Background
Aboriginal peoples in Canada (First Nations, Inuit and Metis) are experiencing an epidemic of type 2 diabetes (T2DM) [1, 2]. Compared to their non-Aboriginal counterparts, First Nations people not only have higher rates of diabetes [2] but are also more likely to develop diabetes if female [2], as younger adults [2], and during childhood and adolescence [3]. Thus, while average life span is shorter among diabetic First Nations people [4] compared to non-First Nations people, the years lived with diabetes is typically longer [4]. This prolonged exposure to the metabolic consequences of diabetes contributes to a greater risk for chronic complications such as diabetic kidney disease [5, 6], particularly when combined with reduced access to and quality of diabetes care [7, 8]. Understanding the mechanisms underlying these ethnicity-based differences is therefore important in developing effective primary and secondary prevention initiatives and in providing optimal management of diabetes and its complications.
While genetic factors contribute to the risk for T2DM [9], they cannot explain the rapid world-wide emergence of diabetes over the past few decades in diverse populations that include many Indigenous groups [10]. Instead, this pandemic has paralleled recent changes in environmental and possibly epigenetic factors [11] – these have been attributed to unprecedented disruptions in traditional lifestyles that have occurred in virtually all human populations, particularly since the middle of the past century [12]. Most attention has focused on the role of changing diets (e.g. higher consumption of simple carbohydrates and calorie dense foods) and reduced physical activity that have led to a parallel pandemic of overweight/obesity [13]. Indeed, overweight/obesity is an important diabetes risk factor among First Nations people which is compounded by a higher proportion with elevated body mass index (BMI) [14]. There is also mounting evidence that increasing rates of childhood obesity and T2DM are partly driven by an increased incidence of diabetic pregnancies among First Nations women – not only women with gestational diabetes [15] but also their children [16] have a higher risk for T2DM.
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In addition to changes in lifestyle, it has become apparent that inequities in the social determinants of health (e.g. poverty, sub-standard housing, low educational attainment, poor food availability, unemployment) [17] are also important predictors of chronic diseases including diabetes [18], and are widespread in Aboriginal communities [19]. These factors are increasingly attributed to the impact of colonization that has severely undermined Indigenous culture and access to resources necessary to improve socio-economic status [20, 21]. In particular, discrimination has been identified as a potent social stressor that may increase vulnerability to physical illness through physiological, psychological and behavioral pathways [22]. The main purpose of this study was to determine if residential school attendance, indicators of cultural disruption and perceptions of discrimination were individual-level predictors of diabetes among adults in two First Nations communities in Canada after adjusting for other recognized diabetes risk factors.
Methods
This was a cross-sectional survey that examined the prevalence, co-morbidities and both widely recognized and unique predictors of diabetes mellitus among First Nations adults living in two Cree First Nations communities in central Saskatchewan in 2012 and 2013. The study was conducted as part of the First Nations Lung Health Project (FNLHP) that used a community-based participatory research approach. The methodology for the overall study has been described in detail elsewhere [23], but its main features and the specific elements of this research are also summarized here.
The overall project was initially developed through two years of dialogue and ten consultation sessions with community leaders, health workers and community members. Thereafter, a Decision Makers Council consisting of band councilors, elders and youth was formed to oversee the FNLHP. We received letters of agreement from the two communities that included a commitment to follow the Canadian Institutes for Health Research (CIHR) guidelines for conducting research in Aboriginal communities. Regular updates with community representatives are ongoing and all findings are shared with community leaders with agreement to go forward. We have conducted 8 focus groups with communities to share findings and have had 2 national meetings on housing and health led by community leaders. Before conducting the survey, the Biomedical Research Ethics Board of the University of Saskatchewan approved the study (Certificate No. Bio #12-89) and written consent was obtained from all participants.
In developing the baseline questionnaires, feedback was first obtained from community advisors (Elders and health services directors/staff) of both participating communities. Advisors also provided input about the best approaches for contacting participants and for collecting questionnaire and clinical assessment data. A pilot study was conducted to optimize the content and administration of the baseline questionnaires. Based on the pilot project responses, several questions were modified in the final survey. In both First Nations communities, the baseline assessment consisted of two stages carried out by trained community research assistants. The first stage involved door-to-door canvassing to advertise the survey by distributing brochures and explaining the need and purpose of the study. For the second stage, every adult (18 years and older) was invited to visit the community health care center to complete interviewer-administered questionnaires and to participate in clinical assessments [23] (height, weight, waist circumference, blood pressure, pulmonary function and allergy skin prick tests). Finally, an identification number was assigned to each household using the community map, and a key informant from each household was asked to provide household level information. The sampling frame and sample size calculations can be found in our Methods paper [23].
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Primary health outcome
The questionnaires were primarily designed to obtain information on the individual and contextual determinants of respiratory health, but also included questions pertaining to general health and other health conditions. Accordingly, the outcome of interest for this study was self-reported physician-diagnosed diabetes mellitus. We did not attempt to distinguish between type 1 and type 2 diabetes.
