METHODS AND RESULTS: Blood pressures, fasting lipid profile and fasting glucose were measured, and DASH score was computed based on a 22-item food frequency questionnaire. Older individuals, women, those not consuming alcohol and those undertaking regular physical activity were more likely to have higher DASH scores. In the Malaysian cohort, while total DASH score was not significantly associated with cardio-metabolic risk factors after adjusting for confounders, significant associations were observed for intake of green vegetable [0.011, standard error (SE): 0.004], and red and processed meat (-0.009, SE: 0.004) with total cholesterol. In the Philippines cohort, a 5-unit increase in total DASH score was significantly and inversely associated with systolic blood pressure (-1.41, SE: 0.40), diastolic blood pressure (-1.09, SE: 0.28), total cholesterol (-0.015, SE: 0.005), low-density lipoprotein cholesterol (-0.025, SE: 0.008), and triglyceride (-0.034, SE: 0.012) after adjusting for socio-demographic and lifestyle groups. Intake of milk and dairy products, red and processed meat, and sugared drinks were found to significantly associated with most risk factors.
CONCLUSIONS: Differential associations of DASH diet and dietary components with cardio-metabolic risk factors by country suggest the need for country-specific tailoring of dietary interventions to improve cardio-metabolic risk profiles.
METHODS: A total of forty-eight males and females (16 Chinese, 16 Indians, and 16 Malay) took part in this randomised, crossover study. Glycaemic response to the reference food (glucose beverage) was measured on three occasions, and GR to three liquids were measured on one occasion each. Liquids with different macronutrient ratio's and carbohydrate types were chosen to be able to evaluate the response to products with different GIs. Blood glucose concentrations were measured in duplicate at baseline (-5 and 0 min) and once at 15, 30, 45, 60, 90, and 120 min after the commencement of beverage consumption.
RESULTS: There were statistically significant differences in GI and GR between the three liquids (P
Objective: This review aims to summarize the clinical evidence regarding the use of chia seed for a wide variety of health conditions.
Data Sources: A number of databases, including PubMed and Embase, were searched systematically.
Study Selection: Randomized controlled trials that assessed the clinical effects of chia seed consumption in human participants were included. The quality of trials was assessed using the Cochrane Risk of Bias Tool.
Data Extraction: Data on study design, blinding status, characteristics of participants, chia seed intervention, comparator, clinical assessment, duration of intake, interval of assessment, and study funding status were extracted. Meta-analysis was performed.
Results: Twelve trials were included. Participants included healthy persons, athletes, diabetic patients, and individuals with metabolic syndrome. Pooling of results showed no significant differences except for the following findings of subgroup analysis at higher doses of chia seed: (1) lower postprandial blood glucose level (mean difference [MD] of -33.95 incremental area under the curve [iAUC] [mmol/L × 2 h] [95%CI, -61.85, -6.05] and -51.60 iAUC [mmol/L × 2 h] [95%CI, -79.64, -23.56] at medium doses and high doses, respectively); (2) lower high-density lipoprotein in serum (MD of -0.10 mmol/L [95%CI, -0.20, -0.01]); and (3) lower diastolic blood pressure (MD of -7.14 mmHg [95%CI, -11.08, -3.19]). The quality of all evidence assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was low or very low. All trials employed only surrogate markers as outcomes.
Conclusions: Future trials with improved methodological quality, well-described clinical events, and validated surrogate markers as outcomes are needed to support the potential health benefits of chia seed consumption.
Systematic Review Registration: PROSPERO registration no. CRD42015029990.
METHODS: Data from the first wave Malaysian Elders Longitudinal Research (MELoR) study comprising urban dwellers aged 55 years and above were utilized. Twelve-month fall histories were established during home-based, computer-assisted interviews which physical performance, anthropometric and laboratory measures were obtained during a hospital-based health check. Gait speed, exhaustion, weakness, and weight loss were employed as frailty markers.
RESULTS: Data were available for 1415 participants, mean age of 68.56 ± 7.26 years, 57.2% women. Falls and metabolic syndrome were present in 22.8% and 44.2%, respectively. After adjusting for age, sex, and multiple comorbidities, metabolic syndrome was significantly associated with falls in the sample population [odds ratio (OR): 1.33, 95% confidence interval (CI): 1.03; 1.72]. This relationship was attenuated by the presence of slow gait speed, but not exhaustion, weakness, or weight loss.
CONCLUSION: Metabolic syndrome was independently associated with falls among older adults, and this relationship was accounted for by the presence of slow gait speed. Future studies should determine the value of screening for frailty and falls with gait speed in older adults with metabolic syndrome as a potential fall prevention measure.
METHODS: We reviewed 22 previous studies that (1) empirically manipulated social support in a stressful situation, (2) measured CVR, and (3) tested a moderator of social support effects on CVR.
RESULTS: Although a majority of studies reported a CVR-mitigating effect of social support resulting in an overall significant combined p-value, we found that there were different effects of social support on CVR when we considered high- and low-engagement contexts. That is, compared to control conditions, social support lowered CVR in more engaging situations but had no significant effect on CVR in less engaging situations.
CONCLUSION: Our results suggest that a dual-effect model of social support effects on CVR may better capture the nature of social support, CVR, and health associations than the buffering hypothesis and emphasize a need to better understand the health implications of physiological reactivity in various contexts. Statement of contribution What is already known on this subject? According to the stress-buffering hypothesis (Cohen & McKay, ), one pathway social support benefits health is through mitigating the physiological arousal caused by stress. However, previous studies that examined the effects of social support on blood pressure and heart rate changes were not consistently supporting the hypothesis. Some studies reported that social support causes elevations in cardiovascular reactivity (CVR) to stress (Anthony & O'Brien, ; Hilmert, Christenfeld, & Kulik, ; Hilmert, Kulik, & Christenfeld, ) and others showed no effect of social support on CVR (Christian & Stoney, ; Craig & Deichert, ; Gallo, Smith, & Kircher, ). What does this study add? When participants were in more engaging conditions, social support decreased CVR relative to no support. When participants were in less engaging conditions, social support did not have a significant effect on CVR. Provide an alternative way to explain the ways social support affects cardiac health.