{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T23:02:02Z","timestamp":1791241322263,"version":"4.1.0"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Health Geogr"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The public health burden caused by overweight, obesity (OO) and type-2 diabetes (T2D) is very significant and continues to rise worldwide. The causation of OO and T2D is complex and highly multifactorial rather than a mere energy intake (food) and expenditure (exercise) imbalance. But previous research into food and physical activity (PA) neighbourhood environments has mainly focused on associating body mass index (BMI) with proximity to stores selling fresh fruits and vegetables or fast food restaurants and takeaways, or with neighbourhood walkability factors and access to green spaces or public gym facilities, making largely naive, crude and inconsistent assumptions and conclusions that are far from the spirit of 'precision and accuracy public health'. Different people and population groups respond differently to the same food and PA environments, due to a myriad of unique individual and population group factors (genetic\/epigenetic, metabolic, dietary and lifestyle habits, health literacy profiles, screen viewing times, stress levels, sleep patterns, environmental air and noise pollution levels, etc.) and their complex interplays with each other and with local food and PA settings. Furthermore, the same food store or fast food outlet can often sell or serve both healthy and non-healthy options\/portions, so a simple binary classification into 'good' or 'bad' store\/outlet should be avoided. Moreover, appropriate physical exercise, whilst essential for good health and disease prevention, is not very effective for weight maintenance or loss (especially when solely relied upon), and cannot offset the effects of a bad diet. The research we should be doing in the third decade of the twenty-first century should use a systems thinking approach, helped by recent advances in sensors, big data and related technologies, to investigate and consider all these factors in our quest to design better targeted and more effective public health interventions for OO and T2D control and prevention.<\/jats:p>","DOI":"10.1186\/s12942-021-00266-0","type":"journal-article","created":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T09:06:19Z","timestamp":1614762379000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Smart city lifestyle sensing, big data, geo-analytics and intelligence for smarter public health decision-making in overweight, obesity and type 2 diabetes prevention: the research we should be doing"],"prefix":"10.1186","volume":"20","author":[{"given":"Maged N.","family":"Kamel Boulos","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keumseok","family":"Koh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,3,3]]},"reference":[{"key":"266_CR1","unstructured":"The World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard. https:\/\/covid19.who.int. Accessed 3 Jan 2021."},{"key":"266_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/S2666-5247(20)30226-3","author":"The Lancet Microbe","year":"2020","unstructured":"The Lancet Microbe. COVID-19 vaccines: the pandemic will not end overnight. Lancet Microbe. 2020. https:\/\/doi.org\/10.1016\/S2666-5247(20)30226-3.","journal-title":"Lancet Microbe."},{"key":"266_CR3","unstructured":"The World Health Organization. Non communicable diseases (Fact sheet, 1 June 2018). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/noncommunicable-diseases. Accessed 6 Jan 2021"},{"key":"266_CR4","doi-asserted-by":"publisher","first-page":"845","DOI":"10.2147\/CLEP.S214909","volume":"11","author":"SB Gribsholt","year":"2019","unstructured":"Gribsholt SB, Pedersen L, Richelsen B, Thomsen RW. Validity of ICD-10 diagnoses of overweight and obesity in Danish hospitals. Clin Epidemiol. 