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Original Article | Open Access | Eur. J. Med. Health Sci., 2024; 6(6), 177-188 | doi: 10.34104/ejmhs.024.01770188

Impact of Some Selected Health Complications on Hypertension in Bangladesh

Mazharul Islam Mail Img Orcid Img ,
Md. Abdulla-Al- Mamun Mail Img Orcid Img ,
Mohammad Ahsan Uddin* Mail Img Orcid Img ,
Asif Nahian Mail Img Orcid Img

Abstract

Hypertension is a silent killer of human life and the numbers of hypertensive patients are increasing globally and nationally. Therefore, the purpose of the study was to investigate age-specific hypertension patterns, alarming age for hypertension, and many determinants of hypertension in Bangladesh, e.g., feminine and nuptial determinants, socio-demographic determinants, health complication determinants, and body composition determinants. The data were collected from Rajshahi district using stratified multistage sampling with technique based on the scheduled questionnaire for this study. To identify the most important determinants, sophisticated statistical tools have been used such as percentage distribution, point bi-serial correlation, phi correlation, Pearson product-moment correlation, path analysis, boot strapping technique, binary backward logistic regression method including Likelihood ratio test, Hosmer-lemeshow test, Nagelkerke R2, Sensitivity and specificity, receiver operating characteristics (ROC) curve etc. From the view of proper critical analysis of impact of some key factors on hypertension, the study was divided into four aspects such as socio-demographic, feminine and nuptial, health complication and body composition aspects.

INTRODUCTION

The study on hypertension is designed to make a broad analysis about the patterns of hypertension in Bangladesh and examine the risk factors of hyper-tension by in-depth assessment. Before beginning the study on hypertension it is important to know about hypertension. Hypertension is nothing but high blood pressure and high blood pressure is higher level of blood pressure. Also, blood pressure is the lateral pressure exerted on the walls of the arteries by blood flowing through the arteries. It reflects the rhythm of the heart beat and is a measure of the volume of blood pressure into the vessels by the heart. The pressure of blood within the arteries is highest whenever the heart contracts and is called systolic pressure. Between beats, when the ven-tricles are at rest, arterial pressure is at its lowest and is called diastolic pressure. 

Among leading disease which occur the premature death, hypertension is one of them. Worldwide prevalence estimates for hypertension may be as much as 1 billion individuals, and approximately 7.1 million deaths per year may be attributable to hypertension (WHO, 2002). This study also reports that systolic blood pressure (>115 mm Hg) is responsible for 62% of cerebrovascular disease and 49% of ischemic heart disease, with little variation by sex. In addition, suboptimal blood pressure is the number one attributable risk for death through-out the world (WHO, 2002). Since most blood pressure related deaths or non fatal events occur in middle age or the elderly, the loss of life years comprises a smaller proportion of the global total, but it is nonetheless substantial (64.3 million disease burden, or 4.4 % of the total) (WHO, 2002). 

Health is wealth and sound health of Bangladeshi peoples is the primary goal of all development plans. But the poor health of Bangladeshi people is an intractable problem as poverty.  Poor health is occurred due to poverty, malnutrition, disease, lack of education, sex discrimination etc.  Among the leading diseases hypertension is one which may lead to heart attack, stroke, heart failure, paralysis, kidney disease, eye damage etc. (Chobanian, 2003). Hence, hypertension is a risk factor of premature death and a barrier of sound health. So, it is essential to formulate an appropriate strategy to control hypertension for healthy life.

LITERATURE REVIEW

Bangladesh is familiar as low income and developing country with high mortality (WB, 2007; WHO, 2002). The mortality rate is 9.23 per thousand and the healthy life expectancy in Bangladesh is 56 where the life expectancy/birth is 69.40 (WHO, 2010). A vast portion of total mortality rate is affected by premature deaths. Among the causes of premature or unexpected death hypertension is one which also leads to various diseases of premature deaths. Hypertension is one of top thirteen diseases of deaths in Bangladesh and causes 1.91% of total deaths (WHO, 2010). In the same report, hypertension related coronary heart disease (17.11%) and stroke (8.57%) are the first and third leading causes of total deaths (WHO, 2010). Another report reveals that hypertension related Ischemic heart disease is the first leading causes of deaths in Bangladesh, accounting for 12% of total deaths (WHO, 2006). 

