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Identifying the energy gap in the German population using results from representative national health surveys (1985–2002)

Published online by Cambridge University Press:  21 April 2010

Nanette Stroebele*
Affiliation:
Institute for Social Medicine, Epidemiology and Health Economics, Charité University Medical Center, Luisenstr. 57, D-10117 Berlin, Germany
James O Hill
Affiliation:
Center for Human Nutrition, University of Colorado Denver, Denver, USA
Stefan N Willich
Affiliation:
Institute for Social Medicine, Epidemiology and Health Economics, Charité University Medical Center, Luisenstr. 57, D-10117 Berlin, Germany
*
*Corresponding author: Email Nanette.Stroebele@charite.de
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Abstract

Objective

The prevalence of overweight and obesity is increasing in most countries, including Germany. The idea of estimating the population-wide energy gap that is likely responsible for the epidemic has recently been introduced and discussed.

Design

Using published estimates of body weight from population-based data of national health surveys (1985–2002), the energy gap was calculated by estimating the distribution of the rate of weight gain within the German population (25–69 years of age) and the amount of excess energy storage that is responsible for this population-wide pattern of weight gain.

Setting

Germany.

Subjects

A representative sample of 26 614 participants (12 984 men, 13 630 women).

Results

The average annual weight gain was 0·22 kg for men and 0·32 kg for women over the 17-year period. An estimated 90 % of the population gained < 0·54 kg/year. Assuming that each kilogram of weight gained represents 32238 kJ (7700 kcal), the estimated energy accumulation was 19 kJ (4·64 kcal)/d in men and 28 kJ (6·75 kcal)/d in women aged 25–69 years. The distribution of estimated energy accumulation for 90 % of the German population was < 50 kJ (12 kcal)/d.

Conclusions

With an assumed energy efficiency of 50 %, the findings suggest that weight gain could be prevented in 90 % of the German population with < 100 kJ (24 kcal) reduction in energy intake or increase in energy expenditure per day. Theoretically, further weight gain might be prevented using a small-changes approach that emphasizes the importance of making small changes in physical activity and food intake.

Type
HOT TOPIC – Overweight and obesity
Copyright
Copyright © The Authors 2010

The prevalence of overweight and obesity is rising in all countries(Reference Yoon, Lee and Kim1Reference Fezeu, Assah and Balkau4), including Germany(5, Reference Mensink, Lampert and Bergmann6). The WHO has declared overweight as one of the top ten risk conditions in the world and one of the top five in developed countries(7). According to data from the Telephone Health Survey 2003, approximately 70 % of adult men and 50 % of women in Germany are currently overweight or obese(Reference Mensink, Lampert and Bergmann6). Various studies have shown that excess weight contributes to CVD, some cancers and type 2 diabetes(Reference Bergström, Pisani and Tenet8, 9). The current epidemic reflects a long-term upward shift in the distribution of BMI across all populations(Reference Flegal, Carroll and Ogden10, Reference Dixon and Waters11). One explanation for the development of obesity is an energy imbalance caused by a combination of more sedentary lifestyles and an increase in consumption of energy (rich foods)(Reference Hill and Peters12Reference French, Story and Jeffery14).

National surveys conducted in Germany between 1985 and 2002 showed an increase in the prevalence of obesity in both genders(Reference Helmert and Strube18), and according to the German National Health Interview and Examination Survey(15) only 13 % of the German adult population met the German guideline of being physically active three times per week for at least 30 min in 1998. A study conducted in Bavaria, Germany, revealed that fewer than a third of the 893 participants met the recommended physical activity levels and, in addition to reduced sports activities, obesity was also linked to increased television viewing and use of computers(Reference Schaller, Seiler and Himmerich16). Furthermore, food consumption in the German population has changed over the years. Although there has been a positive increase in fish, poultry, vegetable and fruit consumption, there has also been an increase in sweets and fried potato dishes(17).

