Health Campaign

Health Campaign – Part I

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Health Campaign – Part I

Obesity

Obesity is the abnormal accumulation of fat that would be a risk to ones health. Obesity is measured through the BMI that is body mass index. BMI is determined through the division of the weight of the person in kilograms by the square of the person’s height, which is in meters. One is considered obese if they have a BMI of thirty and above. A person with a BMI that is between 25 and 29.9 is considered overweight (MNT, 2012). Obesity presents a risk of acquiring chronic diseases that include cancer, diabetes and cardiovascular diseases.

Obesity is caused by several factors. The first factor is consumption of too many calories. The rate of calories consumption rose from 1,542 for women per day, in 1971, to 1,877 each day in 2004. For men the rate had risen from 2,450 in 1971 to 2,618 in 2004. This is because most of the food consumed consists of carbohydrates. The taking of drinks that have been sweetened, has also led to high carbohydrates intake. Other factors include lack of enough sleep, lower rates of smoking for people who have been smoking, lack of exercise for the body and medication.

In the past, obesity was common in countries with high income, but cases are also rising in countries with middle incomes, mostly in urban areas. In America, two thirds of the people are overweight; this includes, one child in five children. Around one third of the people are obese. This has seen the number of people with obesity doubled, 30 percent from 1980, 15 percent. On the other hand, the rate of obesity in children has tripled from 6.5 percent in 1980, to a percentage of 16.3. Billions of dollars are spent every year on dieting and every to do with this topic. On top of that, treating the diseases that are caused by obesity takes about 75 billion dollars.

In businesses, every year there is a loss of around $ 20 billion in productivity from the absence that is caused by illness from obesity. The Act of Affordable Care purpose is to increase Americans’ access to health care that is affordable and of high quality. The HHS, Health and Human Services department secretary has the responsibility of creating a National Strategy that will provide Quality Improvement in Health Care that is the National Quality Strategy. In January 2011, the HHS was also given the task of reporting the status of prevention efforts of obesity in Medicaid program, to the congress.

Public Health Institutes are tasked with dealing with obesity and other health issues. These institutes are coming up with ways of improving their states’ population health, through partnerships. Eighty-five percent of Public Health Institutes create manage activities that address obesity. Their aim is to improve on nutrition and physical activities countrywide. These institutes play several roles in developing this work. They include project management, data management, service delivery, evaluation and research, development and advocacy of policy, technical training and assistance and coalition and convening development (NNPHI, 2008).

Partners include the department of the state and local health, welfare and aging departments, organizations in the community, organizations that are faith- based, the legislature, school districts, health care providers, universities and coalitions. Contributors for these activities include departments of state and local health, coalitions, local foundations, school districts and universities. Obesity is categorized as a complex system. The model that is used in the study of complex systems is known as ABM, that is, Agent-Based computational Modeling. In this method, artificial societies are constructed on computers, in order to model complex dynamics.

Computer codes represent each system’s individual agent. After they have been put in a special context, with particular conditions, the agents are given adaptive instructions, which dictate how they interact with the environment and each other. Output is produced by the agents’ processes of decisions and interactions, at the aggregate and individual levels of the system. As a result, the simulation of the computer leads to the production of macro-level patterns, which move from the bottom up. This makes it suitable for the complex systems’ study. To measure the model, the patterns produced, for example, body mass index distribution changes, can be compared directly with data.

The advantages of using ABMs for complex systems are; agents can have substantial diversity. This is because of the explicit modeling of each individual, that is, types of aggregation are required. It also enables flexibility in the assumptions of the making of decisions and processing information by an individual. In simulation models, the agents may be goal oriented in a case where information is limited and constantly changing. This also provides for diversity. Another advantage is that it can be able to study dynamics that are not at balance. Complex dynamics are mostly not balanced. It is also transparent, enabling the research of teams that are cross-disciplinary, for example, in obesity (NNPHI, 2008).

