Project Research Work - Morbid Obesity among women living in south-eastern Australia

Problem case desacription is as follows:

Back ground:

The obesity epidemic is generally monitored by the proportion of the population whose body mass

index (BMI) exceeds 30 kg/m2. but this masks the growing proportion of those who are morbidly obese.

The aim of this study was to determine how the prevalence of morbid obesity (BMI ≥ 40.0 kg/m2) has changed over a decade among women living in south-eastern Australia.

Methods:

BMI was determined for women in the Geelong Osteoporosis study (GOS) during two time periods, a

decade apart. Height and weight were measured for 1,494 women (aged 20–94 years) during 1993–7 and for 1,076 women (aged 20–93 years), 2004–8, and the BMI calculated as weight in kilograms divided by the square of the height in metres (kg/m2). Prevalence estimates were age-standardised to enable direct comparisons.

Results: Mean BMI increased from 26.0 kg/m2 (95%CI 25.7-26.3) in 1993–7, to 27.1 kg/m2 (95%CI 26.8-27.4) in 2004–8. During this period, the prevalence of morbid obesity increased from 2.5% to 4.2% and the standardised morbidity ratio for morbid obesity was 1.69 (95%CI 1.26-2.27). Increases in mean BMI and prevalence of morbid obesity were observed for all ages and across the socioeconomic spectrum.

Conclusions: These findings reveal that over a decade, there has been an increase in mean BMI among women residing in south-eastern Australia, resulting in a measurable increase in the prevalence of morbid obesity.

Keywords: Morbid obesity, Women, Epidemiology, Body mass index

Obesity-related health expenditure in Australia exceeded $8 billion in 2008, which included expenditure associated with metabolic disease, cardiac disease and surgical complications [3], but it is unclear

how much of this expenditure related to different levels of obesity. It seems that both direct and indirect

costs will amplify as the prevalence of morbid obesity increases.

Back ground:

In Australia, few, if any, studies have described the pattern of morbid obesity in the population. Thus, we

aimed to document changes in the prevalence of morbid obesity (BMI ≥ 40.0 kg/m2) that have occurred over a

decade among women living in south-eastern Australia.

Methods

Subjects

At baseline, an age-stratified sample was recruited so that there were approximately 100 individuals for each 5-year age-group 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64 and 65–69 years, and approximately 200 individuals for each of the age groups 70–79 years and 80 years and older.

Baseline assessments for women enrolled in the GOS occurred during the period 1993–7

(1,494 recruited, 77% response) and again approximately a decade later, 2004–8 (882 of the eligible women were assessed at the 10-year follow-up with 82% response). A further sample of 194 women aged 20–29 years was also randomly generated using the same methods employed for the baseline recruitment (2005–8, 82% response) and included in this study. Thus, data from 1,076 women

were included in analyses for the 2004–8 time period. Most of the cohort (99%) was Caucasian; details of the

study have been provided elsewhere [4]. All participants gave written, informed consent. The Barwon Health Human Research Ethics Committee approved the study.

BMI expressed as weight/height2 (kg/m2). An adult with a BMI of 40.0 kg/m2 or over is described as being morbidly obese (class III obesity) but the term can also refer to those who have a BMI over 35 kg/m2 with obesity-related comorbidities[5]. We identified morbid obesity using BMI criteria alone. Class II obesity corresponded to BMI 35.0-39.9 kg/m2, class I obesity to BMI 30.0-34.9 kg/m2, overweight to BMI 25.0-29.9 kg/m2, normal weight to BMI 18.5-24.9 kg/m2 and underweight to BMI <18.5 kg/m2 [6].

Area-based socioeconomic status (SES) was determined using the Socio-Economic Index for Areas (SEIFA) values based on census data (for 1996 for 1993–7; and for 2006 for 2004–8) from the Australian Bureau of Statistics (ABS). SEIFA values were used to assign an Index of Relative Socioeconomic Disadvantage, which was categorised into quintiles according to cut-off points for the study region.

Statistical analysis

In order to compare the prevalence of each BMI category in 1993–7 and 2004–8, both time period datasets

were stratified into age-groups and age-standardised to the 2006 census population figures for the Barwon Statistical Division (ABS Catalogue No. 2001.0). The standardized morbidity ratio (SMR) for morbid obesity was calculated using the 2004–8 dataset as the standard.

The distribution of BMI was skewed, but was normalised by natural log-transformation. Differences in mean BMI between the two time periods were determined using linear regression models. The variable of interest was the period of assessment (1993–7 or 2004–8) and the models were adjusted for age and SES tested as a potential confounder. Differences in the likelihood of morbid obesity during the two time periods were determined using logistic regression models. The outcome was morbid obesity and the exposure

variable of interest was the period of assessment; models were adjusted for age and SES tested as a confounder. This method enables a comparison of the likelihood of morbid obesity between women of the same age and SES in the different time periods. In the statistical models, interaction terms were tested as effect modifiers and retained in the model if p < 0.05. Statistical analyses were performed using Minitab (version 15; Minitab, State College, PA).

CASE REQUIREMENTS:

Your Project should be complete and contain sections entitled:

·       Hypotheses: this section should contain the hypothesis or hypotheses that you tested. This section should be 1 to 2 pages in length.

·       Research Design: this section should clearly define the independent variable(s), the levels of such, and the dependent variable(s). This section should be 1 to 2 pages in length.

·       Statistical Methods: this section should clearly define all the statistical procedures you employed to test the hypotheses. This section should be 1 to 2 pages in length.

·       Results: this section should be the simple statements that can be derived from the statistical output. This section should be 1 to 2 pages in length.

·       Interpretation: this section should contain the statements regarding whether you fail to reject the hypotheses based on the chosen statistical procedure. This section should be 1 to 2 pages in length.

·       The Final Project should be at least 5 to 7 pages in length. Provide references. The reference page and title page do not count in the final page requirement. APA formatting is required.