What Affect Does Diet and BMI Have on Physical Fitness?

Introduction

Recent studies have shown that the physical fitness of an individual can be a promising indicator in measuring health and risk for outcomes such as obesity, cardiovascular disease, diabetes, cancer, and skeletal health. (1) The World Health Organization (WHO) recommends children and adolescents between the ages of 5-17 should get at least 60 minutes a day of moderate-to vigorous-intensity physical activity. Regular physical activity is associated with many health benefits in children and can improve cardiorespiratory and muscular fitness, as well as bone health (4). It is noteworthy to promote regular physical activity because research shows that cardiorespiratory fitness levels are significantly associated with total body fat and abdominal adipose tissue. (1) Lower levels of cardiorespiratory and muscular fitness are associated with CVD risk factors. (1) And improvements in cardiorespiratory fitness have positive effects on things like depression, anxiety, self-esteem, and academic performance. (1)

Findings from a cross-sectional study done in South Carolina found that children who are obese generally spend less time in moderate and vigorous physical activity than non-obese children. (2) It also found that the energy density of a child or adolescent’s diet is directly associated with fat intake, and both energy dense high-fat diets are associated with obesity. (2) In past studies it has been suggested that reducing dietary ED by combining increased fruit and vegetable intake, as well as decreasing total fat intake, was seen to control hunger and be an effective strategy for weight loss. (3)

High-fat diets can easily turn into unhealthy diets that lead to high risk of CVD and insulin resistance, and high-fat diets generally have high energy densities. (5) According to the CDC, 1 in 6 children and adolescents is obese and obesity affects 12.7 million children and adolescents between the ages of 2-19 years old. There is a 75% predicted increase in obesity by 2018. Children who are overweight and obese are more likely to become overweight and obese as adults. (CDC) Studies have shown that for every hour of exercise a day, risk for obesity is decreased by 10%. (2) The measure of physical fitness in children and adolescents can display health as well as predict future health outcomes as an adult. (7)

The purpose of this study was to evaluate if diet and BMI of children affected physical fitness levels by using data from the NHANES National Youth Fitness Survey. Energy density and total fat in the diet, as well as the BMI of the participants, were the variables used to assess performance on three important physical fitness categories, measured by the outcomes of four different physical fitness tests. The objective was to determine if BMI, energy density, and fat intake was significantly associated with physical fitness levels, and what this could mean as an outcome.

Methods

Data Source & Inclusion Criteria

The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional survey that assesses the health and nutritional status of children and adults in the US. This experiment used the NHANES National Youth Fitness Survey (NNYFS). The NNYS is a one-year, cross-sectional survey conducted by the National Center for Health Statistics in 2012. For the purpose of analysis, this was the main source of physical fitness data. It had the purpose of gathering nationally representative data that represented physical activity and fitness levels, as well as provided an evaluation of health and fitness of children and adolescents ages 3-15. Data was collected through fitness tests and interviews. The nutritional component of data in the NHANES comes from What We Eat In America (WWEIA), gathered through dietary recall from each of the participants.

This analysis included a study sample of all children and adolescents between the ages of 3-15, who participated in the 2012 NHANES National Youth Fitness Survey. However, many children between >6 years met the exclusion criteria and did not participate the physical fitness tests used in this study to evaluate fitness levels. This resulted in a final n of 1,224 participants between the ages of 6-15.

Outcome Measures

The outcome measures in this study included three categories of physical fitness. Physical fitness was evaluated through fitness tests as part of the NNYS. Participants 6-15 years old participated in fitness tests (summer 2012), which evaluated the health of each age group. The NNYFS contains examination data that evaluates body measures, cardiorespiratory endurance, cardiovascular fitness, lower body muscle strength, muscle strength, and gross motor development. For this analysis, physical fitness was measured using the following categories: cardiorespiratory endurance, core muscle strength, and upper body muscle strength.

Cardiorespiratory endurance was measured by examining fitness test results of heart rate at the end of the test (bpm) and maximal endurance time (in seconds). Core muscle strength was determined by the number of seconds plank position was held (in seconds). Upper body strength was evaluated by the number of correctly completed pull-ups the participant could do. Each exercise was assessed in regards to BMI, energy density, and total fat.