Discussing the literature reviews (Hoque et al., 2012; Islam et al., 2012; Islam et al., 2012; Rahim et al., 2012; ICDDR, B, 2011; Khanam et al., 2011; Kokiwar, 2011; Zaman et al., 2010; Midha et al., 2009; Agrawal et al., 2008;  Chen et al., 2006a; Chen et al.,2006b; Saha et al., 2006; Alamgir et al., 2005; Chen, 2005; Sayeed et al., 2005; Zamudio et al., 2005; Cooper-Dehoff et al., 2004; Chobanian et al., 2003; Sayeed et al., 2003; Sayeed et al., 2002; Hannan et al., 2001; Moula et al., 2001; WHO, 2001; Bond et al., 2000; Rahaman et al., 1999; Zaman and Rouf, 1999;Chowdhury et al., 1998; Hoque et al., 1998; Sayeed et al., 1995; Sayeed 1994; Khandakar, 1993; Islam et al., 1983; Islam et al., 1979; Ullah, 1976), it is clear that many studies about hypertension in nationally and internationally have been conducted in biological aspect through a lot of researchers or institutions. But the mentioned knowledgeable sources (literature reviews) indicate that any expected research about health com-plications aspect aspect has not yet been conducted. Hence, some questions may be asked as following:

i. Are there any age patterns as risk factors of hypertension?

ii. Are there any health complications risk factors of hypertension?

More than one reasons or risk factors are suspected for developing hypertension in the mentioned fields. The suspected risk factors are examined by this study. According to WHO (2001), developing countries are thus likely to face an enormous burden of chronic non-communicable diseases in the near future. Of these diseases, hypertension is the most common of the Cardio-vascular diseases which is the leading cause of morbidity and mortality in the industrial world as well as becoming an increasing common disease in the developing countries (Saha et al., 2006; Islam MM et al., 2022). 

Maternal death is an important factor which snatches away at least two life. The causes of maternal death vary by United Nations (UN) region. Hypertension is the first leading cause of maternal mortality in Latin America, accounting for 25.7% of maternal deaths, and also in Developed countries it is second leading cause of maternal health, where it accounts for 14.9% of maternal deaths (Khan et al., 2006). In Asia and Africa, hypertensive disorders, causing 9.10% of maternal deaths. The most important cause of maternal death is “other direct causes” (21%), which includes largely complications during interventions such as those related to caesarean section and anesthesia, followed by hypertensive disorders and embolism (Khan et al., 2006). Also, deaths were occurred by blood pressure are greater in developed countries than developing countries for both sex (WHO, 2002).

From the world-wide information discussed above, it is undoubtedly clear that high blood pressure, other diseases caused by hypertension and blood pressure related diseases plays a vulnerable impact on premature deaths of human life. Since the percentage is small with respect to total world population, but the amount is sustainable. An investigation represents that 27.40% of casus-specific deaths which caused by different causes have been occurred by hypertension related disease such as Ischemic heart disease, rheumatic heart disease, hypertensive heart disease, cerebrovascular diseases, inflammatory heart diseases etc. (WHO, 2011b).  The death rates due to hypertension and hypertension related diseases are increasing day by day. Also, 10.51% deaths have been occurred by blood pressure, heart disease as well as stroke and prevalence of morbidity by blood pressure is 6.20% (BBS, 2005; Begum, 1996).  In another study, about 4% deaths were due to hypertensive complications in Bangladesh (BHSR, 1998).

The prevalence of hypertensive diabetic is increasing rapidly in Bangladesh (Hoque et al., 2012). A report reveals that the overall prevalence rates of systolic and diastolic hypertension in the Bangladesh population were 14.40% and 9.10%, respectively (Sayeed et al., 2002). The crude prevalence of systolic and diastolic hypertension in Bangladesh is 6.80% and 5.40%, respectively (Sayeed et al., 2005).  In an investigation, 11.30% adult people are affected by hypertension (Zaman and Rouf, 1999). Though the number of deaths by hypertension is little, deaths by hypertension related diseases is a major part of total deaths and increasing day by day. Also, the mentioned report proves that the large number of people of Bangladesh living with hypertension and it is increasing day by day. 

MATERIALS AND METHODS:

The data were collected from Rajshahi district using stratified multistage sampling with technique based on the scheduled questionnaire for this study. To identify the most important determinants, sophisticated statistical tools have been used such as percentage distribution, point bi-serial correlation, phi correlation, Pearson product-moment correlation, path analysis, boot strapping technique, binary backward logistic regression method including Likelihood ratio test, Hosmer-lemeshow test, Nagelkerke R2, Sensitivity and specificity, receiver operating characteristics (ROC) curve etc.

In order to study the background characteristics of different variables, the percentage distribution of the considered variables is conducted. This is applied in the study for health complication related background characteristics. To study the relationship between two binary variables, phi correlation technique is more appropriate to proper investigate the relation. Hence, before find out the risk factors of hypertension it is important to verify the relationship between hypertension and other health complications. Ensuring the existence of relationship between hypertension and other selected health complications, it is important to analyze the causal relationship between hypertension and other selected health complication variables. Hence, we have studied the causal relationship applying binary backward logistic regression method. The fitted model and requisite results are displayed in following: 

Now we would like to know how effectively the model we have describes the outcome variable by R square, Hosmer-Lemeshow and classification table. A more complete description of classification accuracy is given by the area under the ROC curve. Bootstrapping is a re-sampling method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation co-efficient or regression coefficient. The bootstrapping method is used for logistic regression coefficients of health complications factors.

