Open access Original research BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Prevalence of pre-­diabetes and undiagnosed diabetes in the Mollerussa prospective observational cohort study in a semi-­rural area of Catalonia Mireia Falguera,1,2 Maria Belén Vilanova,2,3 Nuria Alcubierre,4 Minerva Granado-­Casas,2,5 Josep Ramón Marsal,6,7 Neus Miró,8 Cristina Cebrian,9 Àngels Molló,10 Josep Franch-­Nadal,11,12 Manel Mata-­Cases ‍ ‍,11,13 Esmeralda Castelblanco ‍ ‍,14,15 Didac Mauricio ‍ ‍2,15 To cite: Falguera M, Abstract Vilanova MB, Alcubierre N, Strengths and limitations of this study Objectives To assess the prevalence of undiagnosed et al. Prevalence of pre-­ diabetes and pre-­diabetes in the healthy population in the diabetes and undiagnosed ►► This was a population-­based study of a small co- Mollerussa cohort. As a secondary objective, to identify the diabetes in the Mollerussa hort that included a representative sample of a non-­ variables associated with these conditions and to describe prospective observational previously studied population of a semi-­rural area cohort study in a semi-­rural the changes in glycaemic status after 1 year of follow-­up in Catalonia. area of Catalonia. BMJ Open in subjects with pre-­diabetes. ►► We did not perform an oral glucose tolerance test, 2020;10:e033332. doi:10.1136/ Design Prospective observational cohort study. which is a common test in most studies but is a bmjopen-2019-033332 Setting General population from a semi-­rural area. Protected by copyright. time-­consuming and expensive procedure. Participants The study included 583 participants without ►► Prepublication history and ►► The small number of cases of undiagnosed diabetes a diagnosis of diabetes recruited between March 2011 and additional material for this precluded further statistical analyses on this topic. paper are available online. To July 2014. view these files, please visit Results The prevalence of undiagnosed diabetes was the journal online (http://​dx.​doi.​ 20, 3.4% (95% CI 2.6 to 4.2) and that of pre-­diabetes Background org/​10.​1136/​bmjopen-​2019-​ was 229, 39.3% (37.3 to 41.3). Among those with pre-­ 033332). diabetes, 18.3% had isolated impaired fasting plasma Diabetes mellitus, a public health concern glucose (FPG) (FPG: 100 to <126 mg/dL), 58.1% had with an increasing incidence worldwide, is a Received 30 July 2019 isolated impaired glycated haemoglobin (HbA1c) (HbA1c great threat to general health and is leading Revised 05 December 2019 to increased morbidity and mortality. These 5.7 to <6.5) and 23.6% fulfilled both criteria. Follow-­up Accepted 07 January 2020 data were available for 166 subjects; 41.6%(37.8 to effects are mainly occurring because diabetes 45.4) returned to normoglycaemia, 57.6% (57.8 to 61.4) is a disorder of glucose metabolism that persisted in pre-­diabetes and 0.6% (0 to 1.2) progressed affects multiple organ systems and is associ- to diabetes. Individuals with pre-­diabetes had worse ated with various microvascular and macrovas- cardiometabolic risk profiles and sociodemographic cular complications and several non-­vascular features than normoglycaemic subjects. In the logistic complications. Additionally, a large group regression model, variables significantly associated with of subjects do not fulfil the diabetes criteria pre-­diabetes were older age (OR; 95% CI) (1.033; 1.011 to 1.056), higher physical activity (0.546; 0.360 to 0.827), but have intermediate glycaemic variables, body mass index (1.121; 1.029 to 1.222) and a family between normal and diabetes, and are thus history of diabetes (1.543; 1.025 to 2.323). The variables classified as having pre-­diabetes. One of the significantly associated with glycaemic normalisation were most commonly used definitions of pre-­ © Author(s) (or their employer(s)) 2020. Re-­use older age (0.948; 0.916 to 0.982) and body mass index diabetes is that of the 2010 American Diabetes permitted under CC BY-­NC. No (0.779; 0.651 to 0.931). Association (ADA) criteria:1 2 (a) impaired commercial re-­use. See rights Conclusions Among adults in our region, the estimated fasting plasma glucose (IFG), defined as and permissions. Published by prevalence of undiagnosed diabetes was 3.4% and that fasting plasma glucose (FPG) between 100 BMJ. of pre-­diabetes was 39.3%. After a 1-­year follow-­up, a and <126 mg/dL (5.6 to 5.9 mmol/L); (b) For numbered affiliations see small proportion of subjects (0.6%) with pre-­diabetes end of article. impaired glucose tolerance (IGT), defined progressed to diabetes, while a high proportion (41.6%) as a 2-­hour plasma glucose value after a 75 g returned to normoglycaemia. Individuals with pre-­diabetes Correspondence to who returned to normoglycaemia were younger and had a oral glucose tolerance test (OGTT) between Dr Didac Mauricio; 140 and <200 mg/dL (7.8 to 11.0 mmol/L) ​didacmauricio@​gmail.​com lower body mass index. or (c) glycated haemoglobin (HbA1c) levels Dr Esmeralda Castelblanco; between 5.7% and <6.5% (39 to 46 mmol/ ​esmeraldacas@​gmail.​com mol). Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 1 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Pre-­diabetes is becoming increasingly important as it Briefly, the database of the Catalan Health Institute represents a high risk of developing type 2 diabetes (T2D) (ICS) through its Primary Care Electronic Clinical and cardiovascular diseases.2 3 Moreover, individuals with Station (Estació Clínica Electronica d’Atenció Primaria pre-­diabetes are phenotypically quite similar to patients – eCAP) was used to select the population sample. All with T2D. That is, they tend to be older, with a higher population is passively included in the Primary Care Elec- body mass index (BMI) and higher blood pressure than tronic Clinical record according to the Spanish health people with normal glucose tolerance; in addition, they system, which is based on the principles of universality, tend to have insulin resistance and dyslipidaemia.4 Addi- free access, equity and fairness of financing.18 Then, tionally, multiple risk factors, such as family history, gesta- from a total population of 24 666 potentially eligible tional diabetes and certain ethnicities as well as combined individuals in the healthcare area (subjects older than risk factors such as metabolic syndrome, are known to 25 years and attending any Primary Healthcare Centre predispose subjects to a higher risk for pre-­diabetes and in the same health area), 2226 subjects were randomly its progression to T2D.5 Based only on IGT, the world- selected using a randomiser programme (SPSS software wide prevalence of pre-­diabetes among adults has been V.16.0 for Windows; SPSS), following the principles estimated by the International Diabetes Federation to be of simple random sampling, and were then invited to 7.3% in 2017, with half of these individuals (49%) being participate by telephone contact. Based on their willing- younger than 50 years.6 The National Diabetes Statistics ness to join the study, exclusion criteria, consent and Report in the USA reported that the total crude preva- baseline laboratory data, 594 subjects aged ≥25 years lence of diabetes was 9.4% (30.3 million, 2017 US popu- were finally included.17 The exclusion criteria included lation), with 23.8% undiagnosed and an additional 33.9% a previous diagnosis of diabetes (type 1 diabetes, T2D with pre-­diabetes.7 or any specific subtype of diabetes), treatment with oral In Spain, according to data from the D ​ i@​bet.​es study, antidiabetic drugs or the use of metformin for other based on OGTT, FPG and HbA1c, 13.8% of the adult popu- conditions. In addition, subjects with cardiovascular lation, adjusted for age and sex, had diabetes, and of these disease (heart disease, heart failure, aortic stenosis), individuals up to 6% had undiagnosed diabetes. Further- cancer, kidney disease, anaemia, hepatitis, gastroin- more, an additional 14.8% of individuals presented with testinal diseases, recent abdominal surgery, chronic Protected by copyright. some type of pre-­diabetic state, 3.4% based on IFG, 9.2% obstructive pulmonary disease, chronic infectious based on IGT and 2.2% with disturbances in both, after diseases, use of systemic glucocorticoids or beta blockers adjusting for age and sex.8 9 According to the ADA, up or major psychiatric disorders with psychotic symptoms to 70% of people with pre-­diabetes will develop overt were excluded from the study. Subjects were considered diabetes throughout their lives.10 11 Moreover, each year, to have hypertension or dyslipidaemia if they were using 5% to 10% of subjects with pre-­diabetes will eventually anti-­hypertensive or lipid-­lowering agents. Pre-­diabetes develop overt diabetes, and according to some studies, was defined as any of the following abnormal glycaemic this percentage can reach up to 18% per year; however, variables: FPG 100 to <126 mg/dL or HbA1c 5.7 to this rate may vary with the definition of pre-­diabetes and <6.5%; diabetes was defined as FPG ≥1256 mg/dL or population characteristics.12–15 It has been shown that HbA1c ≥6.5%. Normal glycaemic status was defined by over 3 to 5 years, approximately 25% of subjects progress FPG <100 mg/dL and HbA1c <5.7 according to the 2010 to T2D, 25% return to a normal state of glucose tolerance ADA criteria.1 Eleven subjects without baseline HbA1c and 50% remain in the pre-­diabetic state.16 Thus, the or FPG measurements were excluded. Subjects with pre-­ early diagnosis and screening of pre-­diabetes are essential diabetes at baseline (n=229) underwent a second visit 12 steps towards the prevention of its progression or at least months after the baseline visit, and 166 (72.5%) of them the delay of the onset of T2D. had relevant information at follow-­up. The primary aim of this study was to assess the prev- A fasting blood sample was taken to determine alence of undiagnosed diabetes and pre-­ diabetes in glucose, HbA1c, total cholesterol, high density lipopro- the healthy population in the Mollerussa cohort. As a tein (HDL)-­cholesterol, low density lipoprotein (LDL)-­ secondary objective, we aimed to assess the variables asso- cholesterol, triglycerides, renal function and other ciated with these conditions and to describe the changes parameters following standard protocols.17 The Fatty in glycaemic status after 1 year of follow-­up in subjects Liver Index (FLI) was calculated with the equation devel- with pre-­diabetes. oped by Bedogni et al.19 Insulin resistance was calculated by the homeostatic model assessment-2 insulin resis- tance (HOMA2-­IR), beta cell function (HOMA2-ß) and Methods insulin sensitivity (HOMA2-­S) data were calculated with Subjects a HOMA2 calculator released by the Diabetes Trials Unit, This was a prospective population-­based cohort study University of Oxford: HOMA Calculator. This calculator from the semi-­rural area of ​​Mollerussa in Catalonia is available at: http://www.