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Existing literature (Emery et al., 2004; Raine et al., 2002) has suggested that some demographic variables such as gender, age, education, occupation, income and marital status may be associated with a higher risk for CHD. The interrelationship of these variables might result in further risk of the disease itself and negative outcomes. It is a common observation that females, in traditional societies like Pakistan, with low educational qualification and unemployed status are associated with poor quality of life which consequently increases their risk for certain health problems including cardiac illnesses. Muhammad et al. (2014) demonstrated that lower levels of education and high levels of depression

associated with poor physical health, while increased age of patient, high levels of anxiety, and depression predicted poor mental health. A study conducted in Pakistan (Aziz et al., 2008) showed that overall prevalence rates of cardiac disease was 6.2% with women older than 30 years of age having a significantly increased risk of heart attack compared to men (8.2% versus 4.5%). The prevalence of stroke in women was 3.5% which again was higher than men (1.8%). These findings clearly suggest that prevalence of heart disease is higher in women than men in Pakistan. Another study (Bokhari et al., 2002) conducted in a tertiary care hospital setting, examined the prevalence of depression in patients with heart disease and reported that female patients were at increased risk of negative psychological outcomes (depression) in these patients. However a population based study by Jafar et al.( 2005) found equal prevalence of depression in both men and women. In contrast to this a study by Jafary et al. (2007) reported that the majority (68%) of patients who presented with chest pain complaints to emergency departments were males. These mixed findings on the subject matter suggest further exploration is required as very few studies have been conducted in Pakistan. Kristofferzon et al. (2005) conducted a systematic review of studies published in the early and mid 90s (Hamilton & Seidman, 1993; Brett & Madans, 1995) and observed mixed results in terms of gender differences in prevalence, symptom presentation, access and response to treatment.Gender differences other than prevalence and symptom presentation have also been examined in context of social support (Kristofferzon et al., 2005), coping (Bogg et al., 2000) and determinants of quality of life (Brink et al., 2002). Kristofferzon et al. (2005) found that women with MI reported more

perceived social support than men and coping strategies used by women were different than men. They also reported insignificant gender differences in terms of quality of life. However, a study by Martin (2012) demonstrated that patients with cardiovascular disease (CVD) generally reported a poorer health-related quality of life (HRQOL) compared to healthy age and gender-matched individuals. In addition, Martin (2012) found that female gender appeared as an independent predictor of lower health related quality of life scores with females reporting more preoperative co-morbidities compared to males at both baseline and six months which is likely to have an impact on recovery time and outcomes. This study suggests that efforts should be made to identify and treat female patients with CVD earlier to improve post-surgical outcomes. Petterson et al. (2008) conducted a study in Norway to determine the relationship between sex and health-related quality of life following myocardial infarction as the exiting literature at that time was contradictory. They found that women scored lower than matched control norms on physical functioning, general health, and role functioning as assessed using different physical and mental well-being measures. In contrast, men scored higher on bodily pain. The authors concluded that men and women had different determinants of HRQOL.

A prospective cohort study was undertaken by Jafray et al.(2007) in 17 coronary care units in all the provinces of Pakistan a cohort of 1400 patents who presented with chest pain and were diagnosed with coronary artery disease (CAD) was assessed in terms of risk factors, family history and other co-morbid conditions. The results revealed that 68% of the patients were male and mean