RESULTS AND DISCUSSION

From the view of proper critical analysis of impact of some key factors on hypertension, the study was divided into four aspects such as socio-demo-graphic, feminine and nuptial, health complication and body composition aspects. About 28.10% hypertensive patients were due to socio-demographic aspect. Applying binary logistic regression model in the study of causal relationship, age was found as the most significant variable. i. e. age had positive significant impact on hypertension. Secondly, education had second most significant negative impact on hypertension and its odds ratio focus that for every increase of one year in education, the risk of hypertension increased 0.958 time. It was also found that sedentary life style, working hour (>8 hrs) per day, social stress, occupational stress and mental stress, hereditary hypertension, smoking, taking alcohol and taking excess salt had positive significant impact on raising hypertension where taking regular exercise had negative significant impact on hypertension. Hence, sedentary life style, working hour (>8) per day, social stress, occupational stress, mental stress, hereditary hypertension, smoking, taking alcohol, taking excess salt may be considered as risk factors for raising high blood pressure or hypertension. Though the age was found to be as the highest risk factor, but age increasing is out of human control. 

It was found that the number of systolic hypertensive patients (60.40%) were greater than diastolic hypertensive patients (47.90%) in old age group (≥61 years) where diastolic hypertensive patients (7.40%) were greater than systolic hypertensive patients (3.80%) in young age group (≤39 years) and in middle age group (40-60 years) both are same. Hence, young age (≤39 years) was risk period for occurring diastolic hypertension than systolic and old age (≥61years) was risk period for occurring systolic hypertension than diastolic when middle age (40-60 years) was also risk period for occurring both type of hypertension. The differences between two same percentiles of systolic and diastolic blood pressure were varying from 51 mmHg to 93 mmHg for hypertensive respondents where it is same for normotensive. Hence, the abnormality (>40 mmHg) of the differences is an indicator of hypertension or prehypertension. In the health complication aspect, the adult hypertensive patients were 30.60%. In the analysis of causal relationship (applying binary backward logistic regression method) between hypertension and other health complication, kidney disease was found as a significant variable. i. e. kidney disease had positive significant impact on hypertension and its odds ratio 5.428 indicates that the respondents with kidney disease had 5.428 times risk to occur hypertension than the respondent without kidney disease. Also, tumor, diabetes, sleep apnea, hypothyroidism, hyperthyroidism, tachy-cardia and overweight had the positive significant impact for occurring hypertension. After discussing the binary logistic regression it was further found that kidney disease, tumor, diabetes, sleep apnea, hypothyroidism, hyperthyroidism, tachycardia and overweight might be considered as risk factors for raising high blood pressure or hypertension. In selected feminine and nuptial aspect, the active married female hypertensive patients were 28.90%. In the study of causal relationship (applying backward binary logistic regression model) between hypertension and other feminine and nuptial characteristics, first menstruation age was found to be as significant variable. i. e. first menstruation age had negative significant impact on hypertension. Duration of couple life had significant positive significant impact on hypertension. Use of contraceptive method, menopause, pregnancy and miscarriage had positive significant impact for occurring hypertension compared with those who do not possesses the characteristics. Hence, first menstruation age, duration of couple life, use of contraceptive method, menopause, pregnancy and miscarriage might be considered as risk factors or determinants for raising high blood pressure or hypertension. Using path analysis, the total effect of body mass index, abdominal circumference and ratio of waist to hip on systolic blood pressure were 0.207, 0.185 and 0.118 respectively in which their direct effect were respectively 0.146, 0.082 and 0.047. The total effect of body mass index, abdominal circumference and ratio of waist to hip on diastolic blood pressure were 0.289, 0.231 and 0.138 respectively in which their direct effect were respectively 0.231, 0.079 and 0.043.

Health Complication determinants of hyper-tension

In medicine, complication is an unfavorable evolution of a disease, a health condition or a therapy. Hence, this sub section is devoted for health complications aspect. In the context of health complication, the study is conducted on 2010 respondents of above 18 years old that are separated from total data 2250. For health complication aspects we consider the adult people who are above 18 years old. Because before 18 years old the people are known as child and the children are consider as immature in physically and mentally. 

Health complication related background characteristics

To develop any basic concept about the study, background characteristics of the respondents or target population or nature of the data have to study. This assessment leads to the interpretation of results and to examine any cause-effect relationship among the study variables. The percentages of selected health complication related background charac-teristics among the adult people (above and 18 years old) are displayed in Table 1. Among adult total respondents 4.8% are patients with kidney disease. Our study shows that 13.60% respondents have tumor when 8.2% are diabetic patients. Sleep apnea disease affect 25.10% respondent. The percentages of hypothyroidism and hyperthyroidism disease are 32.40% and 31.70% respectively. The pulse rate per minute above 100 times is known as tachycardia disease and the people affected by tachycardia disease are 5.60%. Among the adult respondents 24.3% are fatty. Finally, the adult hypertensive patients are 30.60%.

Table 1:  Percentage distribution of health complication characteristics. 

