Lifestyle interventions targeted at obtaining/maintaining a healthy body weight and/or incorporating physical activity and healthy eating habits have great potential in improving outcomes in cancer survivors. Cancer diagnosis is a “teachable moment” wherein many patients are highly motivated to make changes (1). Furthermore, a balanced diet and moderate exercise can improve prognosis, quality of life, physical function, and survival across the cancer continuum. As such, groups such as the Amercian Cancer Society, National Comprehensive Cancer Network and the American College of Sports Medicine have released lifestyle guidelines for cancer survivors.

However, implementing changes in individuals and healthcare systems is challenging, to say the least. This is a recent topic covered by Karen Basen-Engquist and a number of colleagues as part of a special Issue of Obesity (Transdisciplinary Research on Energetics and Cancer)(2). Their article provides a 6-point agenda for translating research into clinical and community action, as follows:

  1. Increase the availability of different types of activities for weight management, nutrition counseling, and physical activity. One size will never fit all when it comes to improving health. Individual goals/preference, resources, and logistics all come into play, and cancer-specific programs may be needed.
  2. Improve screening and referral to lifestyle interventions. A system for evaluating and triaging patients for health programs should be developed. Importantly, an individual’s physical status, health needs, and goals should be considered.
  3. Improve the health care provider’s ability to screen, assess, and refer survivors for lifestyle programs. Oncology providers have a powerful role in helping cancer survivors; however, they often do not feel confident in screening, giving advice, or administering recommendations for lifestyle-related constructs. Implementation of processes such as the 5As (Ask, Advise, Assess, Assist, Arrange), which has been successful in tobacco cessation (3) and obesity management (4) might prove beneficial.
  4. Expand the support of oncology-specific professional training and certification. Professional organizations of dietitians, exercise professionals, psychiatrists, and physical therapists have additional certification programs for oncology or are working on developing one for its members. However, professionals with specific expertise in oncology are still greatly needed to address the unique needs of this population.
  5. Expand dissemination and implementation research. Many research programs do not address how a program could be implemented in a real-world setting (external validity). Dissemination of research findings with consideration of the sustainability and generalizability of programs is essential for broader impact.
  6. Advocate for health care policies that support lifestyle services for cancer survivors. Coverage for health programs is highly variable and often has barriers such as large co-payments, no coverage in grandfathered plans, and cost sharing. A potential solution could be incentivizing nutrition and exercise services, although more research is needed to determine the effectiveness of such actions.

As the authors eloquently articulate, the time has come to enable research into action for optimal healthcare in all cancer survivors.


  1. Demark-Wahnefried W, Aziz NM, Rowland JH, Pinto BM. Riding the crest of the teachable moment: promoting long-term health after the diagnosis of cancer. J Clin Oncol 2005;23:5814–30.
  2. Basen-Engquist K, Alfano CM, Maitin-Shepard M, Thomas CA, Schmitz KH, Pinto BM, et al. Agenda for Translating Physical Activity, Nutrition,and Weight Management Interventions for Cancer Survivors into Clinical and Community Practice. Obesity 2017; 25, S9-S22.
  3. Siu AL, Force USPST. Behavioral and pharmacotherapy interventions for tobacco smoking cessation in adults, including pregnant women: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2015;163:622-634.
  4. Rueda-Clausen CF, Benterud E, Bond T, Olszowka R, Vallis MT, Sharma AM. Effect of implementing the 5As of Obesity Management framework on provider-patient interactions in primary care. Clin Obes 2013; 4, 39-44.


Potential mothers, new mothers and mothers of multiples often worry about how their nutrition will affect their children. With the high rates of childhood obesity, some mothers worry more than ever about what they are putting in their bodies. Although this could be a discussion that includes pesticides on food, chemicals in cleaners and even air pollution, let’s just focus on nutrition.


It has been shown that a strong predictor of a child’s future BMI is the mother’s pre-pregnancy BMI (Schou-Anderson et al, 2012). This prediction comes from two sources, environment (how parents eat directly influences how children eat) and genetics (especially epigenetics). Epigenetics is how our cells control gene expression without changing the core DNA sequence and can include both DNA methylation and histone modification. It is consistently reported that maternal diet can directly alter DNA binding sites (Aagaard-Tillery et al, 2008) and DNA methylation (Dudley et al, 2011) in the offspring of mothers fed high fat diets. High fat diets contain energy dense foods consisting of >45% of total calories from fat, essentially mirroring the typical Western diet, which is full of highly palatable, highly processed energy dense foods. While this is certainly not a comprehensive list of publications on this topic, it is safe to say that maternal diet can influence an offspring’s risk of developing obesity through epigenetics (a nice review here). Hence the idea that whatever you eat, your baby also experiences.


