human
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The transition to college has been identified as a critical period for increases in overweight status . Overweight college students are at-risk of becoming obese adults , and , thus prevention efforts targeting college age individuals are key to reducing adult obesity rates . The current study evaluated an Internet intervention with first year college students ( N=170 ) r and omly assigned to one of four treatment conditions : 1 ) no treatment , 2 ) 6-week online intervention 3 ) 6-week weight and caloric feedback only ( via email ) , and 4 ) 6-week combined feedback and online intervention . The combined intervention group had lower BMI s at post-testing than the other three groups . This study demonstrated the effectiveness and feasibility of an online intervention to prevent weight gain among college students IMPORTANCE Weight gain occurs commonly in young adults and has adverse effects on health . OBJECTIVE To compare 2 self-regulation interventions vs control in reducing weight gain in young adults over a mean follow-up of 3 years . DESIGN , SETTING , AND PARTICIPANTS R and omized clinical trial in 2 academic setting s of 599 participants aged 18 to 35 years with body mass index ( BMI , calculated as weight in kilograms divided by height in meters squared ) of 21.0 to 30.0 , recruited via mailings and emails from August 2010 to February 2012 . Data were analyzed from January 2015 to January 2016 . INTERVENTIONS Participants were r and omized to control , self-regulation plus small changes , or self-regulation plus large changes . Both interventions focused on frequent self-weighing to cue behavior changes . " Small changes " taught participants to reduce intake and increase activity , both by approximately 100 calories per day . " Large changes " focused on losing 2.3 to 4.5 kg initially to buffer against expected weight gain . MAIN OUTCOMES AND MEASURES Changes in weight from baseline over mean follow-up of 3 years . Secondary outcomes included proportion gaining at least 0.45 kg from baseline , proportion developing obesity ( BMI , ≥30.0 ) , and weight change baseline to 2 years . RESULTS Among the 599 participants ( 22 % men ; 27 % minority ; mean [ SD ] age , 27.7 [ 4.4 ] years ; mean [ SD ] BMI , 25.4 [ 2.6 ] ) , mean ( SE ) weight changes over a mean follow-up of 3 years were 0.26 ( 0.22 ) , -0.56 ( 0.22 ) , and -2.37 ( 0.22 ) kg in the control , small-changes , and large-changes groups , respectively ( P < .001 ) . Differences among all 3 groups were significant ( large changes vs control , P < .001 ; small changes vs control , P = .02 ; large changes vs small changes , P < .001 ) . On secondary outcomes , both interventions significantly reduced incidence of obesity relative to control ( mean [ SE ] , 8.6 % [ 2.0 % ] , 7.9 % [ 2.0 % ] , and 16.9 % [ 2.7 % ] in the large-changes , small-changes , and control groups , respectively ; P = .02 for large changes vs control and P = .002 for small changes vs control ) ; a smaller percentage of participants in the large-changes group gained 0.45 kg or more ( mean [ SE ] , 23.6 % [ 2.8 % ] , 32.5 % [ 3.8 % ] , and 40.8 % [ 4.4 % ] , respectively ; P < .001 vs control and P = .02 vs small changes ) and weight change from baseline to 2 years was greater in control than in small or large changes ( mean [ SE ] , 0.54 [ 0.33 ] , -0.77 [ 0.33 ] , and -1.50 [ 0.34 ] kg , respectively ; P = .02 vs small changes and P < .001 vs large changes ) . CONCLUSIONS AND RELEVANCE Self-regulation with large or small changes both reduced weight gain in young adults over 3 years relative to control , but the large-changes intervention was more effective . TRIAL REGISTRATION clinical trials.gov Identifier : NCT01183689 Background This paper reports the results of a repeat trial assessing the effectiveness of an online theory-based intervention to promote healthy lifestyle behaviours in new university students . The original trial found that the intervention reduced the number of smokers at 6-month follow-up compared with the control condition , but had non-significant effects on the other targeted health behaviours . However , the original trial suffered from low levels of engagement , which the repeat trial sought to rectify . Methods Three weeks before staring university , all incoming undergraduate students at a large university in the UK were sent an email inviting them to participate in the study . After completing a baseline question naire , participants were r and omly allocated to intervention or control conditions . The intervention consisted of a self-affirmation manipulation , health messages based on the theory of planned behaviour