Clinical and Demographic Factors Associated With Diabetic Retinopathy Among Young Patients With Diabetes

Ferm, Michael Leonard; DeSalvo, Daniel J.; Prichett, Laura; Sickler, James K.; Wolf, Risa M.; Channa, Roomasa

doi:10.1001/jamanetworkopen.2021.26126

Cited by 20 publications

(54 citation statements)

References 61 publications

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“…Individuals with longer duration and earlier onset of DM were at increased risk of developing DR. This result was consistent with the prior literature in numerous populations (37)(38)(39)(40)(41)(42)(43). However, our sample had the advantage of being population based as opposed to hospital or clinic based, which is more the norm (41).…”

Section: Discussionsupporting

confidence: 92%

“…This pattern of association is nowhere near universal in the literature. In several studies from multiple countries, there was no association between DR and measures of obesity (18,41,48,49). Other studies have shown that increasing BMI or obesity measured using various metrics increased risk, especially among those who are obese, and, in some cases, obesity associated with more severe DR (PDR vs NPDR) (50)(51)(52)(53)(54).…”

Section: Discussionmentioning

confidence: 98%

“…This result was consistent with the prior literature in numerous populations (37-43). However, our sample had the advantage of being population based as opposed to hospital or clinic based, which is more the norm (41). Another factor that is consistent with prior literature from diverse populations was the association of DR with poorer glycaemic control as measured by either FPG or HbA1C (41, 44-47).…”

Section: Discussionmentioning

confidence: 99%

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Unusual patterns of risk for diabetic retinopathy in the Mumbai slums: The Aditya Jyot Diabetic Retinopathy in Urban Mumbai Slums Study (AJ-DRUMSS) Report 3

Krishnan

Jain

Nare

et al. 2022

Preprint

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Diabetes onset precedes diabetic retinopathy (DR) by 5-10 years, but many people with diabetes remain free of this microvascular complication. Our aim was to identify risk factors for DR progression in a unique and diverse population, the slums of Mumbai. We performed a population-based cross-sectional analysis of 1163 diabetics over 40 years of age from slums in 18 wards of Mumbai. Data was collected on 33 variables and assessed for association with DR using both univariate and multivariate analyses. Stratified analyses were also performed on males and females, separately. Among hypertensive individuals we also assessed whether duration of hypertension associated with DR. Of 31 non-correlated variables analysed as risk factors for DR, 15 showed evidence of significant association. The most prominent included sex, where being a female associated with decreased risk of DR, while longer duration of diabetes and poor glycaemic control associated with increased risk. The duration of diabetes risk was partially, but significantly, mediated by age of diabetes diagnoses (8.6% of variance explained, p = 0.012). Obesity as measured by several measures, including body mass index (BMI) and measures of central obesity had a negative association with DR; increased measures of obesity consistently reduced risk of DR. There was some agreement with risk factors described in earlier studies (e.g., duration of diabetes and glycaemic control), but other factors such as obesity measures appeared to have a reversed direction of effect compared to most prior studies. These results indicated that the overall pattern of association in the Mumbai slums was novel. Thus, in previously uncharacterized populations, such as the slums that we examined, it is important to evaluate all risk factors de novo to appropriately assess patterns of risk.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

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Unusual patterns of risk for diabetic retinopathy in the Mumbai slums: The Aditya Jyot Diabetic Retinopathy in Urban Mumbai Slums Study (AJ-DRUMSS) Report 3

Krishnan

Jain

Nare

et al. 2022

Preprint

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“…Studies across the world have shown that, the most predictive factors of diabetic retinopathy are socio-demographic and clinical variables such as age, diabetic duration, lipid profiles of a patient and microalbuminuria [5,12,13,14,15,16,17].…”

Section: Introductionmentioning

confidence: 99%

“…A study from Ethiopia reported that, gender, haemoglobin a1c (HbA1c) and hypertension are predictive risk factors of diabetic retinopathy [17]. Some studies have also revealed that the odds of diabetic retinopathy is higher for a patient with higher HbA1c [4,12,15,18], longer duration of diabetes [5,12] and hypertensive patients [4,5,17]. A study based on data from a meta-analysis of seven cohort studies reported that insulin treatment has significant association with diabetic retinopathy in patients with type II diabetes mellitus [13].…”

Section: Introductionmentioning

confidence: 99%

Application of semiparametric model in modelling diabetic retinopathy among type II diabetic patients

Yirdaw

Debusho

2022

Preprint

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Background: The proportion of patients with diabetic retinopathy (DR) has grown with increasing number of diabetic mellitus patients in the world. It is among the top risk factors of blindness worldwide, especially those living in developing countries. The main objective of this study was to identify contributing risk factors of diabetic retinopathy among type II diabetic patients. Method: A sample of 191 type II diabetic patients was selected from the Black Lion Specialized Hospital diabetic unit from 1 March 2018 to 1 April 2018. A multivariate stochastic regression imputation technique was applied to impute the missing values. The response variable, diabetic retinopathy is a categorical variable with two outcomes. Based on the relationship derived from the exploratory analysis, the odds of diabetic retinopathy were not necessarily linearly related to the continuous predictors for this sample of patients. Therefore, a semiparametric model was proposed to identify the contributing factors of diabetic retinopathy. Result: From the sample of 191 type II diabetic patients, 98(51.3%) of them experienced diabetic retinopathy. The results of semiparametric regression model revealed that gender, hypertension, insulin treatment, and frequency of clinical visits had a significant linear relationships with the odds of diabetic retinopathy. In addition, the log-odds of DR has a significant nonlinear relation with the interaction of age by gender (for female patients), duration of diabetes, interaction of cholesterol level by gender (for female patients), haemoglobin A1c, and interaction of haemoglobin A1c by fasting blood glucose with degrees of freedom 3.2, 2.7, 3.6, 2.3 and 3.7, respectively. The interaction of age by gender and cholesterol level by gender appear non significant for male patients. The result from the interaction of haemoglobin A1c (HbA1c) by fasting blood glucose (FBG) showed that the risk of diabetic retinopathy is high when the level of HbA1c and FBG were simultaneously high. Conclusion: Clinical variables related to type II diabetic patients were strong predictive factors of diabetic retinopathy. Hence, health professionals should be cautious about the possible effects and complications of diabetic mellitus which can be caused by the clinical variables. Furthermore, to improve intervention strategies similar studies should be conducted across the country.

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Insulin Pump Use and Diabetic Retinopathy—Is Technology the Key to Preventing Retinopathy in Young People With Type 1 Diabetes?

2021

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Clinical and Demographic Factors Associated With Diabetic Retinopathy Among Young Patients With Diabetes

Abstract: IMPORTANCE Diabetic retinopathy (DR) is a leading cause of vision loss worldwide. As the incidence of both type 1 and type 2 diabetes among youths continues to increase around the world, understanding the factors associated with the development of DR in this age group is important.

Cited by 20 publications

References 61 publications

Unusual patterns of risk for diabetic retinopathy in the Mumbai slums: The Aditya Jyot Diabetic Retinopathy in Urban Mumbai Slums Study (AJ-DRUMSS) Report 3

Unusual patterns of risk for diabetic retinopathy in the Mumbai slums: The Aditya Jyot Diabetic Retinopathy in Urban Mumbai Slums Study (AJ-DRUMSS) Report 3

Application of semiparametric model in modelling diabetic retinopathy among type II diabetic patients

Insulin Pump Use and Diabetic Retinopathy—Is Technology the Key to Preventing Retinopathy in Young People With Type 1 Diabetes?

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