2019;11:845\u201354. https:\/\/doi.org\/10.2147\/CLEP.S214909.","journal-title":"Clin Epidemiol"},{"key":"266_CR5","unstructured":"ICD-10 Version:2016. https:\/\/icd.who.int\/browse10\/2016\/en#\/E10. Accessed 6 Jan 2021"},{"key":"266_CR6","doi-asserted-by":"publisher","DOI":"10.1080\/10408398.2020.1775546","author":"RW Alberca","year":"2020","unstructured":"Alberca RW, De Oliveira LM, Branco ACCC, Pereira NZ, Sato MN. Obesity as a risk factor for COVID-19: an overview. Crit Rev Food Sci Nutr. 2020. https:\/\/doi.org\/10.1080\/10408398.2020.1775546.","journal-title":"Crit Rev Food Sci Nutr."},{"issue":"10","key":"266_CR7","doi-asserted-by":"publisher","first-page":"1892","DOI":"10.1111\/dom.14134","volume":"22","author":"P Vas","year":"2020","unstructured":"Vas P, Hopkins D, Feher M, Rubino F, Whyte MB. Diabetes, obesity and COVID-19: a complex interplay. Diabetes Obes Metab. 2020;22(10):1892\u20136. https:\/\/doi.org\/10.1111\/dom.14134.","journal-title":"Diabetes Obes Metab"},{"key":"266_CR8","doi-asserted-by":"publisher","unstructured":"The GBD 2015 Obesity Collaborators. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med. 2017;377(1):13-27. Doi: https:\/\/doi.org\/10.1056\/NEJMoa1614362","DOI":"10.1056\/NEJMoa1614362"},{"key":"266_CR9","unstructured":"International Diabetes Federation. Diabetes facts & figures (2020. https:\/\/www.idf.org\/aboutdiabetes\/what-is-diabetes\/facts-figures.html). Accessed 6 Jan 2021"},{"key":"266_CR10","doi-asserted-by":"publisher","first-page":"108362","DOI":"10.1016\/j.diabres.2020.108362","volume":"167","author":"AG Ampofo","year":"2020","unstructured":"Ampofo AG, Boateng EB. Beyond 2020: Modelling obesity and diabetes prevalence. Diabetes Res Clin Pract. 2020;167:108362. https:\/\/doi.org\/10.1016\/j.diabres.2020.108362.","journal-title":"Diabetes Res Clin Pract"},{"key":"266_CR11","doi-asserted-by":"publisher","first-page":"107843","DOI":"10.1016\/j.diabres.2019.107843","volume":"157","author":"P Saeedi","year":"2019","unstructured":"Saeedi P, Petersohn I, Salpea P, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019;157:107843. https:\/\/doi.org\/10.1016\/j.diabres.2019.107843.","journal-title":"Diabetes Res Clin Pract."},{"issue":"1","key":"266_CR12","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1186\/1471-2458-12-18","volume":"12","author":"AM El-Sayed","year":"2012","unstructured":"El-Sayed AM, Scarborough P, Galea S. Unevenly distributed: a systematic review of the health literature about socioeconomic inequalities in adult obesity in the United Kingdom. BMC Public Health. 2012;12(1):18. https:\/\/doi.org\/10.1186\/1471-2458-12-18.","journal-title":"BMC Public Health"},{"issue":"1","key":"266_CR13","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1080\/09581596.2014.920078","volume":"25","author":"C Chaufan","year":"2015","unstructured":"Chaufan C, Yeh J, Ross L, Fox P. You can\u2019t walk or bike yourself out of the health effects of poverty: active school transport, child obesity, and blind spots in the public health literature. Crit Public Health. 2015;25(1):32\u201347. https:\/\/doi.org\/10.1080\/09581596.2014.920078.","journal-title":"Crit Public Health"},{"issue":"5","key":"266_CR14","first-page":"9","volume":"20","author":"ME J\u00f8rgensen","year":"2008","unstructured":"J\u00f8rgensen ME, Christensen DL. Ethnicity and obesity: why are some people more vulnerable? Int Diabetes Monit. 2008;20(5):9.","journal-title":"Int Diabetes Monit"},{"issue":"5","key":"266_CR15","doi-asserted-by":"publisher","first-page":"e1003106","DOI":"10.1371\/journal.pmed.1003106","volume":"17","author":"R Mathur","year":"2020","unstructured":"Mathur R, Farmer RE, Eastwood SV, Chaturvedi N, Douglas I, Smeeth L. Ethnic disparities in initiation and intensification of diabetes treatment in adults with type 2 diabetes in the UK, 1990\u20132017: A cohort study. PLOS Med. 2020;17(5):e1003106. https:\/\/doi.org\/10.1371\/journal.pmed.1003106.","journal-title":"PLOS Med"},{"issue":"10","key":"266_CR16","doi-asserted-by":"publisher","first-page":"1751","DOI":"10.1007\/s00125-019-4968-0","volume":"62","author":"SH Golden","year":"2019","unstructured":"Golden SH, Yajnik C, Phatak S, Hanson RL, Knowler WC. Racial\/ethnic differences in the burden of type 2 diabetes over the life course: a focus on the USA and India. Diabetologia. 