Trends in obesity over the last 20 years and implications for the future - Coursework Example

? Statistics assignment Introduction Obesity is generally regarded as a common manifestation of imbalances in energy levels defined as the balancebetween the energy consumption through food, drink and energy expended through the process of metabolism as well as physical activities. The factors which strongly link obesity are mainly lifestyle behavior, diminished physical activity levels, consumption of high energy diets, income levels and so on. In this respect, the body mass index (BMI) includes a significant importance. It is a measurement of the weight defined as kg per square meter. In a conventional manner when the range of BMI is between 25 and 30, then the person is said to be overweight and the person is said to be obese when the value is greater than 30 (Akil & Ahmad, 2011, p. 58). This obesity problem is a common trouble in almost every country in the world especially in the Western countries. Statistical analyses is an important tool which will be directed towards analyzing the trends of obesity in different countries and can give us a clear idea about the historical pattern and suggest important policies for the future. 2. Focus of the paper The main focus in this paper is to conduct statistical analysis to find out different trends of obesity. The country which will be taken into main consideration is USA which. Some propositions will be laid down in this paper and that will be examined with the support of data from valid secondary sources. 3. Obesity in America Obesity is very crucial problem in every society and it is indeed an important problem in the developed nation like United States of America (USA). There has been a growing awareness of the health problems attached with weight as well as availability of light or no fat foods. But despite that there had been a significant incidence of obesity problem in the United States of America. There has been documentation initiating from period as early as 1960s and there has been a consistent year to year rise in the percentage of adults who are suffering from overweight. This trend increases seem to have accelerated. Data collected from the Behavioral Risk Factor Surveillance System (BRFSS) indicates that within a period of 1985-1995 there has been an increase in the BMI from a level of 29.2 to 34.4 and there has been an increase in the percentage from a magnitude of 8.6 to 15.2. The correlation between overweight and many of the chronic diseases as well as various obnoxious health outcomes has made this a serious health concern. Obesity as a factor also gets associated with nation’s burgeoning health care bill. It is estimated that for the year 1990, the costs including direct and indirect costs of the excess weight in the USA were figured at the amount of $46 billion and $ 23 billion respectively (Binkley, Eales & Jekanowski, 2000). The propositions which will be examined in the paper are: 1. There has been an increasing trend in the obesity of USA in the last twenty years 2. Obesity is the highest for USA as compared to other countries 3. Race also plays an important part in USA with respect to obesity 4. The standard deviation of obesity of the data of USA is highly scattered 5. The effects of the policy implemented are ineffective in USA. 4. Analysis Before moving into analysis, the method of data collection is to be mentioned. For the purpose of data collection, we have relied on the government site of USA .The database for data collection which is used is the center for disease control and prevention (CDC) in USA. CDC helps in the creation of expertise, information as well as tools which the people as well as the communities requires for the purpose of protecting their health with the help of promotion, disease prevention, injury and disability as well as preparedness for the threats of new health problems. CDC directs towards accomplishing its mission through working with the partners all over the nation as well as in a global basis for the purpose of detecting as well as investigating the health problems, conducting research as well as implement various strategies and also provide leadership and training environment (Vision, Mission, Core Values, and Pledge, 2013) . Let us start with descriptive statistics. Descriptive statistics are utilized towards describing the fundamental features of data in a particular study. Descriptive statistics helps in the provision of summaries regarding the sample and population measures. Along with simple graphical analysis they are regarded as the base of any quantitative analysis of data. The process of descriptive statistics is used towards presenting quantitative descriptions in a proper manageable form. The descriptive statistics helps in the reduction a lot of data into a simple summary. The analysis in the paper includes a univariate data analysis as it involves the analyses of one variable at a time. The focus will be entailed on various parameters and they are the distribution, central tendency and dispersion. Distribution basically is the summary of the frequency of the individual values or that of ranges of variable or values of a variable. As an instance it can be stated that the simplest distribution would be including every value of a variable and the number of observations involved in them. One of the most common methods is that of describing a single variable with a frequency distribution. Depending on particular value all of the data values are represented. A typical example can be stated to be described as the distribution of various college students in a year in a college which lists the number or that of the percent of students in each of the year. In this respect the notion of histogram can be incorporated. A histogram is basically a representation of a frequency distribution which is represented through rectangles with widths representing class intervals and areas being proportional to various corresponding frequencies. Fig.1 Histogram of the obesity data, USA (Appendix 1) The above diagram represents the histogram of the data that we have considered. The data considered considers seven time ranges starting from 1988 to the year 2010. In this data the percentage of obesity in every time span is different and it is plotted accordingly on the horizontal axis which represents the range of the obesity data. The corresponding frequency of every obesity data does not have any exact frequencies. It represents only the percentage of population who are suffering from obesity problem. So the cumulative frequencies in the above diagram are 100% corresponding to each data of obesity. Bar diagram represents the graphical representation of the univariate data taken into consideration. As for example it includes sales, production figures, and population figures and so on. These can be plotted corresponding to various years. These graphs are of the same width and vary in the observations only. The practice of bar diagram is highly useful in practice as it gives the reader a clear view of the data