While this may not be a novel concept, it is more important than ever to educate mothers (and fathers!) about the influence their diet could have on their future children’s body composition and their overall risk for obesity-associated diseases. While this information may initially leave parents anxiously asking questions like “Is there anything I can do?!”; “Is the damage already done?”; or “What could I have done differently?”, our goal is to provide information that is both reassuring and accurate knowing that with the right nutritional decisions, your child will be just fine!


Multiple studies have shown interventions in eating patterns and exercise work for reducing obesity and risk for associated diseases (reviewed here, here, here, here, here etc.).


The trick? Implementing these changes in your families diet and exercise routines to change the trajectory that epigenetics may have imposed when your little one was no larger than a grain of rice.


As a new parent you can go no longer than 24 hours without hearing the phrase “Breast is Best.” I know this to be true because I became a parent in June of this year. In the hospital we were offered consults with lactation and had no less than six posters in our room touting the benefits of breastfeeding. As a PhD student I was intrigued by the literature behind these recommendations and eagerly spent multiple late night nursing sessions on my iPad reading the latest research. What I found were some studies finding associations with reduced risk of obesity, and others failing to find this same association (literature). Overall, it was concluded in the previous review that breastfeeding was associated with a reduced risk of obesity.

While this was great news, I could not help but question; was this association because of breastmilk or mode of delivery? Bottle feeding is typically associated with formula feeding but a growing number of women have begun pumping their breastmilk after returning to work or in cases of pre-term birth and latch issues.

Could bottle feeding breastmilk still ameliorate the risk of obesity later in life?

I was not the first person to raise this question which has been addressed here, here, here, and here. Overall the consensus seems to be that early bottle feeding, of breastmilk or formula, is associated with an increased risk for excess weight gain and poor self regulation. Exclusively feeding expressed milk is also associated with early cessation of breast-milk feeding.

So this leads to the inevitable question; what is a mother to do?

While the literature is still unclear if bottled breastmilk can fight obesity risk, it is clear the breastmilk has multiple other benefits according to the American Academy of Pediatrics and should be offered when possible. So to those mothers who pump a little, a lot, or all the time, I say pump on ladies!

The Supplemental Nutrition Assistance Program, known as food stamps until 2008, has its roots in President Franklin D. Roosevelt’s New Deal as a part of the Agriculture Adjustment Act of 1933. This act was an effort to reduce the supply-side surplus of agricultural products, which resulted from the demand for increased exports during World War I. The federal government stepped in to restore the purchasing power of agricultural commodities to the levels seen prior to the war, primarily through the taxation of intermediary processers.

In 1939, the “Food Stamps Plan” was passed and began to resemble the current-day SNAP program. The Food Stamps Plan allowed those with low incomes to purchase food stamps with the benefit of a 50% tax-funded match in additional stamps for restricted use on foods designated to be in a surplus. The special stamps for surplus foods were eliminated in 1961.1

Fast forward to 2016 and SNAP has more than 44 million beneficiaries receiving a monthly payment of $125.50 per individual.2 About two-thirds of SNAP recipients are vulnerable individuals such as children, the elderly, and the disabled.  Of those served, 42% earn incomes below 50% of the poverty line, and 40% earn incomes between 51-100% of the poverty line.3 In general, to qualify for SNAP, the individual can’t make over 130% of the federal poverty line in gross monthly income and no more than 100% of the federal poverty line in net monthly income.4  67% of the SNAP recipients are in the aforementioned category of vulnerable individuals and are not expected to work. Of the remaining 33%, about 14% were employed, and 19% were unemployed.3

In a 2015 report by the United States Census Bureau, SNAP was shown to have kept 4.6 million Americans out of poverty, lowering the overall poverty rate by 1.4%.5 The virtues of injecting SNAP monies into the economy have been touted by many Keynesian economists for the theoretical multiplier benefit of consumption spending on the economy. It has been estimated that every $1 spent in the SNAP program generates $1.79 in economic activity.6 Though this point is debated, framing a safety-net program such as SNAP in terms of its downstream effects on the general economy is removed from the intent of the program, which is to provide aid to individuals in need of sustenance. The SNAP program continues to garner much public support as shown by a recent study, which found that 80% of individuals agreed that SNAP benefits should be raised by 19-43% depending on the scenario.7

