Journal of Aging Research thirteen variables, ten were used to predict participation. Health condition limitation, illness or injury were used only to identify the current sample, and “other” was not included as it was not possible to draw a conclusion about illness, or injury from this response. The total number of barriers was derived (range: 0–8 barriers; mean = 1.06 ± 0.72 barriers; median = 1.00) from the number of barriers each participant responded “yes” to. 2.3.3. Self-Reported Health Status. Respondents were asked “In general, would you say your health is” excellent, very good, good, fair, poor. This categorical variable was recoded such that excellent and very good were collapsed together, and fair and poor were collapsed together leaving three levels of self-reported health status. 2.3.4. Chronic Health Conditions. The CCHS-HA included a number of self-reported chronic condition variables that were coded categorically. The following seven were used in the current study: (1) vision function—this variable was derived from ﬁve items based on the respondent’s ability and/or inability to see well enough to read newsprint and be able and/or unable to recognize a friend on the other side of the street, with and/or without glasses or contact lenses. This resulted in three vision categories: no vision problems, problems corrected by lenses, and problems not corrected by lenses. No vision problems and corrected vision were collapsed together resulting in the two categories of no vision problems and vision problems; (2) heart disease—if the respondents reported having either angina or a heart attack, they were considered to have heart disease; (3) chronic obstructive pulmonary disease (COPD)—if the respondent reported having been diagnosed with chronic bronchitis, emphysema, or COPD, which yielded a broad category used to describe limitations in lung airﬂow; (4) diabetes; (5) osteoporosis; (6) living with the eﬀects of a stroke—this was used to reﬂect neurological damage; (7) mobility trouble— this variable was derived from ﬁve items based on the respon- dent’s ability to walk a short distance and/or around their neighborhood, with and/or without the assistance of another person and/or walking equipment and/or a wheelchair. This resulted in four mobility categories: no mobility prob- lems, mobility problems—no assistance required; mobility problems—requires wheelchair; mobility problems—requir- es help/cannot walk. The mobility problems were collapsed together resulting in two mobility categories. 2.4. Data Analyses. Logistic regression techniques were used to examine the relationships between nonparticipation and barriers to participation, self-reported health status, and the seven chronic health conditions. Data were analyzed separately for male and female respondents. Odds ratios and 95% conﬁdence intervals were used to identify the risk of nonparticipation as a function of the predictor variables. Due to the small sample size of nonparticipants (n = 459), results associated with a large range in conﬁdence intervals should be interpreted with caution as they may overestimate the practical signiﬁcance. SPSS 19 was used for all data analyses, with P < 0.05. 3 3. Results Table 1 reveals that a majority of the Canadian seniors in this sample were participants in physical activity over the last 7 days. While a small percentage of the respondents had not been physically active, this is the group of interest. Given that none of these respondents has identiﬁed barriers due to a health condition limitation, illness, or injury, the data show that approximately 10% do not participate in physical activity. Lower participation in the nonparticipants was conﬁrmed through a lower PASE score (139.68) as compared to participants (142.99). Overall, the majority of the respon- dents report excellent/very good health, and a large majority do not suﬀer from the identiﬁed health conditions. As can been seen in Table 2, approximately 89% of par- ticipants, regardless of participation level, did not identify a barrier. When the barriers were used to predict nonpar- ticipation, the results of the logistic regressions suggested that older males and females have diﬀerent barriers to participation (see Table 3). Males were more likely to be non- participants as a function of the availability of the activity (OR = 4.50, CI = 1.09, 18.68), while females were more likely to be a nonparticipants due to a lack of time (OR = 1.45, CI = 1.09, 1.92). Nonparticipation was not related to a lack of motivation in males (OR = 0.69, CI = 0.48, 0.98) and was not related to a lack of energy in females (OR = 0.54, CI = 0.39, 0.76). Overall, the data suggest that barriers do not appear to be responsible for the nonparticipation of Canadian seniors. Given that barriers were not strong predictors of non- participation, we examined the inﬂuence of self-reported general health status. As seen in Table 1, the distribution of respondents across the three levels of health did vary between participants and nonparticipants. Participants more frequently reported their health as being excellent/very good (61.2% versus 49.2%), and fewer participants reported their health as fair/poor (9.1% versus 13.5%). While these dif- ferences in frequency existed, for both males and females there was no relationship between self-reported health status and nonparticipation in physical and leisure activities (see Table 4). With regards to chronic health conditions, males and females identiﬁed a diﬀerent number of predictors to non- participation (see Table 5). For males, who identiﬁed three predictors, the greatest likelihood of nonparticipation was predicted by vision function (OR = 3.06, CI = 1.30, 7.21), followed by mobility troubles (OR = 2.65, CI = 1.01, 6.95), and diabetes (OR = 1.66, CI = 1.12, 2.44). Women identiﬁed four signiﬁcant predictors of nonparticipation; mobility troubles (OR = 2.71, CI = 1.70, 4.31), COPD (OR = 2.11, CI = 1.34, 3.32), diabetes (OR = 1.85, CI = 1.30, 2.63), and heart disease (OR = 1.54, CI = 1.19, 1.99). 4. Discussion The purpose of this study was to examine the relationship between barriers to participation, self-reported health sta- tus, and chronic health conditions on nonparticipation in physical activity in Canadian seniors aged 60+ years who did not identify a health condition limitation, illness, or injury