The first study to introduce the idea of a population-wide energy gap and its estimation model was that of Hill et al.(Reference Hill, Wyatt and Reed19). Using data from the National Health and Nutrition Examination Survey and the Coronary Artery Risk Development in Young Adults study(Reference Lewis, Smith and Wallace20), they estimated the distribution of the rate of weight gain within the population over a period of 8 years. With the assumption of a gradual/linear rate of gain and that each pound of body weight equals 14 644 kJ (3500 kcal), they calculated the annual energy accumulated. The estimated energy accumulation for 90 % of the population was approximately 209 kJ (50 kcal)/d. Thus, it was hypothesized that by some combination of increasing energy expenditure and reducing energy intake by 419 kJ (100 kcal)/d, most of the weight gain in the US population could be prevented. In China, the estimated energy gap for the population was 188 kJ (45 kcal)/d(Reference Zhai, Wang and Wang21). In Australia, using data from the Australian Longitudinal Study on Women’s Health, an average weight gain of approximately 0·5 kg/year for women aged 45–55 years was found, which equates to an energy imbalance of only approximately 42 kJ (10 kcal)/d(Reference Brown, Williams and Ford22). In Swedish adults, the estimated energy gap was 34 kJ (8·2 kcal)/d for men and 52 kJ (12·4 kcal)/d for women(Reference Berg, Rosengren and Aires23).

Müller and his colleagues(Reference Plachta-Danielzik, Landsberg and Bosy-Westphal24) used the same approach to calculate the energy gap in German children using actual measures of fat mass and fat-free mass to calculate energy gain. They found mean daily energy increases of 89 kJ (21·2 kcal)/d in boys and 194 kJ (46·4 kcal)/d in girls aged 10–14 years. The 90th percentile of energy gap in these children who became overweight was 301 kJ (72 kcal)/d for girls and 223 kJ (53·2 kcal)/d in boys. The authors estimated that reductions in energy intakes of 419–586 kJ (100–140 kcal)/d should prevent overweight in German children.

The objective of the present study is to estimate the energy gap of the German adult population using results from national health surveys conducted between 1985 and 2003 by using the average weight gain over the 17-year period and translating the kg (fat) into kJ (kcal) in order to calculate the estimated energy accumulation per year (and per day).

Methods

The published results from four national health surveys conducted between 1985 and 1998 (1984–1986, 1987–1988, 1990–1992 and 1998)(Reference Forschungsverbund25, 26) were used for the analysis. Each cohort included between 2300 and 3700 participants, with a total of 22 807 participants (11 248 men and 11 559 women). The German national health surveys (Bundesgesundheitssurvey, ‘Federal Health Survey’) were used to determine the health status of the German adult population. The surveys were conducted by the Robert Koch-Institute on behalf of the German Ministry of Health. The data from the first two health surveys only include West Germany, and body weight and height were individually measured in a laboratory setting.

In addition, three surveys of the ‘Bertelsmann Health Monitor’ in 2002–2003 (Spring 2002, Fall 2002 and Spring 2003)(Reference Böcken, Braun and Schnee27) with a total of 3707 participants (1736 men and 2071 women) were used. For data collection of the ‘Bertelsmann Health Monitor’, at each data point, approximately 50 000 households across Germany were contacted and the three surveys were merged to report mean height and weight for 2002. The survey was used to obtain information and trends about the existing German health-care sector. Body weight and height were assessed using self-reported measures. Given the existing bias with regard to self-reported height and weight, both measures were adjusted accordingly using results from the national health survey 1984–1986, in which both direct and self-reported measures of height and weight were collected. More details about the adjustments can be found in Helmert and Strube(Reference Helmert and Strube18). All included samples were representative for the German population aged 25–69 years.

For the analysis, the published body weight data, separated by gender, of the seven health surveys reported in Helmert and Strube(Reference Helmert and Strube18) were used to estimate the energy gap in the German population.

Results

Men and women aged 25–65 years using the population-based data from the surveys mentioned above were included to estimate the energy gap in the German population. Table 1 shows the body height, weight and BMI in men and women aged 25–69 years between 1985 and 2002.