The current presidential budget proposal for fiscal year (FY) 2018 entitled A New Foundation For American Greatness suggests cutting the SNAP program by 29% over the next ten years. The proposed budget seems to lament that the typical ebb and flow of this public safety-net program has been replaced in recent years by continual spending increases. SNAP participation usually decreases when the economy is strong and increases when the economy is weak. SNAP reached a historic high during the recession, but even with the improved employment numbers since then, “SNAP participation remains persistently high.” Furthermore, the proposed budget states that the reforms to SNAP will “close eligibility loopholes, target benefits to the neediest households, and encourage work.” Loopholes and safeguards against fraud are important steps to take, especially with the knowledge that the amount of SNAP benefits paid in error totaled $2.2 billion in 2009.8 Prominent forms of SNAP fraud include benefits that are exchanged for cash, embellishment on applications to receive more benefits, and disqualified retailers who continued to accept SNAP.9

The budget proposal also suggests a major structural change to the financing of SNAP. Previously, SNAP was fully funded through the federal government with the states covering the administrative costs, but the new budget proposes a state-federal partnership that will phase in and shift 25% of SNAP costs to the states by 2023.10 The presumable intent of this change in financing is to incentivize states to control costs and put more resources into helping recipients seek employment.

In a Miami Herald op-ed, Mick Mulvaney, director of the U.S. Office of Management and Budget has defended the proposed budget cuts to the SNAP program as a means of making the government more efficient, decreasing the deficit, and allowing individuals to keep more money in their pockets through decreased taxation.11

In the budget proposal, the SNAP program takes the largest cut relative to other public programs. The widespread public support and historical bipartisan support of SNAP makes it hard to foresee the budget passing as proposed without a revision to this particular suggested cut to SNAP. Though the presidential budget is just a recommendation, there are senators on both sides of the aisle who have expressed the sentiment that the budget in its current form is “dead on arrival.”12 House and Senate Appropriations Committees will be considering the FY 2018 spending bills in July after the Independence Day recess so we will soon find out the depth of cuts to the SNAP program.


  1. The History of SNAP. SNAP to Health. Accessed June 26, 2017.
  2. Supplemental Nutrition Assistance Program (SNAP) Participation and Costs, 1969-2016.; 2017. Accessed June 24, 2017.
  3. Chart Book: SNAP Helps Struggling Families Put Food on the Table. Washington, DC; 2017. Accessed June 25, 2017.
  4. Supplemental Nutrition Assistance Program – Fact Sheet on Resources, Income, and Benefits. Published 2017. Accessed June 25, 2017.
  5. Renwick T, Fox L. The Supplemental Poverty Measure: 2015. Washington, DC; 2016. Accessed June 24, 2017.
  6. Hanson K. The Food Assistance National Input-Output Multiplier (FANIOM) Model and Stimulus Effects of SNAP.; 2010. Accessed June 25, 2017.
  7. Kull S, Ramsay C, Lewis E, Williams A. Americans on SNAP Benefits.; 2017. Accessed June 24, 2017.
  8. Brown K. Supplemental Nutrition Assistance Program: Payment Errors and Trafficking Have Declined, but Challenges Remain.; 2010. Accessed June 24, 2017.
  9. What is SNAP Fraud? Published 2017. Accessed June 25, 2017.
  10. A New Foundation For American Greatness – Fiscal Year 2018. Washington, DC; 2017. Accessed June 24, 2017.
  11. Mulvaney M. Mulvaney: The federal budget released today puts taxpayers first. Miami Herald. Published May 22, 2017. Accessed June 24, 2017.
  12. Gambino L. Republicans voice opposition to Trump’s budget: “Dead on arrival.” The Guardian. Published May 23, 2017. Accessed June 25, 2017.

The former First Lady Michelle Obama revealed her “Let’s Move!” campaign in February of 2010 with the intent of curbing the childhood obesity epidemic. The initiative included a modification to the nutrition standards of the U.S Department of Agriculture’s (USDA) National School Lunch and School Breakfast Programs which provide 32 million meals to children daily. The principle legislation effecting these standards is the Healthy Hunger-Free Kids Act (HHFKA) of 2010 which has been touted as the first major reform to school lunch and breakfast in nearly 30 years.