and implementation intention tasks . Participants were followed-up 1 and 6 months after starting university . The primary outcome measures were portions of fruit and vegetables consumed , physical activity levels , units of alcohol consumed and smoking status at 6-month follow-up . Results The study recruited 2,621 students ( intervention n = 1346 , control n = 1275 ) , of whom 1495 completed at least one follow-up ( intervention n = 696 , control n = 799 ) . Intention-to-treat analyses indicated that the intervention had a non-significant effect on the primary outcomes , although the effect of the intervention on fruit and vegetable intake was significant in the per- protocol analyses . Secondary analyses revealed that the intervention had significant effects on having smoked at university ( self-report ) and on a biochemical marker of alcohol use . Conclusions Despite successfully increasing levels of engagement , the intervention did not have a significant effect on the primary outcome measures . The relatively weak effects of the intervention , found in both the original and repeat trials , may be due to the focus on multiple versus single health behaviours . Future interventions targeting the health behaviour of new university students should therefore focus on single health behaviours . Trial registration Current Controlled Trials IS RCT N07407344 Background Too few young people engage in behaviours that reduce the risk of morbidity and premature mortality , such as eating healthily , being physically active , drinking sensibly and not smoking . This study sought to assess the efficacy and cost-effectiveness of a theory-based online health behaviour intervention ( based on self-affirmation theory , the Theory of Planned Behaviour and implementation intentions ) targeting these behaviours in new university students , in comparison to a measurement-only control . Methods Two-weeks before starting university all incoming undergraduates at the University of Sheffield were invited to take part in a study of new students ’ health behaviour . A r and omised controlled design , with a baseline question naire , and two follow-ups ( 1 and 6 months after starting university ) , was used to evaluate the intervention . Primary outcomes were measures of the four health behaviours targeted by the intervention at 6-month follow-up , i.e. , portions of fruit and vegetables , metabolic equivalent of tasks ( physical activity ) , units of alcohol , and smoking status . Results The study recruited 1,445 students ( intervention n = 736 , control n = 709 , 58 % female , Mean age = 18.9 years ) , of whom 1,107 completed at least one follow-up ( 23 % attrition ) . The intervention had a statistically significant effect on one primary outcome , smoking status at 6-month follow-up , with fewer smokers in the intervention arm ( 8.7 % ) than in the control arm ( 13.0 % ; Odds ratio = 1.92 , p = .010 ) . There were no significant intervention effects on the other primary outcomes ( physical activity , alcohol or fruit and vegetable consumption ) at 6-month follow-up . Conclusions The results of the RCT indicate that the online health behaviour intervention reduced smoking rates , but it had little effect on fruit and vegetable intake , physical activity or alcohol consumption , during the first six months at university . However , engagement with the intervention was low . Further research is needed before strong conclusions can be made regarding the likely effectiveness of the intervention to promote health lifestyle habits in new university students . Trial registration Current Controlled Trials , IS RCT N67684181 Context Studies of the natural history of obesity have had limitations , such as cross-sectional design , short follow-up , or narrowly defined population s. Contribution Using data from a national study of Americans born between 1957 and 1964 and followed for nearly two decades , these investigators found that more than 25 % were obese by age 35 years . Obesity developed most quickly in black women , with moderate rapidity in Hispanic women , and most slowly in white women . Hispanic men developed obesity more quickly than other men . More recent birth cohorts became obese faster than earlier cohorts . Implication s Underst and ing ethnic differences in the age of onset and rate of progression of obesity may help efforts to prevent obesity . The Editors The proportion of Americans who are overweight or obese is increasing at an alarming rate . From 1960 to 1999 , the prevalence of excess weight ( body mass index [ BMI ] 25 kg/m2 ) increased from 44 % to 61 % of the adult population ( persons aged 20 to 74 years ) and the prevalence of