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Changes in body mass index in Canadians over a five-year period: Results of a prospective, population-based… Hopman, Wilma M; Leroux, Cristine; Berger, Claudie; Joseph, Lawrence; Barr, Susan I; Prior, Jerilynn C; Harrison, Mark; Poliquin, Suzette; Towheed, Tanveer; Anastassiades, Tassos; Goltzman, David Jul 9, 2007

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ralssBioMed CentBMC Public HealthOpen AcceResearch articleChanges in body mass index in Canadians over a five-year period: Results of a prospective, population-based studyWilma M Hopman*1, Cristine Leroux2, Claudie Berger2, Lawrence Joseph3, Susan I Barr4, Jerilynn C Prior5, Mark Harrison6, Suzette Poliquin7, Tanveer Towheed8, Tassos Anastassiades9, David Goltzman10 and the CaMos Research Group7Address: 1Clinical Research Centre, Kingston General Hospital and Department of Community Health and Epidemiology, Queen's University, Kingston, Ontario, Canada, 2CaMos Methods Centre, McGill University, Montreal, Quebec, Canada, 3Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada, 4Human Nutrition, University of British Columbia, Vancouver, British Columbia, Canada, 5Division of Endocrinology, Department of Medicine, University of British Columbia, British Columbia, Canada, 6Human Mobility Research Centre and the Division of Orthopedics, Department of Surgery, Queen's University, Kingston, Ontario, Canada, 7CaMos National Coordinating Centre, McGill University, Montreal, Quebec, Canada, 8Division of Rheumatology, Department of Medicine; Department of Community Health and Epidemiology, Queen's University, Kingston, Ontario, Canada, 9Division of Rheumatology, Department of Medicine, Queen's University, Kingston, Ontario, Canada and 10Department of Medicine, McGill University and Calcium Research Laboratory, Royal Victoria Hospital, Montreal, Quebec, CanadaEmail: Wilma M Hopman* - hopmanw@kgh.kari.net; Cristine Leroux - cristine.leroux@videotron.ca; Claudie Berger - Claudie@osteo1.ri.mgh.mcgill.ca; Lawrence Joseph - lawrence.joseph@mcgill.ca; Susan I Barr - sibarr@interchange.ubc.ca; Jerilynn C Prior - jprior@vanhosp.bc.ca; Mark Harrison - mmh2@post.queensu.ca; Suzette Poliquin - suzette.poliquin@mail.mcgill.ca; Tanveer Towheed - tt5@post.queensu.ca; Tassos Anastassiades - anastass@post.queensu.ca; David Goltzman - david.goltzman@mcgill.ca; the CaMos Research Group - silvia.dumont@mail.mcgill.ca* Corresponding author    AbstractBackground: The initiation of the Canadian Multicentre Osteoporosis Study in 1996, and subsequent follow-upof the cohort 5 years later, provided longitudinal body mass index (BMI) data for a random sample of Canadians.Methods: Height and weight were measured at baseline and 5 years and used to calculate BMI and assign one ofsix weight categories. Multiple imputation was used to adjust for missing weight at year 5. Data were stratified byage and gender. The proportion of participants moving between categories was generated, and multivariable linearregression was used to identify factors associated with weight change.Results: Baseline data were available for 8548 participants, year 5 data for 6721, and year 5 weight was imputedfor 1827 (17.6%). Mean BMI for every age and gender group exceeded healthy weight guidelines. Most remainedwithin their BMI classification over 5 years, but when change occurred, BMI category was more likely to increasethan decrease. Several sociodemographic, lifestyle and clinical characteristics were associated with change.Conclusion: Mean baseline BMI tended to be higher than recommended. Moreover, on average, men under age45 and women under age 55 were gaining approximately 0.45 kilograms (one pound) per year, which leveled offwith increased age and reversed in the oldest age groups. These findings underscore the need for public healthefforts aimed at combating obesity.Published: 9 July 2007BMC Public Health 2007, 7:150 doi:10.1186/1471-2458-7-150Received: 15 November 2006Accepted: 9 July 2007This article is available from: http://www.biomedcentral.com/1471-2458/7/150© 2007 Hopman et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 11(page number not for citation purposes)BMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150BackgroundThe World Health Organization has recommended anupdated classification system for the assessment of bodymass index (BMI, defined as weight in kilograms dividedby height in meters squared) in adults [1]. This systemdefines underweight as a BMI of < 18.5, normal as 18.5–24.99, overweight as 25.0–29.99, and includes threeclasses of obesity for those with a BMI of 30.0–34.99,35.0–39.99, and ≥ 40.0 [1,2]. Given this new classifica-tion, it is helpful to understand changes in BMI over timein the general population.It is widely accepted that given a certain height, there is arange of weight that is associated with good general health[2,3]. Despite this knowledge, there is evidence that theprevalence of being overweight or obese is reaching epi-demic proportions across all age groups, both in devel-oped and developing countries [2,4-11]. The most recentUS data based on measured height and weight found that65.1% of adults over 18 years were overweight [9]. Cana-dian data based on measured heights and weights foundthat 65% of men and 53% of women over 18 years wereoverweight or obese [12], suggesting that the overall USrate is somewhat higher than that of Canadians [9].Being overweight or obese can have a significant impacton health, as these individuals are more likely to sufferfrom a variety of illnesses [1,2,10,11,13], have anincreased risk of mortality [14-16], and use more healthcare resources and disability days [11] than their normalweight peers. In 2000, the cost of obesity in the US wasestimated at $117 billion dollars [17], while the Canadianestimate for 2001 was $4.3 billion US [18]. Being under-weight is also associated with a number of health risks[2,3,19] and an increased risk of mortality [14,16],although considerably less work has gone into assessmentof underweight as compared to overweight individuals[2,3].Few longitudinal studies have assessed changes in BMIover time. Data with measurements at two-year intervalsfrom the Framingham Heart Study suggest that BMI tendsto be stable over time [20]. The Canada Fitness Survey,which had an upper age limit of 69 years at baseline,found that weights tended to be reasonably stable over 7years [21], although all mean seven-year changes were inan upward direction. However, data from the NationalPopulation Health Survey (Statistics Canada), with 8years of follow-up of self-reported BMI, suggest that 32%of