Diabetes prevalence and risk factors of early-onset adult diabetes: results from the Indonesian family life survey

References

• New world bank country classifications by income level: 2021-2022 [Internet]. World Bank Group. 2021 cited 2021 Sep 07. Available from: https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2021-2022.
   Google Scholar
• World Health Organization. Indonesia Diabetes Country Profile. 2016. cited 2019 Apr 23. Available from: https://www.who.int/diabetes/country-profiles/idn_en.pdf.
   Google Scholar
• Cardiovascular Division & Health Services Research Centre. Reducing the burden of CVD in Indonesia. Newtown: The George Institute for Global Health; 2017. cited 2019 Feb 1]. Available from https://www.georgeinstitute.org/sites/default/files/reducing-the-burden-of-cvd-in-indonesia-evidence-review.pdf
   Google Scholar
• World Health Organization. WHO diabetes country profiles 2016: explanatory notes. 2016. cited 2019 Feb 18. Available from: https://www.who.int/diabetes/country-profiles/diabetes_profiles_explanatory_notes.pdf?ua=1.
   Google Scholar
• International Diabetes Federation. Indonesia: IDF; 2020 [updated 2020 May 14; cited 2021 Feb 28]. Available from: https://www.idf.org/our-network/regions-members/western-pacific/members/104-indonesia.
   Google Scholar
• Indonesia Agency of Health Research and Development. Basic health research (Riskesdas) 2013. Indonesia: Ministry of Health Republic of Indonesia; 2013. cited 2019 Mar 25]. Available from https://www.kemkes.go.id/resources/download/general/Hasil%20Riskesdas%202013.pdf
   Google Scholar
• Indonesia Agency of Health Research and Development. Basic health research (Riskesdas) 2018. Jakarta Indonesia: Ministry of Health of Republic of Indonesia; 2019. cited 2020 Nov 6. Available from: https://www.litbang.kemkes.go.id/laporan-riset-kesehatan-dasar-riskesdas/.
   Google Scholar
• Arisma BJN, Yunus M, Fanani E. [Description of community knowledge on diabetes mellitus risk factors in sub-district Pakisaji in Malang district]. Preventia. 2017;2:2.
   Google Scholar
• Gultom YT [Diabetes mellitus patients’ knowledge on diabetes management at the gatot soebroto army hospital in central jakarta] [thesis]. Depok Indonesia: University of Indonesia; 2012.
   Google Scholar
• Chan JC, Yeung R, Luk A. The Asian diabetes phenotypes: challenges and opportunities. Diabetes Res Clin Pract. 2014;105:135–11. Epub 2014 Jun 21. PubMed PMID: 24947419.
   Web of Science ®Google Scholar
• Barker DJ. Fetal growth and adult disease. Br J Obstet Gynaecol. 1992;99:275–276. Epub 1992 Apr 1. PubMed PMID: 1581269
   PubMedGoogle Scholar
• Chan JC, Malik V, Jia W, et al. Diabetes in Asia: epidemiology, risk factors, and pathophysiology. JAMA. 2009;301:2129–2140. PubMed PMID: 19470990 Epub 2009 May 28.
   PubMed Web of Science ®Google Scholar
• Jiang X, Ma H, Wang Y, et al. Early life factors and type 2 diabetes mellitus. J Diabetes Res. 2013;2013:485082. Epub 2014 Jan 24. PubMed PMID: 24455747; PubMed Central PMCID: PMCPMC3876901.
   PubMed Web of Science ®Google Scholar
• Ma RC, Chan JC, Tam WH, et al. Gestational diabetes, maternal obesity, and the NCD burden. Clin Obstet Gynecol. 2013;56:633–641. Epub 2013 Jul 4. PubMed PMID: 23820121.
   Web of Science ®Google Scholar
• Sarr O, Yang K, Regnault TR. In utero programming of later adiposity: the role of fetal growth restriction. J Pregnancy. 2012;2012:134758. Epub 2012 Dec 20. PubMed PMID: 23251802; PubMed Central PMCID: PMCPMC3518064.
   PubMedGoogle Scholar
• Tam CHT, Ma RCW, Yuen LY, et al. The impact of maternal gestational weight gain on cardiometabolic risk factors in children. Diabetologia. 2018;61:2539–2548.
