Research On The Distribution, Causes, And Effects Of Overweight And Obesity In Australia

Problem Definition

Maybe food is not that good after all!? Or to state it more simply, unobserved food consumption is not good for your health. Even then, what can be the comfortable measure to be termed as observed food consumption and what is not?  Such and other dilemmas alongside a number of other factors such as genetics have left Australia marred from the after effects of unobserved food consumption which more often than not are indicated by overweight and obesity. Shahian (2018) in her article on the causes, effects and probable diagnosis of obesity states that “obesity occurs in an instance where a person has an above average fat in their body.” Further she notes that obesity may be caused by factors such as:

1. Illness
2. Poor diet

• Sedentary lifestyle

1. Family
2. Socioeconomics
3. Genetics

Sadly, obesity as an issue is not only an Australian problem but a trend spread among a number of nations, Zukiewicz et al (2014) on the paradox of obesity in developed nations, identifies that there are more instances of obesity in developed counties than there are in underdeveloped countries. The paper notes “… the number of obese people in Europe has increased threefold over the last 20 years…” (Zukiewicz et al, 2014).

The aim of this paper is to explore the distribution of obesity in the Australian society through exploration of the different social statistics; the analysis will involve stratification of the society into a number of stratums such as age groups, socioeconomic classes, and geo-location. From the analysis, inferences on the effects of various factors that cause overweight and obesity, conclusions on the distribution of obesity effects will be drawn and recommendations to some of the suitable remedy given for consideration by the relevant authorities.

The research’s main concern is to explore the distribution of obesity and overweight majorly in the Australian society as well as examine how Australia performs in the wider image of developed countries. The paper also explores what would be the causes of obesity and overweight. It aims at establishing a pattern between the obesity rates among different social strata through data analysis and inference to previous studies. Following the analysis and discussion, the paper should be able to offer effective guidelines to possible remedies and preventive measures for overweight and obesity.

A survey by Comans et al (2017) indicates that young children are among the major causalities of obesity, therefore begging the question as to what really causes obesity and who is to take responsibility. Depleuch et al (2015) in their paper on obesity and developing countries of the south, argue that obesity is rampant among the affluent in the society, in this regard, he notes that, “…excess weight appears first among the affluent and then among the low-income. According to Flynn MA (2006), for a while obesity has been an issue mostly related to the developed countries; however it has recently encroached developing counties, indicating an increase in the overall statistics recorded on overweight and obesity. The major factors that influence obesity are nutrition adoption of fat-enriched foods mostly found in junk foods. Chapparro (2010) identifies fat-enriched foods as lipid-based which are a “range of fortified, lipid-based products…” which are ready-to-use also known as fast foods most often categorized under junk foods which are among the major contributors of fat in the body. (Chapparro, 2010). In a study on the factors that influence obesity in Australia: Gulay, Roger and Kathy (2017) note that in the year 2009, 1 in 4 adults in Australia were obese which is quite a staggering figure. Most recently, there have been increases in weight as recorded by many Australians. More often, the effects of obesity are demanding. As such these may include:

1. Weight related illnesses
2. Financial strain in order to contain the already gained weight

• Psychological effects such as lack of confidence by the victims due to the feeling of inferiority, etcetera 

Background to the problem

The main aim of this study is to explore the effects obesity, the causes of obesity, the distribution of obesity in Australia as well as the rest of the world. Additionally, the paper aims at examining the growth rate of obesity over the past years and comment on the pattern

There are a number of factors put forward as causes of obesity

• Theory one: Inferior dietary routines

As noted earlier on, unobserved dietary consumption is one of the major factors that cause obesity. Some of the reasons for such dietary patterns may comprise: Most of the young Australia generation is addicted to the low cost street and unhealthy food, additionally busy schedules which deprive a majority of the individuals’ ample time to cook healthy meals and therefore resort to junk foods.

