A CORPORATE INTERVENTION ON THE HEALTH OF EMPLOYEES
COUNTING STEPS FOR HEALTH
Dinai Monique B.Sc.
7/21/2014
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Abstract Introduction
Beside occupational health issues, personal health is also important for Alcoa, like overweight of employees, smoking, and healthy lifestyle. Alcoa has introduced a program to promote and enhance fitness and wellness of employees. This program is called GCC (Global Corporate Challenge). The objective of the program is to keep track of the daily activities of people in number of steps made each day for a period of 16 weeks. With defined targets and challenges throughout the program motivation is improved of the participating employees. At the beginning and end of this challenge some demographic information of the employees were gathered by medical personnel. The information gathered is weight, length and smoking status. The
information gathering was done with a list of employees from HR, which also contains the date of birth, the assigned department and sex.
The aims of this thesis are:
- Analyze the relationship between selected attributes of participants and non-
participants and their as measured pre-intervention (pre-GCC) and post intervention (post-GCC) BMI’s.
- Define the demographic predictors of people in the overweight category.
- Analyze if there is a relationship between participation in the GCC program and obesity.
Methods
Data gathering was done in such a way that the analyses required a cross sectional study design.
The data is sorted on participants and non-participants and demographic characteristics for analyses. Rates and proportions are calculated to get the results. Statistical analyses methods, like t-test, dependant t-test and linear regression, are also used.
Results
There was no significant difference in the BMI change of the GCC participants based on the data available. The participation in the GCC program was more motivated by the overweight and obese group than normal weight group. The variables smoking, age, type of job, ethnicity and sex did not have a significant effect on the BMI change of the participants.
The GCC program did not have a negative impact on the BMI change and should be implemented again, because it can help with promotion of an active and healthy lifestyle.
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Contents
Abstract ... 2
Background and Significance ... 4
Hypothesis ... 7
Preliminary studies ... 8
Literature review ... 9
Approach ... 16
Aims ... 17
Design and methods ... 17
Statistical tests ... 25
Innovation ... 26
Results ... 27
Discussion ... 29
Assumptions and limitations ... 32
Bibliography ... 33
Acknowledgments ... 35
4
Background and Significance
Alcoa, an American multinational company, decided to implement a program to improve the health of their employees throughout the world. The effort to improve employees Health and Safety, started since the beginning of Safety and Health guidelines and laws. Alcoa generally adopted the OSHA (Occupational Safety and Health association) guidelines and where needed decided to use more stringent rules for his subsidiaries. Whether the Alcoa’s subsidiary local regulations demanded the requirements with local laws or not. All subsidiaries are supposed to use Alcoa regulations/protocols if the local law is weaker or easier than the Alcoa protocols.
The wellbeing of employees is crucial for Alcoa. They have implemented several Safety and Health and Wellness systems to keep the employee safe and healthy. Safe in the way that every employee should leave the plant as they arrived on the plant, and healthy in the way that no occupational exposure should harm the health of the employee; wellness in the way that
employees are made aware, stimulated, motivated and are given tools for living and assessing a healthy lifestyle. The Health part is captured by preventive medical surveillance and personal exposure monitoring.
To capture a part of the Wellness establishment in 2013 Alcoa decided to take part in the Global Corporate Challenge (GCC) program which will be held annually. This program was promoted throughout all business units and subsidiaries. The GCC program has the goal to increase and track the physical activity of the participants. In this program the employees have to register as groups of seven to participate in this 100days challenge. Research has shown that the average person makes like 3000 steps a day. This challenge motivates to a daily count of at least 10.000 steps. Swimming and cycling are also possible and the distance is transferred into steps. After registration every participant gets a pedometer free of charge. With email interaction every participant was required to report daily the number of steps on their personal pedometer. Other personal information like weight, eating-drinking habits and health status were also required to assess the personal progress of the participant.
At Suralco L.L.C, one of the subsidiaries, which is located in Suriname, South America, the Medical department decided to take pre and post GCC biometric measurements of employees.
This was done not only in the plant clinic but also in the refinery, with the aim to cover 100%.
The measurement data consist of the name, date of birth, payroll number, length, weight and cigarette smoking status of the employee. This data is being used for this thesis.
This data is sufficient enough to calculate the Body Mass Index (BMI), which is used as an indirect indicator of the body fat and normal weight.
Overweight (BMI between 25 and 30) and obesity (BMI above 30) is a significant medical concern in the world. According the Center for disease control and Prevention (CDC) one third of America is suffering from obesity (Center for disease control and prevention, 2014).More than half of the 671 million obese people in the world live in 10 countries, and America tops the list. Within the world the top ten most obese countries are:
1. United States 2. China
3. India 4. Russia 5. Brazil 6. Mexico
5 7. Egypt
8. Germany 9. Pakistan
10. Indonesia (Health)
Obesity is correlated with the health risks of human beings. Obesity-related medical conditions include heart disease, stroke, type 2 diabetes and certain types of cancer, some of the leading causes of preventable death (Center for disease control and prevention, 2014).
Obesity can be a result of many factors. A lack of energy balance most often causes overweight and obesity. Energy balance means that your energy IN equals your energy OUT. Overweight and obesity happen over time when you take in more calories than you use. Causes are:
- An Inactive Lifestyle - Environment
Our environment doesn't support healthy lifestyle habits; in fact, it encourages obesity. Some reasons include:
o Lack of neighborhood sidewalks and safe places for recreation.
o Work schedules.
o Oversized food portions.
o Lack of access to healthy foods.
o Food advertising.
- Genes and Family History
- Health Conditions
- Medicines
- Emotional Factors
- Smoking
- Age
- Pregnancy
- Lack of Sleep (National institutes of health, 2012) Burden on the medical cost
Excess weight harms health in many ways. It increases the risk of developing conditions such as diabetes, heart disease, osteoarthritis, and some cancers, to name just a few, and reduces the life span. Treating obesity and obesity-related conditions costs billions of dollars a year. By one estimate, the U.S. spent $190 billion on obesity-related health care expenses in 2005—double previous estimates. The enormity of this economic burden and the huge toll that excess weight takes on health and well-being are beginning to raise global political awareness that individuals, communities, states, nations, and international organizations must do more to stem the rising tide of obesity. (Harvard school of public Health, 2014)
Obesity and physical activity
Physical activity may be defined as movement of the body by the contraction and relaxation of skeletal muscles resulting in increased energy expenditure above the resting level.
Health-related physical activity is defined as participation in moderate-intensity physical activity for at least 30 minutes (may be accumulated in 3x10 minute sessions) on most days of the week, OR can also be defined as energy expenditure greater than 800kcal* per week.
