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Claudia Willis (ccw885)NTR338WFinal Draft
EFFECTIVENESS OF PREVENTION PROGRAMS ON CHILD OBESITY
Abstract
The increase in childhood obesity has become an international issue.
Obesity is a leading factor in many deadly diseases. In recent years studies have
been conducted to try to find the best method of lowering obesity rates. The
evaluation of prevention programs during and after school has shown some
positive influence in solving this epidemic. Studies have been separated by focus
either in nutrition education, physical activity, or both. In this review, a variety of
outcome measures including anthropometrics, questionnaires, behavioral
analysis, and diet were compared to evaluate what methods result in the highest
amount of positive change in health. Some differences were found in BMI and
healthy food intake but overall there is still a large need for longer-lasting
changes to be implemented to prevent obesity.
Introduction
Child obesity rates have been increasing for several decades, and has
now become an international epidemic [8]. This is largely due to a shift in lifestyle
habits such as unhealthy eating and inadequate physical activity. It is estimated
that over one-third of children in our nation fall under the category of overweight
or obese [5]. Child obesity is a large link in a chain leading to long-term adult
health risks, like cardiovascular disease and diabetes. The consensus of
literature on the matter agrees that the most effective way to address the
problem of child obesity and the associated life threatening diseases leading into
adult obesity is through prevention interventions. The focus of this research is to
evaluate the effectiveness of afterschool programs in correcting and preventing
childhood obesity.
It is important to outline three main factors that influence the prevalence of
child obesity; behavior, environment, and family [10]. A child’s behavior and
attitude towards a healthy lifestyle for example depression, low self-esteem, or
social anxiety can cause over-eating especially in the post adolescent
demographic. Additionally, sedentary behavior is probably the biggest contributor
to a lack of adequate physical exercise. Children are now more involved in
watching television or using electronics; therefore, they are not burning as much
energy as they would if they were taking part in physical activities. This leads to
the environmental factors that increase the likelihood of child obesity. The media
plays a role in constantly exposing youth to advertisements of unhealthy food
items and sedentary influencers that are targeted specifically to children. School-
based policy is a direct environmental influence on the amount of physical activity
and nutrient-rich foods available to children. Nationwide, only 4.2% of elementary
schools require daily physical education for all students [3], while it is
recommended that children get at least 60 minutes of moderate to rigorous
exercise a day [10]. Another example is community influence; low-income areas
are less likely to provide healthy food choices, grocery stores, community
gardens, or neighborhood health initiatives. Lastly, family influences like
socioeconomic status affects a child’s health outcome. For example, some
families cannot afford expenses such as sport equipment to join a team. Also
cultural background affects the types of foods eaten, along with ideals on home
cooking versus eating out. Family influences include a genetic predisposition to
obesity and certain ethnicities that are more genetically inclined towards obesity
[10]. African-American and Latin-American populations are the most at risk for
child and adult obesity [5].
There are a variety of factors to evaluate when determining the efficacy of
afterschool programs in preventing child obesity; there are major differences in
the successes and failures of the many programs implemented and evaluated.
Greater positive results are outlined by specific factors. One factor was the
experience of leaders implementing the program and the outside support they
received. The most effective physical intervention program, led by trained study
personnel with exercise-related education had the most significant results in
lowering BMI (body mass index)[5]. Another study suggested nurses and staff
training would have greatly influenced the success of the program, because
parent involvement would have aided the children in sustaining the practices they
learned and continued exposure to the habits [14]. Attendance was an area
where many programs struggled; success rates were much higher in programs
with greater attendance [3]. The focus of many programs split between nutritional
and physical activities. For example, some programs implemented exercise and
eating habit lessons while others focused specifically on either physical
improvement or providing information on healthy eating habits. The method of
exercise influences results, for example, the intense forms of aerobic activity
provided significant outcomes in reducing BMI and other biological determinants,
rather than providing a less intense form of exercise like play time [5]. Longevity
of the program was a varying factor in many of the programs, some as short as
eight weeks and the longest being almost four years [3]. One three-year HOP’N
(Healthy Opportunities for Physical Activity and Nutrition) program had a positive
influence on increasing children’s physical activity but provided no impact
changes on BMI [7]. An additional problem many of the programs faced was
seasonal changes; consistency was lost over the summers when the program
could not run, and this negatively affected some results [2]. Another negative
feature of some studies is a lack of follow up evaluations. This is key in keeping
sustainability of the program after the fact and evaluating how much influence a
program made following into adulthood. There is no overwhelming evidence in
support or against the idea that afterschool programs are definitive in preventing
child obesity, but there are positive results to examine. The purpose of these
studies is to introduce lifestyle changes, such as eating healthier and doing more
physical exercise starting at a young age with the hope that these practices are
continued into adulthood. The objective of this review is to evaluate what
methods of intervention in afterschool programs provide the best results for
preventing obesity.
