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This study will be conducted to investigate the effect of DASH diet and Progressive muscle relaxation on cardiovascular risks in postmenopausal women.
Cardiovascular disease is the leading cause of morbidity and mortality in men and women, but the incidence of cardiovascular disease related deaths is higher in women than men. Hypertension is one of the leading risk factors for cardiovascular disease. Aging in both men and women is characterized by increases in blood pressure (BP), but the age-related increases are more rapid in women particularly postmenopausal women than in men. A variety of non-pharmacologic treatments to manage stress have been found effective in reducing blood pressure and the development of hypertension. The DASH eating pattern promotes blood pressure reduction by encouraging the consumption of foods that are low in saturated fat, total fat, cholesterol, and sodium and high in potassium, calcium, magnesium, fiber, and protein. In terms of actual food choices, the DASH eating pattern encourages whole grains, fat free or low-fat dairy products, fruits, vegetables, poultry, fish, and nuts. Foods that are limited include fatty meats, full-fat dairy products, tropical oils (e.g., coconut, palm, and palm kernel oils), and sweets and sugar sweetened beverages. The mechanism by which relaxation techniques lower blood pressure is unclear. One theory suggests that they may help lower the stress and physiologic arousal produced by the autonomic nervous system, thereby reducing blood pressure. So this study is a trial to determine the effect of DASH diet and progressive muscle relaxation in reducing cardiovascular risks in postmenopausal women.
Age
50 - 60 years
Sex
FEMALE
Healthy Volunteers
Yes
Farahnaz Ahmed Mohamed
Suez, Egypt
Start Date
June 10, 2024
Primary Completion Date
November 1, 2024
Completion Date
December 1, 2024
Last Updated
September 19, 2024
90
ESTIMATED participants
DASH diet
DIETARY_SUPPLEMENT
Progressive muscle relaxation
OTHER
Anti hypertensive drugs
DRUG
Lead Sponsor
Cairo University
Data Source & Attribution
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