In accordance with recommendations from the Institute of Medicine report “Nutrition Standards for Foods in Schools: Leading the Way toward Healthier Youth” and the 2010 Dietary Guidelines for Americans, the HHFKA informs the nutrition guidelines that schools must follow in order to be eligible for reimbursement under the National School Lunch Act and the Child Nutrition Act. Various standards resulting from the HHFKA went into effect in 2012, requiring schools to serve more fruits and vegetables, limit sodium, increase the whole grain composition of foods, and increase low-fat and non-fat options. To be more precise, all grains must be 50% whole grain by weight (or have whole grains as the first ingredient), food items can’t have more than 35% of total calories coming from fat, and only 10% of total calories can come from saturated fat. Many exceptions to these regulations exist and are enumerated in the final rule, which codifies the Act. For example, a high-fat food like peanut butter can be served if it is paired with a vegetable or fruit.

A 2014 study evaluated the initial implementation of the HHFKA in a cohort of students at four elementary schools in Washington State. The new guidelines were adhered to by 2013, and compared to the prior year, there was a decrease in average caloric intake by students across each individual macronutrient. Ingestion of key nutrients such as calcium and vitamin C decreased compared to the meals consumed under the old guidelines. Fiber was the only nutrient that was significantly increased. Despite the general dietary improvements that resulted, only about 1,000 meals in total were examined in this study. Following the implementation of these guidelines, childhood obesity rates have remained rather stable, but extrapolating the impact of this program on obesity rates over such a short time interval would not be sensible.

The new secretary of the USDA, Sonny Perdue, announced this past week that schools will be given “greater flexibility in their nutrition requirements for school meal programs in order to make food choices both healthful and appealing to students”. Schools have been facing increased financial burdens by adhering to the HHFKA regulations alongside a decline in school lunch participation, further exacerbating financial strain. Though students may be foregoing school lunches more often, the levels of food waste have not significantly changed compared to pre-implementation. Secretary Perdue acknowledged that 99% of the schools are partially compliant with the HHFKA standards, but noted that this metric is not indicative of program success. The temporary flexibility granted by Secretary Perdue includes a sodium target that is less rigorous, an exemption of the required 51% whole-grain composition, and the ability to serve 1% flavored milk rather than strictly non-fat flavored milks.

Dr. Margo Wootan of the Center for Science in the Public Interest, a consumer advocacy group, expressed disconcert with Secretary Perdue’s regulatory roll back, stating that “ninety percent of American kids eat too much sodium every day” and that “schools have been moving in the right direction, so it makes no sense to freeze that progress in its tracks.” Conversely, the School Nutrition Association, a nonprofit with 57,000 members, applauded this reform in a press release citing the HHFKA regulations as “overly prescriptive and having resulted in unintended consequences including reduced student participation, high costs, and food waste.” The new flexibility emphasizes the authority granted to localities to bolster the requirements of their own school nutrition and physical activity through the use of local “wellness policies.” The temporary deregulation of the HHFKA lowers the proverbial “floor” set by the federal government, giving the states an opportunity to have a direct impact in fighting the obesity epidemic.


For many generations parenting books and gurus alike have heralded the importance of routine. Beginning in infancy, children are scheduled to eat, sleep and play, and busy moms often follow this schedule to assure their youngest children are happy, healthy and well socialized. But, as is always the case, children grow older and become involved in more activities making it difficult to stick with rigid schedules established in infancy.

Recent evidence however has shown that regular mealtimes, bedtimes and limits on television at age 3 were all linked to children having better emotional self-regulation later in life. Self-regulation has two distinct domains, emotional and cognitive. Together, these domains help children control their attention. While these two domains have traditionally been studied together it is important to examine them independently as emotional self-regulation is tied to subcortical structures in the brain while cognitive self-regulation is based in the prefrontal cortex. The prefrontal cortex is known to mature later in development continuing its maturity until the early 20’s so outcomes based on these two domains must be distinct.

Anderson and colleagues (2017) tackled these questions in their recent publication accepted in the Journal of Obesity. Using a prospective study they examined how both domains of self-regulation and routine can impact obesity later in childhood (although only until age 11). The Millennium Cohort Study gathered data from 19,244 families recruited in the UK from 2000-2002. Data was collected beginning at 9 months with follow-ups at ages 3, 5, 7 and 11. Child Social Behavior Questionnaires were used at age 3 to determine self-regulation, while height/weight was used at age 11 to determine BMI and obesity status. A series of logistic regressions were used to understand how self-regulation and routine related to risk for obesity at age 11.

