here the documents for the assignment:
1-The assignment what to do
2-the guideline for the teacher
3-the articles I want to talk about: epidemiologic research
4-a little text about where I'm working
5-down here a copy of my book of the course
Assignment 2: Application of Epidemiology in Community Health Nursing | Value 20%
The purpose of this assignment is to provide you with an opportunity to demonstrate utilization of epidemiology research related to the health of the community.
Determine a specific population that you would like to have more information about, this should be the same population chosen for assignment 1 and the one you anticipate to use for assignment 3 and 4).
Use the Athabasca University Library Databases to search the epidemiology literature. Students will:
Find an applicable research article on your chosen topic.
Summarize and critique your chosen research article.
Consider how this research could be integrated into nursing practice.
Your work will achieve the maximum value/grade if it is succinct and insightful and clearly shows how you have applied the theory learned to a practical situation.
Your critique should include, but is not limited to the following:
What type of study design is it? Provide rationale.
Are the findings reported consistent with information/knowledge that you have? Do the reported relationships make sense?
If reported, how strong is the observed association?
Would you incorporate the findings of this study into your community health nursing practice (i.e., the health promotion program that you are planning) or recommend this study to others? Provide rationale.
What further research question(s) would you develop in relation to this study and/or your observations?
When submitting in the assignment dropbox include a copy of the article in PDF along with your completed assignment.
· Each element of the assignment guidelines is addressed.
· Ability to analyze, evaluate, create, and engage in critical inquiry is evident throughout.
· Adheres to APA 7th edition scholarly format – limit of 5 pages (excluding title, reference, and appendix pages).
Tips from the teacher:
I am sharing some Assignment 2 tips to help summarize the strategies for this assignment.
· Choosing an epidemiologic study: Epidemiology research studies characteristics include:
– what happens to the people:
-the incidence, causes and effects of diseases in populations, and trends and patterns
-investigates factors that determine the presence or absence of diseases and disorders
-reveals risk factors for a particular disease.
-helps us to understand how many people have a disease, if those numbers are changing, and how the disorder affects society and even the economy. As for knowing the correct type of study to choose, the major types of epidemiology study designs are randomized controlled trials, and nonexperimental study types including cohort, case control, cross-sectional and ecological studies.
· Present this assignment as if you think the audience has no background knowledge on the topic- so present as you would in a conference
· Introduction-state the purpose and strategy for the organization and set up the logical flow of the assignment so the reader is engaged and knows what you are doing. Include the purpose as related to the assignment guidelines- the purpose of this assignment is to demonstrate utilization of epidemiology research related to the health of your selected community.
· Provide the rationale for the choice of the epidemiologic research in relation to your community/population that you chose for all the assignments.
· Identify the specific population and selection of the study design with rationale.
· Critique the study with the focus of addressing the points in the marking criteria. i.e. -Critique – the strong points, the weak points, the gaps, omissions and assumptions.
· Are the findings reported consistent with information/knowledge that is available? Do the reported relationships make sense? If reported, how strong is the observed association? (Strength of associations should include statistics depending on the type of measurements in the study.)
· Specify-Would you incorporate the findings of this study into your community health nursing practice (i.e., the health promotion class that you may be planning) or recommend this study to others? Provide rationale. Why or why not? If so, how?
· Use critical inquiry-demonstrate the ability to read and comprehend what the researchers were doing and relate it back to the reader in your own words; paraphrasing is important, and you can think about challenges that incorporating the research might hold to your nursing practice. i.e. How does this study influence your practice as a nurse- i.e. shift how you care for the population or consider providing health promotion programs that are not in existence? Say how and why.
Assignment 2: Application of Epidemiology in Community Health Nursing
Student: Date Received:
Marked by: Marlyss Valiant
· The research article been summarized clearly and concisely
· The research article has been summarized to a(n) insufficent/beginning/satisfactory/good/excellent level
· The type of study design was articulated
· Rationale provided for study design
· The type of study design was articulated to a(n) insufficient/beginning /satisfactory /good/excellent level
· Rationale was provided to a(n) insufficient/ beginning /satisfactory/ good/excellent level
· Are the findings reported consistent with information/knowledge that is available?
