Childhood Obesity Finally, this paper also includes data and trends revealed in individual studies where the findings are relevant.
Overweight: Scaling Back on Childhood Obesity
Childhood obesity has become a growing source of concern in America. Before 1980, 6.5% of children between 6 and 11 years of age were overweight or obese and 5% of children between 12 and 19 years old, but, by 2004, those numbers increased to 18.8% and 17.4%, respectively (Lawrence, Hazlett, & Hightower, 2010). The tripled rate of obesity combined with the impact of being overweight or obese during childhood is a major public health issue.
Being obese or overweight during childhood increases the risk for developing chronic diseases such as depression, hypertension, respiratory problems, high cholesterol, and type 2 diabetes (U.S. Department of Health and Human Services, 2005). Obese adolescents are more likely to become obese adults (DiMattia & Denney, 2008). Obesity expenditures were 8%, or $69 billion in 1990, grew to $92.6 billion, or 9%, by 2002, and are projected to reach 16%, or $860 billion, by 2030 (Lawrence, Hazlett, & Hightower, 2010). Obesity continues in a cycle from parent to child, with a child with 2 obese parents having an 80% chance of becoming obese as well (Nauta, Byrne, & Wesley, 2009). Given this trend of increasing childhood obesity and the cycle it perpetuates, the impact on individuals, and the social and economic costs, it is imperative to examine the issue of childhood obesity further.
This paper will examine data from national studies and a meta-analysis that demonstrates that the growing trend is the result of correlated trends in schools, homes, and society. While this paper focuses on the trends and their relation to obesity, where programs have attempted to reverse trends, they will be discussed. This paper will first discuss the background of obesity and its general etiology. Then, this author will review the methodology of the analysis and data used. The next part will provide findings, analysis, and evaluation. The paper will conclude with brief recommendations.
Obesity is "a chronic condition characterized by an excessive or abnormal increase in the accumulation of fat cells in the body" (Nauta, Byrne, & Wesley, 2009). While a number of factors contribute to a person becoming and remaining obese, the basic etiology or cause of obesity is an imbalance between energy expended and caloric intake (Hagarty et al., 2004). This imbalance is brought on by a combination of genetic, environmental, and behavioral factors (Nauta, Byrne, & Wesley, 2009).
One can have a genetic susceptibility to being overweight, which causes a larger weight from an increase in food intake than for those without the susceptibility (Francis et al., 2007). Behavioral and social factors also play an important role. Food consumption behavior, school food environment, psychological disorders, and family environment all impact the child's propensity for obesity (Lawrence, Hazlett, & Hightower, 2010). In order to understand the trend of obesity rates, the trends of these factors must be analyzed as well.
III. Methodology and Data
This paper looks at data generated by a number of studies. First, the Centers for Disease Control and Prevention (2010), gathered data across the country, in all 50 states, in public and private schools. The limitation of this source of information is that the study only sampled grades 9-12, or ages 14-18, and looked primarily at the week preceding the survey (CDC, 2010). Second, there is a meta-analysis that examined 13 studies with participants generally 0-19 years old, some of which were birth cohorts, and the studies lasted 4-33 years (Tamayo, Christian, & Rathmann, 2010). Third, there is data and statistics from the CDC's National Center for Chronic Disease Prevention and Health Promotion (2010), Division of Adolescent and School Health, which also looks at high school data regarding health education, school environment, nutrition, and ...
This methodology has been chosen because it offers the widest latitude of information. First, obesity and its causes are not easily measured at a single point in time. Rather, a longitudinal study works best. Thus, the cumulative analysis performed by Tamayo, Christian, and Rathmann (2010) is a suitable source of data because the studies it uses offer longitudinal information. Second, environmental factors are different by location and sampling in one area only offers the biases that impact that area. As a result, the Youth Risk Behavior Survey (CDC, 2010) and data from the National Center for Chronic Disease Prevention and Health Promotion (2010) offer a national perspective on the data. Even still, because of the multifaceted nature of this issue, individual studies are needed to provide evidence about the related trends.