Results showed that having a “sometimes-regular bedtime” or “inconsistent bedtimes” were both associated with elevated risk for obesity at age 11. High television/video viewing time was initially associated with higher obesity rates but the result was not significant after controlling for other routines, a result that could be explained by the imprecise measurements used to quantify time spent. Surprisingly, children with mealtimes that varied considerably were found to be less likely to be obese at age 11. While this study agrees with previous literature in terms of bedtime, the results for mealtime were unexpected and need to be considered in the context of the study which was observational and based on parent self-report. Overall, emotional self-regulation and household routines were independent predictors of obesity at age 11 and those children with regular bedtimes, mealtimes, and limits on television/video displayed enhanced emotional self-regulation.

While this study demonstrates the importance of routine, it is important to understand that many factors could not be controlled for, leaving the study with multiple limitations. Still, if putting the kids to bed at the same time could be protective, maybe those rigid schedules shouldn’t be abandoned just yet.



Anderson, S. E., et al. “Self-regulation and household routines at age three and obesity at age eleven: Longitudinal analysis of the UK Millennium cohort study.” International journal of obesity (2005) (2017).

Sowell, Elizabeth R., et al. “Mapping cortical change across the human life span.” Nature neuroscience 6.3 (2003): 309-315.


Student Blogger for Global Nutrition Council at ASN’s Scientific Sessions and Annual Meeting at EB 2016

By: Sheela Sinharoy, MPH

A symposium titled Program Effectiveness for Addressing Undernutrition during the First 1,000 Days provided attendees with examples of programs in Bangladesh, Guatemala, and Burundi.

In Bangladesh, the Rang-Din Nutrition Study tested lipid-based nutrient supplements (LNS) in a community-based program. According to presenter Kay Dewey, the study found that giving LNS to mothers prenatally reduced the prevalence of stunting and increased the birth weight, head circumference, and body mass index (BMI) in infants at birth. LNS and multiple micronutrient powders (MNP) for children were also associated with better developmental and cognitive outcomes. Dr. Dewey noted that the impact on child anthropometry was much larger in food insecure households, so future programs may want to target based on this and other criteria.

Moving from Asia to Africa, Marie Ruel presented results from an impact evaluation of a food-assisted integrated health and nutrition program in Burundi. The program gave food rations to mothers and children and also provided behavior change communication. Interestingly, the nutrition situation in Burundi deteriorated sharply during the program period, but decreases were less severe in the treatment groups. For example, while the prevalence of stunting increased dramatically in the control group, the prevalence in the treatment group remained essentially flat. Thus, although the treatment group did not improve, the results suggest that the intervention protected families who otherwise would have been vulnerable to economic shocks.

Guatemala is another country with a very high prevalence of chronic undernutrition, and Deanna Olney presented results from a study of a similar food assistance program. The impact of the program was greatest among those who received a full family food ration plus an individual ration of corn-soy blend. In these households, mothers had significantly higher mean BMIs, children had a lower prevalence of stunting, and both mothers and children had a lower prevalence of anemia. However, there were no significant impacts on child underweight, wasting, or language or motor development.

The differing impacts of various programs was the impetus for a talk by Per Ashorn, who discussed pathways of impact for fetal growth, linear growth, and cognitive function. He explained that the pathways for linear, ponderal, and head growth are partially different, and there are possibly partially different pathways to childhood length gain and brain function. This suggests a need for multipronged interventions targeting pathways including infection, nutrition, and inflammation, as well as a variety of outcome measures to assess the interventions’ impact.

Of course, cost is an important – and often challenging – issue when planning interventions. The final talk of the symposium was given by Steve Vosti, who explained that programs must balance need, acceptability, use, and both short-term and persistent demand in order to achieve impact. These and many other factors, such as the costs of manufacturing supplements in country and the proportion of locally available ingredients being used, can affect the cost of an intervention. In addition to deciding on the most appropriate intervention to meet a need, practitioners must take these factors into account when planning their programs.

By Emily Roberts

The American Cafeteria

The quality, cost and nutritional adequacy of school lunches have been an ongoing hot bed for debate in our country. The National School Lunch Program has been enact since 1946 and provides lunches to many children of the public school system in the United States (1). The Healthy, Hunger-Free Kids Act of 2010 called for a revision of school meals to meet new nutritional standards that adhere to the 2010 Dietary Guidelines for Americans (2). However these changes have caused some upset including increased cost and waste. As we struggle to perfect the American school lunch, it is helpful to observe how other countries are managing their school lunch programs. My current position as a primary teacher in France gives me the opportunity to witness how the French tackle lunchtime

La Cantine FranÇaise

La cantine, French for the cafeteria, is where children enjoy their lunches if they choose not to return home for the two-hour break. From 11:45am to 1:45pm public schools in France have lunchtime, a time to eat, learn and relax. If the students choose to stay at school for their meal, they often have a wide selection of foods throughout the month from mutton stew, roasted chicken and veal, always paired with a meatless option. Accompanying the main dish is a fruit, vegetable and of course cheese. Throughout the month there are regional recipes capitalizing on local favorites as well as resources.

