Data about the prevalence of being overweight and obesity

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1 Body mass index and health among the working population Epidemiologic data from Belgium GUIDO MOENS, LUC VAN GAAL, ERIK MULS, BART VIAENE, PIERRE JACQUES * Background: The objective of the study was to investigate the distribution of body mass index (BMI; kg/m ) among the working population in Flanders and the Brussels region of Belgium and the association of BMI with gender, age, occupation, smoking, blood pressure and, more specifically, with sick leave. Methods: Routine data on body height and weight were registered in 1994 in a cross-sectional way at periodical medical examination of employees in various industrial sectors. Results for 59,081 male and 4,414 female workers, aged years, were registered on an optical form and stored into a database. Results: Descriptive statistics (mean ± SD) for BMI among males were 25.2 ± 3.92 (median = 24.86) and among females ± 4.3 (median = 23.13). BMI was >25 in 48.5%, >30 in 11.1% and >40 in 0.3% of the males. Among females a BMI >25 was observed in 31.%, >30 in 9.4% and >40 among 0.%. Significant associations were found with age, occupation, smoking, hypertension and sick leave. In both sexes younger persons, clerical workers, smokers and persons with normal systolic or diastolic blood pressure had the lowest BMIs. More prominent in females, a trend of increasing year prevalence of sick leave with increasing BMI group was found. This association was not confounded by age, occupation or other variables in a logistic regression analysis. Conclusions: The high prevalence of a BMI >30, more pronounced in male than in female employees, needs further investigation. In addition, the cross-sectional association with sick leave needs confirmation in prospective studies. Key words: Belgium, body mass index, cross-sectional study, sick leave, working population Data about the prevalence of being overweight and obesity in Belgium, more specifically in the Flanders region, are scarce and limited to selected study populations. 1 In the age group years the prevalence of grade II obesity (BMI >30) has been estimated at between and 20% among females and between 15 and 25% among males. 2 Although in Europe obesity is more common in women, the variability is also larger in women than in men. Moreover, the prevalence is reported to have increased in most European countries.-' Obesity has been shown to be associated with risk factors for cardiovascular diseases, hypertension, diabetes, gallstones and orthopaedic impairments.'*'' Thus, the direct and indirect economic costs of obesity are substantial. In the USA these costs were estimated to be 39 billion dollars in and in the Netherlands the direct annual health care costs approximate 1 billion Dutch guilders or 4% of the total health care budget. 6 * G. Moens u, L Van GaaP, E. Mub 4, B. Vlaene 1, P. Jacques u 1 IDEWE, Leuven, Belgium 2 Deportment of Occupational Medicine, Faculty of Medicine, University of Leuven, Belgium 3 Department of Endocrinology, Faculty of Medicine, University Hospital of Antwerp, Belgium 4 Department of Endocrinology Metabolism and Nutrition, Faculty of Medicine, University Hospital Gasthursberg, Leuven, Belgium Correspondence: Guldo Moens, IDEWE Occupational Health Services, Interleuvenlaan 58, B-3001 Leuven, Belgium, tel , fax Within the legal framework of Belgian occupational health surveillance activities, each day approximately,000 workers undergo a medical examination. At this event a number of relevant data on the health of the workers is recorded. The analysis of these data, if properly collected, could be informative about the health status of employees. Since 198, the largest occupational health service of Flanders (IDEWE) has recorded such data in a computer database. Because body weight and height have routinely been measured and recorded, these data could be used to provide an insight into the characteristics and determinants of being overweight among the working population. This is a novel and interesting use of these occupational health data. The aims of this study were as follows. To investigate the distribution of the categories of body mass index (BMI) in a large sample of the working population in Flanders and Brussels in 1994, the most recent year for which complete data were available for analysis. To investigate the descriptive associations of BMI with age, gender, occupational group, industrial sector, smoking and arterial blood pressure. The association with sick leave was analysed in more depth. METHODS As a measure of obesity, the BMI was used as the ratio of body weight (in kgs) to body height (in m 2 ). Although