6 People who are moderately or vigorously active have been found to be significantly less likely to suffer premature all-cause mortality; cardiovascular diseases such as coronary heart disease, stroke, and high blood pressure; colon cancer; non-insulin dependent diabetes mellitus; and osteoarthritis. Although it is commonly believed that low levels of physical activity and low total energy expenditure are responsible for weight gain, there are few data available that provide conclusive evidence of this. Nevertheless, physical activity has been shown to play an important role in weight control by promoting fat loss while retaining or increasing lean mass (Jo Salmon, 2000). Obese persons are less likely to participate in physical activities.
Work related effects of obesity
Obesity is not an occupational disease, but its global epidemic poses significant current
challenges to occupational health professionals. Moreover, the ‘global tsunami’ of obesity will almost certainly demand increasing commitments from occupational health programs in coming years. Four related issues deserve attention. First, obesity exacts an enormous societal cost in terms of reduced well-being and human lives lost. Second, huge financial costs result from the care and treatment of those with obesity-related diseases. Third, obesity adversely affects workplace costs by decreasing worker productivity and increasing the need for support services and disability management. Fourth, the work environment might contribute to increased
overweight and obesity, but it may also provide opportunities for addressing the problem of absenteeism and presenteeism (Borak, 2011)
The ILO, International Labor Organization, is providing some general guidelines for the improvement of food provided or available for employees in order to have good nourishment, which in turn will have a positive effect on the performance and satisfaction of the employees regarding their work and employer. (Wanjek, 2005)
A good health is important for the employer, that is why pre-employment screening is performed on a person selected to be hired. If criteria are not met then the selected person may not be hired.
Periodic screening of employees is provided in order to identify preventable diseases in a timely matter.
The Alcoa corporate intervention is a welcome intervention for the employees as it shows that the employer cares about the health of the employees. The before and after data related to the BMI of a group of employees, is used to do the statistical tests and analyses in order to proof the hypothesis. The aim of this corporate intervention is to make employees aware of a healthy lifestyle and one pillar of the program stresses the importance of daily exercise.
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Hypothesis
The hypothesis of this thesis is that participants in the Suralco GCC program will have improved BMI scores.
The aims to get the answer on the hypothesis are:
- Analyze the relationship between selected attributes of participants and non-
participants and their as measured pre-intervention (pre-GCC) and post intervention (post-GCC) BMI’s.
- Define the demographic predictors of people in the overweight category. This information can be used for promotion and education in order to reduce or prevent obesity.
- Analyze if there is a relationship between participation in the GCC program and obesity.
8
Preliminary studies
There are many preliminary studies performed on overweight and obese people. All studies agree on the negative effects of obesity on the health and the burden that this creates on the medical care.
In Suriname the following obesity related studies were done:
- The NCD STEPS investigation; Langa wan anu gi wan gosuntu Sranang, done by Ministry of Health 2014.
This report does indicate that in the Surinamese population overweight and obesity is something to be concerned of. In the group of men 47% was overweight or obese. In de group of woman 63% was overweight or obese.
9
Literature review
Introduction of Suralco L.L.C.
The Aluminum Company of America, Alcoa in short, is one of the world's largest producers of aluminum and also the parent of the Suriname Aluminum Company LLC. As a direct result of the discovery of Charles Martin Hall, to manufacture electroplated aluminum, this company as the Pittsburgh Reduction Company was founded in 1888 in Pittsburgh. This company is now known as Alcoa Inc.
The production of alumina and chemicals are the main activities. Alcoa also participates in investment and development projects, which are closely related to its core activities. In addition to raw aluminum, Alcoa manufactures a wide range of finished products such as foil, sheet, wire, pipes, castings, electrical conductors and accessories, clamps, building materials and household items.
Important applications for its products are found in the construction of buildings, all kinds of transportation, aerospace, electrical and packaging industries.
Some salient points about Alcoa :
Alcoa serves the aerospace , automotive, packaging, building and construction , commercial transportation and industrial markets , by offering design , engineering, production and other capabilities of Alcoa's businesses to customers .
In addition to aluminum products and components, which include: flat-rolled products, hard alloy extrusions, and forgings, Alcoa also markets Alcoa ® wheels, fastening systems, precision and investment castings, and building systems.
In 2008 it was 10 times safer to work for Alcoa than in 1991.
Alcoa makes a very sustainable product: over 70 % of the aluminum ever produced is still in use, which is equivalent to 586 million tons of total production in 1886 (806 million tons).
Vision
Alcoa. Advancing each generation Mission Statement
Continue to operate to the mutual benefit of Suralco and Suriname.
Add value in meeting or exceeding the needs of our customers by managing our facilities, our labor/employee relations and relationships with the government in a proficient manner, to deliver alumina and power at the lowest attainable cost, consistent with economic conditions.
Suralco is a subsidiary of the Aluminum Company of America (Alcoa ) and Western Mining Corporation Holdings Limited ( WMC ) .
Founded in Suriname in 1916 as the Suriname Bauxite Maatschappij NV, she kept until 1958 engaged in the mines, processing and export of natural resources bauxite. In that year the
company and Suriname went in to a joint venture, called the Brokopondo Agreement, to develop the hydropower resource in the Suriname River and to the creation of a fully integrated
aluminum industry in this country. The company was then converted to the Suriname Aluminum Company ( Suralco ), located in the State of Delaware in the United States of America , as a Western Hemisphere Trade Corporation .
The construction of commercial facilities, as contained in the Brokopondo agreement,
immediately began in 1958. When the alumina plant and aluminum smelter were put into service
10 in 1965, there were more than SF. 300 million invested. The success of this integrated aluminum company, the first in South America, has considerable and ever-increasing extent, contributed to the prosperity of Suriname.
Aluminum production was abandoned in March 1999.
Furthermore Suralco has a huge impact on the economy of the country through massive purchases of goods and services in the local market, contributions to charity and assistance to cultural activities. Policies and programs of the company are focused on the promotion of trade and industry in the country, as well as improving the living conditions of Suralco workers and their families. (Kroes, 2013)
Suralco is located in Paranam in the district Para. Paranam is on approximately 45 km distance from Paramaribo, the capital of Suriname.
Obesity and overweight
As previously mentioned is obesity a worldwide problem. The World Health Organization also recognizes this problem.
At the other end of the malnutrition scale, obesity is one of today’s most blatantly visible – yet most neglected – public health problems. Paradoxically coexisting with under nutrition, an escalating global epidemic of overweight and obesity – “globesity” – is taking over many parts of the world. If immediate action is not taken, millions will suffer from an array of serious health disorders.
