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Background Studies of neighbourhood walkability and body mass index (BMI) have shown mixed results, possibly due to biases from self-reported outcomes or differential effects across age groups. Our objective was to examine relationships between walkability and objectively measured BMI in various age groups, in a nationally representative population. Methods The study population came from the 2007-2011 Canadian Health Measures Survey, a cross-sectional survey of a nationally representative Canadian population. In our covariate-adjusted analyses, we included survey respondents aged 6-79 who were not pregnant, did not live in rural areas, were not missing data and were not thin/underweight. We used objectively measured height and weight to calculate BMI among adults aged 18-79 and zBMI among children aged 6-17. We categorised respondents into walkability quintiles based on their residential Street Smart Walk Score values. We performed linear regression to estimate differences between walkability quintiles in BMI and zBMI. We analysed adults and children overall; age subgroups 6-11, 12-17, 18-29, 30-44, 45-64 and 65-79; and sex subgroups. Results The covariate-adjusted models included 9265 respondents overall. After adjustment, differences between walkability quintiles in BMI and zBMI were small and not statistically significant, except for males aged 6-17 in the second-highest walkability quintile who had significantly lower zBMIs than those in the lowest quintile. Conclusion After accounting for confounding factors, we did not find evidence of a relationship between walkability and BMI in children or adults overall, or in any age subgroup with sexes combined. However, post hoc analysis by sex suggested males aged 6-17 in more walkable areas may have lower zBMIs. Strengths and limitations of this study * This study uses objective measures of walkability and BMI to examine how the relationship between walkability and BMI differs between different age groups. * This study analyses a large nationally representative Canadian population sample, which allows for stratification by age and adjustment for numerous sociodemographic variables. * Differences between study participants in variables such as caloric intake, amount of time spent in neighbourhood of residence and preference for living in a more walkable neighbourhood were not accounted for. * Residents of rural areas and individuals aged younger than 6 years or older than 79 years are not included in the study, so results may not be generalisable to these populations.