Phase Angle and Body Composition in Long-term Type 1 Diabetes in Adults: A comparative study in a Brazilian Public Reference Outpatient Clinic

Phase Angle and Body Composition in Long-term Type 1 Diabetes in Adults: A comparative study in a Brazilian Public Reference Outpatient Clinic | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Phase Angle and Body Composition in Long-term Type 1 Diabetes in Adults: A comparative study in a Brazilian Public Reference Outpatient Clinic Natália Fenner Pena, Virginia Capistrano Fajardo, Lívia Froes, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4802871/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2024 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted 10 You are reading this latest preprint version Abstract Introduction: Type 1 Diabetes Mellitus (DM1) is a disease that affects a small percentage of the population. Nevertheless prevalence is currently growing, with alarming data on lack of control. The importance of body composition and Phase Angle (PA) as assessed by Bioelectrical Impedance (BIA) in long term DM1 patients lies in the fact that alterations in cellular integrity and body compartments may affect risk profiles and metabolic control. The objective of this study was to compare different PA and body composition parameters in a sample of adults with DM1, with healthy controls. Methods: A comparative study was carried out in a state public university outpatient clinic, including a cohort of adult patients of both sexes, diagnosed with DM1, and a control group matched by age and sex, in a 2:1 ratio. Anthropometric measurements included weight, height and BMI. From the raw bioelectrical impedance data of Resistance and Reactance, Fat-Free Mass (FFM), Fat Mass (FM), Fat-Free Mass Index (FFMI), Fat Mass Index (FMI), PA and standardized PA (SPA) were calculated. Means or medians were compared. Regression models were used to show distinguishing characteristics of both groups or to disclose associations within the diabetic group (HbA1c, disease duration, presence of microvascular complications, capillary blood glucose, BMI and FMI). Results: 88 patients with Type 1 Diabetes and 46 healthy controls were evaluated. PA was lower in diabetics (6.05 vs 6.85, p = 0.000), as well as SPA (-1.47 vs -1.36, p = 0.000). Diabetics displayed higher adiposity (%FM = 29.6 vs 27.6, p = 0.016; FMI = 7.00 vs 6.33, p = 0.016) and lower %FFM. Most of the differences were maintained after sex stratification and diabetic man disclose a lower FFMI than male controls (18.2 vs 20.16, p = 0.029). Conclusion: Patients with DM1 present greater nutritional risk and worse cell membrane integrity when assessed by PA. Significant body composition differences among groups and between sexes were highlighted, with data showing greater adiposity in diabetic women and diabetic men displaying lower muscle mass. These findings suggest the importance including PA and body composition evaluation in the multidisciplinary clinical outpatient follow-up of patients with Type 1 Diabetes, in an attempt to obtain better metabolic control and consequently, a better prognosis. Body Composition Bioimpedance Phase Angle Type 1 Diabetes Figures Figure 1 INTRODUCTION There is an increasing interest in the evaluation of body composition in adult diabetic patients. So far, there has not been many studies on distinct Bioelectrical Impedance (BIA) either direct or derived parameters in patients with Type 1 Diabetes (DM1) with long standing disease. In different countries, evidence indicates that people with DM1, especially children and teenagers, display higher levels of adiposity, more intense weight gain and lower Phase Angle (PA) than healthy controls. Phase angle is a direct BIA measurement that can indicate early alterations at cellular level and may thus become an important tool in the evaluation of a patient’s general health ( 6 , 7 , 8 ). BIA derived parameters, such as body fat percentage (%BF) and fat free percentage (%FF), may offer meaningful information about body composition and metabolism, since alterations in body compartments may affect risk profiles and metabolic control ( 1 , 2 , 3 , 4 , 5 ). This type of information may be acquired during routine outpatient clinical assessment and benefit both the patient and the healthcare professional, as it can result in more assertive information with implications for prevention, helping clinical control and prognosis modification ( 8 , 9 , 10 , 11 , 12 ). Since the DCCT study, weight gain and serum lipid levels in diabetics have been related with inadequate eating practices, excess carbohydrates, lack of physical activity and exogenous insulin administration ( 5 , 10 ). Excess body weight can result from different sources – be it from adipose tissue or, inversely, from muscle hypertrophy; obese individuals with high body mass index (BMI), on the other hand, may present low muscle mass. Usually, healthcare professionals employ only the BMI to evaluate obesity during outpatient anthropometric evaluation ( 13 , 14 ). However, this does not accurately measure adiposity, nor presents a detailed evaluation of body composition, including fat mass and fat-free mass ( 18 ). In diabetic patients, such shortcomings are critical because increased fat deposition is associated with insulin resistance, while muscle mass plays an important role on general health and metabolic regulation. Attention should be directed to the fact that body composition absolute values in kilograms and percentages (fat mass and fat-free mass) may not reflect specific changes in these compartments; parameters that take into consideration body size, such as fat mass and fat-free mass indexes (FMI and FFMI), might also have an important role ( 18 , 19 , 28 ). BIA derived FFMI has been used as criteria to define sarcopenia, and is strongly correlated with appendicular muscle mass as measured by dual energy X-ray absorptiometry (DEXA). Although DEXA is considered to be the golden standard in assessing body composition, its applicability in clinical outpatient settings, especially public ones, is limited by its cost, radiation exposure and portability ( 19 , 23 ). Conversely, BIA – despite its limitations, such as the lack of precision to calculate body water in different conditions, including diabetes – is considered a safe and practical device to monitor body composition. Based on the basic principle that body fluids and electrolytes conduct low tension electricity ( 15 , 16 , 19 , 26 , 27 ), it has the additional advantages of being not only accessible and low cost, but also reliable and non invasive. Although some predictive BIA equations are not population specific, it may provide an assessment of body composition through the directly obtainable parameters of reactance and resistance ( 25 ). According to the Brazilian Diabetes Society (SBD,2024), the treatment of Type 1 Diabetes is multidisciplinary. Each individual, together with his/her family members and healthcare team, must be actively engaged in self-management and treatment planning, including the collaborative development of a dietary plan, in which the distribution of carbohydrates should preferably be individualized, providing better weight, glycemic and general metabolic control ( 43 ). Latest data from International Diabetes Federations (IDF, 2023) indicate that only 1.52 million of the 8.75 million people living with Type 1 Diabetes worldwide in 2022 were under the age of 20; therefore, the lack of available data for the adult population presents an evident gap in research ( 44 ). Also according to data from the IDF, the life expectancy of a person with Type 1 Diabetes in countries such as Brazil can be around 15 years lower than that observed in people with DM1 in developed countries, indicating the need for better health initiatives, attention and treatment. DM1 is a chronic autoimmune disease, and its management has been associated with significant changes in body composition. The main objective of this study is to explore these changes in a cohort of long standing DM1 patients followed at a public university outpatient reference clinic, in an attempt to contribute to the understanding of their role in the health of this specific group of patients. BIA direct (phase angle, standardized phase angle) and indirect parameters (percentage of fat-free mass, percentage of fat mass, fat-free mass index and fat mass index) were compared in long standing DM1 outpatients and normal controls. Knowledge of differences in body composition of diabetics may be of critical importance, since they may be related to the present health and organ integrity, as in the case of PA and SPA, or to metabolic control and prognosis in the case of fat-free mass and fat mass parameters. METHODS This is a comparative study, carried out in a reference public