Most readers of this blog know that children and adolescents have different nutritional requirements than adults and the elderly. However, did you know that what you eat at a certain age can impact your health many years later or even your offspring’s health?
Over the last 50 years, there has been a shift in understanding the causes of disease and contributors to health. Until the late 20th century, biomedical models dominated the understanding of illness. However, evidence started accruing for the role of social and behavioral contributors to illness, leading to newer bio-psychosocial models supplementing acute services with programs designed to manage chronic illnesses and change unhealthy lifestyle choices.
Studies in the 1980s showed that fetal events and experiences could influence adult health in mid-life, leading to newer life course models of health and disease. The latter indicated that social, psychological, and environmental factors operating early in life could significantly impact short- and long-term health outcomes. These observations resulted in the coining of the new concept “life course epidemiology” which, in other words, is the science examining risk factors across the lifespan and how they act differently depending on the age of exposure. Life course models have since expanded to include the contributions of multiple risks and protective factors operating throughout the lifespan to the course of health trajectories over time.
During the past 30 years of research on life course epidemiology, scientists have discovered that fetal exposure and exposure during developmental periods of life to risk factors have health effects many years later. For instance, a study on the Dutch famine during second World War II revealed that exposure to famine during childhood was related to a higher risk of diabetes during adulthood. Notably, those who starved most intensely during the war were the ones who had the highest risk of obesity and diabetes later in life.
How epigenetic factors can explain intergenerational risk transfer
Epigenetic modification refers to changes in gene expression that do not involve alterations to the underlying DNA sequence, such as DNA or hystone methylation, acetylation, phosphorilation, and other molecular changes. Animal and human studies have shown that these modifications can be passed down through generations and have trans-generational effects. For instance, being obese during pregnancy increases the risk of overweight and diabetes later in life in children. However, following a healthy diet during pregnancy is usually associated with lower adiposity in children. An interesting explaination of the latter phenomenon is that epigenetic modifications in specific genes are related to adipose regulation and an altered expression of genes related to appetite regulation.
Also, during pregnancy, glucose, free fatty acids, and inflammatory factors are transferred through the placenta, and they can have crucial metabolic effects resulting in more extensive adipose tissue. Breast milk can also transfer these molecules from the mother to the child. Eating a healthy diet before preconception can result in healthier body composition in the offspring, which is valid for the mother and the father (Fleming et al. 2018).
Epigenetic studies have also provided insight into the mechanisms of biological embedding, demonstrating how gene expression can be modified in response to environmental cues, resulting in lifelong changes in bio-behavioral function. Methylation alterations are present in the DNA of children who experienced adversity due to maternal stress in their early years. Positive environmental factors such as attentive caregiving, warmth, and nurturing behaviors, coupled with a secure family financial situation, can instead promote better future health. Health development is a complex, non-linear process that occurs in multiple dimensions and at various levels and phases. The developmental process resulting in the emergence of health cannot be fully understood using a traditional biomedical approach. Health development is sensitive to the timing and social structuring of environmental exposures and experiences. Time-specific pathways and socially-structured pathways both contribute to the process of biological embedding.
Recent studies in epigenetics and gene-environment interactions have led to a more nuanced understanding of how genes are regulated and expressed. Gene networks interact with each other and the environment in complex, dynamic ways that influence the development and function of biological systems. The post-genomic biological synthesis suggests that gene expression and the architecture and function of biological systems may be affected by both the nature and timing of environmental exposures.
The developmental origin of health and disease
The developmental origins of health and disease theory posited that under-nutrition during pregnancy influences fetal programming that can permanently shape the developing body’s structure, function, and metabolism, paving the way to diseases appearing decades later. The theory suggests that the fetus makes a predictive adaptive response, developing metabolic pathways best suited to a future nutrition-poor environment. After delivery, when nutrition is in plentiful supply, the infant’s metabolism is mismatched with an environment rich in cheap and plentiful calories, predisposing to the development of metabolic syndrome, relative insulin resistance, and obesity. Subsequent rapid catch-up growth after delivery appears to confer an even higher risk of adult-onset disease. Developmental origins theories acted as the foundation of early life course models of health. They shifted the time frame of interest for medical studies from months and years to decades and the entire lifespan.
Childhood obesity is a severe public health challenge worldwide, and there is growing interest in the role of diet quality in early childhood as a determinant of obesity risk. However, findings concerning diet quality and childhood obesity are inconsistent across studies, possibly due to limitations in study design and the use of BMI as a measure of adiposity.