· Do the reported relationships make sense?
· If reported, how strong is the observed association?
· The findings reported are explained in relation to previous information/knowledge to a(n) insufficient/beginning /satisfactory/ good/excellent level
· The reported relationships are articulated to a(n) insufficient/beginning /satisfactory/ good/excellent level
· The observed association are/are not discussed
Integration into Practice
· Explanation of integration into practice was evident
· Recommendations of this study to others was included
· Rationale provided (ie: strengths and limitations of research)
· Integration into practice was evident and explained to a(n) insufficient/beginning /satisfactory/good/excellent level
· Recommendations of this study to others was included/not included
· Rationale was provided and strengths and limitations of the research were included to a(n) insufficient/beginning /satisfactory /good/excellent level
· Were further research questions developed in relation to this study?
· Further research questions developed in relation to study to a(n) insufficient/ beginning/ satisfactory/ good/excellent level
· Ability to analyze, evaluate, create, and engage in critical inquiry is evident throughout
· All elements of the assignment guidelines are addressed
· The ability to analyze, evaluate, create, and engage in critical inquiry is performed to a(n) insufficient/beginning /satisfactory /good/excellent level
· All elements of the assignment guidelines are addressed to a(n) insufficient/beginning /satisfactory /good/excellent level
· Paper is within page limit (5 pages excluding title and reference page).
· Paper uses correct spelling and grammar
· The paper is informative and within page limit
· The paper is organized in a(n) insufficient/ beginning/satisfactory/good/excellent manner
· The paper has many/some/few/no errors in spelling, punctuation, grammar, sentence structure
Adheres to Current APA
· All elements of current APA edition have been met
· The paper was written in a scholarly format including: title page, introduction, phrasing, headings, and conclusion to a(n) insufficient/beginning/ satisfactory/good/ excellent level
· References are published within last 10 years and appropriate for the assignment—completed to a(n) insufficient/beginning/ satisfactory/good/excellent level
· APA current edition format for in text citation and reference page was used to a(n)
insufficient/ beginning /satisfactory /good/excellent level
If you have any questions or need further clarification, please contact me directly via course mail or telephone.
1Scientific RepoRtS | (2019) 9:15909 | https://doi.org/10.1038/s41598-019-52200-x
examining environmental contaminant mixtures among adults with type 2 diabetes in the cree first nation communities of Eeyou Istchee, canada Aleksandra M. Zuk1*, Leonard J. S. tsuji1, evert Nieboer2, ian D. Martin1 & eric n. Liberda3
Type 2 diabetes mellitus (T2DM) disproportionately affects Indigenous populations. It is possible that exposure to complex mixtures of environmental contaminants contribute to T2DM development. This study examined the association between complex environmental contaminant mixtures and T2DM among canadian indigenous communities from the Eeyou Istchee territory, Quebec, Canada. Using data from the cross-sectional Multi-Community Environment-and-Health Study (2005–2009) Principal Component Analysis (PCA) was used to reduce the dimensionality of the following contaminants: 9-polychlorinated biphenyl congeners; 7-organic pesticides; and 4-metal/metalloids. Following this data reduction technique, we estimated T2DM prevalence ratios (PR) and 95% confidence intervals using modified Poisson regression with robust error variance across derived principal components, adjusting for a priori covariates. For both First Nation adult males (n = 303) and females (n = 419), factor loadings showed dichlorodiphenyltrichloroethane (DDT) and lead (Pb) highly loaded on the second principal component (PC) axis: DDT negatively loaded, and Pb positively loaded. T2DM was significantly associated with PC-2 across all adjusted models. Because PCA produces orthogonal axes, increasing PC-2 scores in the fully adjusted model for females and males showed (PR = 0.84; 95% CI 0.72, 0.98) and (PR = 0.78; 95% CI 0.62, 0.98), respectively. This cross-sectional study suggests that our observed association with T2DM is the result of DDT, and less likely the result of Pb exposure. Further, detectable levels of DDT among individuals may possibly contribute to disease etiology.