What’s on the menu?

Montpellier, France Public Elementary Schools

Tuesday March 29th, 2016

A Regional Recipe

Pomelos au sucre grapefruit with sugar

Gardianne de taureau bull meat with onions and carrots

Riz de Camargue long grain rice

Leerdamer cheese

Chocolat de Pâques Easter chocolate

Repas sans viande: flageolets

Meatless recipe: flageolets, a type of legume

Origine de la gardianne de taureau: nÉ, ÉlevÉ et abattu en Franc

Meat Origin: Born, raised and slaughtered in France


Baltimore County, Maryland Public Elementary Schools

Wednesday March 23rd, 2016

Chicken Nuggets

Grilled Cheese Sandwich

Yogurt Box (including yogurt, string cheese, granola clusters, fruit, vegetables and milk)

Green Beans

Carrot Sticks


Meatless option is only offered on Monday

There is no national program in France that helps provide public school lunches assuring that all meals meet certain standards. Rather the menus are developed, reviewed and prepared by each region. Montpellier, France is a general representation of the school lunches in France.

The development and review

A technical team creates the menus that are then reviewed by two certified dietitians (3). The dieticians ensure the meals provide the necessary nutrients for each corresponding age group. They also take into account specific preferences of children. The dieticians will often intervene during lunchtime as well to explain the meals and educate the students on healthy eating.

The preparation

Before preparing the food, there is a careful selection process for products by Quality Assurance. They must be tasted and closely examined to ensure all ingredients meet criteria (such as absence of GMO’s, proper nutritional content and the least additives as possible). They conduct visits to schools to verify proper adherence to the quality guidelines (3,4). Similar to the Unites States, there are strict regulations for the storage, cooking and serving of food to ensure safety.

The price

It ranges from 1€ – 5€ per child depending on the amount of children in each family and the meals consumed (4). This is comparable to the US Average of $2.18 per meal in Elementary Schools (5)

My views

My memories of school bought lunches include pizza, mozzarella sticks, fruit cups and the ice cream cart. Given the limited options I was always a packer. Needless to say I was amazed by the variety, quality and importance of school lunches in France. This local approach to school meal management allows them to utilize local resources and allocate more attention to the nutrition, quality and preference of meals.

USA A school lunch in an elementary school in Maryland with two mini cheeseburgers, applesauce, French fries, broccoli and chocolate milk.

France A school meal I ate at la cantine in a small town outside of Montpellier. A green salad with a light oil dressing, a plain egg omelet, sautÉed carrots, fresh bread, an apple and a piece of almond cake. The omelet was a little boring, but overall a satisfactory lunch.


. Guide de la Restauration Scolaire, Ville de Montpellier

Full March and April Menu

By: Hassan S Dashti, PhD

The most popular New Years resolution by far is weight loss. People kick-start their new year on new ‘detox’ or fad diets with hopes to lose some weight or, less commonly, to adopt a healthy lifestyle, only to quit a few months later. Traffic to websites like and hits an all time high in January! (1) People often envision January 1 of every year as an empowering and motivating moment that enables them to consider making these daring lifestyle changes. People might be less inclined to make these commitments on arbitrary dates like March 1 or October 19. With emerging evidence suggesting seasonal changes in the environment and human physiology, driven primarily by seasonal changes in sunlight and temperature, is it possible that certain start dates or seasons are more conducive to successful weight loss?

Seasonal variations have been observed for numerous communicable and non-communicable diseases (2) and both biological and behavioral traits. One of the earliest observations of seasonal variation in a disease was that of rickets, a disease resulting from vitamin D deficiency (3). Clinical observations indicated that rickets was common in spring, but rare in fall. The subsequent finding of seasonal variation in plasma 25(OH)D levels suggested that summer sunlight exposure was indeed an important determinant of vitamin D status. For more complex traits, like obesity, the seasonal etiology, if present, is likely to be multifactorial!