   Web of Science ®Google Scholar
• Kadayifci FZ, Haggard S, Jeon S, et al. Early-life programming of type 2 diabetes mellitus: understanding the association between epigenetics/genetics and environmental factors. Curr Genomics. 2019;20:453–463. PubMed PMID: 32477001
   Web of Science ®Google Scholar
• Nanditha A, Ma RC, Ramachandran A, et al. Diabetes in Asia and the Pacific: implications for the global epidemic. Diabetes Care. 2016;39:472–485. PubMed PMID: 26908931 Epub 2016 Feb 26.
   PubMed Web of Science ®Google Scholar
• Uma SV, Raman VK, Nochikattil SK. Life course socioeconomic transition and its association with early onset type 2 diabetes: protocol for a sequential exploratory mixed method study. J Clin Diagn Res. 2016;10:LO01–LO5. PubMed PMID: 27504317
   Web of Science ®Google Scholar
• Vaag A, Brøns C, Gillberg L, et al. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes. Acta Obstet Gynecol Scand. 2014;93:1099–1108. PubMed PMID: 25179736 Epub 2014 Sep 3.
   Web of Science ®Google Scholar
• Vaiserman AM. Early-life nutritional programming of type 2 diabetes: experimental and quasi-experimental evidence. Nutrients. 2017;9:236. PubMed PMID: 28273874
   Web of Science ®Google Scholar
• Indrahadi D, Wardana A, Pierewan A. The prevalence of diabetes mellitus and relationship with socioeconomic status in the Indonesian population. J Gizi Klinik Indones. 2021;17:103.
   Google Scholar
• Soewondo P, Pramono LA. Prevalence, characteristics, and predictors of pre-diabetes in Indonesia. Med J Indones. 2011;20:4.
   Google Scholar
• Antono L, Kurniati A, Angela A, et al. The incidence of diabetes in Indonesian young adults: the importance of lifestyle compared to family history. International Conference on Food and Agricultural Sciences (ICFAS 2013); 5-6 Oct 2013; Melaka, Malaysia: IPCBEE; 2013.
   Google Scholar
• Frankenberg E, Karoly L. The 1993 Indonesian family life survey: overview and field report. RAND Labor & Population, 1995 Nov 1995. Report No.: DRU-1195/1-NICHD/AID Contract No.: DRU-1195/1-NICHD/AID.
   Google Scholar
• Frankenberg E, Thomas D The Indonesia family life survey (IFLS): study design and results from waves 1 and 2. RAND Labor & Population, 2000 Mar 2000. Report No.: DRU-2238/1-NIA/NICHD Contract No.: DRU-2238/1-NIA/NICHD.
   Google Scholar
• Herningtyas EH, Hu P, Edenfield M, et al. IFLS wave 5 dried blood spot data user guide. Santa Monica: RAND Labor & Population, 2018 Jan. WR-1143/6-NIA/NICHD Contract No.: WR-1143/6-NIA/NICHD.
   Google Scholar
• Hu P, Herningtyas EH, Strauss J, et al. IFLS C-Reactive protein data user guide. Santa Monica: RAND Labor & Population, 2013 Oct. Contract No.: WR-675/7.
   Google Scholar
• Strauss J, Witoelar F, Sikoki B The fifth wave of the Indonesia family life survey (IFLS5): overview and field report. RAND Labor & Population, 2016 Mar. WR-1143/1-NIA/NICHD Contract No.: WR-1143/1-NIA/NICHD.
   Google Scholar
• Strauss J, Witoelar F, Sikoki B, et al. The fourth wave of the Indonesia family life survey (IFLS4): overview and field report. RAND Labor & Population, 2009 Apr. WR-675/1-NIA/NICHD Contract No.: WR-675/1-NIA/NICHD.
   Google Scholar
• World Health Organization. Regional office for the Western Pacific. In: The Asia-Pacific perspective: redefining obesity and its treatment. Sydney: Health Communications Australia; 2000. p. 55.
   Google Scholar
• American Diabetes Association. Introduction: standards of medical care in diabetes-2020. Diabetes Care. 2020;43:S1–s2. Epub 2019/ 12/22. PubMed PMID: 31862741.
   Web of Science ®Google Scholar
• R Core Team. R: a language and environment for statistical computing. 4.0.3 ed. Vienna Austria: R Foundation for Statistical Computing; 2020.
   Google Scholar
• RAND. The Indonesia family life survey (IFLS): RAND; 2015 [cited 2018]. Available from: https://www.rand.org/well-being/social-and-behavioral-policy/data/FLS/IFLS.html.
   Google Scholar
• American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2021. Diabetes Care. 2021;44:S15–S33.
