Sociodemographic and Clinical Determinants on Health-Related Quality of Life in Emerging Andalusian Adults with Type 1 Diabetes: A Cross-Sectional Study

Citation: Núñez-Baila, M.-Á.; Gómez-Aragón, A.; González-López, J.R. Sociodemographic and Clinical Determinants on Health-Related Quality of Life in Emerging Andalusian Adults with Type 1 Diabetes: A Cross-Sectional Study. J. Clin. Med. 2024,13, 240. https:// doi.org/10.3390/jcm13010240 Academic Editor: Pasquale Mone Received: 30 November 2023 Revised: 16 December 2023 Accepted: 27 December 2023 Published: 31 December 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Journal of Clinical Medicine Article Sociodemographic and Clinical Determinants on Health-Related Quality of Life in Emerging Andalusian Adults with Type 1 Diabetes: A Cross-Sectional Study María-Ángeles Núñez-Baila , Anjhara Gómez-Aragón * and JoséRafael González-López Nursing Department, Faculty of Nursing, Physiotherapy and Podiatry, Universidad de Sevilla, 41009 Seville, Spain; [email protected] (M.-Á.N.-B.); [email protected] (J.R.G.-L.) *Correspondence: [email protected] Abstract: (1) Background: Having type 1 diabetes during emerging adulthood can impact quality of life due to the challenge of balancing optimal glycemic blood levels with a period of transition and exploration. The purpose of this study was to characterize the quality of life of emerging adults aged 18 to 29 years with type 1 diabetes and to determine the associations between dimensions of Health-Related Quality of Life in type 1 diabetes and sociodemographic and diabetes-related variables. (2) Methods: This cross-sectional descriptive study was conducted in Andalusia, Spain, from October 2021 to July 2022. A total of 362 emerging adults with type 1 diabetes (67.4% women, mean age 22.8 ± 3.4 years) participated. Data were gathered via sociodemographic information form and the ViDa1 scale. Statistical evaluations, encompassing descriptive analyses, t-tests, ANOVA, Pearson correlations, and logistic regression, were conducted using SPSSv26, adhering to STROBE guidelines. (3) Results: Among the participants, 52.1% have a glycosylated hemoglobin level over 7%. Interference with Life is correlated with sex, age, and age at diagnosis, with age being the only predictor. Self-Care is correlated with and predicted by glycosylated hemoglobin levels. Well-being is correlated with and predicted by sex, Body Mass Index, and glycosylated hemoglobin levels. Concern about the Condition is correlated with and predicted by sex and glycosylated hemoglobin levels. (4) Conclusions: Despite concerns about their disease, participants generally maintain optimal levels of Health-Related Quality of Life in type 1 diabetes. Predictive factors for Health-Related Quality of Life in type 1 diabetes in this group include sex, age, Body Mass Index, and glycosylated hemoglobin. Keywords: emerging adulthood; type 1 diabetes; Health-Related Quality of Life; cross-sectional study 1. Introduction Type 1 diabetes mellitus (T1DM) is predominantly diagnosed during childhood and persists as a chronic condition into adulthood [ 1 ]. The phase of emerging adulthood, spanning ages 18 to 29 years, presents unique challenges. This period is characterized by significant life transitions, including extended education, fluctuating job markets, evolving life expectations, and shifting societal roles [2,3]. This transitionary phase is also characterized by an identity exploration of values in the social, educational, and personal spheres, striving for self-improvement and goal attainment. While emerging adults generally enjoy good health and no concerns regarding their well-being [ 4 ], those living with T1DM may experience a substantial impact on their Health-Related Quality of Life (HRQoL) [5,6]. From childhood to emerging adulthood, blood glucose levels decrease, with the latter phase being a critical period [ 1 , 7 , 8 ]. Only 17% of early emerging adult (ages 18–25) and 30% of later emerging adults (ages 26–30) met the American Diabetes Association recommendations for