Socioeconomic gradients in cardiovascular risk in Canadian children and adolescents

Shi, Yipu; Groh, Margaret de; Bancej, Christina

doi:10.24095/hpcdp.36.2.02

Cited by 14 publications

(12 citation statements)

References 39 publications

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“…This can be attributed to the impact of higher educational level on health awareness and habits such as eating habits and physical activity [76]. It is therefore recommended that low-educated parents raise awareness of early CVD risk in their children [77]. A significant relationship was observed between parental education and the weight of children in a group of more than 1,500 Sicilian children-the obesity prevalence was significantly higher regarding low education of the mother or father [78].…”

Section: Discussionmentioning

confidence: 99%

The Prevalence of Insulin Resistance and the Associated Risk Factors in a Sample of 14–18-Year-Old Slovak Adolescents

Jurkovičová¹,

Hirošová²,

Vondrová³

et al. 2020

Preprint

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The prevalence of cardiometabolic risk factors has increased in Slovakian adolescents as a result of serious lifestyle changes. This cross-sectional study aimed to assess the prevalence of insulin resistance (IR) and the associations with cardiometabolic and selected lifestyle risk factors in a sample of Slovak adolescents. In total, 2,629 adolescents (45.8% males) aged between 14 and 18 years were examined in the study. Anthropometric parameters, blood pressure, and resting heart rate were measured, fasting venous blood samples were analysed, and HOMA-IR was calculated. The mean HOMA-IR was 2.45±1.91 without a significant intersexual difference. IR (cut-off point for HOMA-IR=3.16) was detected in 18.6% of adolescents (19.8% males, 17.6% females). IR was strongly associated with overweight/obesity (especially central) and with almost all monitored cardiometabolic factors, except for TC and systolic BP in females. The multivariate model selected variables such as low level of physical fitness, insufficient physical activity, breakfast skipping, a small number of daily meals, frequent consumption of sweetened beverages, and low educational level of fathers as the significant risk factors of IR in adolescents. Recognizing the main lifestyle risk factors and early IR identification is important in terms of the performance of preventive strategies. Weight reduction, regular physical activity, and healthy eating habits can improve insulin sensitivity and decrease the incidence of metabolic syndrome, type 2 diabetes, and CVD in adulthood.

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Section: Discussionmentioning

confidence: 99%

The Prevalence of Insulin Resistance and the Associated Risk Factors in a Sample of 14–18-Year-Old Slovak Adolescents

Jurkovičová¹,

Hirošová²,

Vondrová³

et al. 2020

Preprint

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“…These programs (U.S. Department of Health & Human Services Administration for Children & Families, 2015) provide comprehensive early childhood education, health, nutrition, and parental involvement services to lowincome children and their families. Low SES is a known risk factor for high BP in children and adolescents (Shi, de Groh, & Bancej, 2016). Inclusion criteria were age of 3-5 years, enrollment in an HS program, ability to speak and understand instructions given in English, and written parental consent.…”

Section: Methodsmentioning

confidence: 99%

Factors That Influence Blood Pressure in 3- to 5-Year-Old Children: A Pilot Study

Rice

Turner-Henson

Hage

et al. 2017

Biological Research For Nursing

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While incident elevations in blood pressure (BP) are apparent in preschool years, factors influencing BP in this population have received little attention. The purposes of this pilot study were to determine the feasibility of collecting data from preschoolers and their mothers and to determine effect sizes of relationships between BP and sex, race, birth status, body mass index (BMI), waist circumference (WC), geographic location, serum C-reactive protein (CRP), and salivary cortisol (morning, afternoon). A hypothesis-generating correlational design was used; 56 children, aged 3–5 years, were enrolled from six rural and urban Head Start programs in a southeastern state. On Day 1 of data collection, mothers completed demographic questionnaires and children had blood drawn by finger stick. On Day 2, children gave saliva samples for cortisol, were measured for height by stadiometer, weight by digital scales, and WC by tape measure and had their BP measured by Dinamap. Incident elevations in BP were found in 30% of children (17/56), the majority of which were of systolic BP; 65% of those with elevations were of normal weight. Data collection was feasible with few problems. Small-to-medium effect sizes were noted for BP status (normal, prehypertensive, and hypertensive) and cortisol p.m. and birth status (parent-reported prematurity or term); small effect sizes were seen for BP status and BMI, race, sex, and geographic location. CRP and cortisol had medium- and small-to-medium effect sizes, respectively, with diastolic blood pressure. Studies with larger, more diverse samples need to be conducted to test hypotheses posited from these estimated effect sizes.

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“…The importance of these trends to public health and wellbeing are not clear because current rate of investigating and publishing the trends of the CHMS variables is not satisfying. There were less than ten trends of the CHMS variables published between 2015 and 2017 including those only considering selected populations[ 48 , 54 , 55 ]. It can take more than ten years to have a comprehensive understanding in the trends of the biomarkers or physical activities or other variables, given the large numbers of variables in national surveys.…”

Section: Discussionmentioning

confidence: 99%

“…Currently the CHMS data have been mostly used as a novel data source[ 12 , 18 – 23 , 56 , 57 ], rather than a continuous effort to monitor population health. Only several outcomes have been studied continuously among selected populations[ 48 , 54 , 55 ], in addition to the biomonitoring activities by Health Canada[ 24 – 26 ].…”

Section: Discussionmentioning

confidence: 99%

Trend analysis for national surveys: Application to all variables from the Canadian Health Measures Survey cycle 1 to 4

Chao

et al. 2018

PLoS ONE

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BackgroundTrend analysis summarizes patterns over time in the data to show the direction of change and can be used to investigate uncertainties in different time points and associations with other factors. However, this approach is not widely applied to national surveys and only selected outcomes are investigated. This study demonstrates a research framework to conduct trend analysis for all variables in a national survey, the Canadian Health Measures Survey (CHMS).Data and methodsThe CHMS cycle 1 to 4 was implemented between 2007 and 2015. The characteristics of all variables were screened and associated to the weight variables. Missing values were identified and cleaned according to the User Guide. The characteristics of all variables were extracted and used to guide data cleaning. Trend analysis examined the statistical significance of candidate predictors: the cycles, age, sex, education, household income and body mass index (BMI). R (v3.2) and RStudio (v0.98.113) were used to develop the framework.ResultsThere were 26557 variables in 79 data files from four cycles. There were 1055 variables significantly associated with the CHMS cycles and 2154 associated with the BMI after controlling for other predictors. The trend of blood pressure was similar to those published.ConclusionTrend analysis for all variables in the CHMS is feasible and is a systematic approach to understand the data. Because of trend analysis, we have detected data errors and identified several environmental biomarkers with extreme rates of change across cycles. The impact of these biomarkers has not been well studied by Statistics Canada or others. This framework can be extended to other surveys, especially the Canadian Community Health Survey.

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Socioeconomic gradients in cardiovascular risk in Canadian children and adolescents

Cited by 14 publications

References 39 publications

The Prevalence of Insulin Resistance and the Associated Risk Factors in a Sample of 14–18-Year-Old Slovak Adolescents

The Prevalence of Insulin Resistance and the Associated Risk Factors in a Sample of 14–18-Year-Old Slovak Adolescents

Factors That Influence Blood Pressure in 3- to 5-Year-Old Children: A Pilot Study

Trend analysis for national surveys: Application to all variables from the Canadian Health Measures Survey cycle 1 to 4

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