   PubMed Web of Science ®Google Scholar
• American Diabetes Association. 6. Glycemic targets: standards of medical care in diabetes—2020. Diabetes Care. 2020;43:S66–S76.
   PubMed Web of Science ®Google Scholar
• American Diabetes Association. 12. Older adults: standards of medical care in diabetes—2020. Diabetes Care. 2020;43:S152–S62.
   PubMed Web of Science ®Google Scholar
• Sherwani SI, Khan HA, Ekhzaimy A, et al. Significance of HbA1c test in diagnosis and prognosis of diabetic patients. Biomark Insights. 2016;11:95–104. PubMed PMID: 27398023
   PubMed Web of Science ®Google Scholar
• Kristina S, Salsabila A, Hanifah S. Awareness of diabetes mellitus among rural population in Indonesia. Int J Pharm Res. 2020; 13. https://doi.org/10.31838/ijpr/2021.13.01.027.
   Google Scholar
• Ligita T, Wicking K, Francis K, et al. How people living with diabetes in Indonesia learn about their disease: a grounded theory study. PLoS One. 2019;14:e0212019.
   Web of Science ®Google Scholar
• Rhee EJ. Diabetes in Asians. Endocrinol Metab. 2015;30:263–269. PubMed PMID: 26435131
   Web of Science ®Google Scholar
• Chan JC, Lau ES, Luk AO, et al. Premature mortality and comorbidities in young-onset diabetes: a 7-year prospective analysis. Am J Med. 2014;127:616–624. PubMed PMID: 24680795 Epub 2014 Apr 1.
   Web of Science ®Google Scholar
• Lascar N, Brown J, Pattison H, et al. Type 2 diabetes in adolescents and young adults. Lancet Diabetes Endocrinol. 2018;6:69–80. Epub 2017 Aug 30. PubMed PMID: 28847479.
   PubMed Web of Science ®Google Scholar
• Magliano DJ, Sacre JW, Harding JL, et al. Young-onset type 2 diabetes mellitus - implications for morbidity and mortality. Nat Rev Endocrinol. 2020;16:321–331. Epub 2020 Mar 24. PubMed PMID: 32203408.
   PubMed Web of Science ®Google Scholar
• Visaria J, Iyer NN, Raval A, et al. Incidence and prevalence of microvascular and macrovascular diseases and all-cause mortality in type 2 diabetes mellitus: a 10-year study in a US commercially insured and medicare advantage population. Clin Ther. 2019;41:1522–36.e1. PubMed PMID: 31196656 Epub 2019 Jun 15.
   Web of Science ®Google Scholar
• Yeung RO, Zhang Y, Luk A, et al. Metabolic profiles and treatment gaps in young-onset type 2 diabetes in Asia (the JADE programme): a cross-sectional study of a prospective cohort. Lancet Diabetes Endocrinol. 2014;2:935–943. Epub 2014 Aug 2. PubMed PMID: 25081582. 2
   Web of Science ®Google Scholar
• Rao Kondapally Seshasai S, Kaptoge S, Thompson A, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364:829–841. PubMed PMID: 21366474; PubMed Central PMCID: PMCPMC4109980 Epub 2011 Mar 04.
   PubMed Web of Science ®Google Scholar
• Hart JT. Rule of halves: implications of increasing diagnosis and reducing dropout for future workload and prescribing costs in primary care. Br J Gen Pract. 1992;42:116–119. PubMed PMID: 1493028
   PubMed Web of Science ®Google Scholar
• Jaacks LM, Vandevijvere S, Pan A, et al. The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol. 2019;7:231–240. PubMed PMID: 30704950; PubMed Central PMCID: PMCPMC7360432 Epub 2019 Feb 2.
   PubMed Web of Science ®Google Scholar
• Sacerdote C, Ricceri F, Rolandsson O, et al. Lower educational level is a predictor of incident type 2 diabetes in European countries: the EPIC-InterAct study. Int J Epidemiol. 2012;41:1162–1173. PubMed PMID: 22736421 Epub 2012 Jun 28.
   PubMed Web of Science ®Google Scholar
• Seiglie JA, Marcus M-E, Ebert C, et al. Diabetes prevalence and its relationship with education, wealth, and BMI in 29 low- and middle-income countries. Diabetes Care. 2020;43:767–775.
   Web of Science ®Google Scholar
• Flies EJ, Mavoa S, Zosky GR, et al. Urban-associated diseases: candidate diseases, environmental risk factors, and a path forward. Environ Int. 2019;133:105187.
