Índice de Sustentabilidad de los GAD’s

case in this study. The average number of bottles taken per day was similar between current drinkers and ex-drinkers. This reveals a similarity in alcohol intake of the current drinkers and ex-drinkers. This is contrary to the findings about smoking. Only one-third of the respondents reported taking part in one exercise or the other. Most of the exercises reported were brisk walking, climbing stairs, jogging, soccer and dancing. This is expected because most of the day to day activities involve walking around and many people have to climb stairs both at work place and at home. This also explains why the majority of the people said they exercise daily. It was found that up to one-tenth of the respondents had one or more chronic medical conditions. Hypertension was the commonest morbidity found among peoples studied. It confirms the findings of many studies that hypertension remains the most common cardiovascular risk factor among adults.⁸⁰

This study found that the prevalence of overweight and obesity, using BMI were 30.3%

and 14.2% respectively. The prevalence of obesity, using waist circumference among male and female respondents were 7.3% and 30.1% respectively, indicating higher risk of cardiovascular diseases among the females respondents. However, significant associations were found between sex and blood pressure (systolic and diastolic) in which males respondents were more likely to have raised blood pressure. It may not be the same for other cardiovascular diseases. In a recent study, the prevalence of obesity in West Africa was estimated at 10.0%.⁴ The above stated figures are higher than the finding from a study on obesity and hypertension prevalence in populations of African origin, in which

it was found that the prevalence of obesity was 1.7%, and was higher among women than men (2.2% versus. 1.2%).⁴²

The prevalence of raised blood pressure among the respondents was 25.2%. This proportion included those that were known hypertensive and those with raised systolic and/or diastolic blood pressure at the time of the study. This was consistent with the finding of a study that was based on a pooled analysis of available national and regional data in which it was reported that overall prevalence of hypertension in 2000 was estimated to be 26.4% of the world’s population.⁸¹ This study also found that both systolic and diastolic blood pressures increased with increased BMI and that obese individuals were more likely to be hypertensive than those that were not obese. This is consistent with other studies that identified obesity as a risk factor for development of cardiovascular diseases.^23,24,25 It was also found that chance of having obesity increased with increased age and that women were more likely to be obese than men. This was consistent with the find in a similar study carried out in China, in which the prevalence of obesity was higher among women than men.³

The dimensions of HRQOL measured were overall quality of life, satisfaction with heath, physical domain, psychological domain, social relationship domain, environment domain and global domain. The global domain is the average of the combination of the physical, psychological, social and environment domains.

This study found the overall quality of life to be fair with only 8.0 % and 22.7% having good and poor value respectively. Also, satisfaction with health was fair among the majority (69.0%), with 57 (14.2%) and 67 (16.8%) having good and poor values respectively. Among the five domains measured, the physical domain appeared to have the highest value of the quality of life, with a mean score of 72.7%, followed by psychological domain with a mean score of 71.9%. This was contrary to the findings of the study conducted on coping and social support as determinants of quality of life in HIV/AIDS in which the scores on the behavioral and subjective measures of QOL were somewhat below average.¹⁴

The quality of life was fair in all the domains in the majority, with means scores ranging from 60.4 in environment domain to 72.7 physical domain. The proportion with good quality of life was highest in physical domain (16.0%) followed by psychological domain (14.2%), while the proportion with poor quality of life was highest in environment domain (19.8%) followed by psychological domain (17.5%). The majority had fair quality of life in global domain (74.8%) and visual analogue score (54.5%). The proportions with good and poor quality of life in global domain were 10.7% and 14.5%

respectively, while in visual analogue score, the proportions were 21.2% and 24.0%

respectively. The mean scores in the various dimensions of quality of life in this study were slightly higher than what was found in a study carried out to examine characteristics related to social support and antiretroviral medication adherence in KwaZulu-Natal, South Africa in which it was found that social support scores were moderate (Mean = 64.4 ± 14.7) among the study participants.⁸²

In order to determine the relationship of the HRQOL with other variables, simple linear regression analysis of the global domain score was performed on each of the age, income, anthropometric indexes and blood pressure. There were weak negative correlations between global domain of quality of life and age (r = -0.35), family size (r = -0.30), BMI (r = -0.10), waist circumference (r = -0.20), systolic blood pressure (r = -0.27) and diastolic blood pressure (r = -0.22). There were also weak positive correlations between global domain of health related quality of life and personal monthly income (r = 0.28), family monthly income (r= 0.28) and household monthly expenditure of feeding (r = 0.14).

Statistical tests of associations were performed to demonstrate the influence of anthropometric indexes on the blood pressure. Both systolic and diastolic blood pressure were found to significantly increased with waist circumference in female and BMI.