Contextual factors
The contextual factors of interest in this sub-study study were: housing environment, socioeconomic status, household income, and factors that can be attributed to colonization [20, 21]. This was approached by asking questions about knowledge of Indigenous language (Cree), participation in traditional cultural activities, scoring of community strengths (scale 1–12), residential school experience [24] (either personally or by family members), and perceptions of discrimination. The latter variable was created by summing the affirmative responses to 11 situations modified from the 9 item scale published by Krieger [25‐27] (Have you ever experienced discrimination or racism, been prevented from doing something, or been hassled or made to feel inferior in any of the following situations because of your race, cultural group or color: at school; getting hired or getting a job; at work; getting housing; getting medical care; getting medicine at pharmacies; getting service in a store or restaurant; getting credit, bank loans or mortgage; on the street or public setting; from the police or the courts; getting a check cashed). Affirmative responses were divided into three categories of perceived discrimination: low (0–3), moderate (4–7), high (8–11). These differed from Krieger’s cut-offs (0, 1 or 2, 3–9 respectively) because of the additional 2 items (getting medicine at pharmacies; getting a check cashed) and to more clearly identify those experiencing the most discrimination.
Following an extensive review of existing measures of discrimination, we chose the Krieger scale because of its established psychometric properties and its brevity compared to similar scales. Although extensive validation procedures were not conducted (as we did not have the data to do so), pilot testing of the instrument indicated that the scale items resonated with community members. Furthermore, to further enhance the content validity of the scale, two items were added based on community feedback (see above). We were also able to determine that the scale had high internal consistency in our sample (Cronbach alpha = .87), an important component when assessing the validity of a scale. Nonetheless, additional research is needed to further examine its’ validity and reliability in relation to the experiences of Indigenous people in a Canadian context.
Individual factors
The individual factors considered were: lifestyle or behavior-related factors (smoking, alcohol use, body mass index (BMI); waist circumference, and physical activity); and individual educational attainment.
Covariates
Information was obtained on important covariates such as age, sex and marital status. There were also questions pertaining to perceptions of general health as well as selected co-morbid conditions including depression, hypertension, macro-vascular disease (heart disease, stroke, leg ulcers, amputation), micro-vascular disease (eye sight problems and kidney disease), tuberculosis, cancer and several indicators of chronic lung disease.
Statistical analysis
Statistical analyses were conducted using SPSS version 22 (SPSS Inc. Armonk, NY: IBM Corp.). For baseline survey data, frequencies were computed for all variables. Both crude and age specific diabetes prevalence were presented as observed/total and percentage. Chi-square tests were used to determine the univariate association of diabetes prevalence with the independent variables of interest. Logistic regression models were used to predict the relationship between a binary diagnosis of diabetes (yes or no) and a set of explanatory variables. A multilevel logistic regression modeling approach based on a generalized estimating equations, with individuals (1st level) nested within households (2nd level), was utilized to evaluate the effects of both contextual and individual factors after adjustment for covariates of interest. This accounts for the within subject dependencies that occur in the analysis due to multiple people from the same household. A series of multi-level models were fitted to determine whether potential risk factors, confounders, and interactive effects (e.g. individual and contextual risk factors) contributed significantly to the prevalence of diabetes. Based on bi-variable analysis, variables with p < 0.20 were candidates for the multivariate model. All variables that were statistically significant (p < 0.05) as well as important contextual factors (discrimination), were retained in the final multivariable model. Interactions between potential effect modifiers were examined and were retained in the final model if the p-value was <0.05. The predicted probability graphs were prepared for significant interactions. A parsimonious model was selected based on QIC (Quasi likelihood under the Independence model Criteria) goodness-of-fit statistic [28, 29]. The strengths of associations were presented by odds ratios (OR) and their 95 % confidence intervals (CI).
Results
Of the 1570 eligible adults (18 years of age and older) and 580 eligible households in the two First Nations communities, 874 (55.7 %) individuals living in 406 (70 %) households participated in the survey (Table 1). Of those, 443 (51 %) were female and 431 (49 %) were male; their mean age was 35 years (range 18–85 plus 1 person aged 17). There were 112 people with diabetes (42 males and 70 females). The overall crude diabetes prevalence was 12.8 % with a higher proportion of affected females than males (15.8 % versus 9.7 %). The age-specific prevalence ranged from 3.6 % in those under 30 years of age to 32.6 % among those 50 and older.