2019;62(10):1751\u201360. https:\/\/doi.org\/10.1007\/s00125-019-4968-0.","journal-title":"Diabetologia"},{"issue":"1","key":"266_CR17","doi-asserted-by":"publisher","first-page":"20","DOI":"10.2337\/diaclin.28.1.20","volume":"28","author":"CN Massey","year":"2010","unstructured":"Massey CN, Appel SJ, Buchanan KL, Cherrington AL. Improving diabetes care in rural communities: an overview of current initiatives and a call for renewed efforts. Clin Diabetes. 2010;28(1):20\u20137. https:\/\/doi.org\/10.2337\/diaclin.28.1.20.","journal-title":"Clin Diabetes"},{"key":"266_CR18","unstructured":"International Diabetes Federation. Demographic and geographic outline (IDF Diabetes Atlas, 9th edition 2019). https:\/\/diabetesatlas.org\/en\/sections\/demographic-and-geographic-outline.html. Accessed 6 Jan 2021"},{"issue":"2","key":"266_CR19","doi-asserted-by":"publisher","first-page":"e0229438","DOI":"10.1371\/journal.pone.0229438","volume":"15","author":"S Luhar","year":"2020","unstructured":"Luhar S, Tim\u00e6us IM, Jones R, et al. Forecasting the prevalence of overweight and obesity in India to 2040. PLoS ONE. 2020;15(2):e0229438. https:\/\/doi.org\/10.1371\/journal.pone.0229438.","journal-title":"PLoS ONE"},{"key":"266_CR20","unstructured":"The World Obesity Federation (World Obesity). BLOG | Obesity and the SDGs: an opportunity hidden in plain sight. https:\/\/www.worldobesity.org\/news\/blog-obesity-and-the-sdgs-an-opportunity-hidden-in-plain-sight. Accessed 7 Jan 2021"},{"key":"266_CR21","unstructured":"US CDC. Genes and obesity (17 May 2013). https:\/\/www.cdc.gov\/genomics\/resources\/diseases\/obesity\/obesedit.htm. Accessed 8 Jan 2021"},{"issue":"6","key":"266_CR22","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1111\/j.1365-2362.2010.02454.x","volume":"41","author":"C Herder","year":"2011","unstructured":"Herder C, Roden M. Genetics of type 2 diabetes: pathophysiologic and clinical relevance. Eur J Clin Invest. 2011;41(6):679\u201392. https:\/\/doi.org\/10.1111\/j.1365-2362.2010.02454.x.","journal-title":"Eur J Clin Invest"},{"key":"266_CR23","unstructured":"Mayo Clinic. Obesity - Symptoms and causes (18 November 2020. https:\/\/www.mayoclinic.org\/diseases-conditions\/obesity\/symptoms-causes\/syc-20375742). Accessed 8 Jan 2021"},{"issue":"1","key":"266_CR24","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1186\/1476-072X-5-14","volume":"5","author":"X Zhang","year":"2006","unstructured":"Zhang X, Christoffel KK, Mason M, Liu L. Identification of contrastive and comparable school neighborhoods for childhood obesity and physical activity research. Int J Health Geogr. 2006;5(1):14. https:\/\/doi.org\/10.1186\/1476-072X-5-14.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR25","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/1476-072X-11-11","volume":"11","author":"DT Duncan","year":"2012","unstructured":"Duncan DT, Castro MC, Gortmaker SL, Aldstadt J, Melly SJ, Bennett GG. Racial differences in the built environment\u2014body mass index relationship? A geospatial analysis of adolescents in urban neighborhoods. Int J Health Geogr. 2012;11(1):11. https:\/\/doi.org\/10.1186\/1476-072X-11-11.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR26","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1186\/s12942-019-0174-z","volume":"18","author":"K Okuyama","year":"2019","unstructured":"Okuyama K, Abe T, Hamano T, et al. Hilly neighborhoods are associated with increased risk of weight gain among older adults in rural Japan: a 3-years follow-up study. Int J Health Geogr. 