***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: BACKGROUND The federal menu labeling law will require chain restaurants to post caloric information on menus , but the impact of labeling is uncertain . PURPOSE The goal of the current study was to examine the effect of menu labeling on calories purchased , and secondarily , to assess self-reported awareness and use of labels . DESIGN Single-community pre-post-post cross-sectional study . Data were collected in 2008 - 2010 and analyzed in 2011 - 2012 . SETTING / PARTICIPANTS 50 sites from 10 chain restaurants in King County , Washington , selected through stratified , two-stage cluster r and om sampling . A total of 7325 customers participated . Eligibility criteria were : being an English speaker , aged ≥ 14 years , and having an itemized receipt . The study population was 59 % male , 76 % white non-Hispanic , and 53 % aged<40 years . INTERVENTION A regulation requiring chain restaurants to post calorie information on menus or menu boards was implemented . MAIN OUTCOME MEASURES Mean number of calories purchased . RESULTS No significant changes occurred between baseline and 4 - 6 months postregulation . Mean calories per purchase decreased from 908.5 to 870.4 at 18 months post-implementation ( 38 kcal , 95 % CI=-76.9 , 0.8 , p=0.06 ) in food chains and from 154.3 to 132.1 ( 22 kcal , 95 % CI=-35.8 , -8.5 , p=0.002 ) in coffee chains . Calories decreased in taco and coffee chains , but not in burger and s and wich establishments . They decreased more among women than men in coffee chains . Awareness of labels increased from 18.8 % to 61.7 % in food chains and from 4.4 % to 30.0 % in coffee chains ( both p<0.001 ) . Among customers seeing calorie information , the proportion using it ( about one third ) did not change substantially over time . After implementation , food chain customers using information purchased on average fewer calories compared to those seeing but not using ( difference=143.2 kcal , p<0.001 ) and those not seeing ( difference=135.5 kcal , p<0.001 ) such information . CONCLUSIONS Mean calories per purchase decreased 18 months after implementation of menu labeling in some restaurant chains and among women but not men This study investigated the effectiveness of labeling foods with the Choices nutrition logo on influencing cafeteria menu selection and the behavioral determinants of menu choices in work site cafeterias in the Netherl and s. A cluster r and omized controlled trial was conducted .  Intervention cafeterias ( n=13 ) , where the Choices logo was used to promote healthier eating for a 3-week period , were compared with control cafeterias ( n=12 ) , which offered the same menu without the logo .  Sales data were collected daily for 9 weeks , from March to May 2009 . In addition , employees from one intervention and one control company completed an online question naire at baseline and after the intervention ( n=368 ) in which the behavioral determinants of food choice ( ie , attitude , self-efficacy , and intention ) and logo use were measured . Generalized estimating equation analyses , χ² tests , t tests and linear regression analyses were performed . No nutritionally meaningful intervention effects were found in the sales of s and wiches , soups , snacks , fruit , and salads . Also , no significant differences in behavioral determinants were found . " Intention to eat healthier " and " paying attention to product information " were positively associated with self-reported consumption of foods with the Choices logo at lunch . The intervention did not have a significant effect on employees ' lunchtime food choices . Labeling healthy choices might be useful for health-conscious employees in the volitional phase of behavior change . Further research should focus on the possible health benefits of menu reformulation in the catering sector Objective Obesity is a pressing public health problem without proven population -wide solutions . Research ers sought to determine whether a city-m and ated policy requiring calorie labeling at fast food restaurants was associated with consumer awareness of labels , calories purchased and fast food restaurant visits . Design and Methods Difference-in-differences design , with data collected from consumers outside fast food restaurants and via a r and om digit dial telephone survey , before ( December 2009 ) and after ( June 2010 ) labeling in Philadelphia ( which implemented m and atory labeling ) and Baltimore ( matched comparison city ) . Measures included : self-reported use of calorie information , calories purchased determined via fast food receipts , and self-reported weekly fast-food visits . Results The consumer sample was predominantly Black ( 71 % ) , and high school educated ( 62 % ) . Post-labeling , 38 % of Philadelphia consumers noticed the calorie labels for a 33 percentage point ( p<.001 ) increase relative to Baltimore . Calories purchased and number of fast food visits did not change in either city over time . Conclusions While some consumer