Groeneveld et al. BMC Public Health 2011, 11:836 http://www.biomedcentral.com/1471-2458/11/836 participants. Nonetheless, the difference in change was only small (-1.9 vs. -1.6 snacks per week), and the higher snack intake by the younger participants at baseline (+0.7) should be noted. Still, whereas younger partici- pants were more likely to change snacking behavior, the older participants might have decided to change other aspects of diet, e.g. meal size, instead. Finding a signifi- cant and equally large effect 6 months after the interven- tion has ended is important, since only long-term changes in behavior will lead to a sustained decrease of CVD risk. The sustained effect on snack intake probably contributed to the statistically significant decrease in body weight of nearly 2 kg after 6 and 12 months, that we described in an earlier publication [32]. Also, the sta- tistically significant improvement in high density lipopro- tein (HDL-) cholesterol at 12 months that we found [32] might partly have been caused by the changes in dietary behavior. The mediating effect of snack intake in the changes in body weight and cholesterol remains to be determined. As to smoking, according to a recent Cochrane review, previous workplace individual counsel- ing interventions aimed at smoking cessation resulted in quit rates between 6 and 21% in the intervention group [33]. As compared to those studies, the short-term quit rate in the intervention group in our study was high. The relatively high frequency and long duration of contacts of the intervention in our study may have contributed to this result. Another factor that may have contributed to the high cessation rate was the fact that most counselors provided information on nicotine replacement therapy to those clients who were motivated to quit. A combination of counseling and medication use increases success rates, as stated by Fiore et al. [34]. Issues related to behavior change Initial positive results at the short term and weakening of the effects at the longer term is a well-known phenom- enon. Habitual behavior and convenience of the ‘original’ behavior may add to this effect. From this study we can conclude that it is vital to find out the determinants of maintenance of ‘new’ lifestyle behavior. As acknowledged by Pritchett et al. (2005), lifestyle modification often results in health improvements, but the challenge is to find out how to avoid relapse to old habits [35]. If we know why some people maintain new behavior and others do not, tools for prevention of relapse may be developed. Possibly, short three-monthly follow-up counseling ses- sions, either face to face or by telephone, may facilitate maintenance of behavior. As shown in the Finnish Dia- betes Prevention Study, this strategy induced behavior change that was sustained at two years [9]. Another issue which may be targeted in future research is the possible additive effect on environmental changes. During our intervention, behavioral determinants were discussed that Page 7 of 9 could be changed by the participant himself, such as atti- tude and self-efficacy. However, behavior change is not only determined by personal factors, but also by the envir- onment [36]. When creating an environment in which the healthy choice is stimulated, such as healthy foods in the company restaurant, or the opportunity to visit a company fitness center [37], behavior change might be facilitated. Environmental changes are difficult to implement for blue-collar workers, who are physically active at work and usually work at different locations, but could be tested among white-collar workers in the construction industry. Changes in the control group Not only the intervention group improved certain lifestyle behaviors, the participants in the control group did so as well. This is not surprising, since they had just received the results of their periodical health screening and were notified of being at risk for CVD. The ‘measurement effect’, as described by Van Sluijs et al. (2006) may also have been causal to the improvements in the control group found after 6 and 12 months [38]. Moreover, the ‘Hawthorne’ effect, i.e. altering behavior because one is aware of being part of an experiment, may have played a role. The substantial increase in PA in the control group may partly have resulted from the brochures they received at baseline. Last, one should keep in mind that persons who are intrinsically motivated to change lifestyle will be more likely to participate in a lifestyle intervention trial than those who are not. Since these mechanisms apply to both the intervention and the control group, the interven- tion effects have probably not been distorted. Limitations and strengths Some limitations of this study should be mentioned. A well-known limitation is over- and underreporting of behavior. Since this ‘misreporting’ occurred in both groups, it has probably not introduced bias, although it may have attenuated the intervention effects. Another drawback is the fact that no validated questionnaire was used for measuring dietary intake. We had two reasons for doing so. First, we wanted the questionnaire to be com- pleted by all participants, and considered the validated food frequency questionnaires too extensive for this pur- pose. Second, we aimed to determine the intervention effects on certain health-related food groups, and not on exact intake of grams or energy. Another limitation is the fact that participants were not blinded. In our study, the chance of contamination between groups was limited, since the workers were employed at more than 400 differ- ent companies, and recruited and randomized individually. A limitation related to the study population may be selec- tive participation and dropout. The participants were older and more likely to smoke than those who did not participate, and the drop-outs were younger and less likely