glycemic target [ 9 ]. Comparable percentages are evident in the Global TEENs Study [ 10 ], where merely 18.4% of emerging adults reached the glycosylated hemoglobin A1C (A1C) target. Similarly, in the study by Carels et al. [ 11 ], only 18% of emerging adults J. Clin. Med. 2024,13, 240. https://doi.org/10.3390/jcm13010240 https://www.mdpi.com/journal/jcm J. Clin. Med. 2024,13, 240 2 of 15 with T1DM showed an A1C level below 53 mmol/mol. This is compounded by the finding that HRQoL in T1DM is intricately linked to glycemic blood levels, with higher A1C values correlating with lower HRQoL [ 10 , 12 , 13 ]. The complexity of this relationship is accentuated in emerging adults when compared to those with type 2 diabetes [ 14 , 15 ]. The longitudinal study conducted by Stahl-Pehe et al. [ 16 ] indicated a potential inverse correlation between a decline in HRQoL for individuals with T1DM and a reduction in A1C levels over a three-year period, though it did not conclusively establish causality. The HRQoL in people with T1DM is influenced by a myriad of factors. These encompass disease duration [ 1 ], sex disparities with women often reporting lower HRQoL [6,13,15,17] , and the post-high school transition to independence [ 18 ]. A diagnosis during emerging adulthood [ 19 ], especially in the latter stage (25–29 years), is associated with heightened anxiety and a subsequent decline in HRQoL in this demographic [ 20 ]. Moreover, lifestyle practices such as consistent exercise, diligent daily monitoring of blood glucose, carbohydrate counting, and tailored insulin adjustment have been linked to improved HRQoL in emerging adults with T1DM [10]. In addition to life transitions characteristic of emerging adulthood, including university enrollment and evolving social relationships [ 21 ], there exists a significant gap in the literature concerning HRQoL studies for this particular age group with T1DM [ 6 , 10 , 14 , 20 ]. This is in stark contrast to the extensive research focused on children and adolescents [ 7 , 22 – 25 ]. Notably, emerging adulthood, a phase often marked by experimentation and risky behaviors, reveals no substantial differences in activities like alcohol consumption, tobacco use, or physical inactivity between individuals with T1DM and their peers without T1DM [3,26]. While there is a vast knowledge regarding the transition from pediatric to adult care for individuals with T1DM, the following life stage has comparatively garnered less focus [ 27 ]. In the treatment of chronic conditions like T1DM, optimizing HRQoL is an end in itself. This study seeks to bridge this gap by characterizing the HRQoL among emerging adults with T1DM in Andalusia and exploring the association between HRQoL dimensions (including Interference with Life, Self-Care, Well-Being, and Concern about the Condition) and various sociodemographic and clinical factors. We hypothesize that a favorable HRQoL in T1DM among emerging adults is influenced by factors such as blood glucose levels (A1C), duration of diabetes, timing of diagnosis during emerging adulthood, and life challenges and independence milestones like employment status or living arrangements. 2. Materials and Methods 2.1. Study Design and Population This descriptive, cross-sectional study was conducted in Andalusia, Spain, from October 2021 to July 2022. It included both women and men aged between 18 and 29 years, diagnosed with T1DM for at least one year, and residing in Andalusia. According to the 2021 Andalusian database, there were 5991 individuals in this age group diagnosed with T1DM. Using a 95% confidence interval, a representative sample of 361 emerging adults with T1DM was assigned for the study. The sample was purposively recruited through different diabetes associations in Andalusia and complemented by outreach social media and advertising materials. The process of participant enrollment is detailed in Figure 1. The voluntary nature of participation could introduce self-selection bias, as those who chose to participate might have motivations unrelated to T1DM. Participants were asked to complete an online questionnaire via Google Forms, preceded by an explanatory note with the researcher’s contact information. Written informed consent was secured from all participants before they began the questionnaire. J. Clin. Med. 2024,13, 240 3 of 15 J. Clin. Med. 2024, 13, x FOR PEER REVIEW 3 of 15 Written informed consent was secured from all participants before they began the questionnaire. Figure 1. Flow chart of participant enrollment process. 