university outpatient clinic, which included a cohort of adult patients of both sexes with diagnosed DM1, and a control group matched by age and sex, on a 2:1 basis. Data were collected from March 2020 to March 2023. Patients or their proxies and controls signed the Informed Consent Form (FICF) previously approved by the Institutional Ethics Research Committee. Exclusion criteria were age under 18; bedridden patients or with a disability that made it impossible to properly place BIA electrodes; hypersensitivity to electronic devices; chronic kidney disease (CKD) on dialysis; cardiovascular disease in use of a pacemaker; anemia; edematous states; heart failure; nephrotic syndrome; cirrhosis; and pregnancy. Control group volunteers were recruited among medical students and university personnel. Diabetic patients were assessed as part of a nutritional appointment, which included HbA1c result, BIA analysis and capillary blood glucose, in addition to other nutritional parameters (weight, height, body mass index). It also counted on a structured questionnaire that included health background, time of diagnosis, food intake record, average 24-hour consumption of carbohydrates, and presence of diabetic microvascular complications (the presence or any association of retinopathy, neuropathy or non-nephrotic nephropathy). Controls received anthropometric and BIA evaluation. Nutritional Status Assessment Weight and height were obtained with a Tanita® scale by means of adequate and standardized procedure. Body mass index (BMI) was calculated by the standard WHO formula of weight/height² (Who Expert Committee on Physical Status 1995). Bioelectrical Impedance (BIA) Low intensity (800 µA), single frequency (50 kHz) BIA analysis was performed (Quantum X device, RJL systems, 2007). Resistance (R), reactance (Xc), and PA values were obtained by the Body Composition software as proposed by the device manufacturer. A standard procedure was employed, including position of body and members, removal of metals in contact with skin, cleansing with alcohol, and location of electrodes (Kyle 2004; WHO Expert Committee on Physical Status 1995). Standardized PA (SPA) was calculated according to the following Eq. (5): SPA = measured [PA – mean PA (for age and gender)] / population standard deviation for age and gender Fat free mass (FFM) was obtained through the Body Composition Program of the BIA device, according to the following formula: FFM = -4.104 + (0.518 × height 2 /resistance) + (0.231 × weight) + (0.130 × reactance) + (4.229 × sex); men = 1, women = 0; ( 30 ) Fat-free mass percentage (%FFM) was calculated by dividing FFM (kg) by weight (kg). Fat-free mass index (FFMI) was calculated according to the following formula: FFMI = FFM/ height 2 ( 18 ) Glycated Hemoglobin (HbA1C) HbA1C concentrations were measured from blood plasma by methods certified by the National Glycohemoglobin Standardization Program (NGSP). Statistical Analysis Data were presented as absolute and relative frequencies and mean ± SD (standard deviation) or median and percentiles, depending on the distribution as verified by the Shapiro-Wilk test. Besides comparison of means and medians between groups, logistic regressions were carried out with DM1 and control group as dichotomous outcomes in order to verify, within the studied sample, which factors are clearly associated with one of the outcomes. Receiver operating characteristic (ROC) curves were also performed to evaluate the behavior of PA and SPA in distinguishing between diabetics and controls and possible cutoffs associated with a higher probability of belonging to the DM1 group. Linear regression was used in the DM1 group to evaluate the association between the independent variables (HbA1c, duration of disease, presence of microvascular complications, capillary blood glycemia on the day of BIA application, BMI and FFMI) with PA ( 26 ). Due to their strong collinearity, different models were performed separately for BMI and FFMI. Analyses employed the package SPSS®19.0 (Chicago: SPSS Inc. IBM Corp) and considered a significance level of 5%. Sample size calculation (G*Power 3.1.9.4) assumed an effect size of 0.47 for the difference of PA means between a DM1 and a control group ( 5 ), a power of 80%, and an alpha error of 0.05, resulting in a sample size of 43 (controls) e 85 (cases). RESULTS A cohort of 88 patients with long-term Type 1 DM (21.2 + 9.3 years) was compared with a group of 46 controls, matched by sex and age (Table 1 ). Most diabetic patients were uncontrolled according to HbA1c levels (8.96 + 2.09%), and 44.5% had microvascular complications. Table 1 Demographic and Clinical Data DM1 ( n = 88) C ( n = 46) p Age* 36.2 ± 11.3 36.0 ± 11.7 .914 Duration* (min- max) 21.2 ± 9.3 (5–48) - - HbA1C* (min- max) 8.57 ± 1.84(5.50–15.50) - - Complications** 40 (44.5%) - - F M p F M p Sex** 47 (53.4%) 41 (46.6%) - 29 (63.0%) 17 (37.0%) .285 Age 33.1 ± 8.0 39.7 ± 13.3 0.006 34.0 ± 9.2 39.2 ± 14.9 .205 Duration 20.7 ± 9.6 21.8 ± 9.0 0.574 - - - HbA1C* 8.96 ± 2,09 8.12 ± 1.40 0.032 - - - Complications** 19 (40.4%) 21 (51.2%) 0.310 - - * = Student’s T test; ** = Chi square BIA parameters displayed significantly higher PA and SPA medians in the control group (Table 2 ; Fig. 1 ), and significant differences in body composition were observed. Fat-free mass was lower, according to %FFM, and body fat higher in diabetics, according both to %FM and FMI (Table 2 ). When groups are stratified by sex, differences in PA and SPA remained significant, and differences in body composition seemed to be due mainly to a lower percentage of FFM and a higher percentage of FM observed in diabetic women. When FMI was employed, a higher fat content in diabetic women, but not in diabetic men (as with fat mass percentage) was confirmed. A lower fat-free mass content in diabetic men as measured by FFMI; the same was not observed in diabetic women (Table 2 ). Table 2 BIA parameters in Diabetics and Controls DM1 Controls p** BMI* 23.39 23.44 0.175 PA* 6.05 6.85 0.000 SPA* -1.47 -0.36 0.000 %FFM* 70.40 72.40 0.016 %FM* 29.60 27.60 0.016 FFMI* 16.62 16.69 0.653 FMI* 7.00 6.33 0.016 F M DM1(47) C ( 29 ) p** DM1( 41 ) C ( 17 ) p** BMI* 23.19 22.53 0.015 23.47 24.86 0.140 PA* 5.50 6.65 0.000 6.70 8.16 0.000 SPA* -1.63 -0.48 0.000 -1.42 -0.03 0.000 %FFM* 65.10 71.20 0.000 74.30 74.60 0.505 %FM* 34.90 28.8 0.000 25.70 25.40 0.505 FFMI* 15.41 16.08 0.987 18.02 20.16 0.029 FMI* 8.21 6.30 0.001 6.13 6.36 0.713 BMI = body mass index; PA = phase angle; SPA = standardized phase angle; %FFM = percentage of fat-free mass; %FM = percentage of fat mass; FFMI = fat-free mass index; FMI = fat mass index; *median; **Mann Whitney test Results of PA and SPA among groups are illustrated in Fig. 1 , below. A logistic regression was carried out to assess the effect of PA or SPA on the likelihood of belonging to DM1 or control groups. Different models were employed for both parameters. The models were controlled for age and sex, and different parameters of body composition (%FFM, %FM, FFMI and FMI) were entered in separate models, along with PA (or SPA), age and sex. Both PA and SPA were associated with a high discriminatory capacity. The OR (Exp(B)) for PA remained consistent at approximately 0.2 between different models, with CI ranging from approximately 0.100 to 0.400 and p values of 0.000, indicating an 80% reduction in the chances of being part of the DM1 group for every 1 unit increase in PA. Similarly, for SPA, OR remained stable around 0.25, with CI ranging between 0.140 to 0.450, with p values of 0.000, indicating a 75% reduction in the chance of being part of the DM1 group for every 1 unit increase in SPA. The overall models were statistically significant when compared to the null model and explained from 38–46% of the group allocation for PA and from 39–46% for SPA. The models correctly predicted around 80% of cases in both PA and SPA models. Among body composition variables also entered in the models, FMI, but not %FFM or FFMI, showed a discriminatory capacity between diabetics and controls, both in the PA (OR: 1.327; IC: 1.118–1.574; p = 0.001) and SPA (OR: 1.325; IC: 1.114–1.575; p = 0.001) models, indicating a 30% higher chance of belonging to DM1 group for each 1 kg/m 2 increase in FMI. ROC curves for both PA (AUC = 0.719, 0.629–0.808, p = 0.000), and especially for SPA (AUC = 0.805, 0.729–0.881, p = 0.000), also illustrate the discriminatory capacity. Among control patients, only 9 (19,6%) had SPA values below the cutoff of -1.145 obtained with the Youden method, while 58 (65.9%) diabetics displayed SPA below that threshold. Only 3 (6.5%) control patients displayed SPA below the threshold of -1.65, considered the 5th percentile of Brazilian population, while 41(46.6%) had results below this. Linear regression models were employed in the DM1 group to analyze