PAPER

Physical activity and dietary fiber determinepopulation body fat levels: the Seven Countries Study

D Kromhout1*, B Bloemberg1, JC Seidell1, A Nissinen2,3 and A Menotti1,4 for the Seven CountriesStudy Group

1Division of Public Health Research, National Institute of Public Health and the Environment, Bilthoven, The Netherlands;2Department of Public Health and General Practice, University of Kuopio, Kuopio, Finland; 3Department of Neurology, KuopioUniversity Hospital, Kuopio, Finland; and 4Division of Epidemiology, School of Public Health, University of Minnesota,Minneapolis, Minnesota, USA

BACKGROUND: A global epidemic of obesity is developing. Current prevalence rates are about 20 25% in American adultsand 15 20% in Europeans.OBJECTIVE: We investigated the association between population levels of physical activity, dietary fat, dietary fiber andindicators of body fat.DESIGN: Cross-cultural study of 16 cohorts of, in total, 12 763 middle-aged men in seven countries. These men were examinedbetween 1958 and 1964.MEASUREMENTS: Height, weight and subscapular skinfold thickness were measured. Information about job-related physicalactivity and diet was gathered by questionnaire.RESULTS: The population average body mass index (weight=height2) varied between 21.8 and 26.0 kg=m2 and the populationaverage subscapular skinfold thickness between 8.4 and 23.7 mm. The population average physical activity index and dietaryfiber intake were both strongly inversely related to population average subscapular skinfold thickness and explained together90% of the variance in subscapular skinfold thickness. Similar but less strong results were obtained for average population bodymass index.CONCLUSION: At the population level job-related physical activity and dietary fiber but not dietary fat, are importantdeterminants of subscapular skinfold thickness.International Journal of Obesity (2001) 25, 301 306

Keywords: body fat; body mass index; skinfold thickness; physical activity; dietary fat; dietary fiber; ecologic analysis

IntroductionObesity is a common and growing problem in affluent

countries. Current prevalence rates are about 20 25% in

American adults and 15 20% in Europeans.1 Direct costs of

obesity in these regions have been estimated to be respon-

sible for about 5 10% of total health care costs and indirect

costs (due to loss of productivity) are of the same order of

magnitude.2,3 The problem of obesity is smaller in many

countries undergoing economic transition, but is rapidly

increasing there. This increase is accompanied by a sharp

increase in the incidence of type 2 diabetes mellitus and

cardiovascular diseases.4

The development of obesity is the consequence of chronic

and sustained energy imbalance when energy intake exceeds

energy expenditure. Therefore it is necessary to take both

sides of the energy equation simultaneously into account.

Both energy imbalance as well as maintenance of obesity are

thought to be facilitated by energy-dense diets and sedentary

lifestyles.3 Short-term covert manipulation of energy density

of food has shown to affect energy intake.5,6

The role of fat intake in the etiology of obesity is con-

troversial. Epidemiological and long-term intervention stu-

dies did show a relatively small effect of changes in dietary

fat content on energy balance and weight change.7,8 Ecolo-

gical studies on the association between relative fat intake

*Correspondence: D Kromhout, Division of Public Health Research,

National Institute of Public Health and the Environment, PO Box 1,

3720 BA Bilthoven, The Netherlands.

E-mail: daan.kromhout@rivm.nl

Received 3 March 2000; revised 27 September 2000;

accepted 7 November 2000

International Journal of Obesity (2001) 25, 301306 2001 Nature Publishing Group All rights reserved 03070565/01 $15.00www.nature.com/ijo

International Journal of Obesity (2001) 25, 301306 2001 Nature Publishing Group All rights reserved 03070565/01 $15.00www.nature.com/ijo

and body mass index (BMI, weight=height2) have shown

both positive and inverse associations.9 These inconsisten-

cies can be partly explained by the lack of control for energy

expenditure and energy-dense diets. Data from the UK have

suggested that crude indicators of leisure time physical

activity such as amount of television viewing and number

of cars in the household are strongly associated with trends

in obesity rates and differences between socio-economic

classes, whereas the contribution of energy intake by dietary

fat was not related to obesity.10

To our knowledge there have been no attempts to study

differences in obesity rates in populations in relation to the

combination of population energy expenditure levels and

indicators of energy density. In addition, relative fat intake

was usually the sole indicator of dietary intake and energy

expenditure was evaluated mainly by leisure time activities.

Moreover, in virtually all studies BMI was used as a measure

of body fat and the validity of BMI as a measure of body fat

across populations has been questioned.11,12

In the present study we used both average levels of body

fat measured by BMI and subscapular skinfold thickness in

middle-aged men participating in the Seven Countries Study

in the period 1958 1964. The study populations ranged

from farmers to university professors and differences in

energy expenditure were predominantly caused by differ-

ences in job-related physical activity and not by leisure time

activity. Indicators of energy density included not only fat

intake but also fiber intake.