obesity ( BMI 30 kg/m2 ) doubled from 13 % to 27 % ( 1 , 2 ) . Obesity has been linked to increased mortality and chronic morbidity from such diverse causes as hypertension , diabetes , sleep apnea , certain types of cancer , and depression . In the context of this rising prevalence , obesity is increasingly being recognized as an important medical and public health problem ( 3 - 6 ) . Treatment options are available for obesity . However , they can be expensive , often involve difficult lifestyle modifications , and pose adherence problems for many patients . In addition , weight loss , once achieved , is difficult to sustain . Because the health consequences are often long term , the costbenefit ratio of treatment may be more favorable if people who have recently become obese are targeted . Similarly , prevention should focus on those at immediate risk for becoming obese or overweight . Such approaches require a clear underst and ing of who is at highest risk for obesity , when this risk is greatest , and how excess weight develops over time . Although inactivity and high caloric intake are the primary risk factors for obesity , other risk factors have been established . Three of the most influential are age , sex , and race or ethnicity ( 1 , 7 - 9 ) . To better identify people at risk for obesity and those who might benefit from early intervention , we assessed the relationship between weight development and these influential factors . Despite the morbidity and mortality burden of obesity , its natural history has not been well characterized . Current knowledge is based largely on cross-sectional data . Although several large studies have examined weight development in adults , they have important limitations . Only a few tracked weight long enough to detect age-based trends . The first National Health and Nutrition Examination Survey ( NHANES I ) Epidemiologic Follow-up Study examined a representative group of U.S. residents but sample d only two time points , spaced 10 years apart , and had insufficient follow-up to track weight patterns in most minority groups ( 10 ) . The Coronary Artery Risk Development in Young Adults study followed weight development in a large cohort of young black and white Americans but did not provide data for other population s and was geographically restricted ( 8) . Other studies have been performed outside of the United States , but the results may not apply here ( 10 , 11 ) . We design ed our study to address the limitations described earlier . We examined data from the National Longitudinal Survey of Youth 1979 ( NLSY79 ) . This large , prospect i ve cohort study allowed longitudinal examination of weight trends over a time frame sufficient to capture the dynamics of such a slowly changing problem and of an age range during which obesity becomes prevalent . Because not all weight gain has been documented to be harmful , our analysis focused on obesity onset ( defined as the time at which a person reaches obesity ) rather than weight gain . We used the clinical definition of obesity ( BMI 30 kg/m2 ) as our end point because it reflects a point at which mortality risk increases substantially ( 12 ) . Underst and ing how obesity develops over time , who is at greatest risk , and when that risk is highest may be essential in reversing the population trend toward excess weight . Methods Study Group and Obesity Measurement We analyzed data from the NLSY79 , which was initiated by the U.S. Department of Labor , Bureau of Labor Statistics . This survey was design ed to gather information about the labor market activities and other life events of young U.S. citizens . It has been used extensively in economic and sociologic analyses , and the sample design is described elsewhere ( 13 - 16 ) . The cohort of men and women , born between 1957 and 1964 , has been followed for more than two decades . It consists of a nationally representative group , with supplemental sample s overrepresenting minority racial and ethnic groups and poor persons . We excluded a sample of military personnel because this population was removed from the study in 1985 and because physical activity requirements for these individuals could lead to atypical weight patterns . We included only persons who reported that the ethnicity with which they most closely identified was Hispanic , black , or white ( or European origin ) . Height and weight data were self-reported ; height was reported in 1981 and 1985 , and weight was reported 12 times between 1981 and 1998 . Examination of Age-Specific Body Mass Index Patterns Age-specific BMI was calculated for all participants . Height was assumed to remain constant after age  
    Output:
    