2.2. Measures The questionnaire was designed to collect sociodemographic data, including sex, date of birth, age, weight, height, civil status, province of residence in Andalusia, living situation, and current study and employment statuses. Additionally, it gathered healthrelated information, focusing on variables pertinent to T1DM, such as coexisting conditions, the time of T1DM diagnosis, and A1C values. The questionnaire also assessed HRQoL in individuals with T1DM. The HRQoL in T1DM variable was measured using the ViDa1 questionnaire (Likert type, 1–5) with 34 items grouped in 4 dimensions [28]. The score ranges for these dimensions are as follows: Interference with Life dimension from 12 to 60 (Cronbach’s α = 0.86), Self-Care from 10 to 50 points (Cronbach’s α = 0.84), Well-Being from 5 to 25 points (Cronbach’s α = 0.76), and Concern about the Condition from 4 to 20 points (Cronbach’s α = 0.71). Due to the subjective nature of this tool, it does not have cut-off points. In this context, higher scores in Interference with Life and Concern about the Condition indicated lower HRQoL in T1DM, whereas higher scores in Self-Care and Well-Being, reflect improved HRQoL in T1DM. After a consultation with the corresponding author of the article about the tool [28], HRQoL in T1DM was categorized as high or low based on mean scores obtained in each dimension. 2.3. Ethical Considerations The study was conducted in accordance with the principles of the Declaration of Helsinki. It received ethical approval by the Ethics Committee of the University Hospitals Figure 1. Flow chart of participant enrollment process. 2.2. Measures The questionnaire was designed to collect sociodemographic data, including sex, date of birth, age, weight, height, civil status, province of residence in Andalusia, living situation, and current study and employment statuses. Additionally, it gathered healthrelated information, focusing on variables pertinent to T1DM, such as coexisting conditions, the time of T1DM diagnosis, and A1C values. The questionnaire also assessed HRQoL in individuals with T1DM. The HRQoL in T1DM variable was measured using the ViDa1 questionnaire (Likert type, 1–5) with 34 items grouped in 4 dimensions [ 28 ]. The score ranges for these dimensions are as follows: Interference with Life dimension from 12 to 60 (Cronbach’s α = 0.86), Self-Care from 10 to 50 points (Cronbach’s α = 0.84), Well-Being from 5 to 25 points (Cronbach’s α = 0.76), and Concern about the Condition from 4 to 20 points (Cronbach’s α = 0.71). Due to the subjective nature of this tool, it does not have cut-off points. In this context, higher scores in Interference with Life and Concern about the Condition indicated lower HRQoL in T1DM, whereas higher scores in Self-Care and Well-Being, reflect improved HRQoL in T1DM. After a consultation with the corresponding author of the article about the tool [ 28 ], HRQoL in T1DM was categorized as high or low based on mean scores obtained in each dimension. 2.3. Ethical Considerations The study was conducted in accordance with the principles of the Declaration of Helsinki. It received ethical approval by the Ethics Committee of the University Hospitals Virgen Macarena and Virgen del Rocío, under the code 2150-M1-22, as documented in their proceedings dated 11 February 2020. Participants were informed about the voluntary J. Clin. Med. 2024,13, 240 4 of 15 and anonymous nature of their participation, with assurance that their data would be exclusively utilized for scientific purposes. Prior to completing the questionnaire, written consent for the processing of anonymized data was obtained. To maintain privacy, the questionnaire did not request any personal information, and location data were analyzed at the provincial level. 