University of Lahore, Lahore-Pakistan. Participant were stratified into different three age groups (25-40, 41-55, 60 and above). Demographic data and medical history were taken on specially designed questionnaire and used for further analysis. Obesity was determined by calculating body mass index (BMI)

BMI = Weight (Kg)/Height (m) 2

BMI of 30 was considered as a cut off value. Above this value participant were labelled as obese. Independent t-test was used to determine the significance of variance and for Risk assessment odds ratio was calculated by using SPSS software (version 21). P-value less than 0.05 remained as significant.

Results

Results of the current study showed the assessment of risk factors that are found to be involved in onset of myocardial infarction. Frequencies and percentage of different variables shown in the table number 1. Age is considered as a major factor in the development of MI, in the present study age stratified into three subgroups. First subgroup ranging from 30 years to 45 years (35-45). In this age group according to collected data 20% MI participants were present, similarly 30% in second age group (46-60) and 50.0% in third age group that was > 60 years. So as the age increases the risk of MI also increases (Graph-1). In Group A 61.5% were the male and 38.5% female whereas in Group B the 81.7% male having the myocardial infarction as compare to female which constitute only 18.3%. analysis of other risk factors showed 80% of smokers developed MI in Group B as compare to non-smoker which were only 20%. But if we see in detail among 20% of non-smoker other risk factor such as obesity and diabetics either co-exist or can be found isolated. Similarly, the frequency of MI due to risk factors diabetes and obesity found to be 68.3% and 50.0% respectively in group B. (Table-1).

Table-1: Frequencies and percentages of all variables

Individual factors	Category	Frequency (%)
		¹Group A	²Group B	Total
Disease Status	Healthy			52 (46.4)
Disease Status	Myocardia Infarction			60 (53.6)
Age*	30-45 years	12 (23.1)	12 (20.0)	24 (25.9)
	46-60 years	15 (28.8)	18 (30.0)	33 (25.0)
	> 60 Years	25 (48.1)	30 (50.0)	55 (49.1)
Gender	Male	32 (61.5)	49 (81.7)	81 (72.3)
Gender	Female	20 (38.5)	11 (18.3)	31 (27.7)
Smoking	No	30 (57.7)	12 (20.0)	42 (37.5)
Smoking	Yes	22 (42.3)	48 (80.0)	70 (62.5)
Diabetes	No	34 (65.4)	19 (31.7)	53 (47.3)
Diabetes	Yes	18 (34.6)	41 (68.3)	59 (52.7)
Obesity	No	36 (69.2)	30 (50.0)	66 (58.9)
Obesity	Yes	16 (30.8)	30(50.0)	46(41.1)

*Age is stratified into three groups 1. Healthy population 2. Confirmed cases of Myocardial infarction