​dtu.​ox.​ac.​uk/​homacalculator/ (northeast Spain) selected between March 2011 and July (updated 11 October 2017).20 The estimated glomerular 2014. The description of the cohort and the procedures filtration rate (eGFR) was calculated with the Chronic performed were initially published as a cohort profile.17 Kidney Disease Epidemiology Collaboration equation.21 2 Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Student’s t-­test, analysis of variance, the Mann-­Whitney test or the Kruskal-­ Wallis test were used to assess the differences between groups. The X2 test or Fisher’s exact test were used to determine differences in qualitative variables. Tukey's correction was applied to account for multiple tests. Multivariate logistic regression models were used to determine the association of variables with pre-­diabetes, isolated FPG, isolated HbA1c and both FPG and HbA1c at baseline with covariables that were clini- cally or statistically associated. In the pre-­diabetes model, the variables used were age, sex, education level, physical activity, dyslipidaemia, hypertension, family history of diabetes, BMI, waist, glomerular filtration rate and Fatty Liver Index. A stepwise method with selection of vari- ables by backward elimination was used to build the final logistic regression model to predict the normalisation of the glycaemic state; in all models, the goodness-­of-­fit assumption was tested by the Hosmer-­Lemeshow test. The predictive accuracy of the logistic regression model for normalisation was checked by receiver-­operating charac- teristic (ROC) curves and the area under the ROC curve Figure 1 Flow diagram of subjects at baseline and after (AUCROC). ORs with corresponding 95% CIs are shown, follow-­up. HbA1c,glycated haemoglobin. and statistical significance was established as a p value <0.05. Data management and all analyses were performed using R statistical software, V.3.3.1, and SPSS software Sociodemographic variables were recorded by (V.22, IBM, SPSS, Chicago, Illinois, USA). Protected by copyright. researchers following a protocol for the inclusion of patients using a standardised baseline questionnaire Patient and public involvement during the clinical interview. In all cases a physical exam- This research was done without patient involvement. ination (including weight, height, blood pressure and Patients were not invited to comment on the study design waist circumference) was carried out by trained research and were not consulted to develop patient-­ relevant staff. Education level and physical activity were assessed outcomes or interpret the results. Patients were not according to the International Standard Classification invited to contribute to the writing or editing of this docu- of Education22 and the Spanish-­validated International ment for readability or accuracy. Physical Activity Questionnaire,23 respectively. We classi- fied the education level as low level (studied until primary school) and high level (secondary high school education Results or higher). Physical activity was classified as sedentary or Out of the 594 individuals recruited, complete data on active (not regularly vs regularly active). FPG and HbA1c were available from 583 (98.1%). The The study protocol was conducted following the prevalence of undiagnosed diabetes was 20 subjects, 3.4% Declaration of Helsinki. All study participants signed an (95% CI 2.7 to 4.2), and the prevalence of pre-­diabetes informed consent form. was 229 subjects, 39.3% (37.3 to 41.3). Furthermore, the Sample size prevalence based on isolated FPG was 7.2%, and that The sample size was determined based on an estimated based on isolated HbA1c was 22.8%, while based on the pre-­diabetes prevalence of 35.5% and 38% using HbA1c criteria of both FPG and HbA1c, the prevalence was 9.3% levels and the 2010 ADA criteria, respectively.1 24 25 It was (figure 1). estimated that a random sample of 505 subjects was suffi- The differences of clinical and sociodemographic char- cient to assess an estimated prevalence of approximately acteristics between normoglycaemic with pre-­ diabetic 30% with a 95% CI and an error of ±4%.17 and diabetic groups are shown in table 1. Except for sex, family history of diabetes, current smoking status, alcohol Statistical methods consumption status, triglycerides and HDL-­ cholesterol Descriptive statistics of the mean (SD) or median (IQR) levels, there