2019;18(1):10. https:\/\/doi.org\/10.1186\/s12942-019-0174-z.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR27","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/s12942-016-0065-5","volume":"15","author":"A Cebrecos","year":"2016","unstructured":"Cebrecos A, D\u00edez J, Gull\u00f3n P, Bilal U, Franco M, Escobar F. Characterizing physical activity and food urban environments: a GIS-based multicomponent proposal. Int J Health Geogr. 2016;15(1):35. https:\/\/doi.org\/10.1186\/s12942-016-0065-5.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR28","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1186\/1476-072X-10-43","volume":"10","author":"T Hanibuchi","year":"2011","unstructured":"Hanibuchi T, Kondo K, Nakaya T, et al. Neighborhood food environment and body mass index among Japanese older adults: results from the Aichi Gerontological Evaluation Study (AGES). Int J Health Geogr. 2011;10(1):43. https:\/\/doi.org\/10.1186\/1476-072X-10-43.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR29","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1186\/1476-072X-11-14","volume":"11","author":"A Forsyth","year":"2012","unstructured":"Forsyth A, Van Riper D, Larson N, Wall M, Neumark-Sztainer D. Creating a replicable, valid cross-platform buffering technique: The sausage network buffer for measuring food and physical activity built environments. Int J Health Geogr. 2012;11(1):14. https:\/\/doi.org\/10.1186\/1476-072X-11-14.","journal-title":"Int J Health Geogr"},{"issue":"1","key":"266_CR30","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1186\/1476-072X-9-8","volume":"9","author":"PM Owens","year":"2010","unstructured":"Owens PM, Titus-Ernstoff L, Gibson L, Beach ML, Beauregard S, Dalton MA. Smart density: a more accurate method of measuring rural residential density for health-related research. Int J Health Geogr. 2010;9(1):8. https:\/\/doi.org\/10.1186\/1476-072X-9-8.","journal-title":"Int J Health Geogr"},{"key":"266_CR31","doi-asserted-by":"publisher","DOI":"10.1186\/s12940-018-0386-x","author":"T VoPham","year":"2018","unstructured":"VoPham T, Hart JE, Laden F, Chiang Y-Y. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology. Environ Health. 2018. https:\/\/doi.org\/10.1186\/s12940-018-0386-x.","journal-title":"Environ Health."},{"issue":"1","key":"266_CR32","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s12942-019-0171-2","volume":"18","author":"MN Kamel Boulos","year":"2019","unstructured":"Kamel Boulos MN, Peng G, VoPham T. An overview of GeoAI applications in health and healthcare. Int J Health Geogr. 2019;18(1):7. https:\/\/doi.org\/10.1186\/s12942-019-0171-2.","journal-title":"Int J Health Geogr"},{"key":"266_CR33","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/978-1-4302-6014-1_10","volume-title":"Sensor technologies: healthcare, wellness, and environmental applications","author":"MJ McGrath","year":"2013","unstructured":"McGrath MJ, Scanaill CN. Wellness, fitness, and lifestyle sensing applications. In: McGrath MJ, Scanaill CN, editors. Sensor technologies: healthcare, wellness, and environmental applications. New York: Apress; 2013. p. 217\u201348. https:\/\/doi.org\/10.1007\/978-1-4302-6014-1_10."},{"issue":"12","key":"266_CR34","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1038\/s41366-018-0153-7","volume":"42","author":"KA Timmins","year":"2018","unstructured":"Timmins KA, Green MA, Radley D, Morris MA, Pearce J. How has big data contributed to obesity research? A review of the literature. Int J Obes. 2018;42(12):1951\u201362. https:\/\/doi.org\/10.1038\/s41366-018-0153-7.","journal-title":"Int J Obes"},{"issue":"4","key":"266_CR35","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1056\/NEJMsa066082","volume":"357","author":"NA Christakis","year":"2007","unstructured":"Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357(4):370\u20139. https:\/\/doi.org\/10.1056\/NEJMsa066082.","journal-title":"N