those whose weight was normal at baseline becameoverweight, and that almost a quarter of those who hadbeen overweight became obese, while only 10% of thosewho were overweight dropped to the normal categoryThere is a need for a population-based study of measuredBMI in order to examine longitudinal weight change[5,7,13]. The initiation of the Canadian Multicentre Oste-oporosis Study (CaMos) in 1996, and subsequent follow-up of the cohort 5 years later, provided this opportunity.CaMos is not a study of individuals with osteoporosis;rather, it was designed to study the incidence and preva-lence of osteoporosis in a random sample of Canadians25 years of age and older [23]. This allowed us to examinethe number of participants in each of the weight catego-ries at baseline and 5 years, stratified by age and gender,to determine if BMI is increasing and if so, which age andsex groups are at greatest risk.MethodsCaMos is an on-going, prospective cohort study of 9,423non-institutionalized, randomly selected men andwomen aged 25 years and older at baseline, drawn from a50-kilometer radius of nine Canadian cities (St John's,Halifax, Quebec City, Toronto, Hamilton, Kingston, Sas-katoon, Calgary and Vancouver). Baseline assessmentstook place between February 1996 and September 1997,and the 5-year follow-up took place between February2001 and September 2002. All data were obtained bytrained interviewers, who used a questionnaire with goodreproducibility that was designed for the CaMos study.Participants provided written consent.A detailed description of the objectives, methodology andsampling framework for CaMos is available elsewhere[23]. Briefly, households within each region were selectedby random draws of listed telephone numbers, and onerandomly selected household member 25 years of age orolder was asked to participate. Of 22,173 eligible house-holds, 27.5% declined to participate, 30.0% completed ashort questionnaire that provided information about theage, gender and fracture history of the residents, and9,423 (42.5%) went on to participate fully in the study.CaMos was designed to collect epidemiological datarelated to the incidence and prevalence of osteoporosis, soalthough the sampling framework was random, it wasdesigned to include more women than men, and a highernumber of older than younger Canadian residents.Ethics approval was obtained through the Review Boardsof each participating centre. These included MemorialUniversity of Newfoundland Human Investigation Com-mittee (St John's), the Capital Health Research EthicsBoard (Halifax), Comité d'éthique de la recherché cli-nique du Centre Hopitalier Universitaire de Québec(Quebec City), St. Michael's Hospital Research EthicsBoard (Toronto), McMaster University Research EthicsBoard (Hamilton), Queen's University Health SciencesPage 2 of 11(page number not for citation purposes)[22]. and Affiliated Teaching Hospitals Research Ethics Board(Kingston), University of Saskatchewan BiomedicalBMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150Research Ethics Board (Saskatoon), University of CalgaryHealth Research Ethics Board (Calgary), University of Brit-ish Columbia Clinical Research Ethics Board (Vancouver)and the McGill University Health Centre Research EthicsCommittee (Montreal).The majority of participants were scheduled for dual-energy x-ray absorptiometry (DXA) assessment of bonemineral density (BMD) as part of the study protocol, atwhich time both height and weight were measured.Height was measured without shoes, using a wall-mounted stadiometer, ruler on the wall or a measure on aweight scale. Weight was measured in light clothing usinga beam balance or electronic scale. For those who electednot to have the DXA, or for whom it could not be sched-uled, the interviewer measured height and weight with acarpenter's rule and a portable scale. Baseline height andweight were used to calculate the baseline BMI. Five-yearBMI was calculated using the baseline height and theweight at year 5. Baseline height was used to avoid theneed to impute height for those missing height at year 5,as the loss of height over time was expected to be close tozero for the majority of participants. Change in BMI wascalculated as year 5 minus the baseline value, so that pos-itive values would indicate an increase in weight.Multivariable linear regression was used to identify thefactors associated with five year changes in BMI for menand women. Variables were identified on the basis of anextensive literature review, and included sociodemo-graphic characteristics (age, region of Canada, education,annual household income, whether they lived alone andemployment status), clinical characteristics (menopausalstatus, parity, a variety of individual comorbid conditions,and number of comorbid conditions), and other factors(smoking, alcohol use, hours spent walking, hours spentsitting, participation in regular activities, level of pain,level of happiness and perception of general health). Inaddition, since we expected that changes in some of thesevariables could be associated with changes in BMI, changevariables were also examined for menopausal status,comorbidities, smoking, alcohol use, the activity varia-bles, level of pain, level of happiness, and perception ofgeneral health.Univariate associations between all variables and changein BMI were examined to refine the list of predictors iden-tified above, removing any for which there was no evi-dence to support its inclusion. For some, the 95%confidence interval (CI) may have included zero but ifone or both of the upper or lower limits could be of clin-ical interest, the variable was retained, allowing the inves-tigators to see the effects of all variables of potentialtus, parity and alcohol consumption) were retained due towidespread belief that the variable was associated withweight change [22,24-26].Not all participants who provided baseline data partici-pated at year 5, and differences in the characteristicsbetween participants and non-participants could causethe estimates to be biased. For example, this could occurif subjects with certain diseases tended to lose weight ornot participate because they were unwell. Multiple impu-tation [27] was therefore used to at least partially adjustfor possible selection bias for all surviving participantswho did not provide 5-year data. In addition, those whowere pregnant at baseline or year 5 were excluded fromthe analysis, as were those who did not have height and/or weight recorded at baseline.Within the multiple imputation models, linear regressionmodels were fit to predict weight at year 5, using data fromrespondents with complete data at both