2.4. Data Analysis Descriptive statistical measures, including frequency distributions, means, and standard deviations were employed to illustrate participant sociodemographic characteristics of participants and the scores from the ViDa1 questionnaire. Unpaired T-tests for independent samples were utilized to evaluated differences in HRQoL in T1DM based on sex, age, A1C, age at T1DM diagnosis, presence of coexisting conditions, and current educational enrollment. To compare HRQoL in T1DM dimensions across different civil and employment statuses, regions in Andalusia, Body Mass Index (BMI), living situations, and educational levels, ANOVA was utilized, supplemented with the Bonferroni test where necessary. The Kolmogorov–Smirnov and Levene’s tests were applied to verify the normality and the homoscedasticity of each variable, respectively. The Kolmogorov–Smirnov test indicated a non-normal distribution of the sample, while Levene’s test evaluated homoscedasticity, noting exceptions in variance equality in the Well-Being (Civil status), Interference with Life (Andalusian province), and Self-Care (Level of studies) dimensions. Despite potential normality violations, the robustness of the sample size allowed for the application of parametric Student’s t-test and ANOVA. This approach is justified by the absence of extreme bias or flat distributions and a sufficiently large sample size (n> 30 ), conforming to the central limit theorem [ 29 ]. Cohen’s d coefficient and eta square ( η ²) were utilized to estimate the effect size, with thresholds set at 0.2 and 0.01 for a “small” effect size, 0.5 and 0.06 for a “medium” effect size, and 0.8 and 0.14 for a “large” effect size, respectively [30]. Pearson correlation analyses were applied to assess associations among sex (treated as a dummy variable), age, BMI, A1C levels, age at diagnosis, and duration of diabetes. Regression analyses for each HRQoL dimension in T1DM were conducted, with the Goodness of Fit evaluated through homoscedasticity and independence assessment in the residuals, using scatter plots and the Durbin–Watson statistic. The Grubb’s Outlier Test was applied to identify discrepancies between observed and expected values. The variables demonstrated both normality and a linear correlation. Moreover, multicollinearity was ruled out, as evidenced by Factor Inflation Variance and Tolerance values. Four distinct multiple regression models are presented, corresponding to each dimension of the ViDa1 questionnaire, which served as the dependent variables. Independent variables were selected based on significant Pearson correlation coefficients with the ViDa1 dimensions. Additionally, no corrections for multiple testing were applied, which heightens the risk of type I errors. For instance, a Bonferroni correction would have adjusted the significance level for the four conducted regression models, thereby reducing the likelihood of false positives [ 31 ]. All analyses were performed using SPSS version 26.0, with a p-value less than 0.05 deemed statistically significant. Lastly, the research adhered to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, ensuring the reproducibility and result presentation quality. 3. Results 3.1. Characteristics of the Sample Out of 525 initial respondents to the questionnaire, 163 were excluded for not meeting the inclusion criteria, resulting in a final sample of 362 emerging adults with T1DM. The average age of the participants was 22.8 years (SD 3.4), with women constituting 67.4% of the sample. The average age of T1DM diagnosis was 10.9 years (SD 6.7, range: 0–28), and J. Clin. Med. 2024,13, 240 5 of 15 the mean duration since diagnosis was 11.9 years (SD 6.6) (range: 1–28). In addition, over half of the participants had an A1C level above 53 mmol/mol (Table 1). Table 1. Demographic characteristics of the participants (n= 362). Variable Mean SD n % Sex (women) 244 67.4 