Research topics

Obesity measures

The main aim of Fin-HIT is to explore risk and protective factors for excess weight / weight gain. Therefore, we need objective measures of body size and shape such as height, weight and waist circumference. Body mass index (BMI; kg/m2) is a widely used measure to determine overweight and obesity in children and adolescents. However, BMI is more complicated to use among children than adults, since it depends on age and sex, and it is often referred to as BMI-for-age or BMI z-score.

There are two international reference values to classify underweight, normal weight, overweight and obesity in children: the International Obesity Task Force (IOTF) and the WHO growth reference. The prevalence of overweight is slightly overestimated by the WHO growth reference 2007 compared with the IOTF. IOTF incorporates survey data from Brazil, Great Britain, Hong Kong, Singapore, United States, and The Netherlands and is currently utilized in our cohort.

Waist-to-height ratio, calculated by dividing the waist circumference (WC) by height, has recently gained attention as a measure for central obesity in children. The waist-to-height ratio may have an advantage over BMI, which does not provide any information about body fat distribution or body shape. It is considered a more reliable predictor of cardiovascular disease risk in children and adolescents than BMI.

A commonly used measure in Finland is weight-for-height. New Finnish references for weight-for-height were constructed in 2011.

Microbiota

The microbes living in or on humans (the human microbiome) keep us healthy by digesting food, strengthening the immune system and helping to prevent pathogens from invading tissues and organs. The microbiota plays a major role in both health and disease. Most of the microbiota studies have focused on gut, but less is known about the oral and saliva microbiota; their determinants and possible associations with various health outcomes are yet to be explored.

In humans, different salivary bacteria were found between vegans and omnivores (plant- and animal-based diet). We are aiming to identify saliva bacteria that is linked to the development of obesity or signs of metabolic syndrome. In addition, we are exploring different determinants of saliva microbiota diversity and composition (e.g. diet, antimicrobial drugs, oral health, host genetics). Recently, we found a significant difference in microbial diversity and composition in saliva and differently abundant bacteria between body sizes compared with normal weight. The findings will have several implications including technological innovations, but also involve practices in health care and dental services.

Dental caries

Dental caries, also known as tooth decay, is a major health problem worldwide, likely associated with obesity. It is common among both adults and children, but especially children and adolescents are at risk. Besides oral hygiene, frequent consumption of dietary sugars is the leading cause of caries; bacteria in the oral cavity break down dietary sugars and produce acids that destroy tooth enamel, slowly leading to tooth decay. The saliva microbiota may play a critical role in maintaining oral health, and changes in it may lead to various diseases including caries. The microbial presence and activity in saliva could be an indicator of oral health status, and caries can be understood as a shift of the oral microbiota from the commensal to pathogenic bacteria. We are interested to map out the associations between caries, obesity and sugar consumption, and moreover, to study the saliva microbiota profiles in children with and without caries. The purpose is to expand our understanding of the microbial etiology of caries in children, and hopefully provide novel therapeutic strategies for the prevention of caries.

Genetics

Beyond other factors, genetic variants contribute to weight development and BMI. Common obesity is a complex trait that is affected by multiple common genetic variants, which are likely to interact with lifestyle factors, modifying our susceptibility to weight gain. To date, over 100 common genetic variants have been consistently linked with BMI, but together they explain less than 3% of the variation in adult BMI. One of such variants is fat mass- and obesity-associated gene (FTO). More interestingly, the impact of genetic variants on BMI may vary during the life course.

There are situations in which obesity results from the mutation or defect in a single gene (monogenetic obesity). These are rare, early-onset, extreme conditions that may present with additional clinical features including endocrine and mental disorders.

Epigenetic alterations are suspected to contribute to the development of obesity. Epigenetic processes involve altering gene activity without altering the DNA sequence, resulting in phenotypic changes, such as obesity. DNA methylation, the most well studied epigenetic mark, is affected by various lifestyle factors. The epigenetic change process occurs gradually with ageing, smoking, antibiotics, air pollution, and others.

Currently, we are interested to identify important genetic and epigenetic factors, and to evaluate how these factors are associated with weight gain and obesity in adolescents.

Eating behaviour

Poor diet and eating habits during childhood are major contributing factors for various noncommunicable diseases. Eating habits are affected by personal preferences as well as cultural, religious, economical, environmental, and even political factors. Adolescence is a transition period during which eating habits evolve.

The traditional Finnish foods are, among others, milk or butter milk, cooked vegetables and dark grain bread, which are part of a healthy diet. Typical Finnish meal pattern consists of a breakfast, a warm lunch, a warm dinner, and two snacks. Finnish children receive a daily warm lunch at school for free, which is very unique to have, even in Nordic countries. There is room for improvement in adolescents’ diets, though: on average, they consume insufficiently fruits and vegetables, and favour sugary foods and soft drinks.

Adolescents’ craving for sugar can partly be blamed for innate preference for sweet taste, driven by genetics and modified by an exposure to sweet foods. Preference for sweet taste is at strongest in childhood but it decreases with age. Children and adolescents’ sugar consumption is of concern as it can deteriorate dietary quality, have adverse health effects and lead to weight gain. Sugary foods and drinks are typically energy-dense and nutrient-poor, and can replace more nutritious foods in the diet. Especially sugar-sweetened beverages are troublesome as they do not promote satiety response the same way as sugar in a solid form does.

