Do Variations in Breast Milk Composition Account for the Conflicting Evidence Regarding Its Protective Effects On Excess Weight Gain?
As father of three nursing mothers, I am all for breast feeding. Indeed, in several previous posts, I have cited the epidemiological data to suggest that breast feeding may be protective against childhood obesity.
However, this data is far from clear. There are in fact many conflicting studies on this issue, as a result of which breast feeding as protection for weight gain was presented as one of the “obesity myths” in a recent paper in the New England Journal of Medicine.
Now, a study by Tanya Alderete and colleagues from the university of Southern California, Los Angeles, published in the American Journal of Clinical Nutrition, suggests that the variable reports on the role of breast feeding in protecting against excess weight may be related to variations in its composition.
The researchers studied the composition of human milk oligosaccharides (HMOs) in 25 mothers and correlated these to with infant growth and body composition at 1 and 6 mo of age.
As the authors discuss, diversity and HMO composition of breast milk appeared to have disparate effects on body composition and body weight.
Thus, for example, each 1-μg/mL increase in levels of lacto-N-fucopentaose (LNFP) I was associated with an approximately 1 lb lower infant weight at 1 month and a 1.11-kg lower weight with am 0.85-g lower lean mass and a 0.79-g lower fat mass at 6 months.
In contrast, disialyl-lacto-N-tetraose and LNFPII were associated with small but significant increases in body fat mass.
Overall, these effects are not trivial,
“When examined collectively, LNFPI, DSLNT, and FDSLNH explained 33% more of the variance in infant fat mass than did sex, prepregnancy BMI, weight gain during pregnancy, and 6-mo infant age alone.”
As one potential mechanism, the authors suggest that different HMO’s may have differential effects on gut bacteria in these infants.
“HMOs are thought to aid in the growth and metabolic efficacy of the developing infant micro biome…Although we did not collect stool samples, preliminary findings observed in the current study may be partially attributed to the prebiotic effects of HMOs. In support of this, a recent study found a distinct fecal microbiota composition in breastfed compared with formula-fed infants, in which the fecal microbiota in breastfed infants correlated with the HMOs consumed (particularly LNFPI and DSLNT).”
Whatever the mechanism, as the authors note,
“These findings support the hypothesis that differences in HMO composition in mother’s milk are associated with infant growth and body composition.”
Obviously, these kind of studies cannot prove causality nor do they provide definite mechanistic insights.
However, they may open an avenue to better understanding why the literature is so conflicted when it comes to the relationship between breastfeeding and excess weight gain.
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As Canada’s national representative in the World Obesity Federation (formerly IASO), the Canadian Obesity Network is proud to co-host the 13th International Congress on Obesity in Vancouver, 1-4 May 2016.
The comprehensive scientific program will span 6 topic areas:
Track 1: From genes to cells
- For example: genetics, metagenomics, epigenetics, regulation of mRNA and non–coding RNA, inflammation, lipids, mitochondria and cellular organelles, stem cells, signal transduction, white, brite and brown adipocytes
Track 2: From cells to integrative biology
- For example: neurobiology, appetite and feeding, energy balance, thermogenesis, inflammation and immunity, adipokines, hormones, circadian rhythms, crosstalk, nutrient sensing, signal transduction, tissue plasticity, fetal programming, metabolism, gut microbiome
Track 3: Determinants, assessments and consequences
- For example: assessment and measurement issues, nutrition, physical activity, modifiable risk behaviours, sleep, DoHAD, gut microbiome, Healthy obese, gender differences, biomarkers, body composition, fat distribution, diabetes, cancer, NAFLD, OSA, cardiovascular disease, osteoarthritis, mental health, stigma
Track 4: Clinical management
- For example: diet, exercise, behaviour therapies, psychology, sleep, VLEDs, pharmacotherapy, multidisciplinary therapy, bariatric surgery, new devices, e-technology, biomarkers, cost effectiveness, health services delivery, equity, personalised medicine
Track 5: Populations and population health
- For example: equity, pre natal and early nutrition, epidemiology, inequalities, marketing, workplace, school, role of industry, social determinants, population assessments, regional and ethnic differences, built environment, food environment, economics
Track 6: Actions, interventions and policies
- For example: health promotion, primary prevention, interventions in different settings, health systems and services, e-technology, marketing, economics (pricing, taxation, distribution, subsidy), environmental issues, government actions, stakeholder and industry issues, ethical issues
Early-bird registration is now open – click here
Abstract submission deadline is November 30, 2015 – click here
For more information including sponsorship and exhibiting at ICO 2016 – click here
I look forward to welcoming you to Vancouver next year.