association of clinical and anthropometric data (sex, age, duration of disease, rate of microvascular complications, anthropometric variables, HbA1c and capillary blood glycemia) with PA or SPA. No statistically significant association was demonstrated between HbA1C levels and PA or SPA. DISCUSSION This work aimed to evaluate PA and body composition in adult DM1 patients with long-term disease in comparison to healthy individuals, matched according to age and sex. It is known that DM1 is associated with an elevated risk of complications, and that poor metabolic control as determined by HbA1c is correlated with different acute and chronic complications. Body composition and PA have not been thoroughly evaluated in the group with long standing adult DM1. PA is calculated from the direct BIA measurements of resistance (R) and reactance (Xc). Data on PA evaluation in diabetics are scarce and have not been studied in the Brazilian population. Results showed lower PA values, as observed in younger diabetics with DM1. In children and adolescents with recently diagnosed diabetes, N’Samba et al. found significantly lower PA values in comparison to healthy controls (4.85 ± 0.86 vs. 5.62 ± 0.81, p < 0.001). Buscemi, studying patients with both DM1 and DM2, found significantly lower PA values in young male patients with DM1, but not in females. In the present study, when PA values were adjusted for age and sex, by either logistic regression or the use of SPA, the difference between diabetics and controls in both sexes remained significant. A thorough search in different databases (PubMed, Scopus, EMBASE) for studies using SPA in diabetic patients showed that it had not been employed in diabetes, and the present results indicate its potential usefulness. Among control patients, 6.5% displayed values below the SPA threshold of -1.65, which corresponds to the 5th percentile of the Brazilian population, in comparison to 46.6% of diabetics. Besides confirming lower PA values in diabetics in general, the study is in agreement with others that show lower values in diabetic women (Dittmar et al. ( 23 ). This is probably related to the body composition, with a lower amount of fat-free mass. Contrary to our initial hypothesis, an association between PA and HbA1c values could not be demonstrated, possibly because the study was not powered enough for this. Ditmar et al ( 23 ) found an inverse relationship between these parameters that was attributed to catabolism and disease duration. We have demonstrated an inverse association between disease duration and PA, as well as lower fat-free mass as expressed by FFMI in diabetic men. However, no significant relationship with HbA1c levels could be established. The sample was mainly composed of uncontrolled patients. which may have prevented conclusions that could have been obtained with the presence of better controlled ones. In relation to body composition, important differences between diabetics and controls were observed. DM1 patients had an excess of fat mass, both in terms of %FM and FMI, mainly due to the female component of the sample. Body fat increases substantially in girls during puberty, and may be especially marked in girls with diabetes ( 40 , 41 ). This finding may be related to the multiple dose insulin regimens, carbohydrate-rich diets and possibly to the inflammatory activity and insulin resistance/metabolic syndrome, which result in low muscle mass, increased fat mass and poor diabetic control as evaluated by HbA1c ( 40 , 41 , 42 ). A lower muscle mass in diabetic man was shown, which is another feature that has been associated with fat mass increase in DM1. According to Szadkowska et al , DM1 patients are characterized by increased fat mass and put on more weight than controls. These alterations in body composition may determine a future impact on overall health with different metabolic derangements, such as dyslipidemia, arterial hypertension, sarcopenia and insulin resistance. Muscle mass reduction results in a significant impact on insulin sensitivity, glucose and lipid processing and basal metabolic rate, with consequences on metabolic stability in DM1. A recent study ( 38 ) carried out with patients with Type 1 Diabetes from the same research group has highlighted the need for attention to women's metabolic care and body composition, since female patients displayed higher cardiovascular risk than male patients, contrary to usual expectations ( 39 ). The discrepancy observed in the study by (de Araújo F.M et al. , 2024) was explained by the high prevalence of chronic complications in the sample, mainly diabetic retinopathy, a factor that categorizes a patient as having high cardiovascular risk (SBEM - Brazilian Society of Endocrinology and Metabology). Furthermore, women had a higher prevalence of diabetic kidney disease, as well as worse glycemic control and slightly higher levels of LDL cholesterol, which could justify a higher proportion of female patients classified as high cardiovascular risk when evaluated by the Steno T1 Risk Engine (ST1RE), used to predict cardiovascular events in patients with DM1 ( 38 ). Whether these observations could be explained by body composition alterations that may be more profound in women than in men remain to be further clarified. That said, this seems to be an important line of investigation, with some evidence pointing towards this direction ( 29 ). This is a challenging topic, where definite conclusions are lacking, and additional studies with the development of body composition evaluation protocols may contribute to a better metabolic control for the population with Type 1 Diabete CONCLUSION Patients with long-term DM1 present lower PA. In terms of body compartment percentages, diabetics displayed higher fat mass and lower fat-free mass. When corrected by body size, diabetics displayed higher fat mass than controls. Significant body composition differences between sexes were highlighted, with data showing greater adiposity in diabetic women in relation to female controls, and diabetic men displaying lower fat-free mass corrected by height in relation to male controls. These findings indicate the importance of a careful body composition evaluation and follow-up. The aim is to contribute to a better metabolic control and prognostic modification, considering both the extensive body of information on the effects of long-term Type 1 Diabetes, and the data from this and other studies relating duration of disease with PA, a marker of general health. Multidisciplinary outpatient follow-ups should benefit from this approach. Declarations Competing interests All authors declare that they have no conflicts of interest. All patients accepted the Free and Informed Consent Form, previously approved by the University Ethics Committee (UFMG), according to the CAEE (Number: 57752922 2 0000 51 49) previously informed in this study. We have no other funding for this article. Ethical Approval All patients signed and agreed to the terms of consent for participation and also the consent to publish the study. CAEE (Number: 57752922 2 0000 51 49) approval number by the Federal University of Minas Gerais: Authors' contributions Fenner-Pena N had the original study idea, wrote the study proposal and protocol, developed the manuscript, measured the study, and provided training. Fajardo VC evaluated based on data analysis. Froes L- Endocrinologist at the UFMG Diabetes League - participation in data collection. Brazil. Carvalho PAM - technical collaboration on Bioelectrical Impedance data. Brazil. Lauria M. W- Doctoral Coordinator of the UFMG Diabetes League - Participant in all development and projects. Brazil. Torres H. G- Advisor of the Post-Medicine Program - UFMG - participant in all development and projects. Brazil. All authors were conscientious and contributed to the text of these manuscripts. Funding Fenner-PenaN and Fajardo VC have support from the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES-BR) - Financial Code 001 for a doctoral scholarship. 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J Pediatr Gastroenterol Nutr. 2006;44:130–5. https://doi.org/10.1097/01.mpg.0000237935.20297.2f Dittmar M, Reber H, Kahaly GJ. Bioimpedance phase angle indicates catabolism in Type 2 diabetes. Diabetic Medicine . 2015 Sep 1;32(9):1177–85. https://doi.org/10.1111/dme.12710 Sun, S.S.; Chumlea, W.C.; Heymsfield, S.B.; Lukaski, H.C.; Schoeller, D.; Friedl, K.; Kuczmarski, R.J.; Flegal, K.M.; Johnson, C.L.; Hubbard, V.S. Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys. Am. J. Clin. Nutr. 2003, 77, 331–340. Garlini, L.M.; Alves, F.D.; Ceretta, L.B.; Perry, I.S.; Souza, G.C.; Clausell, N.O. Phase angle and mortality: A systematic review. Eur. J. Clin. Nutr. 2019, 73, 495–508. Brizzolara, A.; Barbieri, M.P.; Adezati, L.; Viviani, G.L. Water distribution in insulin-dependent diabetes mellitus in various states of metabolic control. Eur. J. Endocrinol. 