . first , we examined the frequency distributions of sociodemographic , lifestyle , and behavioral characteristics of the students . characteristics of participants were summarized using counts and percentages for categorical variables and mean values (  standard deviations ) for continuous variables . student 's t - tests and chi - square tests were used to calculate bivariate differences for continuous and categorical variables , respectively . we examined the frequency distribution of osa risk according to sociodemographic , lifestyle , and behavioral characteristics . multivariate linear regression models were used to assess the associations of high osa risk with bmi , wc , hc , and whr . multivariate logistic regression models were used to determine odds ratios ( or ) and 95% confidence intervals ( ci ) of the association of high osa risk with general obesity ( bmi  30  kg / m ) , central obesity according to the idf criteria , and whr in the top quartile . confounding variables were considered a priori on the basis of their hypothesized relationship with osa and adiposity . potential confounders included age , sex , year in college , alcohol consumption , use of energy drinks , cigarette smoking status , self - rated health , bp , and participation in moderate or vigorous physical activity . we conducted stratified analyses to evaluate the extent to which , if at all , associations of high osa risk with overweight , general obesity , and central obesity differed by sex , elevated bp , and subjects ' self - rated health . all statistical analyses were performed using statistical analysis software ( sas , version 9.3 ; sas institute , cary , nc ) . of the 916 students included in the analysis , 69.5% were females and the average reported age was 21.8 ( 3.3 ) years . approximately 7.8% were classified as having high risk for osa as determined using previously published scoring and classification scheme of the berlin questionnaire . approximately 28.3% of students were overweight ( bmi : 2529.9  kg / m ) and 12.8% had general obesity according to who criteria ( bmi  30  kg / m ) . using the idf definition , it was determined that 42.7% of students had central obesity ( wc  90  cm for men or wc  80  cm for women ) . high risk for osa was associated with age , poor self - rated health , and cigarette smoking status . however , high risk for osa was not associated with sex , year in college , systolic bp , diastolic bp , alcohol consumption , participation in moderate to vigorous physical activity , or consumption of more than one energy or stimulant drink per week ( table 1 ) . prevalence of high osa risk was highest in the obese bmi category ( figure 1 ) and in individuals who were over 21 years old ( figure 2 ) . table 2 shows the results of the fully adjusted models of the linear regression analyses . high osa risk was statistically significantly associated with higher bmi (  : 3.25 ; standard error : 0.63 , p < 0.001 ) and whr (  : 0.03 ; standard error : 0.01 , p = 0.02 ) . high osa risk was also associated with higher wc (  : 7.32 ; standard error : 1.54 , p < 0.001 ) and hc (  : 5.00 ; standard error : 1.41 , p < 0.05 ) . high risk for osa was associated with almost 10-fold increased odds of general obesity ( or 9.96 ; 95% ci 4.4222.45 ) compared to low risk for osa . students with high osa risk also had 2.78-fold odds of central obesity ( or 2.78 ; 95% ci 1.435.40 ) . however , the odds of high risk for osa were not elevated by overweight status ( or 0.89 ; 95% ci 0.352.23 ) . those with high risk for osa were also more likely to be in the top quartile of whr ( i.e. , whr  0.8875 ) , although statistical significance was not achieved ( or 1.45 ; 95% ci 0.712.95 ) ( table 3 ) . similar strong positive associations between high risk for osa and general obesity ( bmi  30  kg / m ) were evident within strata of sex ( male or female ) , bp ( nonelevated or elevated ) , and self - rated health ( good or poor ) . high risk for osa was not associated with overweight in strata of sex , bp , or self - rated health . for central obesity high risk for osa was associated with central obesity only in men ( or 4.66 ; 95% ci : 1.3316.39 ) , in individuals with elevated bp ( or 7.34 ; 95% ci : 2.3822.59 ) , and in those with good self - rated health ( or 2.60 ; 95% ci 1.285.28 ) while the findings in women and those with poor self - rated health were suggestive of a positive though not statistically significant association ( table 4 ) . in this study of chilean college students , 7.8% were classified as having high risk for osa as defined by the berlin questionnaire and there was a high prevalence of overweight ( 28.3% ) , general obesity ( 12.8% ) , and central obesity ( 42.7% ) . high osa risk was strongly and positively associated with general obesity and central obesity , but not with overweight . although the exact pathway linking osa and obesity remains somewhat unclear , it is recognized that obesity contributes to airway collapse during sleep by causing increased fat deposits around the upper airway , thus narrowing it and diminishing the activity of the muscles in that region [ 2831 ] . conversely , sleep apnea may contribute to excess weight and obesity through sleep loss and daytime sleepiness as apneic individuals rouse often to resume breathing and reenable unobstructed air flow . moreover , insufficient sleep has been associated with increased energy need and food intake . on balance , available evidence suggests mechanisms that may underlay bidirectional relationships between increased adiposity and osa . we found strong positive associations of high osa risk with general obesity , central obesity , bmi , and whr . these findings are largely consistent with findings from numerous prior studies [ 3340 ] . in the wisconsin sleep cohort study , a 10% weight gain was associated with approximately 32% increase in ahi as assessed by polysomnography . in their study of patients at primary