Kalman Filter Implementation of Subglottal Impedance-Based Inverse Filtering to Estimate Glottal Airflow during Phonation.

OBJECTIVES

The present research was conducted aiming at assessing the association of socioeconomic inequality in the prevalence of risk factors associated with cardio-metabolic disorders in a sample population of nationally representative Iranian adolescents and to identify its influencing factors.

METHODS

This study was conducted as part of a national-based surveillance program performed on 5625 individuals aged 10-18 years in 27 provinces in Iran. To determine the socioeconomic status (SES) of participants, we defined a new variable by applying the principal component analysis. Doing so, the socioeconomic inequality in cardio-metabolic risk factors was examined over the tertiles of SES using concentration index (C). Then, Oaxaca-Blinder decomposition analysis was carried out in order to decide upon the roots of inequality in the health system.

RESULTS

The mean (standard deviation) age of participants was 14.73 (2.41) years. The prevalence of cardio-metabolic parameters had considerable difference across SES tertiles. Elevated fasting blood glucose (FBG), elevated triglycerides (TG), abdominal obesity, elevated total cholesterol (TC), and metabolic syndrome (MetS) increased linearly by increasing SES tertiles. C index for depressed high density lipoprotein- cholesterol (HDL-C) was negative, which was suggestive of inequality in favor of high SES groups and for other cardio-metabolic parameters, it was positive, which indicate inequality was in favor of the lowest SES groups. The highest gap between the first and third tertiles of socioeconomic was for frequency of abdominal obesity; 13.18% of the lowest SES groups and 20.11% of the highest SES groups had abdominal obesity which accounts 6.93% gap in favor of the highest SES groups. The living area could be named as the main variables standing for the inequality of elevated FBS, elevated LDL-c, low HDL-c and abdominal obesity frequency between the first and the last SES group. In addition, BMI could stand as the main independent variable explaining the gap in elevated TG, elevated TC, elevated BP and MetS prevalence across the lowest and the highest SES group.

CONCLUSIONS

The study revealed the considerable inequality in the prevalence of cardio-metabolic risk factors between the highest and the lowest SES groups of Iranian adolescents. Living area and BMI are the two main factors which explained inequality in prevalence of cardio metabolic risk factors between SES groups. These estimations could provide health policy markers with practical information for future complementary analyses.