Engl J Med"},{"issue":"5","key":"266_CR36","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1002\/sres.2215","volume":"30","author":"A Hieronymi","year":"2013","unstructured":"Hieronymi A. Understanding systems science: a visual and integrative approach. Syst Res Behav Sci. 2013;30(5):580\u201395. https:\/\/doi.org\/10.1002\/sres.2215.","journal-title":"Syst Res Behav Sci"},{"issue":"2","key":"266_CR37","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s12571-019-00900-7","volume":"11","author":"K Koh","year":"2019","unstructured":"Koh K, Reno R, Hyder A. Examining disparities in food accessibility among households in Columbus, Ohio: an agent-based model. Food Secur. 2019;11(2):317\u201331. https:\/\/doi.org\/10.1007\/s12571-019-00900-7.","journal-title":"Food Secur"},{"issue":"12","key":"266_CR38","doi-asserted-by":"publisher","first-page":"e0243501","DOI":"10.1371\/journal.pone.0243501","volume":"15","author":"I Vojnovic","year":"2020","unstructured":"Vojnovic I, Ligmann-Zielinska A, LeDoux TF. The dynamics of food shopping behaviour: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling. PLoS ONE. 2020;15(12):e0243501. https:\/\/doi.org\/10.1371\/journal.pone.0243501.","journal-title":"PLoS ONE"},{"key":"266_CR39","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/978-1-4939-8790-0_270","volume-title":"System dynamics: theory and applications. Encyclopedia of complexity and systems science series","author":"GB Hirsch","year":"2020","unstructured":"Hirsch GB, Homer J. System Dynamics Applications to Health Care in the United States. In: Dangerfield B, editor. System dynamics: theory and applications. Encyclopedia of complexity and systems science series. New York: Springer US; 2020. p. 209\u201327. https:\/\/doi.org\/10.1007\/978-1-4939-8790-0_270."},{"key":"266_CR40","doi-asserted-by":"publisher","unstructured":"NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19\u00b72 million participants. Lancet. 2016;387(10026):1377-1396. https:\/\/doi.org\/10.1016\/S0140-6736(16)30054-X","DOI":"10.1016\/S0140-6736(16)30054-X"},{"issue":"24","key":"266_CR41","doi-asserted-by":"publisher","first-page":"2515","DOI":"10.1001\/jama.2017.7596","volume":"317","author":"L Wang","year":"2017","unstructured":"Wang L, Gao P, Zhang M, et al. Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013. JAMA. 2017;317(24):2515. https:\/\/doi.org\/10.1001\/jama.2017.7596.","journal-title":"JAMA"},{"key":"266_CR42","doi-asserted-by":"publisher","unstructured":"Kamel Boulos MN, Yang SP. Mobile physical activity planning and tracking: a brief overview of current options and desiderata for future solutions. mHealth. 2021;7:13. https:\/\/doi.org\/10.21037\/mhealth.2020.01.01https:\/\/mhealth.amegroups.com\/article\/view\/38687\/html","DOI":"10.21037\/mhealth.2020.01.01"},{"key":"266_CR43","doi-asserted-by":"crossref","unstructured":"NCD Risk Factor Collaboration (NCD-RisC). Rising rural body-mass index is the main driver of the global obesity epidemic in adults. Nature. 2019;569:260\u2013264. https:\/\/www.nature.com\/articles\/s41586-019-1171-x","DOI":"10.1038\/s41586-019-1171-x"},{"issue":"6","key":"266_CR44","doi-asserted-by":"publisher","first-page":"1453","DOI":"10.3390\/s17061453","volume":"17","author":"G Rateni","year":"2017","unstructured":"Rateni G, Dario P, Cavallo F. Smartphone-based food diagnostic technologies: a review. Sensors (Basel). 