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January 30, 2020Designing A Prospective Cohort Study For Cardiovascular Intervention
Briefing
Approximately, 30% of death among the health complications are occurs due to the disorders in heart and blood vessel. This health problem is known to be cardiovascular diseases (CVD). In most of CVD, the death occurs due to heart attacks and strokes which accounts for one third of premature death. CVD exhibit various signs in our body to alarm us by showing raise in blood pressure, diabetes, cholesterol that leads to overweight and obesity. The main causative factors of CVDs are tobacco usage, alcohol abuse, unhealthy diet and inadequate physical activity. These strategies reduce the risk factor and incidence, which leads to morbidity and mortality due to CVD. There was a strong correlation between the diabetes and CVDs because the primary outcome of diabetes is CVD (Shah et al., 2015)
Interventions like Diet, Physical activity, Phycology can be considered.
| No | INTERVENTION | |
| 1 | Fats and carbohydrate intake (Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study; Lancet 2017; 390: 2050–62) | 1)objective / outcome- To assess the association between fruit, vegetable and legume consumption and cardiovascular disease and mortality in 135,335 individuals in 18 countries 2) Study design & type of prospective study- Prospective cohort study Exposure: Country-specific, validated food frequency questionnaires Covariates: Demographics, other lifestyle, health history, center Outcomes: Major CVD (CV death and nonfatal MI, stroke, and heart failure) (n=4784), using standardized definitions; total mortality (n=5796) 3)Population- Unbiased selection from general population in 667 urban/rural communities in 18 countries N=135,335; aged 35-70 years, without CVD at baseline 4) Duration- Median 7.4 years 5) Data collection- Data were collected at the community, household, and individual levels 6)Follow ups- Detailed follow-up to be done at 3, 6, and 9 years and repeated measures of selected risk factors, causes of death, other health outcomes, and community data to be collected 7) Tools- Dietary intake of the individuals have to be recorded using validated food frequency questionnaires. . Standardised questionnaires used to collect information about demographic factors, socioeconomic status (education, income, and employment), lifestyle (smoking, physical activity, and alcohol intake), health history, and medication use. Physical activity assessed using the International Physical Activity Questionnaire. Physical assessment included weight, height, waist and hip circumferences, and blood pressure 8) Retrieval drop rate- nil |
| 2 | Blood Pressure and Cholesterol Levels Yiyi Zhang, Eric Vittinghoff, Mark J. Pletcher, Norrina B. Allen, Adina Zeki Al Hazzouri, Kristine Yaffe, Pallavi P. Balte, Alvaro Alonso, Anne B. Newman, Diane G. Ives, Jamal S. Rana, Donald Lloyd-Jones, Ramachandran S. Vasan, Kirsten Bibbins-Domingo, Holly C. Gooding, Sarah D. de Ferranti, Elizabeth C. Oelsner, Andrew E. Moran J Am Coll Cardiol. 2019 Jul, 74 (3) 330-341. (Citation) | 1)objective / outcome- independent associations between young adult exposures to risk factors and later life CVD risk, accounting for later life exposures 2) Study design & type of prospective study- the ARIC (Atherosclerosis Risk In Communities) study ; 2) the CARDIA (Cardiovascular Risk Development in Young Adults) study ; 3) the CHS study (Cardiovascular Health Study) ; 4) the FHS-O cohort (Framingham Heart Study Offspring Cohort) ; 5) the Health ABC (Health, Aging and Body Composition) study ; and 6) the MESA study (Multi-Ethnic Study of Atherosclerosis) 3)Population- 36,030 individuals. 4) Duration- Adult life course 5) Data collection- pooled data from multiple cohorts (which together span the adult life course), and leveraged the risk factor patterns observed in the younger cohorts to impute unobserved young adult exposures in the older cohorts 6)Follow ups- From the cohorts 7) Tools- period-specific time-weighted averages (TWAs) of SBP, DBP, LDL, and HDL levels as summary measures of young (18 to 39 years of age) and later adult (≥40 years of age) exposures to CVD risk factors 8) Retrieval drop rate- Nil |
| Morning plasma cortisol Morning plasma cortisol as a cardiovascular risk factor: findings from prospective cohort and Mendelian randomization studies in European Journal of Endocrinology;2019 Vol 181,issue 4 (Citation) | 1)objective / outcome- The identification of new causal risk factors has the potential to improve cardiovascular disease (CVD) risk prediction and the development of new treatments to reduce CVD deaths. In the general population, we sought to determine whether cortisol is a causal risk factor for CVD and coronary heart disease (CHD). 2) Study design & type of prospective study- British Women’s Heart and Health Study (BWHHS) BWHHS is a prospective cohort study of 4286 women who were randomly selected from 23 British towns between 1999 and 2001 and who were aged 60–79 years at baseline,multivariable regression in two prospective nested case-control studies (total 798 participants, 313 incident CVD/CHD with complete data) 3)Population- 4286 women 4) Duration- 3 years 5) Data collection- Serum cortisol levels were determined by radio-immunoassay (MP Biomedicals, UK; intra-assay CV 5.1–7.0%, inter-assay CV 6.0–7.9%) on blood samples obtained at the baseline examination after a minimum 6-h fast between 08:00 h and 17:00 h 6)Follow ups- At periodic regular intervals 7) Tools- Serum cortisol 8) Retrieval drop rate- Nil | |