Globally, diabetes continues to be a growing concern1. In Canada, Indigenous peoples are disproportionately affected by diabetes mellitus (T2DM)2. The lifetime risk of diabetes is estimated to be 8 in 10 among First Nations persons, and 5 in 10 among non-First Nations persons over 18 years of age2. However, the etiology and patho- genesis of diabetes mellitus is yet to be fully understood. Exposure to environmental contaminants and the risk of diabetes has received much research attention as persistent organochlorine pollutants (POPs) have been shown to be associated with type 2 diabetes mellitus3–7.
In an extensive review of predominantly cross-sectional studies, Taylor et al.7 reports a positive association between T2DM and some organochlorine pollutants (e.g., trans-nonachlor, dichlorodiphenyldichloroethylene (DDE), polychlorinated biphenyls (PCBs)). Similarly, in an updated, and globally-relevant review, Kuo et al.8 confirmed the positive association between organochlorine compounds (OCs) and T2DM. More specifically, Pal et al.9 observed higher plasma concentrations of OCs among persons with diabetes from First Nation commu- nities in northern Canada. Similar to organic contaminants, long-term environmental exposure to toxic metals and/or deficiency of essential metals may possibly also contribute to the development of diabetes10. The role of various inorganic metals and metalloids on type 2 diabetes is complex. For example, Khan and Awan10 note that poor glycemic control and diabetes may alter the level of various essential trace elements due to polyuria. Chen
1Health Studies, and the Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada. 2Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada. 3School of Occupational and Public Health, Ryerson University, Toronto, Ontario, Canada. *email: [email protected]
2Scientific RepoRtS | (2019) 9:15909 | https://doi.org/10.1038/s41598-019-52200-x
et al.11 suggested that some heavy metals may play a role in T2DM etiology by adversely affecting islet function. Cross-sectional data show that metals such as cadmium may contribute to hypertriglyceridemia12. Commonly, type 2 diabetes is complicated with dyslipidemia and other factors associated with metabolic conditions which increase the risk of developing cardiovascular diseases and T2DM among Indigenous populations13. Further, toxic metals may act as endocrine disrupters that contribute to adiposity14, which is a risk factor that exacerbates metabolic and physiologic abnormalities associated with T2DM.
In Canada, Indigenous populations have a higher risk of developing T2DM and health-related complications compared to general Canadian population2,15. Therefore, examining the associations between environmental con- taminants and T2DM is a priority, especially among Indigenous communities, where higher body burdens of complex mixtures exist. In this study, we examined the association between complex environmental contaminant mixtures and prevalent type 2 diabetes status among Canadian Cree communities residing in the Eeyou Istchee territory, in northern Quebec, Canada.
Materials and Methods Data sources. The Eeyou Istchee territory, located in the James Bay Region of northern Quebec, Canada consists of nine Cree communities (Fig. 1). The Nituuchischaayihtitaau Aschii – Multi-Community Environment- and-Health Study aim was to provide assessment and surveillance among people of Eeyou Istchee. Eligibility for enrollment in the study included any person living on reserve. The Environment-and-Health Study stratified participants by age: children (0–7 years, and 8–14 years), adults (15–39 years, and 40 years and older). The main objectives examined the health effects of lifestyle factors, (including diet), environmental contaminants exposure, and environmental change on wildlife and aquatic ecosystems resulting from mining, forestry, and hydro-elec- tric developments. In total, nine Cree communities were sampled. However, two of the nine communities were for an initial pilot study on preliminary health assessments conducted between 2002–2005, and not part of the analysis undertaken in this study. The remaining seven communities were studied between 2005–2009, which focused on participant health measures including exposure to environmental contaminates. Due to the time required to travel to between remote communities and collect all the necessary data, field data collection took place a two-to-four-week period over spring/summer. Specifically, one community was sampled in 2005, two in 2007, two in 2008, and two in 2009 (community names withheld at the request of the Cree Board of Health and Social Services of James Bay. Full details about the Multi-Community Environment-and-Health Study are provided16–19. As part of the Nituuchischaayihtitaau Aschii – Multi-Community Environment-and-Health Study, trained research nurses were integral to the study data collection. Participants underwent a physical examina- tion, completed health and dietary surveys, and provided tissue and blood samples for laboratory analysis. An additional medical chart review was performed by a research nurse who had been involved in the clinical field work to verify individual health-related information ascertained from health-questionnaires for all consenting adults. Informed consent was obtained from all participants or their guardians in Cree, English, or French. The Nituuchischaayihtitaau Aschii – Multi-Community Environment-and-Health Study was conducted in accordance with relevant guidelines, regulations, and research agreements. All work conducted was approved by the research
Figure 1. Eeyou Istchee Territory, Quebec, Canada.