Table 1 Mean body height, weight and BMI of German adults (aged 25–69 years) by gender using national health surveys (1985–2002; n 26 614)Footnote *

* Retrieved and modified from Helmert and Strube(Reference Helmert and Strube18).

Pooled means from all three ‘Bertelsmann Health Monitor’ surveys.

Given these data and assuming a linear rate of gain, the average annual weight gain among men was 0·22 kg and 0·32 kg among women over the 17-year period. Assuming weight gain is normally distributed, 90 % of the population gained < 0·54 kg/year (for men = 0·49 kg/year; for women = 0·54 kg/year).

Assuming that each kilogram of weight gained represents 32 238 kJ (7700 kcal), the estimated average energy accumulation is 19 kJ (4·64 kcal)/d in men and 28 kJ (6·75 kcal)/d in women aged 25–69 years. The distribution of estimated energy accumulation for 90 % of the German population is < 50 kJ (12 kcal)/d; men = 43 kJ (10·33 kcal)/d; women = 48 kJ (11·40 kcal)/d.

Since direct measures of energy cannot be used in large population studies, we used estimations of energy efficiency by Hill et al.(Reference Hill, Wyatt and Reed19) and Brown et al.(Reference Brown, Williams and Ford22). The authors assumed an energy efficiency of at least 50 %; meaning for every excess 419 kJ (100 kcal) consumed, at least 209 kJ (50 kcal) of energy are deposited in energy stores. With an energy efficiency of approximately 50 %, the yearly weight gain in the German population could be prevented with < 100 kJ (24 kcal) reduction in energy intake or increase in energy expenditure per day in 90 % of the population. Figure 1 shows the hypothetical weight gain projection for men and women in Germany with and without the 100 kJ (24 kcal)/d energy gap.

Fig. 1 Hypothetical weight projection by gender with and without the 100 kJ (24 kcal)/d energy gap. The solid lines indicate the projected weight gain in the population without any changes, whereas the dotted lines indicate weight maintenance with an energy gap of <100 kJ (24 kcal)/d ( , men; , women)

Discussion

In the present analysis, we estimated the annual energy accumulation of the German adult population using cross-sectional population-based data from several representative surveys. We determined that by a combination of reducing energy intake minimally and increasing energy expenditure modestly further weight gain could be prevented in Germany.

Thus, the magnitude of this daily imbalance between energy intake and energy expenditure is estimated to be relatively small, with energy accumulations of approximately 63 kJ (15 kcal)/d accounting for weight gain in US population studies(Reference Hill, Wyatt and Reed19) and even less for children(Reference Plachta-Danielzik, Landsberg and Bosy-Westphal24, Reference Wang, Gortmaker and Sobol28). However, this gap can lead to an annual weight gain of at least 2 pounds per year and 20 pounds in 10 years(Reference Hill, Wyatt and Reed19).

Given the current prevalence of overweight and obesity in Germany and its rather notable increase in incidence per year, it is surprising that 90 % Germans appear to gain only an estimated ≤ 50 kJ (≤ 12 kcal)/d, compared to approximately 209 kJ (50 kcal)/d in 90 % of the US population. German children (10–14 years) appear to be gaining more than adults(Reference Plachta-Danielzik, Landsberg and Bosy-Westphal24). For the German adult population, an approach that reduces energy intake by 100 kJ (24 kcal)/d could potentially prevent further weight gain in approximately 90 % of the population and thus at least stabilize obesity rates. This equals < 100 g of fat-reduced yoghurt or approximately 5 min of fast walking.

The use of population-based data collected by others limits the extent of the present analysis, and in general self-reported information is inferior to actual weight measurements. Given our lack of access to original data sets, we could not adjust for possible confounders such as changes in smoking status or socio-economic characteristics. In addition, using existing aggregated data does not allow for the adjustment of possible age or gender differences over the years. Since original data were not available, it was not possible to determine whether changes in age or gender distribution might exist and whether they might have influenced the changes in weight over the years.