1996, 135, 609–615. Garcia, PB; Lavado-García, JM; Morán, JM; Leal-Hernández, O.; Canal-Macías, ML; Aliaga, I.; Zamorano, JDP Composição corporal e análise vetorial de impedância bioelétrica em crianças em tratamento com valproato: Um estudo piloto//Composição corporal e análise vetorial de bioimpedância em crianças em tratamento com ácido valproico: Estúdio piloto. Investigue. Clínica 2019 , 60 , 182–192. Thomas EL, Frost G, Taylor-Robinson SD, Bell JD. Excess body fat in obese and normal-weight subjects. Nutr Res Rev 2012; 25: 150-161 [PMID: 22625426 DOI: 10.1017/S0954422412000054] Zeng Q, Chen XJ, He YT, Ma ZM, Wu YX, Lin K. Body composition and metabolic syndrome in patients with type 1 diabetes. World J Diabetes 2024; 15(1): 81-91 Kyle UG, Genton L, Karsegard L, Slosman DO, Pichard C. Single prediction equation for bioelectrical impedance analysis in adults aged 20--94 years. Nutrition. 2001 Mar;17(3):248-53. doi: 10.1016/s0899-9007(00)00553-0 Davis, N.L.; Bursell, J.D.; Evans, W.D.; Warner, J.T.; Gregory, J.W. Body composition in children with type 1 diabetes in the first year after diagnosis: Relationship to glycaemic control and cardiovascular risk. Arch. Dis. Child. 2012, 97, 312–315. Szadkowska, A.; Madej, A.; Ziółkowska, K.; Szyma ´nska, M.; Jeziorny, K.; Mianowska, B.; Pietrzak, I. Gender and Age—Dependent effect of type 1 diabetes on obesity and altered body composition in young adults. Ann. Agric. Environ. Med. 2015, 22, 124–128. [CrossRef] [PubMed] Purnell, J.Q.; Zinman, B.; Brunzell, J.D.; DCCT/EDIC Research Group. The effect of excess weight gain with intensive diabetes mellitus treatment on cardiovascular disease risk factors and atherosclerosis in type 1 diabetes mellitus: Results from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC) study. Circulation. 2013, 127, 180–187. [CrossRef] [PubMed] DCCT Research Group. Weight gain associated with intensive therapy in the Diabetes Control and Complications Trial. Diabetes Care 1988, 11, 567–573. [CrossRef] Zeng Q, Chen XJ, He YT, Ma ZM, Wu YX, Lin K. Body composition and metabolic syndrome in patients with type 1 diabetes. World J Diabetes 2024; 15(1): 81-91 [PMID: 38313851 DOI: 10.4239/wjd.v15.i1.81] Gubitosi-Klug, R.A.; DCCT/EDIC Research Group. The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study at 30 years: Summary and future directions. Diabetes Care. 2014, 37, 44–49. [CrossRef] Pena NF, Mauricio SF, Rodrigues AMS, Carmo AS, Coury NC, Correia MITD, Generoso SV. Association Between Standardized Phase Angle, Nutrition Status, and Clinical Outcomes in Surgical Cancer Patients. Nutr Clin Pract. 2019 Jun;34(3):381-386. doi: 10.1002/ncp.10110. Epub 2018 Jun 5. Erratum in: Nutr Clin Pract. 2019 Aug;34(4):643. doi: 10.1002/ncp.10361. PMID: 29870080. de Araujo, F.M., Comim, Fenner-Pena. N., Lauria, M., et al. A comparative study of cardiovascular risk stratification methods in type 1 diabetes mellitus patients. Diabetol Metab Syndr 16 , 10 (2024). https://doi.org/10.1186/s13098-023-01224-5. Estande GL, Kapral MK, Fung K, Tu JV. Relação entre idade e doença cardiovascular em homens e mulheres com diabetes comparados com pessoas não diabéticas: um estudo de coorte retrospectivo de base populacional. Lanceta. 2006;368(9529):29–36. Tuvemo T, Kobbah M, Proos LA. Growth and subcutaneous fat during the first fi ve years of insulin-dependent diabetes in children. Acta Paediatr Suppl 1997;418:1–5. Nuoffer JM, Kuhlmann B, Hodler C, et al. [Eating behavior, diabetes and weight control in girls with insulin-dependent diabetes mellitus (type 1)]. Schweiz Med Wochenschr 1996;126:1560–5. Pietiläinen KH, Virtanen SM, Rissanen A, et al. Diet, obesity, and metabolic control in girls with insulin dependent diabetes mellitus. Arch Dis Child 1995;73:398–402. Tarcila Ferraz de Campos, Silvia Ramos, Letícia Fuganti Campos, Débora Bohnen Guimarães, Deise Regina Baptista, Daniela Lopes Gomes, Débora Lopes Souto, Maristela Strufaldi, Marlice Marques, Natália Fenner Pena, Sabrina Soares de Santana Sousa. Terapia Nutricional no Diabetes tipo 1. Diretriz Oficial da Sociedade Brasileira de Diabetes (2024). DOI: 00.00000/00000000.0000-0, ISBN: 000-00-0000-000-0. IDF, ATLAS REPORTS. Type 1 diabetes estimates in children and adults – 2022. Type 1 diabetes numbers in children and adults Authors: Graham D Ogle ¹, Fei Wang ¹, Gabriel A Gregory ¹ and Jayanthi Maniam ¹ ¹ T1D Index consortium. Disponível em: www.diabetesatlas.orgType. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2024 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted Editorial decision: Revision requested 25 Aug, 2024 Reviews received at journal 24 Aug, 2024 Reviews received at journal 22 Aug, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviewers agreed at journal 04 Aug, 2024 Reviewers invited by journal 01 Aug, 2024 Editor assigned by journal 31 Jul, 2024 Submission checks completed at journal 31 Jul, 2024 First submitted to journal 25 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4802871","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344804946,"identity":"1425d77d-1401-4738-996f-98a3f49af024","order_by":0,"name":"Natália Fenner Pena","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIiWNgGAWjYLCCBwYMDOwNELYciDjwAK96ZgaGBKAWngMQrjFYSwJBLQwILYlg2/BpMWc/f/BDQoEdAw9777EHH/fcSZ8fdvgh0BY7Od0G7Fose5KZJRIMkhl4eM6lG8549ix34+00A6CWZGOzA9i1GBxIZgBqYWawl8gxk+Y5cDh34+wEkJYDidtwaTn/mPlHgkE9A4/8GzPpPwcOpxvOTv+AX8uNZDagLYcZeCR4zKQZDhxOkJfOIWDLjcdmFgkGx3l4eHLMJHsOPDPcIJ1TcADoO9x+OZ/4+MaHP9VyPOxnzCR+HLgjLz87ffOHDxV2cri0wAAPlD4ADBCwUfiVI4MDDPINxKseBaNgFIyCkQEA2PNhzw92SIkAAAAASUVORK5CYII=","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":true,"prefix":"","firstName":"Natália","middleName":"Fenner","lastName":"Pena","suffix":""},{"id":344804947,"identity":"1b537421-1366-422d-909a-cbe2f54d7b2e","order_by":1,"name":"Virginia Capistrano Fajardo","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Virginia","middleName":"Capistrano","lastName":"Fajardo","suffix":""},{"id":344804950,"identity":"be9c575d-6dbc-412c-8c1a-4749b36d61d8","order_by":2,"name":"Lívia Froes","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Lívia","middleName":"","lastName":"Froes","suffix":""},{"id":344804951,"identity":"f88c05de-56e8-433d-8d30-804fb3cf2bbf","order_by":3,"name":"Paulo Augusto Miranda Carvalho","email":"","orcid":"","institution":"Grupo Santa Casa de Belo Horizonte","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"Augusto Miranda","lastName":"Carvalho","suffix":""},{"id":344804952,"identity":"60219885-4884-453c-86d6-f77152632a21","order_by":4,"name":"Márcio Weissheimer Lauria","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Márcio","middleName":"Weissheimer","lastName":"Lauria","suffix":""},{"id":344804953,"identity":"e33c785d-d134-4e50-a85e-985a00b53b70","order_by":5,"name":"Henrique Oswaldo da Gama Torres","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Henrique","middleName":"Oswaldo da Gama","lastName":"Torres","suffix":""}],"badges":[],"createdAt":"2024-07-25 15:17:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4802871/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4802871/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13098-024-01485-8","type":"published","date":"2024-11-13T15:58:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64008458,"identity":"576ed2d6-623e-4930-8c07-53d1f6b49953","added_by":"auto","created_at":"2024-09-04 22:57:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32852,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot of PA and SPA in DM1 and control groups\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eA: PA distribution according to groups (DM1 and controls) and sex; B: SPA distribution according to groups (DM1 and controls)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4802871/v1/646e31fb24a5215fbc5ac0d4.png"},{"id":69285389,"identity":"6dd0f031-e29c-4732-a599-a3257a5443fe","added_by":"auto","created_at":"2024-11-18 19:25:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":548269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4802871/v1/13adaf7c-dd30-4037-aa0b-ce7f80c94f06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Phase Angle and Body Composition in Long-term Type 1 Diabetes in Adults: A comparative study in a Brazilian Public Reference Outpatient Clinic","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThere is an increasing interest in the evaluation of body composition in adult diabetic patients. So far, there has not been many studies on distinct Bioelectrical Impedance (BIA) either direct or derived parameters in patients with Type 1 Diabetes (DM1) with long standing disease.