time points.Models included baseline height and weight, age, andBMD of the femoral neck from year 5 if available, other-wise at baseline. Separate models were developed for menand women within each age group. Covariate data fromthose missing year 5 weights were then entered into themodels to impute the missing weights. Simultaneousregression parameter estimations and multiple imputa-tions were carried out via a Gibbs sampler algorithm asimplemented in WinBugs software (version 1.4, Cam-bridge, Institute of Public Health, MRC Biostatistics Unit,2004).ResultsComplete baseline data were available for 2572 men and5976 women, for a total of 8548 (90.7% of the originalcohort). Height and/or weight were missing for 277 atbaseline, primarily due to scheduling difficulties for theDXA at two sites. Six were pregnant at baseline or at fol-low-up. Six hundred and forty-four had died by the timeof the 5-year follow-up, and although 592 of these hadprovided baseline data (52 of those who died were alsomissing the baseline measurements), their data were notused since 5-year BMI changes were undefined for thesesubjects.At year 5, data were available for 1959 (76.2%) men and4762 (79.7%) women, for a total of 6721, and wereimputed for 1827 (613 men and 1214 women). Of these1827, 764 were still in the cohort but were missing weightat year 5, largely due to scheduling difficulties and one sitethat had not measured weight at the time of the DXA.Another 415 completed a short questionnaire over the tel-ephone. The reasons for loss to follow-up included 265Page 3 of 11(page number not for citation purposes)interest. Three variables not automatically retained in themodel by these a priori considerations (menopausal sta-who could not be contacted, 106 who withdrew consent,89 who were too sick, 114 who had moved away, and 74BMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150with miscellaneous reasons such as cancelled, no time, orno reason given.Those without complete year 5 were represented in all cat-egories of weight. For men, 33.3% of those in the under-weight group and 35.0% of those in the obese class IIIgroup at baseline were missing year 5 data. For otherweight categories, the proportions with incomplete year 5data ranged from 21.4% (overweight) to 26.3% (obeseclass I). Among women, the proportions with incompletedata ranged from 19.1% of those in the normal weightcategory to 27.8% of those in obese class III. For the othercategories, the proportions were very similar, rangingfrom 20.5% (overweight) to 21.8 (obese class II), suggest-ing that there was no bias due to greater loss to follow-upwithin certain weight categories.Figure 1 contains the mean baseline BMI for men andwomen across 10-year age stratifications, along with theassociated 95% confidence intervals (CI). The mean BMIfor every age group for both genders exceeded the healthyweight guidelines of BMI below 251,2. The lower limit ofthe 95% CI was less than 25 for only one group (women25–34 years), and was exactly 25.0 for women aged 35–44 years. This figure also contains the mean 5-year changein BMI with the 95% CI for the age and gender groups.The increases in BMI were much larger for men between25 and 44 years and women between 25 and 54 years thanin the older groups, in which the BMI tended to decrease.Tables 1 (men) and 2 (women) contain the weight classi-fications at baseline by age group, along with the Year 5values (actual and imputed). For men, with the exceptionof the baseline weight for the 25–34 year age group andthe Year 5 observed and imputation adjusted values forthe 75+ age group, the majority of values fell into the over-weight category. For women, the majority of values werein the normal category for the two youngest groups andthe 75+ age group. For those aged 45–74 years, the per-centages in the normal weight and overweight categorieswere very close. A small majority of those in the 45–54year age group were in the normal weight category, whilean equally small majority of those aged 55–74 years werein the overweight category.Tables 3 (men) and 4 (women) contain the percentagesstaying within a certain BMI category or moving intoanother group, by age. For example, a man in his early40's and of normal weight at baseline has a 62.7% chanceof staying within his weight category, a 0.5% chance ofdropping into the underweight category and a 34.4%chance of moving into the overweight category after 5years. The largest probabilities are within the same weightcategory at baseline and at year 5, suggesting that peopleTable 1: Weight classification at baseline and year five (including imputed) for men. Values are expressed as frequencies and percent of age group totalBaseline Age Time Sample Size* Underweight Normal Weight Overweight Obese Class I Obese Class II Obese Class III25 – 34 BaselineYear 51871872 (1.1)1 (0.5)85 (45.5)70 (37.4)78 (41.7)82 (43.9)18 (9.3)25 (13.4)3 (1.6)7 (3.7)1 (0.5)2 (1.1)35 – 44 BaselineYear 52052052 (1.0)1 (0.5)70 (34.2)53 (25.9)97 (47.3)106 (51.7)28 (13.7)34 (16.6)5 (2.4)6 (2.9)3 (1.5)5 (2.4)45 – 54 BaselineYear 55645651 (0.2)3 (0.5)157 (27.8)145 (25.7)288 (51.1)277 (49.0)89 (15.8)104 (18.4)25 (4.4)31 (5.5)4 (0.7)5 (0.9)55 – 64 BaselineYear 56096082 (0.3)2 (0.3)135 (22.2)132 (21.7)317 (52.1)308 (50.7)125 (20.5)129 (21.2)26 (4.3)33 (5.4)4 (0.7)4(0.7)65 – 74 BaselineYear 57057053 (0.4)3 (0.4)197 (27.9)220 (31.2)361 (51.2)344 (48.8)127 (18.0)117 (16.6)11 (1.6)17 (2.4)6 (0.9)4 (0.6)75 + BaselineYear 53023022 (0.7)6 (2.0)117 (38.7)137 (45.4)143 (47.4)116 (38.4)32 (10.6)36 (11.9)6 (2.0)5 (1.7)2 (0.7)2 (0.7)* Baseline and year 5 values are not always identical due to rounding in the imputation process.Baseline body mass index (BMI) and 5-year change in BMI, by age group and genderFigu e 1Baseline body mass index (BMI) and 5-year change in BMI, by age group and gender. Numbers on the left axis represent body mass index (BMI). Solid squares represent the mean baseline BMI, and the error bars represent the 95% confidence interval (CI). Numbers on the right axis represent mean change in BMI. Open triangles represent the mean 5-year change in BMI, and the error bars represent the 95% CI.2424.52525.52626.52727.52828.52925-34 35-44 45-54 55-64 65-74 75+Age Group+1.52424.52525.52626.52727.52828.52925-34 35-44 45-54 55-64 65-74 75+Age Group+1.5-1-0.5  0+0.5+1 +1  +0.5   0-0.5-1MEN WOMENPage 4 of 11(page number not for citation purposes)Underweight = BMI<18; Normal weight = BMI 18.5–24.99; Overweight = BMI 25.0–29.99; Obese Class I = BMI 30.0–34.99; Obese Class II = BMI 35.0–39.99; Obese Class III = BMI ≥ 40.0BMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150are most likely to