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Moderate Work and Recreational Activities for Diabetes Control among diabetic Patients on Diabetes Treatment

Yuk Yi Lam, Joey Andrews University Dec 1, 2024

Introduction

Diabetes continues to be a highly prevalent chronic illness not only across the world, but also in the United States. In 2021, individuals having diabetes were as many as 38.4 million representing 11.6% of the US population (Fang et al., 2023). As a chronic illness, diabetes is a disease that can usually be controlled but not cured and can get worse over time if it is not well managed. Deaths attributed to diabetes in the United States from 2017 to 2020 were as many as 358,439 making diabetes to be among the leading causes of death in the country (Kim et al., 2022). Some of the comorbidities associated with diabetes in the United States are hypertension, obesity, hyperlipidemia, chronic kidney disease, cardiovascular disease, fatty liver disease and depression (Nowakowska et al., 2019). Diabetes is normally treated using insulin medication, lifestyle interventions such as diet modification and increased physical activity have also been identified to be important in the reduction of diabetes comorbidities and mortality

(Marín-Peñalver et al., 2016). For individuals who are on insulin medication, it is not clear how lifestyle interventions can help in reducing diabetes comorbidities to increase survival rates. It is important to understand how diabetes control as indicated by glycohemoglobin levels is different diabetes patients on insulin medication is different depending on whether the patients undertake moderate recreational activities or not. The present research study attempts to investigate the relationship between moderate recreational activities and glycohemoglobin levels among diabetes patients on insulin medication to identify whether such patients need moderate recreational activities in addition to insulin medication for enhancing diabetes control.

Background and Rationale

Past research has identified that physical activity is one of the lifestyle interventions that could reduce diabetes comorbidities and mortality (Colberg et al., 2016). According to Colberg

et al. (2016), physical activities improve blood sugar control, cardiovascular fitness, muscle strength and insulin sensitivity among individuals with diabetes to reduce diabetes complications and mortality. Physical activity also improve lipid metabolism and decrease insulin resistance among patients with diabetes (Cannata et al., 2020). Physical activities, however, have adverse effects such as increased risk of acute complications like cardiac events, hypoglycemia and hypoglycemia for people with diabetes, especially when it is undertaken vigorously (Colberg et al., 2016). Diabetes patients who are physically active could, therefore, have lower risks of complications and mortality when compared to diabetes patients who are physically inactive because of having improved blood sugar control, lipid metabolism, cardiovascular fitness and insulin sensitivity as well as reduced insulin resistance, especially if the physical activity is not vigorous. The present research study will contribute to the existing literature and inform diabetes management policies and interventions because most studies have focus on diabetes patients in general and not only diabetes patients on insulin medication investigated by this particular study. The study will also contribute to the existing literature and inform diabetes management policies and interventions because most studies do not access interaction between work activities and recreational activities in the enhancement of diabetes control as is the case for the present research study.

Research Question and Hypotheses

Research question

How is diabetes control indicated by glycohemoglobin levels different between diabetes patients on insulin medication undertaking and not undertaking moderate recreational activities depending on undertaking or not undertaking moderate work activities when sex, age and body mass index are controlled?

Null Hypothesis

Diabetes control indicated by glycohemoglobin levels is not different between diabetes patients on insulin medication undertaking and not undertaking moderate recreational activities when sex, age and body mass index are controlled.

Research Hypothesis

Diabetes control indicated by glycohemoglobin levels is different between diabetes patients on insulin medication undertaking and not undertaking moderate recreational activities depending on whether the patient undertake moderate work activities when sex, age and body mass index are controlled.

Theoretical Framework

This study adopts the Self-Determination Theoretical Framework, which postulates that self-care, weight loss and glycemic control are related among patients with diabetes because of being driven by autonomous motivation (Skinner et al., 2003). According to Skinner et al. (2003), autonomous motivation makes us to do things for intrinsic reasons or for ourselves and is predictive of successful self-care, weight loss and glycemic control. Self-Determination Theoretical Framework has been instructive for approaching the issue of diabetes management among patients with Type 2 diabetes by shedding light on how physical activities enhance diabetes control by enabling individuals to lose weight. The present research study will use this particular theoretical framework to indicate how moderate recreational activities interact with moderate work activities to enhance diabetes control as it enables individuals to lose weight.

