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Blood pressure profile and its clinico-social determinants among attendees of urban health and training center of IQ City Medical College, Durgapur, West Bengal.
Corresponding author: Dr. Rakesh Kumar. Flat-D, first floor, JD-3, residential complex, IQ City Medical College, Durgapur, West Bengal, Pin-713206 Email.- dr.rakeshkr082@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Kumar S, Kumar R, Chakraborty SN, Basu D, Richa, Ghose G. Blood pressure profile and its clinico-social determinants among attendees of urban health and training center of IQ City Medical College, Durgapur, West Bengal. J Comprehensive Health 2018; 6(2):112-116.
Abstract
Background:
High blood pressure or Hypertension is one of the leading causes of death among the existing non communicable diseases whereas pre-hypertension is the early intervention area from where HTN can be prevented. Hypertension, pre-hypertension can lead to so many comorbidities and life threatening conditions. Blood pressure profile and its epidemio-social determinants are few, though relationship with clinical and biochemical variables are well studied by many researchers. Apart from some social determinants, sedentary lifestyle, substance abuse, obesity and unhealthy diet are some major factors that contribute in occurrence of hypertension.
Aims and objectives:
To ascertain proportion and clinico-social determinants of different blood pressure profile.
Materials and methods:
Cross-sectional study in an institution among 208 adults, drawn by systematic random sampling, interviewed and examined with a schedule and necessary instruments at exit point. Multivariate logistic regression model taken to see the relationship with different variables.
Results:
16.8% had HTN and 43.8% had pre-HTN. 29.3% males, 19% literates, 46.4% among subjects with some form of substance abuse, 25.7% HTN among physically inactive subjects.
Conclusion:
HTN proportion was as par with other records but proportion of pre-HTN was much higher. HTN and pre-HTN was more among males, people with substance abuse, inactive people, junk food consumers.
Keywords
Blood pressure
Hypertension
Pre-hypertension
Determinants of BP
Introduction:
The world has recently observed epidemiological transition where it was being observed that death due to non-communicable disease exceeded to that of death due to communicable diseases. High blood pressure or Hypertension (HTN) was one of the leading causes of death among the existing non communicable diseases[1] and pre-hypertension (pre-HTN) is the intervention area from where HTN can be prevented if managed judiciously or aggravates to HTN if no or inadequate intervention taken. Hypertension is characterized by Systolic ≥L40 mm of Hg or diastolic BP ≥ 90 mm of Hg[2] and is prevalent among 10 to 30% of Indian population.[3-6] Hypertension, pre-hypertension can lead to so many comorbidities and life threatening conditions like stroke, cardiovascular diseases, renal complications if not recognized or treated adequately or risk factors are not modified. There are several proven factors that can lead to hypertension. Sedentary lifestyle, addition, obesity and unhealthy diet are some major issue. There are also some socio-demographic determinants[7] of hypertension like extreme high and low social class, literacy status, Race, Ethnicity[8] etc.
Hypertension is a well-established fact for adverse Cardio vascular events (CV), renal function, retina changes etc., whereas other blood pressure profiles also creates unhealthy health conditions. Hypotension can cause dizziness, lightheadedness[9] or in extreme it may cause shock though generally low grade hypotension is considered as healthy. Pre-HTN can lead HTN any day.
Proportion study of different BP profile along with its clinico- social determinants were very few in West Burdwan district, particularly in Durgapur, thus a study was conducted to address proportion and clinic-social determinants of different blood pressure profile and to suggest possible health fact finding and intervention.
Materials and Methods:
An institution based observational cross-sectional study was performed among attendees of Urban health and training center, Department of Community Medicine of IQ City medical college, Durgapur, West Bengal from April to August 2017 with prior approval by the institutional ethics committee of IQ City Medical College, Durgapur. Only attendees of age ≥ 18 years were interviewed and examined, whereas severely ill and disagreement for consent were excluded from the study. Sample size was calculated from standard WHO guideline[10] using formula 4PQ/d[2]. Considering Proportion(P) of HTN=10%[3], Q=(1-P), and absolute precision 5 with 95% confidence interval minimum sample size came to be 144. We continued data collection through systematic random sampling technique throughout our data collection period without deploying extra resources due to which a total of 208 participants were included. Sample interval of systematic random sampling was pre decided, based up on the previous record on patient attendance.