2 EUROPEAN JOURNAL OF PUBLIC HEALTH VOL NO. 2 this measure has been shown to be dependent on sex and age as a measure of body fatness, it was the only measure available. A BMI below 20 is considered as underweight and between 20 and 24.9 as desirable.8 From 25 on three categories of being overweight are distinguished: 25 - <30 = grade I obesity, 30 - <40 grade II obesity and 40 = grade III or morbid obesity.8 Body weight and height, age and sex were recorded by the occupational nurse for every employee examined in the year 1994 at the periodical medical examination, which is part of the routine medical surveillance procedure according to the Belgian legislation and which was performed by the occupational health service IDEWE. The persons were employed in approximately 30,000 institutions or factories from various occupational sectors. The sample was not a random sample of the total working population. The total sample consisted of 59,081 men, aged years (mean age = 35.2 years and median = 34 years) and 4,414 women, aged years (mean age = 33.9 years and median = 33 years) or a total of 6,495 employees, which comprises approximately 4% of the total population employed in the Flanders and Brussels regions. Various health-related characteristics are routinely measured and recorded at the examination for surveillance purposes. Only those variables known as potentially associated with BMI were selected: smoking habits, arterial blood pressure and sick leave - defined as absence from work due to sickness, reported retrospectively over the past year, yielding a year period prevalence and measured in frequency and in number of days. All data were recorded by approximately 0 trained occupational medical teams (physician and nurse) on an optically readable form and stored in a computer database. Measuring instruments were centrally gauged and measurements were performed using standardized procedures by 0 medical teams. To assess die magnitude and characteristics of observer variation, 95% confidence intervals (95% CI) were calculated for each observer and for the selected variables. The distribution of these intervals around the population value was random and symmetrical. Statistical testing consisted of the y} test, Student's t-test, analysis of variance and the non-parametric median test. The association of sick leave with BMI was analysed in more depth and controlled for confounding variables. Using a logistic regression analysis the odds ratios (ORs) for sick leave were calculated for the various BMI categories, taking the category with the 'desirable' BMI (20 - <25) as the reference group. All statistical testing was performed with the SPSS 5.0 package. RESULTS Figure I shows the prevalence of the different BMI categories according to gender: 49% of the male employees had a BMI of 25 or more, 11% of 30 or more and 0.3% of 40 or more. Among female employees the figures 9 were slightly lower: 32% had a BMI 25, 9% a BMI Prevalence (%) d 1_ I (n=59081) " (n=4414) BMI group Figure 1 Prevalence of standard BMI categories according to gender in a sample of Flemish employees; 1994 and 0.% a BMI 40. The difference between men and women is most obvious for grade I obesity. Table I shows the variation in BMI according to selected variables. Descriptive statistics (meantsd) for BMI among males were 25.2±3.92 (median 24.86) and among females 24-03±4-3 (median=23.13). The frequency distribution is slightly skewed to the right, more prominently among women and the 90th percentile in both genders is at approximately 30 kg/m2 (not shown). BMI varies with age, from 23.5 among men younger than 25 years to 2 in the age group 55 years and older. Among women the trend is comparable but situated at a lower level: from 23.1 to In both men and women a slightly higher BMI is recorded among blue-collar workers than among white-collar workers. This difference is, however, more pronounced in subjects with a BMI of 30 or more. In accordance with this finding, the highest mean BMI and prevalence of obesity were observed in miners and transport workers, and the lowest among clerks, staff personnel and professionals. Smokers had slightly lower BMIs than non-smokers, but although statistically significant, these differences were not large. Among females in particular, persons who reported sick leave had higher BMIs. The association with blood pressure is prominent: in both genders systolic and diastolic hypertension are strongly related to BMI. A gradual increase in systolic and diastolic blood pressure is seen with increasing BMI, which is more pronounced in males than in females (not shown). Although these differences are all statistically significant (p<0.001), this is partly due to the large sample size. Thus, when assessing these figures, the absolute differences have to be taken into account. The association with sick leave was studied more closely. A gradual increase in the sick leave prevalence from 32% in the lowest to 48% in the highest BMI group was found in females. In males the differences were smaller (from 28. to 31.0%). It can also be seen in table 2 that the mean and median number of days of absence among absentees rises with increasing levels of obesity. Finally, we investigated whether the association of BMI with sick leave prevalence was not confounded by other variables linked to BMI as well as to sick leave. These