reports noticing and using calorie information , no population level changes were noted in calories purchased or fast food visits . Other controlled studies are needed to examine the longer term impact of labeling as it becomes national law The increase in the weight of American adults and children has been positively associated with the prevalence of the consumption of food-away-from-home . The objective was to assess the accuracy of cl aim ed nutritional information of foods purchased in contracted foodservices located on the campus of an institution of higher education . Fifty popular food items were r and omly collected from five main dining outlets located on a selected campus in the northeastern United States . The sampling was repeated three times on separate occasions for an aggregate total of 150 food sample s. The sample s were then weighed and assessed for nutrient composition ( protein , cholesterol , fiber , carbohydrates , total fat , calories , sugar , and sodium ) using nutrient analysis software . Results were compared with foodservices ' published nutrition information . Two group comparisons , cl aim ed and measured , were performed using the paired- sample t-test . Descriptive statistics were used as well . Among the nine nutritional values , six nutrients ( total fat , sodium , protein , fiber , cholesterol , and weight ) had more than 10 % positive average discrepancies between measured and cl aim ed values . Statistical significance of the variance was obtained in four of the eight categories of nutrient content : total fat , sodium , protein , and cholesterol ( P < .05 ) . Significance was also reached in the variance of actual portion weight compared to the published cl aims ( P < .001 ) . Significant differences of portion size ( weight ) , total fat , sodium , protein , and cholesterol were found among the sample d values and the foodservices ' published cl aims . The findings from this study raise the concern that if the actual nutritional information does not accurately reflect the declared values on menus , conclusions , decisions and actions based on posted information may not be valid We surveyed 7318 customers from 275 r and omly selected restaurants of 11 fast food chains . Participants purchased a mean of 827 calories , with 34 % purchasing 1000 calories or more . Unlike other chains , Subway posted calorie information at point of purchase and its patrons more often reported seeing calorie information than patrons of other chains ( 32 % vs 4 % ; P<.001 ) ; Subway patrons who saw calorie information purchased 52 fewer calories than did other Subway patrons ( P<.01 ) . Fast-food chains should display calorie information prominently at point of purchase , where it can be seen and used to inform purchases OBJECTIVE The present study is to describe , on the basis of recent Finnish population surveys , ( i ) the frequencies of  school and worksite canteen use , ( ii ) the determinants of having a hot lunch during school or working hours and ( iii ) the associations of lunch eating patterns with food habits . SETTING The study summarises mainly basic reports and studies concerning catering services conducted in Finl and based on nationally representative population surveys . Design and subjectsCross-sectional study . The most important surveys cited in this paper are the School Health Promotion Study , the Work and the Working Conditions survey , the National FINDIET 2002 Study , and the Health Behavior and Health among Finnish Adult Population survey . RESULTS School lunch is eaten by on average 70 - 90 % of children aged 9 - 18 years . Of all employees , 30 % eat at a worksite canteen daily , whereas 30 % of men and 45 % of women eat packed lunches . Nationally representative cross-sectional population surveys show that the use of catering services is associated with more healthy food habits ; schoolchildren eating school meals and employees eating lunch at a worksite canteen tend to make food choices closer to nutritional recommendations as compared to those not using catering services to the same degree . CONCLUSIONS Some evidence exists that catering services in schools and worksites contribute to healthy eating habits in the population . In order to verify the positive role of catering services more scientific research with prospect i ve and intervention design studies will be needed OBJECTIVE To examine the influences of nutritional information and consumer characteristics on meal quality expectations , food selection and subsequent macronutrient intakes of consumers offered a reduced-fat option in a restaurant . DESIGN A target , full-fat ( FF ) main restaurant meal option was developed in a version substantially reduced in fat and energy ( RF ) . Restaurant patrons were r and omly placed into one of four treatment groups varying in provision of menu information about the target dish , and the actual version of that dish served ( if ordered ) . A full-fat blind ( FFB ) control group was given no nutritional information in the menu and was