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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56:M780-M784 (2001)
© 2001 The Gerontological Society of America

Height and Body Weight in Elderly Adults

A 21-Year Population Study on Secular Trends and Related Factors in 70-Year-Olds

Debashish Kumar Deya, Elisabet Rothenberga,b, Valter Sundha, Ingvar Bosaeusb and Bertil Steena

a Departments of Geriatric Medicine, Göteborg University, Sweden
b Departments of Clinical Nutrition, Göteborg University, Sweden

Debashish Kumar Dey, Department of Medicine, Göteburg University, Vasa Hospital, Pav 15, Plan 5, S 411 33 Göteburg, Sweden E-mail: debashish.dey{at}geriatrik.gu.se.

Decision Editor: John E. Morley, MB, BCh


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Body size in elderly adults is partly due to aging and partly to secular trends. This study describes secular trends in three anthropometric measures (i.e., height, body weight [BW], and body mass index [BMI]) of 70-year-olds over a period of 21 years and their relation to social and lifestyle factors.

Methods. A total of 3128 70-year-olds from four birth cohorts born between 1901 and 1922 in Gothenburg, Sweden, were examined between 1971 and 1992 in the Geriatric Medicine Department, Göteborg University. Trends in anthropometric measures were examined by permutation test. Influence of the subjects' birth year, physical activity, smoking habits, and education on anthropometric measures were investigated by multiple linear regression.

Results. Individuals in later-born cohorts were found to be 1 to 2 cm taller and 1.5 to 6.3 kg heavier than earlier-born cohorts. For BMI, a positive trend was significant only in 70-year-old male participants. "Year of birth" was a positive predictor for BW (p < .001) and BMI (p < .001) in male participants and for height (p < .05) and BW (p < .01) in female participants. Physical inactivity was a positive (p < .01) and "current smoking" a negative (p < .001) predictor for BMI in both sexes. "More than basic education" was a positive predictor for height (p < .001) in both sexes and a negative predictor for body weight (p < .01) and BMI (p < .001) in female participants only.

Conclusions. Trends of increasing height, BW, and BMI were found among the Swedish elderly participants. This may be partly due to differences in smoking habits, physical activity, education, food habits, childhood nutrition, and living conditions between the cohorts.

BODY composition changes with aging (1)(2), and longitudinal decrease in height, body weight (BW), and body cell mass at older ages has been described (3)(4). Such changes may be universal, but their expression and incidence may vary considerably within and between groups of elderly adults (5). The smaller body size in older people is partly due to actual shrinkage over the life span (aging) and partly due to earlier generations being physically smaller than recent ones (secular trend) (6) or due to selective survival (7).

Geographic and ethnic variations in anthropometry reflect differences in lifestyle, environment, genetics, and health status in different populations (8). Such a difference also influences the rate and manifestations of aging (9). In a single population, individual variation occurs due to the differences in the rate of aging and in physiological systems within the same individual (10).

The aim of this study was to describe secular trends in height and BW of 70-year-olds and to investigate the influences of education, smoking habits, and physical activity on anthropometry in elderly adults born over a period of 21 years between 1901 and 1922.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
This study comprises data on 3128 70-year-olds (1426 males and 1702 females) from four birth cohorts born between 1901 and 1922 and were examined between 1971 and 1992 (Table 1 ). The general design, procedures, methods of data collection, and representativeness of these cohorts have been reported elsewhere (11)(12)(13)(14)(15). BW was recorded to the nearest 0.1 kg and standing height was measured to the nearest centimeter (16). Measures were done in the morning with light clothing. Body mass index (BMI) was calculated from weight (kilograms) divided by height (meters) squared. To minimize methodological differences, all measurements were performed aiming at identical methods by means of, for example, personal contacts and training together of the different investigators throughout the study.


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  		Table 1. Description of Population in Four 70-Year-Old Cohorts

 
Statistical Methods
Tests for trends between the cohorts were performed by a nonparametric permutation test of correlation (17). Two-tailed p values were considered to describe the level of significance. Multiple linear regression was done separately for height, BW, and BMI with the subject's year of birth, physical activity, smoking habits, and education as predictor variables.

Predictor Variables
The frequencies of predictor variables are presented in Table 2 . The cohorts' year of birth was used as a covariate in the regression model. In cohorts I and II, subjects were asked four questions about their leisure time physical activity during adult life (Table 3 ) and data pertaining to age 60 to 70 were used here. Physical activity data were collected according to a six-grade scale (18) in cohort III and through four questions in cohort V (Table 3 ). In the analyses, physical activity was divided into two dichotomous variables, "physically active" and "physically inactive," and the former was used in the regression model as reference (Table 3 ). A detailed smoking history was obtained for all subjects at age 70 and the subjects were then divided into three groups: daily smokers at age 70, ex-smokers (previous daily smokers and quit smoking before age 70), and never-smokers at age 70. In the regression model "never-smokers" was used as reference. The level of education was divided into two groups: "basic" (six-year compulsory schooling) and "more than basic." Basic education was used as a reference in the regression model.