Characteristics

Percent (%)

Characteristics

Percent (%)

Characteristics

Percent (%)

Kidney Disease

Sleep Apnea

Tachycardia

No

95.2

No

74.9

No

94.4

Yes

4.8

Yes

25.1

Yes

5.6

Total

100

Total

100.0

Total

100.0

Tumor

 

Hypothyroidism

 

Over Weight

 

No

86.4

No

67.60

No

75.7

Yes

13.6

Yes

32.4

Yes

24.3

Total

100

Total

100.0

Total

100.0

Diabetes

 

Hyperthyroidism

 

Hypertension

 

No

91.8

No

68.3

No

69.4

Yes

8.2

Yes

31.7

Yes

30.6

Total

100

Total

100.0

Total

100.0

Association between hypertension and health complications

To study the relationship between two binary variables, phi correlation technique is more appropriate to proper investigate the relation. Hence, before find out the risk factors of hypertension it is important to verify the relationship between hypertension and other health complications. Also, the results are represented in Table 2. This table depicts that the relationships between hypertension and other variables such as kidney disease, tumor, diabetes, sleep apnea, hypothyroidism, hyperthy roidism, tachycardia and overweight are highly significant at 1% level of significance. These relationships have been studied by phi correlation because all variables are binary.

Table 2: Association between hypertension and health complications. 


Impact of health complication determinants on hypertension 

Ensuring the existence of relationship between hypertension and other selected health complications, it is important to analyze the causal relationship between hypertension and other selected health complication variables. Hence, we have studied the causal relationship applying binary backward logistic regression method. The fitted model and requisite results are displayed in following: 




To study the causal relationship between hypertension and other health complication, kidney disease is found as a significant variable. i. e. kidney disease has positive significant impact on hypertension and its odds ratio 5.428 indicates that the respondents with kidney disease have 5.428 times risk to occur hypertension than the respondent without kidney disease. Secondly, tumor has positive significant impact on hypertension and the odd ratio 1.643 indicates that the respondents with tumor have 1.643 times odds or risk of occurring hypertension compared with those who do not have tumor. Thirdly, diabetes has positive significant impact on hypertension and its odd ratio indicates that the respondents with diabetes have 3.452 times odds or risk of occurring hypertension compared with those who do not have diabetes disease. Sleep apnea has positive significant impact on hypertension and the odds ratio indicates that the respondents who possess the sleep apnea have 15.795 times risk for occurring hypertension compared with those who do not possess. Also, hypothyroidism, hyperthyroidism and tachycardia disease have positive significant impact on hypertension and the odds ratios estimate that the respondents who possess hypothyroidism, hyperthyroidism and tachycardia disease have 1.662, 8.096 and 1.771 times risk respectively for occurring hypertension compared with those who do not possess. 

Table 3: Stepwise logistic regression of hypertension on health complications. 

Characteristics

Regressor Coefficient (β)

Standard Error of β

Wald Test

d. f

P - Value

Odds Ratio

95% Confidence Interval

Lower

Upper

Kidney Disease

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

1.692

.376

20.236

1

.000

5.428

2.597

11.342

Tumor

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

.496

.273

3.315

1

.069

1.643

.963

2.803

Diabetes

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

1.239

.285

18.845

1

.000

3.452

1.973

6.039

Sleep Apnea

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

2.760

.191

207.804

1

.000

15.795

10.853

22.986

Hypothyroidism

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

.508

.184

7.658

1

.006

1.662

1.160

2.382

Hyperthyroidism

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

2.091

.172

147.608

1

.000

8.096

5.778

11.345

Tachycardia

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

.572

.314

3.322

1

.068

1.771

.958

3.275

Over Weight

 

 

 

No (r)

-

-

 

 

-

-

 

 

Yes

.939

.169

30.782

1

.000

2.558

1.836

3.564

Constant

-3.266

.141

535.066

1

.000

.038

 

 

Note: r represents the reference category.

Finally, over weighted or fatty respondents are in risk of 2.558 times for occurring hypertension than normal normal respondents. After discussing the binary logistics regression it is established that kidney disease, tumor, diabetes, sleep apnea, hypothyroidism, hyperthyroidism, tachycardia and over weight may be considered as risk factors for raising high blood pressure or hypertension. 

Assessing the fit of the logistic regression model

Now we would like to know how effectively the model we have describes the outcome variable by R square, Hosmer-Lemeshow and classification table. Also, the results of assessment are displayed in Table 4

Table 4: Results of assessment of fitted logistic regression model. 

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

1134.885

0.487

0.70

Hosmer and Lemeshow Statistic

df

P - Value

2.985

5

0.71

Classification Table

Predicted Hypertension

%

No

Yes

Observed Hypertension

No

1327

68

95 (specificity)

Yes

148

467

76 (sensitivity)

 

90

Area Under ROC Curve = 0.93

The Table 4 depicts the value of Negelkerke R square is 0.70 which implies that all selected variables of logistic regression model have explained 70% of outcome variable. Also, the value of the Hosmer-Lemeshow goodness-of-fit statistic is 2.985 and the corresponding p-value is 0.75 with 5 degree of freedom which indicates that the model seems to fit quite well. The results of classifying the observations of hypertension using fitted logistic regression model are presented in same table. The overall rate of correct classification is estimated as 90% with 95% of the hypertension free group (specificity) and only 75% of the hypertensive group (sensitivity) being correctly classified.

