Effects of low sodium diet versus high sodium diet on blood pressure, renin, aldosterone, catecholamines, cholesterol, and triglyceride

Graudal, Niels; Hubeck-Graudal, Thorbjørn; Jürgens, Gesche

doi:10.1002/14651858.cd004022.pub5

Cited by 53 publications

(33 citation statements)

References 279 publications

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“…These disparities in risk of and death from either form of stroke in part might explain the slightly larger reductions in incidence and deaths from haemorrhagic stroke observed in our projections. There are ongoing concerns about potential negative sideeffects of whole of populations reduction in salt intake down to 5-6 g/day, citing insufficient evidence (35) and potential unintended consequences to hormones (increased renin, adrenaline, aldosterone) and lipids (36). Most of these concerns are based on observational studies with less robust methods and short-term trials of large salt reductions (37).…”

Section: Comparisons and Implications Of The Findingsmentioning

confidence: 99%

Dietary Salt Reduction, Prevalence of Hypertension and Avoidable Burden of Stroke in Vietnam: Modelling the Health and Economic Impacts

Aminde

Phung

et al. 2021

Front. Public Health

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Dietary salt reduction has been recommended as a cost-effective population-wide strategy to prevent cardiovascular disease. The health and economic impact of salt consumption on the future burden of stroke in Vietnam is not known.Objective: To estimate the avoidable incidence of and deaths from stroke, as well as the healthy life years and healthcare costs that could be gained from reducing salt consumption in Vietnam.Methods: This was a macrosimulation health and economic impact assessment study. Data on blood pressure, salt consumption and stroke epidemiology were obtained from the Vietnam 2015 STEPS survey and the Global Burden of Disease study. A proportional multi-cohort multistate lifetable Markov model was used to estimate the impact of achieving the Vietnam national salt targets of 8 g/day by 2025 and 7 g/day by 2030, and to the 5 g/day WHO recommendation by 2030. Probabilistic sensitivity analysis was conducted to quantify the uncertainty in our projections.Results: If the 8 g/day, 7 g/day, and 5 g/day targets were achieved, the prevalence of hypertension could reduce by 1.2% (95% uncertainty interval [UI]: 0.5 to 2.3), 2.0% (95% UI: 0.8 to 3.6), and 3.5% (95% UI: 1.5 to 6.3), respectively. This would translate, respectively, to over 80,000, 180,000, and 257,000 incident strokes and over 18,000, 55,000, and 73,000 stroke deaths averted. By 2025, over 56,554 stroke-related health-adjusted life years (HALYs) could be gained while saving over US$ 42.6 million in stroke healthcare costs. By 2030, about 206,030 HALYs (for 7 g/day target) and 262,170 HALYs (for 5 g/day target) could be gained while saving over US$ 88.1 million and US$ 122.3 million in stroke healthcare costs respectively.Conclusion: Achieving the national salt reduction targets could result in substantial population health and economic benefits. Estimated gains were larger if the WHO salt targets were attained and if changes can be sustained over the longer term. Future work should consider the equity impacts of specific salt reduction programs.

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Section: Comparisons and Implications Of The Findingsmentioning

confidence: 99%

Dietary Salt Reduction, Prevalence of Hypertension and Avoidable Burden of Stroke in Vietnam: Modelling the Health and Economic Impacts

Aminde

Phung

et al. 2021

Front. Public Health

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“…Studies showed the association between nutritional determinants and overweight/obesity, dyslipidemia, hypertension and T2DM indicating the nutritional intake influences prevalence or prevention for overweight/obesity, dyslipidemia, hypertension and T2DM [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4–7th Korea National Health and Nutrition Examination Survey

