McDougall Hanley Quilliam 2022

• Paste quoted text from the Methods section of the article on the next line. Do not include quotation marks or a bullet mark:

Given the count nature of the dependent variable (WHO-5), associations between mental well-being and freshwater blue space proximity and exposure were analysed using negative binomial regressions. Overdispersion was observed in the data and Poisson regression was, therefore, unsuitable (Hilbe, 2011).

• Write your translation on the next line:

In this paper, one outcome being measured was a non-zero whole number score ranking the mental well-being of study participants, assessed via the World Health Organization 5 Well Being Index. The researchers analysed the association between mental well-being and the distance to the closest freshwater blue space, as well as the length of time spent visiting that blue space. Negative binomial regression was a more suitable analysis technique for this data set rather than the Poisson regression, since the mental well-being scores of participants were highly variable.

• Paste quoted text from the Introduction of the article on the next line. Do not include quotation marks:

Self-reported accounts of blue space exposure, such as recalled visit frequency or contact time, offer an opportunity to quantify an individual’s exposure to different freshwater blue space types in a way which captures the heterogeneity of individual exposure. Self-

reported accounts of exposure are, therefore, well-suited to addressing a number of the aforementioned knowledge gaps in current freshwater blue space and health research.

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Including self-reports on how often and how long the individuals being surveyed visit the freshwater blue spaces in their proximity allows the researchers to more accurately quantify each individual’s exposure, accounting for differences rather than assuming all individuals with the same proximity to a freshwater blue space have the same exposure to the space. This additional information will help in addressing some of the existing knowledge gaps this paper intends to answer.

• Paste quoted text from the Results section in the article on the next line. Do not include quotation marks:

The contact time models displayed broadly similar results to those focusing on associations between visit frequency and both health outcomes.

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Models that observed the association between the length time spent at the freshwater blue space and mental well-being/general health had generally similar results to models that focused on the association between the frequency of visiting the freshwater blue space and mental well-being/general health.

• Paste quoted text from the Discussion section of the article on the next line. Do not include quotation marks:

Although our data suggests frequently visiting rivers is associated with greater mental well-being, unlike canals and the sea, this relationship was not observed when contact time in the last month was considered. Whilst identifying dose–response relationships is beyond the scope of this research, our findings tentatively indicate different dose–response relationships among blue space types (Shanahan et al., 2015).

• Write your translation on the next line:

The data suggests that frequently visiting rivers is associated with great mental well-being but spending longer periods of time when visiting rivers is not associated with greater mental well-being. Spending longer periods of time visiting canals and the sea, however, was associated with greater mental well-being. Although it is beyond the focus of this research, this indicates that the amount of time spent at different freshwater spaces may have varying impacts on mental well-being.

Future research should specifically explore the details of what features maximize the positive impact of freshwater blue spaces on mental well-being and general health – for example, investigate the optimal size of the space and specify the presence of surrounding infrastructure such as walkways, bike paths, or parks. This will enable future urban planners to design/optimize new or existing freshwater blue space in a way that is most beneficial to the health of the population in collaboration with public health policy.

I found it most challenging to understand how the negative binomial regression models were derived, and how the individual and area-level covariates were factored into these models. Background information from someone with more in-depth statistics knowledge would be helpful here!