Receiver operating characteristics (ROC) curve for health complication factors

The area under the ROC curve in the present study for socio-demographic aspects is 0.93 which indicates that the models ability is excellent to discriminate between those respondents who have hypertension than who do not have. 

Fig. 1: ROC curve for health complications.

Receiver operating characteristics (ROC) curve for health complication factors

The area under the ROC curve in the present study for socio-demographic aspects is 0.93 which indicates that the models ability is excellent to discriminate between those respondents who have hypertension than who do not have.

Logistic regression for health complications by bootstrapping 

Using bootstrapping method, regression coefficients of health complications factors have been found approximately same with comparing the logistic regression coefficients. The small amount of bias may be ignored. These results are shown in the Table 5.

Table 5: Logistic regression for health complications by bootstrapping. 

Bootstrap

Logistic Regressor

Coefficient (β)

Bootstrapping Regressor Coefficient (β)

Bias

Standard Error of β

P-value

95% Confidence Interval

Lower

Upper

Kidney Disease

1.692

1.695

.000

.464

.001

.694

2.625

Tumor

.496

.504

.009

.262

.056

.002

1.046

Diabetes

1.239

1.244

.023

.300

.001

.688

1.885

Sleep Apnea

2.760

2.760

.024

.195

.001

2.402

3.168

Hypothyroidism

.508

.510

-.005

.204

.009

.091

.889

Hyperthyroidism

2.091

2.091

.028

.193

.001

1.742

2.495

Tachycardia

.572

.570

-.005

.316

.065

-.114

1.138

Over Weight

.939

.940

.015

.173

.001

.592

1.277

Constant

-3.266

-3.259

-.024

.141

.001

-3.585

-3.021

CONCLUSION

Though with increasing age the rate of both type hypertension is increasing but young age (<40years) is more risk period for occurring diastolic hyper-tension than systolic and old age (>60years) is more risk period for occurring systolic hypertension than diastolic when middle age (40-60 years) is also risk period for occurring both type of hypertension. The differences between two same percentiles of systolic and diastolic blood pressure are increasing with increasing percentiles cut-offs for hypertensive respondents and the differences are almost same with increasing percentiles for normotensive. Age, educational level, sedentary lifestyle, working hour (>8hrs) per day, taking regular exercise, social stress, occupational stress, mental stress, hereditary hypertension, smoking, taking alcohol, taking excess salt are statistically highly related with hypertension at one percent level of significant except taking regular exercise. Also, sedentary lifestyle, working hour (>8hrs) per day, taking regular exercise, social stress, occupational stress, mental stress, hereditary hypertension, smoking, taking alcohol, taking excess salt have statistically highly impact on hypertension. Though age may be considered as risk factor, but age increasing is out of human control. Health complications kidney disease, tumor, diabetes, sleep apnea, hypothyroidism, hyperthyroidism, tachycardia and overweight are statistically highly related with hypertension at one percent level of significance. The feminine and nuptial variables first menstruation age, duration of couple life, use of contraceptive method, pregnancy, miscarriage, and menopause have significant impact on hypertension. Body mass index, abdominal circumference and ratio of waist to hip are statistically highly correlated with systolic and diastolic blood pressure at one percent level of significance. 

ETHICAL APPROVAL

Not Applicable

AUTHOR CONTRIBUTIONS

All the authors contributed to conceptualize and design the study. M.I. contributed in report writing, A.A.M. contributed in data collection and A.N. contributed in data analysis of the study. M.A.U. prepared journal article from the research report.

ACKNOWLEDGMENT

First and foremost, the authors are grateful to Almighty Allah. The authors are also thankful to anonymous reviewers and editors for their helpful comments and suggestions.

CONFLICTS OF INTEREST

The author declares no conflict of interest.

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Article References:

  1. Alamgir, A. K. M. et al., (2005). Hypertension Prevalence and Related Factors in an  Urban  Affluent Community in Bangladesh. Bang J Med Sci, 01(11), 22-25. 
  2. AHA, (2011). Understanding-Blood Pressure Readings, American Heart Association (AHA), USA.  http://www.heart.org/HEARTORG/Conditions/High Blood Pressure/About High Blood Pressure/Understanding-BloodPressure-Readings_UCM_301764  
  3. Agrawal, V. K. et al. (2008). Prevalence and Determinants of Hypertension in a Rural Community. MJAFI, 64, 21-25.
  4. Bond, V. et al. (2000). Blood Pressure Reactivity to Mental Stress and Aerobic Fitness in Normotensive Young Adult African-American Males with Parental History of Hypertension. Stress Med., 16, 219-227. http://www3.interscience.wiley.com/cgibin/fulltext/72510212/PDFSTART 
  5. Bennett, et al. (1991). A Simplified General Method for Cluster-sample Surveys of Heath in Developing Countries. pp. Trimest. Statist. Sanit. Mond. 44.
  6. BIDS, (2001). Fighting Poverty Bangladesh Human Development Report 2000. Bangladesh Institute of Development Studies (BIDS), Dhaka, Bangladesh.
  7. BBS, (2005). Population Census - 2001; Community Series, Zila: Rajshahi. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangla-desh.
  8. BBS, (2005). Statistical Year Book of Bangladesh - 2004. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  9. BBS, (2005). Statistical Year Book 2005. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  10. BBS, (2007a). Statistical Year Book of Bangladesh - 2005. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  11. BBS, (2007b). Statistical Year Book of Bangladesh - 2006. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  12. BBS, (2011a). Statistical Year Book of Bangladesh - 2010. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  13. BBS, (2011b). Population & Housing Census 2011: Preliminary Results. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh. https://doi.org/203.112.218.65/WebTestApplication/userfiles/Image/BBS/PHC2011PreliminaryResult.pdf  
  14. BBS, (2012). Statistical Year Book of Bangladesh - 2011. Bangladesh Bureau of Statistics (BBS), Dhaka, Bangladesh.
  15. Begum, S., (1996). Health Dimensions of Poverty in Bangladesh. Bangladesh Institute of Development Studies (BIDS), Dhaka, Bangla-desh.
  16. BHSR, (1998). Cause of death and morbidity profile. Bangladesh Health Service Report (BHSR), Government of Bangladesh, Dhaka, Bangladesh. 
  17. Bernier, et al. (1997). Nuclear Medicine Technology and Techniques. 4th edition. Mosby-Year Book Inc., ISBN: 0-8151-1991-7, P-230. 2. 
  18. Cameron, et al. (1978). Medical physics. Jhon wiley & sons, Inc., New York, P-162. 
  19. Chen, Y. et al. (2006a). Arsenic Exposure from Drinking Water, Dietary Intakes of Vitamins and Folate, and Risk of High Blood Pressure in Bangladesh: A   Population-based, Cross-sectional Study. American Journal of Epidemiology, 165 (5), 540-552.
  20. Chen, Y. et al. (2006b). Nutritional Influence on Risk of High Blood Pressure in Bangladesh: a Population-Based Cross-Secitional Study. The American  Journal of Clinical Nutrition, 84, 1224-1232. 
  21. Chen, Y., (2005). Dietary Factors, Arsenic Exposure, and Risk of High Blood Pressure in Bangladesh. Columbia University, New York.
  22. Chobanian, A. V. et al. (2003). Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. Hypertension, 42, 1206-1252. http://www.hypertensionaha.org 
  23. Cooper-Dehoff, R. M. et al. (2004). Characteristics of Contemporary Patients with Hypertension and Coronary Artery Disease. Clin Cardiol, 27, 571-576. http://www3.interscience.wiley.com/cgi-bin/full text/113493717/PDFSTART 
  24. Chowdhury, A. H. et al. (1998). Association of Angiotensin Converting Enzyme (ACE) Gene Polymorphism with Hypertension in a Bangladeshi Population. Bangladesh Med Res Counc Bull., 27(2), 69 - 78.
  25. Chowdhury, A. K. M. N. et al. (1981). Dasherkandi Project Studies: Demography, morbidity and mortality in a rural community of Bangladesh. Bangladesh Med  Res Council Bull, 22–39.
  26. GOB, (2004). Bangladesh Economic Review 2004. Government of Bangladesh (GOB) Finance Division, Ministry of Finance, Dhaka.
  27. Efron, B. and Tibshirani, R., (1993). An Introduction to the Bootstrap. Boca Raton, FL: Chapman & Hall/CRC. ISBN 0-412-04231-2. 
  28. Hoque, M. N. et al. (2012). Determinants of Blood Pressure Control in Hypertensive Diabetic Patients in Rajshahi District of Bangladesh. J Biomet Biostat, ISSN:  2155-6180, S7.  
  29. Hoque, M. S. et al. (1998). An Exercise Training Combined with Dietary Program for patients with Hypertension. Bangladesh Med Res Counc Bull., 24 (1), 14-19.