Methodology

Research Design

Research design used for the study will be the cross-sectional survey research design. Variables investigated will be glycohemoglobin levels as the dependent variable of interest, moderate recreational activities as the independent variable of interest, moderate work activities as possible effect modifier and gender, age and BMI as possible confounding factors. Data on these variables would be collected at only one particular point in time. This is because data on the variables of interest is collected at only one point in time when a cross-sectional survey design is used for conducting a research study (Wang & Cheng, 2020). A cross-sectional survey research design will be used for conducted this particular research study because of being appropriate for the collection of data intended to assess relationship between variables investigated without establishing causality between the variables as what the study was intended to achieve.

Sample

The data analyzed for the study will be obtained from the 2015/2016 national health and nutrition examination survey (NHANES 2015/16). Sample size of the study will be 899 individuals and will include only diabetes patients taking insulin or diabetic pills to lower blood sugar regardless of their sex, age or body mass index. This is because the study will be investigating relationship between variables of interest only among diabetes patients who are currently on diabetes treatment. Sampling method used for selecting individuals for the sample was a complex, multi-stage probability sampling with oversampling of certain population subgroups. This is intended to ensure that the study represents the population of

non-institutionalized civilians in the Unites States as much as possible to enhance generalizability of the findings obtained.

Measurement/Instrumentation

Glycohemoglobin level was measured as a percentage, age was measured in years as reported by the study participant and body mass index was measured in kilograms per meter squared. For measuring glycohemoglobin level, an analyzer was used for diluting the whole blood spacemen with a hemolysis solution, step-wise elusion was used for removing hemoglobin fractions from the column material and photometer flow cell was used for measuring changes in the absorbance at 415 nm. The other instrument used for collection of data required for the study was a questionnaire for capturing sex and age of the study participants. Glycohemoglobin levels as the dependent variable of interest and both age and body mass index as possible confounding factors will be continuous variables because of having been measured on an interval or ratio scale. Moderate recreational activities as the independent variable of interest, moderate work activities as the possible effect modifier and gender as the other possible conducting factor were dichotomous because of having only two categories that were not ordered.

Method of Data Collection

Data collection methods used were clinical examinations, medical and laboratory tests and interviews. Clinical examinations were used to assess diabetes status of the study participants and identify whether participants were currently undertaking diabetes treatment for inclusion in the sample investigated for this particular study. Medical and laboratory tests, on the other hand, were used for assessing glycohemoglobin levels of the study participants and interviews were used for capturing demographic characteristics of the study participants that

included both sex and age and assessing whether study participants were undertaking or not undertaking moderate recreational activities and/or moderate work activities.

Internal Validity

Data on the dependent variable of interest was collected using medical and laboratory tests that had already been validated. Independent variables of interest, on the other hand, were binary categorical and did not require study participants to recall past experiences. This is likely to have eliminated recall bias and reduced measurement errors to improve interval validity of the study. Data on body mass index was also obtained using medical examination instead of being self-reported by the study participants, which could have eliminated recall and social desirability bias to enhance internal validity of the study. Selection of study participants for the study was also undertaken randomly, which could have eliminated participant selection bias to enhance internal validity of the study.

Data Analysis

Analysis of the data collected for the study will be undertaken using SAS version 9.4. Analysis of the study will start with descriptive statistics that will include mean and standard deviation computed for the continuous variables and frequencies and relative frequencies obtained for the dichotomous variables for assessing distribution of the variables investigated among individuals in the sample. Descriptive statistics will be followed by simple linear regression analyses intended to identify how the dependent variable is related to the independent variable and the possible effect modifier when possible confounding factors are not controlled. Simple regression analyses would be followed by multiple linear regression analysis intended to identify how dependent variable is related to the independent variable depending on the possible effect modifier when possible confounding factors are controlled. Simple and multiple linear

regression analyses are used for the study because the dependent variable is continuous given that it had been measured on an interval or ratio scale. The level of significance was set at 5% ( α

= 0.05).