Yesterday, I attended the inaugural networking event of the Canadian Obesity Network’s Toronto Chapter. Judging by the enthusiasm of the almost 100 folks who came out to this event, this chapter appears off to a great start.
As expected for any CON event, the participants came from virtually every walk of interest in obesity – from professional to personal – research, prevention, clinic, policy, industry, NGOs.
Hopefully, we will see similar activities and chapters starting across Canada in the coming months – the success off this event shows that there is a dire need for local networking to address local issues related to obesity prevention and management.
For more information on the Toronto Chapter (CON-YYZ) click here.
For more information on how to start a CON chapter in your city click here.
Thus, a study by Asheley Skinner and colleagues, published in the New England Journal of Medicine, shows that increased cardiometabolic risk is tightly linked with severe obesity both in children and young adults.
The study looks at cross-sectional data from overweight or obese children and young adults (3-19 yrs) who were included in the US National Health and Nutrition Examination Survey (NHANES) from 1999 through 2012.
Among 8579 children and young adults with a body-mass index at the 85th percentile or higher (according to the Centers for Disease Control and Prevention growth charts), 46.9% were overweight, 36.4% had class I obesity, 11.9% had class II obesity, and 4.8% had class III obesity.
Overall, for a given weight, males tended to have higher cardiometabolic risk than females.
Even after controlling for age, race or ethnic group, more severe obesity maps more likely to be associated with low HDL cholesterol level, high systolic and diastolic blood pressures, and high triglyceride and glycated hemoglobin levels.
Importantly, while this relationship was constantly present in males, the there were fewer significant differences in these variables according to weight category among female participants, suggesting that for a given body weight, girls were less likely to be at cardiometabolic risk compared to boys.
Thus, while body weight (or body fat) may not be a precise measure of individual health, the risk for having one or more cardiometabolic risk factor increases substantially with increasing severity of obesity.
However, it is also important to note that even in kids and youth with class III obesity, 70% of participants had normal lipids and about 90% of participants did not have elevated blood pressure or glycated hemoglobin.
This points to the fact that for a given body weight there is indeed wide variability in whether or not someone actually has cardiometabolic risk factors.
Thus, whether or not it makes sense to target every kid that presents with an elevated BMI for intervention, remains to be shown – most likely such an approach would probably not be cost-effective.
As in adults, it seems that interventions in kids are probably best targeted by global risk rather than simply by numbers on a scale.
Readers may be aware of the “Resource Dilution Hypothesis”, which postulates that there is a dilution of familial resources available to children in large families, and a concentration of such resources in small ones.
This “dilution” effect could not only affect material factors (including food, participation in organized sports, higher education, etc.) but also emotional factors (including parents undivided attention, time, interaction, etc.).
While the importance of this “dilution” effect remains hotly debated, at face value, it sounds plausible.
Indeed, there is no doubt that in most Western countries (with increasing standard of living), recent decades have seen a substantial reduction in the number of offspring per family, resulting in a significant increase in first and second-borns as part of the overall population.
Now, a large longitudinal study by José Derraik and colleagues, published in the Journal of Epidemiology and Community Health, reports that first-born women (in Sweden) tend to be significantly heavier (and slightly taller) than second-born women, leading the authors to suggest that decreasing family size may have something to do with the increase in obesity seen over time in that country.
Indeed, based on this study involving 13,406 pairs of sisters who were either first-born or second-born (n=26 812), the first-born were about 2.4% heavier than their second-born sisters with a 30-40% greater chance of having overweight or obesity.
While this difference may seem rather subtle, at a population level, over generations, such effects can well result in substantial shifts in the population BMI, as a greater proportion of people are first-born. (if every family had 5 children, 20% of kids would be a first-born, If every family has 2 children, 50% of kids would be a first-born, if every family had only 1 kid, 100% of kids would be a first-born)
As interesting as this idea may seem, there are several issues with this type of analysis, which may well be confounded by all kinds of issues and can hardly prove causality. Nevertheless, a similar finding has been reported in male first-borns and the hypothesis certainly has significant face value.
Paradoxically, however, although overall family sizes have decreased, people in lower socioeconomic strata, who tend to have more kids, also tend to have the highest obesity rates. The obvious explanation for this would perhaps also implicate the “resource dilution hypothesis”, as more kids means less money for food, resulting in more (cheaper) caloric-dense processed foods and greater food insecurity.
Accordingly, I would predict that there may well be a “U” or “J” shaped relationship between family size and obesity in the offspring – if anyone has data on this, I’d certainly be interested.