3Scientific RepoRtS | (2019) 9:15909 | https://doi.org/10.1038/s41598-019-52200-x
ethics boards of McGill University and Laval University, in partnership with the Cree Board of Health and Social Services of James Bay and McMaster University.
Study population. In the 2005–2009 Environment-and-Health Study, 1750 participants were recruited. Our analysis included the following adults over the age of 20 years of age who had: (1) medical-chart verified T2DM diagnoses; (2) complete environmental contaminant exposure profiles; (3) undergone physical examina- tion, completed interviewed health questionnaires, and underwent a phlebotomy blood draw were retained for analyses. Medical chart reviews were conducted in only seven of the nine communities for self-reported medical conditions. Therefore, adults who had not undergone medical chart review were excluded from analysis. Adults with type 1 diabetes were also excluded. This resulted in a total of 722 cases, representing seven of the nine com- munities from the Eeyou Istchee territory. A flow chart of the sample is presented in the Supplemental Fig. S1.
environmental contaminant analyses. Details concerning the analytical methods and related QA/QC are provided in Liberda et al.20. Briefly, OCs were recovered from blood plasma using solid-phase extraction and cleaned on a florisil columns prior to high resolution gas chromatography-mass spectrometry (HRGC-MS) analysis. Limits of detection (LODs) were based on a signal-to-noise ratio of 3:1 also as previously reported. Polychlorinated biphenyl (PCBs) congeners (CBs 99, 187, 183, 180, 170, 153, 128, 118, and 105), organic pes- ticides (cis-Nonachlor, Dichlorodiphenyltrichloroethane [p,p’-DDT], Dichlorodiphenyldichloroethylene [p,p’-DDE], Hexachlorobenzene [HCB], Mirex, oxy-chlordane, trans-Nonachlor) were all assessed for their concentrations.
Whole blood samples were drawn from participants to measure concentrations of a selection of elements (Lead [Pb], total mercury [Hg], cadmium [Cd], and selenium [Se]) and were kept frozen until analyzed at the Institut National de Santé Publique du Québec (INSPQ) Human Toxicology Laboratory using inductively cou- pled plasma mass spectrometry (ICP–MS) as detailed in Nieboer et al.21. All limits of detection (LODs) and the analytical methods are also described therein.
Contaminants that were detected in less than 10% of the total participants were excluded from analyses. Several methods exist for imputing missing values, however, the most common methods used for imputing sam- ples with limits below the detection limit are using half the detection limit or one over the square root of two multiplied by the detection limit22. Non-detections for all individuals’ contaminant body burdens were imputed as half the detection limit as is recommended by the United States Environmental Protection Agency23. Due to year-to-year analytical detection limit variation (i.e., lower detection limits due to better technology and stand- ards), we utilized the highest detection limit through all years to prevent false differences owing the improvement of the limit of detection overtime, and hence community.
outcome assessment. Health information was initially obtained through interviewer-administered ques- tionnaires. Medical chart reviews were conducted for each consenting participant to confirm and gain additional health information (i.e., medication use and medical history). All participants who were diagnosed with type 2 diabetes were confirmed through medical chart review.