remain within their BMI classifications.The major exceptions to this are in underweight men inmost age groups (Table 3), where weight gain into thenormal range generally occurred. Furthermore, in general,the data suggest that if there is a change, there is a fargreater probability of increasing by a category comparedto decreasing by a category in the younger age groups; thisreverses for the older age groups and at higher levels ofweight.The results of movement from one BMI category toanother over 5 years are very similar for women (Table 4).A woman in her early 40's with a normal baseline weighthas an 82.7% chance of staying in that category, a 2.1%chance of dropping into the underweight group and a13.6% chance of moving into the overweight category.However, with increasing age and/or for those in higherBMI categories, there is an increased likelihood of drop-ping by a category relative to increasing by a category.Table 5 contains the results of the regression modeling.Thirteen variables were retained in the model for women,while 11 were retained for men. Eight of these (7 for men)were measured at baseline and 5 (4 for men) were basedon change between baseline and follow-up. The modelsaccounted for just under 9% of the total variation in out-come, so much of the variance is unexplained by our cov-ariates. In general, variables associated with an increase inweight included household income greater than $20,000,and education levels lower than a university degree. Allregions of Canada were associated with less gain, as com-pared to the reference category (Saskatoon, representingCentral Canada). All age categories for both genders wereassociated with weight gain when compared to the refer-Current smokers and those who had never smoked tendedto gain less weight as compared to those who had quitsmoking, although only one of the four comparisonsattained clinical importance in that the 95% CI did notinclude zero. Higher alcohol consumption was associatedwith small declines for both men and women, but theresults were inconclusive for both. Those who felt lesshappy or whose happiness assessment stayed about thesame, also saw less gain as compared to those who indi-cated that their level of happiness had improved,although this result was inconclusive for men. Some cate-gories of changes in participation in regular activity,change in number of sedentary hours, and perception ofoverall health were also associated with increases in BMIfor either men or women, although not always in theexpected direction. For example, those who indicated thattheir number of sedentary hours was quite low still saw asmall increase in the parameter estimates.For women, the association between number of live birthsand weight change was virtually non-existent. Finally,after adjusting for age, the effect of menopause was alsoinconclusive, although it is of clinical interest that thosewho had not yet become menopausal, or who hadbecome menopausal recently, saw small declines as com-pared to those who were already menopausal at baseline.DiscussionThese results add to the growing body of literature sug-gesting that the prevalence of overweight and obesity isincreasing. The mean baseline BMI exceeded 25.0 forevery age and gender category studied, ranging from 25.6(women aged 35–44) to 27.7 (men aged 55–64). Themean change over 5 years does not appear large at faceTable 2: Weight classification at baseline and year five (including imputed) for women. Values are expressed as frequencies and percent of age group totalBaseline Age Time Sample Size* Underweight Normal Weight Overweight Obese Class I Obese Class II Obese Class III25 – 34 BaselineYear 51871885 (2.7)4 (2.1)101 (54.0)84 (44.7)50 (26.7)56 (29.8)15 (8.0)25 (13.3)10 (5.4)11 (5.9)6 (3.2)8 (4.3)35 – 44 BaselineYear 52782773 (1.1)3 (1.1)155 (55.8)140 (50.5)70 (25.2)66 (23.8)34 (12.2)44 (15.9)7 (2.5)16 (5.8)9 (3.2)8 (2.9)45 – 54 BaselineYear 51082108310 (0.9)12 (1.1)433 (40.0)382 (35.3)377 (34.8)382 (35.3)158 (14.6)189 (17.5)81 (7.5)79 (7.3)23 (2.1)39 (3.6)55 – 64 BaselineYear 51564156219 (1.2)28 (1.8)526 (33.6)469 (30.0)629 (40.2)623 (39.9)269 (17.2)315 (20.2)87 (5.6)92 (5.9)34 (2.2)35 (2.2)65 – 74 BaselineYear 51945194037 (1.9)56 (2.9)680 (35.0)692 (35.7)735 (37.8)713 (36.8)362 (18.6)352 (18.1)99 (5.1)99 (5.1)32 (1.7)28 (1.4)75 + BaselineYear 592091824 (2.6)49 (5.3)367 (39.9)414 (45.1)351 (38.2)317 (34.5)142 (15.4)113 (12.3)32 (3.5)22 (2.4)4 (0.4)3 (0.3)* Baseline and year 5 values are not always identical due to rounding in the imputation process.Underweight = BMI<18; Normal weight = BMI 18.5–24.99; Overweight = BMI 25.0–29.99; Obese Class I = BMI 30.0–34.99; Obese Class II = BMI 35.0–39.99; Obese Class III = BMI ≥ 40.0Page 5 of 11(page number not for citation purposes)ence category of age 75+, as already demonstrated in Fig-ure 1.value, ranging from an increase of 1.07 for the youngestgroup of men to a drop of 0.96 for the oldest group ofBMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150women. However, if one adds the mean change to themean baseline value, all values remain greater than 25,and the values increase for all but the two oldest agegroups, for both men and women. In view of the fact thatthe mean BMI exceeded 25 even in the youngest agegroups in both men and women (Figure 1), it seems likelythat excess weight gain has its inception before age 25.Weight regulation depends on a balance between energyinput to the hypothalamus and brain stem controls foodintake, and peripheral circulating adipostat factors andgut hormones are highly important in appetite controland food intake regulation [28]. The results presented inTables 1 and 2 suggest that the number within the BMIcategories remains relatively stable despite the trendtowards small annual increases as seen in Figure 1, whichis consistent with previous research [20,21] and the well-developed homeostatic role for weight regulation [28].Table 3: Percentage of men staying within baseline weight category versus switching to another categoryAge at baseline(years)Category at BaselineUnderweight At Year 5 (95% CI)Normal Weight At Year 5 (95% CI)Overweight At Year 5 (95% CI)Obese Class I At Year 5 (95% CI)Obese Class II At year 5 (95% CI)Obese Class III At Year 5 (95% CI)25 – 34 Underweight 21.2 (0.0–77.3) 60.5 (8.6–100.0) 3.9 (0.0–25.0) 3.6 (0.0–22.1) 3.4 (0.0–21.8) 7.4 (0.0–39.3)Normal Weight 1.2 (0.0–4.5) 67.9 (57.0–78.7) 30.3 (19.9–41.0) 0.2 (0.0–1.3) 0.1 (0.0–0.6) 0.2 (0.0–1.2)Overweight 0.1 (0.0–0.7) 13.1 (5.8–21.4) 71.1 (59.4–82.2) 15.2 (6.3–24.5) 0.2 (0.0–1.4) 0.2 (0.0–1.3)Obese Class I 0.5 (0.0–3.1) 0.5 (0.0–3.3) 3.5 (0.0–15.6) 68.2 (44.0–90.7) 26.0 (5.2–48.3) 1.2 (0.0–6.2)Obese Class II 2.6 (0.0–16.2) 2.7 (0.0–16.3) 2.7 (0.0–17.1) 5.9 (0.0–36.6) 50.2 (5.8–94.9) 35.9 (0.1–80.0)Obese Class III 5.8 (0.0–37.5) 5.7 (0.0–36.6) 6.0 (0.0–39.8) 5.8 (0.0–38.4) 6.1 (0.0–38.5) 70.6 (14.4–100.0)35 – 44 Underweight 18.1 (0.0–74.9) 62.9 (9.5–100.0) 4.2 (0.0–27.2) 3.7 (0.0–24.1) 3.7 (0.0–23.1) 7.3 (0.0–37.1)Normal Weight 0.5 (0.0–2.8) 62.7 (49.6–76.5) 34.4 (21.3–47.9) 0.6 (0.0–3.0) 1.6 (0.0–4.5) 0.3 (0.0–1.5)Overweight 0.1 (0.0–0.6) 7.3 (2.0–13.5) 79.1 (69.6–87.9) 13.0 (6.0–20.9) 0.2 (0.0–1.0) 0.2 (0.0–1.1)Obese Class I 0.3 (0.0–2.1) 0.4 (0.0–2.4) 17.2 (3.5–32.9) 73.1 (54.2–90.7) 8.3 (0.0–20.0) 0.7 (0.0–3.7)Obese Class II 1.8 (0.0–11.0) 1.8 (0.0–10.8) 1.8 (0.0–10.7) 2.3 (0.0–14.3) 49.3 (11.3–87.8) 43.0 (6.3–81.1)Obese Class III 2.6 (0.0–16.5) 2.7 (0.0–16.7) 2.9 (0.0–17.9) 2.7 (0.0–16.9) 8.1 (0.0–46.4) 81.0 (37.0–100.0)45 – 54 Underweight 36.3 (0.0–98.2) 34.3 (0.0–98.1) 5.9 (0.0–38.7) 5.7 (0.0–37.6) 6.0 (0.0–38.3) 11.8 (0.0–58.1)Normal Weight 1.4 (0.0–3.5) 73.9 (66.1–81.4) 23.9 (16.7–31.5) 0.7 (0.0–2.1) 0.1 (0.0–0.4) 0.1 (0.0–0.6)Overweight 0.0 (0.0–0.2) 9.9 (6.1–13.7) 76.6 (71.4–82.0) 13.0 (8.8–17.2) 0.4 (0.0–1.1) 0.1 (0.0–0.4)Obese Class I 0.1 (0.0–0.7) 0.1 (0.0–0.7) 19.8 (11.5–29.4) 68.7 (57.9–79.1) 11.1 (4.4–18.3) 0.2 (0.0–1.1)Obese Class II 0.4 (0.0–2.3) 0.4 (0.0–2.3) 4.3 (0.0–12.1) 12.4 (0.7–26.1) 72.1 (53.9–90.3) 10.4 (0.9–23.0)Obese Class III 2.1 (0.0–13.4) 2.1 (0.0–13.2) 2.1 (0.0–13.3) 2.2 (0.0–13.6) 34.5 (0.0–77.3) 56.9 (15.4–99.0)55 – 64 Underweight 40.7 (0.3–85.2) 40.9 (0.1–85.6) 3.8 (0.0–23.8) 3.7 (0.0–23.2) 3.6 (0.0–23.2) 7.4 (0.0–39.3)Normal Weight 0.2 (0.0–1.4) 74.0 (66.2–81.6) 24.7 (17.4–32.6) 0.9 (0.0–2.5) 0.1 (0.0–0.5) 0.2 (0.0–0.8)Overweight 0.0 (0.0–0.2) 9.7 (6.3–13.5) 78.0 (72.9–82.9) 12.2 (8.4–16.1) 0.0 (0.0–0.3) 0.1 (0.0–0.3)Obese Class I 0.9 (0.0–2.5) 0.1 (0.0–0.6) 21.5 (13.6–29.5) 67.1 (58.0–76.1) 10.3 (5.0–16.4) 0.2 (0.0–0.9)Obese Class II 0.4 (0.0–2.3) 0.4 (0.0–2.2) 0.5 (0.0–2.6) 16.0 (2.8–30.5) 72.8 (54.4–89.5) 10.0 (0.6–21.7)Obese Class III 2.2 (0.0–13.4) 2.1 (0.0–12.8) 2.1 (0.0–12.7) 23.8 (0.0–59.2) 29.3 (0.0–76.9) 40.5 (0.0–85.5)65 – 74 Underweight 29.6 (0.0–69.7) 57.1 (16.4–96.5) 2.5 (0.0–15.7) 2.8 (0.0–17.1) 2.6 (0.0–16.4) 5.4 (0.0–27.6)Normal Weight 0.5 (0.0–1.8) 86.2 (80.7–91.5) 13.1 (8.0–18.5) 0.1 (0.0–0.4) 0.1 (0.0–0.3) 0.1 (0.0–0.5)Overweight 0.3 (0.0–0.9) 13.1 (9.3–16.8) 80.1 (75.4–84.4) 6.5 (3.7–9.2) 0.0 (0.0–0.2) 0.1 (0.0–0.3)Obese Class I 0.1 (0.0–0.5) 0.9 (0.0–2.6) 21.3 (13.8–29.4) 71.3 (62.5–79.7) 6.2 (2.2–11.0) 0.2 (0.0–0.8)Obese Class II 0.8 (0.0–5.0) 0.9 (0.0–5.0) 9.5 (0.0–26.1) 24.2 (2.3–49.6) 62.3 (34.8–90.6) 2.3 (0.0–12.2)Obese Class III 1.5 (0.0–8.6) 1.5 (0.0–9.2) 1.5 (0.0–9.4) 1.5 (0.0–8.7) 31.4 (3.0–63.4) 62.7 (29.2–93.9)75 + Underweight 62.6 (9.0–100.0) 18.8 (0.0–74.9) 3.8 (0.0–23.6) 3.6 (0.0–22.9) 3.8 (0.0–23.4) 7.4 (0.0–38.4)Normal Weight 4.0 (0.2–8.5) 87.3 (80.0–94.3) 7.5 (2.2–13.4) 0.9 (0.0–2.6) 0.1 (0.0–0.5) 0.2 (0.0–0.9)Overweight 0.1 (0.0–0.4) 24.3 (16.5–32.3) 68.7 (60.0–77.0) 6.7 (2.4–11.3) 0.1 (0.0–0.4) 0.1 (0.0–0.8)Obese Class I 0.3 (0.0–1.7) 0.4 (0.0–2.2) 23.2 (7.6–38.6) 70.1 (52.6–86.6) 5.4 (0.0–14.4) 0.6 (0.0–3.2)Obese Class II 1.5 (0.0–9.1) 1.5 (0.0–8.8) 16.5 (0.0–43.2) 35.5 (0.1–74.4) 40.5 (0.0–78.0) 4.5 (0.0–23.1)Obese Class III 3.7 (0.0–23.7) 3.5 (0.0–22.5) 3.8 (0.0–24.3) 3.7 (0.0–23.7) 18.2 (0.0–74.8) 67.0 (12.2–100.0)CI = Confidence IntervalPage 6 of 11(page number not for citation purposes)intake via food and energy expenditure. Evolving knowl-edge indicates that complex neuronal and hormonalThe results in Tables 3 and 4 suggest that the highest per-centage of those studied will remain within their originalBMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150weight classification after 5 years. Only in men who wereinitially underweight was there a tendency to increase BMIinto the normal range. This observation may be consistentwith the thesis that the complex neurohormonal regula-tion of weight regulation may have evolved primarily toprevent starvation [28].In considering the relative stability of the weight catego-ries despite evidence of increasing weight over time, oneexample, a woman at the average Canadian height of 163centimetres (cm) would weigh 49.1 kg for a BMI of 18.50and 66.3 kg for a BMI of 25.0, representing an increase of17.2 kg (37.9 pounds) to move into the overweight cate-gory if starting at the lowest point in the normal weightcategory. To do the same, a man at the average Canadianheight of 178 cm would weigh 58.5 kg for a BMI of 18.50and 79.1 kg for a BMI of 25.0, representing an increase of20.6 kg (45.4 pounds). In these two examples, to move upTable 4: Percentage of women staying within baseline weight category versus switching to another categoryAge at baseline(years)Category at BaselineUnderweight At Year 5 (95% CI)Normal Weight At Year 5 (95% CI)Overweight At Year 5 (95% CI)Obese Class I At Year 5 (95% CI)Obese Class II At year 5 (95% CI)Obese Class III At Year 5 (95% CI)25 – 34 Underweight 54.4 (18.1–89.8) 36.8 (3.4–72.2) 1.7 (0.0–10.4) 1.8 (0.0–11.3) 1.8 (0.0–10.7) 3.5 (0.0–18.2)Normal Weight 1.0 (0.0–3.7) 75.5 (65.9–84.4) 22.8 (13.7–31.8) 0.4 (0.0–2.0) 0.1 (0.0–0.5) 0.2 (0.0–1.0)Overweight 0.2 (0.0–1.1) 10.5 (2.6–19.7) 56.9 (41.5–71.4) 29.5 (16.2–43.2) 2.5 (0.0–7.0) 0.4 (0.0–2.0)Obese Class I 0.6 (0.0–3.5) 0.7 (0.0–4.2) 24.5 (4.5–47.1) 51.6 (24.9–75.8) 8.6 (0.0–23.7) 14.0 (0.7–30.7)Obese Class II 0.9 (0.0–5.5) 1.0 (0.0–5.9) 1.0 (0.0–5.6) 14.6 (0.0–37.7) 57.7 (29.0–88.6) 24.8 (1.8–50.2)Obese Class III 1.5 (0.0–9.2) 1.5 (0.0–9.1) 1.5 (0.0–9.0) 1.6 (0.0–9.3) 34.5 (3.1–68.5) 59.3 (23.8–92.3)35 – 44 Underweight 2.5 (0.0–15.5) 84.1 (48.6–100.0) 2.6 (0.0–15.4) 2.7 (0.0–16.5) 2.7 (0.0–16.9) 5.4 (0.0–28.3)Normal Weight 2.1 (0.1–4.6) 82.7 (76.3–89.1) 13.6 (7.8–19.3) 1.4 (0.1–3.4) 0.1 (0.0–0.4) 0.1 (0.0–0.7)Overweight 0.2 (0.0–0.9) 12.5 (4.6–21.4) 58.3 (45.2–70.6) 28.5 (17.8–40.4) 0.3 (0.0–1.9) 0.3 (0.0–1.6)Obese Class I 0.3 (0.0–1.6) 0.3 (0.0–2.1) 12.5 (2.1–24.9) 59.8 (42.0–77.6) 26.2 (10.9–42.8) 0.9 (0.0–4.5)Obese Class II 1.3 (0.0–7.6) 1.4 (0.0–8.3) 1.4 (0.0–8.0) 20.9 (0.0–52.3) 58.9 (22.4–96.4) 16.3 (0.0–47.8)Obese Class III 1.0 (0.0–5.8) 1.0 (0.0–5.9) 1.1 (0.0–6.5) 1.0 (0.0–6.3) 24.3 (0.9–50.3) 71.6 (43.4–96.5)45 – 54 Underweight 56.9 (28.8–84.3) 38.5 (12.3–65.9) 0.9 (0.0–5.6) 1.0 (0.0–6.1) 0.9 (0.0–5.1) 1.9 (0.0–9.9)Normal Weight 1.4 (0.3–2.7) 78.7 (74.5–82.8) 19.3 (15.3–23.1) 0.6 (0.0–1.3) 0.0 (0.0–0.1) 0.0 (0.0–0.2)Overweight 0.0 (0.0–0.2) 9.7 (6.6–13.2) 68.2 (62.8–73.2) 20.7 (16.4–25.3) 1.4 (0.4–2.7) 0.1 (0.0–0.3)Obese Class I 0.1 (0.0–0.4) 0.7 (0.0–2.1) 21.3 (14.5–28.4) 61.3 (53.2–69.5) 15.8 (9.7–22.0) 0.8 (0.0–2.2)Obese