age of all the patients was 52.2 years. A study ( Njelekela et al., 2009) on gender related differences in CVD risk factors in urban Tanzania revealed that risk factors such as obesity, low HDL-cholesterol, and high level of glucose was more prevalent in women when compared with men. However the odds (95 %Cl: 0.3-1.0) of having hypertension were 50% higher in men compared to women (Njelekela et al., 2009). Haitjema et al. (2014) examined HRQOL and the association with outcome during follow-up in a population undergoing surgery for peripheral artery disease or cerebrovascular large artery disease. They reported that HRQOL is poor and does not associate with CVD burden within patients suffering from severe atherosclerotic disease. Limited research is available on the difference in coping styles of males and females as well as the physical after effects on both genders of MI, post trauma. Those studies that are available, however, point to different coping mechanisms for both genders in terms of life after MI (Caulin-Glazer et al., 2001; Chan et al., 2005). Findings also indicate that females are at a greater risk of non-referral following rehabilitation after MI compared to males (Caulin-Glazer et al., 2001; King et al., 2001). These studies also indicate that due to various psychological reasons such as self esteem and ability to cope, female patients are at a higher risk of not completing their rehabilitation treatment compared to men (Yohannes et al., 2007). This review indicates that gaps exist in terms of generating adequate evidence about patterns of gender differences in terms of prevalence, presentation of symptoms, access and response to treatments as well as association between specific risk factor and determinants of quality of life of MI patients of both genders. The psychosocial conditions in South-Asian countries have an impact

on women lives from various dimensions thus further highlights the need to investigate the relationship between these variables and quality of life in MI patients. Other socio-environmental factors that have a significant effect on post MI HRQOL include the age, marital status of the patient (Farley et al., 2003; Husak et al., 2004; Shanks et al., 2010; Yohannes et al., 2007), education (Chan et al., 2005; Shanks et al., 2010), work status as well as the ability to rejoin work post trauma (Chan et al., 2005;Hagan et al., 2007) and income levels (Shanks et al., 2010).

Studies have shown (Beck & Offenbetcher, 2001; Conn et al., 1991) that age is an important factor which might affect health related quality of life in MI patients. A research study by Saleheen & Frossard (2004) on CAD risk factors and acute myocardial infarction in Pakistan revealed significant differences between young (<45 years of age) and old (>45 years of age) AMI patients. In the total sample of 976 patients, young AMI patients were more likely to have hypertension, a family history of coronary artery disease, high cholesterol, high LDL and high triglycerides (Saleheen & Frossard,2004) compared to older patients. Pettersen et al. (2008), while discussing findings of their research identified a relationship between young age and improved treatment response which is supported by previous research (Bengtsson et al., 2004; Wolinsky et al., 1998). Studies in South Asian countries have found population susceptibility to acute myocardial infarction (AMI). A study designed to evaluate the association of risk factors for AMI in native South Asians, especially at younger ages, compared with individuals from other countries. The result supported that the mean age for first

AMI was lower in South Asian countries (M=53.0; S,D.=11.4 years) than in other countries (M=58.8; S.D.=12.2 years) indicating that in South-Asian communities, people of young age are at increased risk for heart diseases (Joshi et al., 2007). Health-related quality of life (HRQOL) has also been identified as a predictor of survival in patients with CAD and heart failure (Westin et al., 2005). A significant relationship was also found between HRQOL and myocardial Infarction (Bengtsson et al., 2004). Results revealed that HRQOL of MI patients with in the age group <59 years was more impaired compared to older patients (≥59 years) even after 2 years following a myocardial infarction (Bengtsson et al., 2004). Abdelmoneim, (2014) conducted a prospective cross-sectional observational study in Egypt aimed at reporting the demographics of Acute Coronary Syndrome (ACS) and made some contradictory observations. This study demonstrated high prevalence of ACS in younger age group and that male gender, smoking and family history of similar disease were significant risk factors.

In addition to gender and age, socioeconomic status (SES) is a significant determinant of CHD worldwide (Fiscella & Franks, 2004). Socioeconomic status (SES) identifies a person’s hierarchal place in a society by referring to his/her education, occupation and income which ultimately determine an individual’s living standards and progress. Rao et al. (2003) specifically examined the income-based disparities in healthcare processes and outcomes in patients with acute coronary syndromes. Patients in this study were grouped into low, middle, and high-income categories based on the USA. Census bureau definition of

