本篇文章主要是超重人群健康分析，研究发现，超重人群与基础代谢指数之间存在着直接的相关性。同样的模式也适用于女性和男性，腰围越高的人血压越高(2012年英国健康调查)。的统计数据显示,有一个相关性环境和BMI的测量,年龄,出生时体重,性别以及教育水平.Bases购买食物和饮料,每个个体是4.1%的总摄入量能量低在2012年与2008年相比。这是一个显著的统计下降相关，在整个4年的时间内，证实了长期下降相关明显(社会科学研究方法，2014)。2012年，平均每人每天摄入2209千卡的能量。本篇休斯顿论文代写文章由美国论文人EducationRen教育网整理，供大家参考阅读。
There was a direct correlation found to exist between those who are overweight and their Basal metabolic index. The pattern was same for females and males revealing a higher blood pressure for those with raised circumference of their waist (Health survey for England 2012). Also the statistics revealed that there was a correlation between environment and the measurement of BMI, age, weight at birth, gender as well as level of education .Bases on the purchase of food and drink, the total intake of energy per individual was 4.1 percent low in 2012 when compared with that of 2008. This was a significant statistical downward correlation throughout a period of 4 years confirming the long term downward correlation apparent (Social science research methods, 2014). Total intake of energy was considered at an average of 2209 kcal per individual each day in the year 2012.
Health Outcomes as per the correlational analysis indicated that there is a strong positive correlation between scores of obesity and negative health outcomes.
The following graph has been taken from health statistics database. It depicts Spearman’s rho correlation coefficients inclusive of “a” being the correlation that exists between physical activity of habitual nature and energy density on an average along with dietary fat percent saturated through visiting year and b is the correlation between habitual fibre intake and physical activity (Lichtenstein et al 2006).
The following is canonical correlational analysis to evaluate health attitudes and obesity correlated with composition of body taken from the statistics (Lichtenstein et al 2006) (Social science research methods, 2014). The variance percent is explained through initial indices and initial indices with standardization for canonical co-efficiency.
Here significance is given at P is lesser than 0.1 and significance at P is less than 0.05 for dependant significance variates evaluation with univariate association test along with initial correlation analysis (Health at a glance 2013). It was evident that the relationship existing between variables in the groups was different from an year to the other but the correlation existing between the population groups that is obesity correlates as well as composition of body decreased with every visit to the health care with decrease in correlation with regard to linear trends for combined data wherein R2 =0.72 (Health survey for England 2013). This revealed a reduction related to age in relationship lying between correlates of obesity and composition of body.
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