However, we assume that the data used in the reference study adequately adjusted for potential confounders and sample distribution changes. It is also not the intention of the authors to calculate the precise caloric differences and weight changes of the German population over the years, but rather to point out that the estimated energy imbalance of this magnitude is in all likelihood a result of the increase in overweight and obesity in the population.

The energy gap concept of Hill et al.(Reference Hill, Wyatt and Reed19) has been criticized as not accounting for the fact that obese individuals have accumulated more stored energy than lean individuals(Reference Swinburn, Sacks and Lo29). Hill et al.(Reference Hill, Peters and Wyatt30) clarify this by distinguishing between the energy gap for prevention of additional weight gain (which does not depend on stored energy) and the energy gap for maintenance of weight loss. The energy gap for the treatment of obesity is much larger due to the reduction in energy requirements after weight loss(Reference Hill, Peters and Wyatt30). It is not suggested that this approach can restore the population to normal weight, but rather that it can stabilize obesity rates and prevent further weight gain.

It should be noted that in calculating the energy gap, Hill et al.(Reference Hill, Wyatt and Reed19) used an energy efficiency of 50 % for storage of excess energy in order to model the most conservative case. In reality, excess energy may be stored with greater efficiency under most conditions. If one assumes that the efficiency of storage of excess energy is > 50 %, the energy gap would be reduced.

Even though the energy gap is based on theoretical estimations and assumptions and empirical results are urgently necessary, we believe that the energy gap in the German population is still small and further weight gain could be prevented using the small-changes approach. This method emphasizes the importance of small increases in physical activity, as well as small decreases in food intake(Reference Hill, Wyatt and Reed19, Reference Hill31). Both changes can be achieved with relatively minimal effort, for example walking approximately 1 km/d, which equals approximately 167 kJ (40 kcal) of energy expenditure or by reducing portion size modestly with each meal every day. There is already existing evidence that the small-changes approach can be effective. Dolan et al.(Reference Dolan, Weiss and Lewis32) and Bravata et al.(Reference Bravata, Smith-Spangler and Sundaram33) show the feasibility and effectiveness of making small changes to increase physical activity. School and family programmes using the small-changes approach have also shown promising results(Reference Stewart, Dennison and Lohl34Reference Rodearmel, Wyatt and Stroebele36). In regard to dietary behaviour, Rolls et al.(Reference Roll, Drewnowski and Lediwke37) have consistently shown that decreases in energy density produce small reductions in energy intake. With the use of the small-changes approach, we believe that it might be possible to stabilize obesity rates in most populations.

We believe that making small changes to everyday living is more feasible and sustainable than big changes such as complete diet alterations or the transformation from a sedentary to a highly active lifestyle. In addition, our current environment does not support an active lifestyle. Small environmental changes could include various improvements such as more bike paths in cities, better public transportation systems or easier access to healthy foods in public places such as schools and cafeterias. In the United States, there are already initiatives by various entities such as the American Society of Nutrition, the Institute of Food Technology and the International Food Information Council, which support the small-changes approach and are ready to contribute to the goal of changing people’s lifestyle behaviour in collaboration with the private sector and the government(Reference Hill31). Given the rise in obesity rates in Germany, creating a German initiative with similar goals supported by various private and governmental institutions and stakeholders of different industries such as food supply or sporting goods is urgently needed. It is crucial that the public and private sector work together in order to create an environment that encourages people to make small changes towards a healthier lifestyle.

Acknowledgments

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. There are no conflicts of interest. N.S. and J.O.H. analysed the data and drafted and revised the manuscript. N.S. wrote the first draft of the manuscript. J.O.H. and S.N.W. made substantial contributions to the interpretation and writing of the manuscript and its revision.