Methods
A literature search was done in order to collect studies for this review. The
first search was conducted using the University of Texas at Austin library
“ScoUT” database. This search engine looks through all available educational
based literature from a variety of subject specific resources like Wiley Online
Library, PubMed, Web of Science, and a number of Journals pertaining to
nutritional studies. The necessary inclusion criteria included: (1) must be
published in English; (2) must be available online; (3) limit to articles from peer-
reviewed publications; (4) must be published between 2010-2015. This narrowed
the related articles. Some keywords and sentences used were “child obesity and
physical activity” or “child obesity prevention AND intervention”. My second
search was done using the Endnote search engine exclusively linked to the
PubMed database, after typing in the keywords “Child Obesity prevention
programs AND after school AND school based” it resulted in a number of
additional case studies to review on.
Six main articles were chosen that provided a variety of subject
characteristics to compare but all still following a similar design for intervention.
A study conducted by C. Howe et al. pertained strictly to young overweight male
black boys and the physical results from intense physical activity intervention.
This study is unique in that it includes only one demographic with a specific
program focus on physical activity, but designed to have a short duration of only
ten months. The outcome measures of this small sample of 106 participants
cluster-randomized trial were body composition, cardiovascular fitness, and
physical activity assessments [5]. A study lead by Z. Yin et al. much like the
previous study also focused strictly on physical activity intervention with similar
intensity but for a greater period of time of three years versus ten months. This
cluster-randomized trial had a medium sample of 572 participants. Researchers
focused on finding differences in percent body fat and cardiorespiratory fitness
levels [22]. This next study by author U. Meyer et al. was a cluster-randomized
trial with a medium sample size of 502 subjects conducted in Switzerland. This
study also focused on a strictly physical activity intervention much like the ones
previously mentioned. The duration of this study was one of the longest because
although the intervention was only 9 months, follow ups were conducted three
years later, making it almost four years in length from start to finish. Some
outcome measures such as percent body fat, aerobic fitness levels, and physical
activity levels were considered and analyzed in this time. One unique outcome
measure in this study was a questionnaire on quality of life conducted before and
after the intervention [13]. The HOP’N program study by D. Dzewaltowski et al.
provided the largest sample of 961 participants. This study design was much
heavier on follow up and consistency of habits throughout the three-year
duration, rather than immediate results. This randomized control trial focused on
both physical activity and nutrition education. The outcomes measured in HOP’N
were BMI, physical activity levels, and pre/post tests [7]. Another study
conducted by L. Nabors et al. is similar to the HOP’N study in that it has a split
focus on nutritional education and physical activity, but unlike the other studies it
used a sample of only 54 participants for this pilot study. The outcome measures
include parent and child satisfaction ratings, pre/post surveys, and coaching
interviews [14]. This last study by C. Herscovivi et al. was a randomized trial with
a medium sample size of 369 subjects. This was the only study with the sole
focus of the intervention program be nutritional education based. This study took
place in a low-income area of Argentina. Outcomes were compared by gender
and evaluated by BMI and intake questionnaires [16].
Results
A total of 22 articles were chosen to evaluate for this review, with a main
focus on six particular intervention studies. Five of which were randomized
control trials, and one pilot study. The number of participants in each study
ranged from 54 to 961, and ages varied from 1st to 5th grade. Two of the studies
were conducted abroad in Switzerland and Argentina, while the other four were
conducted all across the United States. Across the six main studies there were a
variety of demographics included. African-American, Latin-American, and
Caucasian ethnicities were the most prevalent and accounted for. Most studies
also documented gender percentages and socio-economic status by income
area or qualification for free/reduced lunch. The results of this research will be
compared by outcome measures, and additionally evaluated by program focus;
(1) physical activity (PA), (2) nutrition and health education (NTR), and (3) both
nutrition education and physical activity (PA+NTR).