Risk factor covariates. Covariate measures were ascertained through either self-report, by interviewer administered health questionnaires, or via direct physical examination, which included a blood draw. Detailed aspects of each are provided in Nieboer et al.19. Age was categorized into the following groups: 20–39, 40–59, and ≥60 years. Educational attainment was self-reported and defined according to the following groups: com- pleted less than high school, high school, and some or more college. The survey questionnaire collected infor- mation on smoking habits, which classified participants as “current, former and never smoker.” Due to the low prevalence of ‘never-smokers” in our analysis smoking status is a composite measure of “current and occasional smokers” compared to “former or non-smokers. Standing height and body weight was measured at the time of the physical examination. Body mass index (BMI) was calculated according to weight in kilograms (kg) divided by height measures (meters squared, m2). Total lipids concentrations were determined using methods described by Rylander et al.24.
Statistical methods. Statistical analysis. Descriptive statistics were calculated for all contaminant con- centrations and covariates, stratified by sex and diagnosis of T2DM. Continuous variables were reported as means ± standard deviations (SD) or geometric means, where appropriate. Categorical data are reported as fre- quencies and percentages. Using SAS PROC GENMOD procedures, we separately estimated adjusted prevalence ratios (PR) using modified Poisson regression with robust error variance25,26. Multivariable models examined the association between T2DM (a non-rare binary outcome) and derived principal components (PCs) adjusted for the following a priori covariates: age, plasma lipid concentrations, BMI, smoking status, and education. Overall, the following covariates were missing among females and males, respectively; education: 1.7% (n = 7) and 2.97% (n = 9); BMI: 1.9% (n = 8) and 5.3% (n = 16) and; smoking status: 1.4% (n = 6) and 2.97% (n = 9). Consequently, numbers of individuals in subsequent regression analyses were reduced slightly depending upon the number of valid observed covariates. Statistical analyses were carried out using SAS v9.4 (SAS Institute, Inc., Cary, NC) and all figures were generated using R (version 3.5.2; Vienna, Austria).
Principal component analysis. Principal component analysis (PCA) was used to transform an initial set of 21 plasma or whole blood contaminant variables (i.e., PCB congeners, organic pesticides, and metals/metalloid) into a reduced number of uncorrelated (i.e., orthogonal) predictor variables by maximizing the variance of the original variables into derived fewer dimensions or principal components (PC)27,28. We used the correlation matrix of con- taminant variables as the input matrix for PCA, and put all original variables on a common scale. Components with eigenvalues exceeding 1.0 were retained and used to define independent summary axes. Therefore, the first
4Scientific RepoRtS | (2019) 9:15909 | https://doi.org/10.1038/s41598-019-52200-x
principal component axes (i.e., PC-1) will account for the largest variance in the data, and any subsequent PCs (i.e., orthogonal to the first) will account for a portion of the variance not accounted for in the preceding compo- nent. The new derived PCs (i.e., scores) are linear combinations of all original variables. Values, or scores, for indi- viduals on these new PC variables are measures of shared exposure to the original contaminant concentrations. Prior to the PCA, contaminant concentrations were log10-transformed (variate + 1), improving normality of the distribution29,30. Separate PCAs were performed for female and male cohorts, owing to differential prevalence of T2DM between sexes and differing levels of exposure for females and males31. Absolute component loadings of 0.50 or greater were identified as important for a given principal component. Thus, signs of loadings are arbi- trary, only the relative magnitude and patterns are meaningful32. Separate-sex principal component (PC) scores summarized new, synthetic measures of contaminant burdens for both males and females. These uncorrelated PC score variables were then used as independent predictors in the regression analysis of T2DM.