Demographic Characteristics and Potential Confounding Variables

In order to assess if physical fitness was affected, variables of BMI, energy density (kcal), and total fat (gm) were used. The NHANES gathered data of total nutrient intakes from dietary interviews given by well-trained professionals. The dietary intake data can be used to estimate the types and amounts of food (as well as beverages) consumed throughout the past 24-hours. In the NHANES, body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (rounded to one decimal place). In order to analyze BMI as a categorical variable (BMI Category), sex-specific BMI quartiles were created from body mass index data and cutoff criteria from the CDC’s sex-specific 2000 BMI-for-age growth charts. BMI category provided four quartiles: 1) Underweight, 2) Normal weight, 3) Overweight, and 4) Obese.

Energy density and total fat were variables used to measure diet of children and adolescents. Dietary intake for energy density and total fat was measured using 24-hour recalls. To account for confounding factors, which occur when the outcome is influenced by a third factor, data from the NHANES regarding age, gender, race and income were used as covariates and all models run were adjusted according to this. What was looked at was whether energy, total fat, and BMI were significantly (inversely) associated with a decrease in physical fitness of children and adolescents.

Statistical Measures Used

Data from the NHANES was analyzed using SAS University Edition (SAS Institute, Cary, NC). To examine if there was a significant association of physical fitness levels with BMI and energy density / total fat intake, the PROC REG procedure was used. PROC REG procedure was used to analyze significance, if any, in upper body muscle strength (pull-ups), core muscle strength (plank), and cardiorespiratory endurance (heart rate, maximal endurance time). These models were adjusted for age in years at exam, race, and gender, and significance was determined with a value of p<0.05. BMI Category was analyzed using the GLM procedure to predict an outcome based on a categorical variable. Graphical data shown below is the performance outcomes based on the data from results of the GLM procedure of BMI category and the specific physical fitness exercises.

Results

The data obtained from this study indicates that there was a significant inverse relationship observed between diet / BMI and various aspects of physical fitness of children and adolescents. There was a significant negative association of energy density in pull-ups (p=0.0458) and heart rate at the end of test (p=0.0195). Total fat intake had a significant inverse affect on heart rate (p=0.0404).

BMI was the most significant factor in affecting physical fitness. Children who are overweight/obese have less upper body strength than non-obese children. The mean number of pull-ups was approximately 5. Children who are obese completed on average almost 4 less pull-ups than children who are of normal weight (see figure 1).

Figure 1.

julia-paper
Source: Julia Wood

Children who are overweight/obese exhibit lower levels of cardiorespiratory endurance than normal weight children. Maximal endurance time was measured in seconds and measures the amount of time the actual exercise test takes (does not include warm up or recovery). The mean maximal endurance time was 650 seconds. Children who were overweight/obese were not able to perform the exercise test as long as those of normal weight. Overweight children lasted about 632 seconds, while obese children only lasted about 551 seconds, compared to normal weight children who could last approximately 632 seconds.

Children with a higher BMI have a lower level of cardiorespiratory endurance. The mean heart rate at the end of the test was 220 beats per minute (bpm). A non-obese child of normal weight had a heart rate of 249 bpm, while an overweight child had a heart rate of 208 bpm and an obese child had a heart rate of 209 bpm.

Children with a higher BMI display lower levels of core muscle strength. The plank is an exercise that assesses muscular endurance and core strength around the trunk and pelvis (NNYFS). Children with a normal weight had a greater ability to hold the plank position. Almost 35 seconds longer than obese children and almost 15 seconds longer than children who are overweight (see Figure 2).

Figure 2.

coremuscle
Source: Julia Wood

Strengths and Limitations

 In light of the results from this analysis, it is important to note the strengths as well as limitations. Strengths of using the NNYFS include the fact that it is a cross-sectional study that represents physical fitness levels and health of US children and adolescents as a whole. This means that the results can be applied to the entire population of US children and adolescents. Results show that there is a prevalence of low physical fitness levels in children and adolescents who have high BMI and an increased intake of high-fat/energy dense diets. From this analysis, the simple promotion of increased physical activity as well has healthy diets can be put out into the public in hopes of slowing the obesity epidemic and better health in children.

There are some weaknesses to this research. Diet factors of energy density and total fat were used in this study. Data was acquired for these two factors by dietary recall, so there is a possibility of recall bias. Also, the NHANES National Youth Fitness survey is of a cross-sectional survey design, so although analysis can point out prevalence stemming from results, it cannot determine causality. This study also uses two physical fitness tests that somewhat depend on weight/body mass. Pull-ups as well as plank exercises may be subject to influence based on body weight, which could skew results.

