Shifting weights, shifting trends a joinpoint analysis of BMI changes (2008–2022)

Authors

Abstract

Aim According to the World Health Organization (WHO) European Regional Office’s 2022 European Obesity Report, Türkiye ranks first in Europe for overweight and obesity rates in both sexes combined and among women. In this context, the present study examined long-term trends in obesity prevalence, physical activity levels, and fruit and vegetable consumption in Turkey.
Methods This study used secondary data from the Türkiye Health Survey conducted by the Turkish Statistical Institute (TURKSTAT). The indicators analyzed included “Distribution of individuals’ body mass index by sex, 2008–2022” and “Indicators related to physical activity and fruit and vegetable consumption, 2014–2022.” Trends were evaluated using Joinpoint regression analysis to identify statistically significant changes over time.
Results Since 2008, the prevalence of overweight and obesity has increased. The most pronounced rise in obesity occurred between 2012 and 2014, with an increase of 2.7%. Statistically significant increases in obesity were observed among women and in the total population between 2008 and 2014 (p < 0.000001). Physical inactivity increased throughout the study period, with higher and faster growth observed among women. Additionally, between 2014 and 2022, a statistically significant increase was detected in the proportion of women (p < 0.000001) and men (p < 0.000001) who reported never consuming fruits and vegetables.
Conclusion In Turkey, especially among Generation Y, unhealthy dietary habits, insufficient physical activity, and weight gain are becoming increasingly common. These findings highlight the urgent need for targeted health action.

Keywords

Introduction

The World Health Organization (WHO), through the multinational monitoring of trends and determinants in cardiovascular disease (MONICA) project conducted between 1983 and 1986, identified that the majority of adults were at risk of disease due to overweight or obesity, and for the first time defined obesity as a global epidemic ¹. Since 2004, the WHO has transformed obesity prevention into global strategies, developing health policies that support the United Nations Millennium Development Goals ². In 2014, the WHO warned that in Africa, the number of overweight or obese children had nearly doubled since 1990; that childhood obesity must be prevented; and that obesity, known as a risk factor for adult obesity and non-communicable diseases, must be urgently reduced to protect the health of both current and future generations ³. Indeed, in 2022, 43% of adults aged 18 and over were classified as overweight and 16% as obese, and in 2024, 35 million children under the age of five were assessed as overweight ^4,5,6,7. In fact, the 2016 report made an important observation by alerting generations. While classifying by age groups is undoubtedly valuable, I believe that addressing obesity on a generational basis—within the framework of “generations” as the WHO suggests—may help to better recognize the environmental impacts of what could be considered a pandemic of obesity.
Following Galton’s introduction of the concept of intergenerational transmission, the intergenerational transmission of obesity—shaped by genetic, income, health behavior, and environmental factors—has been recognized as a phenomenon that gave rise to the concept of the obesogenic environment ⁸. Overweight and obesity, through their adverse molecular and cellular alterations, resemble aging ⁹. In a study evaluating four generations, negative generational shifts in body mass index (BMI) were observed over time among those born in the 1960s, 1950s, and 1930s (Silent Generation, Baby Boomers, and Generation X), with younger generations having higher BMIs at the same age compared to older generations ⁹.
Furthermore, parent–offspring BMI correlations were found to be stronger in more recent generations than in earlier ones, and the correlation between the BMIs of those born in 1958 (Baby Boomers) and their offspring remained strong even after controlling for socioeconomic status and lifestyle factors ⁸. In addition, mothers are known to play a dominant role in the transmission of obesity within families, both through intrauterine programming and by influencing the development of their children’s health behaviors ¹⁰.
Indeed, the concept of “generation,” which reveals social differentiation over approximately 20-year periods and reflects the changes that societies undergo during these intervals—while primarily distinguished by age—can also be regarded as a more dynamic concept in this context ¹¹.
So, what has changed around us? In the first half of the 20th century, following the end of World War II, digital technology began to develop. Since the early 1970s, with computers gradually entering people’s lives, we have witnessed the dizzying pace of progress in computing and the internet—an era in which internet-based communication became central—known as the informatics revolution or Industry 3.0. We are now in the period of Industry 4.0, characterized by cyber-physical systems, the Internet of Things, the Internet of Services, and the integration of virtual and physical systems, along with the emergence of artificial intelligence ¹². This process, which has evolved from the Industrial Society (Society 3.0) to the Information Society (Society 4.0), continues to develop under the Super Smart Society (Society 5.0) model ¹³, shaping our lives and influencing our habits.
In this study, obesity—defined by WHO as a pandemic and known to have multifactorial influences—is examined within the context of the technological era in which humanity is almost surrounded by the interaction of technology with work, daily life, behaviors, health, and the environment. The presence of the Super Smart Society, artificial intelligence, and robotic life is also considered an environmental factor. Using data from the Türkiye Health Survey, this research evaluates the impact on generations (Generation Y and Z) in terms of physical exercise and fruit and vegetable consumption. By addressing obesity from a generational perspective—thus also assessing environmental factors alongside physical activity and dietary habits—this is considered to be the first study in Türkiye to evaluate national data in this context, potentially contributing to the field.