The first study evaluated is the most intense PA program on the spectrum
for physical activity interventions. This study by C. Howe et al. has the most
significant changes in outcome measures from baseline to follow up. The study
design for this program had a vigorous schedule of 80 min of MVPA (moderate to
vigorous physical activity) lead by a trained personnel staff five days out of the
week. When looking at the results of these African-American male participants,
the intervention group had a significant lower body fat percentage of -2.25 versus
the control group, which only lowered -0.63 (figure 1). The intervention group with
higher attendance was also successful in lowering BMI by -0.2 while all other
groups BMI actually increased (figure 2). The intervention group with the greater
attendance was able to improve their Vmax oxygen levels, which was a unique
outcome measure for this study. The largest change by far was the amount of
MVPA (figure 3). From baseline to follow up it increased 34.8 minutes a day [5].
The following strictly PA intervention study conducted by Z. Yin et al. was
similar in that it that it included 80 min of PA, but was lead by a less qualified
staff. The study stated that there were no significant differences in any of the
outcome measures from baseline to follow up. Although the control group did
improve in some of the outcome measures many of the results fluctuated due to
some faults in the study design. For example WC (waist circumference) improved
in the intervention groups after a one-year follow up, but by the three-year follow
up WC lowered to a similar value of that at baseline. Similar trends in the other
outcome measure values like %BF (percent body fat) were present [22].
This next PA focused study conducted by U. Meyer et al., provided no
significant results in primary outcomes from pre-to-post intervention. Only one of
the secondary outcomes improved despite no significant changes in body
composition from the skin fold tests, there were increases in the shuttle run test
for the intervention group versus the control group at the three year follow up
after the nine month intervention (figure 4). A problem in the reliability of these
results is due to a 58% drop out rate by the end of the last follow up [13].
The HOP’N study conducted by D. Dzewaltowski et al. is one example of
a study that tried to incorporate both physical activity and nutritional health into
the design (PA+NTR). Although this PA+NTR focused study resulted in no
anthropometric changes in BMI between intervention and control groups there
was a significant change in MVPA in the overweight intervention group. From
baseline to one-year follow up MVPA went from less than 12 minutes to about
15, then from one-year to two-year follow up it increased to about 18 minutes of
MVPA (figure 5). The PA of this study was less vigorous than in other PA
interventions because it used “sports engagement” as the form of PA instead of a
stricter measurement of MVPA by heart rate or Vmax oxygen levels. The study
incorporated some nutritional education by presenting some information on
important health practices before each PA lesson, researchers also recorded F/V
(fruit and vegetable) intake by counting the choice in snack that participants
chose each day [7].
In this next PA+NTR focused study by L. Nabors et al., incorporated a
design that allowed for playtime, which included some physical activity, but there
were no outcomes based on any anthropometric or clinical measures. The
results of this study showed that children in the intervention groups had a decline
in the number of unhealthy sweet food items, and increase in fruit intake. This
was measured using pre/post testing and recall of meals. Also 71.4% of the
intervention participants correctly identified non-healthy foods and 91% were able
to identify healthy food items based off the “Traffic Light Diet” nutrition education
lessons [14]. Both PA+NTR focused studied used untrained personnel when
leading these programs.
This last NTR only focus study conducted by C. Herscovici et al. placed an
emphasis on gender differences in low-income areas in Argentina. These results
were heavily outlined by nutrient education outcomes versus physical activity
outcomes. Although there was no significant change in BMI the nutrition and
health programs helped provide significant positive results in the female
demographic. The girls in the intervention groups made more choices in
consumption of healthy food items versus the boy intervention groups. Overall
the program positively influenced the intake of healthy food items, but was
unable to significantly change the intake of unhealthy food items (figure 6). This
intervention was unique in that it was able to modify the cafeteria food being
offered at the intervention schools, and supplemented meals with healthier food
items to choose from [16].