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  		Table 2. Frequencies of Predictor Variables in Four 70-Year-Old Cohorts

 

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  		Table 3. Levels and Patterns of Leisure Time Physical Activity in Four 70-Year-Old Cohorts

 

   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Secular Trends in Height, BW, and BMI at Age 70
The mean values are presented in Table 4 . Males and females of cohorts II and V were found 1 and 2 cm taller compared to cohort I, respectively. In both sexes significant trends were found in height, in which individuals in later-born cohorts were taller, with exceptions in cohort III (Table 4 ). For BW, a positive trend was significant in both males (p < .001) and females (p < .05) with a mean difference of 6.3 and 1.5 kg, respectively, between cohort I and V (Table 4 ). A positive trend was only significant (p < .001) for BMI in males across the cohorts.


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  		Table 4. Height, Body Weight (BW) and Body Mass Index (BMI) in 70-Year-Olds

 
Predictors for Height, BW, and BMI at Age 70
"Year of birth" was a significant positive predictor for BW (p < .001) and BMI (p < .001) in males and for height (p < .05) and BW (p < .01) in females (Table 5 ). Physical inactivity was a significant negative predictor for height (p < .05) and a positive predictor for BMI (p < .01) in both sexes (Table 5 ). Current smoking habit was a significant negative predictor for BW (p < .001) and BMI (p < .001) in both sexes. "More than basic education" was a significant positive predictor for height (p < .001) in both sexes and a negative predictor for BW (p < .01) and BMI (p < .001) in females (Table 5 ).


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  		Table 5. Predictors for Height, Body Weight and Body Mass Index (BMI) of 70-Year-Olds

 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Population
The samples are representative for the population of that age and period of time in Gothenburg, Sweden. Responders did not differ significantly from nonresponders in relation to sex, marital status, and income (11)(13)(14)(15), which fulfills one of the definitive prerequisites for age-cohort comparisons (9). Although the response rate in later-born cohorts of this study decreased from 85% in cohort I to 66% in cohort V (Table 1 ), it is still higher than in many other similar studies (15).

Study Design
This 21-year cohort comparison study is based on cross-sectional data. The limitations with cross-sectional studies are that they are influenced by secular and survival effect differences within the study population (6). The design of this study is cross-sequential (19). It measures independent samples of individuals of a specific age at different times and thus can overcome the limitations in purely cross-sectional studies (20). Furthermore, the subjects' ages were almost the same across cohorts and thus did not confound the secular trend, which is more common in cross-sectional studies.

Methods
Because the methods were aimed to be identical in examinations and data collection for all birth cohorts, the study fulfilled another prerequisite for age-cohort comparison (9). The physical activity data were collected in somewhat different ways across the cohorts (Table 3 ) and, to make a comparison, we dichotomized the levels of physical activity that might have resulted in loss of information regarding differential effects of various levels of physical activity between the cohorts.

Results
Later-born cohorts in this study, with some exceptions, were taller and heavier than earlier-born cohorts. The observed positive trend for height and BW agreed with earlier results (21). The differences in BW were more pronounced in males compared to females, which might have resulted in a significant positive trend in BMI of males across the cohorts. The gender difference in trends of BMI may be explained partly by different smoking habits in males and females. The percentage of smokers decreased consistently across the male cohorts but the opposite was true for the females (Table 2 ).

Individuals in cohort III were shorter compared to cohort II and of similar height compared to cohort I. Variations in adult height reflected a number of conditions in childhood, including economic status, psychosocial factors (22)(23), education, and upward social mobility (24)(25). Thus, variation in height is related to the individual's lifetime exposure to certain genetic, environmental, and social factors. On the other hand, variations in BW are more related to an individual's current health status, physical activity, smoking and dietary habits, and other factors.

The cohorts examined in this study were born from the very begining of the century until 1922, and there might be differences in food intake, hygiene, and social conditions in childhood and early adult life. World War I occurred during the childhood of cohort III and at that time cohort V was not yet born. During World War I there were periods with an insufficient food supply in Gothenburg (26). To what extent this may have interfered with the results cannot be evaluated by this study. However, in a study of a Swedish population, differences in height between members of higher and lower socioeconomic groups were found (27). Furthermore, individuals in cohort III were more physically inactive compared to those of cohort II and it was found in the multiple regression analysis that physical inactivity is negatively related to height (Table 5 ).

Higher education was found to be positively related to height in both sexes and negatively related to BW and BMI in females. The findings are consistent with earlier results (25)(28). The positive relationship between physical inactivity and BMI is also consistent with an earlier report (28). A negative relation between smoking and BW and BMI was found and is consistent with earlier findings (29).

Conclusion
In this 21-year cohort comparison study, significant trends of increasing height, BW, and BMI were found across the cohorts. The trends may be partly due to differences in smoking habits, physical activity, and food habits across the cohorts. Social conditions (e.g., education) as well as conditions in childhood might also have played some role.


   Acknowledgments
 
This work has been done at the Department of Geriatric Medicine, Göteborg University, within the framework of the gerontological and geriatric population studies in Gothenburg, Sweden—the H70 studies. The gerontological and geriatric population studies in Gothenburg (H70) were supported by grants from the Swedish Ministry of Health and Social Affairs, Commission for Social Research, the Swedish Council for Planning and Coordination of Research, the Gothenburg Medical Services Administration, the Wilhelm and Martina Lundgren Foundation, the Swedish Medical Research Council, the Dr. Félix Neubergh Foundation, the Gothenburg Administration of Social Services, the Swedish Social Research Council, the Hjalmar Svensson Foundation, the Elsa and Eivind K:son Sylvan Foundation, and the Gun and Bertil Stohnes Foundation.

Received February 13, 2001

Accepted March 26, 2001


   References
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 Methods
 Results
 Discussion
 References
 

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