were significant differences in the majority were estimated for quantitative variables with a normal of parameters, including age and BMI, between the three or non-­normal distribution, respectively. Qualitative vari- groups. ables were assessed using absolute and relative frequen- We observed an association in age, BMI, waist circum- cies. Normally distributed data were analysed using the ference, systolic and diastolic blood pressure, alcohol Shapiro-­ Wilk test. Comparisons between groups of all consumption status, hypertension, dyslipidaemia, variables were performed to evaluate the differences. triglycerides, total cholesterol, LDL-­cholesterol, insulin Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 3 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Table 1 Clinical and sociodemographic differences among glycaemic status groups of the Mollerussa cohort Pre-­diabetes FPG 100 to Normoglycaemia <126 mg/dL, or Diabetes FPG <100 mg/dL HbA1c 5.7% to FPG≥126 mg/dL or Mean difference NG vs Mean difference NG vs and HbA1c <5.7% <6.5% HbA1c ≥6.5% PD (95% CI) DM (95% CI) N 334 229 20 – – Sex, women 193 (57.8%) 135 (59.0%) 13 (65.0%) 1.2 (-7.1 to 9.4) 7.2 (-14.3 to 28.8) Age, years 47.1 (12.8) 54.6 (12.3) 61.2 (13.6) 7.5 (5.4 to 9.6) 14.2 (8.4 to 19.9) 2 BMI, kg/m 25.3 (4.27) 27.5 (4.75) 30.2 (5.48) 2.1 (1.4 to 2.9) 4.9 (2.9 to 6.9) BMI categories  Normal weight 160 (50.0%) 67 (30.2%) 4 (20.0%) −18.6 (-26.6 to -10.7) −27.9 (-46.2 to -9.6)  Overweight 120 (37.5%) 106 (47.7%) 5 (25.0%) 10.4 (2.1 to 18.6) −10.9 (-30.6 to 8.7)  Obesity 40 (12.5%) 49 (22.1%) 11 (55.0%) 9.4 (3.1 to 15.8) 43.0 (20.9 to 65.1) Waist, cm 91.9 (11.9) 97.0 (12.3) 101 (16.8) 5.1 (2.9 to 7.2) 9.3 (3.8 to 14.9) SBP, mm Hg 119 (16.3) 126 (16.6) 130 (18.6) 6.7 (3.9 to 9.5) 10.9 (3.5 to 18.5) DBP, mm Hg 75.7 (10.0) 78.2 (9.88) 78.0 (9.24) 2.5 (0.8 to 4.2) 2.3 (-2.2 to 6.8) Hypertension 37 (11.1%) 49 (21.4%) 9 (45.0%) 10.3 (4.0 to 16.6) 33.9 (11.9 to 55.9) Dyslipidaemia 27 (8.08%) 39 (17.0%) 5 (25.0%) 8.9 (3.2 to 14.6) 16.9 (-2.3 to 36.1) Family history DM 94 (29.6%) 78 (37.0%) 8 (42.1%) 5.9 (-1.9 to 13.7) 11.8 (-10.1 to 33.9) Education, high level 265 (82.6%) 145 (65.0%) 11 (55.0%) −16.0 (-23.6 to -8.4) −24.3 (-46.6 to -2.1) Physical activity 243 (75.9%) 141 (63.2%) 10 (50.0%) −11.2 (-19.1 to -3.3) −22.7 (-45.2 to -0.3) Current smoker 82 (24.6%) 63 (27.5%) 3 (15.0%) 3.0 (-4.4 to 10.4) −9.5 (-25.9 to 6.8) Protected by copyright. Alcohol, g/day 8.33 (13.9) 12.3 (21.3) 10.6 (17.2) 4.0 (0.9 to 6.9) 2.2 (-5.8 to 10.3) FPG, mg/dL 86.6 (7.04) 97.0 (11.2) 119 (15.2) 10.4 (8.8 to 11.9) 32.6 (28.4 to 36.8) HbA1c, % 5.25 (0.26) 5.80 (0.29) 6.26 (0.54) 0.6 (0.5 to 0.6) 1.0 (0.9 to 1.1) HbA1c, mmol/mol 33.8 (2.81) 39.9 (3.12) 45.0 (5.92) 6.1 (5.6 to 6.6) 11.1 (9.7 to 12.5) eGFR mL/min/1.73 m2 96.6 (14.1) 90.4 (15.9) 85.5 (18.1) −6.2 (-8.7 to -3.7) −11.2 (-17.9 to -4.4) Triglycerides, mg/dL 104 (90.0) 111 (63.2) 116 (47.3) 6.6 (-6.8 to 19.9) 11.2 (-24.7 to 47.1) T-­cholesterol, g/dL 197 (38.2) 205 (32.4) 214 (31.1) 7.9 (1.9 to 14.0) 16.9 (0.7 to 33.1) HDL, mg/dL 58.7 (15.0) 58.8 (14.3) 64.6 (17.6) 0.1 (-2.4 to 2.6) 5.9 (-0.86 to 12.6) LDL, mg/dL 119 (31.4) 125 (29.4) 126 (27.7) 6.3 (1.1 to 11.4) 7.5 (-6.3 to 21.4) Insulin, µU/mL 7.99 (3.78) 10.1 (5.46) 16.2 (17.1) 2.1 (1.2 to 3.0) 8.2 (5.8 to 10.7) Fatty Liver Index 34.0 (26.9) 44.3 (28.6) 59.4 (33.0) 10.3 (5.5 to 15.0) 25.4 (12.8 to 38.0) HOMA2-β 104 (31.8) 97.7 (31.9) 89.0 (48.4) −6.3 (-11.8 to -0.8) −14.9 (-29.7 to -0.2) HOMA2-­S 118 (52.1) 94.0 (43.4) 63.3 (26.7) −23.8 (-32.0 to -15.6) −54.4 (-76.3 to -32.6) HOMA2-­IR 1.03 (0.48) 1.33 (0.72) 2.16 (2.08) 0.3 (0.2 to 0.4) 1.1 (0.8 to 1.4) Mean (SD) and n (%). BMI, body mass index; DBP, diastolic blood pressure; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, glycated haemoglobin; HDL, high-­density lipoprotein cholesterol; HOMA2-ß, homeostatic model assessment-2 beta cell function; HOMA2-­ IR, homeostatic model assessment-2 insulin resistance; HOMA2-­S, homeostatic model assessment-2 insulin sensitivity; LDL, low-­density lipoprotein cholesterol; NG, normoglycaemia; PD, pre-­diabetes; SBP, systolic blood pressure; T-­cholesterol, total cholesterol. test, FLI and HOMA2-­IR, which were higher in individ- of pre-­diabetes increased with increasing age, with uals with pre-­diabetes than in individuals with normogly- percentages of 17.4%, 28.6%, 46.4%, 50% and 52.9% in caemia and were higher in the diabetic group than in the participants aged <35 years, 36 to 45 years, 46 to 55 years, pre-­diabetic group. On the other hand, physical activity, 56 to 65 years and >65 years, respectively. Regarding education level, eGFR, HOMA2-β and HOMA2-­S exhib- BMI categories of normal weight (BMI <25 kg/m2), over- ited a negative trend between the same groups. In the weight (BMI 25 to 29.9 kg/m2) and obese (BMI >30 kg/ pre-­diabetic group, 41.9% had impaired FPG and 81.7% m2), the prevalence of pre-­diabetes was 29%, 45.9%, and had impaired HbA1c. On the other hand, among the 49%, respectively (online supplementary file 1 figure 1). newly identified diabetic subjects, up to 80% met the FPG