Conclusion

Our findings from this study indicate that a child or adolescent’s BMI and diet affect his or her performance on physical fitness tests. Children and adolescents who are overweight or obese (85th-95th percentile or >95th percentile) are seen to have lower levels of cardiorespiratory endurance, upper body muscular strength, and core muscle strength. High BMI was seen to negatively affect physical fitness the most and was more significant than any other factor (p<.001).

There is a significant inverse association between energy dense / high-fat diets and various aspects of cardiorespiratory endurance and upper body strength. Physical fitness is a marker of health and can predict health as an adult. Regular physical activity of at least 60 minutes a day for children and adolescents promotes health and fitness and may help to prevent obesity. Strategies promoting healthy eating may also slow the obesity epidemic.

References

  1. Ortega, F. B., Ruiz, J. R., Castillo, M. J., & Sjöström, M. (2008). Physical fitness in childhood and adolescence: a powerful marker of health. International journal of obesity, 32(1), 1-11.
  2. Ebbeling, C. B., Pawlak, D. B., & Ludwig, D. S. (2002). Childhood obesity: public-health crisis, common sense cure. The lancet, 360(9331), 473-482.
  3. Ello-Martin, J. A., Roe, L. S., Ledikwe, J. H., Beach, A. M., & Rolls, B. J. (2007). Dietary energy density in the treatment of obesity: a year-long trial comparing 2 weight-loss diets. The American journal of clinical nutrition, 85(6), 1465-1477.
  4. Janssen, I., & LeBlanc, A. G. (2010). Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. International journal of behavioral nutrition and physical activity, 7(1), 1.
  5. Guldstrand, M. C., & Simberg, C. L. (2007). High-fat diets: healthy or unhealthy?. Clinical Science, 113(10), 397-399.
  6. Schrauwen, P., & Westerterp, K. R. (2000). The role of high-fat diets and physical activity in the regulation of body weight. British Journal of Nutrition, 84(04), 417-427.
  7. Harper, M. G. (2006). Childhood obesity: strategies for prevention. Family & community health, 29(4), 288-298.

Julia Wood is a senior at Fairfield University in Connecticut where she is preparing to graduate in May 2017 with a degree in Biology and minor in Health Studies. Julia was a 4-year member of the Fairfield women’s D1 cross-country team.

Research Study Indicates Exercise App Use Decreases BMI

A recent study by Journal of Medical Internet Research indicates that exercise apps increase the amount of leisure time that users spend exercising, as well as decreasing their BMI. Researchers from Lander College, Columbia University, Long Island University, and Marymount Manhattan College surveyed 726 people regarding their usage of exercise apps and exercise apps. Sixty-three percent of the sample group had never used an exercise app, 16 percent had used an app in the past but no longer used it, and 20 percent currently used an exercise app.

The current users were 27 percent more likely than the others to self-report being active. The survey showed that the groups reported being equally active during non-leisure time such as incidental exercise like walking to work. The app users said they were more active than other groups during leisure time. Lower body mass index was also correlated with higher app usage in the study.

weight-loss-Social-Media-Apps
Source: http://mugsypr.com

It’s possible that a higher interest in exercise, which might be more likely among those with a lower BMI, can account for the use of the app and length of use. Therefore, it’s likely that individuals who are more interested in exercise are more likely to seek out exercise apps to help them achieve their goals. Exercise apps also increase self-efficacy. The researchers wrote:

“The results presented in this study suggest that apps, as intervention delivery systems, have the potential to significantly improve population exercise levels and may thus have a significant impact on future public health outcomes.”

Paired with a diet app such as FitClick Talk-to-Track, which is associated with sustained and successful weight loss, users can better monitor their intake and customize their exercise plan to specific days.

Over 1 in 3 Adults Worldwide Are Now Overweight or Obese

According to a brand new study, the global prevalence of obesity is on the rise – and this seems to be true of men and women, adults and children, and those in developed and developing countries. But there are some interesting differences according to country, age, and gender and even some potentially positive news.

bathroom-scaleThe results come from a massive study just published in the journal Lancet assessing the worldwide change in the prevalence of people who are overweight or obese (BMI≥25kg/m2). By massive, I’m referring to the fact that this study used data from a whopping 1769 individual studies from 183 countries. That alone is an impressive feat.

Let’s dig a bit deeper into the study findings, shall we?

Globally, between 1980 and 2013, the proportion of men who were overweight or obese increased from 28.8% to 36.9%, while the proportion of women in this category increased from 29.8% to 38.0%.

Across time, the prevalence of overweight/obesity was higher in developed than in developing countries across all ages.

For instance, in 2013, the US accounted for 13% of all obese people worldwide! This is a tremendous statistic given that the US accounts for approximately 4.4% of the world’s population.