Obesity is a complex condition, one with serious social and psychological dimensions, that affects virtually all age and socioeconomic groups and threatens to overwhelm both developed and developing countries. In 1995, there were an estimated 200 million obese adults worldwide and another 18 million under-five children classified as overweight. As of 2000, the number of obese adults has increased to over 300 million. Contrary to conventional wisdom, the obesity epidemic is not restricted to industrialized societies; in developing countries, it is estimated that over 115 million people suffer from obesity-related problems.
Generally, although men may have higher rates of overweight, women have higher rates of obesity.
For both, obesity poses a major risk for serious diet-related non-communicable diseases, including diabetes mellitus, cardiovascular disease, hypertension and stroke, and certain forms of cancer. Its health consequences range from increased risk of premature death to serious chronic conditions that reduce the overall quality of life. (World Health organization, 2014)
Diet and body weight are related to health status. Good nutrition is important to the growth and development of children. A healthy diet also helps people reduce their risks for many health conditions, including: Overweight and obesity, Malnutrition, Iron-deficiency anemia, Heart disease, High blood pressure, Dyslipidemia (poor lipid profiles), Type 2 diabetes, Osteoporosis, Oral disease, Constipation, Diverticular disease, Some cancers. (Heathy People 2020, 2014) Ten facts about obesity from WHO (World health organization 2014, 2014)
1. Overweight and obesity are defined as "abnormal or excessive fat accumulation that may impair health"
Body mass index (BMI) – the weight in kilograms divided by the square of the height in meters (kg/m2) – is a commonly used index to classify overweight and obesity in adults. WHO defines overweight as a BMI equal to or more than 25, and obesity as a BMI equal to or more than 30.
11 2. More than 1.4 billion adults were overweight in 2008, and more than half a billion
obese
In 2008, more than 1.4 billion adults were overweight and more than half a billion were obese.
At least 2.8 million people each year die as a result of being overweight or obese. The prevalence of obesity has nearly doubled between 1980 and 2008. Once associated with high-income
countries, obesity is now also prevalent in low- and middle-income countries.
3. Globally, over 40 million preschool children were overweight in 2008
Childhood obesity is one of the most serious public health challenges of the 21st century.
Overweight children are likely to become obese adults. They are more likely than non-
overweight children to develop diabetes and cardiovascular diseases at a younger age, which in turn are associated with a higher chance of premature death and disability.
4. Overweight and obesity are linked to more deaths worldwide than underweight 65% of the world's population lives in a country where overweight and obesity kills more people than underweight. This includes all high-income and middle-income countries. Globally, 44% of diabetes, 23% of ischaemic heart disease and 7–41% of certain cancers are attributable to
overweight and obesity.
5. For an individual, obesity is usually the result of an imbalance between calories consumed and calories expended
An increased consumption of highly calorific foods, without an equal increase in physical activity, leads to an unhealthy increase in weight. Decreased levels of physical activity will also result in an energy imbalance and lead to weight gain
6. Supportive environments and communities are fundamental in shaping people’s choices and preventing obesity
Individual responsibility can only have its full effect where people have access to a healthy lifestyle, and are supported to make healthy choices. WHO mobilizes the range of stakeholders who have vital roles to play in shaping healthy environments and making healthier diet options affordable and easily accessible.
7. Children's choices, diet and physical activity habits are influenced by their surrounding environment
Social and economic development as well as policies in the areas of agriculture, transport, urban planning, environment, education, food processing, distribution and marketing influence
children's dietary habits and preferences as well as their physical activity patterns. Increasingly, these influences are promoting unhealthy weight gain leading to a steady rise in the prevalence of childhood obesity.
8. Eating a healthy diet can help prevent obesity People can:
1) maintain a healthy weight
2) limit total fat intake and shift fat consumption away from saturated fats to unsaturated fats 3) increase consumption of fruit, vegetables, pulses, whole grains and nuts
4) limit the intake of sugar and salt.
9. Regular physical activity helps maintain a healthy body
People should engage in adequate levels of physical activity throughout their lives. At least 30 minutes of regular, moderate-intensity physical activity on most days reduces the risk of cardiovascular disease, diabetes, colon cancer and breast cancer. Muscle strengthening and balance training can reduce falls and improve mobility among older adults. More activity may be required for weight control.
12 10. Curbing the global obesity epidemic requires a population-based multi-sectorial,
multi-disciplinary, and culturally relevant approach
WHO's Action Plan for the Global Strategy for the Prevention and Control of Non- communicable Diseases provides a roadmap to establish and strengthen initiatives for the surveillance, prevention and management of non-communicable diseases, including obesity.
Based on these facts it is certain that some kind of initiative is required to fight the obesity problem. As already mentioned above in fact 9 is physical activity one of the solutions. We will have a closer look into the causes of obesity.
An Inactive Lifestyle
Physical Activity (PA) has a powerful impact on metabolic and cardiovascular health, Physical inactivity has been identified as the biggest public health problem of the 21st century. This is ironic, since as little as 50 years ago, nearly half of all private industry jobs required at least moderate-intensity labor and only 20% of families owned more than one vehicle. Contrast this to 2010, where fewer than 20% of all jobs required workers to expend at least a moderate-intensity effort and nearly 60% of households owned two or more cars. Labor-saving technologies have been attributed to declines in the energy expended during work but that is only part of the issue.
Some other causes of this sedentary transition include higher levels of employment in jobs that require sitting all day, low neighborhood walkability and longer television viewing, and spending more time commuting in an automobile. (Der Ananian C, 2013). The proportion of inactive adults is higher in women than in men and increases with advancing age. While race, ethnicity, and income or educational attainment are not considered in many countries when assessing the demographics of PA behaviors, health disparities dictates examination of PA levels by race and ethnicity and educational attainment. (Der Ananian C, 2013). Increasing population level PA will require a systemic, multi-sectorial approach. It is well known that individual efforts to initiate behavior change have limited success and the likelihood of long-term maintenance is even lower.
Public health efforts targeting PA need to make the choice to be physically active easy while simultaneously making it difficult to lead a sedentary lifestyle. They also need to focus attention on collective responsibilities for helping people make and sustain behavior changes (Der
Ananian C, 2013). Programs improving social support in community enhance one’s social support network for physical activity. Examples of strategies commonly used in social support settings include establishing exercise buddies, exercise contracts with an exercise leader or walking clubs. Often times, social support is used in conjunction with individually adapted behavioral strategies to enhance effectiveness. (Der Ananian C, 2013)
Environment
Our environment doesn't support healthy lifestyle habits; in fact, it encourages obesity. Some reasons include:
o Lack of neighborhood sidewalks and safe places for recreation.