| Healthy Lifestyle (Citation) Healthy Lifestyle and Risk of Heart Failure Results From 2 Prospective Cohort Studies Susanna et al;12 Apr 2016;Circulation: Heart Failure. 2016;9:e002855 | 1)objective / outcome- healthy lifestyle factors with HF incidence in 2 population-based prospective cohort studies. 2) Study design & type of prospective study- 33 966 men (Cohort of Swedish Men) and 30 713 women (Swedish Mammography Cohort) who were 45 to 83 years of age and free of HF and ischemic heart disease at baseline 3)Population- study population in the current analyses were participants of the Cohort of Swedish Men (COSM) and the Swedish Mammography Cohort (SMC) 4) Duration- 13 years 5) Data collection- Incident HF cases were ascertained by linkage with the Swedish National Patient Register and the Swedish Cause of Death Register. Cox proportional hazards regression was used to analyze the data 6)Follow ups- nformation on smoking, weight, height, alcohol consumption, education, aspirin use, family history of myocardial infarction before 60 years of age, and history of diabetes mellitus, hypertension, and hypercholesterolemia was obtained by a self-administered questionnaire. Through linkage with the Swedish National Patient Register, we obtained information on diagnoses of atrial fibrillation and myocardial infarction. Participants were considered to have diabetes mellitus if they had a diagnosis of diabetes mellitus in the Swedish National Patient or Diabetes Registers or a self-report of diabetes mellitus in the questionnaire. BMI was calculated from self-reported weight and height (kg/m2). Physical activity was assessed with a prior validated questionnaire on time spent on various activities during the previous year. In this study, we added up time per week spent engaged in walking/bicycling and exercise. Diet was assessed with a validated food frequency questionnaire that inquired about average intake of 96 foods/food items during the previous year. 7) Tools- A healthy lifestyle was defined as being a nonsmoker and physically active (≥150 min/wk), and having body mass index between 18.5 and 25 kg/m2 and a healthy diet (defined as adherence to a modified Mediterranean diet) 8) Retrieval drop rate | |
| Best-practice interventions in blood pressure,blood glucose and total cholesterol (Citation) | 1)objective / outcome- best-practice) interventions could reduce socioeconomic inequalities of coronary heart disease mortality 2) Study design & type of prospective study- We undertook a prospective cohort study on 17 186 male civil servants aged 40–69 years between 1967 and 1970 in the UK (the Whitehall study). Socioeconomic position was based on employment grade. We compared the potential reduction in excess coronary heart disease mortality in men of low with those of high socioeconomic position with either best-practice interventions 3)Population- 19 019 non-industrial London-based male government employees aged 40–69 years between Sept 14, 1967, and Jan 15, 1970 (response rate 74%) 4) Duration- 15 years 5) Data collection- A trained observer took a single blood-pressure reading from the participant’s left arm with a London School of Hygiene sphygmomanometer. 22 We recorded systolic blood pressure at the first appearance of the Korotkoff sounds. We took a capillary blood sample from the earlobe after an overnight fast. Participants then drank a 50-g anhydrous dextrose preparation. We measured plasma cholesterol concentration with the standard Technicon method N24a, 21 and we took a second blood sample 2 h later. We measured post-load blood glucose concentration by the ferricyanide reduction method on an autoanalyser 6)Follow ups- 15-year mortality data were obtained from the National Health Service (NHS) Central Register with the NHS identifi cation number assigned to each citizen in the UK 7) Tools- (reduction of systolic blood pressure by 10 mm Hg, of total cholesterol by 2 mmol/L, and of blood glucose by 1 mmol/L in pre-diabetic people; halving the prevalence of non-insulin-dependent diabetes; and complete cessation of cigarette smoking) or primordial prevention. 8) Retrieval drop rate- 3.7% |
Conclusion
This intervention also involved in screening fasting blood specimens, glucose, total cholesterol and high-density lipoprotein (HDL) along with smoking status, medication used and other necessary demographic variables can be obtained by questionnaire. The primary outcome of this study can be estimated for certain time line and will be compared with Framingham risk equations. This equation helps in estimating the risk factors and condition which involved in development of CVD (Maruthur, Wang, & Appel, 2009) The adherence towards the intervention should also been estimated for optimizing the process.