Table 1
Study population characteristics – adults 18 and oldera
Parameters | Number | Percent |
|---|---|---|
Eligible Households | 580 | - |
Participating Households | 406 | 70 |
Eligible Adults | 1570 | - |
Participating Adults (total) | 874 | 55.7 |
Men | 431 | 49.3 |
Women | 443 | 50.7 |
Total self-reported diabetes | 112 | 12.8 |
Men | 42 | 9.7 |
Women | 70 | 15.8 |
Diabetes by Age Group (Total) | ||
50 and older | 56 (172) | 32.6 |
40–49 | 23 (135) | 17.0 |
30–39 | 19 (175) | 10.9 |
Under 30 | 14 (392) | 3.6 |
Table 2 shows the univariate relationships between key variables and diabetes. Those with diabetes were more likely to be female, older, divorced/separated/widowed, and to be retired/homemaker/disabled. Single people and those who were either employed or students were less likely to have diabetes. In this study, lower educational attainment and reduced household income were not predictors of diabetes although the prevalence was significantly higher among people living in houses requiring major repairs. First Nations people who were overweight, obese or had an increased abdominal girth were respectively 5.9, 14.5 and 8.5 times more likely to have diabetes than those with normal adiposity. Regular alcohol intake and being a current smoker both significantly reduced diabetes risk in univariate analysis but not after adjusting for other independent variables. There was a trend for exercise to reduce diabetes risk in a dose-dependent manner but this relationship was not statistically significant.
Table 2
Univariate associations between diabetes and individual characteristics
Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) | Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) |
|---|---|---|---|---|---|
Sex | Life Style | ||||
Female | 15.8 | 1.73 (1.16, 2.58) | Body Mass Index | ||
Male | 9.7 | 1.00 (ref) | Obese | 23.8 | 14.5 (6.09, 34.61) |
Overweight | 11.2 | 5.86 (2.40, 14.35) | |||
Age | Normal | 2.1 | 1.00 (ref) | ||
50+ years | 32.6 | 13.5 (7.27, 24.98) | |||
40-49 years | 17.0 | 5.63 (2.79, 11.35) | Abdominal Girtha
| ||
30-39 years | 10.9 | 3.39 (1.69, 6.78) | High risk | 19.2 | 8.50 (4.06, 17.79) |
17-29 years | 3.6 | 1.00 (ref) | Not available | 16.1 | 5.73 (2.35, 13.97) |
Low risk | 2.7 | 1.00 (ref) | |||
Marital Status | |||||
Single | 8.4 | 0.47 (0.31, 0.74) | Smoking Status | ||
Divorced/separated/widowed | 29.8 | 2.19 (1.21, 3.94) | Current smoker | 10.9 | 0.53 (0.30, 0.95) |
Married/common law | 16.3 | 1.00 (ref) | Ex-smoker | 20.2 | 1.10 (0.56, 2.15) |
Never Smoker | 18.6 | 1.00 (ref) | |||
Education Attained | |||||
Less than high school | 12.8 | 0.99 (0.66, 1.49) | Alcohol Intakeb
| ||
High school or higher | 12.9 | 1.00 (ref) | Regular | 8.8 | 0.58 (0.35, 0.98) |
Never or not regular | 14.2 | 1.00 (ref) | |||
Household income | |||||
$0- $9,999 | 12.2 | 0.92 (0.55, 1.56) | Exercise | ||
$10,000- $19,999 | 12.6 | 0.96 (0.49, 1.85) | Yes | 11.9 | 0.78 (0.51, 1.19) |
Refused/Not stated | 13.2 | 1.01 (0.60, 1.69) | No | 14.9 | 1.00 (ref) |
$20,000+ | 13.0 | 1.00 (ref) | |||
Duration of Exercise | |||||
Employment Status | 0 - <15 minutes | 15.1 | 1.16 (0.66, 2.05) | ||
Employed (full/part/student) | 9.6 | 1.00 (ref) | 15-30 minutes | 10.8 | 0.79 (0.42, 1.50) |
Retired/homemaker/disabled | 20.2 | 2.38 (1.41, 4.04) | 31-60 minutes | 9.8 | 0.71 (0.36, 1.40) |
Unemployed | 11.6 | 1.23 (0.74, 2.04) | >60 minutes | 13.3 | 1.00 (ref) |
House Environment | Sleep Hours | ||||
Crowding | More than 7 hours | 11.4 | 0.77 (0.43, 1.40) | ||
<1 person/bedroom | 19.5 | 1.87 (1.04, 3.36) | 6-7 hours | 14.0 | 0.99 (0.56, 1.76) |
1 person/bedroom | 15.5 | 1.41 (0.85, 2.34) | 5 hours or less | 14.3 | 1.00 (ref) |
>1 person/bedroom | 11.5 | 1.00 (ref) | |||
House needs repair | |||||
Yes, major repairs | 15.7 | 1.66 (1.00, 2.74) | |||
Yes, minor repairs | 12.5 | 1.28 (0.72, 2.25) | |||
No, only regular maintenance | 10.4 | 1.00 (ref) | |||
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Table 3 shows the relationship between diabetes and factors that can be attributed to colonization. Diabetes prevalence was slightly higher among participants who had attended residential schools than those who had not (13.5 % versus 12.4 %) but the difference was not statistically significant (OR 1.10; 95 % CI 0.74, 1.66). Similarly, having a parent or grandparent who had attended residential school did not significantly predict diabetes among study participants, although the overall number of community members who did not have an inter-generational family exposure to residential schools was <10 %. Additional analyses (not shown) that examined the relationship between diabetes and residential school attendance by sex, age group, micro/macro-vascular complications and community, also revealed no statistically significant relationships. The degree to which people participated in cultural events or perceived community strength were also neither predictive nor protective in their relationship with diabetes. In contrast, those who spoke Cree or lived exclusively in their home communities were significantly more likely to have diabetes than those who spent some time off-reserve. However, ability to speak Cree was not a significant predictor of diabetes after adjusting for other independent variables.