Ethical Consideration

This particular study will use only secondary data that is publicly available obtained through the NHANES 2015/16, which makes it not to require ethical approval by the Institutional Research Review Board. Data collected for the study had already been anonymized, which ensures that participants wellbeing, privacy and confidentiality is protected. Participation in NHANES 2015/16 was also voluntary and individuals need to provide informed consent for them to be allowed to undertake the survey. This is an indication that participation in this study could be regarded as being voluntary and study participants could be regarded as having provided informed consent for their data to be used for the study.

Limitations of the Study

This particular research study will have two main limitations. The first limitation is that the findings obtained could be outdated because the data analyzed for the research study could be outdated given that it was collected more than seven years ago. The other limitation is not being able to establish causality of relationship between dependent variable and dependent variable because of failing to control all known and unknown factors that could confound the relationship between dependent and independent variables. Possible confounding factors analyzed for the present research study are only sex, age and body mass index, which are not the only factors that could confound relationship between glycohemoglobin levels as the dependent variable of interest and moderate recreational activities as the independent variable of interest.

Significance of the Study

The present study will be highly important in informing policies and interventions on the management of diabetes. Contrary to what is the case for the previous studies, this particular study will indicate whether moderate physical activities are necessary for the management of diabetes to reduce complications and mortality among patients who are already undertaking diabetes medication. The study will also indicate whether moderate recreational activities needed for the management of diabetes to reduce complications and mortality only among individuals not undertaking moderate work activities contrary to what is the case for the previous studies.

References

Cannata, F., Vadalà, G., Russo, F., Papalia, R., Napoli, N., & Pozzilli, P. (2020). Beneficial Effects of Physical Activity in Diabetic Patients. Journal of Functional Morphology and Kinesiology, 5(3), 70. https://doi.org/10.3390/jfmk5030070

Colberg, S. R., Sigal, R. J., Yardley, J. E., Riddell, M. C., Dunstan, D. W., Dempsey, P. C., Horton, E. S., Castorino, K., & Tate, D. F. (2016). Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care, 39(11), 2065–2079. https://doi.org/10.2337/dc16-1728

Fang, L., Sheng, H., Tan, Y., & Zhang, Q. (2023). Prevalence of diabetes in the USA from the perspective of demographic characteristics, physical indicators and living habits based on NHANES 2009-2018. Frontiers in Endocrinology, 14, 1088882. https://doi.org/10.3389/fendo.2023.1088882

Kim, D., Alshuwaykh, O., Sandhu, K. K., Dennis, B. B., Cholankeril, G., & Ahmed, A. (2022).

Trends in All-Cause and Cause-Specific Mortality Among Individuals With Diabetes Before and During the COVID-19 Pandemic in the U.S. Diabetes Care, 45(6), e107–e109. https://doi.org/10.2337/dc22-0348

Marín-Peñalver, J. J., Martín-Timón, I., Sevillano-Collantes, C., & del Cañizo-Gómez, F. J. (2016). Update on the treatment of type 2 diabetes mellitus. World Journal of Diabetes, 7(17), 354–395. https://doi.org/10.4239/wjd.v7.i17.354

Nowakowska, M., Zghebi, S. S., Ashcroft, D. M., Buchan, I., Chew-Graham, C., Holt, T., Mallen, C., Van Marwijk, H., Peek, N., Perera-Salazar, R., Reeves, D., Rutter, M. K., Weng, S. F., Qureshi, N., Mamas, M. A., & Kontopantelis, E. (2019). The comorbidity

burden of type 2 diabetes mellitus: Patterns, clusters and predictions from a large English primary care cohort. BMC Medicine, 17, 145. https://doi.org/10.1186/s12916-019-1373-y Skinner, T. C., Cradock, S., Arundel, F., & Graham, W. (2003). Four Theories and a Philosophy:

Self-Management Education for Individuals Newly Diagnosed With Type 2 Diabetes.