Discussion

Myocardial infarction is a leading cause of sudden death. The pathological disturbance involved in the onset of MI is the formation of atheroma in coronary arteries, thereby damaging the heart muscle (Chandrashekhar et al., 2020). Any factor that facilitate the formation of atheroma is considered as the risk factor of MI. Advanced age and smoking impact on all stages of atherosclerosis formation. Similarly, diabetes and obesity also contribute in disruption of endothelial covering of vessels and inflammation, reported in literature by many scientists and pathologists (Xi et al., 2017). Past studies revealed the frequency and mortality rate due to MI is related to gender difference. Male gender has more prone to have MI if they have risk factors as age, body fat, and smoking whereas systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse rate, and smoking were considered to be significant risk factors for women (Li et al., 2017). Population based, analytic epidemiologic study would be needed to confirm or deny hypotheses based on these observations. Smoking proved to be the significant risk factor for both genders and remained the major health hazard leading to MI. Cigarette smoking ( CS) impacts all phases of atherosclerosis from endothelial dysfunction to acute clinical events, the latter being largely thrombotic (d’Alessandro et al., 2020; Head et al., 2017). The exact toxic components of cigarette smoke and the mechanisms involved in CS-related cardiovascular dysfunction are largely unknown, because it is also observed that non- smoker without family history develop MI even in the early ages of the life span. but CS increases inflammation, thrombosis, and oxidation of low-density lipoprotein cholesterol (Chu et al., 2020). Recent experimental and clinical data support the hypothesis that cigarette smoke exposure increases oxidative stress as a potential mechanism for initiating cardiovascular dysfunction. Besides gender and smoking, other risk factors such as obesity and increased adipose tissue influence the pathogenesis of atherosclerosis. The adipose tissue, which is in fact a dynamic organ, is divided in white adipose tissue (WAT) and brown adipose tissue (BAT) and is associated with metabolic and inflammatory systems, with protective effects on energy homeostasis (Cercato and Fonseca, 2019). WAT secretes peptides and proteins that act by regulating biological and physiological conditions and play an important role in obesity, insulin resistance, inflammatory and immune functions, atherosclerosis and cardiovascular disease. Inflammatory infiltrate into adipocytes are a common finding in subjects with obesity or metabolic syndrome (Reddy et al., 2019). An inflammatory status can also be detected by circulating biomarkers. Diabetes is a metabolic disorder, defined as the dysregulation of processes involved in metabolism of glucose (López-Pastor et al., 2020). Mostly diabetes and obesity share a common mechanism in development of inflammatory process lead to the atherosclerosis and ultimately the MI (De Rosa et al., 2018). One of the drastic complication of diabetes is MI due to accelerated atherosclerotic plaque formation and thrombosis. Other complications include nephropathy retinopathy vascular damage and neuropathy (Yokoyama et al., 2018). Mostly diabetic patients present with atypical symptoms due to autonomic neuropathy and make it difficult to diagnose MI (Jung et al., 2017). Hence diabetes hampers in timely initiation of treatment that lead to permeant damage of cardiac muscles. Metabolic homeostasis is regulated by incretins, like GLP-1, which are gut hormones released in response to a meal and influence regulation of insulin and the cardiovascular system. GLP-1 stimulates insulin release by modulating the GI functions and control appetite (Meyer-Gerspach et al., 2016). It is degraded by enzyme dipeptidyl peptidase-4 (DPP-4), involved in adipose tissue inflammation, which in its way is related to insulin resistance. Obesity increases DPP-4 expression reducing the cardiovascular and metabolic effects mediated by GLP-1 levels (Zhuge et al., 2016). This impairment in the incretin axis promotes an imbalance between GLP-1 and GLP-2 which in turn contributes to insulin resistance and dyslipidemia. In addition, secretion of GLP-1 is reduced causing an incretin dysregulation and consequently blocking satiety in obese population (Deacon, 2018). Whereas DPP-4 either aggravates the incretin defect or stimulates T cell proliferation, increased concentrations have shown to be positively related with BMI, insulin and leptin levels, and negatively associated with adiponectin (Mikov et al., 2020). These aspects seem relevant in the management of obesity. In addition, an increased in the amount of reactive oxygen species (ROS) and reactive nitrogen species (RNS) can also be detected in parallel to the disturbances in the microbiota that are related to increased lipopolysaccharide (LPS) release in the bloodstream which in turn activates toll like receptor 4 (TLR4) (Ishimoto et al., 2018). Finally, increased perivascular adipose tissue promotes local inflammation and impairment of endothelium function. Results of our study reinforce the finds of past literature related to the risk factors of myocardial infarction. Pathological mechanism proposed clearly that smoking, age, diabetes and obesity are among the most common risk factors MI.

Graph-1: Correlation of MI with Age in Group B

To check the significance of various factors chi square test was applied and p- valve of less than 0.05 considered significant (Table-2)

Table-2: Association between heath status with gender, age, smoking, diabetes and BMI

	Health Status			p-Value*
	Healthy	Myocardial Infarction	Total	p-Value*
Gender
Male	32	49	81	0.018
Female	20	11	32	0.018
²Age
35-45 Years	11	13	24	¹0.640
45-60 Years	15	18	33
> 60 Years	25	30	55
Smoking
No	30	12	42	0.000
Yes	22	48	70	0.000
Diabetes
No	34	19	53	0.000
Yes	18	41	59	0.000
Obesity
No	36	30	66	0.039
Yes	16	30	46	0.039

*Chi-square test was used to check the significance of variance 1. The p valve is insignificant because we took age and sex matched control group. 2. Age is stratified in to three categories, as the age increases in Group B the percentage of MI also increases with linear correlation.

Conclusion

From the results of the current analysis of local population, it can be inferred that the smoking, diabetes and obesity are the major contributory factors in the development of myocardial infarction.

Recommendation

Prevention is always better then cure and prevention costs less than cure of a disease both financially and morbidity. So everyone should focus of the elimination of risk factors of MI and Nutritionist and Dietitian also should pay their role in the community awareness in this regard.

Limitation

Sample size is small to justify the risk assessment of different factors related to myocardial infarction

Conflict of interest

Author declared no conflict of interest.

Funding

This study is not funding by any third party.

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