\u003c/p\u003e \u003cp\u003eIn different countries, evidence indicates that people with DM1, especially children and teenagers, display higher levels of adiposity, more intense weight gain and lower Phase Angle (PA) than healthy controls.\u003c/p\u003e \u003cp\u003ePhase angle is a direct BIA measurement that can indicate early alterations at cellular level and may thus become an important tool in the evaluation of a patient\u0026rsquo;s general health (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). BIA derived parameters, such as body fat percentage (%BF) and fat free percentage (%FF), may offer meaningful information about body composition and metabolism, since alterations in body compartments may affect risk profiles and metabolic control (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). This type of information may be acquired during routine outpatient clinical assessment and benefit both the patient and the healthcare professional, as it can result in more assertive information with implications for prevention, helping clinical control and prognosis modification (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince the DCCT study, weight gain and serum lipid levels in diabetics have been related with inadequate eating practices, excess carbohydrates, lack of physical activity and exogenous insulin administration (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExcess body weight can result from different sources \u0026ndash; be it from adipose tissue or, inversely, from muscle hypertrophy; obese individuals with high body mass index (BMI), on the other hand, may present low muscle mass. Usually, healthcare professionals employ only the BMI to evaluate obesity during outpatient anthropometric evaluation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, this does not accurately measure adiposity, nor presents a detailed evaluation of body composition, including fat mass and fat-free mass (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In diabetic patients, such shortcomings are critical because increased fat deposition is associated with insulin resistance, while muscle mass plays an important role on general health and metabolic regulation. Attention should be directed to the fact that body composition absolute values in kilograms and percentages (fat mass and fat-free mass) may not reflect specific changes in these compartments; parameters that take into consideration body size, such as fat mass and fat-free mass indexes (FMI and FFMI), might also have an important role (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBIA derived FFMI has been used as criteria to define sarcopenia, and is strongly correlated with appendicular muscle mass as measured by dual energy X-ray absorptiometry (DEXA). Although DEXA is considered to be the golden standard in assessing body composition, its applicability in clinical outpatient settings, especially public ones, is limited by its cost, radiation exposure and portability (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, BIA \u0026ndash; despite its limitations, such as the lack of precision to calculate body water in different conditions, including diabetes \u0026ndash; is considered a safe and practical device to monitor body composition. Based on the basic principle that body fluids and electrolytes conduct low tension electricity (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), it has the additional advantages of being not only accessible and low cost, but also reliable and non invasive. Although some predictive BIA equations are not population specific, it may provide an assessment of body composition through the directly obtainable parameters of reactance and resistance (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the Brazilian Diabetes Society (SBD,2024), the treatment of Type 1 Diabetes is multidisciplinary. Each individual, together with his/her family members and healthcare team, must be actively engaged in self-management and treatment planning, including the collaborative development of a dietary plan, in which the distribution of carbohydrates should preferably be individualized, providing better weight, glycemic and general metabolic control (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLatest data from International Diabetes Federations (IDF, 2023) indicate that only 1.52\u0026nbsp;million of the 8.75\u0026nbsp;million people living with Type 1 Diabetes worldwide in 2022 were under the age of 20; therefore, the lack of available data for the adult population presents an evident gap in research (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlso according to data from the IDF, the life expectancy of a person with Type 1 Diabetes in countries such as Brazil can be around 15 years lower than that observed in people with DM1 in developed countries, indicating the need for better health initiatives, attention and treatment.\u003c/p\u003e \u003cp\u003eDM1 is a chronic autoimmune disease, and its management has been associated with significant changes in body composition. The main objective of this study is to explore these changes in a cohort of long standing DM1 patients followed at a public university outpatient reference clinic, in an attempt to contribute to the understanding of their role in the health of this specific group of patients.\u003c/p\u003e \u003cp\u003eBIA direct (phase angle, standardized phase angle) and indirect parameters (percentage of fat-free mass, percentage of fat mass, fat-free mass index and fat mass index) were compared in long standing DM1 outpatients and normal controls. Knowledge of differences in body composition of diabetics may be of critical importance, since they may be related to the present health and organ integrity, as in the case of PA and SPA, or to metabolic control and prognosis in the case of fat-free mass and fat mass parameters.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis is a comparative study, carried out in a reference public university outpatient clinic, which included a cohort of adult patients of both sexes with diagnosed DM1, and a control group matched by age and sex, on a 2:1 basis. Data were collected from March 2020 to March 2023. Patients or their proxies and controls signed the Informed Consent Form (FICF) previously approved by the Institutional Ethics Research Committee. Exclusion criteria were age under 18; bedridden patients or with a disability that made it impossible to properly place BIA electrodes; hypersensitivity to electronic devices; chronic kidney disease (CKD) on dialysis; cardiovascular disease in use of a pacemaker; anemia; edematous states; heart failure; nephrotic syndrome; cirrhosis; and pregnancy. Control group volunteers were recruited among medical students and university personnel. Diabetic patients were assessed as part of a nutritional appointment, which included HbA1c result, BIA analysis and capillary blood glucose, in addition to other nutritional parameters (weight, height, body mass index). It also counted on a structured questionnaire that included health background, time of diagnosis, food intake record, average 24-hour consumption of carbohydrates, and presence of diabetic microvascular complications (the presence or any association of retinopathy, neuropathy or non-nephrotic nephropathy). Controls received anthropometric and BIA evaluation.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eNutritional Status Assessment\u003c/h2\u003e \u003cp\u003eWeight and height were obtained with a Tanita\u0026reg; scale by means of adequate and standardized procedure. Body mass index (BMI) was calculated by the standard WHO formula of weight/height\u0026sup2; (Who Expert Committee on Physical Status 1995).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBioelectrical Impedance (BIA)\u003c/h2\u003e \u003cp\u003eLow intensity (800 \u0026micro;A), single frequency (50 kHz) BIA analysis was performed (Quantum X device, RJL systems, 2007). Resistance (R), reactance (Xc), and PA values were obtained by the Body Composition software as proposed by the device manufacturer. A standard procedure was employed, including position of body and members, removal of metals in contact with skin, cleansing with alcohol, and location of electrodes (Kyle 2004; WHO Expert Committee on Physical Status 1995). Standardized PA (SPA) was calculated according to the following Eq.\u0026nbsp;(5):\u003c/p\u003e \u003cp\u003eSPA\u0026thinsp;=\u0026thinsp;measured [PA \u0026ndash; mean PA (for age and gender)] / population standard deviation for age and gender\u003c/p\u003e \u003cp\u003eFat free mass (FFM) was obtained through the Body Composition Program of the BIA device, according to the following formula:\u003c/p\u003e \u003cp\u003eFFM = -4.104 + (0.518 \u0026times; height\u003csup\u003e2\u003c/sup\u003e/resistance) + (0.231 \u0026times; weight) + (0.130 \u0026times; reactance) + (4.229 \u0026times; sex); men\u0026thinsp;=\u0026thinsp;1, women\u0026thinsp;=\u0026thinsp;0; (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFat-free mass percentage (%FFM) was calculated by dividing FFM (kg) by weight (kg).