Table 3
Univariate associations between diabetes and factors related to colonization
Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) | Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) |
|---|---|---|---|---|---|
Residential School Attendance | |||||
Study participant? | Take part in cultural events? | ||||
Yes | 13.5 | 1.10 (0.74, 1.66) | Always/almost always | 12.3 | 1.08 (0.45, 2.60) |
No | 12.4 | 1.00 (ref) | Sometimes | 14.3 | 1.29 (0.60, 2.78) |
Rarely | 9.8 | 0.84 (0.34, 2.12) | |||
Parents/grandparents? | Never | 11.4 | 1.00 (ref) | ||
Yes | 12.2 | 0.65 (0.36, 1.19) | |||
Do not know | 13.3 | 0.72 (0.28, 1.85) | Community Strengthb
| ||
No | 17.4 | 1.00 (ref) | Low | 14.2 | 1.28 (0.85, 1.95) |
High | 11.4 | 1.00 (ref) | |||
Experience discriminationa
| |||||
High (8–11) | 2.4 | 0.15 (0.03, 0.65) | Past Year Spent on Reserve | ||
Moderate (4–7) | 15.1 | 1.15 (0.70, 1.87) | All 12 months | 15.5 | 2.46 (1.48, 4.08) |
Little (0–3) | 13.6 | 1.00 (ref) | Less than 12 months | 7.0 | 1.00 (ref) |
Language | |||||
Can speak Cree | 21.2 | 3.65 (2.37, 5.64) | |||
Cannot speak Cree | 6.9 | 1.00 (ref) | |||
Table 3 also shows the association between perceptions of discrimination and diabetes prevalence. Those experiencing the highest level of discrimination had the lowest prevalence of diabetes when compared to those experiencing little discrimination (2.7 % versus 13.6 %; OR 0.15; 95 % CI 0.03, 0.55). Those exposed to a moderate level of discrimination had a slightly higher prevalence of diabetes than the reference group but the difference was not statistically significant.
The univariate associations between diabetes and several important co-morbidities are shown in Table 4. Overall, people with diabetes were 3.6 times more likely to perceive their general health as fair and over 4 times as likely to perceive it as poor compared to those without diabetes. These perceptions paralleled the presence of micro-vascular and macro-vascular disease (ORs 3.63 and 4.25 respectively). People with diabetes were also more likely to report a significant history of cancer, tuberculosis and asthma. Although chronic respiratory diseases and obstructive sleep apnea were more prevalent in people with diabetes, the findings did not achieve statistical significance. Nonetheless, symptoms such as shortness of breath, snoring and abnormal sleepiness were significantly associated with diabetes, as were several tests indicating poorer lung function. Finally, there was a trend for people with diabetes to have higher blood pressures, mental health problems and depression but once again the findings were not statistically significant.
Table 4
Univariate associations between diabetes and co-morbidities
Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) | Parameter | Diabetes Prevalence (%) | Odds Ratio (95 % CI) |
|---|---|---|---|---|---|
Shortness of Breath | Tuberculosis | ||||
Yes | 16.7 | 2.17 (1.40, 3.36) | Yes | 22.0 | 2.08 (1.07, 4.03) |
No | 8.5 | 1.00 (ref) | No | 12.0 | 1.00 (ref) |
Asthma | Sleep Apnea | ||||
Yes | 19.5 | 1.87 (1.17, 2.98) | Yes | 19.4 | 1.73 (0.89, 3.36) |
No | 11.4 | 1.00 (ref) | No | 12.2 | 1.00 (ref) |
General Physical Health | Chronic Respiratory Diseasesc
| ||||
Poor | 22.7 | 4.11 (1.19, 14.26) | Yes | 21.2 | 1.95 (0.96, 3.99) |
Fair | 20.5 | 3.61 (1.28, 10.20) | No | 12.1 | 1.00 (ref) |
Good | 11.3 | 1.78 (0.61, 5.17) | |||
Very good | 7.3 | 1.10 (0.34, 3.54) | Snore | ||
Excellent | 6.7 | 1.00 (ref) | Yes | 15.2 | 1.64 (1.07, 2.53) |
Do not know | 12.3 | 1.28 (0.71, 2.31) | |||
Mental Health | No | 9.9 | 1.00 (ref) | ||
Fair to poor | 18.5 | 1.68 (0.98, 2.89) | |||
Excellent to good | 11.9 | 1.00 (ref) | Snore Volume | ||
Loud to very loud | 21.0 | 2.43 (1.41, 4.19) | |||
Depression | Softer than talking | 10.6 | 1.08 (0.59, 1.98) | ||
Yes | 16.8 | 1.54 (0.95, 2.50) | Do not know | 12.9 | 1.35 (0.81, 2.26) |
No | 11.5 | 1.00 (ref) | Never | 9.9 | 1.00 (ref) |
Macro Vascular Complicationsa
| Epworth Sleepiness Scale | ||||
Yes | 32.1 | 4.25 (2.67, 6.77) | Abnormal | 17.6 | 1.73 (0.99, 3.03) |