This creates a burden to go to the gym or park where some physical activity could have been performed to burn the extra calories used. In our social environment it is difficult to create space in our busy schedule to do exercise.
That’s why a combination of daily activities with moderate level of exercise is very popular, and does not require making extra time for exercise.
13 o Work schedules.
Seasons and work schedules can have influence on the exercise frequency. In rainy or cold seasons there may be no encouragement to leave the house for exercise. Work schedule also play their part in being motivated to exercise.
Depending on the type of person, a late start of work may be used to do exercise before going to work. On the other side when leaving work early there may be time left to do exercise after work. Some persons work in continuous schedule type of work, which means that there is no fix time of work, but changes after some time from the day shift, to the afternoon shift, to the night shift. This also requires good planning of food at work and may be used as an excuse to eat junk food frequently.
o Oversized food portions.
This is a personal choice and may become a habit, especially when delicious food is involved. If no habit of physical activity is exercised then this can lead to obesity.
o Lack of access to healthy foods.
Poor people don’t always have access to variety of foods. They have to choose from what’s available. This may cause that the food consumed is one sided and consist for a major part of something high in carbohydrates, like rice. This can cause malnutrition and obesity.
o Food advertising.
Advertises about food are very common on the television and can be very persuasive in letting people believe in the quality of the food. But most times it is about fatty and sweet foods, high in fat, salt and sugar.
o Social economic status (SES)
Several studies, have documented an inverse relationship between SES and obesity in previous years. In a recent review, Ball and colleagues examined 34 articles to test the hypothesis that persons from lower SES strata are at
increased risk of weight gain. Their hypothesis was supported for
predominantly non-African American samples, but not for African American samples. Reviewing relevant studies, they found little support for a
relationship between SES and weight gain among African Americans. In contrast, depending on the particular indicator for SES that was used (i.e., occupational status, education, and income), they found that lower SES was associated with an increased risk of weight gain in non-African American individuals. Specifically, the authors found an inverse association between occupational status and weight gain for men and women. When SES was assessed using education as the indicator, the relationship became less strong (particularly among men). Using income level as the particular indicator for SES, findings for associations between weight gain and SES were inconsistent for both men and women. Finally, the authors noted a differential rate of weight gain by SES and attributed that finding to an early onset of weight gain
14 in a person’s life, when parental SES may still be influential. (Myles S. Faith, 2006)
Genes and Family History
Whatever the environment, some people stay thin and some become obese. Research shows that obesity tends to run in families. Studies with twins and adopted children have shown that genes, rather than shared lifestyles, play a key role in this.
Obesity-related genes could affect how we metabolize food or store fat. They could also affect our behavior, making us inclined towards lifestyle choices that increase our risk of being obese:
• Some genes may control appetite, making us less able to sense when we are full.
• Some genes may make us more responsive to the taste, smell or sight of food.
• Some genes may affect our sense of taste, giving us preferences for high fat foods, or putting us off healthy foods.
• Some genes may make us less likely to engage in physical activity.
People with obesity-related genes are not destined to be obese. But they will have a higher risk of obesity. In the modern environment, they may need to work harder than others to maintain a healthy body weight by making long-term, sustained lifestyle changes. (cancer research UK, 2009)
Health Conditions
Some illnesses may lead to obesity or weight gain. These may include Cushing's disease, and polycystic ovary syndrome. Drugs such as steroids and some antidepressants may also cause weight gain. (Center of disease and control, 2012)
Medicines
Some medicines may change the metabolism of energy in the body. Due to several processes which may be disturbed, delayed or speeded up, the energy consumption by the body may slow down and may be stored as fat, leading to obesity. Drugs such as steroids and some
antidepressants may also cause weight gain. (Center of disease and control, 2012) Emotional Factors
The causes of obesity are rarely limited to genetic factors, prolonged overeating or a sedentary lifestyle. What we do and don't do often results from how we think and feel. For example, feelings of sadness, anxiety or stress often lead people to eat more than usual. Unless you act to address these emotions, however, these short-term coping strategies can lead to long-term problems.
Depression can both cause and result from stress, which, in turn, may cause you to change your eating and activity habits. Many people who have difficulty recovering from sudden or
emotionally draining events (e.g., loss of a close friend or family member, relationship difficulties, losing a job or facing a serious medical problem) unknowingly begin eating too much of the wrong foods or forgoing exercise. Before long, these become habits and difficult to change.
Binge eating, a behavior associated with both obesity and other conditions such as anorexia nervosa, is also a symptom of depression. A study of obese people with binge eating problems found that 51 percent also had a history of major depression. (Sara Weiss, 2014)
15 Smoking
Smoking's effect on body weight could lead to weight loss by increasing the metabolic rate, decreasing metabolic efficiency, or decreasing caloric absorption (reduction in appetite), all of which are associated with tobacco use. The metabolic effect of smoking could explain the lower body weight found in smokers. Given the metabolic effect of smoking, it is expected that the greater the number of cigarettes smoked, the lower the smoker's body weight. However, cross- sectional studies indicate that heavy smoking could be associated with a greater risk of obesity (9, 10, 14, 39, 40). In the Cancer Prevention Study I (40), whereas smokers had lower body weight than did never or former smokers, heavy smokers (≥2 packs cigarettes/d) were more likely to be overweight than were other smokers. (Arnaud Chiolero, 2008)
Age
The prevalence of obesity is strongly related to age. The 16-24 year age group – both males and females – is substantially less at risk of becoming obese than older age groups, and the incidence of obesity for males in this age range has declined very slightly in recent years. Those aged between 25 and 34 have the second lowest rates of obesity. Middle aged people and those of retirement age are the most 'at-risk' groups.
More young men and women in the 16-24 age groups have a 'desirable' BMI of between 20 and 25 than any other BMI category. Men of this age are twice as likely to be underweight as they are to be obese. (Rationis, 2014)
Pregnancy
Gaining more than the recommended weight during pregnancy can put women at increased risk of becoming obese and developing related health problems, including high blood pressure, later in life, according to new research. Correspondingly, women whose weight gain during
pregnancy was low were at lower risk of becoming overweight or obese and developing
associated health problems. High pregnancy weight gain can lead to long-term obesity. (Science Daily, 2014)[
Lack of Sleep
According Prevention.com the following reasons can lead to weight gain and systematically to obesity:
Sleep less, burn less Sleep less, eat more Sleep less crave more
Sleep less, hang on to fat more
Sleep less, have more time to eat (prevention.com, 2012) Popular solutions against obesity
Frequent exercise to burn the excess calories taken in by food and drinks will help partly.