2017;17(6):1453. https:\/\/doi.org\/10.3390\/s17061453.","journal-title":"Sensors (Basel)"},{"issue":"1","key":"266_CR45","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1186\/s12966-017-0488-9","volume":"14","author":"FJ Pendergast","year":"2017","unstructured":"Pendergast FJ, Ridgers ND, Worsley A, McNaughton SA. Evaluation of a smartphone food diary application using objectively measured energy expenditure. Int J Behav Nutr Phys Act. 2017;14(1):30. https:\/\/doi.org\/10.1186\/s12966-017-0488-9.","journal-title":"Int J Behav Nutr Phys Act"},{"issue":"2","key":"266_CR46","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1111\/1747-0080.12401","volume":"75","author":"V Teixeira","year":"2018","unstructured":"Teixeira V, Voci SM, Mendes-Netto RS, da Silva DG. The relative validity of a food record using the smartphone application MyFitnessPal. Nutr Diet. 2018;75(2):219\u201325. https:\/\/doi.org\/10.1111\/1747-0080.12401.","journal-title":"Nutr Diet"},{"key":"266_CR47","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.jpeds.2016.11.015","volume":"182","author":"EL Kenney","year":"2017","unstructured":"Kenney EL, Gortmaker SL. United States adolescents\u2019 television, computer, videogame, smartphone, and tablet use: associations with sugary drinks, sleep, physical activity, and obesity. J Pediatr. 2017;182:144\u20139. https:\/\/doi.org\/10.1016\/j.jpeds.2016.11.015.","journal-title":"J Pediatr"},{"issue":"4","key":"266_CR48","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1111\/j.1365-2796.2005.01545.x","volume":"258","author":"K Patja","year":"2005","unstructured":"Patja K, Jousilahti P, Hu G, Valle T, Qiao Q, Tuomilehto J. Effects of smoking, obesity and physical activity on the risk of type 2 diabetes in middle-aged Finnish men and women. J Intern Med. 2005;258(4):356\u201362. https:\/\/doi.org\/10.1111\/j.1365-2796.2005.01545.x.","journal-title":"J Intern Med"},{"key":"266_CR49","unstructured":"Amazon Halo: A better measure of health. https:\/\/www.aboutamazon.com\/news\/devices\/a-better-measure-of-health. Accessed 29 Dec 2020"},{"issue":"1","key":"266_CR50","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1186\/s12942-017-0103-y","volume":"16","author":"G Klous","year":"2017","unstructured":"Klous G, Smit LAM, Borl\u00e9e F, et al. Mobility assessment of a rural population in the Netherlands using GPS measurements. Int J Health Geogr. 2017;16(1):30. https:\/\/doi.org\/10.1186\/s12942-017-0103-y.","journal-title":"Int J Health Geogr"},{"key":"266_CR51","unstructured":"Stevens M, D\u2019Hondt E. Crowdsourcing of Pollution Data using Smartphones. In: Proceedings of UbiComp \u201910, Copenhagen, Denmark, 26\u201329 September 2010. http:\/\/soft.vub.ac.be\/Publications\/2010\/vub-tr-soft-10-15.pdf"},{"key":"266_CR52","unstructured":"Hurwitz J, Nugent A, Halper F, Kaufman M. Unstructured Data in a Big Data Environment (dummies). https:\/\/www.dummies.com\/programming\/big-data\/engineering\/unstructured-data-in-a-big-data-environment\/. Accessed 16 Jan 2021"},{"issue":"4","key":"266_CR53","doi-asserted-by":"publisher","first-page":"372","DOI":"10.3390\/fi7040372","volume":"7","author":"MN Kamel Boulos","year":"2015","unstructured":"Kamel Boulos MN, Yassine A, Shirmohammadi S, Namahoot CS, Br\u00fcckner M. Towards an \u201cInternet of Food\u201d: food ontologies for the internet of things. Future Internet. 2015;7(4):372\u201392. https:\/\/doi.org\/10.3390\/fi7040372.","journal-title":"Future Internet"},{"key":"266_CR54","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.infsof.2014.06.011","volume":"58","author":"M Bano","year":"2015","unstructured":"Bano M, Zowghi D. A systematic review on the relationship between user involvement and system success. Inf Softw Technol. 2015;58:148\u201369. https:\/\/doi.org\/10.1016\/j.infsof.2014.06.011.","journal-title":"Inf Softw Technol"},{"key":"266_CR55","unstructured":"Zhuang M, Concannon D, Manley E. A framework for evaluating dashboards in healthcare. ArXiv (Preprint, 10 September 2020). https:\/\/arxiv.org\/abs\/2009.04792"},{"issue":"6176","key":"266_CR56","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.1126\/science.1248506","volume":"343","author":"D Lazer","year":"2014","unstructured":"Lazer D, Kennedy R, King G, Vespignani A. Big data. The parable of Google Flu: traps in big data analysis. Science. 