No | 10.1 | 1.00 (ref) | Normal | 11.0 | 1.00 (ref) |
Micro Vascular Complicationsb
| Systolic Blood Pressure | ||||
Yes | 29.0 | 3.63 (2.33, 5.66) | High | 15.4 | 1.44 (0.93, 2.22) |
No | 10.1 | 1.00 (ref) | Not Available | 12.7 | 1.16 (0.59, 2.29) |
Low | 11.3 | 1.00 (ref) | |||
Cancer | |||||
Yes | 31.0 | 3.32 (1.49, 7.40) | |||
No | 11.9 | 1.00 (ref) | |||
Lung function measurements | Mean ± SD | Odds Ratio (95 % CI) | |||
FVC | |||||
Diabetes-Yes | 3.8 ± 1.0 | 0.45 (0.34, 0.60) | |||
Diabetes-No | 4.6 ± 1.1 | 1.00 (ref) | |||
FEV1
| |||||
Diabetes-Yes | 3.0 ± 0.8 | 0.38 (0.28, 0.52) | |||
Diabetes-No | 3.8 ± 0.9 | 1.00 (ref) | |||
FEV1/FVC ratio % | |||||
Diabetes-Yes | 80.5 ± 7.4 | 0.97 (0.94, 0.99) | |||
Diabetes-No | 82.7 ± 7.2 | 1.00 (ref) | |||
Tables 5 show results from two models of diabetes risk based on multivariate logistic regression analysis. The first was carried out with and without BMI included in the model; and the second with and without abdominal girth. In both models the results were similar. Increasing age and increasing adiposity (either BMI or high risk abdominal girth) were highly predictive of diabetes when measures of adiposity were included in the model, while female sex was not. In contrast, when BMI and abdominal girth were removed from the model, women were over 50 % more likely to have diabetes than men (OR 1.54; 95 % CI 1.00, 2.38).
Table 5
ORs of diabetes risk based on multivariate logistic regression analysis
Model with BMI | Model without BMI | ||||
|---|---|---|---|---|---|
Parameter | Odds Ratio (95 % CI) |
P value | Parameter | Odds Ratio (95 % CI) |
P value |
Sex | Sex | ||||
Female | 1.21 (0.78, 1.88) | 0.397 | Female | 1.54 (1.00, 2.38) | 0.050 |
Male | 1.00 (ref) | Male | 1.00 (ref) | ||
Age | Age | ||||
50+ years | 8.72 (4.62, 16.46) | <0.0001 | 50+ years | 12.82 (6.94, 23.67) | <0.0001 |
40–49 years | 3.62 (1.78, 7.35) | <0.0001 | 40-49 years | 5.15 (2.58, 10.27) | <0.0001 |
30–39 years | 2.44 (1.19, 4.99) | 0.015 | 30-39 years | 3.28 (1.63, 6.58) | 0.001 |
17–29 years | 1.00 (ref) | 17-29 years | 1.00 (ref) | ||
Body Mass Index | |||||
Obese | 8.97 (3.58, 22.52) | <0.0001 | |||
Overweight | 3.86 (1.51, 9.87) | 0.005 | |||
Normal | 1.00 (ref) | ||||
Past year duration in reserve | Past year duration in reserve | ||||
All 12 months | 1.69 (0.96, 2.97) | 0.068 | All 12 months | 1.83 (1.05, 3.18) | 0.032 |
Less than 12 months | 1.00 (ref) | Less than 12 months | 1.00 (ref) | ||
Ever experienced discrimination | Ever experienced discrimination | ||||
High (8–11) | 0.11 (0.02, 0.54) | 0.007 | High (8–11) | 0.12 (0.03, 0.54) | 0.006 |
Moderate (4–7) | 1.23 (0.70, 2.16) | 0.464 | Moderate (4–7) | 1.24 (0.73, 2.13) | 0.428 |
Little (0–3) | 1.00 (ref) | Little (0–3) | 1.00 (ref) | ||
Model with Abdominal Girth | Model without Abdominal Girth | ||||
Parameter | Odds Ratio (95 % CI) |
P value | Parameter | Odds Ratio (95 % CI) |
P value |
Sex | Sex | ||||
Female | 1.01 (0.64, 1.58) | 0.978 | Female | 1.54 (1.00, 2.38) | 0.050 |
Male | 1.00 (ref) | Male | 1.00 (ref) | ||
Age | Age | ||||
50+ years | 9.87 (5.29, 18.41) | <0.0001 | 50+ years | 12.82 (6.94, 23.67) | <0.0001 |
40–49 years | 4.12 (2.01, 8.46) | <0.0001 | 40-49 years | 5.15 (2.58, 10.27) | <0.0001 |
30–39 years | 2.64 (1.28, 5.46) | 0.009 | 30-39 years | 3.28 (1.63, 6.58) | 0.001 |
17–29 years | 1.00 (ref) | 17-29 years | 1.00 (ref) | ||
Abdominal Girth | |||||
High risk | 5.87 (2.67, 12.92) | <0.0001 | |||
Not available | 4.40 (1.75, 11.07) | 0.002 | |||
Low risk | 1.00 (ref) | ||||
Past year duration in reserve | Past year duration in reserve | ||||
All 12 months | 1.84 (1.05, 3.20) | 0.032 | All 12 months | 1.83 (1.05, 3.18) | 0.032 |
Less than 12 months | 1.00 (ref) | Less than 12 months | 1.00 (ref) | ||
Ever experienced discrimination | Ever experienced discrimination | ||||
High (8–11) | 0.11 (0.02, 0.49) | 0.004 | High (8–11) | 0.12 (0.03, 0.54) | 0.006 |
Moderate (4–7) | 1.11 (0.63, 1.93) | 0.717 | Moderate (4–7) | 1.24 (0.73, 2.13) | 0.428 |
Little (0–3) | 1.00 (ref) | Little (0–3) | 1.00 (ref) | ||