Class II 0.1 (0.0–0.7) 0.1 (0.0–0.7) 7.5 (2.6–13.4) 14.4 (6.4–22.8) 54.7 (43.0–65.7) 23.1 (14.0–32.6)Obese Class III 0.4 (0.0–2.6) 0.4 (0.0–2.4) 0.4 (0.0–2.6) 0.6 (0.0–3.7) 17.8 (1.8–35.4) 80.4 (62.3–96.8)55 – 64 Underweight 51.2 (28.4–74.2) 46.3 (23.5–68.9) 0.5 (0.0–3.0) 0.5 (0.0–2.9) 0.5 (0.0–3.1) 1.0 (0.0–5.3)Normal Weight 3.0 (1.5–4.7) 73.9 (69.8–77.7) 22.4 (18.7–26.2) 0.6 (0.1–1.4) 0.0 (0.0–0.1) 0.0 (0.0–0.2)Overweight 0.3 (0.0–0.8) 11.1 (8.4–13.8) 71.5 (67.6–75.3) 16.9 (13.9–20.2) 0.2 (0.0–0.6) 0.0 (0.0–0.2)Obese Class I 0.0 (0.0–0.2) 0.8 (0.0–1.9) 19.5 (14.5–24.7) 68.1 (62.0–74.1) 10.7 (6.8–14.9) 0.8 (0.0–1.9)Obese Class II 0.1 (0.0–0.7) 1.2 (0.0–3.7) 2.5 (0.1–5.8) 23.4 (14.3–33.5) 59.1 (47.8–70.0) 13.6 (6.3–21.2)Obese Class III 0.3 (0.0–1.6) 0.3 (0.0–1.7) 0.3 (0.0–1.7) 6.1 (0.4–14.1) 31.0 (15.7–46.6) 62.0 (45.3–77.5)65 – 74 Underweight 73.2 (58.8–87.6) 25.5 (12.2–40.7) 0.3 (0.0–1.6) 0.3 (0.0–1.6) 0.3 (0.0–1.6) 0.5 (0.0–2.7)Normal Weight 3.8 (2.2–5.4) 82.1 (78.9–85.2) 13.3 (10.6–16.1) 0.6 (0.1–1.3) 0.2 (0.0–0.5) 0.0 (0.0–0.2)Overweight 0.4 (0.0–0.9) 16.7 (13.8–19.5) 73.1 (69.5–76.6) 9.5 (7.1–11.8) 0.3 (0.0–0.7) 0.0 (0.0–0.1)Obese Class I 0.0 (0.0–0.2) 1.2 (0.2–2.3) 21.8 (17.3–26.6) 69.6 (64.5–74.7) 6.7 (4.1–9.6) 0.6 (0.0–1.4)Obese Class II 0.1 (0.0–0.6) 0.1 (0.0–0.5) 7.2 (2.5–12.1) 26.4 (16.8–35.5) 61.9 (51.0–71.6) 4.3 (0.7–8.8)Obese Class III 0.3 (0.0–1.8) 0.3 (0.0–2.0) 0.3 (0.0–1.9) 0.5 (0.0–2.9) 30.6 (14.3–47.4) 68.0 (50.5–83.9)75 + Underweight 76.4 (55.5–94.3) 21.6 (2.9–40.8) 0.4 (0.0–2.6) 0.4 (0.0–2.2) 0.4 (0.0–2.6) 0.8 (0.0–4.2)Normal Weight 8.2 (5.1–11.7) 82.0 (77.4–86.5) 9.6 (6.4–13.1) 0.1 (0.0–0.5) 0.0 (0.0–0.2) 0.1 (0.0–0.3)Overweight 0.1 (0.0–0.4) 29.9 (24.3–35.2) 63.1 (57.2–68.8) 6.8 (4.1–9.7) 0.0 (0.0–0.2) 0.1 (0.0–0.3)Obese Class I 0.1 (0.0–0.4) 2.1 (0.1–4.8) 41.1 (31.7–49.8) 53.8 (44.6–63.0) 2.7 (0.4–5.7) 0.1 (0.0–0.7)Obese Class II 0.3 (0.0–1.9) 0.3 (0.0–1.7) 7.1 (0.4–16.4) 39.7 (21.9–59.1) 50.8 (32.2–70.1) 1.8 (0.0–8.0)Obese Class III 2.1 (0.0–12.2) 2.2 (0.0–13.2) 2.1 (0.0–12.7) 3.4 (0.0–21.3) 27.0 (0.0–70.9) 63.3 (20.2–100.0)CI = Confidence IntervalPage 7 of 11(page number not for citation purposes)must bear in mind that a person can stay within theirweight category despite a significant weight gain. Forby one BMI point, the woman would have to gain 2.6 kg(5.7 pounds), while the man would have to gain 3.1 kgBMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150Table 5: Multivariable linear regression models for change in BMI for women and menVariable Women Parameter Estimates and 95% Confidence IntervalsMen Parameter Estimates and 95% Confidence IntervalsIntercept 3.6 (2.8, 4.3) 1.2 (0.5, 2.0)Region of Canada (Reference = Central)East -0.82 (-1.09, -0.55) -0.66 (-0.99, -0.32)Quebec -0.50 (-0.78, -0.22) -0.54 (-0.88, -0.20)Ontario -0.39 (-0.61, -0.16) -0.35 (-0.62, -0.08)West -0.24 (-0.47, -0.00) -0.45 (-0.73, -0.16)Age at baseline (Reference = 75+)25–34 1.97 (0.23, 3.71) 1.55 (1.10, 2.00)35–44 2.13 (1.59, 2.68) 1.19 (0.76, 1.63)45–54 1.64 (1.34, 1.94) 0.75 (0.40, 1.10)55–64 1.11 (0.88, 1.35) 0.76 (0.43, 1.09)65–74 0.69 (0.46, 0.92) 0.41 (0.09, 0.73)Annual Household Income (Reference = < $20,000)$21,000–$40,000 0.13 (-0.07, 0.33) 0.28 (-0.04, 0.60)$41,000–$60,000 0.08 (-0.16, 0.32) 0.44 (0.10, 0.78)$61,000–$80,000 0.44 (0.13, 0.74) 0.36 (-0.01, 0.74)> $80,000 0.18 (-0.12, 0.48) 0.65 (0.27, 1.02)Education (Reference = University degree(s))< High school diploma 0.31 (0.06, 0.55) 0.12 (-0.14, 0.39)High school or Trade school diploma 0.25 (0.02, 0.48) 0.32 (0.07, 0.56)Some University, or University certificate/diploma0.36 (0.08, 0.64) 0.10 (-0.20, 0.40)Average level of pain, past week (reference = no pain) Mild to moderate, prevents no activities 0.19 (0.01, 0.37) 0.11 (-0.11, 0.33)Moderate, prevents a few activities 0.08 (-0.12, 0.28) -0.12 (-0.40, 0.16)Moderate to severe, prevents some activities 0.34 (0.06, 0.63) 0.02 (-0.39, 0.43)Severe pain that prevents most activities 0.00 (-0.66, 0.67) 0.04 (-0.76, 0.85)Smoking status (reference = quit smoking)Current smoker -0.49 (-0.74, -0.24) -0.18 (-0.46, 0.09)Never smoked -0.12 (-0.27; 0.04) -0.01 (-0.21, 0.19)Number of live births -0.02 (-0.06, 0.02) n/aAlcohol/week (Reference = None)1 to 6 (WOMEN) or 1 to 13 (MEN) 0.06 (-0.10, 0.21) -0.09 (-0.30, 0.13)7 or more (WOMEN) or 14 or more (MEN) -0.16 (-0.39, 0.07) -0.25 (-0.55, 0.05)Menopausal status (reference = menopaused at baseline)Not menopaused -0.16 (-0.50, 0.17) n/aMenopaused in the past 5 years -0.15 (-0.49, 0.20)Change, participation in regular activity (reference = did not, do now)Did not, and do not now (no, no) 0.28 (0.05, 0.52) 0.42 (0.12, 0.71)Did, but do not anymore (yes, no) 0.28 (0.04, 0.53) 0.27 (-0.04, 0.58)Did and still do (yes, yes) 0.24 (0.01, 0.47) 0.17 (-0.11, 0.45)Change, number of sedentary hours (reference = high to low)Low to high 0.32 (0.09, 0.56) 0.52 (0.22, 0.83)High at baseline, stayed high 0.13 (-0.08, 0.33) 0.23 (-0.03, 0.49)Low at baseline, stayed low 0.17 (-0.04, 0.38) 0.38 (0.13, 0.64)Page 8 of 11(page number not for citation purposes)Our data did suggest a moderate effect of region, with thecentral region most likely to show an increase in BMI. Oneprevious Canadian study noted almost no effect of region[22], but a study of region in the USA did note higher ratesof obesity in the South Central and Northeast Centralregions as compared to New England, the Atlantic regions,Mountain and Pacific regions [17]. Younger participantsgained more weight than older participants, and theimpact of menopause was small but in the expected direc-tion [24], with more weight gain in those who werealready menopausal at baseline.Current smokers had less gain than those who had neverlevel of happiness had improved. Finally, a decrease inself-rated health, which has been associated with higherBMI in other research [30], was associated with increasedBMI in women but not in men. For men, increase in BMItended to be associated with a perception of improvedgeneral health.One limitation to this study was the loss to follow-up, asonly 90.7% of the baseline sample could be included evenwhen using multiple imputation. Moreover, multipleimputation also has assumptions and limitations. Forexample, the technique assumes that the baseline datawere sufficiently detailed to predict year 5 weights, andBMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150Change in how happy they usually feel (reference = improved)Decline in how happy they usually feel -0.37 (-0.65, -0.10) -0.33 (-0.66, 0.01)Feel about the same -0.23 (-0.44, -0.02) -0.09 (-0.35, 0.17)Perception of general health (reference = poor, and stayed that way)High, dropped