• Theory two: Genetics

A paper by Ulaval (2018) indicate that there are various types of obesity that concentrate in a family, as such, the chance of a person from a line of family with a history of obesity to be obese are relatively higher than that of a person from a non-obese history. Studies indicate that genes are susceptible to solely lead to obesity. Such disorders include the Bardet-Biedl and Prader-WIlli syndromes. Nevertheless, it is not always that genes may lead to health complications; in the case of obesity it is often a combination of both genes and behavior that cause genes to be included as a causal agent of obesity.

• Theory three: Socioeconomic factors

Researches done by Pampel et al. (2012) suggest that, “The higher the nation’s economic development, the higher the shift in the obesity rates…”

• Theory four: Level of physical activities

Pampel (2012) argues that “…activities such as reading, attending cultural events, and going to the movies…” are effectual in lowering the BMI (Body Mass Weight) just the same as exercise. Whereas, passive activities like watching television or movies had no effect on lowering the BMI.

To enable focus of the researcher on the specific objectives of the research, the following research questions are used:

1. What are the factors that are likely to cause overweight and obesity?
2. Does overweight indicate a path to obesity i.e. does overweight act as a preliminary stage to obesity or are they disjoint?

• Is there a difference in the Australian population strata of persons with instances of overweight and obesity?

Previous studies have expressed different views and projections of the situation of obesity and overweight in Australia. Sadly, there have not been enough social groups out to take the responsibility of ensuring reduction of the rates obesity despite exposure of the pending epidemic by both researchers and scholars. In a study by Moretto and Byrnes (2017) on the role of government on the fight against obesity in their paper about “Public Preferences for the Use of Taxation and Labeling Policy Measures to Combat Obesity in Young Children in Australia,” they debate that the government is interested on initiatives of launching taxation policy however from the recent survey it is noted that taxation policy has not make a great impact over street food addiction of young generation. Comans et al. (2017) argue that unless the young generation reconsider their take on unhealthy foods the issue of obesity is likely to stay for a while. The previous researches do not highlight the underlying events that may lead to addiction of junk foods but only concentrate on the ultimate addiction. Therefore, making leaps past the root causes of unhealthy food observances into conclusions of the effect of such unhealthy food observances, therefore creating a gap. 

Literature review

The secondary data for this project was obtained from the Australian health department database for the years 1995 to 2015. It is divided into various data-sets according to categories which include (Region- urban and rural, Age – young and old, Australian cities, Adults (1995-2015). Whereas, the primary data is obtained from sample surveys filled by members of different Australian strata groups.

In order to examine the research questions, two sets of hypotheses are formulated to help in the process of establishing the rate of obese and overweight in Australia and how it is related to various factors such as:

1. Age
2. Place of residence

• Rural areas / Urban areas

To explore the difference of obesity rates between different Australian cities, the hypotheses to determine the statistical difference are:

Null hypothesis

H₀: Factors such as overweight lead to obesity in both children and adults

Alternative

H₁: There is no relationship between factors such as overweight and obesity children and adults, i.e. obesity and overweight do not correlate children grow into obese adults.

To test the difference of obesity between urban and rural areas, the hypothesis includes:

Null hypothesis

H₀: There is more obesity in urban centers than in rural areas

Alternative

H₁: There is no statistical difference between the obesity rates of urban and rural areas

The data analysis tool for the study was the SPSS software, while the data collection of secondary sources was from the ministry of health databases through the internet. 