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As in univariate analysis (above), place of habitation continued to be a significant predictor of diabetes in 3 of the 4 multivariate models. Thus, those living on-reserve for all 12 months of the year were more likely to have diabetes than those who spent at least part of the time off-reserve. Finally, those experiencing the highest levels of discrimination experienced a significantly lower risk of diabetes (OR 0.11; 95 % CI 0.02, 0.54) after adjusting for other key variables such as sex, BMI (or waist circumference) and age group. Removal of adiposity measures from the analysis did not affect this finding. However, we additionally looked for possible trends in other variables that might explain the inverse relationship between diabetes and perceptions of discrimination (data not shown). Compared to those with the lowest levels of perceived discrimination, a larger proportion of people with the highest levels of perceived discrimination were employed or students (41 % versus 34.1 %; p = 0.791), married or common-law (53 % versus 37.3 %; p = 0.007), had household incomes > $20,000 (38.6 % versus 23.1 %; p = 0.022), and had attended residential schools (68.7 % versus 35.7 %; p < 0.0001).
Discussion
The prevalence of diabetes among adults in two Saskatchewan First Nations communities was higher than that reported for the province’s non-First Nations population [2], as well as for a predominantly Caucasian sub-group living in rural Saskatchewan during a similar time period [30]. As expected, we found that increasing age and body weight were strong predictors of diabetes in these First Nations communities. We again confirmed the marked predilection of diabetes for First Nations females [2] and have now shown that this is at least partly explained by increased adiposity. With respect to the primary objective of the study, we were unable to show at the individual level that residential school attendance by either study participants or their parents/grandparents significantly increased diabetes risk. The same was true for inability to speak Cree and/or low participation in cultural events. The most unique finding of this study was that those experiencing the highest levels of discrimination at an individual level had the lowest prevalence of diabetes.
As far as we are aware, this is the first study that has examined the relationship between individual-level diabetes risk and factors related to colonization within First Nations communities, while adjusting for a comprehensive set of other important and recognized predictors of diabetes. In addition to female gender, increasing age, higher BMI and elevated waist circumference, known diabetes risk factors include social determinants of health [17, 18] such as poorer income, employment status, education and quality of housing. In our study, better housing and being employed or engaged as a student were associated with lower diabetes prevalence on univariate analysis, but did not remain significant in the final model. Higher household income adequacy and education were not protective for diabetes before or after adjusting for other variables. However, it is possible that we did not sufficiently discriminate between the highest and lowest levels of education and income, and/or that participant numbers in the study did not afford us the statistical power to show a difference. With respect to life style, univariate analysis showed a trend towards lower diabetes prevalence among those who engaged in physical activity, and there were lower rates of diabetes among those who currently smoked or consumed alcohol on a regular basis. In other studies, alcohol intake has been shown to protect against diabetes [31] while smoking is an important diabetes risk factor [32]. Since neither activity remained in the final model in this study, it is possible that our univariate findings were related to higher alcohol intake and smoking rates among younger people who have a much lower prevalence of diabetes.