Consistent scientific results support the protective role of breastfeeding on childhood obesity. Which mechanisms could be involved in this protective role is something that has long been discussed. Scientists suggested that breastfeeding could teach children self-regulate food intake. Also, breast milk contains oligosaccharides and hormones such as leptin and adiponectin, which can positively affect children and their gut microbiomes.
Interestingly, differences in diet quality at six months of age tend to persist later in life. At 12 months, 3, and 6 years of age, children with lower consumption of processed foods at six months also had a higher diet quality later. Okubo et al. (2015) used longitudinal data. They found that the overall quality of a child’s diet across early childhood showed solid independent associations with adiposity at age six but not with BMI. The study also observed tracking of a dietary pattern characterized by frequent consumption of fruits, vegetables, and fish from infancy to early childhood. These findings suggest that public health initiatives to improve the diet quality of young children need to start very early in life and that more vulnerable children may be readily identifiable in the population. The study highlights the limitations of using BMI to measure adiposity in early childhood and suggests that direct assessment of fat mass, such as DXA, may be more sensitive. Okubo et al. (2015) showed that the diet quality score does not sensibly change between the age of six months and six years, which also happens for body composition.
Norris et al. (2022) compared the BMI of children and adolescents (5-19 years) globally and found that adolescents are growing up during unprecedented changes in food environments, micronutrient deficiency, food insecurity, overweight, and obesity.
The Dunedin Multidisciplinary Health and Development Study (Poulton et al., 2015) is a 40-year longitudinal study with significant findings related to self-control, early conscientiousness, cannabis use, psychosocial distress, genetic risks, neurodegeneration, early-life adversity, and psychiatric conditions. The study has shown that self-control skills mastered in childhood are more important than socioeconomic status or IQ in predicting adults’ physical health, wealth, life satisfaction, addiction, crime, and parenting of the next generation. The research has also demonstrated that measuring early conscientiousness can identify which healthy patients will develop health problems in the future. Long-term cannabis use is associated with elevated risks for psychosis, periodontal disease, cognitive decline, and loss of IQ points. The study has also highlighted the association between psychosocial distress and accelerated telomere erosion, which affects the pace of aging and age-related disease, including persistent asthma since childhood.
Additionally, the study has investigated the effects of prospectively ascertained early-life adversity on adult physiology and physical health in midlife and found that early-life psychosocial stress leads to poor health and accelerated aging. The research has also demonstrated that the high cumulative prevalence of anxiety, depression, and substance dependence is about twice as high as previously reported. The findings suggest that genes tell us very little, and the combination of genes and environments matters most. Therefore, modifying the environment remains a sensible intervention strategy for improving health and development. The results of this study also emphasize the benefits of using digital retinal imaging technology in the study of schizophrenia.
The retina represents a non-invasive window on the condition of the vasculature inside the brain and body. One can use it to track changes in brain integrity and cognitive decline over the life course. Despite the many studies conducted on children and adults, research on nutrition during adolescence has received little funding.
Biological age vs. anagraphic age
The burden of chronic diseases associated with aging increases exponentially after the fifth decade of life. Therefore, we need more research on aging in young humans who have not yet developed age-related diseases. However, the main obstacle to studying aging in young adults is the lack of methods to quantify the pace of aging. The fact that aging can progress at different speeds in different individuals has led to a new concept, commonly referred to as “biological age” (Belsky et al. 2015). The latter represents how old someone’s cells and tissues are, based on physiological markers of aging. Notably, it often differs, for better or worse, with chronological age, which is the sheer number of years someone has been alive. It is impressive that the biological age can be ten years greater or smaller than the chronological age.
Belsky et al. (2015) examined a population-representative birth cohort of 1,037 young adults to test whether there was evidence of individual variation in aging. The hypothesis was that cohort members with “older” physiologies at age 38 had been aging faster than their same-aged peers with “younger” physiologies. The study found that some 38-year-old cohort members were biologically older than others, indicating that young adults age at different rates. Moreover, those with advanced biological age had experienced a more rapid pace of aging over the past 12 years compared to their biologically younger peers. Biologically older study members reported having more difficulties with physical functioning and showed a decline in cognitive performance compared to their biologically younger peers. These findings indicate that even in young adults, some individuals may be aging more rapidly than others, which can influence physical and cognitive functioning indicators. The study also found that biologically older study members perceived themselves as in poorer health, and independent observers perceived them as looking older than their biologically younger peers. Overall, Belsky’s study demonstrates that aging can be quantified in young adults and highlights the importance of intervening to reverse or delay the march toward age-related diseases while people are still young.
