The prevalence of prediabetes, diabetes, and insulin resistance among urban obese children of south Andhra Pradesh in India

Determinants of childhood and adolescent obesity and it's effect on metabolism in South Indian population

OBJECTIVES

The primary objective is to determine the risk factors underlying the development of childhood and adolescent obesity. The secondary objective is to determine the predictors of metabolic syndrome (MetS) in childhood and adolescent obesity and its metabolic alterations in the South Indian population.

METHODS

This is a cross-sectional study conducted over two years. We have screened 3,195 school children and adolescents from lower and lower-middle socioeconomic groups. From this pool, by random cluster sampling technique, we have included 166 overweight and obese individuals and 38 control subjects. We have analyzed their sociodemographic, dietary, lifestyle, anthropometric, clinical, and metabolic parameters.

RESULTS

The prevalence of overweight and obesity in rural areas was 14.2 and 7.6 %, respectively, and in urban areas, it was 16.1 and 8.8 %, respectively. The age distribution of the control and study group is 12.3 ± 1.5 and 13.0 ± 1.9 years with a male-to-female ratio of 1.4:1 and 1.6:1, respectively. Our study found a higher average consumption of energy-dense food and screen time in the obese group compared to the control group. The average outdoor play time was 1.5 h per day in the control group and less than 0.5 h per day in the obese group. In our study, the waist-to-height ratio (WHtR) optimum cutoff value of 0.56, has 95 % sensitivity and 84 % specificity, effectively identifying MetS cases. HOMA-IR optimum cutoff value of 2.25, has 96 % sensitivity and 72 % specificity. The triglyceride-glucose index (TGI) optimum cutoff value of 4.51, has 92 % sensitivity and 88 % specificity indicating a strong balance between correctly identifying positive and negative MetS cases.

CONCLUSIONS

Our study found that even in lower socioeconomic status, there is a higher prevalence of childhood and adolescent obesity due to an urbanized lifestyle in rural areas, a sedentary lifestyle, higher consumption of low-cost energy-dense foods, and higher screening time in this electronic era. We also conclude that WHtR is a simple anthropometric marker that predicts MetS more effectively than BMI and WHR among children and adolescents. HOMA-IR and TGI are effective biochemical markers to identify metabolically unhealthy obesity early.

How close are children with obesity to becoming an adult with chronic illnesses?

OBJECTIVES

Childhood obesity has become a global threat due to its serious negative consequences. We aimed to determine the patterns of metabolic syndrome and cardio-metabolic risk factors in Turkish children with obesity.

METHODS

We examined 169 schoolchildren with obesity in April and May 2019 in Samsun, Turkey. After clinical evaluation and anthropometric measurements, fasting blood samples were collected to measure total cholesterol, low and high-density lipoprotein, fasting blood glucose, triglycerides, and insulin levels.

RESULTS

The proportion of those who met the metabolic syndrome criteria in boys was 14.3%, but it was twice as high in girls (28.2%). The most prevalent component of cardio-metabolic risk factor was increased waist circumference (96.4%) followed by a high homeostasis model assessment insulin resistance index (74.6%) and high blood pressure (29.0%). While the average high-density lipoprotein was higher in boys than in girls, on the contrary, insulin, HbA1c, and homeostasis model assessment insulin resistance concentrations were higher in girls. The prevalence of dyslipidemia was also higher in girls (67.1%) than in boys (47.6%), as were all impaired metabolic syndrome components.

CONCLUSIONS

One in five children with obesity was at risk of metabolic syndrome. For early intervention and prevention, children with obesity should be monitored in terms of cardio-metabolic risk factors, but obese girls are more prioritized.

Independent and combined influences of physical activity, screen time, and sleep quality on adiposity indicators in Indian adolescents

BACKGROUND

Inadequate physical activity (PA), excess screen time (ST), and sub-optimal sleep quality tend to co-occur during adolescence. Yet, little is known about the associations of these behaviors as a cluster with adiposity indicators in Indian adolescents. This study aimed to evaluate the independent and combined influences of PA, ST, and sleep quality on body mass index (BMI) and waist to height ratio (WHtR) in 10-15 years old adolescents in Mumbai, India. A secondary aim was to explore if these influences vary between sexes.

METHODS

Cross-sectional study. Adolescents (n = 772, mean age 13.2 (1.4) years) reported frequency and duration of moderate to vigorous PA (MVPA) and time spent using screens on a previously validated instrument. Sleep quality was estimated using the Pittsburg Sleep Quality Index (PSQI). Weight, height, and waist circumference were measured. Mixed effect logistic regression analyses were performed to explore associations between adiposity indicators (BMI z scores > +1SD and WHtR > 0.5) and unhealthy behaviors (PA < 60 min/d, ST > 120 min/d and PSQI scores > 5), stratified by sex.

RESULTS

The combined prevalence of overweight and obesity was 38.3%. Overall, 62.0 and 85.0% reported MVPA< 60 min/d and ST > 120 min/d respectively. Girls reported higher ST (218.21 (69.01) min/d) as compared to boys (165.3 (101.22) min/d, p < 0.001). Clustering of low PA and excess ST was observed in 69.2% and of all three unhealthy behaviors in 18.8%. Among girls, MVPA < 60 min/d (OR = 1.78, 95% CI 1.54-1.92, p < 0.001) and PSQI scores > 5 (OR = 2.01, 95% CI 1.78-2.25, p < 0.001) predicted increased BMI. The odds of overweight/obesity were 2.10 times higher in boys reporting low PA and 4.13 times higher in those with low PA+ ST > 120 min/d. Clustering of all three unhealthy behaviors increased prevalence of obesity in both sexes.

CONCLUSIONS

The results indicated a co-existence of multiple unhealthy lifestyle factors of obesity and that clustering of these behaviors can further aggravate obesity risk as compared to their independent effects. Integrated interventions that leverage the cumulative benefits of being active, less sedentary and sufficient sleep are warranted to facilitate greater improvements in obesity risk behaviors.

Exploring the Prevalence of Undiagnosed Prediabetes, Type 2 Diabetes Mellitus, and Risk Factors in Adolescents: A Systematic Review

PROBLEM

The prevalence of prediabetes and type 2 diabetes (T2D) is increasing in adolescents worldwide. Most studies have focused on the clinical features, treatment, and complications for adolescents and so the need to generate insight into the risk factors and prevalence of undiagnosed prediabetes and T2D in adolescents across the globe remains.

ELIGIBILITY CRITERIA

Relevant articles that were published from 2007 up to and including January 2017 were identified through electronic searches of CINAHL, Cochrane, Medline, PsycInfo, PubMed, Scopus, Web of Science, and Sociological Abstracts (Proquest). Four independent researchers examined the articles for eligibility.

SAMPLE

Sixteen studies were included that investigated the risk and prevalence of undiagnosed prediabetes and T2D in adolescents aged 12-19.

RESULTS

The most commonly measured risk factors included obesity/overweight, family history, and ethnicity. Other studies measured risk factors associated with insulin resistance, including hypertension, acanthosis nigricans, and dyslipidemia. Prevalence of undiagnosed prediabetes and T2D varied among regions globally with rates ranging from 3.3 to 14.3% and 0.1 to 2.2%, respectively.

CONCLUSIONS

Undiagnosed prediabetes and T2D and the associated risk factors are prevalent in many regions in countries worldwide, significantly impacting adolescents and their families.

IMPLICATIONS

Future research is required to inform interventions aimed at preventative measures for early screening and detection of prediabetes and T2D in adolescents, as well as the development of multi-disciplinary teams that include pediatric nurses and the specialized care they provide.