Materials and Methods

This study was designed as a retrospective and cross-sectional analysis using publicly available data sets regularly published by the Turkish Statistical Institute (TURKSTAT), specifically the “Indicators with Physical Activity and Fruit/Vegetable Consumption (2014–2022)” and “Body Mass Index Distribution of Individuals by Sex (2008–2022)” ¹⁴. The general purpose of the Türkiye Health Survey is to outline the health profile of individuals and to collect information on health indicators, which constitute a significant component of the development indicators reflecting a country’s level of advancement. This survey enables international comparisons and provides insights into national needs. The dataset is nationally representative and internationally comparable, with available data for the years 2008, 2010, 2012, 2014, 2016, 2019, and 2022.
Body Mass Index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m²). The BMI classifications used were as follows: Underweight: BMI < 18.50, Normal weight: 18.50 ≤ BMI < 25.00, Pre-obese (Overweight): 25.00 ≤ BMI < 30.00, Obese: BMI ≥ 30.00. Physical activity was assessed based on the time spent on health-enhancing, non-work-related aerobic physical activity. Individuals were classified into five categories: no physical activity, less than 60 minutes, 60–150 minutes, 150–300 minutes, and more than 300 minutes per week. Fruit and vegetable consumption was evaluated according to the number of portions consumed daily and categorized as follows: none, 1–4 portions, and 5 or more portions.
Ethical ApprovalIn accordance with Turkish Statistical Law No. 5429, data obtained from official publications or databases within the scope of the Official Statistics Portal may be reused without prior permission, provided that proper citation is given. The study was conducted in accordance with the principles of the Declaration of Helsinki. As the research was based solely on publicly available internet data, no ethics committee approval was required or obtained.
Statistical AnalysisTrends over time were analyzed using Joinpoint regression analysis (Version 5.0.1, National Cancer Institute, Bethesda, Maryland, USA; http://surveillance.cancer.gov/joinpoint/). The Annual Percentage Change (APC) and corresponding 95% Confidence Intervals (CI) were calculated to evaluate the trends observed.
Reporting GuidelinesThis study was reported in accordance with the STROBE guidelines.

Results

Since 2008, a decrease in the proportion of individuals with normal weight has been observed, while the prevalence of both overweight and obesity has increased (Supplementary Table 1 and Table 2). Notably, the highest increase in obesity was recorded between 2012 and 2014, with a rise of 2.7%. However, the statistically significant increase was observed between 2008 and 2014 in both obese women and the total population (p < 0.000001) (Supplementary Table 3).
In terms of gender distribution, overweight was more common among men, while obesity and underweight were more prevalent among women (Supplementary Figure 1).
Regarding physical activity, the proportion of physically inactive individuals increased over the years, with a predominance among women. In contrast, men were the majority among those who engaged in more than 300 minutes and between 60 and 150 minutes of physical activity per week (Supplementary Table 4).
However, a statistically significant increase was observed only among women who exercised less than 60 minutes per week during the 2014–2022 period (p < 0.000001). (Supplementary Table 5) (Supplementary Figure 2).
Interestingly, during the same period, a statistically significant decrease in physical activity was found among women exercising more than 300 minutes (p = 0.021196), as well as in the total population (p = 0.005599) and men (p < 0.000001). (Supplementary Table 5)
In terms of fruit and vegetable consumption, the majority of individuals reported consuming 1 to 4 portions per day, with women comprising the larger share in this category. However, among those who reported no consumption of fruits or vegetables, men were in the majority (Table 1) (Supplementary Figure 3). A statistically significant increase in the rate of no fruit and vegetable consumption was observed among both women (p < 0.000001) and men (p < 0.000001) between 2014 and 2022 (Supplementary Table 6).