MethodsBetween 1958 and 1964, 12 763 men aged 40 59 were

enrolled in the Seven Countries Study. In these countries

16 cohorts were established, 11 in rural areas in Finland,

Italy, Greece, the former Yugoslavia and Japan, two cohorts

of railroad employees in the USA and Italy, one of workers in

a large co-operative in Serbia, one of university professors in

Belgrade and one of inhabitants of a small commercial

market town in The Netherlands. The characteristics of

these cohorts have been described in detail.13 15

All men in the Seven Countries Study were classified at

entry according to their job-related habitual physical activity

pattern.13 Class 1 men were bedridden. Class 2 men were

sedentary and engaged in little exercise. This category

embraced clerks, salesmen, managers, teachers etc. Class 3

men were moderately active during a substantial part of the

day and consisted of bakers, butchers, plumbers, small shop-

keepers etc. Class 4 men performed hard physical work much

of the time and examples of this category are farmers,

lumberjacks, fishermen, blacksmiths etc. For each cohort

the percentage of men in each class was determined and

the average calculated. The average index was multiplied by

1000 in order to get values in the order of magnitude

comparable to energy expenditure expressed in kcal.

Weight was measured with a balance to the nearest 100 g

without shoes, in light undergarment, according to a stan-

dardized protocol.13 Height was measured to the nearest

0.5 cm without shoes. The subscapular skinfold thickness

was measured twice in a standardized way at the right side

of the body. The average was used in the analysis. For the

Japanese cohorts Tanushimaru and Ushibuka the subscapu-

lar skinfold thickness values of the 10 y follow-up survey

were used because this skinfold was not measured at the

baseline examination.

Between 1959 and 1964 dietary information was collected

in small random samples of 14 of the 16 cohorts.16 In the

other two cohorts dietary information was gathered around

1970. The weighed record method was used in all dietary

surveys. In 1985 and 1986 the original dietary data of these

cohorts were coded by one dietitian in a standardized way.

The average intake of different foods consumed in the 16

cohorts was calculated and summarized in 16 food groups.

In 1987, equivalent food composites representing the

average food intake of each cohort at baseline were collected

from local markets by two dietitians. These foods were

transported in cooling boxes to the laboratory of the Depart-

ment of Human Nutrition, Agricultural University, Wagen-

ingen, The Netherlands (Head, MB Katan). The foods were

cleaned and equivalent food composites prepared according

to the average consumption patterns of the cohorts. The

foods were homogenized and frozen at 20C until chemicalanalyses of the different nutrients took place. Total lipids

were isolated according to Osborne and Voogt.17 Total

energy intake is the sum of total protein, fat and carbohy-

drates. Total dietary fiber was determined with an enzymatic

gravimetric method.18

The physical activity index, dietary intake variables, BMI

and subscapular skinfold thickness represent the average

for each cohort. Analyses concern only inter-cohort

comparisons. Because of the limited degrees of freedom,

the multiple regression models never included more than

four independent variables. Only two-sided P-values are

reported.

ResultsThe population average BMI varied between 21.8 in Tanush-

imaru ( Japan) and 26.6 kg=m2 in the Rome Railroad (Italy)

(Table 1). The population average subscapular skinfold thick-

ness varied between 8.4 in Velika Krsna (Serbia) and 23.7 mm

in Belgrade (Serbia). The correlation coefficient between the

population average BMI and subscapular skinfold thickness

was 0.75 (P

(Serbia). Only 13 of the 12 763 men were bedridden. The

population average energy intake varied from 2251 kcal=day

in the American Railroad to 3609 kcal=day in Slavonia (Croa-

tia). The correlation between the population average physi-

cal activity index and energy intake was 0.45 (P

the strengths of the study is the variation in average levels of

body fat in the populations studied (range of average sub-

scapular skinfold thickness, 8 24 mm, and range for BMI,

22 27 kg=m2). The data were collected at a time when most

of the variation in total daily energy expenditure in middle-

aged men was determined by the level of physical activity at

work. In addition, this is to our knowledge the first study to

investigate cross-cultural differences in levels of body fat

examining key indicators of energy intake, energy density

and energy expenditure in one single data-set. The timing of

data collection in the Seven Countries Study limits the

extrapolation to the contemporary situation but the results

are probably applicable for many countries in the world in

different phases of economic transition. Another advantage

is the availability of subscapular skinfold thickness in

addition to BMI.

Table 2 Regression coefficients for population average physical activity index, dietary fat and fiber in relation toaverage BMI in the Seven Countries Study

UV MV

Lifestyle variable b 95% CI b 95% CI

PAI 0.0018 0.0029; 0.0007** 0.0015 0.0026; 0.0004*Dietary fat (g=day) 0.0135 0.0050; 0.0320 0.0146 0.0008; 0.0300Dietary fiber (g=day) 0.0408 0.1118; 0.0301 0.0404 0.0996; 0.0187

BMIbody mass index. PAIphysical activity index. UVunivariate model. MVmultivariate model including physicalactivity index, dietary fat and dietary fiber as independent variables. b regression coefficient. CI confidence interval.*P

For ecological analyses it is important to know how stable

the position is of each cohort in the distribution of a body

fat indicator. Although the population average BMI of

16 cohorts increased from 24.0 to 24.8 kg=m2 and the

population average subscapular skinfold thickness from

12.5 to 14.8 mm during a follow-up period of 10 y, the

correlation coefficients for these indicators of body fat mea-

sured 10 y apart amounted to about 0.9 (P

designed to show that an increase in physical activity and

dietary fiber can prevent obesity.