Successful weight loss is largely determined by the ability to reduce overall caloric intake, which depends on food availability and internal hunger cues. Living at a time where food is essentially abundant year-round in the Western world, people are typically not dealing with food shortages. For most processed foods, seasonal price variability is also absent, particularly in metropolitan areas, so people’s intakes are likely to be homogenous year-round (4,5). However, seasonal price variability of nutrient dense fruits and vegetables may limit a person’s likelihood to adhere to diets higher in fruits and vegetables. For example, strawberry prices tend to decrease through the first four months of the year and rise again from September to December. Fresh apples, on the other hand, have a fairly weak seasonal price pattern as a result of new apple varieties with later harvest dates and sophisticated storage technology. But it seems that despite the constant supply of most foods at steady prices, seasonal variation in dietary intake may exist. In the Framingham Heart Study, for example, self-reported total energy intake was 86 kcal/day higher during the fall than in the spring (6). Also, percentage of calories from carbohydrate, fat and saturated fat showed slight seasonal variation, with a peak in the spring for carbohydrate and in the fall for total fat and saturated fat intake. Of course these differences may be due to seasonal differences in self-reporting and recall, but if it’s true, is weight loss in the spring more successful than the fall?

Another important aspect of weight loss to consider is seasonal variability in energy expenditure.

The investigation from the Framingham Heart Study (6) also observed seasonal variation in physical activity, including common activities such as gardening, carpentry, lawn mowing, golf and running for men, and gardening, swimming, health club exercise, dancing and bicycling for women. Not surprisingly, people residing in the Northeast are less inclined to engage in outdoor physical activity. This sedentary lifestyle in the winter may partly explain the reason why people tend to be the heavier in the winter! (7)

Newer studies are investigating more complex physiologic changes that might interfere with energy balance. Recent observations in humans suggest that cold exposure may induce the conversion of white adipose tissue to more metabolically active brown-like adipose tissue (8). This ‘beiging’ effect of cold exposure could potentially have clinical implications for diabetes and obesity. Other studies have observed seasonal variability in metabolism and epigenetics as well (9,10). Whether these physiologic differences can override energy imbalance resulting from seasonal lifestyle differences is currently unknown.

To test whether there are seasonal differences in weight loss success we’d ideally test this in a randomized and controlled weight loss trial whereby people are prescribed hypocaloric diets and assigned random start dates. This can also be investigated analytically in previously conducted weight loss cohorts. Various methodologies are available for the assessment of seasonality and those range from simple comparisons across seasons, to simple models such as fitting monthly counts to a sine curve, or more complex statistical models (2).

Despite the little evidence we have so far relating seasonality and energy balance, healthcare providers, including nutritionists, should account for seasonality in their practice, and tailor their dietary (food and fluids) and physical activity recommendations accordingly – it’d be senseless to recommend berries when they are unavailable at stores or outdoor exercise when it’s uncomfortably warm! But perhaps reaching that point of enthusiasm for weight loss is the most important factor predicting weight loss success, so if January 1 is that date when motivation hits in, then so be it!


2.Christiansen CF, Pedersen L, Sørensen HT, Rothman KJ. Methods to assess seasonal effects in epidemiological studies of infectious diseases–exemplified by application to the occurrence of meningococcal disease. Clin Microbiol Infect. 2012 Oct;18(10):963–9.
3.Stamp TC, Round JM. Seasonal changes in human plasma levels of 25-hydroxyvitamin D. Nature. 1974 Feb 22;247(5442):563–5.
4.Evolving U.S. Fruit Markets and Seasonal Grower Price Patterns, by Kristy Plattner, Agnes Perez, and Suzanne Thornsbury, USDA, Economic Research Service, September 2014
5.Bernstein S, Zambell K, Amar MJ, Arango C, Kelley RC, Miszewski SG, et al. Dietary Intake Patterns Are Consistent Across Seasons in a Cohort of Healthy Adults in a Metropolitan Population. J Acad Nutr Diet. 2016 Jan;116(1):38–45.
6.Ma Y, Olendzki BC, Li W, Hafner AR, Chiriboga D, Hebert JR, et al. Seasonal variation in food intake, physical activity, and body weight in a predominantly overweight population. Eur J Clin Nutr. 2006 Apr;60(4):519–28.
7.Visscher TLS, Seidell JC. Time trends (1993-1997) and seasonal variation in body mass index and waist circumference in the Netherlands. Int J Obes Relat Metab Disord. 2004 Oct;28(10):1309–16.
8.Iyengar P, Scherer PE. Obesity: Slim without the gym – the magic of chilling out. Nat Rev Endocrinol. 2016 Feb 26.
9.van Ooijen AMJ, van Marken Lichtenbelt WD, van Steenhoven AA, Westerterp KR. Seasonal changes in metabolic and temperature responses to cold air in humans. Physiol Behav. 2004 Sep 15;82(2-3):545–53.
10.Aslibekyan S, Dashti HS, Tanaka T, Sha J, Ferrucci L, Zhi D, et al. PRKCZ methylation is associated with sunlight exposure in a North American but not a Mediterranean population. Chronobiol Int. 2014 Jul 30;:1–7.