Obesity rates in different countries
Country	Overweight but not obese (%)	Obese (%)	Overweight or obese (%)
Australia	Mean	35.50	27.90	63.40
Grouped Median	35.50	27.90	63.40
Belgium	Mean	32.40	18.60	51.00
Grouped Median	32.40	18.60	51.00
Canada	Mean	34.50	25.80	60.30
Grouped Median	34.50	25.80	60.30
Chile	Mean	39.40	25.10	64.50
Grouped Median	39.40	25.10	64.50
Czech Republic	Mean	34.00	21.00	55.00
Grouped Median	34.00	21.00	55.00
Estonia	Mean	33.30	18.00	51.30
Grouped Median	33.30	18.00	51.30
Finland	Mean	40.20	24.80	65.00
Grouped Median	40.20	24.80	65.00
France	Mean	32.40	16.90	49.30
Grouped Median	32.40	16.90	49.30
Germany	Mean	36.40	23.60	60.00
Grouped Median	36.40	23.60	60.00
Hungary	Mean	32.30	30.00	62.30
Grouped Median	32.30	30.00	62.30
Ireland	Mean	38.00	23.00	61.00
Grouped Median	38.00	23.00	61.00
Israel	Mean	39.30	22.90	62.20
Grouped Median	39.30	22.90	62.20
Japan	Mean	20.10	3.70	23.80
Grouped Median	20.10	3.70	23.80
Korea	Mean	28.10	5.30	33.40
Grouped Median	28.10	5.30	33.40
Latvia	Mean	31.40	23.20	54.60
Grouped Median	31.40	23.20	54.60
Luxembourg	Mean	35.50	22.60	58.10
Grouped Median	35.50	22.60	58.10
Mexico	Mean	39.20	33.30	72.50
Grouped Median	39.20	33.30	72.50
New Zealand	Mean	35.20	31.60	66.80
Grouped Median	35.20	31.60	66.80
OECD average	Mean	34.20	22.80	57.00
Grouped Median	34.20	22.80	57.00
Slovak Republic	Mean	34.60	16.90	51.50
Grouped Median	34.60	16.90	51.50
Turkey	Mean	33.10	22.30	55.40
Grouped Median	33.10	22.30	55.40
United Kingdom	Mean	36.00	26.90	62.90
Grouped Median	36.00	26.90	62.90
United States	Mean	31.90	38.20	70.10
Grouped Median	31.90	38.20	70.10
Total	Mean	34.22	22.80	57.02
Grouped Median	34.50	23.00	60.00

Figure 6: Area map for distribution of obesity in developed countries

Figure 7: Children Statistics of obesity and overweight

	N	Minimum	Maximum	Mean	Std. Deviation
Overweight but not obese- boys (%)	7	14.2	29.4	20.800	5.0030
Obese- boys	7	4.8	8.2	6.729	1.1772
Overweight but not obese-girls (%)	7	8.7	21.4	16.400	4.1396
Obese	7	5.5	11.5	8.629	1.7566
Overweight but not obese-All children (%)	7	11.3	24.7	18.771	4.4984
Obese	7	6.0	10.0	7.771	1.2880
Valid N (listwise)	7

Spread of obesity according to age group
				Overweight but not obese- boys (%)	Obese- boys	Overweight but not obese-girls (%)	Obese	Overweight but not obese-All children (%)	Obese
Age group	12–15	1	23.3	4.8	18.8	9.0	21.2	6.9
Total	Mean	23.300	4.800	18.800	9.000	21.200	6.900
16–17	1	29.4	8.2	17.7	8.7	24.7	7.9
Total	Mean	29.400	8.200	17.700	8.700	24.700	7.900
2–4	1	14.2	6.7	8.7	9.0	11.3	8.7
Total	Mean	14.200	6.700	8.700	9.000	11.300	8.700
5–7	1	15.8	8.1	13.6	11.5	14.6	10.0
Total	Mean	15.800	8.100	13.600	11.500	14.600	10.000
8–11	1	20.6	6.0	21.4	5.5	21.0	6.0
Total	Mean	20.600	6.000	21.400	5.500	21.000	6.000
Total aged 2–17 years	1	20.4	6.7	16.4	8.5	18.4	7.5
Total	Mean	20.400	6.700	16.400	8.500	18.400	7.500
Total aged 5–17 years	1	21.9	6.6	18.2	8.2	20.2	7.4
Total	Mean	21.900	6.600	18.200	8.200	20.200	7.400
Total		Mean	20.800	6.729	16.400	8.629	18.771	7.771