Results of qualitative research have consistently identified various dimensions of cultural continuity/disruption as important to the health of Indigenous Canadians [33, 34]. However, the results of quantitative research on this topic are mixed. On the one hand, several quantitative studies have demonstrated associations between greater cultural continuity and better mental health outcomes [35, 36]. For example, Chandler and Lalonde have shown that cultural continuity in First Nations communities is protective against youth suicide [37, 38]. In addition, preliminary research conducted as part of the larger study from which our data is drawn, also shows a significant relationship between discriminatory experiences and compromised mental health among First Nations adults [39]. However, a number of other quantitative studies in Canada have reported either no or mixed/contradictory associations between indicators of cultural continuity and health, depending upon the health outcome and particular aspect of culture under study [40‐42]. With respect to metabolic disorders, there is only one study that suggests that cultural continuity may be protective against diabetes for First Nations people [43]. After adjusting for differences in income, employment rates and education in 31 First Nations communities in Alberta, Oster and colleagues recently reported on an ecologic study that showed lower diabetes prevalence in those communities that had a greater retention of Indigenous language.
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In this study, lack of participation in cultural events and low scoring of community strengths was neither predictive nor protective for diabetes on an individual level. People who spoke Cree were over 3 times more likely to have diabetes than others on univariate analysis but this did not remain significant in the final model. It is likely that the univariate finding was due to a larger proportion of older people with a knowledge of Cree, since increasing age is also a strong predictor of diabetes. It should be emphasized that an important difference between this study and that of Oster et al. mentioned above [43], is that we examined the individual-level risk of diabetes by his/her knowledge of Cree. In contrast, Oster et al. examined the relationship between diabetes prevalence and Indigenous language knowledge at the community level. At face value, these findings may appear contradictory. However, had they looked at within-community data (and regardless of a particular community’s prevalence of diabetes), it is quite possible that Oster et al. would have also found a higher proportion of older individuals with diabetes, and it is also quite possible that older diabetic individuals were more likely to speak an Indigenous language than their younger counterparts.
Although study participants who had attended residential school had a slightly higher prevalence of diabetes than those who had not, the finding was not statistically significant. Furthermore, while those whose parents or grandparents had attended residential school trended towards a lower prevalence of diabetes than participants without that family history, the difference was also not significant. Because of the stressful and often traumatic experiences that many residential school survivors report [24], as well as the intra- and inter-generational impact of those experiences [44], we had anticipated that residential school attendees and their offspring might have a higher risk for diabetes. It is known that stress can be diabetogenic through many pathways [22] including endocrine mechanisms [45] and by causing chromosomal damage [46]. However, it is possible that the detrimental impact of residential schools on the health of individuals within First Nations communities is so pervasive that it is difficult to find a truly unexposed comparison group. Furthermore, there are many additional causes of stress within First Nations communities and it may not be possible to readily differentiate between the relative importance of residential school exposure and other stress-producing experiences. Larger study populations and/or comparison with non-First Nations groups truly unexposed to the impact of residential schools should be considered in future research examining this question.
We had also speculated that those experiencing the most discrimination would have a higher prevalence of diabetes, once again because of increased stress. Instead, we found the opposite. The extent to which people perceived discrimination during day-to day experiences was inversely related to diabetes prevalence, and this highly significant finding was present even after adjusting for other important independent variables. What could explain this relationship? It was not because of characteristics most clearly associated with lower diabetes prevalence such as younger age, being male and having normal adiposity. It also seems unlikely that avoidance of the health care system and delay of diabetes diagnosis could explain such a significant finding. Rather, the main thread that appears to connect those within this group is that they were experiencing negative interactions in what were predominantly non-Aboriginal settings. Indeed, our multivariate model results showed that spending time away from the reserve was protective for diabetes. Finally, and consistent with recent research involving Indigenous Australian adults [47, 48], we also observed that people experiencing the most discrimination (and lowest diabetes prevalence) tended to be employed or students, and were significantly more likely to be married and to have higher household incomes. It is therefore possible that experiencing discrimination is a proxy measure for being engaged in and with society off-reserve. That engagement may lead to improvements in the social determinants of health - including higher socio-economic status - and engender physical health benefits, at least with respect to diabetes risk. As discussed above, however, this comes at a high emotional price via increased experiences of interpersonal discrimination [39]. This is perhaps the most important finding of our study and requires further reflection as well as corroboration to fully understand its implications. As with the impact of residential schools, comparison of First Nations with non-First Nations populations, while adjusting for social determinants of health, could clarify the links between discrimination and physical health outcomes like diabetes.
First Nations people with diabetes were more likely than others to experience a number of co-morbidities and to evaluate their general health as fair or poor. Because the primary focus of the main study was on lung health [23], much of the questionnaire pertained to pulmonary conditions, and many significant associations of these with diabetes were present on univariate analysis. While none were significant in initial multivariate models that included co-morbidities (perhaps largely due to age adjustment), it is likely that obstructive sleep apnea is common among First Nations people with diabetes because obesity is an important risk factor for both [49]. Not surprisingly, both macro and micro vascular complications were very common among those with diabetes and these relationships remained highly significant in initial multivariate models that included co-morbidities. Interestingly, women with diabetes were less likely than men to have micro-vascular complications like kidney and eye disease. This is consistent with other research that shows a higher cumulative incidence of end stage renal disease among First Nations men [4].
