Introduction

Epidemiological data are paramount resources towards targeting and developing evidence- based control measures in the projects of public health and safety. Evidence of population health reports help the medical science to articulate deviations and irregularities in measurable statistics, based on which empirical approach towards obtaining qualitative, as well as quantitative data sets become necessary. In this study principles, methods and applications of epidemiological data regarding Obesity is relevantly discussed in order to develop an inferential understanding of the healthcare investigation process. However, strengths and limitations of the data sets will also be analysed to depict a clear understanding of sustainable health promotion.

Critical consideration of the role of epidemiology towards investigating population health regarding Obesity

Principles:

Principles of epidemiology of public health practice associated with concepts, procedures and statistics of surveys, based on which frequency measures of diseases can be interpreted effectively. As per the ideas of Woldemichael (2019), epidemiology has been developed to focus on epidemics of communicable diseases, which can derive data regarding infection rates, patterns, similar symptoms as well as death rates. One of the transparent principles of epidemiology is to search for determinants. Causes as well as other factors related to the occurrence of the disease can be investigated in order to identify patterns of spreading the disease. Risk factors associated with a disease such as obesity can also be testified through epidemiological procedures. On the contrary, principles of epidemiology is also concerned with the frequency and patterns of health issues in a specific population, which can help medical science to develop measures of handling the epidemics (Erina et al. 2019). However, the principle of systematic and unbiased approach is related to careful observation as well as valid comparison, which can obtain economic as well as behavioural solutions for the epidemics.  

Methods:

Methods of epidemiological data generation play an important role towards understanding the present trends related to healthcare attributes, based on which effective change in medical interventions can be obtained. As opined by Owolabi et al. (2018), major epidemiological data implementation methods are descriptive, analytic and experimental. These approaches can be taken into consideration to investigate the occurrence of the disease. Descriptive epidemiology can describe outbreaks of the epidemics in terms of person, place and time, which can generate a clear understanding of experimental conjectures of the disease. Socio-demographic characteristics of cases including societal variable such as age, sex, ethnicity, occupation and social status can be investigated and explained through descriptive epidemiology. In the dataset of baseline characteristics representation, it can be seen that ultra-processed food consumption has been increased among graduates due to desk jobs, which shows a result of obesity in the present context of healthcare. However, the statistics of family history of obesity shows a clear understanding of the rates of different occupation groups, which can enhance the potential of the epidemiology to create a baseline for societal medical interventions.       

Applications:

Epidemiological data can help medical institutions to identify new out breaking patterns of a disease such as Obesity, AIDS and Cholera. These datasets can also provide clues of mostly affected population groups and can also suggest strategies to control as well as prevent the outbreak. Community diagnosis can also be performed through developing epidemiology of diseases in the present context of population health. It is important to calculate individual risks towards labelling the disease interventions in order to create a pathway for reversing the impact of the data relevantly (Ng et al. 2021)). Since, Obesity increases the risk of chronic disease morbidity such as depression, diabetes, cancer and cardiovascular diseases, epidemiological methods can help the population to identify the fatal causes behind the spread and to eradicate external captivity of the disease in the present context of healthcare. However, the datasets show increased physical activity among the elderly population, which can be promoted to the young population for maintaining physical disparities among specific age groups.

On the other hand, mental health is also a relative measure in epidemiology, which can be assessed by the researchers during accumulating information through questionnaires. Casual challenges such as BMI rate, vascular dementia and depression are the key considerations of Obesity in the present context of mental health. Based on the views of Ortega et al. (2020), epidemiological tools such as interactive participation as well as qualitative data collection can be utilised by the researchers in order to depict a clear idea of individual mental health asserisons during suffering from Obesity. However, the approach towards analytical measuring of mental functioning and physical attributes can help the development of epidemiology to obtain relevant data sets against Obesity incumbents.

Role of qualitative as well as quantitative data and intelligence towards shaping population growth

Discussion of the accumulated data for exploring Obesity

Qualitative data depict clear and perquisite understanding of human perceptions towards the diseases, which help analysis procedures to intercept the ideologies effectively. On the contrary, quantitative data provides empirical calculations and statistics regarding percuisitive variables of diseases, based on which visualised presentation of the information can be possible through charts, graphs and maps (Xue et al. 2018). Characteristics such as educational status, family history of obesity and smoking habits have been assessed on a 10 year scale through quantitative data collection, which shows an increased mass fluctuation in standard deviation annexations. Causes of Obesity such as sitting for hours, energy, carbohydrate, protein as well as lipid intakes have been accumulated to derive implicit results to the epidemiology. However, habits of fruit, vegetable as well as fast-food consumption have also been incorporated in order to derive the information regarding the mass involvement.

On the other hand, baseline analysis can help epidemiological data incorporation processes through estimating the sample sizes, based on which proportions and ratios can be generated against the incumbents. Information regarding fried food, sweet and meat consumptions can derive a sustainable idea of the level of Obesity among the population. As per the ides of Maugeri and Barchitta, (2019), it is important to maintain a statistical regularity for promoting the features of epidemiology in the field of medical science. Since the information regarding generic habits has created a divergence in data analysis, it can be said that an inferential approach towards articulating the negative measures such as corroborative annexation and unethical response can derive explicit results on public health management.

Strengths and limitations of the qualitative as well as quantitative data regarding Population health management

Strengths:

The qualitative data has demonstrated the impact of Obesity among the population as well as diverse perceptions towards the disease due to perceived challenges. The qualitative information that has been interpreted from the given statistics can illustrate the condominium effects of Obesity in the present context of healthcare promotion. On the contrary, quantitative evidences such as Cox proportional HRs helped the epidemiology of Obesity to incorporate substantial characteristics such as age, sex and multivariable in order to develop a diverse analysis on Obesity Epidemic (Rutberg and Bouikidis, 2018). Due to the approach towards quantitative analysis the research has been performed within a large sample, based on which effective change can be obtained in medical interventions. However, quantitative data collection procedures helped the epidemiology to utilise randomised samples, which helped the narratives of the epidemiology on Obesity management.

