Mapping diabetes burden by school-district for school-based diabetes prevention interventions in selected cities in Michigan, USA


To decrease diabetes morbidity and mortality rates, early interventions are needed to change lifestyles that are often cemented early, making school-based interventions important. However, with limited resources and lack of within-county diabetes data, it is difficult to determine which local areas require intervention. To identify at-risk school districts, this study mapped diabetes prevalence and related deaths by school district using geographic information systems (GIS). The 2010-2014 records of diabetes-related deaths were identified for 13 cities in Michigan, USA. Diabetes prevalence was estimated using the weighted average of population by school district from the ‘500 Cities Project’ of the Centres of Disease Control and prevention (CDC). Prevalence and mortality rates were mapped by school district and the correlation between diabetes prevalence and mortality rate analysed using the Spearman’s rank correlation. Years of potential life lost (YPLL) were calculated using a 75-year endpoint. The result indicated there were geographic variations in diabetes prevalence, mortality and YPLL across Michigan. Most census tracts in the cities of Detroit, Flint and downtown Grand Rapids had higher diabetes prevalence and mortality rate with rs (628)=0.52, P<0.005. School districts with high mortality rates also had high prevalence with rs (13)=0.72, P=0.002. Flint City School District showed a higher rate of diabetes prevalence, death and YPLL than others and should thus be considered a priority for diabetes prevention interventions. Using school districts as the geographic spatial unit of analysis, we identified local variation in diabetes burden for targeting school-based diabetes prevention interventions.



PlumX Metrics


Download data is not yet available.


Aboites H, Bigum C, Bouvier R, Clanfield D, Kuehn L, Hatcher R, Houhton E, LeClaire M, Rowan L, Spreen CA, Vally S, 2010. The school as community hub: Beyond education’s iron cage. Our Schools/Our Selves. Canadian Centre for Policy Alternatives 19(4):100. Available from:

Barreto SM, Passos VM, Almeida SK, Assis TD, 2007. The increase of diabetes mortality burden among Brazilian adults. Revista Panamer Salud Públ 22:239-45. DOI:

Blue Cross Blue Shield of Michigan (BCBSM) Foundation, 2016. Nearly 150 schools statewide to join innovative health and wellness-based building healthy communities program. Available from: Accessed: 4 September 2020.

Braveman P, Sadegh-Nobari T, Egerter S, 2008. Early childhood experiences: Laying the foundation for health across a lifetime. Available from: Accessed: 3 January 2018.

CDC, 2004. Instructions for completing the cause-of-death section of the death certificate. Available from: Accessed: 6 September 2017.

CDC, 2012. Principles of epidemiology. An introduction to applied epidemiology and biostatistics. Available from: Accessed: 6 September 2017.

CDC, 2016a. 500 Largest cities,* by state and population. Available from: Accessed: 6 September 2017. Cite in te thext

CDC, 2016b. 500 Cities: local data for better health. Health outcomes. Available from: Accessed: 6 September 2017.

CDC, 2019. 500 Cities Project: local data for better health. Available from: Accessed: 4 September 2020.

CDC, 2020a. National Diabetes Statistics Report, 2020. Atlanta, GA. U.S. Dept of Health and Human Services. Available from: Accessed: 4 September 2020.

CDC, 2020b. YRBSS. Available from: Accessed: 4 September 2020

CDC, 2020c. Behavioral risk factor surveillance system (BRFSS). Available from: Accessed: 4 September 2020

Chaturvedi N, Jarrett J, Shipley MJ, Fuller JH, 1998. Socioeconomic gradient in morbidity and mortality in people with diabetes: cohort study findings from the Whitehall study and the WHO Multinational Study of Vascular Disease in Diabetes. BMJ 316:100-5. DOI:

Connolly V, Unwin N, Sherriff P, Bilous R, Kelly W, 2000. Diabetes prevalence and socioeconomic status: a population based study showing increased prevalence of type 2 diabetes mellitus in deprived areas. J Epidemiol Community Heal 54:173-7. DOI:

Dendup T, Feng X, Clingan S, Astell-Burt T, 2018. Environmental risk factors for developing type 2 diabetes mellitus: a systematic review. Int J Environ Res Public Health 15:78. DOI:

Diabetes Prevention Program Research Group, 2002. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393-403. DOI:

Gardner JW, Sanborn JS, 1990. Years of potential life lost (YPLL) - What does it measure?. Epidemiology 1:322-9. DOI:

Geraghty EM, Balsbaugh T, Nuovo J, Tandon S, 2010. Using geographic information systems (GIS) to assess outcome disparities in patients with type 2 diabetes and hyperlipidemia. J Am Board Fam Med 23:88-96. DOI:

Gortmaker SL, Peterson K, Wiecha J, Sobol AM, Dixit S, Fox MK, Laird N, 1999. Reducing obesity via a school-based interdisciplinary intervention among youth. Planet Health Arch Pediatr Adolesc Med 153:409. DOI:

Gregg EW, Zhuo X, Cheng YJ, Albright AL, Narayan KV, Thompson TJ, 2014. Trends in lifetime risk and years of life lost due to diabetes in the USA, 1985-2011: a modelling study. Lancet Diabetes Endocrinol 2:867-74. DOI:

Holme JJ, 2002. Buying homes, buying schools: school choice and the social construction of school quality. Harvard Educ Rev 72:177-206. DOI:

Kochanek K, Murphy SL, Xu JQ, Tejada-Vera B, 2016. Deaths: final data for 2014. National Vital Statistics Reports 65(4). Hyattsville, MD: National Center for Health Statistics. Available from: Accessed: 6 September 2017.

Lawrence RS, Gootman JA, Sim LJ, 2009. Adolescent health services: missing opportunities. National Academic Press, Washington, D.C., USA. Available from: Accessed: 3 January 2018.

Link CL, Mckinlay JB, 2009. Disparities in the prevalence of diabetes: is it race/ethnicity or socioeconomic status? results from the Boston Area Community Health (BACH) survey. Ethnic Dis 19:288-92.

Livingood WC, Razaila L, Reuter E, Filipowicz R, Butterfield RC, Lukens-Bull K, Edwards L, Palacio C, Wood DL, 2010. Using multiple sources of data to assess the prevalence of diabetes at the sub county level, Duval County, Florida, 2007. Prev Chronic Dis 7:A108.

Macera CA, 2003. Promoting healthy eating and physical activity for a healthier nation. Available from: Accessed: 3 January 2018.

McBean AM, Li S, Gilbertson DT, Collins AJ, 2004. Differences in diabetes prevalence, incidence, and mortality among the elderly of four racial/ethnic groups: Whites, Blacks, Hispanics, and Asians. Diabetes Care 27:2317-24. DOI:

Michigan Department of Education, 2019. Michigan Profile for Healthy Youth (MiPHY). Available from:,4615,7-140-74638_74639_29233_44681---,00.html Accessed: 4 September 2020

Murea M, Ma L, Freedman BI, 2012. Genetic and environmental factors associated with type 2 diabetes and diabetic vascular complications. The review of diabetic studies. RDS 9:6-22. DOI:

National Conference of State Legislatures (NCSL), 2016. Diabetes health coverage: state laws & programs [cited 2018 Jan 3]. Available from: Accessed: 4 September 2020.

Nield A, Quarrell S, Myers S, 2013. Community based early intervention for the prevention of type 2 diabetes: a case report of the Kahnawake schools diabetes prevention project. J Diabetes Metab 4:1-6. DOI:

Peterson KE, Fox MK, 2007. Addressing the epidemic of childhood obesity through school-based interventions: What has been done and where do we go from here? J Law Med Ethics 35:113-30. DOI:

Redding S, 1991. What is a school community, anyway. School Commun J 1:7-9.

Roux AVD, 2001. Investigating neighborhood and area effects on health. Am J Public Health 91:1783-9. DOI:

Saydah S, Lochner K, 2010. Socioeconomic status and risk of diabetes-related mortality in the US. Public Health Rep 125:377-88. DOI:

Spanakis EK, Golden SH, 2013. Race/ethnic difference in diabetes and diabetic complications. Curr Diab Rep 13:814-23. DOI:

Spratt SE, Batch BC, Davis LP, Dunham AA, Easterling M, Feinglos MN, Granger BB, Harris G, Lyn MJ, Maxson PJ, Shah BR, 2015. Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability. J Clin Transl Endocrinol 31:26-36. DOI:

State of Michigan, 2016. GIS open data. Available from: Accessed: 6 September 2017.

The HEALTHY Study Group, 2010. A school-based intervention for diabetes risk reduction. N Engl J Med 363:443-53. DOI:

US Census Bureau, 2017. TIGER/Line® Shapefiles and TIGER/Line® Files. Available from: Accessed: 6 September 2017.

US Census Bureau, 2020. 2010 Census Urban Area FAQs. Available from:

Original Articles
Diabetes, school districts, geographic information systems, years potential life lost, school-based diabetes prevention, USA.
  • Abstract views: 142

  • PDF: 50
How to Cite
Nurjannah, N., Curtis, A. B., Baker, K. M., & Paul, R. (2021). Mapping diabetes burden by school-district for school-based diabetes prevention interventions in selected cities in Michigan, USA. Geospatial Health, 16(1).