[Show abstract][Hide abstract] ABSTRACT: As universal screening of hypertension performs poorly in childhood, targeted screening to children at higher risk of hypertension has been proposed. Our goal was to assess the performance of combined parental history of hypertension and overweight/obesity to identify children with hypertension. We estimated the sensitivity, specificity, negative and positive predictive values of overweight/obesity and parental history of hypertension for the identification of hypertension in children.
We analyzed data from a school-based cross-sectional study including 5207 children aged 10 to 14 years from all public 6th grade classes in the canton of Vaud, Switzerland. Blood pressure was measured with a clinically validated oscillometric automated device over up to three visits separated by one week. Children had hypertension if they had sustained elevated blood pressure over the three visits. Parents were interviewed about their history of hypertension.
The prevalence of hypertension was 2.2%. 14% of children were overweight or obese and 20% had a positive history of hypertension in either or both parents. 30% of children had either or both conditions. After accounting for several potential confounding factors, parental history of hypertension (odds ratio (OR): 2.6; 95% confidence interval (CI): 1.8-4.0), overweight excluding obesity (OR: 2.5; 95% CI: 1.5-4.2) and obesity (OR: 10.1; 95% CI: 6.0-17.0) were associated with hypertension in children. Considered in isolation, the sensitivity and positive predictive values of parental history of hypertension (respectively 41% and 5%) or overweight/obesity (respectively 43% and 7%) were relatively low. Nevertheless, considered together, the sensitivity of targeted screening in children with either overweight/obesity or paternal history of hypertension was higher (65%) but the positive predictive value remained low (5%). The negative predictive value was systematically high.
Restricting screening of hypertension to children with either overweight/obesity or with hypertensive parents would substantially limit the proportion of children to screen (30%) and allow the identification of a relatively large proportion (65%) of hypertensive cases. That could be a valuable alternative to universal screening.
[Show abstract][Hide abstract] ABSTRACT: Several guidelines recommend universal screening for hypertension in childhood and adolescence. Targeted screening to children with parental history of hypertension could be a more efficient strategy than universal screening. Therefore, we assessed the association between parental history of hypertension and hypertension in children, and estimated the sensitivity, specificity, negative, and positive predictive values of parental history of hypertension for hypertension in children.
The present study was a school-based cross-sectional study including 5207 children aged 10-14 years from all public 6th grade classes in the Canton of Vaud, Switzerland. Children had hypertension if they had sustained elevated blood pressure over three separate visits.
In children, the prevalence of hypertension was 2.2%. Some 8.5% of mothers and 12.9% of fathers reported to be hypertensive. Maternal history of hypertension (odds ratio 2.0, 95% confidence interval 1.2-3.3) and paternal history of hypertension (odds ratio 2.2, 95% confidence interval 1.4-3.6) were independent risk factors for hypertension in children. Nevertheless, the sensitivity of parental history of hypertension for the identification of hypertension in children was low (from 4% for both parents' positive history up to 41% for at least one parent's positive history). Positive predictive values were also low (between 4 and 5%).
Children with hypertensive parents were at higher risk of hypertension. Nevertheless, parental history of hypertension helped only marginally to identify hypertension in offspring. Targeting screening only toward children with a parental history of hypertension may not be a substantially better strategy to identify hypertension in children compared with universal screening.
Journal of Hypertension 03/2015; 33(6). DOI:10.1097/HJH.0000000000000560 · 4.72 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Overdiagnosis is the diagnosis of an abnormality that is not associated with a substantial health hazard and that patients have no benefit to be aware of. It is neither a misdiagnosis (diagnostic error), nor a false positive result (positive test in the absence of a real abnormality). It mainly results from screening, use of increasingly sensitive diagnostic tests, incidental findings on routine examinations, and widening diagnostic criteria to define a condition requiring an intervention. The blurring boundaries between risk and disease, physicians' fear of missing a diagnosis and patients' need for reassurance are further causes of overdiagnosis. Overdiagnosis often implies procedures to confirm or exclude the presence of the condition and is by definition associated with useless treatments and interventions, generating harm and costs without any benefit. Overdiagnosis also diverts healthcare professionals from caring about other health issues. Preventing overdiagnosis requires increasing awareness of healthcare professionals and patients about its occurrence, the avoidance of unnecessary and untargeted diagnostic tests, and the avoidance of screening without demonstrated benefits. Furthermore, accounting systematically for the harms and benefits of screening and diagnostic tests and determining risk factor thresholds based on the expected absolute risk reduction would also help prevent overdiagnosis.