According the campaign to end obesity much can be done to reverse the epidemic, yet important opportunities to tackle obesity at the national policy level -- including changes that enable more Americans to eat healthy and be active, as well as those that provide appropriate medical treatment for patients -- have gone largely unmet (Campaign to end obesity, 2014)
16
Approach
For this thesis, the available data was very crucial. The GCC is a web based program in which the daily progress was reported by the participant himself. Not all of the data was made public.
Only the names of the participant, the group name and daily step input was made public. During the period of 23 may till 11 Sept 2013 several moments of checks came up where the request from the GCC database was to report the weekly weight, or to participate in a health status poll or to participate in mini-challenges. This information was not made public.
At the start of GCC the Medical department started a campaign to measure the baseline BMI status of the employees. There was no selection made whom to measure or not. A total coverage of 37% of the total employee population was reached during the pre-GCC BMI measurements.
The process consisted of taking the height, the weight and smoking status of the person on a total workforce list. During this campaign the same measurement stick for the height and same scale for the weight was used for everyone. After the GCC was completed then the next campaign started to measure the Post-GCC BMI. During the post-GCC measurement a total of 63% was reached.
Looking at the data available the following variables were identified:
- GCC participant. Person voluntary participating in the GCC program. This group has pre- and post measurements to calculate the BMI
- GCC non-participant. Person not participating in the GCC program. This group may also have pre- and post measurements to calculate the BMI or measurement at the beginning or end of the period.
- BMI, BODY MASS INDEX, is calculated by taking the weight in kilograms and dividing it with the square of height in meters, BMI = Kg/m2. The interpretation of BMI is as follows:
(Vermont department of health)
Weight BMI
Under weight < 18.5
Healthy 18.5 – 24.9
Overweight 25 – 29.9
Obese category I 30 – 34.9 Obese category II 35 – 39.9 Obese category III ≥ 40 - Sex. Male or Female
- Smoking status. This information was simply gathered by asking the question: “Do you smoke?”. This means passive smokers are included in the criteria non-smoker. All others are classified as smokers.
- Overweight. Persons with a BMI of 25 and higher.
- Field worker. Persons performing work mostly on the floor or field, not in the office.
- Administrative worker. Person performing work mostly in the office
- Ethnicity. This variable was determined by the name of the person, personal contact and with help of a colleague who has 20 years experience as HR-employee and currently is functioning as health and safety superintendant. The categories identified are:
o Javanese, offspring of immigrants from Indonesia
17 o Hindustani(West Indians), offspring of immigrants from India
o Creole(Afro-Americans), offspring of immigrants and slaves from Africa o Native Indian(Amery Indians), offspring from native Indians
o Mix, offspring with parents not from the same ethnicity group
- # of steps. Numbers of steps inputted by the participant on a daily basis into the GCC database. This data is a download from the GCC database.
Aims
The aim of this thesis is to:
- Analyze the relationship between selected attributes of participants and non-
participants and their as measured pre-intervention (pre-GCC) and post intervention (post-GCC) BMI’s.
- Define the demographic predictors of people in the overweight category. This information can be used for promotion and education in order to reduce or prevent obesity.
- Analyze if there is a relationship between participation in the GCC program and obesity.
Design and methods
The following epidemiological methods are used to reach the aims:
- Cross sectional method.
In a cross-sectional study, data are collected on the whole study population at a single point in time to examine the relationship between disease (or other health related state) and other variables of interest. Cross-sectional studies therefore provide a snapshot of the frequency of a disease or other health related characteristics in a population at a given point in time. This methodology can be used to assess the burden of disease or health needs of a population, for example, and is therefore particularly useful in informing the planning and allocation of health resources.
Potential bias in cross-sectional studies
Non-response is a particular problem affecting cross-sectional studies and can result in bias of the measures of outcome. This is a particular problem when the
characteristics of non-responders differ from responders.
Analysis of cross-sectional studies
In a cross-sectional study all factors (exposure, outcome, and confounders) are
measured simultaneously. The main outcome measure obtained from a cross-sectional study is prevalence:
For continuous variables such as blood pressure or weight, values will fall along a continuum within a given range. Prevalence may therefore only be calculated when
18 the variable is divided into those values that fall below or above a particular pre- determined level. Alternatively mean or median levels may be calculated.
In analytical cross-sectional studies the odds ratio can be used to assess the strength of an association between a risk factor and health outcome of interest, provided that the current exposure accurately reflects the past exposure.
Strengths and weaknesses of cross-sectional studies Strengths
• Relatively quick and easy to conduct (no long periods of follow-up).
• Data on all variables is only collected once.
• Able to measure prevalence for all factors under investigation.
• Multiple outcomes and exposures can be studied.
• The prevalence of disease or other health related characteristics are important in public health for assessing the burden of disease in a specified population and in planning and allocating health resources.
• Good for descriptive analyses and for generating hypotheses.
Weaknesses
• Difficult to determine whether the outcome followed exposure in time or exposure resulted from the outcome.
• Not suitable for studying rare diseases or diseases with a short duration.
• As cross-sectional studies measure prevalent rather than incident cases, the data will always reflect determinants of survival as well as aetiology.
• Unable to measure incidence.
• Associations identified may be difficult to interpret.
• Susceptible to bias due to low response and misclassification due to recall bias.
Pre-GCC data
Out of the 785 employees a total of 287 employees participated in the pre-GCC BMI
measurement. From the 287 measured a total of 146 were GCC participants. The distribution of the BMI of the GCC participants is shown in table1.
Table 1: Distribution of the BMI of the total population according the pre-GCC measurement BMI All measured GCC participants Proportion
< 18.5 5 3 60%
18.5 – 24.9 84 50 60%
25 – 29.9 123 80 65%
30 – 34.9 52 31 60%
35 – 39.9 16 9 56%
≥ 40 7 5 71%
Total 287 146
19 Post GCC data
Out of the 785 a total of 494 employees participated in the post-GCC BMI measurement. From the measured a total of 299 were GCC participants. The distribution of the BMI of the GCC participants is shown in table 2.