Sensitivity analysis. Based on findings from the regression models, we examined the frequency of detection of two variables (i.e., DDT and Pb) by diagnosed T2DM status in contingency analysis. Adjusted Standardized Residuals (ARS) of contaminant levels measured above or below the limit of detection were calculated for T2DM. An association between the frequency of detectability of contaminants, above or below the limit of detection with T2DM status was explored by examining overall chi-square significance and ASRs greater than (|1.96|) in a 2 × 2 contingency table. Complete-case analysis was also performed as a sensitivity check, which found no appreciable difference in results using the same modified Poisson regression models33.
ethics approval and consent to participate. All work conducted was approved by the research eth- ics boards of McGill University and Laval University, in partnership with the Cree Board of Health and Social Services of James Bay and McMaster University. Informed consent was obtained from all participants or their guardians in Cree, English, or French.
Results Descriptive results. Summary statistics of Cree population data for demographic, risk factors variables and contaminants are presented in Table 1. In total, there were 722 participants, 419 females, and 303 males. The prev- alence of T2DM among females and males was 23% (n = 95) and 16.5% (n = 50), respectively.
The mean age among participants with T2DM was 47.9 years and 56.2 years for females and males with diagnosed type 2 diabetes, respectively. Among female respondents, 24.2% self-reported attaining some or more college education whereas among males, 17% had attained some form of college education. Among adults with diabetes, body mass index (BMI) at the time of examination was higher for females (39 kg/m2) than males (34.5 kg/m2). As well, there was a two-fold higher prevalence of self-reported smoking status (i.e., current and occasional compared to former or never) among females with T2DM. The total mean lipid concentrations also differed among females and males among adults with diagnosed T2DM, 6.4 g/L and 5.9 g/L, respectively.
Contaminant principal component analysis (PCA) loadings. Sex-stratified contaminant PC loadings are shown in Fig. 2. Among females, eigenvalues greater than 1 were found for the first two components. PC-1 explained 73% of the total variance in the original log transformed concentrations, which for increasing PCA scores, resulted in high positive loadings for PCBs, organochlorines, and Hg. On the second axis, PC-2 accounted for 5% of the variation, showing that DDT had a negative loading relative to the positive loading of Pb on PC-2 among females. However, for decreasing PCA scores, DDT loadings are interpreted as positive relative to Pb, which is interpreted as having negative loadings.
Among males, contaminant PCA revealed three orthogonal axes, which explained 72%, 6%, and 5%, of the variation for PC-1, PC-2, and PC-3, respectively. Similar to females, PC-1 was highly positively loaded by PCBs, most organochlorines, and Hg. DDT had a strong negative loading, but high positive loading for lead Pb, and a moderate loading for Hg for the second PC axis. Lastly, cadmium and selenium loaded positively on the third PC axis for males.
PCA biplot of orthogonal PC axes overlaid with T2DM status among Indigenous Cree adults in the Eeyou Istchee territory (Fig. 3).
Main effects of the association between PCA scores and type 2 diabetes. Multivariable modified Poisson regression analyses are presented in Tables 2 and 3, which investigates the relationship between prevalent T2DM and the extracted orthogonal principal components of contaminant exposure, for both adult females and males, respectively. Among adult females, the prevalence ratio for PC-2 (but not for PC-1), was significantly associ- ated with T2DM across all adjusted models. After fully adjusting for covariates, the final model for females shows, PC-2 (PR = 0.84; 95% CI: 0.72, 0.97) was significantly associated with T2DM. For increasing PC-2 scores, DDT neg- atively loaded, and Pb was positively loaded, on the second axes. Therefore, as PC-2 axis scores increase (i.e., DDT loadings decreases and Pb loadings increases), resulting in a PR significantly less than 1. Conversely, as PC-2 axis score decreases (i.e., DDT loadings increase and Pb loadings decrease), PC-2 is significantly associated with preva- lent T2DM (PR = 1.19; 1.03, 1.38) among females. Similarly, among adult males, PC-2 (explaining 5% of variation) also was significantly associated with prevalent T2DM across all adjusted models. PC-2 was shown to have a strong positive and negative loading for Pb and DDT, respectively. In the fully adjusted
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