The CDC (2010) identifies dietary behaviors that minimize the risk of obesity or, in other words, contribute to the risk if the individual does not have these behaviors. These are eating fruit or drinking 100% fruit juice two or more times per day; eating vegetables three or more times per day; drinking three or more glasses of milk per day; not drinking soda at least once per day (CDC, 2010). The National Center for Chronic Disease Prevention and Health Promotion (2010) builds on this concept with statistics regarding nutrition services and the school dietary environment.
The CDC (2010) and the National Center for Chronic Disease Prevention and Health Promotion (2010) also examine the physical activity undertaken by adolescents. The CDC (2010) accumulated data frequency of physical activity for at least 60 minutes per day, computer use, television-watching habits, and physical education courses (or lack thereof). The physical activity of the child impacts the balance of caloric intake to expended energy.
The Tamayo, Christian, and Rathmann (2010) study offers input on psychosocial factors. These are the environmental aspects that contribute to obesity. Specifically, the environmental factors include the parents' occupation or occupations, parental education levels, and family income (Tamayo, Christian, & Rathmann, 2010). The other individual sources noted the contribution to risk of a working mother (Maher, Fraser, & Lindsay, 2010) and the positive impact of certain measures (Fisher et al., 2003).
This collection of data, though piecemeal, offers the most thorough look at the complex issue of child obesity and its trends. With the limited time and resources for this research, these sources of data are the best. They will help identify the increase in obesity and the increase in the factors that contribute to obesity's prevalence, opening up options for focused, future research.
IV. Findings, Analysis, and Evaluation
Of children ages 6 to 11, 18.8% are obese and 17.4% of adolescents 12 to 19 years old are obese (Lawrence, Hazlett, & Hightower, 2010). The CDC found a lack of healthy dietary behaviors and insufficient physical activity. Only 33.9% of students had eaten fruit had fruit juices two or more times per day, only 13.8% had vegetables (excluding fries, potato chips, and other fried potatoes), only 14.5% had 3 or more glasses of milk, and only 37% had been physically active for at least 60 minutes, 5 times that week (CDC, 2010).
The school's nutritional environment and physical education requirements or opportunities added to the issue. Only 18% of students were able to purchase fruits or vegetables, but 50% could purchase chocolate candy (National Center for Chronic Disease Prevention and Health Promotion, 2010). Only 45% of schools had physical activity clubs or intramural activities, 2% of schools required daily physical education for the entire year and, amongst those that had even partial physical education requirements, 41% allowed students to be exempted (National Center for Chronic Disease Prevention and Health Promotion, 2010). Physical education has been declining while obesity has been rising. Forty-two percent of students participated in daily physical education classes in 1991 (Fisher et al., 2003).
Schools have the ability to positive impact students' health behaviors. A school-based health intervention program decreased prevalence of obesity in girls ages 11 to 13 (Fisher et al., 2003). Unfortunately, the statistics regarding school health education and interventions do not indicate that schools are taking advantage. Only 53% teach nutrition and dietary behavior in a required health course and only 38% teach physical activity topics in a required health education course (National center for Chronic Disease Prevention and Health Promotion, 2010). Additionally, health professionals at schools do not or cannot intervene. For example, while 99% of nurses in one survey noted their awareness of the increasing rate of childhood obesity and their opinion that alleviating childhood obesity is more important than alleviating adult obesity, only 43% recommend weight loss treatment for obese children (Nauta, Byrne, & Wesley, 2009).
Tamayo, Christian, and Rathmann (2010) noted significant results only in some of the examined studies. For example, income disparities had consistently negative impact on obesity rates, with being from a low income family being "a significant predictor of obesity at an earlier age" (Tamayo, Christian, & Rathmann, 2010). Some scholars have suggested the increase in female employment, the corresponding decline of the family meal, and the increased consumption of fast food or other unhealthy options has contributed to the rise of obesity (Maher, Fraser, & Lindsay, 2010). Parental…
Finally, this paper also includes data and trends revealed in individual studies where the findings are relevant.
Development of Policy Responses The first step in the development of these policy strategies was to identify that a problem existed with childhood obesity and frame the problem so that it could brought to light and intervention strategies debated. While some of the framing of this issue may have been based upon misinformation, policymakers did attempt to frame the problem which is in line with the Australian policy development cycle. This