\u003c/p\u003e \u003cp\u003eFat-free mass index (FFMI) was calculated according to the following formula:\u003c/p\u003e \u003cp\u003eFFMI\u0026thinsp;=\u0026thinsp;FFM/ height\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGlycated Hemoglobin (HbA1C)\u003c/h2\u003e \u003cp\u003eHbA1C concentrations were measured from blood plasma by methods certified by the National Glycohemoglobin Standardization Program (NGSP).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were presented as absolute and relative frequencies and mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD (standard deviation) or median and percentiles, depending on the distribution as verified by the Shapiro-Wilk test.\u003c/p\u003e \u003cp\u003eBesides comparison of means and medians between groups, logistic regressions were carried out with DM1 and control group as dichotomous outcomes in order to verify, within the studied sample, which factors are clearly associated with one of the outcomes. Receiver operating characteristic (ROC) curves were also performed to evaluate the behavior of PA and SPA in distinguishing between diabetics and controls and possible cutoffs associated with a higher probability of belonging to the DM1 group.\u003c/p\u003e \u003cp\u003eLinear regression was used in the DM1 group to evaluate the association between the independent variables (HbA1c, duration of disease, presence of microvascular complications, capillary blood glycemia on the day of BIA application, BMI and FFMI) with PA (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Due to their strong collinearity, different models were performed separately for BMI and FFMI.\u003c/p\u003e \u003cp\u003eAnalyses employed the package SPSS\u0026reg;19.0 (Chicago: SPSS Inc. IBM Corp) and considered a significance level of 5%. Sample size calculation (G*Power 3.1.9.4) assumed an effect size of 0.47 for the difference of PA means between a DM1 and a control group (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), a power of 80%, and an alpha error of 0.05, resulting in a sample size of 43 (controls) e 85 (cases).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA cohort of 88 patients with long-term Type 1 DM (21.2\u0026thinsp;+\u0026thinsp;9.3 years) was compared with a group of 46 controls, matched by sex and age (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Most diabetic patients were uncontrolled according to HbA1c levels (8.96\u0026thinsp;+\u0026thinsp;2.09%), and 44.5% had microvascular complications.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and Clinical Data\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDM1 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eC (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e36.2\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e36.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.914\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuration* (min- max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e21.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3 (5\u0026ndash;48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1C* (min- max)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e8.57\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.84(5.50\u0026ndash;15.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplications**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e40 (44.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (53.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (46.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (63.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (37.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.7\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.2\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1C*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.96\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.12\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplications**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (40.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e* = Student\u0026rsquo;s T test; ** = Chi square\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eBIA parameters displayed significantly higher PA and SPA medians in the control group (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), and significant differences in body composition were observed. Fat-free mass was lower, according to %FFM, and body fat higher in diabetics, according both to %FM and FMI (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eWhen groups are stratified by sex, differences in PA and SPA remained significant, and differences in body composition seemed to be due mainly to a lower percentage of FFM and a higher percentage of FM observed in diabetic women. When FMI was employed, a higher fat content in diabetic women, but not in diabetic men (as with fat mass percentage) was confirmed. A lower fat-free mass content in diabetic men as measured by FFMI; the same was not observed in diabetic women (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBIA parameters in Diabetics and Controls\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDM1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep**\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e23.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePA*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSPA*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%FFM*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e70.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e72.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%FM*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e29.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e27.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e16.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e7.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDM1(47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC (\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep**\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDM1(\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep**\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePA*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSPA*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%FFM*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%FM*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.029\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFMI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.713\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eBMI\u0026thinsp;=\u0026thinsp;body mass index; PA\u0026thinsp;=\u0026thinsp;phase angle; SPA\u0026thinsp;=\u0026thinsp;standardized phase angle; %FFM\u0026thinsp;=\u0026thinsp;percentage of fat-free mass; %FM\u0026thinsp;=\u0026thinsp;percentage of fat mass; FFMI\u0026thinsp;=\u0026thinsp;fat-free mass index; FMI\u0026thinsp;=\u0026thinsp;fat mass index; *median; **Mann Whitney test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eResults of PA and SPA among groups are illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, below.\u003c/p\u003e\n\u003cp\u003eA logistic regression was carried out to assess the effect of PA or SPA on the likelihood of belonging to DM1 or control groups. Different models were employed for both parameters. The models were controlled for age and sex, and different parameters of body composition (%FFM, %FM, FFMI and FMI) were entered in separate models, along with PA (or SPA), age and sex. Both PA and SPA were associated with a high discriminatory capacity. The OR (Exp(B)) for PA remained consistent at approximately 0.2 between different models, with CI ranging from approximately 0.100 to 0.400 and \u003cem\u003ep\u003c/em\u003e values of 0.000, indicating an 80% reduction in the chances of being part of the DM1 group for every 1 unit increase in PA. Similarly, for SPA, OR remained stable around 0.25, with CI ranging between 0.140 to 0.450, with \u003cem\u003ep\u003c/em\u003e values of 0.000, indicating a 75% reduction in the chance of being part of the DM1 group for every 1 unit increase in SPA. The overall models were statistically significant when compared to the null model and explained from 38\u0026ndash;46% of the group allocation for PA and from 39\u0026ndash;46% for SPA. The models correctly predicted around 80% of cases in both PA and SPA models.\u003c/p\u003e\n\u003cp\u003eAmong body composition variables also entered in the models, FMI, but not %FFM or FFMI, showed a discriminatory capacity between diabetics and controls, both in the PA (OR: 1.327; IC: 1.118\u0026ndash;1.574; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and SPA (OR: 1.325; IC: 1.114\u0026ndash;1.575; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) models, indicating a 30% higher chance of belonging to DM1 group for each 1 kg/m\u003csup\u003e2\u003c/sup\u003e increase in FMI.