to poor 0.38 (0.15, 0.60) 0.13 (-0.17, 0.43)Poor, went to high 0.02 (-0.22, 0.27) 0.29 (0.04, 0.53)Perception of health stayed high 0.12 (-0.06, 0.31) 0.11 (-0.12, 0.33)The first eight variables are based on baseline data; the remaining 5 represent change between baseline and the 5-year follow-up.Table 5: Multivariable linear regression models for change in BMI for women and men (Continued)(6.8 pounds). Given the results in Figure 1, this suggeststhat men under age 45 and women under age 55 may beputting on approximately 0.45 kg or one pound per year,which levels off in the middle-aged groups and begins toreverse in the oldest age groups.The regression models suggest that there are factors asso-ciated with change in BMI, but much of the varianceremains unexplained, and the models must be interpretedwith caution due to the wide confidence intervals associ-ated with many of the estimates. Nevertheless, the find-ings tend to be consistent with previous research,although there are some notable exceptions. For example,several studies have noted an association betweenincreased weight and a variety of comorbid conditions[3,11] as well as the number of comorbid conditions [11],which was not observed in the current study. This could inpart be because comorbidities may have been less severethan is typical for many diseases, as very sick subjectstended not to participate or to drop out of the cohort.Moreover, previously noted associations betweenincreased weight and lower income [10,22] were notfound. Activity restriction also had little effect, despiteprevious research to the contrary [22], but that may bebecause other variables such as change in sedentary hoursand change in participation in regular activity are also inour models. Level of pain also produced little in the wayof interesting results, other than for women who notedmoderate to severe pain that prevented some activities.which is consistent with other research [5,22], while theresults for alcohol intake suggest that higher levels inintake are associated with small declines in weight, whichdiffers from previous findings [22]. However, it should benoted that alcohol consumption in this sample was rela-tively low, with a median of 0.2 drinks per week for thewomen and 2.0 per week for the men.All education levels below the University level were asso-ciated with more weight gain, which was more pro-nounced for women and consistent with past findings[5,10,18]. Number of children appeared to have littleeffect on weight change for women, which has also beennoted by others [26], despite widely held beliefs to thecontrary [25,26]. However, this may be because manyrespondents had their children long before the baselinemeasurement, and parity may therefore have contributedto baseline weight rather than change in weight.The ability to assess the effect of behaviour change, and itsimpact on change in weight, is one of the strengths of thisstudy. Compared to those who did not participate inphysical activity but do now, all other groups showedsmall BMI gains, supporting other research that demon-strated a healthy effect of increased activity on BMI[10,29]. Moreover, compared to those who went from ahigh to a low number of sedentary hours, the other groupsshowed small gains in BMI. Those who indicated thattheir level of happiness had declined or stayed the samesaw small decreases in BMI compared with those whosePage 9 of 11(page number not for citation purposes)smoked or had recently quit, particularly for women, that, given the information available for predicting miss-BMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/150ing year 5 weights, those who participated are similar atbaseline to those who did not participate [31]. It is possi-ble that despite adjusting for baseline characteristics, thenon-respondents at year 5 were different from those withcomplete data. However, inclusion of the imputed datawas considered to be preferable to simply basing all esti-mates on those with complete data at both time points, asat least some bias adjustment is preferable to none.Caution must be used when interpreting any results basedon BMI data. While BMI is a commonly used indicator ofweight category, it is a composite measure that is unableto distinguish between fat and lean tissue [20]. Moreover,the BMI cut-points for overweight and obese subjects mayneed to be adjusted for certain non-white people, as wellas the elderly [2,10]. Finally, waist circumference, which isalso an important indication for assessing obesity-relatedhealth risk [2,10,32], was not measured in the CaMoscohort.ConclusionThis study provides evidence that Canadians have a higherBMI than that which is currently recommended for opti-mal health. Moreover, weight appears to be increasing inyounger age groups, although this reverses after age 65 inboth men and women. These findings suggest that a sub-stantial number of people may be putting their health atrisk due to being overweight or obese. Although there is atendency to stay in the same weight category, this increasein BMI over time underscores the need for public healthefforts aimed at combating the current epidemic of obes-ity, especially in younger men and women.Competing interestsThe author(s) declare that they have no competing inter-ests.Authors' contributionsWMH, CB, SIB, JCP, MH and TT participated in the con-ception and design of this CaMos ancillary study; CL, CBand LJ were responsible for the analysis; all were involvedin the interpretation of the findings and drafting the man-uscript; all have read and approved the final manuscript.Appendix 1: CaMos Research GroupCaMos Coordinating Centre, McGill University, Montreal,Quebec: David Goltzman (principal investigator), AlanTenenhouse (principal investigator emeritus), SuzettePoliquin (national coordinator), Suzanne Godmaire(research assistant), Claudie Berger (study statistician),Lawrence Joseph (consultant statistician).Memorial University, St. John's Newfoundland: CarolDalhousie University, Halifax, Nova Scotia: Susan Kirk-land, Stephanie Kaiser (co-directors), Barbara Stanfield(coordinator).Laval University, Quebec City, Quebec: Jacques P. Brown(director), Louis Bessette (co-director), Marc Gendreau(coordinator).Queen's University, Kingston, Ontario: Tassos Anastassia-des (director), Tanveer Towheed (co-director), BarbaraMatthews (coordinator).University of Toronto, Toronto, Ontario: Bob Josse (direc-tor), Tim Murray (co-director), Barbara Gardner-Bray(coordinator), Nancy Kreiger (principal investigator).McMaster University, Hamilton, Ontario: Jonathan D.Adachi (director), Alexandra Papaioannou (co-director),Laura Pickard (coordinator).University