References

1. Yoon, KH, Lee, JH, Kim, JW et al. (2006) Epidemic obesity and type 2 diabetes in Asia. Lancet 368, 16811688.Google Scholar
2. Campbell, T & Campbell, A (2007) Emerging disease burdens and the poor in cities of the developing world. J Urban Health 84, i54i64.Google Scholar
3. Wang, Y & Beydoun, MA (2007) The obesity epidemic in the United States – gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiol Rev 29, 628.Google Scholar
4. Fezeu, LK, Assah, FK, Balkau, B et al. (2008) Ten-year changes in central obesity and BMI in rural and urban Cameroon. Obesity 16, 11441147.Google Scholar
5. Statistisches Bundesamt (2006) Leben in Deutschland. Haushalte, Familien und Gesundheit – Ergebnisse des Mikrozensus 2005 (Living in Germany. Households, Families and Health – Results from the Micro census 2005). Wiesbaden, Germany: Statistisches Bundesamt.Google Scholar
6. Mensink, GBM, Lampert, T & Bergmann, E (2005) Übergewicht und Adipositas in Deutschland 1984–2003 (Overweight and obesity in Germany 1984–2003). Bundesgesundheitsblatt Gesundheitsheitsforschung Gesundheitsschutz 48, 13481356.Google Scholar
7.World Health Organization (2009) Regional Office for Europe. Highlights on health. http://www.euro.who.int/eprise/main/ZZ_ToBeDeleted/CHH/SWE/chap2/20041123_4 (accessed July 2005).Google Scholar
8. Bergström, A, Pisani, P, Tenet, V et al. (2001) Overweight as an avoidable cause of cancer in Europe. Int J Cancer 91, 421430.Google Scholar
9. World Health Organization (2002) The World Health Report 2002: Reducing Risks, Promoting Healthy Life. Geneva: WHO.Google Scholar
10. Flegal, KM, Carroll, MD, Ogden, CL et al. (2002) Prevalence and trends in obesity among US adults, 1999–2000. JAMA 288, 17231727.Google Scholar
11. Dixon, T & Waters, AM (2003) A Growing Problem: Trends and Patterns in Overweight and Obesity among Adults in Australia, 1980 to 2001. Bulletin no. 8. Canberra: Australian Institute of Health and Welfare.Google Scholar
12. Hill, JO & Peters, JC (1998) Environmental contributions to the obesity epidemic. Science 280, 13711374.Google Scholar
13. Hill, JO & Melanson, EL (1999) Roundtable consensus statement: overview of the determinants of overweight and obesity: current evidence and research issues. Med Sci Sport Exerc 31, S515.Google Scholar
14. French, SA, Story, M & Jeffery, RW (2001) Environmental influences on eating and physical activity. Annu Rev Public Health 22, 309335.Google Scholar
15. Robert Koch-Institut, Statistisches Bundesamt (2007) Gesundheitsberichterstattung des Bundes. Gesundheit in Deutschland (Government Health Report. Health in Germany). Berlin: Robert-Koch-Institut.Google Scholar
16. Schaller, N, Seiler, H, Himmerich, S et al. (2005) Estimated physical activity in Bavaria, Germany, and its implications for obesity risk: results from the BVS-II Study. Int J Behav Nutr Phys Act 2, 6.Google Scholar
17. Deutsche Gesellschaft für Ernährung (2008) Ernährungsbericht 2008 (Nutrition Report 2008). Bonn: Deutsche Gesellschaft für Ernährung.Google Scholar
18. Helmert, U & Strube, H (2004) Trends in the development and prevalence of obesity in Germany between 1985 and 2002. Gesundheitswesen 66, 409415.Google Scholar
19. Hill, JO, Wyatt, HR, Reed, GW et al. (2003) Obesity and the environment: where do we go from here? Science 299, 853855.Google Scholar
20. Lewis, CE, Smith, DE, Wallace, DD et al. (1997) Seven-year trends in body weight and associations with lifestyle and behavioural characteristics in black and white young adults: the CARDIA study. Am J Public Health 87, 635642.Google Scholar