Swiss medical weekly: official journal of the Swiss Society of Infectious Diseases, the Swiss Society of Internal Medicine, the Swiss Society of Pneumology 01/2015; 145:w14060. DOI:10.4414/smw.2015.14060 · 2.09 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Objective:
To describe the goals and methods of contemporary public health surveillance and to present the activities of the Observatoire Valaisan de la Santé (OVS), a tool unique in Switzerland to conduct health surveillance for the population of a canton.
Narrative review and presentation of the OVS.
Public health surveillance consists of systematic and continuous collection, analysis, interpretation and dissemination of health data necessary for public health planning. Surveillance is organized according to contemporary public health issues. Switzerland is currently in an era dominated by chronic diseases due to ageing of the population. This "new public health" era is also characterized by the growing importance of health technology, rational risk management, preventive medicine and health promotion, and the central role of the citizen/patient. Information technologies provide access to new health data, but public health surveillance methods need to be adapted. In Switzerland, health surveillance activities are conducted by several public and private bodies, at federal and cantonal levels. The Valais canton has set up the OVS, an integrative, regional, and reactive system to conduct surveillance.
Public health surveillance provides information useful for public health decisions and actions. It constitutes a key element for public health planning.
[Show abstract][Hide abstract] ABSTRACT: Objective
Although dual-energy X-ray absorptiometry (DEXA) is the preferred method to estimate adiposity, body mass index (BMI) is often used as a proxy. However, the ability of BMI to measure adiposity change among youth is poorly evidenced. This study explored which metrics of BMI change have the highest correlations with different metrics of DEXA change.
Data were from the Quebec Adipose and Lifestyle Investigation in Youth cohort, a prospective cohort of children (8–10 years at recruitment) from Québec, Canada (n=557). Height and weight were measured by trained nurses at baseline (2008) and follow-up (2010). Metrics of BMI change were raw (ΔBMIkg/m2), adjusted for median BMI (ΔBMIpercentage) and age-sex-adjusted with the Centers for Disease Control and Prevention growth curves expressed as centiles (ΔBMIcentile) or z-scores (ΔBMIz-score). Metrics of DEXA change were raw (total fat mass; ΔFMkg), per cent (ΔFMpercentage), height-adjusted (fat mass index; ΔFMI) and age-sex-adjusted z-scores (ΔFMz-score). Spearman's rank correlations were derived.
Correlations ranged from modest (0.60) to strong (0.86). ΔFMkg correlated most highly with ΔBMIkg/m2 (r = 0.86), ΔFMI with ΔBMIkg/m2 and ΔBMIpercentage (r = 0.83–0.84), ΔFMz-score with ΔBMIz-score (r = 0.78), and ΔFMpercentage with ΔBMIpercentage (r = 0.68). Correlations with ΔBMIcentile were consistently among the lowest.
In 8–10-year-old children, absolute or per cent change in BMI is a good proxy for change in fat mass or FMI, and BMI z-score change is a good proxy for FM z-score change. However change in BMI centile and change in per cent fat mass perform less well and are not recommended.
Archives of Disease in Childhood 05/2014; 99(11). DOI:10.1136/archdischild-2013-305163 · 2.90 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In contrast to obesity, information on the health risks of underweight is sparse. We examined the long-term association between underweight and mortality by considering factors possibly influencing this relationship.
We included 31,578 individuals aged 25-74 years, who participated in population based health studies between 1977 and 1993 and were followed-up for survival until 2008 by record linkage with the Swiss National Cohort (SNC). Body Mass Index (BMI) was calculated from measured (53% of study population) or self-reported height and weight. Underweight was defined as BMI < 18.5kg/m2. Cox regression models were used to determine mortality Hazard Ratios (HR) of underweight vs. normal weight (BMI 18.5- < 25.0kg/m2). Covariates were study, sex, smoking, healthy eating proxy, sports frequency, and educational level.