Interestingly, more men than women were overweight and obese in developed countries like the US and Canada, whereas the opposite was true in developing countries (overweight and obesity was more prevalent in women).

The rates of overweight and obesity peaked in men at about 55 years of age; meanwhile the peak age in women was approximately 60 years.

And adults weren’t the only ones putting on the pounds; rates of excess weight in children and adolescents also increased. Between 1980 and 2013 in developed countries, the prevalence of overweight and obesity has increased from 16.9% to 23.8% among boys and from 16.2% to 22.6% among girls.

While the greatest increase in obesity prevalence occurred between 1992 and 2002, this trend has tapered down in the past decade, particularly in developed countries.

That is, as a species, we’re still getting fatter, albeit at a slower pace.

This was the good news I was referring to above. Not the most encouraging, but given the barrage of negative news regarding the obesity pandemic, I’ll take what I can get.

Excess weight has previously been estimated to cause 3.4 million global deaths per year, and it has been postulated that, at least in the US, the rise in obesity could actually result in shorter life expectancy for future generations – thereby reversing the temporal trend of increasing life expectancy over time. The fact that a growing proportion of the global population is crossing the threshold into excess weight suggests that this daunting prediction may become true.

The exact cause of this global weight increase is anyone’s guess. The authors of this paper suggest the usual suspects: increased caloric intake, changes in the composition of diet, decreased levels of physical activity. Then they promptly throw their hands up.

Due to the continued westernization of many developing countries across the globe, no one should be surprised if the global rates of obesity continue to climb into the future. The slight plateauing in the rise of obesity in developed countries may indicate that some of the strategies enacted over the past decade are actually having some impact. Hopefully, we can help developing countries launch similar public health strategies and turn the tide before obesity rates in these countries mirror those of more developed (and chubbier) counterparts.

Interesting fact: The research was funded by the Bill & Melinda Gates Foundation.

This post was reposted from Obesity Panacea with permission from Peter Janiszewski who has a PhD in clinical exercise physiology. He’s a medical writer/editor, a published obesity researcher, university lecturer, and an avid traveler. You can connect with Peter on Twitter. For more information please visit his website.

Why BMI (Body Mass Index) is Not the Best Option

human_compositionMany of us have heard about body mass index (BMI) and know that it uses height and weight in a formula (that was developed more than 150 years ago) and gives you an idea of where you are regarding your current body weight (i.e. ideal, overweight, obese etc.). BMI is a calculation that takes into account your height and overall weight but does not factor in body fat or more importantly lean muscle tissue. It seems this formula may work for some but if you’re small in stature, older or athletic, the calculation will be inaccurate. This is why most athletes like football players are considered overweight or even obese when their stats are entered into the following BMI calculation:

BMI = Body weight (lbs.) / Height(2) (inches) x 703

If lean muscle and body fat are not calculated into the equation then there is NO WAY it can be accurate, especially for individuals who carry more muscle.

According to many government agencies like the CDC a healthy weight for someone in terms of BMI is about 18.5 to 24.9 – this means if you’re over 25 your over weight. If your BMI happens to be >30 your considered obese. We need to start factoring in height, weight and lean muscle level into this profile and in turn get a more accurate reading.

Maybe we should just use the bathroom scale? The issue with this is that it does not give an accurate picture either it just gives you a number. It’s the ratio of that number (muscle:fat) that you need to determine and track over time and your scale will not differentiate the ratio of muscle and fat. Maybe you can start to use a waist-to-hip ratio (waist/hip measurement) and a %body fat score as part of your own personal health index.  The bottom line is you need to start paying more attention to ratio of muscle to fat that your carrying on that body of yours. There are many ways to determine %body fat (Skinfolds, BIA, TOBEC, DEXA, Hydrostatic weighing, etc.) If you’re unable to use any of these methods then take a simple measurement around your waist. This does not determine overall body fat but it can tell you a great deal. Men should not exceed 40 inches and women 35 inches in regard to a waist measurement.

At the Koko FitClubs around the country we have our members take a FitCheck reading that takes a snap shot of their body composition. It takes into consideration their height, weight, sex and age and offers two important metrics – their current lean muscle level and eBMI (“enhanced” body mass index).

It all comes down to the simple fact that it’s not about one single number – a number like BMI alone or what your bathroom scale tells you should not define who you are. Start paying more attention to the amount of muscle tissue your body is carrying, your strength level or maybe the size of your waist or hips…you’ll be much better off as you age!