Discussion

The years in which WHO first defined obesity as a global epidemic and established a global strategy correspond to the childhood and adolescence/early adulthood of Generation Y, and the childhood years of Generation Z ^1,11. The increase in obesity observed between 2008 and 2014 coincides with the early adulthood of Generation Y and the childhood stage of Generation Z. Therefore, during the periods we examined, we see an increase in adult obesity in Generation Y. This is because, between 1980 and 2005, the mean BMI increased from 24.1 to 25.5 kg/m² in men and ranged from 23.1 to 24.3 kg/m² in women ¹⁵. Most existing studies from Spain, Canada, Denmark, Portugal, South Australia, and Finland have also shown that obesity prevalence increased among both men and women between the mid-1990s and the early 2000s ¹⁶. The same trend is observed for the United States and the United Kingdom ¹⁷. Thus, the Turkish data are consistent with the findings of Loef and Pollard, indicating an upward trend in BMI. Furthermore, as in Godfrey’s study, this can also be interpreted as an effect of the increase in maternal obesity.
In addition, Generation Y can be considered a critical generation—not only as the first to be fully aware of obesity risks and to experience the development of social awareness and prevention strategies, but also because they are now parents themselves, making them significant both for their own health and that of their children. Moreover, the period of the highest obesity increase, 2.7% between 2012 and 2014, coincides with the young adulthood years of Generation Y. By contrast, Generation X—now aged 45–60—were young or middle-aged adults during the time when obesity was first recognized as a global epidemic. Indeed, between 1980 and 2005, their mean BMI increased from 23.3 to 25.8 kg/m², and the proportion of individuals with obesity rose from 3.3% to 12.8% ¹⁸. For this generation, awareness about obesity may have developed relatively late.
As for Generation Z, who were in their mid-to-late teens in 2022, they are at risk of increased overweight and obesity, but—unlike Generation Y—there is insufficient adult data to fully assess their impact, and future data will be needed for evaluation. However, both Generation Z and Generation Alpha are likely to contribute to the rise in obesity due to the significant global increase in the consumption of ultra-processed foods (UPFs)—including sugar-sweetened beverages (SSBs), sweet or salty packaged snacks, confectionery, processed meat products, ready-made meals, and refined grain products. Meta-analyses have shown that, particularly among children and adolescents, this pattern is an important risk factor not only for obesity but also for type 2 diabetes and cardiovascular disease ¹⁹. Indeed, our study also observed a statistically significant increase between 2014 and 2022 in the proportion of women and men who reported never consuming fruits and vegetables, indirectly supporting the notion of an increase in what could be described as unhealthy eating habits. A general trend of declining dietary quality appears to be widespread across the population.
Considering that nearly one-third of adults worldwide have been physically inactive since the 2000s—with a 23.4% increase—and that inactivity continues to rise, it seems inevitable that the 2030 physical activity targets will face significant setbacks. In about half of all countries and two-thirds of regions, there are upward trends in the prevalence of insufficient physical activity, and women are more likely than men to be physically inactive, which appears to be a contributing factor to rising obesity rates ⁷. At the country level, 136 nations are not on track to meet the 2030 physical activity targets, while 61 are considered to be on the right path. Of these 61, 22 are classified as being more likely to meet the targets with greater certainty—12 from high-income Western European countries, four from Oceania, and six from sub-Saharan Africa. This indicates that even in high-income countries, physical inactivity is increasing ⁷.
In our national data, unfortunately, we also see that a sedentary lifestyle has become more prevalent over the years, with this increase being more pronounced among women. While this offers an important clue as to how gender roles may shape participation in physical activity, the significant increase between 2014 and 2022 among women who engage in less than 60 minutes of exercise per week may also point to the existence of more systemic barriers to women’s access to and participation in physical activity—barriers that lie at the intersection of lifestyle, habits, and biological, cultural, and behavioral factors. Nevertheless, the globally increasing trend of physical inactivity cannot be overlooked.
Considering that the increase in obesity between 2008 and 2014 corresponds to early adulthood for Generation Y and childhood for Generation Z, we can note that the age cohorts observed in the study by Strain and colleagues also largely overlap with these generations. It is plausible to think that certain environmental factors—such as computer use—may have played a role here. In 2014, there were 1.8 billion people who frequently played computer or video games; in just six years, this number rose to 2 billion. The global average weekly gaming time increased from 8.45 to 12.38 hours, and while players span all ages, they are predominantly children and adolescents ²⁰. This suggests that part of the cause of increasing physical inactivity among these generations may be linked to internet and screen dependency.
According to Turkish Statistical Institute ²¹ data, total internet usage in Türkiye was 35.9% in 2008, rose to 53.8% in 2014, and reached 87.1% in 2023—indicating that the growth in physical inactivity may also be associated with technology-driven changes in environmental conditions. Moreover, during these extended screen times, children and adolescents are frequently exposed to food and beverage advertising and marketing strategies that, according to international nutrition standards, are deemed inappropriate for this age group. As Guo’s work notes ²², these advertisements often promote unhealthy food products, highlighting how physical inactivity and poor dietary habits are intertwined.