Underweight individuals represented 3.0% of the total study population (n = 945), and were mostly women (89.9%). Compared to normal weight, underweight was associated with increased all-cause mortality (HR: 1.37; 95%CI: 1.14-1.65). Increased risk was apparent in both sexes, regardless of smoking status, and mainly driven by excess death from external causes (HR: 3.18; 1.96-5.17), but not cancer, cardiovascular or respiratory diseases. The HR were 1.16 (0.88-1.53) in studies with measured BMI and 1.59 (1.24-2.05) with self-reported BMI.
The increased risk of dying of underweight people was mainly due to an increased mortality risk from external causes. Using self-reported BMI may lead to an overestimation of mortality risk associated with underweight.
BMC Public Health 04/2014; 14(1):371. DOI:10.1186/1471-2458-14-371 · 2.26 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The diagnosis of hypertension in children is difficult because of the multiple sex-, age-, and height-specific thresholds to define elevated blood pressure (BP). Blood pressure-to-height ratio (BPHR) has been proposed to facilitate the identification of elevated BP in children.
We assessed the performance of BPHR at a single screening visit to identify children with hypertension that is sustained elevated BP.
In a school-based study conducted in Switzerland, BP was measured at up to three visits in 5207 children. Children had hypertension if BP was elevated at the three visits. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for the identification of hypertension were assessed for different thresholds of BPHR. The ability of BPHR at a single screening visit to discriminate children with and without hypertension was evaluated with receiver operating characteristic (ROC) curve analyses.
The prevalence of systolic/diastolic hypertension was 2.2%. Systolic BPHR had a better performance to identify hypertension compared with diastolic BPHR (area under the ROC curve: 0.95 vs. 0.84). The highest performance was obtained with a systolic BPHR threshold set at 0.80 mmHg/cm (sensitivity: 98%; specificity: 85%; PPV: 12%; and NPV: 100%) and a diastolic BPHR threshold set at 0.45 mmHg/cm (sensitivity: 79%; specificity: 70%; PPV: 5%; and NPV: 99%). The PPV was higher among tall or overweight children.
BPHR at a single screening visit had a high performance to identify hypertension in children, although the low prevalence of hypertension led to a low PPV.
Journal of Hypertension 03/2014; 32(5). DOI:10.1097/HJH.0000000000000152 · 4.72 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Control of blood pressure (BP) remains a major challenge in primary care. Innovative interventions to improve BP control are therefore needed. By updating and combining data from 2 previous systematic reviews, we assess the effect of pharmacist interventions on BP and identify potential determinants of heterogeneity.
Randomized controlled trials (RCTs) assessing the effect of pharmacist interventions on BP among outpatients with or without diabetes were identified from MEDLINE, EMBASE, CINAHL, and CENTRAL databases. Weighted mean differences in BP were estimated using random effect models. Prediction intervals (PI) were computed to better express uncertainties in the effect estimates. Thirty-nine RCTs were included with 14 224 patients. Pharmacist interventions mainly included patient education, feedback to physician, and medication management. Compared with usual care, pharmacist interventions showed greater reduction in systolic BP (-7.6 mm Hg, 95% CI: -9.0 to -6.3; I(2)=67%) and diastolic BP (-3.9 mm Hg, 95% CI: -5.1 to -2.8; I(2)=83%). The 95% PI ranged from -13.9 to -1.4 mm Hg for systolic BP and from -9.9 to +2.0 mm Hg for diastolic BP. The effect tended to be larger if the intervention was led by the pharmacist and was done at least monthly.
Pharmacist interventions - alone or in collaboration with other healthcare professionals - improved BP management. Nevertheless, pharmacist interventions had differential effects on BP, from very large to modest or no effect; and determinants of heterogeneity could not be identified. Determining the most efficient, cost-effective, and least time-consuming intervention should be addressed with further research.
Journal of the American Heart Association 03/2014; 3(2):e000718. DOI:10.1161/JAHA.113.000718 · 4.31 Impact Factor