Table 2 shows the characteristics of pre-­diabetic indi- criteria and 85% met the HbA1c criteria. The prevalence viduals by glycaemic state: isolated FPG, isolated HbA1c 4 Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Table 2 Clinical and sociodemographic characteristics by glycaemic status of the individuals with pre-­diabetes HbA1c 5.7% to <6.5% Impaired HbA1c Impaired FPG and FPG 100 to P HbA1c P HbA1c P FPG vs 5.7% to <6.5% 100 to <126 mg/dL <126 mg/dL P overall vs FPG vs both both N 133 42 54 – – – – Sex, women 84 (63.2%) 19 (45.2%) 32 (59.3%) 0.12 0.181 0.74 0.369 Age, years 53.4 (12.4) 50.6 (11.8) 60.6 (10.5) <0.001 0.388 0.001 <0.001 BMI, kg/m2 25.8 (24.5 to 28.9) 27.8 (24.5 to 30.6) 27.5 (25.6 to 30.5) 0.056 0.534 0.036 0.534 BMI categories 0.018 0.107 0.05 0.032  Normal weight 43 (33.1%) 16 (41.0%) 8 (15.1%)  Overweight 64 (49.2%) 12 (30.8%) 30 (56.6%)  Obesity 23 (17.7%) 11 (28.2%) 15 (28.3%) Waist, cm 95.0 (88.0 to 102) 98.0 (90.0 to 106) 101 (95.0 to 107) 0.008 0.232 0.006 0.333 SBP, mm Hg 124 (16.1) 129 (15.5) 128 (18.4) 0.169 0.296 0.29 0.991 DBP, mm Hg 78.0 (9.44) 79.5 (12.0) 77.9 (9.39) 0.674 0.675 0.999 0.723 Hypertension 21 (15.8%) 9 (21.4%) 19 (35.2%) 0.014 0.542 0.019 0.32 Dyslipidaemia 25 (18.8%) 4 (9.52%) 10 (18.5%) 0.358 0.515 1 0.515 Family history DM 43 (34.1%) 18 (48.6%) 17 (35.4%) 0.265 0.471 1 0.471 Education, high level 91 (69.5%) 23 (59.0%) 31 (58.5%) 0.252 0.455 0.455 1 Physical activity 88 (67.2%) 21 (53.8%) 32 (60.4%) 0.281 0.547 0.68 0.68 Current smoker 38 (28.6%) 14 (33.3%) 11 (20.4%) 0.338 0.693 0.496 0.496 Alcohol, g/day 2.92 (0.00 to 15.2) 7.42 (0.90 to 16.3) 1.53 (0.00 to 17.9) 0.369 0.336 0.735 0.336 FPG, mg/dL 89.2 (6.89) 106 (4.97) 109 (5.96) <0.001 <0.001 <0.001 0.14 Protected by copyright. HbA1c, % 5.80 (5.70 to 6.00) 5.40 (5.40 to 5.57) 5.95 (5.80 to 6.10) <0.001 <0.001 <0.001 <0.001 HbA1c, mmol/mol 39.9 (38.8 to 42.1) 35.5 (34.7 to 37.4) 41.5 (39.9 to 43.2) <0.001 <0.001 <0.001 <0.001 2 eGFR, mL/min/1.73 m 93.6 (79.6 to 103) 93.2 (79.7 to 107) 89.3 (73.1 to 97.2) 0.076 0.556 0.073 0.073 Triglycerides, mg/dL 88.0 (72.0 to 134) 86.5 (67.0 to 130) 106 (74.5 to 132) 0.332 0.729 0.304 0.304 Total cholesterol, mg/dL 205 (34.5) 209 (28.6) 203 (29.8) 0.689 0.767 0.947 0.677 HDL-­cholesterol, mg/dL 58.0 (51.0 to 69.0) 52.0 (45.0 to 65.8) 57.0 (51.0 to 66.0) 0.128 0.141 0.755 0.18 LDL-­cholesterol, mg/dL 125 (32.2) 133 (25.5) 120 (23.5) 0.114 0.278 0.593 0.096 Insulin, µU/mL 8.00 (6.10 to 10.0) 9.90 (6.90 to 15.9) 10.9 (7.90 to 15.6) <0.001 0.01 <0.001 0.577 Fatty Liver Index 34.4 (16.9 to 59.2) 42.2 (17.7 to 73.6) 53.8 (32.2 to 73.0) 0.016 0.373 0.011 0.378 HOMA2-β 96.6 (81.5 to 122) 81.7 (64.5 to 118) 82.8 (63.0 to 108) 0.001 0.034 0.002 0.693 HOMA2-­S 98.0 (77.2 to 127) 75.0 (47.2 to 107) 67.5 (47.5 to 91.3) <0.001 0.003 <0.001 0.564 HOMA2-­IR 1.00 (0.80 to 1.30) 1.30 (0.90 to 2.15) 1.50 (1.10 to 2.10) <0.001 0.005 <0.001 0.545 Significant values are shown in bold. Mean (SD), median (IQR) and n (%). BMI, body mass index; DBP, diastolic blood pressure; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, glycated haemoglobin; HDL, high-­density lipoprotein; HOMA2-β, homeostatic model assessment-2 beta cell function; HOMA2-­IR, homeostatic model assessment-2 insulin resistance; HOMA2-­S, homeostatic model assessment-2 insulin sensitivity; LDL, low-­density lipoprotein; SBP, systolic blood pressure. and both altered FPG and HbA1c. Thus, among the 229 these differences were statistically significant. Finally, subjects with pre-­ diabetes, 42 (18.3%) had abnormal the isolated HbA1c group had an elevated HOMA2-β. isolated FPG, 133 (58.1%) had abnormal isolated HbA1c Although there were no statistically significant differ- and 54 (23.6%) had both abnormal FPG and HbA1c. ences, the proportion of men was higher in the isolated Patients with both abnormal FPG and HbA1c were older, FPG group, whereas the proportion of women was higher had larger waist circumferences, had increased FLI and in the isolated HbA1c and both FPG and HbA1c groups. HOMA2-­IR, were more likely to be overweight or obese Among the three groups, no statistically significant differ- and have hypertension and had lower HOMA2-­S. The ences were found regarding the following variables: sex, isolated FPG group had a higher proportion of subjects dyslipidaemia, family history of diabetes, education level, with a family history of diabetes, higher alcohol consump- physical activity, current smoking status, alcohol consump- tion, higher levels of total cholesterol and LDL-­cholesterol tion, triglycerides, total cholesterol, HDL-­cholesterol or and lower levels of HDL-­cholesterol, although none of LDL-­cholesterol. Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 5 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. Table 3 Outcomes at follow-­up of patients with different altered glucose metabolism statuses at baseline Follow-­up Variables Baseline N with follow-­up Normalised Persisted Progressed Pre-­diabetes 229 (39.3%) 166 (90.7%) 52 (41.6%) 112 (57.8%) 2 (0.6%) Isolated FPG 42 (7.2%) 3 (1.8%) 1 (33.3%) 1 (33.3%) 1 (33.3%) Isolated HbA1c 133 (22.8%) 114 (68.7%) 47 (41.3%) 67 (58.7%) 0 (0%) Both altered 54 (9.3%) 49 (29.5%) 4 (8.2%) 44 (89.8%) 1 (2%) FPG, fasting plasma glucose; HbA1c, glycated haemoglobin. Pre-diabetes follow-up Association of pre-diabetes with glycaemic status Of the 229 individuals with pre-­diabetes at baseline, 166 The multivariate logistic regression model of pre-­ (72.5%) had clinical and laboratory data after 12 months diabetes versus normoglycaemia showed that the vari- of follow-­up. Of them, 52 (41.6%) returned to a normal ables associated with pre-­diabetes were older age (OR; glycaemic status, 112 (57.6%) persisted in their state of 95% CI) (1.033; 1.011 to 1.056), higher physical activity pre-­diabetes and only 2 (0.6%) progressed to diabetes. levels (0.546; 0.360 to 0.827), higher BMI (1.121; 1.029 Table 3 shows the outcome of the follow-­up of the isolated to 1.222) and a family history of diabetes (1.543; 1.025 FPG, HbA1c and both FPG and HbA1c groups. to 2.323) (figure 2A). The models for isolated FPG Protected by copyright. Figure 2 Multivariate logistic regression models: (a) Model of pre-­diabetes versus normoglycaemic state in the Mollerussa cohort at baseline. Significant p values are shown in BOLD. Hosmer-­Lemeshow test p=0.295. (b) Model of normalised versus persisted in subjects with follow-­up data. Significant p values are shown in BOLD. Hosmer-­Lemeshow test p=0.931. eGFR, estimated glomerular filtration rate. 6 Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. alterations, isolated HbA1c alterations and both FPG and higher in older, overweight and obese participants.24 26 27 HbA1c alterations are shown in online supplementary file Many other studies found this relationship of age and obesity 2 tables 1, 2 and 3, respectively. The variables associated with the risk and incidence of diabetes.28–31 with isolated FPG were older age (1.032; 1.008 to 1.057), In the 1999 to 2002 National Health and Nutrition Exam- higher physical activity levels (0.535; 0.318 to 0.899) and ination Survey (NHANES), the prevalence of undiagnosed a family history of diabetes (1.798; 1.067 to 3.028). On the diabetes was 2.8%, and up to 26% of the participants had other hand, the only variable associated with impaired IFG.32 However, the age-­standardised prevalence of pre-­ HbA1c was older age (1.048; 1.029 to 1.067). Finally, in diabetes based on HbA1c and FPG combined was similar the model for altered FPG and HbA1c, the variables asso- in the periods between 1999 and 2002 and 2003 and 2006 ciated were older age (1.056; 1.026 to 1.086) and high FLI at 29.2% and 29.3%, respectively, but increased signifi- (1.031; 1.002 to 1.061). cantly to 36.2% in the period between 2007 and 2010.33 This prevalence continued to increase to as high as 38% Prediction of normalisation in 2012 among adults from the USA.25 The change in the Logistic regression model, as described in the methods prevalence of pre-­diabetes over time occurred because of section, starting with the variables age, sex, waist circum- a significant change in elevated HbA1c, whereas the preva- ference, BMI, hypertension, physical activity, family lence based on elevated FPG was similar over this period.33 history of diabetes, education level, total cholesterol, Thus, in our population, as in the NHANES study, HbA1c HDL-­cholesterol, FLI and HOMA2-­IR, was performed to was the most significant contributor to pre-­diabetes preva- identify factors independently associated with the predic- lence, followed by FPG, which is in concordance with the tion of glycaemic status normalisation (online supplemen- findings in the Caribbean population27 and discordant tary file 2 table 4). The variables that predicted glycaemic with the reports from the NHANES study between 2011 normalisation were older age (0.948; 0.916 to 0.982) and and 2014 in which they reported that FPG was the most BMI (0.779; 0.651 to 0.931) (figure 2B); this model had significant contributor to pre-­diabetes prevalence followed a good predictive ability (AUCROC 0.77; p<0.001) (online by HbA1c.34 Our results show that individuals with isolated supplementary file 3 figure 2). impaired HbA1c when diagnosed with pre-­diabetes might have a slightly better cardiometabolic risk profile than Protected by copyright. those with isolated FPG, while those individuals with both Discussion impaired FPG and HbA1c had the worst cardiovascular We found that the prevalence of undiagnosed diabetes was risk. These results are in line with the findings of the 3.4%, and the prevalence of pre-­diabetes was 39.3% in this prospective observational study in the primary care setting semi-­rural population in Catalonia (northeast Spain). The of a Spanish cohort with pre-­diabetes (PREDAPS) of our prevalence of pre-­diabetes was three-­fold higher based on group.35 36 HbA1c than that based on FPG. Subjects with pre-­diabetes Additionally, two meta-­analyses found that among indi- defined by both HbA1c and FPG criteria had unfavourable viduals with pre-­diabetes based on the ADA criteria, all-­ clinical and sociodemographic profiles related to increased cause