  30. Hannan, M. A. et al. (2001). Stroke: Seasonal Variation and Association with Hypertension. Bangladesh Med Res Counc Bull., 27(2), 69 - 78. 
  31. Hansson, L. et al. (1998). Effects of intensive blood-pressure lowering and low-dose aspirin in patients with hypertension: principal results of the hypertension optimal treatment (HOT) randomized trial. Lancet, 351, 1755-62.
  32. ICDDR, B, (2011). Determinants of qualified hypertension diagnosis in surveillance sites of Bangladesh: findings from a cross-sectional study. Health and Science Bulletin, 9(4), International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDRB), Dhaka, Bangladesh.
  33. Islam, A. K. et al. (2012). Hypertension in Bangladesh: a review. Indian Heart J. 64(3), 319-23. 
  34. Islam, M. R. et al. (2012). Association between Hypertension and Chronic Arsenic Exposure in Drinking Water: A Cross-Sectional Study in Bangladesh. Int. J. Environ. Res. Public Health, 9(12), 4522-4536.
  35. Islam, N. M., (2008). An Introduction to Research Methods. Mullick & Brothers, New Market, Dhaka.
  36. Islam, N. et al. (1983). Hypertension in the rural population of Bangladesh-a preliminary survey. Bangladesh Med Res Council Bull, ix: 11–14.
  37. Islam MM, Noor FN, Uddin MA, and Hasan MR. (2022). Risk factors for under-five child mortality: evidence from Bangladesh multiple indicator cluster survey (MICS) 2019. Eur. J. Med. Health Sci., 4(3), 79-90. https://doi.org/10.34104/ejmhs.022.079090 
  38. Islam, N. et al. (1979). Hypertension in Secretariate Population of Bangladesh. Bangladesh Med Res Counc Bull., 5(1), 19-24.
  39. Kokiwar, P. R., (2011). Prevalence of hypertension in a rural community of central India.  Int J Biol Med Res, 2(4), 950 - 953.
  40. Khan, K. S. et al., (2006). WHO Analysis of Causes of Maternal Death: A Systematic Review. Lancer, 367, 1066-1074. 
  41. Khanam, M. A. et al. (2011). Hypertension: Adherence to Treatment in Rural Bangladesh-Findings from a Population-based Study. International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR, B), GPO Box 128, Dhaka 1000, Bangladesh.
  42. Khandakar, R. K., (1993). Evaluation of Hypertension and Other Risk Factors in Ischemic Heart Disease. Chin Med J (Engl)., 106(5), 290-292. 
  43. Kearney, P. M. et al. (2005). Global burden of hypertension: analysis of worldwide data. Lancet, 365, 217-23.
  44. Khan, N. A. et al. (2005). The 2005 Canadian Hypertension Education Program (CHEP) recommendations for the management of hypertension: part 2 - therapy. Can J Cardiol, 21, 657-72.
  45. Lloyd-Jones, D. M. et al. (2004). Framingham risk score and prediction of lifetime risk for coronary heart disease. Am J Cardiol, 94, 20-24.
  46. Menotti, A. et al. (2001). Cardiovascular risk factors as determinants of 25- year all-cause mortality in the seven countries study. Eur J Epidemiol, 17, 337-46.
  47. MFMER, (2010). Low blood pressure (hypotension) causes. Mayo Foundation for Medical Education and Research (MFMER), Mayo-Clinic.com. http://www.mayoclinic.com/health/low-bloodpre ssure/DS00590/DSECTION=causes  
  48. Moula, A. et al. (2001). Helping to Form Club of Diabetic and Hypertensive Patients for Engaging in Walking and Changing Lifestyle: An Experience from Chakaria. International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR, B), GPO Box 128, Dhaka 1000, Bangladesh
  49. Murray, C. J. L. et al. (2000). A Critical Examination of Summary Measures of Population Health. Bulletin of the World Health Organization, 78, 981-994.
  50. Murray, C. J. L. et al. (2002). Health Gaps: An Overview and Critical Appraisal. World Health Organization (WHO), Geneva, Switzerland. http://www.who.int/pub/smph/en/index.html 
  51. Malik, A., (1976). Congenital and acquired heart diseases (a survey of 7062 persons). Bangladesh Med Res Council Bull., II, 115–119.
  52. Midha, T. et al. (2009). Prevalence and Determinants of Hypertension in the Urban and Rural Population of a North Indian District. East Afr J Public Health, 6(3), 268-73.
  53. NHBPEPCC, (1997). The sixth report of the joint national committee on prevention, detection, valuation, and treatment of high blood pressure. National High Blood Pressure Education Program Coordinating Committee (NHBPEPCV), Arch Intern Med, 157, 2413-2446
  54. Neuhauser, H. K. et al. (1998). A comparison of Framingham and SCORE-based cardio-vascular risk estimates in participants of the German National Health Interview and Examination Survey. Eur J Cardiovasc Prev Rehabil, 12, 442-50.
  55. Rahaman, M. et al., (1999). Hypertension and Arsenic Exposure in Bangladesh. American Heart Association, 33, 74-78.
  56. Rahim, M. A. et al. (2012). The Prevalence rate of Hypertension in Rural Population of Bangladesh. Journal of Dhaka National Medical College & Hospital, 18(1).