Table 2: Distribution of the BMI of the total population according the post-GCC measurement BMI All measured GCC participants Proportion
< 18.5 3 1 30%
18.5 – 24.9 133 85 64%
25 – 29.9 223 143 64%
30 – 34.9 92 48 52%
35 – 39.9 28 14 50%
≥ 40 15 8 53%
Total 494 299
Table 3: Number and proportions of overweight persons in the age groups according pre- and post GCC measurements based on total population
Age groups
Total Pre-GCC
overweight Proportion
Post-GCC
overweight Proportion
20-29 36 3 8.33% 5 13.89%
30-39 163 45 27.60% 70 42.95%
40-49 398 96 24.12% 206 51.76%
50-60 196 54 27.55% 77 39.29%
Table 4: Number and proportions of overweight persons in the ethnicity groups according the pre-and post GCC measurements based on total population
Ethnicity Total
Pre-GCC
overweight Proportion
Post-GCC
overweight Proportion
hindustani 171 44 25.73% 69 40.35%
javanese 320 80 25% 153 47.81%
creole 213 53 24.88% 106 49.77%
mix 58 17 29.31% 20 34.48%
chinese 3 1 33.33% 1 33.33%
native indian 11 3 27.27% 8 72.72%
Table 5: Number and proportions of smoking and non-smoking persons according the pre-and post GCC measurements based on total interviewed.
Smoking Total measured Pre-GCC Proportion Total measured Post-GCC Proportion
yes 62 41 66.13% 123 74 60.16%
no 225 108 48.00% 462 284 61.47%
20 Table 6: Number and proportions of overweight persons divided in the field-and office worker groups according the pre-and post GCC measurements based on total population.
Type of work Total
Pre-GCC
overweight Proportion
Post-GCC
overweight Proportion
Field worker 395 85 21.52 196 49.62
Office worker 338 94 27.81 162 47.93
Table 7: Number and proportions of overweight persons divided in the Male and Female groups according the pre-and post GCC measurements based on total population.
Sex Total Pre-GCC
overweight Proportion Post-GCC
overweight Proportion
Male 700 159 23.71 316 45.14
Female 85 36 37.64 42 49.41
The epidemiological study design used is the cross sectional design, because the data is gathered on a certain point of time. If the total population is used to fill in the blocks of the design of a cross sectional study, then the following is obtained:
To fill in this design the following has to be identified:
Defined population: this is the total employee list of Suralco at the start of GCC Exposure: participation in GCC
Disease: BMI higher then 25 (Overweight and obese) Not exposed: employees not participating in GCC No disease: BMI less than 25
The numbers in the design are numbers out of the database after the GCC program was
completed. This because of the fact that after the GCC program was completed the exposure was completed also. The before information would not fit in this design. With the information of the design the prevalence of the disease and the exposure can be calculated by using the 2 x 2 table.
Defined population = Suralco employee population
785
Gather data on exposure and disease
Exposed: have disease GCC participant; overweight
213
Exposed: do not have disease GCC participant; normal BMI
86
Not exposed: have disease No GCC participant; overweight
145
Not exposed: do not have disease
No GCC participant; normal BMI
50
21 Table 8: 2x2 table to calculate prevalence of the disease (overweight) in the total population,
based on pre-and post GCC data
Disease No disease
Exposed 213 (a) 86 (b)
Not exposed 145 (c) 50 (d)
Prevalence of the disease with exposure: (a/ (a + b)) = (213/ (213+86)) = 0.71 Prevalence of disease without exposure: (c/ (c + d)) = (145/ (145 +50)) = 0.74 Prevalence of exposure with the disease: (a/ (a + c)) = (213/ (213+145)) = 0.60 Prevalence of exposure without disease: (b/ (b + d)) = (86/ (86 + 50)) = 0.63 Explanation of the prevalence’s will be done in de result section.
To compare the participants and the non-participants the following tables was prepared. The demographics and other variables are included just to have an overview between the two groups.
To fill in the data in the table the pre- GCC measurement information was used. This information can provide some relations between the reason for participation and also an indication which group was more eager or willing to participate.
Table 9: Demographics characteristics of participants in the GCC program according the pre- GCC measurement
Variables GCC participant
BMI < 25 ≥ 25 unknown
number 45 101 153
Smoking Yes No unknown
number 27 119 153
Sex Male Female unknown
number 249 50 0
Type of work Office Field unknown
number 230 197 0
Ethnicity H J Ch Cr M NI Cau unknown
number 71 123 2 72 26 4 1 0
Age 20-29 30-39 40-49 50-60 unknown
number 34 116 229 47 9
H: Hindustani, J: Javanese, Ch: Chinese, Cr: Creole, M: Mix, NI: native Indian, Cau: Caucasian
The following table gives an overview of the GCC non-participants according the pre-GCC data sorted for the demographic characteristics and other variables.
22 Table 10: Demographics characteristics of non-participants in the GCC program according the pre-GCC measurement
Variables GCC non-participant
BMI < 25 ≥ 25 unknown
number 24 7 124
Smoking Yes No unknown
number 15 56 124
Sex Male Female unknown
number 181 14 0
Type of work Office Field unknown
number 108 198 42
Ethnicity H J Ch Cr M NI Cau unknown
number 67 146 0 104 24 7 0 0
Age 20-29 30-39 40-49 50-60 unknown
number 13 59 161 52 42
H: Hindustani, J: Javanese, Ch: Chinese, Cr: Creole, M: Mix, NI: native Indian, Cau: Caucasian The numbers of participants and non-participants sorted by ethnicity for the 4 major ethnic groups are as presented by the following table. To calculate the participation rate by ethnicity also the following table was used:
Table 11: overview of participants and non-participants divided by ethnicity based on the pre- GCC data
Ethnicity Participant Non- participant
Total
Hindustani 71 (a) 67 (b) 138
Javanese 123 © 146 (d) 269
Creole 72 (e) 104 (f) 176
Mix 26 (g) 24 (h) 50
Total 292(i) 341(j)
Participation rate of Hindustani: (a/ (a + b)) = (71/ (71+67)) = 0.51x 100% = 51%
Participation rate of Javanese: (c/ (c + d)) = (123/ (123 +146)) = 0.46 x 100% = 46%
Participation rate of Creole p: (e/ (e + f)) = (72/ (72+104)) = 0.41x 100% = 41 % Participation rate of Mix: (g/ (g + h)) = (26/ (26 +24)) = 0.52 x 100% = 52%
The proportion of Hindustani participants: (a/i) x 100% = 24,32%
The proportion of Javanese participants: (c/i) x 100% = 64,06%
The proportion of Creole participants: (e/i) x 100% = 24,66%
The proportion of Mix participants: (26/i) x 100% = 8,90%
23 For the calculation of proportion of participants in certain age group and the participation rate of each age group is done by using table 12.
