1.
24-h urinary sodium excretion and the risk of adverse outcomes.
Vuori, MA, Harald, K, Jula, A, Valsta, L, Laatikainen, T, Salomaa, V, Tuomilehto, J, Jousilahti, P, Niiranen, TJ
Annals of medicine. 2020;(8):488-496
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Abstract
AIMS: The objective was to evaluate whether sodium intake, assessed with the gold standard 24-h urinary collections, was related to long-term incidence of death, cardiovascular disease (CVD) and diabetes mellitus (DM). METHODS A cohort of 4630 individuals aged 25-64 years collected 24-h urine samples in 1979-2002 and were followed up to 14 years for the incidence of any CVD, coronary heart disease (CHD), stroke, heart failure (HF) and DM event, and death. Cox proportional hazards models were used to estimate the association between the baseline salt intake and incident events and adjusted for baseline age, body mass index, serum cholesterol, prevalent DM, and stratified by sex and cohort baseline year. RESULTS During the follow-up, we observed 423 deaths, 424 CVD events (288 CHD events, 142 strokes, 139 HF events) and 161 DM events. Compared with the highest quartile of salt intake, persons in the lowest quartile had a lower incidence of CVD (hazard ratio [HR] 0.70; 95% confidence interval [CI], 0.51-0.95, p = .02), CHD (HR 0.63 [95% CI 0.42-0.94], p = .02) and DM (HR 0.52 [95% CI 0.31-0.87], p = .01). The results were non-significant for mortality, HF, and stroke. CONCLUSION High sodium intake is associated with an increased incidence of CVD and DM.
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Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of different data sources.
Paalanen, L, Koponen, P, Laatikainen, T, Tolonen, H
European journal of public health. 2018;(4):754-765
Abstract
BACKGROUND Three data sources are generally used in monitoring health on the population level. Health interview surveys (HISs) are based on participants' self-report. Health examination surveys (HESs) yield more objective data, and also persons who are unaware of their elevated risks can be detected. Medical records (MRs) and other administrative registers also provide objective data, but their availability, coverage and quality vary between countries. We summarized studies comparing self-reported data with (i) measured data from HESs or (ii) MRs. We aimed to describe differences in feasibility and comparability of different data sources for monitoring (i) elevated blood pressure or hypertension (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol. METHODS We conducted a literature search to identify studies, which validated self-reported measures against objective measures. We found 30 studies published since the year 2000 fulfilling our inclusion criteria (targeted to adults and comparing prevalence among the same persons). RESULTS Hypertension and elevated total cholesterol were prone to be under-estimated in HISs. The under-estimate was more pronounced, when the HIS data were compared with HES data, and lower when compared with MRs. For diabetes, the HISs and the objective methods resulted in fairly similar prevalence rates. CONCLUSION The three data sources measure different manifestations of the risk factors and cannot be expected to yield similar prevalence rates. Using HIS data only may lead to under-estimation of elevated risk factor levels or disease prevalence. Whenever possible, information from the three data sources should be evaluated and combined.
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Scaling up diabetes prevention in Victoria, Australia: policy development, implementation, and evaluation.
Dunbar, JA, Jayawardena, A, Johnson, G, Roger, K, Timoshanko, A, Versace, VL, Shill, J, Philpot, B, Vartiainen, E, Laatikainen, T, et al
Diabetes care. 2014;(4):934-42
Abstract
OBJECTIVE The Australian lifestyle intervention program Life! is only the second reported, large-scale diabetes prevention program. This article describes the genesis and the successful establishment of Life! and its key outcomes for participants and implementation. RESEARCH DESIGN AND METHODS Life!, a behavior-change intervention, comprises six group sessions over 8 months. The Victorian Department of Health funded Diabetes Australia-Victoria to implement the program. Experience of the Greater Green Triangle diabetes prevention implementation trial was used for intervention design, workforce development, training, and infrastructure. Clinical and anthropometric data from participants, used for program evaluation, were recorded on a central database. RESULTS Life! has a statewide workforce of 302 trained facilitators within 137 organizations. Over 29,000 Victorians showed interest in Life!, and 15,000 individuals have been referred to the program. In total, 8,412 participants commenced a Life! program between October 2007 and June 2011, and 37% of the original participants completed the 8-month program. Participants completing sessions 1 to 5 lost an average of 1.4 kg weight (P < 0.001) and waist circumference of 2.5 cm (P < 0.001). Those completing six sessions lost an average of 2.4 kg weight (P < 0.001) and waist circumference of 3.8 cm (P < 0.001). The weight loss of 2.4 kg represents 2.7% of participants' starting body weight. CONCLUSIONS The impact of Life! is attributable to applying available evidence for the system's design of the intervention and collaboration between policy makers, implementers, and evaluators using the principles of continuous quality improvement to support successful, large-scale recruitment and implementation.