Age (range: 18–29 years) 22.8 3.4 18–24 244 67.4 25–29 118 32.6 Glycosylated hemoglobin 55.2 12 (range: 26.8–79.2 mmol/mol) <53 mmol/mol 172 47.1 ≥53 mmol/mol 190 52.1 Years of development of type 1 diabetes 11.9 6.8 (range 1–28) Age at type 1 diabetes diagnosis 10.9 6.7 (range 0–28) Body Mass Index (kg/m2)124.0 4.3 (range: 17.15–48.68) Low weight 12 3.3 Normal weight 248 68.5 Pre-obesity or overweight 77 21.3 Obesity class 1 13 3.6 Obesity class 2 9 2.9 Obesity class 3 3 0.8 Civil status Single 295 81.5 Domestic partnership 62 17.1 Married 5 1.4 Employment status Does not work 178 49.2 Full-time work 86 23.8 Part-time work 37 10.2 Casual or temporary work 50 13.8 Self-employed 10 2.8 Andalusia: geographic location Almeria 22 6.1 Cadiz 38 10.5 Cordoba 32 8.8 Granada 53 14.6 Huelva 16 4.4 Jaen 21 5.8 Malaga 61 16.9 Seville 119 32.9 1The WHO Classification of adults according to BMI. Overall, emerging adults with diabetes generally reported a favorable HRQoL in the context of T1DM. More than half declared a low Interference with Life (79.6%), along with high levels of Self-Care (76.5%) and Well-Being (64.4%). However, a notable 68.5% of participants expressed considerable concern about their condition, with hyperglycemia and the potential for future diabetes complications being the most concerning factors. Detailed item-wise and overall scores for each dimension of HRQoL are presented in Table S1. The most prevalent coexisting conditions among this sample included food allergies (20.4%), skin problems (16.9%), and various other conditions (10.5%). Notably, hypothyroidism (9.9%), asthma (8.3%), celiac disease (7.5%), obesity (6.4%), gastroparesis (5.5%), lactose intolerance (4.7%), food allergy (4.4%), cardiovascular disease (2.8%), and mental health disorder (1.4%) were also observed. Table S2 provides a comprehensive overview of how these health conditions influenced each HRQoL dimension in T1DM. J. Clin. Med. 2024,13, 240 6 of 15 3.2. Relationships of Participants’ Quality of Life with Their Demographic Characteristics and Clinical Diabetes Determinants For each HRQoL dimension in the context of T1DM, mean scores were compared across independent samples using the unpaired Student’s t-test. This statistical approach was utilized to identify potential differences in HRQoL outcomes based on several key variables: sex, age group, A1C levels, timing of the diagnosis, current student status, and the presence of coexisting diseases (Tables 2and 3). Additionally, the influence of each specific coexisting disease on every HRQoL dimension was thoroughly investigated. The findings from this detailed examination are presented in Table S2, as referenced at the end of Section 3.1. In the Interference with Life dimension, women were found to experience greater interference in life due to T1DM compared to men. Furthermore, among emerging adults, those aged between 25 and 29 years reported more significant disruption in their lives due to diabetes than their younger counterparts aged 18 to 24 years. Additionally, a diagnosis at or after the age of 18 was associated with more pronounced interference in life than in those diagnosed before this age. Interestingly, individuals who have been living with T1DM for less than five years reported greater life interference compared to those who have managed the condition for over five years. Similarly, the presence of a coexisting condition alongside T1DM was linked to increased interference in life, highlighting the compounded challenges faced by emerging adults managing multiple health conditions. With respect to the Well-Being dimension, men reported higher levels of well-being compared to women, with this disparity being of approximately medium effect size. Moreover, emerging adults with an A1C level lower than 53 mmol/mol exhibited greater well-being than those with an A1C of 53 mmol/mol or higher. The presence of a coexisting condition alongside T1DM was found to reduce well-being levels compared to individuals without additional health conditions, also characterized by a medium effect