Figure 10: Statistics of persons older than 18 years

Obesity statistics of persons above the age of 18
			Overweight but not obese-Men	Obese-men	Overweight but not obese-Women	Obese-Women	Overweight but not obese-Persons	Obese-Persons
Age group	18–24	1	26.9	17.3	17	17.3	22	17.1
25–34	1	41.9	20.8	25.1	17.3	33.4	19
35–44	1	47.5	26.7	27.6	30.7	37.4	28.6
45–54	1	46.7	33.2	28.6	33	37.6	33
55–64	1	44.5	36.8	33.3	34.9	38.8	35.9
65–74	1	42.20	38.20	36.10	32.70	38.90	35.40
75–84	1	44	32.40	41.40	27.10	43.40	29.60
85 years and over	1	47.3	11.20	35	21.50	38.80	17.80
Total 18 years and over	1	42.4	28.4	28.8	27.4	35.5	27.9

Figure 11: Socioeconomic statistics on obesity and overweight in Australia

Statistics of obesity according to remoteness and social classes
				Persons	Women	Men
Remoteness area	Group 1 (lowest socioeconomic group)	1	67	61	72
Total	Mean	66.50	61.20	72.00
Group 2	1	65	58	73
Total	Mean	65.30	57.80	73.20
Group 3	1	65	59	71
Total	Mean	64.70	59.00	70.70
Group 4	1	63	56	69
Total	Mean	62.60	55.50	69.40
Group 5 (highest socioeconomic group)	1	58	48	69
Total	Mean	58.00	47.70	68.60
Inner regional	1	69	63	75
Total	Mean	69.20	63.30	75.40
Major cities	1	61	53	69
Total	Mean	61.10	53.30	69.10
Outer regional/Remote	1	69	64	74
Total	Mean	69.10	64.30	74.30
Total		Mean	64.56	57.76	71.59

Correlations
			Age group	Overweight but not obese-Men	Obese-men	Overweight but not obese-Women	Obese-Women	Overweight but not obese-Persons	Obese Persons
Spearman’s rho	Age group	Correlation Coefficient	.	.	.	.	.	.	.
Sig. (2-tailed)	.	.	.	.	.	.	.
N	0	0	0	0	0	0	0
Overweight but not obese-Men	Correlation Coefficient	.	1.000	.017	.267	.477	.385	.267
Sig. (2-tailed)	.	.	.966	.488	.194	.306	.488
N	0	9	9	9	9	9	9
Obese-men	Correlation Coefficient	.	.017	1.000	.483	.828**	.561	.950**
Sig. (2-tailed)	.	.966	.	.187	.006	.116	.000
N	0	9	9	9	9	9	9
Overweight but not obese-Women	Correlation Coefficient	.	.267	.483	1.000	.360	.946**	.517
Sig. (2-tailed)	.	.488	.187	.	.342	.000	.154
N	0	9	9	9	9	9	9
Obese-Women	Correlation Coefficient	.	.477	.828**	.360	1.000	.479	.904**
Sig. (2-tailed)	.	.194	.006	.342	.	.192	.001
N	0	9	9	9	9	9	9
Overweight but not obese-Persons	Correlation Coefficient	.	.385	.561	.946**	.479	1.000	.644
Sig. (2-tailed)	.	.306	.116	.000	.192	.	.061
N	0	9	9	9	9	9	9
Obese Persons	Correlation Coefficient	.	.267	.950**	.517	.904**	.644	1.000
Sig. (2-tailed)	.	.488	.000	.154	.001	.061	.
N	0	9	9	9	9	9	9
**. Correlation is significant at the 0.01 level (2-tailed).

Paired Samples Test
		Paired Differences	t	df	Sig. (2-tailed)
		Mean	Std. Deviation	Std. Error Mean	95% Confidence Interval of the Difference
		Lower	Upper
Pair 1	Obese – Overweight but not obese- boys (%)	-12.1714	5.7564	2.1757	-17.4952	-6.8477	-5.594	6	.001

Figure 14: Statistics to test hypothesis (two)

One-Sample Test
	Test Value = 0
		95% Confidence Interval of the Difference
	t	df	Sig. (2-tailed)	Mean Difference	Lower	Upper
ObesePersons	10.951	8	.000	27.144	21.43	32.86
Overweight but not obese-Persons	18.163	8	.000	36.200	31.60	40.80