served the FF version . The other three groups were all served the modified RF version : ( i ) reduced-fat blind ( RFB ) , who were given no nutritional information ; ( ii ) reduced-fat informed ( RFI ) , who were given nutritional information ; and ( iii ) reduced-fat informed with details ( RFID ) , who were given the same nutritional information plus recipe modification details . Subjects rated their expected and actual liking , the pleasantness of taste , texture and appearance of the dish , how well the dish matched their expectations , and the likelihood of purchase again . Additional measures included the other dish selection s , sociodemographic and attitudinal information . SETTING A silver service ( training ) restaurant . SUBJECTS Members of the public ( n = 279 ) consuming meals in the restaurant . RESULTS The presence of nutritional information on the menu did not significantly increase subsequent intakes of energy and fat from the rest of the meal , and did not significantly influence sensory expectations or post-meal acceptance measures ( which also did not differ between the FF and RF versions ) . Consumer characteristics relating to fat reduction attitudes and behaviours were significantly related to the selection of different dishes . CONCLUSIONS Provision of RF alternatives in a restaurant can have significant positive dietary benefits . Menu nutritional information did not affect measures of meal acceptance . Further studies should identify which types of information formats might be most effective in enhancing the selection of ' healthy ' options This study assessed whether the inclusion of kilojoule labelling alone or accompanied by further nutrition information on menus led adults to select less energy-dense fast food meals . A between-subjects experimental design was used with online menu boards systematic ally varied to test the following labelling conditions : none ( control ) ; kilojoule ; kilojoule+percent daily intake ; kilojoule+traffic light ; and kilojoule+traffic light+percent daily intake . Respondents were 1294 adults aged 18 - 49 in Victoria , Australia who had purchased fast food in the last month and were r and omly assigned to conditions . Respondents in the no labelling condition selected meals with the highest mean energy content and those viewing the kilojoule and kilojoule+traffic light information selected meals with a significantly lower mean energy content , that constituted a reduction of around 500kJ ( 120kcal ) . Respondents most commonly reported using the traffic light labels in making their selection s. These findings provide support for the policy of disclosure of energy content on menus at restaurant chains . Given the magnitude of the reduction in energy density reported , and the prevalence of fast food consumption , this policy initiative has the potential to yield health benefits at the population level CONTEXT National recommendations for the prevention and treatment of obesity emphasize reducing energy intake . Foods purchased in restaurants provide approximately 35 % of the daily energy intake in US individuals but the accuracy of the energy contents listed for these foods is unknown . OBJECTIVE To examine the accuracy of stated energy contents of foods purchased in restaurants . DESIGN AND SETTING A vali date d bomb calorimetry technique was used to measure dietary energy in food from 42 restaurants , comprising 269 total food items and 242 unique foods . The restaurants and foods were r and omly selected from quick-serve and sit-down restaurants in Massachusetts , Arkansas , and Indiana between January and June 2010 . MAIN OUTCOME MEASURE The difference between restaurant-stated and laboratory-measured energy contents , which were corrected for st and ard metabolizable energy conversion factors . RESULTS The absolute stated energy contents were not significantly different from the absolute measured energy contents overall ( difference of 10 kcal/portion ; 95 % confidence interval [ CI ] , -15 to 34 kcal/portion ; P = .52 ) ; however , the stated energy contents of individual foods were variable relative to the measured energy contents . Of the 269 food items , 50 ( 19 % ) contained measured energy contents of at least 100 kcal/portion more than the stated energy contents . Of the 10 % of foods with the highest excess energy in the initial sampling , 13 of 17 were available for a second sampling . In the first analysis , these foods contained average measured energy contents of 289 kcal/portion ( 95 % CI , 186 to 392 kcal/portion ) more than the stated energy contents 
    Output:
    
DATA ANALYSIS The results were mixed , but a partial influence of menu labeling on food choices was more frequent than an overall influence or no influence .
Menu labeling  was more effective in cafeterias than in restaurants .
Qualitative information , such as healthy-food symbols and traffic-light labeling , was most effective in promoting healthy eating .
Calorie labeling in menus is not effective to promote healthier food choices .