Food consumption can be measured with various methods and on several levels. We have used a food frequency questionnaire that indicates how many times a week the respondent eats or drinks certain food items. We are interested in associations of different eating behaviours with weight status, weight gain, and other health outcomes in adolescents.

Physical activity and screen time

Physical activity can be defined as any bodily movement produced by the contraction of skeletal muscles that increases energy expenditure above a basal level. Exercise, in the other hand, refers to physical activity that is planned, structured, repetitive and performed with the goal of improving health or fitness. In short, all exercise is physical activity, but not all physical activity is exercise.

Sedentary behaviour (from the Latin sedere, ‘to sit’) refers to any waking behaviour that does not increase energy expenditure substantially above the resting level while sitting, reclining or lying (e.g. sitting in an automobile). Further, sedentary screen time refers to the time spent using a screen-based devise (e.g. smartphone, tablet, computer, television) while being sedentary (= sitting, reclining or lying).

In the Fin-HIT, we have assessed both the children’s and their guardians’ physical activity and screen time with a questionnaire when the children were around 9-12 years old and again at a follow-up when they were 13-15 years old. The purpose is to examine whether and how physical activity and screen time are related to weight, weight gain and other aspects of the children’s health.

Autoimmune diseases

Autoimmune diseases are chronic diseases caused by an abnormal immune response toward a person’s own healthy tissues. For unknown reasons, the prevalence of many autoimmune diseases in children such as type 1 diabetes mellitus, autoimmune thyroiditis, juvenile idiopathic arthritis and inflammatory bowel disease has been increasing in the past decades. Our hypothesis is that these diseases might have mutual risk factors. Thus, it is important to recognize the risk factors in order to prevent further increases in the prevalence.

Our aim in the Fin-HIT study is to search for potential environmental factors that might trigger autoimmune diseases. We search these risk factors among maternal and perinatal factors, dietary patterns, body composition, exposure to antibiotics (pre- and perinatally) and change of oral microbiota. Our findings will increase the understanding of the role of environmental factors in the development of autoimmune diseases, and could, therefore, be utilized in prevention. They may also provide tools for early detection of autoimmune diseases.

 

References:

Brambilla P, Bedogni G, Heo M, Pietrobelli A. Waist circumference-to-height ratio predicts adiposity better than body mass index in children and adolescents. Int J Obes (Lond). 2013;37(7):943–6.

Cole TJ, Lobstein T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes. 2012 Aug;7(4):284-94.

de Onis M, Onyango AW, Borghi E et al. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007 Sep;85(9):660-7.

Fidler Mis N, Braegger C, Bronsky J et al. Sugar in Infants, Children and Adolescents: A Position Paper of the European Society for Paediatric Gastroenterology, Hepatology and Nutrition Committee on Nutrition. J Pediatr Gastroenterol Nutr. 2017 Dec;65(6):681–696.

Hayden C, Bowler JO, Chambers S, et al. Obesity and dental caries in children: a systematic review and meta-analysis. Community Dent Oral Epidemiol 2013; 41; 289–308.

Hoppu U, Lehtisalo J, Tapanainen H, Pietinen P. Dietary habits and nutrient intake of Finnish adolescents. Public Health Nutr. 2010 Jun;13(6A):965–72.

Jensen CB, Ängquist LH, Mendall MA, et al. (2018) Childhood body mass index and risk of inflammatory bowel disease in adulthood: A population-based cohort study. Am J Gastroenterol 113: 694-701.

Mikkilä V, Räsänen L, Raitakari O, Pietinen P, Viikari J. Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in Young Finns Study. BR J NUTR. 2005;93(6):923–31.

Physical Activity Guidelines for Americans 2nd version. U.S. Department of Health and Human Services 2018. https://health.gov/paguidelines/second-edition/pdf/Physical_Activity_Guidelines_2nd_edition.pdf. Accessed 20 February 2019.

Roos E, Prättälä R. Meal Pattern and Nutrient Intake Among Adult Finns. Appetite. 1997;29(1):11–24.

Saari A, Sankilampi U, Hannila ML, Kiviniemi V, Kesseli K, Dunkel L. New Finnish growth references for children and adolescents aged 0 to 20 years: Length/height-for-age, weight-for-length/height, and body mass index-for-age. Ann Med. 2011 May;43(3):235-48.

Shenoi S, Shaffer ML, Wallace CA. (2016) Environmental Risk Factors and Early‐Life Exposures in Juvenile Idiopathic Arthritis: A Case–Control Study. Arthritis Care & Research 68: 1186-1194.

Tremblay MS, Aubert S, Barnes JD et al. Sedentary Behavior Research Network (SBRN) – Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act 2017;14:75.

Virta LJ, Saarinen MM, Kolho K-. (2017) Inflammatory Bowel Disease Incidence is on the Continuous Rise Among All Paediatric Patients Except for the Very Young: A Nationwide Registry-based Study on 28-Year Follow-up. J Crohns Colitis 11: 150-156.

WHO Child Growth Standards. Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age. Methods and development. WHO 2006

Yang F, Zeng X, Ning K, et al. Saliva microbiomes distinguish caries-active from healthy human populations. ISME J. 2012; 6(1):1-0.

Zalewski BM, Patro B, Veldhorst M et al. Nutrition of Infants and Young Children (One to Three Years) and its Effect on Later Health: A Systematic Review of Current Recommendations (Early Nutrition Project). Crit. Rev. Food Sci. Nutr. 2017, 57, 489–500.