3 BMI and health among Belgian employees confounders were age, occupation, smoking behaviour and hypertension. Table 3 shows the results of the logistic regression analysis. It can be seen that among females the ORs were not affected by the confounders and that among males the association became even stronger. However, because the OR is an overestimate of the prevalence ratio when the prevalences are high (>%), 1 ' the analysis has only to be taken as indicative of the possible influence of confounding factors on the association. From the analysis, it was also seen that smoking was not a negative confounder of the association with sick leave. DISCUSSION The findings from this cross-sectional study suggest that BMI distribution differs between male and female Flemish employees. Almost half of the male population in the investigated sample had a BMI of 25 or more. The only comparison data for Belgium are available from the BIRNH study, 1 where a representative sample of 5,18 Belgian males and 5,142 females, aged 25 to 4 years, was investigated for a number of cardiovascular risk factors (e.g. nutritional habits and blood lipids) in The mean BMI in males was 25.8 (SD=3.9) and in females 25. (SD=4-6). These figures are comparable to our findings in men (25.3), but in women die mean BMI (24.0) is lower in our data. Direct comparisons with other industrialized countries are difficult because different age groups, population samples and criteria for obesity have been used. ^ In comparison with, for example, The Nedierlands 12 and Spain, 13 die prevalence of obesity in Flemish employees is higher in males, but comparable in females: a BMI of >30 was observed in % of Dutch men and 9% of Dutch women aged years (data from ) 12 and in 6.5% of Spanish men and 8% of Spanish women aged years (data from 198). 13 The prevalence of obesity in the same age groups in men and Table 1 BMI (mean and standard deviation) and prevalence of BMI >30 (%) in Flemish employees by gender, age group, employment contract, occupational group, smoking habits, hypertension and absenteeism; 1994 Variable Gender n 59, SD 3.92 BMI 30 (%) 11.1 n 4, SD 43 BMl 30(%) 9.4" Age group (years) < ^55,821 20,16 15,502 9,205 2, b C 8,668 18,502 13,55 5,199 1, b l c Employment White collar Blue collar,940 32, " 12.1 C 21,21 15, " C Occupational group Professionals Staff/Management Clerical worker Salesman Farmer Mine worker Transportation worker 4, , , , , Craftsman Services employee 24,629 3, b C 4,512, O b C Smoking habits Non-smoker Smoker Sickness absenteeism (during the past 12 months) No Yes Arterial blood pressure Systolic ^140 mm Hg Systolic > 140 mm Hg Diastolic S90 mm Hg Diastolic >90 mm Hg 33,60 22,853 39,623 16,082 50,214 6, , " d " " c * C C 33, ,43 42, ,925 1, " * ' " C C CF 44.1 C a: Differences between means statistically significant, p<0.001, Students t-test. b: Differences between means statistically significant, p<0.001, analysis of variance, c: Differences between categories statistically significant, p<0.001, % test. d: Difference! between means statistically significant, p<0.05, Students t-test.

4 EUROPEAN JOURNAL OF PUBLIC HEALTH VOL NO. 2 women was estimated to be 8 and 9% in the UK, 9 and 8% in Canada and 12 and 15% in the USA 14, respectively. BMI is significantly associated with all the selected variables, although some of these associations were not clinically relevant. Most of these associations are in accordance with findings from other studies, 12 ' 15 e.g. the trend of increasing BMI with age, which is particularly strong in the age groups between 35 and 54 years. In addition, the differences according to type of employment contract and occupation are congruent with previous observations: persons with a higher educational level have consistently lower BMIs. 12 ' 16il Educational level and nutritional behaviour seem to be more important predictors of BMI than the level of physical activity of a given occupation. The association with arterial blood pressure was particularly strong and more prominent among men, a finding that has been confirmed in prospective studies. 18 Because obesity is a strong risk factor for several major public health problems, leading to substantial economic costs due to the increased use of health care facilities and other costs associated with disease, disability and death, the association with sick leave in our data is not surprising. A comparable finding was also reported by Rosmond et al. among middle-aged men. In our data, this association is particularly apparent among females and the association is not confounded by other variables. When interpreting this finding we have to remember that this is a sample of employed persons, who overall are healdiier than the general population. The real impact of a lowering of BMI on sick leave figures cannot be precisely estimated from our results, due to the limitations of the cross-sectional design and the healthy worker bias, 19 which impairs generalization to the general population. However, such an estimate can be obtained by calculating the attributable fractions 19 based on the mean number of sick leave days (table 2) and the odds ratios listed in cable 3. The attributable fraction among the exposed is the fraction of the