of Saskatchewan, Saskatoon, Saskatchewan:Wojciech P. Olszynski (director), K. Shawn Davison (co-director), Jola Thingvold (coordinator).University of Calgary, Calgary, Alberta: David A. Hanley(director), Jane Allan (coordinator).University British Columbia, Vancouver, British Colum-bia: Jerilynn C. Prior (director), Yvette Vigna (coordina-tor).AcknowledgementsCaMos was funded by the Canadian Institutes of Health Research (CIHR), Merck Frosst Canada Ltd., Eli Lilly Canada Inc., Novartis Pharmaceuticals Inc., The Alliance: Safoni-Aventis & Procter and Gamble Pharmaceuticals Canada Inc., The Dairy Farmers of Canada, The Arthritis Society. None of the funding agencies were directly involved in the design or conduct of the study, the collection, management, analysis or interpretation of the data, or the preparation, review or approval of the manuscript.The authors thank all the participants in the Canadian Multicentre Oste-oporosis Study.References1. Health Canada: Canadian Guidelines for Body Weight Classifi-cation in Adults.  Ottawa: Health Canada Publications Centre, Pub-lication ID 4645; 2003. 2. Gilmore J: Body Mass Index and Health. Statistics CanadaCatalogue 82-003.  Health Reports 1999, 11:31-43.3. Lau DCW: Call for action: preventing and managing theexpansive and expensive obesity epidemic.  CMAJ 1999,160:503-506.4. Torrance GM, Hooper MD, Reeder BA: Trends in overweight andobesity among adults in Canada (1970 – 1992): evidencefrom national surveys using measured height and weight.  IntJ Obesity 2002, 26:797-804.5. Tremblay MS, Katzmarzyk PT, Willms JD: Temporal trends inoverweight and obesity in Canada, 1981 – 1996.  Int J Obesity2002, 26:538-543.Page 10 of 11(page number not for citation purposes)Joyce (director), Christopher Kovacs (co-director), EmmaSheppard (coordinator).6. Katzmarzyk PT: The Canadian obesity epidemic, 1985 – 1998.CMAJ 2002, 166:1039-1040.Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central BMC Public Health 2007, 7:150 http://www.biomedcentral.com/1471-2458/7/1507. Flegal KM, Carroll MD, Ogden CL, Johnson CL: Prevalence andtrends in obesity among US adults, 1999–2000.  JAMA 2002,288:1723-7.8. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, FlegalKM: Prevalence of overweight and obesity among US chil-dren, adolescents and adults, 1999–2002.  JAMA 2004,291:2847-50.9. Raine KD: Overweight and Obesity in Canada: A PopulationHealth Perspective.  Ottawa, Ontario:Canadian Institute forHealth Information; 2002. 10. Trakas K, Lawrence K, Shear NH: Utilization of health careresources by obese Canadians.  CMAJ 1999, 160:1457-1462.11. Tjepkema M: Adult obesity in Canada: Measured height andweight. Statistics Canada.   [http://www.statcan.ca/english/research/82-620-MIE/2005001/articles/adults/aobesity.htm]. accessedJuly 5, 200712. World Health Organization: Obesity : Preventing and Managingthe Global Epidemic.  In Report of a WHO Consultation on ObesityVolume 894. Issue i-xii Geneva: World Health Organization;2000:1-253. 13. Ogden CL, Carroll MD, Flegal KM: Epidemiologic trends in over-weight and obesity.  Endocrinol Metab Clin North Am 2003,32:741-60.14. Katzmarzyk PT, Craig CL, Bouchard C: Underweight, overweightand obesity: relationships with mortality in the 13-year fol-low-up of the Canadian Fitness Survey.  J Clin Epi 2001,54:916-20.15. Katzmarzyk PT, Ardern CI: Overweight and obesity mortalitytrends in Canada, 1985–2000.  Can J Public Health 2004, 95:16-20.16. Flegal KM, Graubard BI, Williamson DF, Gail MH: Excess deathsassociated with underweight, overweight and obesity.  JAMA2005, 293:1861-7.17. American Society of Plastic Surgeons: The obesity epidemic.  Plas-tic and Reconstructive Surgery 2006, 117:1S-7S.18. Katzmarzyk PT, Janssen I: The economic costs associated withphysical activity and obesity in Canada: an update.  Can J ApplPhysiol 2004, 29:90-115.19. De Laet C, Kanis JA, Odén A, Johanson H, Johnell O, Delmas P, Eis-man JA, Kroger H, Fujiwara S, Garnero P, McCloskey EV, MellstromD, Melton LJ 3, Meuniere PJ, Pols HA, Reeve J, Silman A, TenenhouseA: Body mass index as a predictor of fracture risk: A meta-analysis.  Osteoporosis International 2005, 16:1330-8.20. Heo M, Faith MS, Pietrobelli A: Resistance to change of adultbody mass index.  Int J Obesity 2002, 26:1404-1405.21. Katzmarzyk PT, Perusse L, Malina RM, Bouchard C: Seven-year sta-bility of indicators of obesity and adipose tissue distributionin the Canadian population.  Am J Clin Nutr 1999, 69:1123-1129.22. Le Petit C, Berthelot JM: Obesity: A Growing Issue. In Healthytoday, health tomorrow? Findings from the National Popula-tion Health Survey.  Statistics Canada Catalogue 82–618-MWE2005003 2005.23. Kreiger N, Tenenhouse A, Joseph L, MacKenzie T, Poliquin S, BrownJ, Prior JC, Rittmaster R: Research Notes: The Canadian Multi-centre Osteoporosis Study (CaMos): Background, Rationale,Methods.  Can J Aging 1999, 18:376-87.24. Lovejoy JC: The menopause and obesity.  Primary Care 2003,30:317-25.25. Wolfe WS, Sobal J, Olson CM, Frongillo EA Jr, Williamson DF: Par-ity-associated weight gain and its modification by sociode-mographic factors: A prospective analysis in US women.  IntJ Obes Rel Metabolic Dis 1997, 21(9):802-810.26. Lee SK, Sobal J, Frongillo EA, Olson CM, Wolfe WS: Parity andbody weight in the United States: differences by race andsize of place of residence.  Obes Res 2005, 13:1263-9.27. Rubin D: Multiple Imputation for Non-response in Surveys.Wiley: New York; 1987. 28. Park AJ, Bloom SR: Neuroendocrine control of food intake.  CurrOpin Gastroenterol 2005, 21:228-233.29. Pi-Sunyer FX: The obesity epidemic: Pathophysiology and con-sequences of obesity.  Obesity Research 10(Suppl 2):97S-104S.30. Kaplan MS, Huguet N, Newsom JT, McFarland BH, Lindsay J: Preva-lence and correlates of overweight and obesity among olderadults: findings from the Canadian National PopulationHealth Survey.  J Gerontol A Biol Sci Med Sci 2003, 58:1018-30.31. Kmetic A, Joseph L, Berger C, Tenenhouse A: Multiple imputationto account for missing data in a survey: estimating the prev-alence of osteoporosis.  Epidemiology 2002, 13:437-44.32. Douketis JD, Paradis G, Keller H, Martineau C: Canadian guide-lines for body weight classification in adults: application inclinical practice to screen for overweight and obesity and toassess disease risk.  CMAJ 2005, 172:995-8.Pre-publication historyThe pre-publication history for this paper can be accessedhere:http://www.biomedcentral.com/1471-2458/7/150/prepubyours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralPage 11 of 11(page number not for citation purposes)

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