Discussion and Conclusion
When analyzing an accumulation of data from a variety of outcome
measures, trends begin to arise between certain study designs and positive
results. For example BMI changes were evident when PA program intervention
was vigorous. Also researchers were much more likely to increase F/V healthy
food intake than to decrease unhealthy food intake in intervention participants.
These trends help outline the attributes that when incorporated into a study’s
design provide better outcomes in results. Incorporating a strict program focus is
more likely to result in more positive data than split focus. For example if
nutritional education is the main focus, researchers should stick to making
differences in knowledge outcomes and not expect drastic BMI changes from
lessons on healthy food items. A more intense PA guided exercise routine that
incorporates MVPA not just “playtime” exercise. Also restricting the program
duration to one or two years in length. Too long of a program looses participants’
interest, but one year is enough to make anthropometric changes that
participants will want to continue improving upon. Lastly outside program
involvement pertaining to using trained personnel, experienced coaches, and
incorporating a high amount of parent involvement.
When looking at the results from the PA interventions you can tell how one
result in particular indicated the importance of consistency. In the study
conducted by C. Howe et al., the changes in MVPA from base line to follow up
ten months later show a consistent increase of not only duration of exercise but
also vigor [5]. It would be beneficial for the study to follow up again multiple years
later to see if that consistency and increase of MVPA remained. This point of
consistency is important to evaluate because continuing these healthy exercise
habits is the only way to ensure prevention of obesity in later years. We cannot
truly evaluate the success of an obesity prevention program imposed on children
unless we can also determine the outcome of their health as an adult. The
following PA study by U. Meyer et al., which resulted in no significant differences
in any outcomes from the beginning of the study to the end of it, were due to
many holes in its design. The study had a skew in results due to gaps in the
program duration. Duration of the program was a huge problem. There were
three studies that lasted up to three years or more from baseline to follow up, and
all of those studies had a lower number of positive results on outcome measures
than any of the other programs that were shorter in length [7,13,22]. Logically,
one would think with a longer program it would allow for more repetition and
therefore a more consistent change in habits. In these studies that wasn’t the
case at all. The problem most likely lies in that the programs are school-based,
and during the summers no school takes place so there is a lot of time and data
that is lost.
The two PA+NTR studies had some interesting trends in common.
Although these programs focused on physical activity and nutritional education,
the outcome measures for nutrition education were more positive than for those
of physical education. In both studies there was no change in BMI for intervention
groups, but there were positive changes in eating habits and improvements in
intake of healthier food items [7,14].
The one NTR study was completely dependent on behavioral changes
and changes in knowledge about nutritional food items. Many of the differences
in base line to follow up were determined by diet recall of participants. For
example, the children would interview and fill out questionnaires that asked them
what they ate the day before. When dealing with participants that young of age
their memory isn’t always reliable and this leaves room for many errors in
accurately documenting data [16].
Some of the strengths in these studies were the use of large sample sizes,
providing multiple follow-ups to track progress, using trained personnel, and
having a varying amount of intervention program. This variety ranged from
programs that provided four workshops over a six month period to a daily boot
camp type work out five days a week over a ten month period. Many of the
studies conducted built off of one another to improve upon the mistakes made in
other studies. For example, in the gender comparison study they provided
healthy snacks and were able to modify the cafeteria menu items [16]. Another
gender specific study using an all female group called the “LA Sprouts” did
something similar in emphasizing an even greater focus on providing and
growing healthy food items, to have these nutritionally superior food items as
immediate choices [9]. This influences what the participants consume, and with
exposure to healthier food items you are more likely to eat them rather than just
learning about healthy food items but never actually seeking them out to eat. This
was just one example of how these studies are continuously improving upon one
another to be more effective.
Some limitations of these studies included, low parental involvement, high
drop out rates, gaps in program duration, consideration of sexual maturation, and
reliability of diet recalls in children. Participation was a huge challenge for many
studies. It is normal to lose participants over time in a study, but many long-term
studies had to suffer loosing large portions of their participants. This lead to an
increase of sample sizes and monetary compensation for continued involvement.