21. Zhai, F, Wang, H, Wang, Z et al. (2008) Closing the energy gap to prevent weight gain in China. Obes Rev 9, Suppl. 1, 107112.Google Scholar
22. Brown, WJ, Williams, L, Ford, JH et al. (2005) Indentifying the energy gap: magnitude and determinants of 5-year weight gain in midage women. Obes Res 13, 14311441.Google Scholar
23. Berg, C, Rosengren, A, Aires, N et al. (2005) Trends in overweight and obesity from 1985 to 2002 in Göteborg, West Sweden. Int J Obes 29, 916924.Google Scholar
24. Plachta-Danielzik, S, Landsberg, B, Bosy-Westphal, A et al. (2008) Energy gain and energy gap in normal-weight children: longitudinal data of the KOPS. Obesity 16, 777783.Google Scholar
25. Forschungsverbund, DHP (editor) (1998) Die Deutsche Herz-Kreislauf-Präventionsstudie. Design und Ergebnisse (The German Cardiovascular Prevention Study). Bern: Hans Huber.Google Scholar
26. Robert Koch-Institut (1998) Bundesgesundheitssurvey 1998. Erfahrungen, Ergebnisse, Perspektiven (German Federal Health Survey). Gesundheitswesen 61, 55222.Google Scholar
27. Böcken, J, Braun, B & Schnee, M (editors) (2002) Gesundheitsmonitor 2002 (Health Monitor 2002). Die ambulante Versorgung aus Sicht der Bevölkerung und Ärzteschaft. Gütersloh: Bertelsmann Stiftung.Google Scholar
28. Wang, YC, Gortmaker, SL, Sobol, AM et al. (2007) Estimating the energy gap among US children: a counterfactorial approach. Pediatrics 118, e1721e1733.Google Scholar
29. Swinburn, BA, Sacks, G, Lo, SK et al. (2009) Estimating the changes in energy flux that characterize the rise in obesity prevalence. Am J Clin Nutr 86, 17231728.Google Scholar
30. Hill, JO, Peters, JC & Wyatt, HR (2009) Using the energy gap to address obesity: a commentary. J Am Diet Assoc 109, 18481853.Google Scholar
31. Hill, JO (2009) Can a small-changes approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and the International Food Information Council. Am J Clin Nutr 89, 447484.Google Scholar
32. Dolan, MS, Weiss, LA, Lewis, RA et al. (2006) Take the stairs instead of the escalator: effect of environmental prompts on community stair use and implications for a national ‘small steps’ campaign. Obes Rev 7, 2532.Google Scholar
33. Bravata, DM, Smith-Spangler, C, Sundaram, V et al. (2007) Using pedometers to increase physical activity and improve health. JAMA 298, 22962304.Google Scholar
34. Stewart, JA, Dennison, DA, Lohl, HW et al. (2004) Exercise level and energy expenditure in the Take 10! in-class physical activity program. J Sch Health 74, 397400.Google Scholar
35. Rodearmel, SJ, Wyatt, HR, Barry, M et al. (2006) A family-based approach to preventing excessive weight gain. Obesity (Silver Spring) 14, 13921401.Google Scholar
36. Rodearmel, SJ, Wyatt, HR, Stroebele, N et al. (2007) Small changes in dietary sugar and physical activity as an approach to preventing excessive weight gain: the America On the Move family study. Pediatrics 120, 28692879.Google Scholar
37. Roll, BJ, Drewnowski, A & Lediwke, JH (2005) Changing the energy density of the diet as a strategy for weight management. J Am Diet Assoc 105, S98S103.Google Scholar
Figure 0

Table 1 Mean body height, weight and BMI of German adults (aged 25–69 years) by gender using national health surveys (1985–2002; n 26 614)*

Figure 1

Fig. 1 Hypothetical weight projection by gender with and without the 100 kJ (24 kcal)/d energy gap. The solid lines indicate the projected weight gain in the population without any changes, whereas the dotted lines indicate weight maintenance with an energy gap of <100 kJ (24 kcal)/d (, men; , women)