agent
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The transition to college has been identified as a critical period for increases in overweight status . Overweight college students are at-risk of becoming obese adults , and , thus prevention efforts targeting college age individuals are key to reducing adult obesity rates . The current study evaluated an Internet intervention with first year college students ( N=170 ) r and omly assigned to one of four treatment conditions : 1 ) no treatment , 2 ) 6-week online intervention 3 ) 6-week weight and caloric feedback only ( via email ) , and 4 ) 6-week combined feedback and online intervention . The combined intervention group had lower BMI s at post-testing than the other three groups . This study demonstrated the effectiveness and feasibility of an online intervention to prevent weight gain among college students IMPORTANCE Weight gain occurs commonly in young adults and has adverse effects on health . OBJECTIVE To compare 2 self-regulation interventions vs control in reducing weight gain in young adults over a mean follow-up of 3 years . DESIGN , SETTING , AND PARTICIPANTS R and omized clinical trial in 2 academic setting s of 599 participants aged 18 to 35 years with body mass index ( BMI , calculated as weight in kilograms divided by height in meters squared ) of 21.0 to 30.0 , recruited via mailings and emails from August 2010 to February 2012 . Data were analyzed from January 2015 to January 2016 . INTERVENTIONS Participants were r and omized to control , self-regulation plus small changes , or self-regulation plus large changes . Both interventions focused on frequent self-weighing to cue behavior changes . " Small changes " taught participants to reduce intake and increase activity , both by approximately 100 calories per day . " Large changes " focused on losing 2.3 to 4.5 kg initially to buffer against expected weight gain . MAIN OUTCOMES AND MEASURES Changes in weight from baseline over mean follow-up of 3 years . Secondary outcomes included proportion gaining at least 0.45 kg from baseline , proportion developing obesity ( BMI , ≥30.0 ) , and weight change baseline to 2 years . RESULTS Among the 599 participants ( 22 % men ; 27 % minority ; mean [ SD ] age , 27.7 [ 4.4 ] years ; mean [ SD ] BMI , 25.4 [ 2.6 ] ) , mean ( SE ) weight changes over a mean follow-up of 3 years were 0.26 ( 0.22 ) , -0.56 ( 0.22 ) , and -2.37 ( 0.22 ) kg in the control , small-changes , and large-changes groups , respectively ( P < .001 ) . Differences among all 3 groups were significant ( large changes vs control , P < .001 ; small changes vs control , P = .02 ; large changes vs small changes , P < .001 ) . On secondary outcomes , both interventions significantly reduced incidence of obesity relative to control ( mean [ SE ] , 8.6 % [ 2.0 % ] , 7.9 % [ 2.0 % ] , and 16.9 % [ 2.7 % ] in the large-changes , small-changes , and control groups , respectively ; P = .02 for large changes vs control and P = .002 for small changes vs control ) ; a smaller percentage of participants in the large-changes group gained 0.45 kg or more ( mean [ SE ] , 23.6 % [ 2.8 % ] , 32.5 % [ 3.8 % ] , and 40.8 % [ 4.4 % ] , respectively ; P < .001 vs control and P = .02 vs small changes ) and weight change from baseline to 2 years was greater in control than in small or large changes ( mean [ SE ] , 0.54 [ 0.33 ] , -0.77 [ 0.33 ] , and -1.50 [ 0.34 ] kg , respectively ; P = .02 vs small changes and P < .001 vs large changes ) . CONCLUSIONS AND RELEVANCE Self-regulation with large or small changes both reduced weight gain in young adults over 3 years relative to control , but the large-changes intervention was more effective . TRIAL REGISTRATION clinical trials.gov Identifier : NCT01183689 Background This paper reports the results of a repeat trial assessing the effectiveness of an online theory-based intervention to promote healthy lifestyle behaviours in new university students . The original trial found that the intervention reduced the number of smokers at 6-month follow-up compared with the control condition , but had non-significant effects on the other targeted health behaviours . However , the original trial suffered from low levels of engagement , which the repeat trial sought to rectify . Methods Three weeks before staring university , all incoming undergraduate students at a large university in the UK were sent an email inviting them to participate in the study . After completing a baseline question naire , participants were r and omly allocated to intervention or control conditions . The intervention consisted of a self-affirmation manipulation , health messages based on the theory of planned behaviour