This problem is still ongoing, and keeping participants involved in a study is
difficult but many research teams are developing ways to improve upon this
problem.
From an initial perspective to now, I thought that research on the topic of
child obesity would result in more positive findings. Although some difference has
been made, an issue of this spectrum and morbidity should have a greater
amount of significant changes. A problem of this magnitude needs a solution,
and the steps being taken are still minimal compared to the drastic changes
necessary. Ideas for future research are coming about to generate these
changes like using celebrity lead programs to motivate children to participate in
more exercise activities and lower drop out rates. Also gearing research to
propose policy changes like increasing budgets for school lunch programs to be
able to afford healthy options. Ultimately, a lifestyle change needs to be made
starting from the beginning of schooling. Greater education on nutrition and what
healthy foods are, along with intensely guided physical activity, are what will
make the greatest influence starting from a young age.
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Appendix
Figure 1: C. Howe et al.
Figure 2: C. Howe et al.
Figure 3: C. Howe et al.
Figure 4: U. Meyer et al.
Figure 5: D. Dzewaltowski et al.
Figure 6: C. Herscovici et al.
CHARTS:
ARTICLE
TYPE OF STUDY
DESIGN # OF SUBJECTS
OUTCOMES
MEASURES
RESULTS DISCUSSION POINTS
Lngterm effcts of a KISS fitness & adiposity
Intervention-PA
Cluster-randomized control trial
50228 classes15 schols(289 followup)
BFAerobic fitnisPAQualofLIfe
SkinfoldShuttle runAccelomtrquestionare
I>C group in AFEffects not maintained
9 monthsfollow up-3yrsnot already fat kidsin switzerland
Gender diff and obese prevention in ARG
Intervention-NTR ed
Randomized trial
369 cldrn9-11 yrolds6 schls
Intake of healthy v unh Questionares
BMI
Girls had better results
6monthsbetter at promoting healthy foods than cutting back unhelth foods-boys v girls-poor ppl
HOP’N Intervention-PA-NTR ed
RCT 9613-4 grade8 schools
Chng in ageGndr BMI z-scPA -accelomtr
BMIsPA v sedPre/post tests
PA vs sed was positive BMI – no sig changePre/post =+R
Time= 3yrsSplit focusG+BF/V eval
10-month PA in Black boys
Intervention-PA
RCT 1068-12 yrsonly black boys
ATT- <60%NATT->60%CNTRL
CVBody compPA
ATT dcrs in %BFCV- similar -CNTLbest
Time= 10 mnth
Impact of 3 yr ASOPP in elem schl
Intervention-PA
Cluster random
5723rd grd18 schools
Only for 60% atten
%BFCRFCMM
%BF & CRF positive for intervention- no diff in cholesterol or BP b/t cntl and interv grps
80 min wkoutTime = 3 yrLost over summers
Impl of ASOPP; help young chld towrd improved hlth
Intervention-NTR ed- play time
pilot 54 chld2 schools
Traffic light diet- eating habitsCHEE/CATCH- Activity levels (AL)
Prnt/chld satisfactionPre/post surveyCoaching – MI interviewing
Incrs in ALRest of data insig
Nurses and training improving resultsGreen v redComm problemScl1 – blk/classschl2- wht/gym
Study Type n Age Duration Location Intervention
C. Howe et al.
Randomized Control
I=62C=44106
8-12 10 months USA PA (physical activity)AS (after school)
Z. Yin et al.
Cluster Randomized
574 7-9 2 yrs and 9 months
USA PAAS(FitKid Program)
U. Meyer et al
Cluster Randomized Control
I=297C=205502
6-13 9 months (then followup 3 yrs later)
Switzerland PAAS(KISS program)
D. Dzewaltowski et al.
Cross-sectional Randomized Control Trial
961 9-11 3 yrs USA PA+NTRAS(CATCH and HOP’N programs)
L. Nabors et al.
Pilot 54 4-9 2 yrs (summers only)
USA PA+NTRAS(CATCH and Traffic Light Diet programs)
C. Herscovici et al.
ProspectiveRandomized Control Trial
I=205C=164369
9-11 6 months Argentina NTRDS (during school)