Table 12: overview of participants and non-participants sorted by age groups based on the pre- GCC data
Age groups Participant Non-
participant Total
20-29 34 (a) 13 (b) 47
30-39 116 (c) 59 (d) 175
40-49 229 (e) 161 (f) 390
50-60 47 (g) 52 (h) 99
Total 426 (i) 285(j)
Participation rate of age group 20-29: (a/ (a + b)) = (34/ (34+13)) x 100% = 72,34%
Participation rate of age group 30-39: (c/ (c + d)) = (116/ (116 +59)) x 100% = 29,74%
Participation rate of age group 40-49: (e/ (e + f)) = (229/ (229+161)) x 100% = 58,72 % Participation rate of age group 50-60: (g/ (g + h)) = (47/ (47 +52)) x 100% = 47,47%
The proportion of participants in age group 20-29: (a/i) x 100% = 7,98%
The proportion of participants in age group 30-39: (c/i) x 100% = 27,23%
The proportion of participants in age group 40-49: (e/i) x 100% = 53,76%
The proportion of participants in age group 50-60: (g/i) x 100% = 11,03%
For the calculation of proportion of participants related to the smoking status and the participation rate of smoking and non-smoking group the following table is used.
Table 13: overview of participants and non-participants sorted by smoking and non-smoking based on the pre-GCC data
Participant Non-
participant Total
Smoking 27 (a) 15 (b) 42
Non-smoking 119 (c) 56 (d) 175
Total 146 (e) 71 (f)
Participation rate of smoking participants: (a/ (a + b)) = (27/ (27+15)) x 100% = 64,29%
Participation rate of non-smoking participants: (c/ (c + d)) = (119/ (119 +56)) x 100% = 68%
The proportion of smoking participants: (a/e) x 100% = 18,49%
The proportion of non-smoking participants: (c/f) x 100% = 81,51%
For the calculation of proportion of participants in the male and female group and the participation rate of the male and female group the following table is used.
24 Table 14: overview of participants and non-participants sorted by male and female based on the pre-GCC data
Participant Non- participant
Total
Male 249 (a) 181 (b) 430
Female 50 (c) 14 (d) 64
Total 299 (e) 195 (f)
Participation rate of male participants: (a/ (a + b)) = (249/ (249+181)) = x 100% = 57,91%
Participation rate of female participants: (c/ (c + d)) = (50/ (50 +14)) = x 100% = 78,13%
The proportion of male participants: (a/e) x 100% = 83,28%
The proportion of female participants: (c/f) x 100% = 16,72%
For the calculation of proportion of participants in the field worker- and office worker group and the participation rate of the field worker- and office worker group the following table is used.
Table 15: overview of participants and non-participants sorted by male and female based on the pre-GCC data.
Participant Non- participant
Total
Field worker 197 (a) 108 (b) 233
Office worker 230 (c) 198 (d) 322
Total 427 (e) 306 (f)
Participation rate of the field worker: (a/ (a + b)) = (197/ (197+108)) = x 100% = 64,59%
Participation rate of the office worker: (c/ (c + d)) = (230/ (230 +198)) = x 100% = 53,74%
25 Statistical tests
The GCC program started on the 23rd of May and ended on the 11th of September of 2013. To see if the GCC program had impact on the BMI of the participants, the dependant t-test was performed with the SPSS software. The t-test compares the mean of the pre-GCC BMI with the mean of the post-GCC BMI. For this test the participants with both BMI’s, pre-and post, were used. This was a total of 152 participants, both had measurements.
The mean of pre-GCC BMI is 27. 76. The mean of the post-GCC BMI is 27.65. The difference between the mean is 0.12 and the significance is greater than 0.05.
Also the BMI change of the non-participants was tested using the dependant t-test. For this test a total of 71 non-participants with pre- and post BMI were found. The mean of pre-GCC BMI is 27.56. The mean of the post-GCC BMI is 27.55. The difference between the mean is 0.01 and the significance is greater than 0.05.
To see if there is a difference in the pre-GCC BMI of participants and the pre-BMI of non- participants, the independent test is used. The comparison could be made between 178 GCC participants and 109 non-participants. The mean of the pre-BMI in participants is 27.76. The mean of the pre-BMI in non-participants is 27.56. The p-value is 0.800 > 0.05.
To see if there is a difference in the post-GCC BMI of participants and the post-BMI of non- participants, the independent test is used. The comparison could be made between 299 GCC participants and 195 non-participants. The mean of the post-BMI in participants is 27.64. The mean of the post-BMI in non-participants is 27.55. The p-value is 0.909 > 0.005.
The Linear regression method was used to test the influence of the independent variables smoking, age, type of work, ethnicity and sex on the BMI change of the GCC participants.
The significance of Type of work is 0.370, of sex is 0.973, of smoking is 0.941, of ethnicity is 0.521 and of age is 0.991. All p-values are higher than 0.05.
26
Innovation
An intervention by the employer to implement a program with the aim to have a positive change on the health of the employees is a very welcome change. This type of mind setting of the employer can have success at the employees and this can lead to positive influence at home and further. If this success is communicated and shared with other employers than this can lead to increase of health under the employees and by influence at home and in their families to a healthier Community and eventually to a healthier Suriname.
As far as I know this type of intervention is the first to be implemented in Suriname. Even if the hypothesis is not proven still this type of intervention can contribute to encourage employees to reach a healthy weight.
This specific intervention may be used as pilot and lessons learned may be improved to have a better result and have more success. Some of the improvements can be:
- Increased awareness of overweight and the consequences
- The program may be longer to have a sustainable result
- Structural approach
- Also interact on the food provided or available to the employees
- Regular information sessions
- Regular monitoring by third party for objective results
- Together with other beneficial programs, like incentives.
27
Results
We hypothesized that it could well be that the GCC program would have improved the BMI scores of the participants in the GCC program. This hypothesis could not be proved by this thesis according the data available.
Based on the pre-GCC data was the proportion (42, 86%) of the overweight category the largest measured group. This group was also the highest in proportion (47, 26%) to participate in the GCC program.
The proportion of the overweight category was also the highest measured (45.14%) in the post- GCC data and also the highest (47, 83) in participating in the program.
The percentage of overweight persons in the overweight and obese category based on the pre- GCC data is 70%. This is also the percentage of overweight persons in the participating group.
This means that the participating group reflects the same percentage of overweight persons as measured in the total population during the pre-GCC measurements.
The percentage of overweight persons in the overweight and obese category based on the post- GCC data is 73%. The percentage of overweight persons in the participating group is 71%. There is a slight difference of 2%. The participating group reflects on average the same percentage of overweight persons as measured in the total population during the post-GCC measurements.
The proportion of overweight persons is higher in the 30-39 age group (27.60%) and the 50-60 age group (27.55%) based on the pre- GCC data.
Age group 40-49 is the most obese group proportionate wise according the Post-GCC data.