\u003c/p\u003e\n\u003cp\u003eROC curves for both PA (AUC\u0026thinsp;=\u0026thinsp;0.719, 0.629\u0026ndash;0.808, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000), and especially for SPA (AUC\u0026thinsp;=\u0026thinsp;0.805, 0.729\u0026ndash;0.881, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000), also illustrate the discriminatory capacity. Among control patients, only 9 (19,6%) had SPA values below the cutoff of -1.145 obtained with the Youden method, while 58 (65.9%) diabetics displayed SPA below that threshold. Only 3 (6.5%) control patients displayed SPA below the threshold of -1.65, considered the 5th percentile of Brazilian population, while 41(46.6%) had results below this.\u003c/p\u003e\n\u003cp\u003eLinear regression models were employed in the DM1 group to analyze association of clinical and anthropometric data (sex, age, duration of disease, rate of microvascular complications, anthropometric variables, HbA1c and capillary blood glycemia) with PA or SPA. No statistically significant association was demonstrated between HbA1C levels and PA or SPA.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis work aimed to evaluate PA and body composition in adult DM1 patients with long-term disease in comparison to healthy individuals, matched according to age and sex.\u003c/p\u003e \u003cp\u003eIt is known that DM1 is associated with an elevated risk of complications, and that poor metabolic control as determined by HbA1c is correlated with different acute and chronic complications. Body composition and PA have not been thoroughly evaluated in the group with long standing adult DM1.\u003c/p\u003e \u003cp\u003ePA is calculated from the direct BIA measurements of resistance (R) and reactance (Xc). Data on PA evaluation in diabetics are scarce and have not been studied in the Brazilian population.\u003c/p\u003e \u003cp\u003eResults showed lower PA values, as observed in younger diabetics with DM1. In children and adolescents with recently diagnosed diabetes, N\u0026rsquo;Samba \u003cem\u003eet al.\u003c/em\u003e found significantly lower PA values in comparison to healthy controls (4.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 vs. 5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Buscemi, studying patients with both DM1 and DM2, found significantly lower PA values in young male patients with DM1, but not in females. In the present study, when PA values were adjusted for age and sex, by either logistic regression or the use of SPA, the difference between diabetics and controls in both sexes remained significant. A thorough search in different databases (PubMed, Scopus, EMBASE) for studies using SPA in diabetic patients showed that it had not been employed in diabetes, and the present results indicate its potential usefulness. Among control patients, 6.5% displayed values below the SPA threshold of -1.65, which corresponds to the 5th percentile of the Brazilian population, in comparison to 46.6% of diabetics.\u003c/p\u003e \u003cp\u003eBesides confirming lower PA values in diabetics in general, the study is in agreement with others that show lower values in diabetic women (Dittmar \u003cem\u003eet al.\u003c/em\u003e(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). This is probably related to the body composition, with a lower amount of fat-free mass.\u003c/p\u003e \u003cp\u003eContrary to our initial hypothesis, an association between PA and HbA1c values could not be demonstrated, possibly because the study was not powered enough for this.\u003c/p\u003e \u003cp\u003eDitmar \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) found an inverse relationship between these parameters that was attributed to catabolism and disease duration. We have demonstrated an inverse association between disease duration and PA, as well as lower fat-free mass as expressed by FFMI in diabetic men. However, no significant relationship with HbA1c levels could be established. The sample was mainly composed of uncontrolled patients. which may have prevented conclusions that could have been obtained with the presence of better controlled ones.\u003c/p\u003e \u003cp\u003eIn relation to body composition, important differences between diabetics and controls were observed. DM1 patients had an excess of fat mass, both in terms of %FM and FMI, mainly due to the female component of the sample. Body fat increases substantially in girls during puberty, and may be especially marked in girls with diabetes (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). This finding may be related to the multiple dose insulin regimens, carbohydrate-rich diets and possibly to the inflammatory activity and insulin resistance/metabolic syndrome, which result in low muscle mass, increased fat mass and poor diabetic control as evaluated by HbA1c (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA lower muscle mass in diabetic man was shown, which is another feature that has been associated with fat mass increase in DM1. According to Szadkowska \u003cem\u003eet al\u003c/em\u003e, DM1 patients are characterized by increased fat mass and put on more weight than controls.\u003c/p\u003e \u003cp\u003eThese alterations in body composition may determine a future impact on overall health with different metabolic derangements, such as dyslipidemia, arterial hypertension, sarcopenia and insulin resistance. Muscle mass reduction results in a significant impact on insulin sensitivity, glucose and lipid processing and basal metabolic rate, with consequences on metabolic stability in DM1.\u003c/p\u003e \u003cp\u003eA recent study (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) carried out with patients with Type 1 Diabetes from the same research group has highlighted the need for attention to women's metabolic care and body composition, since female patients displayed higher cardiovascular risk than male patients, contrary to usual expectations (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The discrepancy observed in the study by (de Ara\u0026uacute;jo F.M \u003cem\u003eet al.\u003c/em\u003e, 2024) was explained by the high prevalence of chronic complications in the sample, mainly diabetic retinopathy, a factor that categorizes a patient as having high cardiovascular risk (SBEM - Brazilian Society of Endocrinology and Metabology). Furthermore, women had a higher prevalence of diabetic kidney disease, as well as worse glycemic control and slightly higher levels of LDL cholesterol, which could justify a higher proportion of female patients classified as high cardiovascular risk when evaluated by the Steno T1 Risk Engine (ST1RE), used to predict cardiovascular events in patients with DM1 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Whether these observations could be explained by body composition alterations that may be more profound in women than in men remain to be further clarified. That said, this seems to be an important line of investigation, with some evidence pointing towards this direction (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis is a challenging topic, where definite conclusions are lacking, and additional studies with the development of body composition evaluation protocols may contribute to a better metabolic control for the population with Type 1 Diabete\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003ePatients with long-term DM1 present lower PA. In terms of body compartment percentages, diabetics displayed higher fat mass and lower fat-free mass. When corrected by body size, diabetics displayed higher fat mass than controls. Significant body composition differences between sexes were highlighted, with data showing greater adiposity in diabetic women in relation to female controls, and diabetic men displaying lower fat-free mass corrected by height in relation to male controls.\u003c/p\u003e \u003cp\u003eThese findings indicate the importance of a careful body composition evaluation and follow-up. The aim is to contribute to a better metabolic control and prognostic modification, considering both the extensive body of information on the effects of long-term Type 1 Diabetes, and the data from this and other studies relating duration of disease with PA, a marker of general health. Multidisciplinary outpatient follow-ups should benefit from this approach.