Diabetes Spectrum, 16(2), 75–80. https://doi.org/10.2337/diaspect.16.2.75 Wang, X., & Cheng, Z. (2020). Cross-Sectional Studies: Strengths, Weaknesses, and

Recommendations. Chest, 158(1S), S65–S71. https://doi.org/10.1016/j.chest.2020.03.012

,

[Project Title]

by

Student Name

Project Submitted in Partial Fulfillment

of the Requirements for Course FDNT 560

Health Research Methods

Andrews University

Fall 2024

Contents Chapter 1. Introduction 7 Introduction 7 Background 7 Problem Statement 7 Purpose of the Study 7 Research Question (s) and Hypothesis (es) 7 Theoretical framework 7 Nature of the study 7 Scope and delimitations 7 Limitations 7 Significance 8 Summary 8 Chapter 2, Literature Review 9 Chapter 3. Methods 10 Research Design and Rationale 10 Population 10 Sampling and Sample Size 10 Measurement 10 Procedure and Data Collection 10 Data Analysis Plan 10 Summary 11 Limitations, significance, possible impacts, and dissemination plan 12 References 13 Appendices 14

List of Tables (If applicable)

Table 1 9

List of Figures (If applicable)

Figure 1. 10

Abstract

Insert abstract here; it should be no more than one page long.

Chapter 1. Introduction

Introduction

Begin text here.

Use other level headings as appropriate and ensure that level 1 and level 2 headings are included in your table of contents.

Background

Problem Statement

Purpose of the Study

Research Question (s) and Hypothesis (es)

Theoretical framework

Nature of the study

Scope and delimitations

Limitations

Significance

Summary

Chapter 2, Literature Review

In this chapter, you should have a short introductory paragraph, then move to your main topic headings, sub-headings, etc. Your sub-headings here (if you include them) should relate to specific variables in your research questions or hypothesis.

Describe your theoretical framework or models.

Remember that a literature review is a systematic synthesis of prior research and knowledge on your topic. This is not supposed to be a list of summaries of articles one after another. This YouTube video provides a good explanation on how to write your literature review. You may also copy and paste this link in your browser to access the video. https://youtu.be/bCh_3VqwTnI?si=3yJjsJ2nSKWhWfxj

Restate your study purpose in the final paragraph of your literature review.

Chapter 3. Methods

This is a description of how you plan to arrive at answers to your research questions (Sub-headings (Sections) in this chapter vary depending on the nature of the research project). The sections should address the following, at a minimum.

Research Design and Rationale

In this section, identify the research design and describe your study variables (independent, dependent, covariate, mediating, and/or moderating variables, as appropriate), including their level of measurement.

Population

Define the target population

Describe the participants, including selection (Inclusion/exclusion criteria),

Sampling and Sample Size

Identify the sampling strategy and the sample size

Measurement

Any tools or your own survey questionnaires. Provide the level of measurement for your key variables, including their value options.

Procedure and Data Collection

How will you collect your data? What steps will you follow? If you are using secondary data, how did they go about collecting their data? What steps did they follow?

Data Analysis Plan

Identify software used for analyses; Provide details of any data cleaning procedures, recoding, and new variable creation as appropriate; describe in detail the analysis plan including any statistical tests that will be used to test the hypothesis (es); rationale for inclusion of any potential covariates and/or confounding variables if applicable.

Any ethical considerations, including IRB plans

Summary

Provide a summary of your design and methods.

Limitations, significance, possible impacts, and dissemination plan

References

Appendices

Appendices (which could include as needed)

Final Codebook

Survey questionnaire and/or other measurement tools

Budget & Justification

Project Implementation Timeline (Gantt Chart)

Any other items that may apply to your study

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