A High-Protein and Low-Glycemic Formula Diet Improves Blood Pressure and Other Hemodynamic Parameters in High-Risk Individuals

Using a Bodily Weight-Fat Scale for Cuffless Blood Pressure Measurement Based on the Edge Computing System

Blood pressure (BP) measurement is a major physiological information for people with cardiovascular diseases, such as hypertension, heart failure, and atherosclerosis. Moreover, elders and patients with kidney disease and diabetes mellitus also are suggested to measure their BP every day. The cuffless BP measurement has been developed in the past 10 years, which is comfortable to users. Now, ballistocardiogram (BCG) and impedance plethysmogram (IPG) could be used to perform the cuffless BP measurement. Thus, the aim of this study is to realize edge computing for the BP measurement in real time, which includes measurements of BCG and IPG signals, digital signal process, feature extraction, and BP estimation by machine learning algorithm. This system measured BCG and IPG signals from a bodily weight-fat scale with the self-made circuits. The signals were filtered to reduce the noise and segmented by 2 s. Then, we proposed a flowchart to extract the parameter, pulse transit time (PTT), within each segment. The feature included two calibration-based parameters and one calibration-free parameter was used to estimate BP with XGBoost. In order to realize the system in STM32F756ZG NUCLEO development board, we limited the hyperparameters of XGBoost model, including maximum depth (max_depth) and tree number (n_estimators). Results show that the error of systolic blood pressure (SBP) and diastolic blood pressure (DBP) in server-based computing are 2.64 ± 9.71 mmHg and 1.52 ± 6.32 mmHg, and in edge computing are 2.2 ± 10.9 mmHg and 1.87 ± 6.79 mmHg. This proposed method significantly enhances the feasibility of bodily weight-fat scale in the BP measurement for effective utilization in mobile health applications.

Habitual isomaltulose intake reduces arterial stiffness associated with postprandial hyperglycemia in middle-aged and elderly people: a randomized controlled trial

Endothelin-1 (ET-1), produced by vascular endothelial cells, plays a pivotal role in the regulation of vascular tone. Isomaltulose, a naturally occurring sweetener and structural isomer of sucrose, reduces postprandial hyperglycemia, but its effect on arteriosclerosis due to hyperglycemia is unknown. The effects of 12 weeks of isomaltulose administration on ET-1 levels, a peptide that regulates arterial stiffness, blood pressure, and vascular tone, were tested before and after an oral glucose tolerance test. Fifty-four healthy middle-aged and older adults (30 men and 24 women) were divided into two groups: (1) a 25 g isomaltulose jelly drink intake group (Group I, 27 participants, mean age 55 ± 1 years) and (2) a sucrose jelly drink intake group (Group S, 27 participants, mean age 55 ± 1 years), each consuming isomaltulose or sucrose daily for 12 weeks, and a randomized, controlled study was conducted. Participants visited the laboratory before the intervention and 4, 8, and 12 weeks after the intervention to measure carotid-femoral (cf) and brachial-ankle (ba) pulse wave velocity (PWV), systolic blood pressure (BP), plasma glucose (PG), insulin, and ET-1 levels before and 60 and 120 min after a 75-g OGTT. baPWV, and ET-1 levels before intervention were significantly increased after 75-g OGTT compared to before 75-g OGTT in both groups (p < 0.05). The post-intervention baPWV, and ET-1 levels were significantly increased after 75-g OGTT in Group S compared to before 75-g OGTT (p < 0.05), whereas no significant changes were observed in Group I. These results suggest that consumption of isomaltulose, which has a lower GI than sucrose, is more effective in preventing the increases in systemic arterial stiffness associated with postprandial hyperglycemia in healthy middle-aged and older adults.

Clustering of the causes of death in Northeast Iran: a mixed growth modeling

BACKGROUND

Processing and analyzing data related to the causes of mortality can help to clarify and monitor the health status, determine priorities, needs, deficiencies, and developments in the health sector in research and implementation areas. In some cases, the statistical population consists of invisible sub-communities, each with a pattern of different trends over time. In such cases, Latent Growth Mixture Models (LGMM) can be used. This article clusters the causes of individual deaths between 2015 and 2019 in Northeast Iran based on LGMM.

METHOD

This ecological longitudinal study examined all five-year mortality in Northeast Iran from 2015 to 2019. Causes of mortality were extracted from the national death registration system based on the ICD-10 classification. Individuals' causes of death were categorized based on LGMM, and similar patterns were placed in one category.

RESULTS

Out of the total 146,100 deaths, ischemic heart disease (21,328), malignant neoplasms (17,613), cerebrovascular diseases (11,924), and hypertension (10,671) were the four leading causes of death. According to statistical indicators, the model with three classes was the best-fit model, which also had an appropriate interpretation. In the first class, which was also the largest class, the pattern of changes in mortality due to diseases was constant (n = 98, 87.50%). Second-class diseases had a slightly upward trend (n = 10, 8.92%), and third-class diseases had a completely upward trend (n = 4, 3.57%).