Nutrition through the life cycle: 60+ individuals
We know very well that a high-quality diet directly translated into better physical performance at 60-64, as shown by grip strength, walk speed, chair rise time, standing balance time, and other methods. Physical performance measures also represent useful markers of early aging. When referring to “high-quality diets,” most studies use indexes that assign specific points to one’s diet, depending on intakes of healthy foods (e.g., fruit, vegetables, wholegrain cereals, etc.). Such indexes include the Mediterranean diet score and the healthy eating index. Many studies have shown that individuals higher in the latter indexes have higher chair rise speed, for instance.
Nutrition throughout the life cycle: where do we go next?
So far, most studies on life course epidemiology have focused on high-income countries, mainly Europe. However, of the 17 million people that die prematurely each year because of non-communicable diseases, over 80% live in low- and middle-income countries. Since there are many cultural and environmental differences between the latter and high-income countries, extrapolating evidence from studies conducted in Western countries might be misleading. A good example that helps understand the fundamental differences between poor and rich countries is that greater adiposity is commonly related to higher socioeconomic positions in low- and middle-income countries. In contrast, the opposite is usually true in high-income countries.
Besides conducting more studies in countries that are underrepresented in epidemiology today, we also need to characterize life course exposures using an interdisciplinary approach. New technologies are emerging (e.g., sensors, AI applications, etc.) that allow scientists to track different exposures and collect enormous amounts of data. The latter also requires new data analysis skills and storage facilities to store and analyze complex and varied big data sets. We also need to discuss how to translate this future new knowledge into health benefits for all populations. For instance, if specific exposures (including behavior) can increase the risk of a disease, how can we nudge people away from this exposure?
Reducing health inequalities which are strictly consequent to income inequalities and access to health facilities, begs a particular interest. Improving people’s lives today will translate into better health for future generations. As for health and nutrition, we have not yet understood the complete role that nutrition has as a determinant of health across generations.
To promote healthier lifestyles and prevent diseases across generations, we need to enhance our comprehension of how individual experiences and health trajectories work. This requires a better understanding of how to facilitate collaborations between different fields, such as epidemiology, biology/medicine, social sciences, and behavioral sciences.
Moreover, we must realize the potential of later life interventions to support middle-aged and older adults in maintaining their functional capacity and reducing their risk of developing diseases throughout their life course. By doing so, we can improve the health outcomes of individuals and promote overall well-being in our communities.
Gene expression studies will focus on gene networks and their phenotypic variants, which will likely identify critical gene networks that may be involved in a range of pathologies. Environmental epigenetics will help us understand how non-genetic mechanisms can encode stable phenotypes that can respond to environmental changes. New longitudinal cohort studies will allow for the analysis of epigenetic profiles before clinical disease onset. Using biomarkers and identifying endophenotypes will facilitate early detection of individuals on a pathway to reduced health, allowing for preemptive interventions to avoid full-blown disease states.
Early childhood is a time for “intensive health development care,” and interventions must focus on early childhood before critical periods for the setting of biological systems have passed. Several recent studies have connected environmental and other adversities in pre- and early post-natal life with development of a range of mental health disorders in children and adolescents.
References
- Belsky DW, Caspi A, Houts R, et al. (2015). Quantification of biological aging in young adults. Proc. Natl. Acad. Sci. 112 (30) E4104-E4110.
- Halfon N, Larson K, Lu M, Tullis E, Russ S. Life course health development: past, present, and future. Matern Child Health J. 2014 Feb;18(2):344-65.
- Fleming et al. (2018). Origins of lifetime health around the time of conception: causes and consequences. Lancet 391:1842-52
- Norris SA, Frongillo EA, Black MM, Dong Y, Fall C, Lampl M, Liese AD, Naguib M, Prentice A, Rochat T, Stephensen CB, Tinago CB, Ward KA, Wrottesley SV, Patton GC. Nutrition in adolescent growth and development. Lancet. 2022 Jan 8;399(10320):172-184.
- Okubo H, Crozier SR, Harvey NC, Godfrey KM, Inskip HM, Cooper C, Robinson SM. Diet quality across early childhood and adiposity at 6 years: the Southampton Women’s Survey. Int J Obes (Lond). 2015 Oct;39(10):1456-62.
- Poulton R, Moffitt TE, and Silva PA. The Dunedin Multidisciplinary Health and Development Study: overview of the first 40 years, with an eye to the future. Soc Psychiatry Psychiatr Epidemiol. 2015; 50(5): 679–693.
