Analysis of Childhood Obesity in Alabama and Delaware: A Cohort Study

Objective: The objective is to evaluate data sets for children aged 24 to 59 months that identified the risk factors of being obese and overweight and compare it between two U.S. states (Alabama and Delaware). Methods: An analysis of survey data sets published between 2013 and 2017, comparing the factors of obesity and its prevalence amongst different races of 50,760 children aged 24 to 59 months in the U.S., was conducted using Microsoft Excel 2016 and IBM SPSS version 1.0.0. Results: Hispanic children have the highest rate of obesity in the U.S compared to all other races. Children aged 2 - 4 years old from Alabama were more at risk for being overweight and obese compared to those from Delaware. Those between the ages of 48 - 59 months of age were more at risk than the other age groups. Conclusions: Childhood obesity is a predisposing factor for adult obesity. There is a need to identify the risk factors of obesity early in a person’s life and address them appro-priately.

include underwater weighing (densitometry), multi-frequency bioelectrical impedance analysis (BIA), magnetic resonance imaging (MRI), waist circumference, and skin-fold thickness [4]. Worldwide, factors such as the environment that one grows up in, lifestyle preferences and culture play an important role in the rising prevalence of obesity [4].
One's diet habits play a huge role as well. A source mentions that a poorquality diet that consists of high-calorie foods lacking the necessary micronutrients needed for optimal neurobehavioral development and growth can contribute to the issue of obesity and cause severe diet-related chronic diseases and deficits in learning capacities [5]. If nothing is done about this health issue, the child is at risk for developing chronic diseases later in life. The hypothesis of this research is to examine the contributing factors to childhood obesity in Hispanic children in the U.S., compared to other populations. For children living in the United States, other contributing factors to obesity are family income level, parent's educational level, geographical location, and immigration status. To reduce the prevalence of childhood obesity, several evidence-based public health strategies have been put in place. This includes, promoting breastfeeding, limiting screen time, encouraging physical activity, increasing fruit and vegetable consumption, regulating portion size, and limiting the intake of sugar-sweetened beverages [6].

Methods
The dataset used for this study is titled, the Nutrition, Physical Activity, and Obesity-Women, Infant, and Child. It includes data on the weight status for young children aged 3 months to 4 years old from Women, Infant, and Children Participant and Program Characteristics (WIC-PC). WIC is a program put in place by the Food and Nutrition Service of the U.S. Department of Agriculture (USDA) to provide a combination of direct nutritional supplementation, nutrition education and counseling, and increased access to health care and social service providers for pregnant, breastfeeding, and postpartum women; infants; and children up to age five [7].
Data was collected between the time periods of 2008 to 2014 for all states in the U.S. To determine the child's weight status, questions such as percent of WIC children aged 2 to 4 years who have an overweight classification, percent of WIC children aged 2 to 4 years who have obesity, and percent of WIC children aged 3 -23 months old who have a high weight-for-length was asked. Variables such as sample size, low and high confidence intervals, were all calculated.
An analysis of the survey data sets across the different states in the U.S. comparing the risk factors of being overweight and obese and its prevalence amongst different races of children aged 24 months to 59 months old in the U.S, was done using Microsoft Excel 2016. Birth dates were used to calculate age. Children were assigned to a weight status category of overweight (BMI ≥ 85 th percentile and <95 th percentile) or obese (≥95 th percentile) based on CDC growth chart criteria.

O. M. Muomah Open Journal of Pediatrics
Analysis was done for two U.S. states with a higher prevalence of childhood obesity in Alabama and Delaware. Variables such as age, gender, and race were analyzed. A clustered column was then created to interpret the individual data sets and represent the figures. 50,760 children aged 24 months to 59 months in two different U.S states were a part of this study. For the states of Alabama and Delaware, the 2014 data was used. Using IBM SPSS version 1.0.0, a Chi-square test was conducted to show statistical significance between all identified variables.

