BackgroundIt is unclear whether weighted or unweighted regression is preferred in the analysis of data derived from respondent driven sampling. Our objective was to evaluate the validity of various regression models, with and without weights and with various controls for clustering in the estimation of the risk of group membership from data collected using respondent-driven sampling (RDS).MethodsTwelve networked populations, with varying levels of homophily and prevalence, based on a known distribution of a continuous predictor were simulated using 1000 RDS samples from each population. Weighted and unweighted binomial and Poisson general linear models, with and without various clustering controls and standard error adjustments were modelled for each sample and evaluated with respect to validity, bias and coverage rate. Population prevalence was also estimated.ResultsIn the regression analysis, the unweighted log-link (Poisson) models maintained the nominal type-I error rate across all populations. Bias was substantial and type-I error rates unacceptably high for weighted binomial regression. Coverage rates for the estimation of prevalence were highest using RDS-weighted logistic regression, except at low prevalence (10%) where unweighted models are recommended.ConclusionsCaution is warranted when undertaking regression analysis of RDS data. Even when reported degree is accurate, low reported degree can unduly influence regression estimates. Unweighted Poisson regression is therefore recommended.

First Nations adults living in Hamilton experience a disproportionate burden of mental health and addictions. By working in partnership with urban Aboriginal organizations, it is possible to produce policy- and service-relevant data and address the current deficiency in appropriate mental health and substance use services for urban Aboriginal people.

ObjectiveThis study explores the relationship between health access barriers and diabetes in an urban First Nations population in Canada.DesignData from a self-identified urban First Nations population were collected using respondent-driven sampling (RDS). As no clear approach for regression modelling of RDS data is available, two logistic regression modelling approaches, including survey-based logistic and generalised linear mixed models, were used to explore the relationship between diabetes and health barriers of interest, including access to healthcare, food, housing and socioeconomic factors.SettingHamilton, Ontario, Canada.ParticipantsThis cross-sectional study used data collected from the Our Health Counts study, in partnership with the De dwa da dehs nye>s Aboriginal Health Centre, which recruited 554 First Nations adults living in Hamilton using RDS.ResultsAfter adjusting for covariates, multivariable regression techniques showed a statistically significant relationship between a self-reported diagnosis of diabetes and a lack of culturally appropriate care among urban First Nations peoples (OR: 12.70, 95% CI 2.52 to 57.91). There was also a trend towards a relationship between diabetes and not having a doctor available in the area, feeling that healthcare provided was inadequate and a lack of available healthcare services in the area.ConclusionsUrban First Nations peoples who felt the health service they received was not culturally appropriate were more likely to have diabetes, compared with those who did not feel the service they received was culturally inappropriate. Establishing more healthcare services that integrate First Nations cultures and traditions could improve access to care and the course of treatment for urban First Nations peoples living with diabetes.

ContextCardiovascular diseases (CVD) are a leading cause of illness and death for Indigenous people in Canada and globally. Appropriate medication can significantly improve health outcomes for persons diagnosed with CVD or for those at high risk of CVD. Poor health literacy has been identified as a major barrier that interferes with client understanding and taking of CVD medication. Strengthening health literacy within health services is particularly relevant in Indigenous contexts, where there are systemic barriers to accessing literacy skills.ObjectiveThe aim of this study is to test the effect of a customized, structured health literacy educational program addressing CVD medications.MethodsPre-post-design involves health providers and Indigenous clients at the De dwa da dehs nye>s Aboriginal Health Centre (DAHC) in Ontario, Canada. Forty-seven Indigenous clients with or at high risk of CVD received three educational sessions delivered by a trained Indigenous nurse over a 4- to 7-week period. A tablet application, pill card and booklet supported the sessions. Primary outcomes were knowledge of CVD medications and health literacy practices, which were assessed before and after the programe.ResultsFollowing the program compared to before, mean medication knowledge scores were 3.3 to 6.1 times higher for the four included CVD medications. Participants were also more likely to refer to the customized pill card and booklet for information and answer questions from others regarding CVD.ConclusionsThis customized education program was highly effective in increasing medication knowledge and health literacy practice among Indigenous people with CVD or at risk of CVD attending the program at an urban Indigenous health centre.

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