Acknowledgments. This research was funded by the European Union’s research and innovation
program H2020 and is documented in grant No 727816. In particular, PULSE was funded under
the call H2020-EU-3.1.5 in the topic SCI-PM-18-2016 - Big Data Supporting Public Health
Policies.
More information on: www.project-pulse.eu.
References
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for Smart sustainable cities: what indicators and standards to use and when? Cities 89, 141–
153 (2019)
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2940 (2019)
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determinants of health. Final report of the Commission on Social Determinants of Health,
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policy, and community. PLoS Med. 9(8), 1–6 (2012)
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the special issue. Work Aging Retire. 4(1), 1–9 (2018)
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336 (2016)
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diabetes mellitus: do we need the oral glucose tolerance test? Ann. Intern Med. 136(8), 575–
581 (2002)
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systems for predicting incident diabetes mellitus in U.S. adults aged 45 to 64 years. Ann.
Intern Med. 150(11), 741–751 (2009)
12. Di Camillo, B., et al.: HAPT2D: high accuracy of prediction of T2D with a model combining
basic and advanced data depending on availability. Eur. J. Endocrinol. 178(4), 331–341
(2018)
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Britain (2004)
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program H2020 and is documented in grant No 727816. In particular, PULSE was funded under
the call H2020-EU-3.1.5 in the topic SCI-PM-18-2016 - Big Data Supporting Public Health
Policies.
More information on: www.project-pulse.eu.
References
1. EEA (European Environment Agency): Air Quality in Europe 2019 EEA Report No
10/2019, Copenhagen (2019)
2. Aapo, H., Peter Bosch, P., Airaksinen, M.: Comparative analysis of standardized indicators
for Smart sustainable cities: what indicators and standards to use and when? Cities 89, 141–
153 (2019)
3. Ottaviano, M., et al.: Empowering citizens through perceptual sensing of urban environmental and health data following a participative citizen science approach. Sensors 19(13),
2940 (2019)
4. World Health Organization - UN HABITAT: Global report on urban health. Geneva (2016)
5. WHO: Closing the gap in a generation: health equity through action on the social
determinants of health. Final report of the Commission on Social Determinants of Health,
Geneva (2008)
6. Corburn, J., Cohen, A.K.: Why we need urban health equity indicators: integrating science,
policy, and community. PLoS Med. 9(8), 1–6 (2012)
7. Toma, A., Hamer, M., Shankar, A.: Associations between neighborhood perceptions and
mental well-being among older adults. Health Place 34, 46–53 (2015)
8. Fisher, G.G., Lindsay, H.R.: Overview of the health and retirement study and introduction to
the special issue. Work Aging Retire. 4(1), 1–9 (2018)
9. Jenny, N.S., et al.: Biomarkers of key biological pathways in CVD. Global Heart 11(3), 327–
336 (2016)
10. Stern, M.P., Williams, K., Haffner, S.M.: Identification of persons at high risk for type 2
diabetes mellitus: do we need the oral glucose tolerance test? Ann. Intern Med. 136(8), 575–
581 (2002)
11. Kahn, H.S., Cheng, Y.J., Thompson, T.J., Imperatore, G., Gregg, E.W.: Two risk-scoring
systems for predicting incident diabetes mellitus in U.S. adults aged 45 to 64 years. Ann.
Intern Med. 150(11), 741–751 (2009)
12. Di Camillo, B., et al.: HAPT2D: high accuracy of prediction of T2D with a model combining
basic and advanced data depending on availability. Eur. J. Endocrinol. 178(4), 331–341
(2018)
13. Waller, L.A., Gotway, C.A.: Applied Spatial Statistics for Public Health Data. Wiley, Great
Britain (2004)
14. Esnaola, S., Montoya, I., Calvo, M., Aldasoro, E., Audícana, C., Ruiz, R., et al.: Atlas de
mortalidad en áreas pequeñas de la CAPV (1996–2003). Donostia-San Sebastián. Servicio
Central de Publicaciones del Gobierno Vasco (2010)
430
D. Vito et al.