health care centers in dubai , mahboub et al . found that approximately 70% of those at high risk for osa had a bmi  30  kg / m while about 75% of the low risk group had bmi < 30 likewise , blondet et al . found in a study of middle - aged puerto ricans that among men with bmi < 30  kg / m , 98% had high risk for osa compared to 50% among nonobese men . in addition , the authors noted that 70% of women with bmi > 28  kg / m were at high risk for osa compared to only 28% of those with bmi < 28  kg / m . the prevalence of high risk for osa among students with general obesity in our study was substantially higher ( 28.3% ) compared to that in normal weight ( 4.6% ) and overweight ( 5.4% ) students . although participants in many studies examining obesity and osa risk are older and heavier than our population , significant positive associations between sleep apnea and obesity have also been found in pediatric and adolescent populations [ 4346 ] . while we found no association between overweight bmi category and high risk for osa in our sample , peppard et al . observed a positive association between overweight bmi category and ahi in the wisconsin sleep cohort study . despite our finding of no association , overweight students should be targeted for interventions as these students are at higher risk for obesity in the near future compared to normal weight students . the prevalence of high risk for osa in our sample ( 7.8% ) is higher than what is reported among us young adults . for instance , authors of a study among 1,845 students enrolled in a southeastern us college reported a prevalence of 4% as assessed using the sleep-50 survey . however , our finding is lower than high osa risk estimates reported for us adults ( 26% ) who participated in the 2005 sleep in america poll . we found no significant difference in frequency of osa risk by sex ( 9.3% for men and 7.1% for women ; p = 0.25 ) within our sample , although other investigators have shown that men have a higher risk for osa compared to women  the main hypothesis being that men tend to have more fat deposits in the upper part of the body , that is , around the neck , trunk , and abdomen . the prevalence of general obesity in our study ( 12.8% ) was relatively low when compared to the prevalence reported for chilean adults by the oecd ( 25.1% ) or that determined from a multistage cluster sampling of adults 40 years old in santiago , chile ( 31.7% ) [ 4 , 11 ] . however , the combined prevalence of overweight and obesity ( i.e. , bmi  25  kg / m ) in our study was greater than that observed in a study of 3,461 chilean students aged 1724 years ( 41.1% versus 19% ) . when we examined the frequency of bmi  25  kg / m by age within our sample , there was still a high prevalence of excess weight in the respective groups : 1824 year - olds ( 39.5% ) and 2535 year - olds ( 48.4% ) ; p = 0.04 . these high frequencies of overweight and obesity in young adulthood are of concern as they may have implications for the development of cardiometabolic conditions in later life . first , numerous validation studies have reported moderate to high consistency between results of the berlin questionnaire and parameters of polysomnography , the gold - standard for diagnosing sleep disorders . second , we employed various statistical methods and assessed the relationship between high osa risk and various indices of adiposity . third , the likelihood for misclassification of obesity was reduced as trained research nurses used standard protocols to take anthropometric measurements , thus avoiding reliance on students ' self - report . there are some limitations that should be considered when interpreting the results of our study . given our cross - sectional study design , we are unable to determine if high risk for osa preceded obesity . another limitation is that participants were not sampled randomly ; rather , we relied on subjects ' willingness to participate . approximately 8% of students were excluded because of incomplete information on sleep apnea or anthropometric data . we found no significant difference between the prevalence of poor self - rated heath among individuals in our sample and those who were excluded ( 12.1% versus 6.8% ; p = 0.29 ) nor any significant difference in the distribution of cigarette smoking status ( p = 0.28 ) . however , excluded students tended to be older than those in our sample ( mean  sd age : 23.4    5.0 versus 21.8    3.3 ; p < 0.01 ) . given that osa risk increases with age , it is possible that we missed individuals with high osa risk among those who had incomplete sleep apnea or anthropometric information . thus , the prevalence of high risk for osa in our study could be an underestimate . conversely , given the high prevalence of obesity within this sample , the use of odds ratios may give an exaggeration of the true estimate . we can not exclude the possibility of residual confounding by unmeasured factors such as socioeconomic status , dietary intake ( e.g. , consumption of fruits , vegetables , or fast foods ) , or student 's course load . finally , due to the relatively small sample size , the 95% confidence intervals for the estimates from the logistic regression and stratified analyses are quite large and imprecise . our findings support significant positive associations of high osa risk with general obesity and central obesity . additional longitudinal evidence is needed to establish the temporal relationship of osa and obesity . if our findings are confirmed , health care services for college students should include health promotion and disease prevention strategies about the importance of maintaining healthy weight . strategies should also include health education modules that may be used to improve students ' knowledge about sleep disorders , as prevention and control of cardiometabolic risk factors in young adulthood may have implications for preventing and mitigating chronic disease burden in later life .