and implementation intention tasks . Participants were followed-up 1 and 6 months after starting university . The primary outcome measures were portions of fruit and vegetables consumed , physical activity levels , units of alcohol consumed and smoking status at 6-month follow-up . Results The study recruited 2,621 students ( intervention n = 1346 , control n = 1275 ) , of whom 1495 completed at least one follow-up ( intervention n = 696 , control n = 799 ) . Intention-to-treat analyses indicated that the intervention had a non-significant effect on the primary outcomes , although the effect of the intervention on fruit and vegetable intake was significant in the per- protocol analyses . Secondary analyses revealed that the intervention had significant effects on having smoked at university ( self-report ) and on a biochemical marker of alcohol use . Conclusions Despite successfully increasing levels of engagement , the intervention did not have a significant effect on the primary outcome measures . The relatively weak effects of the intervention , found in both the original and repeat trials , may be due to the focus on multiple versus single health behaviours . Future interventions targeting the health behaviour of new university students should therefore focus on single health behaviours . Trial registration Current Controlled Trials IS RCT N07407344 Background Too few young people engage in behaviours that reduce the risk of morbidity and premature mortality , such as eating healthily , being physically active , drinking sensibly and not smoking . This study sought to assess the efficacy and cost-effectiveness of a theory-based online health behaviour intervention ( based on self-affirmation theory , the Theory of Planned Behaviour and implementation intentions ) targeting these behaviours in new university students , in comparison to a measurement-only control . Methods Two-weeks before starting university all incoming undergraduates at the University of Sheffield were invited to take part in a study of new students ’ health behaviour . A r and omised controlled design , with a baseline question naire , and two follow-ups ( 1 and 6 months after starting university ) , was used to evaluate the intervention . Primary outcomes were measures of the four health behaviours targeted by the intervention at 6-month follow-up , i.e. , portions of fruit and vegetables , metabolic equivalent of tasks ( physical activity ) , units of alcohol , and smoking status . Results The study recruited 1,445 students ( intervention n = 736 , control n = 709 , 58 % female , Mean age = 18.9 years ) , of whom 1,107 completed at least one follow-up ( 23 % attrition ) . The intervention had a statistically significant effect on one primary outcome , smoking status at 6-month follow-up , with fewer smokers in the intervention arm ( 8.7 % ) than in the control arm ( 13.0 % ; Odds ratio = 1.92 , p = .010 ) . There were no significant intervention effects on the other primary outcomes ( physical activity , alcohol or fruit and vegetable consumption ) at 6-month follow-up . Conclusions The results of the RCT indicate that the online health behaviour intervention reduced smoking rates , but it had little effect on fruit and vegetable intake , physical activity or alcohol consumption , during the first six months at university . However , engagement with the intervention was low . Further research is needed before strong conclusions can be made regarding the likely effectiveness of the intervention to promote health lifestyle habits in new university students . Trial registration Current Controlled Trials , IS RCT N67684181 Context Studies of the natural history of obesity have had limitations , such as cross-sectional design , short follow-up , or narrowly defined population s. Contribution Using data from a national study of Americans born between 1957 and 1964 and followed for nearly two decades , these investigators found that more than 25 % were obese by age 35 years . Obesity developed most quickly in black women , with moderate rapidity in Hispanic women , and most slowly in white women . Hispanic men developed obesity more quickly than other men . More recent birth cohorts became obese faster than earlier cohorts . Implication s Underst and ing ethnic differences in the age of onset and rate of progression of obesity may help efforts to prevent obesity . The Editors The proportion of Americans who are overweight or obese is increasing at an alarming rate . From 1960 to 1999 , the prevalence of excess weight ( body mass index [ BMI ] 25 kg/m2 ) increased from 44 % to 61 % of the adult population ( persons aged 20 to 74 years ) and the prevalence of