size. Table 2. Differences between groups based on sociodemographic and clinical diabetes determinants using t-Student (Interference with Life and Self-Care). Interference with Life Self-Care Score Range: 12–60 Score Range: 5–25 n Mean SD t d Mean SD t d Sex Male 118 25.8 10.2 −2.009 * 0.23 40.7 5.5 1.169 0.13 Female 244 28.1 10.3 40.0 5.5 Age Group 18–24 244 26.3 10.0 − 2.840 ** 0.32 40.5 5.5 1.146 0.15 25–29 118 29.6 10.4 39.7 5.5 Glycosylated Hemoglobin <53 mmol/mol 172 27.2 10.2 −0.297 0.03 41.9 4.4 5.722 *** 0.61 ≥53 mmol/mol 190 27.5 10.3 38.7 6.0 Age at diagnosis <18 years 294 26.6 10.1 − 3.168 ** 0.42 40.2 5.6 0.113 0.02 ≥18 years 68 30.9 10.5 40.2 5.2 Diabetes evolution time <5 years 62 30.3 11.4 2.450 * 0.33 40.9 5.2 1.132 0.15 ≥5 years 300 26.8 9.9 40.1 5.6 Coexisting condition No 157 25.3 9.1 −3.515 *** 0.37 40.6 5.5 1.291 0.13 Yes 205 29.0 10.9 39.9 5.5 Studying at that moment No 100 28.1 11.0 0.853 0.10 40.1 5.7 −0.245 0.04 Yes 262 27.1 10.0 40.3 5.5 *p<0.05; ** p<0.01; *** p<0.001. J. Clin. Med. 2024,13, 240 7 of 15 Table 3. Differences between groups based on sociodemographic and clinical diabetes determinants using t-Student (Well-Being and Concern about the Condition). Well-Being Concern about the Condition Score Range: 9–30 Score Range: 21–51 n Mean SD t d Mean SD t d Sex Male 118 23.2 5.0 5.188 *** 0.52 16.8 4.8 − 3.198 ** 0.36 Female 244 20.4 4.9 18.5 4.7 Age Group 18–24 244 21.5 5.1 0.986 0.11 17.7 4.7 −1.165 0.15 25–29 118 20.9 5.0 18.4 4.9 Glycosylated Hemoglobin <53 mmol/mol 172 22.2 4.7 3.186 ** 0.34 17.3 5.1 2.497 * 0.25 ≥53 mmol/mol 190 20.5 5.3 18.5 4.4 Age at diagnosis <18 years 294 21.2 5.2 −0.355 0.06 17.8 4.7 −1.459 0.21 ≥18 years 68 21.5 4.9 18.7 5.3 Diabetes evolution time <5 years 62 21.5 5.0 0.305 0.04 18.4 4.8 0.805 0.10 ≥5 years 300 21.3 5.1 17.9 4.8 Coexisting condition No 157 22.7 4.5 4.815 *** 0.51 17.4 4.7 −1.748 0.21 Yes 205 20.2 5.3 18.3 4.8 Studying at that moment No 100 21.5 5.3 0.535 0.06 18.8 5.2 2.012 * 0.24 Yes 262 21.2 5.0 17.6 4.6 *p<0.05; ** p<0.01; *** p<0.001. Similarly, in Concern about the Condition dimension, a marked difference was noted between sex, with women exhibiting greater concern than men. Furthermore, emerging adults with an A1C level of 53 mmol/mol or higher also showed increased concern about their condition compared to those with a level below 53 mmol/mol. The level of concern about diabetes was observed to be higher in individuals with a coexisting condition, as opposed to those with only T1DM. In addition, those not currently studying reflected higher concern about diabetes than those who were students at that moment. In the Self-Care dimension, individuals with an A1C level below 53 mmol/mol demonstrated significantly higher self-care scores compared to those with an A1C level of 53 mmol/mol or higher. This difference was characterized by a medium effect size. 3.3. Relationships of Participants’ Quality of Life with Their Demographic Characteristics and Clinical Diabetes Determinants The ANOVA analysis demonstrated the association of factors such as the civil status, geographic dispersion, BMI, living situation, type of education, and employment status on each HRQoL in the T1DM dimension (Table S3). A significant correlation was observed between Well-Being and BMI classifications. Notably, there were marked differences in well-being levels between emerging adults of normal weight and those classified as having class I obesity. Similarly, another significant correlation was identified between Well-Being and education levels. Considerable differences in Well-Being were observed among emerging adults with varying levels of education. The lowest levels of Well-Being were found in individuals who had only completed compulsory secondary education, in contrast to those with higher educational attainments, including high school, higher degree, undergraduate, and postgraduate levels. While the ANOVA analysis revealed significant correlations between civil status and living situation with aspects of Well-Being, the post hoc analysis did not confirm these