Kim

Lim

Kim

2021

IJERPH

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Few studies have been conducted to classify and predict the influence of nutritional intake on overweight/obesity, dyslipidemia, hypertension and type 2 diabetes mellitus (T2DM) based on deep learning such as deep neural network (DNN). The present study aims to classify and predict associations between nutritional intake and risk of overweight/obesity, dyslipidemia, hypertension and T2DM by developing a DNN model, and to compare a DNN model with the most popular machine learning models such as logistic regression and decision tree. Subjects aged from 40 to 69 years in the 4–7th (from 2007 through 2018) Korea National Health and Nutrition Examination Survey (KNHANES) were included. Diagnostic criteria of dyslipidemia (n = 10,731), hypertension (n = 10,991), T2DM (n = 3889) and overweight/obesity (n = 10,980) were set as dependent variables. Nutritional intakes were set as independent variables. A DNN model comprising one input layer with 7 nodes, three hidden layers with 30 nodes, 12 nodes, 8 nodes in each layer and one output layer with one node were implemented in Python programming language using Keras with tensorflow backend. In DNN, binary cross-entropy loss function for binary classification was used with Adam optimizer. For avoiding overfitting, dropout was applied to each hidden layer. Structural equation modelling (SEM) was also performed to simultaneously estimate multivariate causal association between nutritional intake and overweight/obesity, dyslipidemia, hypertension and T2DM. The DNN model showed the higher prediction accuracy with 0.58654 for dyslipidemia, 0.79958 for hypertension, 0.80896 for T2DM and 0.62496 for overweight/obesity compared with two other machine leaning models with five-folds cross-validation. Prediction accuracy for dyslipidemia, hypertension, T2DM and overweight/obesity were 0.58448, 0.79929, 0.80818 and 0.62486, respectively, when analyzed by a logistic regression, also were 0.52148, 0.66773, 0.71587 and 0.54026, respectively, when analyzed by a decision tree. This study observed a DNN model with three hidden layers with 30 nodes, 12 nodes, 8 nodes in each layer had better prediction accuracy than two conventional machine learning models of a logistic regression and decision tree.

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“…An increase in salt intake as a matter of fact, have been associated with the risk of developing cardiovascular diseases and stroke [11]. On the contrary, recent studies have expressed concern that reduced sodium intake can lead to an adverse effect on health like unhealthy changes in blood lipids and renal function [12]. Exercise has been found to potentially reduce SBP in hypertensive patients [13].…”

Section: Discussionmentioning

confidence: 99%

Effect of a Pharmacist Intervention on Self Management Practices Among Hypertensive-Diabetic Patients Receiving Care in a Nigerian Tertiary Hospital

Onyinye

Adibe

Victoria

2021

Int J Pharm Pharm Sci

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Objective: The objective of this study was to evaluate the effect of a pharmacist-led intervention on self-management practices among hypertensive-diabetic patients receiving care in a Nigeria tertiary hospital. Methods: The study adopted a prospective, longitudinal; single-blind, two-arm randomised controlled trial to implement a pharmacist-led educational intervention on hypertension management among patients in Federal Medical Centre Lokoja, Kogi State. All the patients who met the eligibility criteria and gave their written consent to participate in the study were recruited into the study randomized in the intervention group (IG) and Control (CG). Data was collected using Hypertension Self Care Activity Level Effects (H-SCALE) questionnaire. The retrieved questionnaires were first coded into Microsoft Excel (2014) for cleaning of errors, after which the data was exported into the Statistical Product and Services Solutions (SPSS for windows, Version 16.0. SPSS Inc. 2007, Chicago, USA) software. Descriptive statistics such as frequencies, percentages and mean scores were used to summarise the data. All responses were first presented as frequencies and percentages. Chi-square was used to determine the correlation between socio-demographic and patients’ clinical characteristics. Independent sample t-test and paired sample t-test were used to compare differences between and within groups. Results: At baseline, more patients in the control group were adherent to their medications 16 (11.5) and had low salt diets 47 (33.8) than patients in the intervention group. However, more patients in the intervention group were non-smokers 127 (88.8) and engaged more in physical activity 38 (26.6) than patients in the control group. However, more of the patients in the control group were adherent to weight management practices 38 (27.3) than patients in the intervention group 36 (25.2), at baseline. All the patients in both study groups reported to have taken alcohol in the past seven days. It can be seen that, patients in the intervention group at endpoint, differed positively from the control group at baseline in adherence to medication, physical activity, reducing alcohol consumption and smoking cessation. It can also be observed that the baseline intervention group differed positively from the endpoint in medication adherence (t=-26.045, p<0.001); physical activity (t=-15.081, p<0.001); weight management practices (t=-5.479, p<0.0010, and alcohol consumption 9t=-11.550, p<0.001). Conclusion: A pharmacist led educational intervention had a positive impact on the self-management practices of hypertensive-diabetes patients.

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Effects of low sodium diet versus high sodium diet on blood pressure, renin, aldosterone, catecholamines, cholesterol, and triglyceride

Cited by 53 publications

References 279 publications

Dietary Salt Reduction, Prevalence of Hypertension and Avoidable Burden of Stroke in Vietnam: Modelling the Health and Economic Impacts

Dietary Salt Reduction, Prevalence of Hypertension and Avoidable Burden of Stroke in Vietnam: Modelling the Health and Economic Impacts

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4–7th Korea National Health and Nutrition Examination Survey

Effect of a Pharmacist Intervention on Self Management Practices Among Hypertensive-Diabetic Patients Receiving Care in a Nigerian Tertiary Hospital

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