  57. Sayeed, M. A. et al. (2002). Prevalence of Hypertension in Bangladesh: Effect of Socio-economic Risk Factor on Difference between Rural and Urban Community. Bangladesh Med Res Counc Bull., 28(1), 7-18.
  58. Stevens, S. S., (1946). On the Theory of Scales of Measurement. Science. No. 103 Fuilford. J. P. 1971. Psychometric Methods. New York: MEGrw-Hill.
  59. Saha, M. S. et al. (2006). Serum Lipid Profile of Hypertensive Patients in the Northern Region of Bangladesh. J. bio-sci., 14, 93-98.
  60. Sayeed, M. A., (1994). Blood Pressure and Glycemic Status in Relation to Body Mass Index in a Rural Population of Bangladesh. Bangladesh Med Res Counc Bull., 20(2), 27-35.
  61. Sayeed, M. A. et al. (2005). Diabetes and Hypertension in Pregnancy in a Rural Community of Bangladesh: a population-Based Study. Diabet Med., 22(9), 1267-1271.
  62. Sayeed, M. A. et al. (1995). Prevalence of Diabetes and Hypertension in a Rural Population of Bangladesh. Diabetes Care, 18(4), 555-558.
  63. Sayeed, M. A. et al. (2003). Waist-to-Height ratio is a Better Obesity Index than Body Mass Index and Waist-to-hip Ratio for Predicting Diabetes, Hypertension and Lipidemia. Bangla-desh Med Res Counc Bull., 29(1), 01 - 10.
  64. Sayeed, M. A. et al. (1994). Blood pressure and glycemic status in relation to body mass index in a rural population of Bangladesh. Bangladesh Med Res Council Bull 1994; 20, 27–35.
  65. Touyz, R.M. et al. (2004). The 2004 Canadian recommendation for the management of hypertension: part III -lifestyle modification to prevent and control hypertension. Can J Cardiol, 20, 55-59.
  66. Ullah, W., (1976). Hypertension in Mixed Community. Bangladesh Med Res Counc Bull., 2, 95-99.
  67. WHO, (2011a). Country Profile: Bangladesh. World Health Organization (WHO), Geneva, Switzerland. http://www.who.int/countries/bgd/en/ 
  68. WHO, (2011b). Data and Statistics. World Health Organization (WHO), Geneva, Switzerland. http://www.who.int/research/en 
  69. WHO, (2006). Mortality Country Fact Sheet 2006. World Health Organization (WHO), Geneva, Switzerland.
  70. WHO, (2010). World Life Expectancy: Live Longer Live Better.  World Health Organization (WHO), Geneva, Switzerland.
  71. WHO, (2003). World Health Report 2003: Shaping in Future. World Health Organization (WHO), Geneva, Switzerland. 
  72. WHO, (2002). World Health Report 2002: Reducing Risk Promoting Healthy Life. World Health Organization (WHO), Geneva, Switzerland.
  73. WHO, (2001a). Prevalence, Awareness, Treatment and Control of Hypertension among the Elderly in Bangladesh and India: a Multicentre Study. World Health Organization (WHO), 79(6), 490-500.
  74. WHO, (2001b). The world health report 2001- Mental Health: New Understanding, New Hope. World Health Organization (WHO), Geneva, Switzerland.
  75. WHO, (2004). World Health Report 2004: Changing History. World Health Organization (WHO), Geneva, Switzerland.
  76. WHO, (2007). The top 10 causes of Death. World Health Organization (WHO), Fact Sheet No. 310, Geneva, Switzerland.
  77. WHO, (1997). Preventing and Managing the Global Epidemic of Obesity: Report of the World Health Organization Consultation of Obesity. World Health Organization (WHO), Geneva, Switzerland.
  78. WB, (2007) World Development Indicators Database. World Bank (WB), Washington, U. S. A.
  79. WHO, (2005). Preventing chronic disease: a vital investment: WHO global report. World Health Organization (WHO), Geneva, Switzerland. http://www.who.int/chp/chronic_disease_report/en/ index  
  80. Zaman, S. M. M. et al. (2010). Management of Hypertension: A Bangladeshi Perspective. Bangladesh Medical Journal, 39(1).
  81. Zamudio, S. et al. (1995). High Altitude and Hypertension during Pregnancy. Willey Inter-science Journal. http://www3.interscience.wiley.com/cgi-bin/ abstract/110504400/ABSTRACT 
  82. Zaman, M. M. and Rouf, M. A., (1999). Prevalence of Hypertension in a Bangladesh Adult Population. Journal of Human Hypertension, 13, 547-549.

Article Info:

Academic Editor 

Dr. Abduleziz Jemal Hamido, Deputy Managing Editor (Health Sciences), Universe Publishing Group (UniversePG), Haramaya, Ethiopia.

Received

October 1, 2024

Accepted

November 16, 2024

Published

November 27, 2024

Article DOI: 10.34104/ejmhs.024.01770188

Corresponding author

Mohammad Ahsan Uddin*
Department of Statistics, University of Dhaka, Dhaka, Bangladesh.

Cite this article

Islam M, Mamun MAA, Uddin MA, and Nahian A. (2024). Impact of some selected health complications on hypertension in Bangladesh. Eur. J. Med. Health Sci., 6(6), 177-188. https://doi.org/10.34104/ejmhs.024.01770188


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