Limitations

The data used in this study are limited to the available dataset provided within the scope of the Turkish Statistical Institute’s Türkiye Health Survey. In particular, the absence of data on individuals under the age of 15 and the restricted access to certain variables have somewhat narrowed the scope of the study.

Conclusion

Evaluating generational patterns of obesity is not a simple matter. However, it is important to recognize that technological developments have introduced obesogenic environmental factors into our lives. Since the mid-19th century, with mechanization—and more revolutionary developments occurring from the 1980s onward—we can see that the mass production, distribution, and sale of food items such as bread, biscuits, cakes, pies, sauces, and meat products with increasingly varied formulations coincided with the youth and middle adulthood of Generation X and the childhood of Generation Y.
A study covering the years 1938–2001 for Canada, 1987–2003 for Brazil, and 1998–2012 for 79 countries, grouped by income level, shows that processed foods have evolved into meals that are more energy-dense, higher in harmful fats, sugar, and salt, and lower in fiber. We also see that consumption of these processed products is linked to overweight, obesity, and other metabolic diseases ²³. Furthermore, considering that low- and middle-income countries represent large markets and are likely to grow significantly in the next decade ²⁴, we can observe that the obesogenic environment has grown as part of industrial development, and that the risk of obesity associated with these environmental factors may continue to persist in less developed countries.
An analysis of 163 studies spanning nearly 100 years and involving 9,912 adults found that basal metabolic rate decreased in both sexes, with total energy expenditure, basal energy expenditure, and activity-related energy expenditure declining by approximately 0.34 MJ/day over the last century. When these declines in energy expenditure are combined with increased sedentary behavior—partly linked to high “screen time” (TV, computer, and phone use) ²⁵—we can conclude that the obesogenic environment is closely related to the industrial revolution.
When the patterns of change in energy expenditure components in men and women since the early 1990s are evaluated alongside the continuing development processes of the Industrial Society (Society 3.0), the Information Society (Society 4.0), and the Super Smart Society (Society 5.0) model, it becomes clear that changing food consumption and decreasing physical activity align with the concept of the obesogenic environment.
From the 1990s onward, we can also see how well-founded the WHO’s warnings have been. Given our country’s classification as a developing nation—with data showing declining fruit and vegetable consumption, a potentially growing market for ready-to-eat foods, and increasing obesity—it is understandable that reduced physical activity levels may also be linked to industrialization. Therefore, this study, by evaluating the obesity epidemic in the context of generations (a perspective rarely taken before), identifies that industrial developments may have contributed to the obesity epidemic in ways previously unrecognized. In this context, considering the potential to prevent obesity prevalence among Generation Z, Generation Alpha, and future generations, both global policy regulations and individualized prevention efforts—possibly incorporating computer software or robotic applications—should be considered. Since we are now in the Super Smart Society model, where robots are expected to become part of daily life, I believe that for generations born into this technology, both nutrition and physical inactivity will be the main issues.

Declarations

Abbreviations

APC: annual percentage change
BMI: body mass index
CI: confidence interval
MONICA: multinational monitoring of trends and determinants in cardiovascular disease
SSBs: sugar-sweetened beverages
STROBE: strengthening the reporting of observational studies in epidemiology
TURKSTAT: Turkish Statistical Institute
UPFs: ultra-processed foods
WHO: World Health Organization

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