Looking at the 4 large ethnic groups, Hindustani, Javanese, Creole and mix, more overweight persons (29.31) are from the mix group based on the pre-GCC data. According the post-GCC data the more overweight ethnic group is the Javanese group (49.77%).
Based on the pre-GCC data the smoking group was higher in overweight persons (66%) related to the non-smoking group. based on the post-GCC data the proportion of overweight persons was almost the same in the smoking (60%) and non-smoking group (61%).
Office workers are more overweight related to field workers based on both pre- and post-GCC measurements.
Females are proportionately more overweight then males based on pre-and post-GCC measurements.
When the total population is divided by participants and non-participants and sorted by ethnicity Hindustani, Javanese, Creole and Mix, then the participation rate is the highest in the mix ethnicity group (52%), followed by the Hindustani (51%), the Javanese (46%) and the Creole (41%).
The proportion of the Javanese group (64,06%) was the largest within the participants, followed by the Creole (24,66%) , the Hindustani (24,32%) and the mix group (8,9%).
28 When the total population is divided by participants and non-participants and sorted by age groups 20-29, 30-39, 40-49 and 50-60, then the participation rate is the highest (72,34%) in the 20-29 age group, followed by the age group 40-49 (58,72%), the age group 50-60 (47, 47%) and the age group 30-39 (29.74%).
The proportion of participants was the highest in the age group 40-49, followed by the age group 30-39. The proportion of the other two age groups is less than 10%.
When the total population is divided by participants and non-participants and sorted by smoking and non-smoking then the participation rate is higher in the non-smoking participant (68%). The participation rate in the smoking group is 64,29%.
The proportion of participant with a smoking status is 18, 49%, whereas the proportion of non- smokers in the participants group is 81, 51%.
When the total population is divided by participants and non-participants and sorted by male and female then the participation rate in the female group (78,13%) is higher than the male group (57,91%).
The total participants group consisted of 83, 28% male and 16, 72% female.
When the total population is divide by participants and non-participants and sorted by the group field worker or office worker the participation rate is higher in the field worker group (64,59%).
The participation rate in the office worker group is 53, 74%.
The total participants group consisted of 50, 20% office workers and 53, 86% field workers.
Overweight is more prevalent in the non-participating group (74%) related to the participating group (71%). But the difference is very small
Almost 70% of the participants were overweight and obese according the pre-GCC data and almost 72% were overweight and obese according the post GCC data.
There was not much difference in the BMI after the GCC period in participants. This may have been due to negative change in diet and /or positive change in muscle mass, which affects the BMI change adversely. The lack of additional biometric measurements of the waist
circumference and body fat percentage is a pity, because that could help to differentiate.
There was also no significant change of BMI in the non-participants. This suggests that these persons continued their lifestyle as before.
The variables smoking, age, type of job, ethnicity and sex also did not have a significant effect on the BMI change of the participants.
The GCC program did not have a negative impact on the BMI change and should be implemented again.
29
Discussion
The initiative of the GCC program is a very good intention to make people aware about their (lack of) physical activity, (un)healthy eating habits and health. The intention of weigh reduction is not reached significantly in reality. To get to an opinion about the influence of the program on the improvement of health there is a need for more data such as for instance waist circumference/
Waist-Hip ratio change, Lipid level change, HDL-cholesterol-Total cholesterol ratio change, blood pressure change, HbA1c change, lowered quantity of hypertension-Diabetic-dyslipidaemia medication; but this program is a great starting point for persons looking for a way to improve their health.
The participation of overweight persons in the GCC program was a reflection of the total population as measured.
According the GCC database the program was a success and much result were achieved.
According the official report released by the Foundation for chronic disease prevention the GCC program was a success. This statement was based on the following:
- Increase in physical activity level
o 75 % of employees meet or exec the 10,000 step recommended daily activity level (vs. 24% pre-GCC)
o 91% said the GCC has had a positive impact on their relationship with exercise
- Change in health scores
o 84% of employees now rate their overall health as ether good, very good or excellent (vs. 53% pre-GCC
o 53% of employees have moved up one or more health score categories having participated in GCC.
- Long term behavioral change
o 94% of employees reported they were more conscious of opportunities in their day to add more steps
o 90% of employees reported that the GCC had helped them take more personal accountability for their own health.
- Improvement to nutrition
o 64% of employees are more aware about what they eat.
- Weight management
o 71% of employees reported losing weight during the challenge
o Those who lost weight reported an average weight loss of 4.1 kg
o Total estimated weight loss: 1,291 kg
If we look at the results derived from the statistical data than the question may be raised if the self reporting by the participant was truthful or not. It could have been that the reporting was done more optimistic than realistic.
The GCC program success could be better measured if a complete baseline of pre-BMI of all employees’ was achieved and also after completion of GCC.
The following could have had influence on the success rate calculated statistically:
- Selection bias
30 Selection bias may not only have occurred at entry, but could also have happened at the later BMI measurement. In case successful participants were less inclined to have their second BMI measured, this could have been resulted in an apparent failure of the program. This could be explained by the possibility that successful participations had no extra incentive to have their BMI measured again, knowing for themselves already that they have been successful. BMI measurements were also done in the field though.
Personal communication of participants points towards this possibility. They say:”
why should I bother to go to the medical department to have my measurements taken?
I am already putting effort in reporting my steps”.
- Program was short
The duration of the program may not have been such that the BMI may have reduced as wished. This could have contributed to discouragement and disappointment at the participants’ near the end of the period. They may have stopped putting effort before end of the GCC program.
Increase of motivation of participants and non-participants
The participation rate and motivation can be improved by incentive programs. This could also contribute to better and more reliable results of the research.
On request of the Medical department a SWOT (Strength, Weaknesses, opportunities and treats) analyses was performed to evaluate the medical department related to the GCC as part of a strategic analyses. Strengths and weaknesses are internal to the organization, while opportunities and threats generally relate to external factors.
Strength Weaknesses Opportunities Treats
All tools are available to do monitoring activities
Manpower availability, less medical employees due to manpower reduction. Workload issue of employees.
Regionalize GCC guidelines and nutritional advices to improve
awareness, motivation and participation
Decreasing of Suralco’s autonomy in Health and Wellness programs International, high
standard, proven e- program
Easy access to employee medical history/records
Medical service is mainly focused on curative health service and fit for duty- chemical surveillance services
Communication by GCC of in-depth analysis result from 2013 to the
management and workforce to improve
participation rate in the 2014 GCC program
National increase of unhealthy sedentary lifestyle
Strong corporate logistics
Management Suralco not leading by example
Increase of regional (Paranam)
unhealthy food suppliers