differences. However, the ANOVA results suggested a higher level of well-being among single individuals and increased interference in life for those living independently. To provide a comprehensive visual overview of the findings from both the t-Student and ANOVA tests, a detailed pictorial scheme is presented following this section (Figure 2). J. Clin. Med. 2024,13, 240 8 of 15 This summary visually encapsulates the key insights and patterns that emerged from the analyses conducted in Sections 3.2 and 3.3. J. Clin. Med. 2024, 13, x FOR PEER REVIEW 8 of 15 those with higher educational attainments, including high school, higher degree, undergraduate, and postgraduate levels. While the ANOVA analysis revealed significant correlations between civil status and living situation with aspects of Well-Being, the post hoc analysis did not confirm these differences. However, the ANOVA results suggested a higher level of well-being among single individuals and increased interference in life for those living independently. To provide a comprehensive visual overview of the findings from both the t-Student and ANOVA tests, a detailed pictorial scheme is presented following this section (Figure 2). This summary visually encapsulates the key insights and patterns that emerged from the analyses conducted in Sections 3.2 and 3.3. Figure 2. Key factors reducing Health-Related Quality of Life in Type 1 diabetes mellitus—insights from t-Student and ANOVA. 1 A1C: Glycosylated hemoglobin A1C. 2 T1DM: Type 1 diabetes mellitus. 3 BMI: Body Mass Index. 4 HRQoL: Health-Related to Quality of Life.↑:Increase in variable value. 3.4. Pearson Correlations between Sex, Age, Body Mass Index, A1C, Age at Diagnosis, Disease Evolution Time, and HRQOL in T1DM Dimensions of Vida1 Questionnaire Pearson correlation analysis indicated that Interference with Life was related to sex, age, and age at diagnosis. In contrast, Self-Care was found correlated solely with A1C levels. Both Concern about the Condition and Well-Being demonstrated correlations with sex and A1C levels, with Well-Being also showing a relationship with BMI. The duration of diabetes did not show significant correlations with any of the HRQoL in T1DM dimensions. Detailed intercorrelations among other variables are presented in Table 4. Table 4. Correlation results between dimensions of Health-Related Quality of Life and sociodemographic and clinical diabetes determinants. Variables Interference with Life Self-Care Well-Being Concern about the Condition Sex 0.0105 * 0.166* −0.264 *** Age 0.176 ** Body Mass Index −0.168 ** Glycosylated hemoglobin −0.335 *** 0.124 * −0.182 *** Age at diagnosis 0.116 * * p <0.05; ** p <0.01; *** p <0.001. FACTORS REDUCING HRQoL4 IN EMERGING ADULTS WITTH T1DM INTERFERENCE WITH LIFE DIABETES DIAGNOSTIC: 18+ AGE GROUP: 25–29 WELL-BEING SELF-CARE A1C1 ↑ CONCERN ABOUT THE CONDITION A1C1 ↑ NOT CURRENTLY STUDYING A1C1 ↑ BMI3 ↑ LOWER EDUCATION LEVEL DIABETES DURATION: <5 YEARS T1DM2 + OTHERS T1DM2 + OTHERS T1DM2 + OTHERS Figure 2. Key factors reducing Health-Related Quality of Life in Type 1 diabetes mellitus—insights from t-Student and ANOVA. 1 A1C: Glycosylated hemoglobin A1C. 2 T1DM: Type 1 diabetes mellitus. 3BMI: Body Mass Index. 4HRQoL: Health-Related to Quality of Life.↑: Increase in variable value. 3.4. Pearson Correlations between Sex, Age, Body Mass Index, A1C, Age at Diagnosis, Disease Evolution Time, and HRQOL in T1DM Dimensions of Vida1 Questionnaire Pearson correlation analysis indicated that Interference with Life was related to sex, age, and age at diagnosis. In contrast, Self-Care was found correlated solely with A1C levels. Both Concern about the Condition and Well-Being demonstrated correlations with sex and A1C levels, with Well-Being also showing a relationship with BMI. The duration of diabetes did not show significant correlations with any of the HRQoL in T1DM dimensions. Detailed intercorrelations among other variables are presented in Table 4. Table 4. Correlation results between dimensions of Health-Related Quality of Life and sociodemographic and clinical diabetes determinants. Variables Interference with Life Self-Care Well-Being Concern about the Condition Sex 0.0105 * 0.166* −0.264 *** Age 0.176 ** Body Mass Index −0.168 ** Glycosylated hemoglobin −0.335 *** 0.124 * −0.182 *** Age at diagnosis 0.116 * *p<0.05; ** p<0.01; *** p<0.001. 