Acknowledgements

The authors are grateful to the principal investigators in the

different countries who initiated the Seven Countries Study

and for their effort in carrying out the study for more than

25 y.

References1 Seidell, JC, Flegal KM. Assessing obesity: classification and epi-

demiology. Br Med Bull 1997; 53: 238 252.2 Seidell JC. The impact of obesity on health status: some implica-

tions for health care costs. Int J Obes Relat Metab Disord 1995;19(Suppl 6): S13 S16.

3 World Health Organization. Obesity: preventing and managing theglobal epidemic. World Health Organization: Geneva; 1998.

4 Amos AF, McCarty DJ, Zimmet P. The rising global burden ofdiabetes and its complications: estimates and projections to theyear 2010. Diabet Med 1997; 14(Suppl 5): S1 S85.

5 Prentice AM. Manipulation of dietary fat and energy density andsubsequent effects on substrate flux and food intake. Am J ClinNutr 1998; 67: 535S 541S.

6 Rolls BJ, Bell EA, Castellanos VH, Chow M, Pelkman CL, ThorwartML. Energy density but not fat content of foods affected energyintake in lean and obese women. Am J Clin Nutr 1999; 69: 863 871.

7 Bray GA, Popkin BM. Dietary fat intake does affect obesity! Am JClin Nutr 1998; 68: 1157 1173.

8 Willett WC. Dietary fat and obesity: an unconvincing relation.Am J Clin Nutr 1998; 68: 1149 1150.

9 Lissner L, Heitmann BL. Dietary fat and obesity: evidence fromepidemiology. Eur J Clin Nutr 1995; 49: 79 90.

10 Prentice AM, Jebb S. Obesity in Britain: gluttony or sloth? Br Med J1995; 311: 437 439.

11 Deurenberg P, Yap M, van Staveren WA. Body mass index andpercent body fat: a meta analysis among different ethnic groups.Int J Obes Relat Metab Disord 1998; 22: 1164 1171.

12 Heitmann BL, Swinburn B, Carmichael H, Rowley K, Plank L,McDermott R, Leonard D, ODea K. Are there ethnic differencesin the association between body weight and resistance, measuredby bioelectrical impedance? Int J Obes Relat Metab Disord 1997; 21:1085 1092.

13 Keys A, Aravanis C, Blackburn HW et al. Epidemiological studiesrelated to coronary heart disease: characteristics of men aged 40 59 in seven countries. Acta Med Scand 1967; 460: 1 392.

14 Keys A (ed). Coronary heart disease in seven countries. Circulation1970; 41(Suppl 1): 1 211.

15 Keys A. Seven countries: a multivariate analysis of death and coronaryheart disease. Harvard University Press: Cambridge, MA; 1980.

16 Kromhout D, Keys A, Aravanis C et al. Food consumption pat-terns in the 1960s in seven countries. Am J Clin Nutr 1989; 49:889 894.

17 Osborne DR, Voogt P. Soxhlet method. In: Analysis of nutrients andfoods, 1st edn, Academic Press: London; 1978. pp 155 156.

18 William S (ed). Total dietary fiber in foods; enzymatic gravimetricmethod. Changes in methods. J Ass Off Anal Chem 1985; 68: 399.

19 Han TS, Seidell JC, Curral JEP, Morrison CE, Deurenberg P, LeanMEJ. The influence of height on waist circumference as an indexof adiposity in adults. Int J Obes Relat Metab Disord 1997; 21:83 89.

20 Donahue RP, Abbott RD, Bloom E, Reed DM, Yano K. Centralobesity and coronary heart disease in men. Lancet 1987; i: 821 824.

21 Higgins M, Kannel WB, Garrison R, Pinski J, Stokes J III. Hazardsof obesity the Framingham experience. Acta Med Scand 1988723(Suppl): 23 36.

22 Seidell JC. Dietary fat and obesity: an epidemiologic perspective.Am J Clin Nutr 1998; 67(Suppl): 546S 550S.

23 Drenowski A, Popkin BM. The nutrition transition: new trends inthe global diet. Nutr Rev 1997; 55: 31 43.

24 Hill JO, Peters JC. Environmental contributions to the obesityepidemic. Science 1998; 280: 1371 1374.

25 Egger G, Swinburn B. An ecological approach to the obesitypandemic. Br Med J 1997; 315: 477 480.

26 Heitmann BL, Lissner L, Sorensen TIA, Bengtsson C. Dietary fatintake and weight gain in women genetically predisposed forobesity. Am J Clin Nutr 1995; 61: 1213 1217.

27 Heitmann BL, Kaprio J, Harris JR, Rissanen A, Korkeila M, Kos-kenvuo M. Are genetic determinants of weight gain modified byleisure-time physical activity? A prospective study of Finnishtwins. Am J Clin Nutr 1997; 66: 672 678.

Physical activity, dietary fiber and body fatD Kromhout et al

306

International Journal of Obesity