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflicts of interest. All patients accepted the Free and Informed Consent Form, previously approved by the University Ethics Committee (UFMG), according to the CAEE (Number: 57752922 2 0000 51 49) \u0026nbsp;previously informed in this study. We have no other funding for this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll patients signed and agreed to the terms of consent for participation and also the consent to publish the study. CAEE (Number: 57752922 2 0000 51 49) approval number by the Federal University of Minas Gerais: \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFenner-Pena N had the original study idea, wrote the study proposal and protocol, developed the manuscript, measured the study, and provided training.\u003c/p\u003e\n\u003cp\u003eFajardo VC evaluated based on data analysis. Froes L- Endocrinologist at the UFMG Diabetes League - participation in data collection. Brazil. Carvalho PAM - technical collaboration on Bioelectrical Impedance data. Brazil. Lauria M. W- Doctoral Coordinator of the UFMG Diabetes League - Participant in all development and projects. Brazil. Torres H. G- Advisor of the Post-Medicine Program - UFMG - participant in all development and projects. Brazil.\u003c/p\u003e\n\u003cp\u003eAll authors were conscientious and contributed to the text of these manuscripts.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFenner-PenaN and Fajardo VC have support from the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES-BR) - Financial Code 001 for a doctoral scholarship.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLiu, L.L.; Lawrence, J.; Davis, C.; Liese, A.D.; Pettitt, D.J.; Pihoker, C.; Dabelea, D.; Hamman, R.; Waitzfelder, B.; Kahn, H.; et al. Prevalence of overweight and obesity in youth with diabetes in USA: The SEARCH for Diabetes in Youth Study. Pediatr. 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N., Lauria, M., \u003cem\u003eet al.\u003c/em\u003e A comparative study of cardiovascular risk stratification methods in type 1 diabetes mellitus patients. \u003cem\u003eDiabetol Metab Syndr\u003c/em\u003e\u003cstrong\u003e16\u003c/strong\u003e, 10 (2024). https://doi.org/10.1186/s13098-023-01224-5.\u003c/li\u003e\n\u003cli\u003eEstande GL, Kapral MK, Fung K, Tu JV. Rela\u0026ccedil;\u0026atilde;o entre idade e doen\u0026ccedil;a cardiovascular em homens e mulheres com diabetes comparados com pessoas n\u0026atilde;o diab\u0026eacute;ticas: um estudo de coorte retrospectivo de base populacional. Lanceta. 2006;368(9529):29\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eTuvemo T, Kobbah M, Proos LA. Growth and subcutaneous fat during the first fi ve years of insulin-dependent diabetes in children. Acta Paediatr Suppl 1997;418:1\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eNuoffer JM, Kuhlmann B, Hodler C, et al. [Eating behavior, diabetes and weight control in girls with insulin-dependent diabetes mellitus (type 1)]. Schweiz Med Wochenschr 1996;126:1560\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003ePietil\u0026auml;inen KH, Virtanen SM, Rissanen A, et al. Diet, obesity, and metabolic control in girls with insulin dependent diabetes mellitus. Arch Dis Child 1995;73:398\u0026ndash;402.\u003c/li\u003e\n\u003cli\u003eTarcila Ferraz de Campos, Silvia Ramos, Let\u0026iacute;cia Fuganti Campos, D\u0026eacute;bora Bohnen Guimar\u0026atilde;es, Deise Regina Baptista, Daniela Lopes Gomes, D\u0026eacute;bora Lopes Souto, Maristela Strufaldi, Marlice Marques, Nat\u0026aacute;lia Fenner Pena, Sabrina Soares de Santana Sousa. Terapia Nutricional no Diabetes tipo 1. Diretriz Oficial da Sociedade Brasileira de Diabetes (2024). DOI: 00.00000/00000000.0000-0, ISBN: 000-00-0000-000-0.\u003c/li\u003e\n\u003cli\u003eIDF, ATLAS REPORTS. Type 1 diabetes estimates in children and adults \u0026ndash; 2022. Type 1 diabetes numbers in children and adults Authors: Graham D Ogle \u0026sup1;, Fei Wang \u0026sup1;, Gabriel A Gregory \u0026sup1; and Jayanthi Maniam \u0026sup1; \u0026sup1; T1D Index consortium. Dispon\u0026iacute;vel em: www.diabetesatlas.orgType.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Body Composition, Bioimpedance, Phase Angle, Type 1 Diabetes","lastPublishedDoi":"10.21203/rs.3.rs-4802871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4802871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e Type 1 Diabetes Mellitus (DM1) is a disease that affects a small percentage of the population. Nevertheless prevalence is currently growing, with alarming data on lack of control. The importance of body composition and Phase Angle (PA) as assessed by Bioelectrical Impedance (BIA) in long term DM1 patients lies in the fact that alterations in cellular integrity and body compartments may affect risk profiles and metabolic control. The objective of this study was to compare different PA and body composition parameters in a sample of adults with DM1, with healthy controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A comparative study was carried out in a state public university outpatient clinic, including a cohort of adult patients of both sexes, diagnosed with DM1, and a control group matched by age and sex, in a 2:1 ratio. Anthropometric measurements included weight, height and BMI. From the raw bioelectrical impedance data of Resistance and Reactance, Fat-Free Mass (FFM), Fat Mass (FM), Fat-Free Mass Index (FFMI), Fat Mass Index (FMI), PA and standardized PA (SPA) were calculated. Means or medians were compared. Regression models were used to show distinguishing characteristics of both groups or to disclose associations within the diabetic group (HbA1c, disease duration, presence of microvascular complications, capillary blood glucose, BMI and FMI).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 88 patients with Type 1 Diabetes and 46 healthy controls were evaluated. PA was lower in diabetics (6.05 \u003cem\u003evs\u003c/em\u003e 6.85, \u003cem\u003ep\u003c/em\u003e = 0.000), as well as SPA (-1.47 \u003cem\u003evs\u003c/em\u003e -1.36, \u003cem\u003ep\u003c/em\u003e = 0.000). Diabetics displayed higher adiposity (%FM = 29.6 \u003cem\u003evs\u003c/em\u003e 27.6, \u003cem\u003ep\u003c/em\u003e = 0.016; FMI = 7.00 \u003cem\u003evs\u003c/em\u003e 6.33, \u003cem\u003ep\u003c/em\u003e= 0.016) and lower %FFM. Most of the differences were maintained after sex stratification and diabetic man disclose a lower FFMI than male controls (18.2 \u003cem\u003evs\u003c/em\u003e20.16, \u003cem\u003ep\u003c/em\u003e = 0.029).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003ePatients with DM1 present greater nutritional risk and worse cell membrane integrity when assessed by PA. Significant body composition differences among groups and between sexes were highlighted, with data showing greater adiposity in diabetic women and diabetic men displaying lower muscle mass. These findings suggest the importance including PA and body composition evaluation in the multidisciplinary clinical outpatient follow-up of patients with Type 1 Diabetes, in an attempt to obtain better metabolic control and consequently, a better prognosis.\u003c/p\u003e","manuscriptTitle":"Phase Angle and Body Composition in Long-term Type 1 Diabetes in Adults: A comparative study in a Brazilian Public Reference Outpatient Clinic","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-04 22:57:49","doi":"10.21203/rs.3.rs-4802871/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-25T13:32:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-24T21:18:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-22T21:31:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339172878002487064561807054134585737736","date":"2024-08-20T08:02:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215047018694999222827811477075628922510","date":"2024-08-12T19:17:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226670227491980272800636580329294381988","date":"2024-08-04T08:15:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-01T08:31:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-31T19:59:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-31T06:00:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Diabetology \u0026 Metabolic Syndrome","date":"2024-07-25T15:16:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b0f25e5-1dac-46c8-a3b7-60a0ffa98316","owner":[],"postedDate":"September 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-18T19:17:55+00:00","versionOfRecord":{"articleIdentity":"rs-4802871","link":"https://doi.org/10.1186/s13098-024-01485-8","journal":{"identity":"diabetology-and-metabolic-syndrome","isVorOnly":false,"title":"Diabetology \u0026 Metabolic Syndrome"},"publishedOn":"2024-11-13 15:58:13","publishedOnDateReadable":"November 13th, 2024"},"versionCreatedAt":"2024-09-04 22:57:49","video":"","vorDoi":"10.1186/s13098-024-01485-8","vorDoiUrl":"https://doi.org/10.1186/s13098-024-01485-8","workflowStages":[]},"version":"v1","identity":"rs-4802871","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4802871","identity":"rs-4802871","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}