and cardiovascular disease (CVD) mortality were cardiovascular risk. These factors were older age; abdom- increased37 and that the risk of cardiovascular disease inal obesity; higher triglycerides; increased FLI and a higher increased independently of the glucose assessment in proportion of overweight, obesity and hypertension. In our comparison to the risk of normoglycaemic subjects.38 population, age was the variable most strongly associated Moreover, a recent study concluded that those who with pre-­diabetes based on all specific glycaemic status vari- returned to normoglycaemia from FPG-­ defined or ables: isolated impaired FPG, isolated impaired HbA1c or HbA1c-­ defined pre-­ diabetes were not at reduced risk both impaired FPG and HbA1c. Other variables associated of future CVD or death.39 Studies of shorter duration, with pre-­diabetes were lower physical activity levels, a family over 3 to 5 years, have shown that approximately 25% of history of diabetes and obesity. Finally, the characteristics subjects progress to diabetes, 25% return to a normal state related to normalisation at follow-­up were younger age and of glucose tolerance and 50% remain in the pre-­diabetic lower BMI. state;16 after 1 year, 18.8% of subjects with pre-­diabetes The prevalence of pre-­diabetes and undiagnosed diabetes returned to normoglycaemia and approximately 30% in our healthy population were within the ranges found in with abnormal FPG, 29.1% with abnormal HbA1c and other population studies defining pre-­diabetes based on 7.6% with abnormalities in both FPG and HbA1c returned the 2010 ADA criteria, using FPG and/or HbA1c. Among to a normal state of glucose tolerance.40 In our findings these studies, a large national Chinese study (with 170 287 from a 1-­year follow-­up, the rate of reversion from pre-­ subjects) showed a prevalence of pre-­diabetes of 35.7% and diabetes to normoglycaemia was approximately 40%, and a prevalence of undiagnosed diabetes of 6.9%.26 In a study approximately 60% of participants remained in the pre-­ of the Caribbean population, the corresponding figures diabetic state. On the other hand, lifestyle modifications, were 44.1% for pre-­diabetes and 7.3% for undiagnosed such as weight loss and increased physical activity, among diabetes.27 In England, based on HbA1c levels, the pre-­ other factors associated with pre-­diabetes, reduced the diabetes prevalence was 35.5% in the adult population in risk of diabetes among these subjects.13 41 According to 2011.24 In these studies, the prevalence of pre-­diabetes was these reports, in our study, lower BMI was a factor that was Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 7 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. independently associated with the normalisation of the Author affiliations 1 glycaemic state, and an active lifestyle decreased the risk Primary Health Care Centre Cervera, Gerència d'Atenció Primaria, Institut Català de la Salut, Lleida, Spain of having pre-­diabetes. 2 Department of Medicine, University of Lleida & Biomedical Research Institute of The results of this study need to be interpreted in light Lleida, Lleida, Spain of its strengths and weaknesses. First, the number of partici- 3 Primary Health Care Centre Igualada Nord, Gerència d'Atenció Primaria, Institut pants in our study is smaller in comparison to other studies. Català de la Salut, Lleida, Spain 4 In addition, the study may not be representative of urban Department of Nutrition and Dietetics, Avantmedic, Lleida, Spain 5 Department of Endocrinology & Nutrition, University Hospital Germans Trias I Pujol areas in our region. Thus, the results may not be general- & Health Sciences Research Institute, Badalona, Spain isable to other territories with different population charac- 6 Unitat de Suport a la Recerca Lleida, Fundació Institut Universitari per a la Recerca teristics in our country. However, the Mollerussa cohort is a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), & CIBER of Epidemiology a representative sample of the region, which is a specific and Public Health (CIBERESP), Lleida, Spain 7 Department of Cardiovascular, Vall d'Hebron Research Institute, Barcelona, Spain semi-­ rural area that has never been specifically investi- 8 Primary Health Care Centre Tàrrega, Gerència d’Atenció Primaria, Institut Català de gated. Second, our study sample is probably healthier la Salut, Lleida, Spain than the general population, as we excluded subjects 9 Primary Health Care Centre Mollerussa, Gerència d'Atenció Primaria, Institut Català with already known diabetes and other comorbidities, a de la Salut, Lleida, Spain 10 lower number of subjects were counted in the denomi- Primary Health Care Centre Guissona, Gerència d'Atenció Primaria, Institut Català de la Salut, Lleida, Spain nator, thus resulting in a higher prevalence of this condi- 11 DAP-­Cat Group, Unitat de Suport a la Recerca Barcelona, Fundació Institut tion. Third, we did not assess glucose tolerance through Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina an oral glucose tolerance test, which is common in most (IDIAPJGol), & CIBER on Diabetes and Associated Metabolic Diseases (CIBERDEM), population studies. Although this assay is sensitive, it is Barcelona, Spain 12 also less specific for identifying subjects who could develop Primary Health Care Centre Raval Sud, Gerència d'Atenció Primaria Barcelona, Institut Català de la Salut, Barcelona, Spain diabetes.42 Furthermore, the oral glucose tolerance test has 13 Primary Health Care Centre La Mina, Gerència d'Atenció Primària Barcelona, a low reproducibility and is a rather time-­consuming and Institut Català de la Salut, Barcelona, Spain expensive procedure.9 43 Conversely, HbA1c and FPG are 14 DAP-­Cat Group, Unitat de Suport a la Recerca Barcelona, Fundació Institut cost-­effective and more convenient for patients. Currently, Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina Protected by copyright. FPG is an accepted screening method to detect diabetes (IDIAPJGol), Barcelona, Spain 15 Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau & and pre-­diabetes. HbA1c improves the sensitivity of FPG in Institut d’Investigació Biomédica Sant Pau (IIB Sant Pau), & CIBER on Diabetes and the detection of early T2D in high-­risk subjects32 44 and is a Associated Metabolic Diseases (CIBERDEM), Barcelona, Spain better predictor of CV events than FPG.45 Fourth, we only followed up those participants with pre-­diabetes. Thus, we Acknowledgements The authors thank Jordi Real for their valuable assistance could not analyse the probability of changing from normo- in conducting the statistical analysis. CIBER of Diabetes and Associated Metabolic Diseases is an initiative from Instituto de Salud Carlos III (Plan Nacional de I+D+I glycaemia to pre-­diabetes or diabetes in this study. Finally, and Fondo Europeo de Desarrollo Regional). it is probable that the use of the WHO pre-­diabetes criteria Contributors MF, EC and DM conceived and designed the study; MBV, JFN and in our study would have resulted in a smaller proportion MMC participated in the study design; MBV, MF, NA, MGC, NM, AM and CC collected of subjects who returned to a normal glycaemic state. The the data; EC and JRM performed the statistical analyses; MF, EC, MMC and DM WHO established a normal concentration of FPG between wrote the manuscript. All authors critically reviewed the manuscript and approved the final version to be published. 110 and <126 mg/dL.46 Funding This study was funded by Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol). Conclusions Competing interests None declared. For the first time, our study provides information on the Patient consent for publication Not required. prevalence of diabetes and pre-­diabetes in the Mollerussa healthcare area, a Mediterranean semi-­ rural area in Ethics approval The project was approved by the Ethics Committee of the Primary Health Care University Research Institute (IDIAP) Jordi Gol (PI12/043) Barcelona, northeast Spain. Individuals with pre-­diabetes had a more Spain. unfavourable cardiometabolic risk profile than normogly- Provenance and peer review Not commissioned; externally peer reviewed. caemic subjects. Moreover, individuals with abnormalities Data availability statement Data are available upon reasonable request. Readers in both criteria used to diagnose pre-­diabetes had the worst may contact Dr Didac Mauricio (​didacmauricio@​gmail.​com) regarding the data. risk profile. Finally, after 1 year of follow-­up, few people Open access This is an open access article distributed in accordance with progressed to diabetes, while more than 40% returned to the Creative Commons Attribution Non Commercial (CC BY-­NC 4.0) license, a normal glycaemic state and nearly 60% persisted in the which permits others to distribute, remix, adapt, build upon this work non-­ pre-­diabetic state. These results suggest that the use of both commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made FPG and HbA1c criteria in clinical practice could help indicated, and the use is non-­commercial. See: http://​creativecommons.​org/​ identify people with high diabetes and cardiovascular risk. licenses/​by-​nc/​4.​0/. Moreover, the identification of individuals with pre-­diabetes ORCID iDs provides an opportunity for intervention through lifestyle Manel Mata-­Cases http://​orcid.​org/​0000-​0003-​3693-​3622 modification and pharmacological treatments not only to Esmeralda Castelblanco http://​orcid.​org/​0000-​0002-​2061-​6270 reduce the development of diabetes. Didac Mauricio http://​orcid.​org/​0000-​0002-​2868-​0250 8 Falguera M, et al. BMJ Open 2020;10:e033332. doi:10.1136/bmjopen-2019-033332 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033332 on 20 January 2020. Downloaded from http://bmjopen.bmj.com/ on October 24, 2023 at Univesity Autonomous of Barcelona. References 25 Menke A, Casagrande S, Geiss L, et al. Prevalence of and trends 1 Olson DE, Rhee MK, Herrick K, et al. Screening for diabetes and in diabetes among adults in the United States, 1988-2012. JAMA pre-­diabetes with proposed A1C-­based diagnostic criteria. Diabetes 2015;314:1021–9. 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