The main aim of this article is to examine the relationship between socio-economic status and obesity. Extensive research work has been carried out to study the various socio-economic status (SES) indicators and their association with the disease.
From the research, the general pattern of association for both genders to the various socio-economic indicators displayed a high percentage for positive relations and a relatively low percentage for negative relationships as one moved from regions with established socio-economic status to areas with small socio-economic developments respectively.
The findings also documented that women from high social classes were associated with education, while positive association for women in medium and low socio-economic status was associated with income levels and material possessions. It is important to learn about these associations so as to know the differences in obesity using socio-economic status (SES).
There are several social determinants used to shade more light and insight on the differences that exist in the socio-economic front in as far as obesity is concerned. Some of the determinants included occupational class, social status, education, household income, economic difficulties and satisfaction.
The data for the research was obtained from a section of youthful men and women from the City of Helsinki and the survey process was conducted by Helsinki health study surveyors who collected the information from the year 2000 to 2001 and managed to interview 4, 975 women and 1, 252 men respondents. They then fixed a logistics model to extrapolate the documented data and calculate the values for the association between socio-economic status and obesity expressed as BMI ≥ 30 kg/m2.
Measuring the disease
The data obtained was used to calculate the percentage rates of obesity and it was found that the set benchmark for the disease was exceeded with a margin of 14% for women and 15% for men. Various socio-economic indicators were used as determinants; for instance, educational level of the respondent was divided into three categories which included basic education, secondary education and tertiary education.
For occupational class, it was divided into sub-groups as professionals, semi-professionals, non-manual laborers and manual laborers. Other indicators as parental education, economic difficulties, household income, childhood difficulties and homeownership were also subdivided into their respective sub-groups where the respondents had to provide the required information in all the given fields.
From the tabulated data, appropriate correlations between the socio-economic indicators could now be statistically analyzed. The stratified analysis portrayed that all the socio-economic indicators were positively correlated and that there was a more consistent patterning of the disease among women than in men with a confidence interval of 95%.
From the statistics, obesity was more pronounced among individuals with economic difficulties but was not affected by economic satisfaction. In women, various indicators as material resources, age and economic satisfaction were associated with the disease.
The samples that were used in this study were self-administered questionnaires sent to a section of middle-aged employees to act as a representative of the whole population. Two cross-sectional surveys were carried out, one conducted in the year 2000, while the following survey in 2001. The surveys were done on individuals between the ages of 40 to 60 years taking into consideration the aspect of gender.
The sample was somewhat biased because the number of women interviewed was about four times that of men and it was also unfair to leave out 16 women respondents on the grounds that they were pregnant. That was a violation of human rights and a show of gender biasness.
After critically analyzing the socio-economic indicators, it was found that they were all related to obesity more so in women with an exception of material resources and fulfillment of their needs. These determinants were, however related to the disease after considering age factor in the whole equation. In the case for men, statistical regression analysis showed that they were in tandem with the statistics from the female gender only that they did not reach the significant threshold levels.
The findings from the research showed that those with low levels of education had high prevalence rate for obesity in both genders while the low occupational levels were mostly associated with the women. Even though obesity did not change with household income, statistics showed that renters were more obese than the flat occupiers.
When material resources were considered in determining the indicators for obesity, economic difficulties remained associated with the disease while economic satisfaction ceased being part of it. Effects of various indicators on obesity may be mediated by other factors as poor economy status leading to food insecurity in the country and hence promoting the disease.
Using household income as a socio-economic indicator is not a very reliable determinant as income levels tend to change time and again hence not preferred for long term statistics. They also rely on self-reported data and questionnaires that might be easily tampered with or doctored.
Another problem is that some respondents may give inaccurate or false information hence curtailing the course of obtaining accurate statistics. Obtaining of cross-sectional information on socio-economic indicators simultaneously may also be a tall order due to the many variables involved.