poverty. The results revealed that low-income patients had more chronic medical conditions. Further among low-income patients, the use of some evidence-based medications and cardiac procedures was lower and the unadjusted rates of 30-day death and six-month death or MI was higher. After multivariable adjustment, there was no consistent pattern for disparity in care processes, but the trend for higher short and intermediate-term death or MI persisted for low-income patients. Graham (2006) looked into the role of socio- economic position in health inequalities and suggested that socioeconomic position affects health indirectly by influencing environmental risks (e.g. poor living conditions, increased vulnerability for occupational hazards, traffic danger etc) and psychosocial factors (e.g. poor social support from family, stressful life events). Fiscella & Tancredi (2008) identified some clinical, psychosocial, and behavioral factors that play role in mediating the relationship between SES and CHD. Denvir et al. (2006) reported that low SES was associated with more re- admissions and poor quality of life in patients with CHD. Shishehbor et al. (2008) conducted a study on patients at risk for developing CHD and found an independent relationship between lower SES and poor involvement, as well capacity, to perform physical exercise which consequently increased the risk for mortality. Low education, occupation status and income very often limit access to a healthy diet, knowledge and affordability of treatment procedures and place people at greater risk of engaging in unhealthy behaviors (smoking, alcohol abuse). This may also lead to poor compliance with treatment procedures and thus influence prognosis. (Fiscella & Tancredi, 2008) This situation is more pertinent with reference to South-Asian community where people are in general

more at risk for poor health conditions attributable to poor demographic and economic conditions as well as influence of cultural factors that may determine health related attitudes and behaviors. Similarly Mielck et al. (2014) reported that people in lower SES groups are exposed to an increased burden of ill health primarily due to their increased vulnerability for health complications and deteriorated quality of life. This review, based on several years of research, has shown socio-economic status to be strong determinant of poor health conditions and quality of life in MI patients.

Mortality rates have been linked with marital status and other social networks suggesting beneficial effects of social support on long and healthy life (Schwarzer & Reickmann, 2002). Family systems and marital status are also assumed to be a strong determinant of HRQOL in South-Asian societies as both are a major source of social support systems in collective societies. A cross- sectional study was carried out at the out-patient clinics of the Aga Khan University Hospital, Pakistan. Researchers explored participants’ levels of satisfaction with current family system, opinions about changing trends in family systems, and its implications on health. Four hundred people aged 65 and above were interviewed. 56.5% were living in the joint family system (JFS), and 43.5% were living in a nuclear family system (NFS). 85% of participants said that a family system had a significant impact on health care. 91.5% respondents were satisfied with their family system and respondents pointed towards a shift in trend i.e. family systems in Pakistan were changing from JFS to NFS (Itrat, 2007). Since social support is an important determinant of morbidity and

mortality in patients with CHD (Uchino, 2009), the changing family systems are likely to have implications in our society. Previous research from Western societies (Hemmingway & Marmot, 1999; Glynn et al 1999) have shown that individuals who are single and lack social support are more likely to die within five years post CHD than those who are married and have social support. Luttik et al. (2006) in a follow-up study of 179 patients with heart failure on their hospital readmission explored the relationship between marital status and quality of life and life endurance within 9-months of heart attack. The results of study indicated that individuals living alone were more at risk of having poor quality of life.

Other than socio-demographic variables discussed above, patient life style and eating habits have an important role to play in determining the risk of cardiac diseases. More comforting lifestyles, less time available for physical activity and intake of foods which are high in fat are some of the well-known risk factors for cardiac disease, particularly in middle and elder age groups (Blair & Jackson, 2001). An empirical study conducted by Arthur et al. (2002) showed that although exercise was instrumental in promoting recovery of patients following a Coronary Artery bypass grafting (CABG) within first 6 months after treatment, home based interventions fared far better than hospital based interventions. Smith et al. (2004) demonstrated similar results at a follow up of 1 year after treatment, maintaining that home based interventions scored better as opposed to centre-based interventions. This study was also significant since it used the Physical Activity Scale for the Elderly (PASE) in an attempt to evaluate the

average routine physical activity between home based and centre-based intervention groups. The results conclusively showed that overall, patients recovering from cardiac events scored much better on habitual physical activity than their normally healthy counterparts within the same age group.

As a result health-care professionals, as well as social welfare agencies, are exploring ways to minimize the risk and enhance factors which have better healthcare outcomes for cardiac patients.