2014;343(6176):1203\u20135. https:\/\/doi.org\/10.1126\/science.1248506.","journal-title":"Science"},{"key":"266_CR57","doi-asserted-by":"publisher","first-page":"100294","DOI":"10.1016\/j.ccs.2019.100294","volume":"20","author":"O Lock","year":"2020","unstructured":"Lock O, Bednarz T, Leao SZ, Pettit C. A review and reframing of participatory urban dashboards. City Cult Soc. 2020;20:100294. https:\/\/doi.org\/10.1016\/j.ccs.2019.100294.","journal-title":"City Cult Soc"},{"key":"266_CR58","doi-asserted-by":"publisher","DOI":"10.1080\/15481603.2020.1868211","author":"Z Ma","year":"2020","unstructured":"Ma Z, Chen M, Yue S, et al. Activity-based process construction for participatory geo-analysis. GIScience Remote Sens. 2020. https:\/\/doi.org\/10.1080\/15481603.2020.1868211.","journal-title":"GIScience Remote Sens"},{"key":"266_CR59","unstructured":"O'Donnell E. Zip Code vs. Genetic Code. Harvard Magazine (online). 2019 (Jul-Aug). https:\/\/harvardmagazine.com\/2019\/07\/nature-nurture-genetics. Accessed 29 Dec 2020"},{"key":"266_CR60","doi-asserted-by":"publisher","DOI":"10.3389\/fcell.2014.00049","author":"RR Kanherkar","year":"2014","unstructured":"Kanherkar RR, Bhatia-Dey N, Csoka AB. Epigenetics across the human lifespan. Front Cell Dev Biol. 2014. https:\/\/doi.org\/10.3389\/fcell.2014.00049.","journal-title":"Front Cell Dev Biol."},{"key":"266_CR61","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/bs.pmbts.2016.02.002","volume":"140","author":"A Lopomo","year":"2016","unstructured":"Lopomo A, Burgio E, Migliore L. Epigenetics of obesity. Prog Mol Biol Transl Sci. 2016;140:151\u201384. https:\/\/doi.org\/10.1016\/bs.pmbts.2016.02.002.","journal-title":"Prog Mol Biol Transl Sci"},{"key":"266_CR62","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.psychsport.2016.12.001","volume":"31","author":"NM Schutte","year":"2017","unstructured":"Schutte NM, Nederend I, Hudziak JJ, Bartels M, de Geus EJC. Heritability of the affective response to exercise and its correlation to exercise behavior. Psychol Sport Exerc. 2017;31:139\u201348. https:\/\/doi.org\/10.1016\/j.psychsport.2016.12.001.","journal-title":"Psychol Sport Exerc"},{"key":"266_CR63","doi-asserted-by":"publisher","first-page":"110547","DOI":"10.1016\/j.nut.2019.06.027","volume":"67\u201368","author":"L Crovesy","year":"2019","unstructured":"Crovesy L, Rosado EL. Interaction between genes involved in energy intake regulation and diet in obesity. Nutrition. 2019;67\u201368:110547. https:\/\/doi.org\/10.1016\/j.nut.2019.06.027.","journal-title":"Nutrition"},{"issue":"4","key":"266_CR64","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1097\/NT.00000000000001","volume":"51","author":"CD Davis","year":"2016","unstructured":"Davis CD. The gut microbiome and its role in obesity. Nutr Today. 2016;51(4):167\u201374. https:\/\/doi.org\/10.1097\/NT.00000000000001.","journal-title":"Nutr Today"}],"container-title":["International Journal of Health Geographics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12942-021-00266-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12942-021-00266-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12942-021-00266-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T09:08:43Z","timestamp":1614762523000},"score":1,"resource":{"primary":{"URL":"https:\/\/ij-healthgeographics.biomedcentral.com\/articles\/10.1186\/s12942-021-00266-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,3]]},"references-count":64,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["266"],"URL":"https:\/\/doi.org\/10.1186\/s12942-021-00266-0","relation":{},"ISSN":["1476-072X"],"issn-type":[{"value":"1476-072X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,3]]},"assertion":[{"value":"3 March 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"MNKB is Editor-in-Chief of International Journal of Health Geographics.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"12"}}