Discussion and Analysis

As shown from figure 4 above, the Australian population has an average rate of 35.50 rates of people who are overweight but not yet obese and an average of 27.90 obese people which is one of the highest in developed countries. Finland, Chile and Israel have the highest number of people who are overweight but not obese at an average of 40.20, 39.40, and 39.30 respectively. However, Finland has a 24.0% rate of people with obesity. Such high statistics indicate that Obesity is not a single country’s problem but a global issue. For instance, USA has the highest obesity rate of approximately 38.20%. On average the percentage of boys who are overweight but not obese of the age between 2 and 17 is 20.8%, while the obesity rate among boys is 8.2%. Moreover, overweight girls’ average at 16.4% and the percentage of obesity among young girls is 8.629. The overall percentage of overweight instances among children is 18.771 while obesity is 7.771. From the statistics there are more overweight boys than girls, however, there are more obese girls than boys, and therefore the statistics indicate that girls make a larger proportion of obese children.

Research Questions

Figure 6 indicate that boys between the ages of 16-17 have the highest rates of obesity of 8.2% compared to those between the ages of 12-15 who average at 4.8%. The highest percentage of obese girls is those of the age of 5-7 at 11.5%. Overall, children between the ages of 5-7 have the highest rate of obesity at 10.0%

Notably, from figure 9, persons from the lowest socioeconomic group have the highest percentage of obesity (66.50%) followed by the second lowest, all the way to the highest class who have the lowest level of obesity at 58.0%. Additionally, people from the inner regions have an obesity percentage of 69.20%, while those from urban regions have an obesity rate of 61.0% and those from outer (rural regions) have an obesity percentage of 69.10%.

In testing whether factors such as overweight does lead to obesity among children the null hypothesis of whether there exists statistical evidence to conclude that overweight instances in children lead to obesity at a significance level of 5% is used. The p-value is 0.001 which is less than 0.005. We fail to reject the null hypothesis and conclude that if a child is overweight, there are chances that they may eventually be obese. Moreover, the rate of obesity between urban and rural areas (inner regions) as well as outer regions is statistically different following a difference in distribution of obesity percentage between urban regions, rural areas and outer regions. We therefore reject the second null hypothesis that there is no sufficient statistical evidence that the rate of obesity between urban and rural areas is the same and conclude that there is difference in the rates of obesity between different regions as well as socioeconomic strata.

The study contributes to the wide literature on the effects of weight issues on health, thereby aiding raise awareness on the extent to which unmonitored weight can affect the health of individuals. In addition, the study helps outline the various factors that are causal agents of overweight and/ or obesity. As such, it sensitizes on the very factors that individuals ought to avoid or concentrate on in order to ensure their BMI is on the right scale, in aim of avoiding weight related illnesses. Lastly, the study explores the health issues such as hypertension resulting from obesity or overweight.

The study is limited by the chosen sampling method, whereby, the sample chosen may not be representative of the whole Australian population. Additionally, the secondary data obtained is not fully verified and therefore there might be inherited errors which may tamper with the integrity of the output of the results.

Conceptual Framework

For future research purposes, there should be a consideration on studies on natural remedies to weight related concerns. For instance, are there natural means of dissociating gene caused obesity, and if there is. The emphasis to undertake public sensitization on such means of weight control should be undertaken by the government.

Conclusion

In conclusion, following the study on the causes, effects and distribution of overweight and obesity in Australia it can be noted that there are various factors affect the rate of obesity among different persons, such factors include:

1. Lifestyle
2. Economic status/class

• Overweight

1. Regions

Some factors such as region may not be directly correlated with obesity but do affect other factors such as lifestyle. From the analysis, persons from interior regions exhibit the highest rates of obesity as well as those from lower economic classes. Therefore, it can be concluded that, economic ability influence to a large extent factors such as health observations and fitness exercises among Australian households, i.e. the higher the economic status, the higher the ability to check on health matters. Other factors such as weight are directly correlated with obesity such that overweight persons are more prone to being obese compared to underweight persons. In conclusion, there are a wide range of factors which eventually influence overweight cases which may include unhealthy lifestyles in a number of developed countries.

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