CONCLUSIONS

Identifying the rising trends of diseases leading to death using LGMM can be a suitable tool for the prevention and management of diseases by managers and health policy. Some chronic diseases are increasing up to 2019, which can serve as a warning for health policymakers in society.

High-Protein, Low-Glycaemic Meal Replacement Improves Physical Health-Related Quality of Life in High-Risk Persons for Metabolic Syndrome-A Subanalysis of the Randomised-Controlled ACOORH Trial

While obesity impairs health-related quality of life (HRQOL), lifestyle interventions targeting weight reduction have been effective in improving HRQOL. Therefore, we hypothesised that a meal replacement-based lifestyle intervention, which has been shown to successfully reduce weight, would also improve HRQOL more effectively than a lifestyle intervention alone. In the international, multicenter, randomised-controlled ACOORH-trial (Almased-Concept-against- Overweight-and-Obesity-and-Related-Health-Risk), overweight or obese participants with elevated risk for metabolic syndrome (n = 463) were randomised into two groups. Both groups received telemonitoring devices and nutritional advice. The intervention group additionally used a protein-rich, low-glycaemic meal replacement for 6 months. HRQOL was estimated at baseline, after 3 and 12 months, using the SF-36 questionnaire, and all datasets providing HRQOL data (n = 263) were included in this predefined subanalysis. Stronger improvements in the physical component summary (PCS) were observed in the intervention compared to the control group, peaking after 3 months (estimated treatment difference 2.7 [1.2; 4.2]; p < 0.0001), but also in the long-term. Multiple regression analysis demonstrated that insulin levels and the achieved weight loss were associated with the mental component summary (MCS) after 12 months (p < 0.05). Thus, meal replacement-based lifestyle intervention is not only effective in weight reduction but, concomitantly, in enhancing HRQOL.

Cuffless and Touchless Measurement of Blood Pressure from Ballistocardiogram Based on a Body Weight Scale

Currently, in terms of reducing the infection risk of the COVID-19 virus spreading all over the world, the development of touchless blood pressure (BP) measurement has potential benefits. The pulse transit time (PTT) has a high relation with BP, which can be measured by electrocardiogram (ECG) and photoplethysmogram (PPG). The ballistocardiogram (BCG) reflects the mechanical vibration (or displacement) caused by the heart contraction/relaxation (or heart beating), which can be measured from multiple degrees of the body. The goal of this study is to develop a cuffless and touchless BP-measurement method based on a commercial weight scale combined with a PPG sensor when measuring body weight. The proposed method was that the PTTBCG-PPGT was extracted from the BCG signal measured by a weight scale, and the PPG signal was measured from the PPG probe placed at the toe. Four PTT models were used to estimate BP. The reference method was the PTTECG-PPGF extracted from the ECG signal and PPG signal measured from the PPG probe placed at the finger. The standard BP was measured by an electronic blood pressure monitor. Twenty subjects were recruited in this study. By the proposed method, the root-mean-square error (ERMS) of estimated systolic blood pressure (SBP) and diastolic blood pressure (DBP) are 6.7 ± 1.60 mmHg and 4.8 ± 1.47 mmHg, respectively. The correlation coefficients, r2, of the proposed model for the SBP and DBP are 0.606 ± 0.142 and 0.284 ± 0.166, respectively. The results show that the proposed method can serve for cuffless and touchless BP measurement.

Early and Strong Leptin Reduction Is Predictive for Long-Term Weight Loss during High-Protein, Low-Glycaemic Meal Replacement-A Subanalysis of the Randomised-Controlled ACOORH Trial

Lifestyle interventions including meal replacement are suitable for prevention and treatment of obesity and type-2-diabetes. Since leptin is involved in weight regulation, we hypothesised that a meal replacement-based lifestyle intervention would reduce leptin levels more effectively than lifestyle intervention alone. In the international, multicentre, randomised-controlled ACOORH-trial (Almased-Concept-against-Overweight-and-Obesity-and-Related- Health-Risk), overweight or obese participants with metabolic syndrome criteria (n = 463) were randomised into two groups and received telemonitoring devices and nutritional advice. The intervention group additionally used a protein-rich, low-glycaemic meal replacement. Data were collected at baseline, after 1, 3, 6, and 12 months. All datasets providing leptin data (n = 427) were included in this predefined subanalysis. Serum leptin levels significantly correlated with sex, body mass index, weight, and fat mass at baseline (p < 0.0001). Stronger leptin reduction has been observed in the intervention compared to the control group with the lowest levels after 1 month of intervention (estimated treatment difference −3.4 µg/L [1.4; 5.4] for females; −2.2 µg/L [1.2; 3.3] for males; p < 0.001 each) and was predictive for stronger reduction of body weight and fat mass (p < 0.001 each) over 12 months. Strongest weight loss was observed after 6 months (−5.9 ± 5.1 kg in females of the intervention group vs. −2.9 ± 4.9 kg in the control group (p < 0.0001); −6.8 ± 5.3 kg vs. −4.1 ± 4.4 kg (p = 0.003) in males) and in those participants with combined leptin and insulin decrease. A meal replacement-based lifestyle intervention effectively reduces leptin which is predictive for long-term weight loss.