obesity ( BMI 30 kg/m2 ) doubled from 13 % to 27 % ( 1 , 2 ) . Obesity has been linked to increased mortality and chronic morbidity from such diverse causes as hypertension , diabetes , sleep apnea , certain types of cancer , and depression . In the context of this rising prevalence , obesity is increasingly being recognized as an important medical and public health problem ( 3 - 6 ) . Treatment options are available for obesity . However , they can be expensive , often involve difficult lifestyle modifications , and pose adherence problems for many patients . In addition , weight loss , once achieved , is difficult to sustain . Because the health consequences are often long term , the costbenefit ratio of treatment may be more favorable if people who have recently become obese are targeted . Similarly , prevention should focus on those at immediate risk for becoming obese or overweight . Such approaches require a clear underst and ing of who is at highest risk for obesity , when this risk is greatest , and how excess weight develops over time . Although inactivity and high caloric intake are the primary risk factors for obesity , other risk factors have been established . Three of the most influential are age , sex , and race or ethnicity ( 1 , 7 - 9 ) . To better identify people at risk for obesity and those who might benefit from early intervention , we assessed the relationship between weight development and these influential factors . Despite the morbidity and mortality burden of obesity , its natural history has not been well characterized . Current knowledge is based largely on cross-sectional data . Although several large studies have examined weight development in adults , they have important limitations . Only a few tracked weight long enough to detect age-based trends . The first National Health and Nutrition Examination Survey ( NHANES I ) Epidemiologic Follow-up Study examined a representative group of U.S. residents but sample d only two time points , spaced 10 years apart , and had insufficient follow-up to track weight patterns in most minority groups ( 10 ) . The Coronary Artery Risk Development in Young Adults study followed weight development in a large cohort of young black and white Americans but did not provide data for other population s and was geographically restricted ( 8) . Other studies have been performed outside of the United States , but the results may not apply here ( 10 , 11 ) . We design ed our study to address the limitations described earlier . We examined data from the National Longitudinal Survey of Youth 1979 ( NLSY79 ) . This large , prospect i ve cohort study allowed longitudinal examination of weight trends over a time frame sufficient to capture the dynamics of such a slowly changing problem and of an age range during which obesity becomes prevalent . Because not all weight gain has been documented to be harmful , our analysis focused on obesity onset ( defined as the time at which a person reaches obesity ) rather than weight gain . We used the clinical definition of obesity ( BMI 30 kg/m2 ) as our end point because it reflects a point at which mortality risk increases substantially ( 12 ) . Underst and ing how obesity develops over time , who is at greatest risk , and when that risk is highest may be essential in reversing the population trend toward excess weight . Methods Study Group and Obesity Measurement We analyzed data from the NLSY79 , which was initiated by the U.S. Department of Labor , Bureau of Labor Statistics . This survey was design ed to gather information about the labor market activities and other life events of young U.S. citizens . It has been used extensively in economic and sociologic analyses , and the sample design is described elsewhere ( 13 - 16 ) . The cohort of men and women , born between 1957 and 1964 , has been followed for more than two decades . It consists of a nationally representative group , with supplemental sample s overrepresenting minority racial and ethnic groups and poor persons . We excluded a sample of military personnel because this population was removed from the study in 1985 and because physical activity requirements for these individuals could lead to atypical weight patterns . We included only persons who reported that the ethnicity with which they most closely identified was Hispanic , black , or white ( or European origin ) . Height and weight data were self-reported ; height was reported in 1981 and 1985 , and weight was reported 12 times between 1981 and 1998 . Examination of Age-Specific Body Mass Index Patterns Age-specific BMI was calculated for all participants . Height was assumed to remain constant after age  
    Output:
    