Limitations:

Qualitative data accumulated by interacting with specific population groups have been time-consuming, which was one of the primary limitations of the study. As per the views of Noyes et al. (2018), investigation of casualties has always been difficult, which created another limitation towards qualitative data accumulation. On the contrary, the target population can be more specific, which can derive convenience based sampling for the development of Obesity epidemiology. Inabilities have also been seen during analysing the data sets, based on which limited view of the data has prevailed in this study. However, expensive measures for conducting mass data collection has also impacted the quality of data in the present context of population based healthcare management.

Critical analysis of the role of the accumulated data towards informing public health activity for handling the Obesity epidemic

Qualitative data that has been accumulated in the study played an important role towards analysing the mode sets and perception of people towards Obesity. Based on the ideas of Iqbal et al. (2019), several groups do not give credit to the fact that being fit is a measurable entity, which impacted population management negatively. Inappropriate measures towards assessing public health can derive massive change in subordinate regulations that has been developed by medical councils of states. Perceptions towards mental health, employability and social status have been accumulated through qualitative data analysis, which shows relativistic measures of data inequality towards handling the Obesity epidemic.

On the contrary, information regarding age, sex, occupation and social ethnicity have been recorded through quantitative data collection, which helped the framework to assess the requirements of conducting the research for the development of Obesity epidemiology. As opined by de Mutsert et al. (2018), it is important to mandate social conjectures for creating a supportive atmosphere for analysing the after effects of Obesity, based on which empirical evidence of mass awareness of the disease can be fortified. However, components such as standard deviations and intelligence based mapping can impact the present setup of epidemiology in the present context of medical interventions. 

Analysis of the research evidences

Qualitative approaches such as accumulating different perceptions about Obesity causes and social avoidance to the disease increased the potential of the epidemiology, based on which effective change in medical interventions can be obtained. As argued by Chooi et al. (2019), it is important to incorporate subjective ideas of data collection, which can help studies to assess the mental ability of the care seekers in the context of population based healthcare. However, perceptions about mental ability, social conjectures, financial status and moral have also been assessed in these datasets, based on which empirical evidence of draft presentation can be fortified.

On the contrary, information regarding the ability of consuming food has also been included during quantitative data assimilation, which increased the potential of the study towards assessing the characteristics of Obesity among the population. Measures of baseline BMI and blood pressure rates have been incorporated by the researchers in order to collect empirical data regarding Obesity (Merkel, 2020). However, the strategy towards accumulating information regarding Obesity through quantitative data collection has impacted the analysis of social conjecture towards evidence based epidemiology.

Recommendations for public health practise

Recommendation 1: Development of supporting health services and clinical interventions

Lack of reimbursement and lack of time towards addressing obesity during consulting sessions with physicians impacted the societal conjectures of the population. Involvement of primary care and nutrition based diet plans can eliminate the components of Obesity (Turner et al. 2018). However, public healthcare services can incorporate subjective clinical interventions consisting of weight loss medication guidelines in order to promote physical sustainability within the population.

Recommendation 2: Influencing healthy eating and physical activity

Health eating can derive self-awareness among people, based on which mass weight reduction initiatives can be seen in the present context of healthcare. As per the views of Kumanyika (2019), policies that directly influence behaviours can be incorporated by the medical authorities in order to spread social awareness of the disadvantages of being obese. However, physical activity such as running, walking and playing outdoor games can be promoted to school and universities in order to maintain the physical attributes of the population.

Recommendation 3: Developing socio-economic environments

Supportive environments play an important role towards engaging obese people towards achieving their goals. Development of walking as well as running communities can be created in order to aware and engage people towards fit initiatives irrespective of their social and financial status (Turner et al. 2018). However, the approach towards the development of socio-economic environments can enhance self-confidence and self-reliance within individuals, which can direct the population towards physical sustainability.

Recommendation 4: Practices of Health Check-ups repeatedly

It has been noted from the above discussion that, obesity as a significant health issue has evidently impacted a large area of the current population of the whole world, and the very reason for this disease is excessive fat. Since the disease generally occurs due to heavy body fat, it will be recommended to initiate the practices of health check-ups repeatedly to keep monitoring the state of health and obesity rate. This particular solution will be hopeful for both avoiding obesity and other related diseases that can harm the health aspects of a person (Puhl et al. 2020). However, daily checkups may be a consistent process where time and effort are both needed, for which that person needs to initiate the parasite with a daily routine chart.

Recommendation 5: Consuming Less Fat-based Foods and Substituting them with Nutritious Food

On the other hand, consuming less fat-based foods and substituting them with nutritious food might be another significant and effective solution that every person needs to consider. This particular recommendation will be useful to adopt a healthy life as well as avoid other related diseases.  However, due to eating habits, many people faced difficulties changing their diet plans. For that reason, making a diet plan from each nutritionist will be useful to maintain good health as well as avoid the possibility of obesity.

Conclusion

From the above discussion, it can be concluded that the aspect of epidemiology and population health is a significant matter to discuss, where information about human health and effect from various aspects has been found. In this study, a detailed discussion on the background of epidemiology has been added, which has provided brief information on the content of health aspects. Moreover, in the study, a detailed section of investigation towards population health has been added that sheds light on the aspects of obesity and its key impacts on human life. Furthermore, the study has also discussed population growth in the context of obesity effects by analysing both qualitative and quantitative data along with its limitations. On the other hand, the study has a critical analysis of the collected data for gathering data on public health activity to handle the obesity epidemic has also been included.