   PubMed Web of Science ®Google Scholar
• Barker D, Eriksson J, Forsén T, et al. Fetal origins of adult disease: strength of effects and biological basis. Int J Epidemiol. 2002;31:1235–1239.
   PubMed Web of Science ®Google Scholar
• Hales CN, Barker DJP. The thrifty phenotype hypothesis: type 2 diabetes. Br Med Bull. 2001;60:5–20.
   PubMed Web of Science ®Google Scholar
• Yajnik CS. Early life origins of insulin resistance and type 2 diabetes in India and other Asian countries. J Nutr. 2004;134:205–210. Epub 2004 Jan 6. PubMed PMID: 14704320.
   PubMed Web of Science ®Google Scholar
• Tamayo T, Christian H, Rathmann W. Impact of early psychosocial factors (childhood socioeconomic factors and adversities) on future risk of type 2 diabetes, metabolic disturbances and obesity: a systematic review. BMC Public Health. 2010;10:525. Epub 2010 Sept 3. PubMed PMID: 20809937; PubMed Central PMCID: PMCPMC2940917.
   PubMed Web of Science ®Google Scholar
• Demakakos P, Marmot M, Steptoe A. Socioeconomic position and the incidence of type 2 diabetes: the ELSA study. Eur J Epidemiol. 2012;27:367–378.
   Web of Science ®Google Scholar
• Tsenkova V, Pudrovska T, Karlamangla A. Childhood socioeconomic disadvantage and prediabetes and diabetes in later life: a study of biopsychosocial pathways. Psychosom Med. 2014;76:622–628. PubMed PMID: 25272201
   Web of Science ®Google Scholar
• Sutanegara D, Budhiarta AA. The epidemiology and management of diabetes mellitus in Indonesia. Diabetes Res Clin Pract. 2000;50:S9–s16. Epub 2000 Oct 12. PubMed PMID: 11024578.
   Web of Science ®Google Scholar
• Directorate General of Non-Communicable Disease Prevention and Control. Program P2PTM dan indikator [non-communicable disease prevention and control program and indicators]. Jakarta Indonesia: Ministry of Health Indonesia; 2016 cited 2021 Apr 17. Available from: http://p2ptm.kemkes.go.id/profil-p2ptm/latar-belakang/program-p2ptm-dan-indikator.
   Google Scholar
• Pranandari LL, Arso SP, and Fatmasari EY. [Noncommunicable disease management post program implementation analysis at sub-district Banguntapan in Bantul district]. Journal Kesehatan Masyarakat. 2017;5:4.
   Google Scholar
• Primiyani Y, Masrul M, and Hardisman H. [Noncommunicable disease management post program implementation analysis in Solok City]. Journal Kesehatan Andalas. 2019;8:2.
   Google Scholar
• Baird J, Jacob C, Barker M, et al. Developmental origins of health and disease: a lifecourse approach to the prevention of non-communicable diseases. Healthcare. 2017;5:14. PubMed PMID: 28282852; PubMed Central PMCID: PMCPMC5371920 Epub 2017 Mar 12.
   Web of Science ®Google Scholar
• Leighton E, Sainsbury CA, Jones GC. A practical review of C-Peptide testing in diabetes. Diabetes Ther. 2017;8:475–487. Epub 2017 May 8. PubMed PMID: 28484968. 8
   PubMed Web of Science ®Google Scholar
• Dejkhamron P, Santiprabhob J, Likitmaskul S, et al. Type 1 diabetes management and outcomes: a multicenter study in Thailand. J Diabetes Investig. 2021;12:516–526.
   Web of Science ®Google Scholar
• Patterson CC, Karuranga S, Salpea P, et al. Worldwide estimates of incidence, prevalence and mortality of type 1 diabetes in children and adolescents: results from the international diabetes federation diabetes atlas, 9th edition. Diabetes Res Clin Pract. 2019; 157. Epub 2019 Sep 10. https://doi.org/10.1016/j.diabres.2019.107842. PubMed PMID: 107842.
   Google Scholar
• Pulungan AB, Fadiana G, Annisa D. Type 1 diabetes mellitus in children: experience in Indonesia. Clin Pediatr Endocrinol. 2021;30:11–18. Epub 2021 Jan 5. PubMed PMID: 33446947.
   Google Scholar
• World Health Organization. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus: abbreviated report of a WHO consultation. Geneva: World Health Organization; 2011. cited 2021 Jan 18. Available from: https://www.ncbi.nlm.nih.gov/books/NBK304267/pdf/Bookshelf_NBK304267.pdf.
   Google Scholar