In the study of obesity, ABM would allow the modeling of many mechanisms at the same time, in several scale levels, including important diversity sources. Complex systems can also be measured through System Dynamics. In this technique, three components are used to model a system (Hammond). These components are stocks, flows and feedback tools. Stocks are variables, which decrease or increase with time, for example, BMI. Flows are a stock’s change rates, while feedback loops join flows and stock by time. Another method of measuring complex systems is Dynamic Microsimulation. It is the same as ABM in the bottom-up focus. It assumes that agents are not interacting.

In this approach, it makes analysis easy. However, this also makes it difficult some mechanisms, for example, contagion, social influence and imitation to be captured. The other technique that can be used in studying complex systems is Markov modeling. It also has some features that are similar to ABM. These features include the capturing of distributions and modeling of their dynamics. The models are directly implemented in software packages, which are standard. They cannot manage states of dynamics transition and assume a dimension of state that is low. This hence, decreases their flexibility.

The models that would be most effective in studying obesity, would those which capture many mechanisms at many levels, (separate) macro and micro dynamics and data, give an account of heterogeneities that are significant and permit the implementation of policy. When used together repetitively, empirical and modeling study give great results. Through the generation of theory and hypotheses and highlighting of the most important data, modeling can enable empirical inquiry to be directed. Revised models can be informed by new evidence and data. Obesity targets both men and children (Hammond, 2011).

Research shows that by 2015, the number of people who are overweight will grow to 2.3 billion, while the number of people who are obese will grow to 700 million, if the present trends continue. Statistics also show that heaviest youngsters are more likely to die prematurely than the thinnest youngsters are when they reach adult hood. Cases of obesity are increasing among children. Even though children have fewer health problems that are weight related, children who are overweight stand at the risk of becoming adolescents as well as adults who are overweight. This increases the risk of them contracting chronic diseases. They also stand a high risk of being sad and developing stress and low self-esteem.

Obesity among adults began to rise at a high rate after 1980. The rate of obesity is currently highest among blacks who are non-Hispanic, at 44.1 percent overall, with 49.6 percent for women and 37.3 percent for men. This number is followed by Hispanics at 38.7 percent overall, with 43.0 percent women and 34.3 percent men and then by non- Hispanic whites at 32.4 percent overall, with 33.0 percent in women and 31.9 percent in men. Epidemiologic surveillance systems used for monitoring obesity include information from the Pediatric Nutrition Surveillance System (PedNSS). This can be used in the monitoring obesity in children who participate in programs of public health. It also seeks to describe obesity, in relation to place, time and person. The National Health and Nutrition Examination Survey (NHANES) also monitor obesity in the USA, by sampling individuals (Hammond, 2011).

Epidemiology includes observation, analytic research, hypotheses testing, experiments, intervention and surveillance, to determine the public health. It determines the cause of a disease by studying the population. One of the tools for monitoring and targeting interventions is Public health surveillance. Public health surveillance is the interpretation of data that has been collected and analyzed, in order to prevent control injuries and diseases. It is a tool, which gives an estimate of the status of health and population behaviors.

Since it can measure the proceeds of the population directly, it serves as a useful tool for measuring intervention effects and requirement of intervention. The importance of surveillance is providing information for decision makers to manage and lead with more effect, hence empowering them. Senior managers in finance and health ministries in developing countries have recognized that information from systems of surveillance is useful in evaluation of programs and targeting resources.

Reference

Medical News Today (MNT). (2012). All About Obesity. Retrieved from http://www.medicalnewstoday.com/info/obesity/

National Network of Public Health Institutes (NNPHI). (2008). Fostering Innovations that Improve Health. 2008. Retrieved from http://nnphi.org/uploads/media_items/public-health-institute-activity-and-capacity-physical-activity-and-nutrition-overview.original.pdf

Hammond, Ross, A. (2011). Complex Systems Modeling for Obesity Research. 2011. CDC. Retrieved from http://www.cdc.gov/pcd/issues/2009/jul/09_0017.htm