representation. The bar diagram or that of a bar chart may be horizontal, vertical and graphical. The following diagram shows the bar diagram which represents the trend of obesity data in USA over the past twenty years. Fig2. Bar chart showing the trends in obesity in USA over a span of twenty years (Appendix 1) The above diagram shows that the obesity figures in USA are rising in an increasing manner over the years. This supports the first proposition. The age group used is from 12-19 years. Now bar chart will be also used for showing country wise obesity data and will highlight on proving the second proposition. Fig.3 Obesity percentage across various countries (Appendix 2) The above bar chart shows that among the comparison of various countries which have high obesity rate increases, USA has the most predominant incidence of obesity. This proves the second proposition. The data has been used for 2003. Pie charts are one of the most commonly used chart type in representing data. The application of pie charts are often found in newspapers, business reports, blogs, internet articles and many other places. The slices in the pie chart are basically mutually exclusive and they do not usually overlap. The values need to be categorized in such a way that they do not get counted on several times. The percentages of slices sum to 100 percentage. Now, the third proposition will be proved by the help of pie chart. In USA we have found that the president Barack Obama himself comes from a black origin but the problem of obesity has been most prominent among the Non-Hispanic Blacks. This will be shown in a pie chart. The analysis will be cross sectional with a fixed time period i.e. 2012. Fig.3 Obesity across race in USA, 2012 (Appendix 3) The above pie chart shows that the Non-Hispanic Blacks are have the most prominent obesity rates in USA. Measures of central tendency are a distribution which helps in determining the center of the values of distribution of values. The three types of central tendency are mainly mean, median and mode. The mean is the average which measures the most commonly used method for the purpose of describing the measures of central tendency. Mean 32.95 Standard Error 0.924391692 Median 33.1 Mode Standard Deviation 2.264287968 Sample Variance 5.127 Kurtosis -1.831576266 Skewness 0.000697734 Range 5.6 Minimum 30.3 Maximum 35.9 Sum 197.7 Count 6 Table 1. Descriptive statistics (Appendix 4) The above table provides the value of descriptive statistics of the data in use. The data in use includes the crude obesity rates of USA. The arithmetic mean of the data taken into consideration is 32.65 percentages which represents that within the period of twenty years the mean obesity of USA stands at a level of 32.65. This states that 32.65 percent of the total population of USA is suffering from obesity. Median is the value which points out the exact middle value of the observation. The median value of the data taken into consideration is 33.1 which states that 33.1% of the population in USA is within the time span of twenty years. The mode is the most frequently occurring value in the set of scores. To determine the mode, you might again order the scores as shown above, and then count each one. The most frequently occurring value is the mode. In this case, the mode value is nil as the corresponding value of frequency of the obesity taken is nil. Measures of dispersion indicate the spread of values with respect to the central tendency. There are two common measures of dispersion which are dispersion as well as standard deviation. The range depicts the difference between the highest value and lowest value. The range value of this distribution is 5.6. More the difference more scattered is the data. Standard deviation is a more accurate as well as detailed measure of dispersion which represents the outliers within the data exaggerating the range. The standard deviation in this data is 2.264 which represents that the value from the mean is highly scattered. This signifies that the standard deviation is high and it also proves the third proposition. 5. Limitations in legal implementation There has been strict ban on the sugary drinks in the schools of America. But the policies have been rather ineffective in USA especially among the kids and the students. The use of soda pop and sports drinks are immense among the students within USA. Studies published in the Archives of Pediatrics & Adolescent Medicine have analyzed the eating habits of the students from 5th grade to 8th grade students in 40 schools across the USA. It was found that regardless of strict school policies on the soda pop and sweetened drink there has been rampant consumption of these stuffs among the students in USA. Various researchers from Illinois University in Chicago went through a study of cross section of schools with different soda pop policies. The survey results suggested that the schools and the public health authorities require on a more rigorous basis towards developing anti-obesity strategies that go beyond simply from the imposition of a blanket ban on the soda. The reports stated that the students drank the same amount of sweetened drink at least once a week. The bans may state that it can reduce the in school access and the latest study directs that the kids are finding alternative ways towards access of sugary drinks (School soda ban ineffective in fight against childhood obesity, according to study, 2011). 6. Conclusion The paper represents the trends in obesity of USA within a span of twenty years. With the help of statistical tools it has been proved that the obesity is increasing and it is a major problem. The obesity data is highly scattered and there has been limitations in the policy implementation and this needs to be modified and restructured. . References 1. Akil, L & Ahmad, A, (2011), EFFECTS OF SOCIOECONOMIC FACTORS ON OBESITY RATES IN FOUR SOUTHERN STATES AND COLORADO, Ethnicity & Disease, Vol. 21 2. Binkley, J, K, Eales, J & Jekanowski, M, (2000), The relation between dietary change and rising US obesity, Internal journal of obesity, Vol. 24, Issue.8 3. Health, United States, (2011). Available at < http://www.cdc.gov/nchs/hus/healthrisk.htm> (accessed on 25 February, 2013) 4. Health statistics, Obesity most recent by country, (2013). Available at, < http://www.nationmaster.com/graph/hea_obe-health-obesity> (accessed on 25 February, 2013) 5. School soda ban ineffective in fight against childhood obesity, according to study, 2011). 6. Vision, Mission, Core Values, and Pledge, (2013). Available at, (accessed on 25 February, 2013) Appendix 1 (Health, United States, 2011, fig10.) Appendix 2. Countries Obesity (12-19 years) USA 30.60% UK 23% Australia 21.70% Japan 14.10% Mexico 24.20% (Health, United States, 2011) Appendix 3 Non-Hispanic blacks 49.50% Mexican Americans 40.40% Hispanics 39.10% Non-Hispanic White 34.30% (Health statistics, Obesity most recent by country, 2013). Appendix 4 1999-2000 30.3 2001-2002 30.6 2003-2004 32.3 2005- 2006 34.7 2007-2008 33.9 2009-2010 35.9 (Health, United States, 2011, fig.10) Read More