Strengths of this study included the community-based participatory research model used, the large proportion of eligible adults and households that participated, and our ability to investigate the potential role of both known and unrecognized variables in understanding the disproportionate risk for diabetes experienced by First Nations communities. Accordingly, this is the first study that we are aware of to examine the potential role of factors related to colonization in diabetes risk while at the same time adjusting for a comprehensive set of other known diabetes predictors. Limitations include the cross sectional nature of the study and the associated inability to be confident about cause-effect relationships. To limit the length of the questionnaire, we omitted questions on important predictors of diabetes such as family history. Although the sample size was sufficient for the main study, the relatively small number of people with diabetes in this sub-study may have prevented us from demonstrating some relationships that truly exist, most importantly the impact of residential school attendance on diabetes risk. The discrimination scale that was used reflects racism on a personal level and we were not able to study the impact of other forms of racism [50] on diabetes risk. For example, it is quite possible that some elements of systemic racism experienced by First Nations people might be more clearly associated with diabetes risk. This reinforces the need for more research focusing on quantitative measurements of cultural disruption, residential school impact and racism among Indigenous peoples. Finally, while our sample had an equal gender distribution, it contained a relatively larger proportion of older people compared to the overall Saskatchewan First Nations population [51]. Therefore, we may not be able to generalize our findings to other First Nations communities.
Conclusions
Increased diabetes prevalence in two Saskatchewan First Nations communities was significantly related to known diabetes risk factors including female sex, increasing age and BMI but we were unable to demonstrate in this study that diabetes was associated with residential school exposure, perceptions of community strength or inability to speak Cree. An unanticipated finding was that those experiencing the most discrimination had the lowest prevalence of diabetes. While the reasons underlying this latter finding remain unclear, engagement with society off-reserve may have certain physical health benefits for First Nations people that relate to improved socio-economic status and other undefined influences. However, our findings suggest that better physical health comes at a high emotional price via increased experiences of interpersonal discrimination [39]. While this important observation may apply to other Indigenous peoples in Canada and elsewhere, it requires corroboration in diverse jurisdictions. Additional dialogue with the communities as well as further reflection and in-depth analysis will help to fully understand its implications.
Availability of data and materials
The data used in the analysis is kept in a secure location within the Canadian Center for Health and Safety in Agriculture, University of Saskatchewan. As part of the contractual agreement with the two First Nations communities involved in the study, the data is not publicly available.
Acknowledgements
This study was funded by a grant from the Canadian Institutes of Health Research “Assess, Redress, Re-assess: Addressing Disparities in Respiratory Health among First Nations People”, CIHR MOP-246983-ABH-CCAA-11829. The First Nations Lung Health Project Team consists of: James Dosman, MD (Designated Principal Investigator, University of Saskatchewan, Saskatoon, SK Canada); Dr. Punam Pahwa, PhD (Co-principal Investigator, University of Saskatchewan, Saskatoon SK Canada); Jo-Ann Episkenew, PhD (Co-principal Investigator, Indigenous People’s Health Research Centre, University of Regina, SK Canada), Sylvia Abonyi, PhD (Co-principal Investigator, University of Saskatchewan, Saskatoon, SK Canada); Co-Investigators: Mark Fenton, John Gordon, Bonnie Janzen, Chandima Karunanayake, Malcolm King, Shelly Kirychuk, Niels Koehncke, Joshua Lawson, Greg Marchildon, Lesley McBain, Donna Rennie, Vivian R Ramsden, Ambikaipakan Senthilselvan; Collaborators: Amy Zarzeczny, Louise Hagel, Breann Davis, John Dosman, Roland Dyck, Thomas Smith-Windsor, William Albritton; External Advisor: Janet Smylie; Project Manager: Kathleen McMullin; Community Partners: Jeremy Seeseequasis, P. Jenny Gardipy, Candace Scott, Laurie Jimmy, Laura McCallum, Jarret Nelson. We are grateful for the contributions of community leaders included in the study that facilitated the engagement necessary for the study and to all of the participants who donated their time and expertise to participate in the survey.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
RD conceived of the study, participated in its design and analysis, and drafted the manuscript. CK participated in the design of the study and carried out the statistical analysis. BJ, JL, VRR, DR, and SA are co-investigators on the research grant, helped design the study, and reviewed and revised the manuscript for important intellectual content. JPG and LM provided community input into the design of the study, helped with acquisition of data, and reviewed and revised the manuscript from a community perspective. JD, JAE and PP are co-principal investigators on the research grant, helped design the study, and reviewed and revised the manuscript for important intellectual content. All authors read and approved the final manuscript.