Statistical tests of associations were also performed in order to identify the factors influencing the various dimensions (domains) of HRQOL using chi-square. Factors that were found to significantly influence one or more dimensions of the HRQOL were demographic: age, marriage type (monogamous versus polygamous) and ethnicity; socio-economic: level of education, respondent’s average monthly income, average income of family, monthly expenditure on feeding per month by family and means of transportation to work; Other factors: BMI and blood pressure. Age was found to be significantly associated with overall quality of life. Younger respondents generally scored higher in the quality of life (p = 0.01. A higher proportion of them tend to have good perception of their quality of life while a lower proportion tends to have poor perception compared with the older respondents. This is understandable because older individuals are more likely to

have chronic medical conditions that negatively influence their quality of life. It was consistent with the finding of a similar study in which it was found that the prevalence of indicators for poor mental health decreased with increasing age.⁵⁹

The type of marriage (monogamous versus polygamous) appeared to have influence on the perception of overall quality of life (p = 0.0001). The respondents in monogamous marriage scored higher than their counterparts in polygamous marriage in their perception of overall quality of life suggesting that monogamy has some beneficial effects on the quality of life. The respondents from Igbo ethnic group appeared to score higher in their overall perception of quality of life compared with other ethnic groups (p

= 0.01). The better perception of the quality of life found among the Igbos might be attributed to their cultural background and value system. They tend to adapt to any situation they found themselves. Further studies are suggested to identify the socio-cultural factors that influence the coping capability with life situations in our environment. Sex did not appear to play any significant role in determining the quality of life in this study. But in a similar study in Rhode Island, United States, sex was found to be weakly associated with physical and mental health.¹⁸ Another study revealed that women reported a higher prevalence than men for all of the HRQOL indicators.⁵⁹

Level of education was found to be significantly associated with overall perception (p = 0.002) and global domain (p = 0.00) of the quality of life. This is understandable because higher level of education is usually associated with increased awareness and knowledge.

Many studies have demonstrated the role of education in the health of individuals.

Educated individuals tend to have better health indices. In a similar study conducted to assess HIV symptoms and demographic, social and disease variables of people living with HIV in South Africa, the results suggested that lower educational levels were significant associated with poor HRQOL.⁸³ Occupation also appeared to be significantly associated with overall perception of the quality of life in this study (p = 0.01). The unskilled workers scored lower in the quality of life compare with skilled workers and the professionals. This may be because unskilled workers were more likely to earn less and subsequently have less money to spend on feeding and good housing which would in turn negatively influence the HRQOL. Other similar studies have shown that QOL is associated with education, income and occupation.²⁰

The employment status did not appear to significantly influence the quality of life, but type of employment appeared to influence their overall global domain of HRQL (p = 0.002). A greater proportion (18.2%) of those who were self employed had poor quality of life compared with 4.8% and 7.4% of those who were employed in the public and private (non-self) sectors respectively. It may be that those that were self employed were majorly petty traders and unskilled workers with low income, which might in turn negatively influence their quality of life. A similar study revealed that respondents who were unemployed had higher rates than others for most of the poor Health Related Quality of Life indicators.⁵⁹

The average monthly income of the respondents appeared to influence their overall perception (p = 0.02) and global domain (p = 0.00). The proportion of respondents with good quality of life increased with increased monthly income. Similar trends were observed with the family monthly income and family monthly expenditure on feeding.

This is understandable because higher income tends to increase the standard of living of people in terms of the quality of housing and feeding. This has been demonstrated in a previous study that the prevalence of all poor Health Related Quality of Life indicators increased with decreasing levels of annual household income.⁵⁹ The means of transportation to workplace was also found to be significantly associated with the quality of life among the population studied. The respondents that trek or enter commercial bus scored lower in their quality of life compared with those that take motorcycle or ride private or company car. The association between means of transportation and quality of life might be attributed to the difference in income levels among the respondents.

Considering the influence of life style on the quality of life of respondents as revealed in this study, smoking and alcohol intake were not found to be significantly associated with any aspect of the quality of life. However, it was found that a greater proportion of those who exercise had good overall quality of life compared to those who do not exercise, but the difference was not statistically significant (p = 0.09). The findings of a study on exercise participation, BMI, and HRQOL in women of menopausal age, revealed that women who were regularly active reported better health-related quality of life scores than women who were not regularly active.²³ Exercise is generally believed to promote good health. Exercise is particularly important for improving physical and mental functioning of the body. It is also useful for promoting social relationship especially when it is organized as in case of game or sport. Further study is suggested to find out the role of exercise in determining HRQOL in the developing countries.

This study has found that increased BMI, systolic blood pressure and diastolic blood pressure negatively influenced the quality of life of respondents. Respondents with higher

values of these indices scored lower in their overall perception and global domain quality of life, and satisfaction with their health. This was consistent with the findings of others studies in which obesity was associated with decrements in overall quality of life whether it is physical, psychological, or social.5,6,7,8,18,19,20 In another study to examine the associations between socio-demographic variables, body weight and quality of life in schizophrenic outpatients, it was found that quality of life in schizophrenic patients is related to body weight, and the burden of obesity is primarily experienced as a physical problem.⁵⁷ Another similar study showed that quality of life scores were optimal when BMI was in the range of 20 to 25.²³