By: Emma Partridge

American consumers are undoubtedly moving toward natural foods. An analysis by Datassential of consumer foodservice issue concerns may explain some factors in this overall trend; consumers appeared most concerned with antibiotics and steroids in animal proteins and/or dairy products, local food sources and manufacturers surviving, and GMOs, among other issues.1 Fortune magazine calls it “the war on big food” – but are consumers benefitting from more than just those ‘left out’ factors?2 I had the chance to sit down with Dr. Mario Kratz, researcher at the Fred Hutchinson Cancer Research Center, core faculty member of the University of Washington (UW), and Associate Director of the UW Diabetes Research Center, to discuss a few of these food trends and what their intrinsic health benefits might be.

One trend of note is the move toward full-fat dairy products. Whole milk sales rose 11% in the first half of 2015 alongside a 14% fall in skim milk purchases.3 While many speculate this shift is in line with movement toward wholesome, unprocessed foods, there are unrecognized benefits to full-fat dairy beyond its less-processed nature. Full-fat dairy may increase satiety, or lead a person to feel more full than if (s)he ate a low-fat dairy product. In evaluations of 16 dairy fat studies, Dr. Kratz’s team found that, of studies comparing high-fat dairy to low-fat dairy, high-fat dairy intake was actually associated with better weight outcomes, and was not associated with higher weight. Further, 11 of the 16 studies revealed that people who ate more dairy fat or high-fat dairy foods tended to be leaner and/or gain less weight over time than those who ate less dairy fat.4 The results from these analyses make a case for full-fat dairy as a protectant against weight gain, potentially due to increased satiety response. Additionally, there are other fatty acids present in full-fat dairy that can act as hormones, and small amounts of these fatty acids may be beneficial. The scientific reasoning behind the presence of many fatty acids supports full-fat dairy and, on the other side of that coin, there is no data supporting healthful benefits from consuming non-fat, low-fat, or isolated-fat dairy products in which many of the fatty acids have been removed.5

Another food trend of note over the past few years is that of coconut oil. While part of the trend may be attributable to its non-cooking uses, coconut oil is also highly heat resistant, has a long shelf life, and is rich in medium chain saturated fatty acids (MCFAs). The heat-stability of coconut oil is beneficial to reducing intake of harmful free radicals, but MCFAs may be the most significant of coconut oil’s intrinsic health benefits. In a study comparing long chain fatty acids, generally purported to be less-healthy fatty acids, to MCFAs, researchers found MCFA-treated mice exhibited increased energy expenditure, reduced adiposity, and improved insulin sensitivity.6 It is possible, then, that consumers following the coconut oil trend may be reaping such metabolic health benefits.

Perhaps the most significant trend to watch is that of developing healthy, lifestyle-based eating patterns, which is recommended by the 2015 Dietary Guidelines Advisory Committee in the recently-released 2015-2020 Dietary Guidelines for Americans. In a media-driven world of shoulds and should-nots, the Dietary Guidelines Advisory Committee took a different approach with this year’s release: develop patterns of healthy eating and physical activity within the environment around you. Dr. Kratz argues something similar, that pattern matters and a varied eating pattern may allow for small amounts of cravings and diet-breakers, thusly providing a method to control them.5 In short, his “number one” advice point is, “in spite of whatever craze you may be following right now…if you find something new, you should find a way to incorporate it into your overall diverse diet.”

1.Webster M. Changing Consumer Behaviors and Attitudes. Culinary Institute of America; 2015.
2.Kowitt B. Special report: the war on big food. Fortune 2015.
3.O’Connor A. Consumers Are Embracing Full-Fat Foods. The New York Times 2015. Why Whole Milk May Be Better Than Skim. Bottom Line Health 2014.
5.Mario Kratz P, MS. In: Emma Partridge MC, ed2016.
6.Montgomery MK, Osborne B, Brown SHJ, et al. Contrasting metabolic effects of medium- versus long-chain fatty acids in skeletal muscle. Journal of Lipid Research. 2013;54(12):3322-3333.