outcome prevalence (sick leave) among die exposed (high BMI group), which can be attributed to the exposure when compared to the less exposed (lower BMI group). These calculations indicate that sick leave prevalence could be lowered by 13 and 22% and die mean number of sick leave days by 23 and 28% if male and female employees respectively, widi a BMI between 30 and 39, could succeed in lowering their BMI to levels below 25. Because of die limitations mentioned above, this estimate is likely to be an underestimate. Finally, the main limitations when interpreting diese findings have to be addressed. First, although large, diis sample is not representative of all Flemish employees nor of the general population. However, die sample remains informative about the BMI distribution and its associations. Second, die reliability and validity of die measurements have to be considered. Aldiough standardization of instruments and procedures is a primary goal in die occupational health service IDEWE, systematic Table 2 and median number of days of sick leave according to BMI group in Flemish employees reporting sick leave; 1994 BMI group (kg/m ) 20-< <30 30-< ,668 5,583 1, " Median 8 1,65,634 3,425 1, " Median Total 14, , a: Because the variable 'number of days of stek leave' was not normally distributed, the non-paiametnc median test was used, b; Differences between medians statistically significant, p<0.001, median test. Table 3 Crude and adjusted odds ratios (OR) for sick leave (outcome variable) calculated from a logistic regression with die (desirable) BMI category ( ) as the reference category (exposure variable); Flemish employees; 1994 BMI group (lcg/m 2 ) 20 - <25 25-<30 30-<40 40 Crude OR (95% CI) Adjusted OR (95% CI) a 1.08 ( ) 1.06( ) 0.98 ( ) 1.01 ( ) 1.0( ) 1.15( ) 1.13 ( ) 1.25( ) Crude OR (95% CI) Adjusted OR (95% CI) b 0.90 ( ) 0.90 ( ) 1.15( ) 1.14( ) 130( ) 1.29( ) 1.88( ) 1.86( ) a: Adjusted for age, smoking habits, occupational group, systolic blood pressure; other variables did not significantly improve die model (residual * 2 p-0.4c98 and Wald statistic for BMI group in the final model p-0.c09). b: Adjusted for age, smoking habits, occupational group; other variables did not significantly improve the model (residual X 2 p and Wald statistic for BMI group in the final model p<0.cc01).

5 BMJ and health among Belgian employees errors are unavoidable when measurements are made by approximately 0 observers and, thus, could impair the external validity of the findings. However, when considering the internal validity we found that observer errors were randomly distributed around the population parameter. 9 In addition, there were no indications that systematic errors were linked to one of the investigated variables. It should also be remembered diat many population-based studies of obesity rely on self-reported body height and weight, which reduces the reliability of BMI values in these studies. Finally, the cross-sectional and retrospective study design render this type of study particularly susceptible to epidemiological bias. 'Healthy worker bias' 19 probably brings about an underestimation of the problem because diseased (and obese) workers are likely to give up the study base as time goes by. Selection bias is likely to act stronger in females because consecutive pregnancies are a reason to leave the work force and these are also linked to an increase in BMI. This bias could thus partly explain the lower scores for females in our data. In addition, recall bias is likely to occur when persons are asked to report their sick leave over the past year. Research into the validity of our data has shown that this under-reporting could amount to 15%. If the underreporting is linked to BMI, an underestimation of the effect will result. No causal inferences about the associations found in this study can therefore be made, but it can be inferred that the real effects are most likely larger than those shown. In conclusion, the problem of obesity in the working population in the Flanders and Brussels regions of Belgium warrants further research and efforts to prevent obesity. The rising prevalence in most industrialized countries is a major public health issue and a populationbased prevention strategy 20 ' 21 aiming at a downward shift in the BMI distribution of the whole population seems to be the most appropriate strategy to tackle the problem. This implies a transformation in our thinking on transport, environment, work facilities, education, health and food policies. 20 This study was supported by a grant from SANDOZ NUTRITION. Quality assurance investigation of the database was funded by a grant from the Belgian Federal Government (DWTC project no. ST/93/003). The authors would like to thank Chr. Grootaert (Sandoz Nutrition), R, De Wit and G. Mylle (1DEWE) for editorial and research 1 Kornitzer M, Bara L (for the BIRNH study group). Clinical and anthropometric data, blood chemistry and nutritional patterns in the Belgian population according to age and sex. Acta Cardiol 1989;44: Seidell JC. 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