Results
Hispanic children have the highest rate of obesity in the U.S compared to all other races. Children aged 2 -4 years old from Alabama were more at risk for being overweight and obese compared to those from Delaware. Those between 48 -59 months of age were more at risk than the other age groups. Confidence Intervals were also included to show significance.
As identified in Table 1 which shows the 2014 demographic characteristics of children with obesity in Alabama and Delaware, an analysis of 43,509 children from Alabama were classified as being either obese or overweight. Comparison done for the different age groups show that age plays a large role in childhood obesity with age group 48 to 59 months having a higher percentage of overweight (17.6%) and obese (18.6%) children when compared to other age groups ranging from 24 -47 months. Gender was not a precursor for childhood obesity as identified by the ratio of obese males and females. The race was found to be a contributing factor to childhood obesity with 20.3% of Hispanic children being overweight, while 25.2% were obese, a much higher percentage when compared to other races, as identified in Figure 1. In total, 16.5 percent of children in Alabama were found to be overweight compared to 16.3 percent who were found to be obese.
In the state of Delaware, 7251 children were classified as being either obese or overweight. As identified in Figure 2, comparison done for the different age groups show that age plays a large role in childhood obesity with age group 48 to 59 months having a higher percentage of overweight (16.3%) and obese (21.6%) children when compared to other age groups ranging from 24 -47 months. Gender was not a precursor for childhood obesity as identified by the ratio of obese males and females. The race was found to be a contributing factor to childhood obesity with 25.9% of Hispanic children being overweight, while 24.2% were obese, a much higher percentage when compared to other races. There was no identified data on American Indian/Alaska children who were obese or overweight. In total, 16.2 percent of children in Delaware were found to be overweight compared to 17.2 percent who were found to be obese.
To show statistical significance, a chi-square test was conducted to test which variable(s) was directly associated with childhood obesity. The variables tested were age, gender, and race. As shown in Table 2, chi (8.727) > df (5.99) proved that age was statistically significant and is directly associated with one's weight; chi (0.03599) < df (3.84) proved that gender was not statistically significant and Open Journal of Pediatrics is not directly associated with one's weight; chi (143.204) > df (9.49) proved that race was statistically significant and is directly associated with one's weight.

Discussion
After comparison of data for both the states of Alabama and Delaware, the values show that being Hispanic is a strongly significant factor to being either overweight or obese when compared to other races. Hispanic children are more prone to being overweight/obese due to socioeconomic factors such as family O. M. Muomah  income level, educational level, geographical location, and immigration status.
Additionally, the female populations are more predisposed to being overweight/obese when compared to the male population. Also, age is a factor because children who were between 48 months to 59 months showed more significance with a higher confidence interval than other age groups.
Some of the limitations to this study were missing data for some sample siz-   Including other risk factors such as parent's educational level, immigrant generation, and household language would have further strengthened the study.
Another limitation was the missing data for American Indians in the state of Delaware. Having a completion date for all races would have helped with a better comparison between the two (2) U.S. states.

Conclusions
In conclusion, being overweight is considered a risk factor for childhood obesity portable also play a major role in a child's diet. This is because parents of children from a poor background might be too busy working and not have the luxury of time and money to buy or cook healthy foods often settling with just the fast-food option which is not as healthy. Genetics plays a major role in the weight of a child with several identified cases of children with parents/family members who were obese, hence, having a higher tendency of being overweight or obese themselves. Additionally, lack of transportation could negatively affect their food choices. It is certainly an issue because it limits the parent from easily accessing a grocery store; it also limits their access to educational nutritional programs [8].
What is already known on this topic • Previous research shows that overweight kindergartners had four times the risk of becoming obese by the age of 14 years as normal-weight kindergartners [9].
• Another study revealed that breastfeeding was a protective factor against obesity, especially when given at the early stages of one's life.
What this study adds • This study analyses predisposing factors such as age, gender, and race that contribute to childhood obesity.
• This study indicates that breastfeeding at 1 year of age was associated with a decreased weight percentile for age, body mass index percentile and z-score for age, and waist circumference below the 90th percentile [10].

Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper. (e) Describe any sensitivity analyses

Results
Participants 13* (a) Report numbers of individuals at each stage of study-e.g. numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analyzed 5, 6 (b) Give reasons for non-participation at each stage 5, 6 (c) Consider use of a flow diagram 5, 6 Descriptive data 14* (a) Give characteristics of study participants (e.g. demographic, clinical, social) and information on exposures and potential confounders 5, 6 (b) Indicate number of participants with missing data for each variable of interest 5, 6