3.5. Multiple Regression Analyses for Each Dimension of Quality of Life in Type 1 Diabetes (Interference with Life, Self-Care, Well-Being, and Concern about the Condition) In the multivariable analysis, only variables that were statistically significant in the univariate analysis were included. Age, with a predictive power of 2.8%, was found to predict Interference with Life. Self-Care was predicted by A1C, which accounted of 11.2% of the variance (R 2 ). Well-Being was predicted by sex, A1C, and BMI, collectively contributing to an R 2 of 11.5%. Concern about the Condition had two significant predictors: sex and A1C, with an R2of 3.8%. Details of each regression model are in Table 5. J. Clin. Med. 2024,13, 240 9 of 15 Table 5. Regression analysis examining sociodemographic and clinical diabetes determinants of each dimension of Health-Related Quality of Life. Interference with Life Stand. C. Beta Adjusted R2 Age 0.176 0.028 F (1.360) =11.563; p< 0.05; R2= 0.031 Self-Care Stand. C. beta Adjusted R2 Glycosylated hemoglobin −0.378 *** 0.112 F (3.358) =19.893; p< 0.05; R2= 0.112 Well-Being Stand. C. beta Adjusted R2 Sex −0.255 *** 0.067 Glycosylated hemoglobin −0.173 *** 0.098 Body Mass Index −0.142 ** 0.115 F (3.358) = 16.672; p< 0.05; R2= 0.123 Concern about the Condition Stand. C. beta Adjusted R2 Sex 0.166 ** 0.025 Glycosylated hemoglobin 0.207 * 0.038 F (2.359) = 8.066; p< 0.05; R2= 0.043 *p<0.05; ** p<0.01; *** p<0.001. In this study, no correction for multiple testing—such as the Bonferroni method—was applied. However, it is noteworthy that even if such a correction had been employed, the significance of all predictors would have been retained, with p-values remaining below 0.0125 (calculated as α = 0.05/4). The only exception to this was A1C as a predictor of Concern about the Condition, which did not maintain its significance under this adjusted threshold. 4. Discussion This study reveals that in Andalusia, emerging adults with T1DM generally experience good HRQoL in T1DM, characterized by high levels of well-being and self-care, coupled with low levels of life interference. However, concerns related to diabetes remain significant. Despite the apparent homogeneity, variations are observed within the Interference with Life dimension, particularly among women and those living independently. Factors such as coexisting conditions, diagnosis of T1DM at or after age 18, or a shorter duration of T1DM may contribute to increased interference with life. Age emerged as the key predictor in this dimension. Regarding Self-Care, participants with an A1C level below 53 mmol/mol exhibited higher self-care levels, with A1C identified as predictor. Lower well-being levels were associated with being female, having an A1C above 53 mmol/mol, comorbidities, marital status, obesity, or lower educational levels. Predictors for Well-Being included A1C, BMI, and sex. Concern about diabetes was notably higher among women, individuals with A1C above 53 mmol/mol, and those not currently engaged in studies. Sex and A1C were identified as predictive factors for this dimension. When compared to findings in the study by Alvarado-Martel et al. [ 28 ] on emerging adults with T1DM, similar mean scores can be observed in the dimensions of Interference with Life (27.4 SD 10.3 vs. 27.8 SD 7.8) and Self-Care (40.2 SD 5.5 vs. 40.2 SD 7.7). However, greater differences emerge in the Well-Being (21.3 SD 5.1 vs. 23.1 SD 4.7) and Concern about the Condition (17.9 SD 4.9 vs. 18.5 SD 3.7) dimensions, with our participants showing lower levels of Well-being and Concern about the Condition. In the study by Alvarado-Martel et al. [ 28 ], the levels of A1C <53 mmol/mol were found to correlate with higher Self-Care scores and a lower concern about diabetes, a finding