A predesigned, pretested, semi-structured schedule was used to interview study subjects and relevant clinical methods were applied to note waist circumference (WC), height, weight, BMI, BP etc. Blood pressure profile was taken according JNC8 guideline.[2]
Operational definition:
Substance abuse:
Those who were using any form of addicting substance like alcohol consumption, tobacco use etc., within previous 3 months were considered as 'Yes' in substance abuse
Physical activity:
Those who were involved in moderate to severe intensity of physical activity for at least 5 days in a week for previous 3 months were considered as physically active.
Junk food consumers:
Those who were consuming junk foods like carbonated beverage, roadside oily food, pastries etc., for twice in a week for previous 3 months were considered as junk food consumers
After collection, data were entered in Microsoft Excel Sheet and was analyzed with IBM SPSS software version 20. Results were presented in forms of tables, mean value. Chi-square tests were done for categorical data and Multinomial (Multivariate) logistic regression was done to find relationship between Blood pressure profiles with different variables.
HTN. 25.7% of inactive study population had HTN.
Table 4 showed multinomial logistic regression model where Normotensives were counted as reference category and in some category were considered as '0' due their redundancy in regression model.
Variables | Frequency | Percentage (%) | |
---|---|---|---|
Blood Pressure Profile | Hypertensive | 35 | 16.8 |
Pre-HTN | 91 | 43.8 | |
Normotensive | 82 | 39.4 | |
Gender | Male | 92 | 44.2 |
Female | 116 | 55.8 | |
Education | Literate | 147 | 70.7 |
Illiterate | 61 | 29.3 | |
Addition | Yes | 56 | 26.9 |
No | 152 | 73.1 | |
Junk Food habit | Yes | 134 | 64.4 |
No | 74 | 35.6 | |
Physical Activity | No | 70 | 33.7 |
Yes | 138 | 66.3 | |
Total | 208 | 100 |
Mean | Sth. Deviation | |
---|---|---|
AGE (in years) | 37.81 | 13.385 |
BMI (kg/m2) | 22.144 | 3.1254 |
WC(in cm) | 79.98 | 9.897 |
Variables | BP | Chi-square value | P Value | |||
---|---|---|---|---|---|---|
HTN | Pre-HTN | Normal | ||||
Gender | Male | 27(29.3) | 43(46.7) | 22(23.9) | 25.773 | 0.000 |
Female | 8(6.9) | 48(41.4) | 60(51.7) | |||
Substance abuse | Yes | 26(46.4) | 19(33.9) | 11(19.6) | 49.201 | 0.000 |
No | 9(5.9) | 72(47.4) | 71(46.7) | |||
Education | Literate | 28(19.0) | 55(37.4) | 64(43.5) | 8.219 | 0.016 |
Illiterate | 7(11.5) | 36(59.o) | 18(29.5) | |||
Junk Food | Yes | 17(12.7) | 67(50.0) | 50(37.3) | 7.625 | 0.022 |
No | 18(24.3) | 24(32.4) | 32(43.2) | |||
Physical Activity | No | 18(25.7) | 15(21.4) | 37(52.9) | 21.798 | 0.000 |
Yes | 17(12.3) | 76(55.1) | 45(32.6) |
HTNa | B | Std. Error | Wald | df | Sig. | Exp(B) | |
---|---|---|---|---|---|---|---|
Hypertensive | |||||||
Intercept | -7.720 | 3.113 | 6.151 | 1 | .013 | ||
AGE | .073 | .041 | 3.169 | 1 | .075 | 1.076 | |
PERCAPITAINOME | -.001 | .000 | 6.647 | 1 | .010 | .999 | |
BMI | -.074 | .121 | .377 | 1 | .539 | .928 | |
Waist Circumference in cm | .077 | .051 | 2.249 | 1 | .134 | 1.080 | |
Male | .801 | .807 | .985 | 1 | .321 | 2.227 | |
Female | 0b | . | . | 0 | . | . | |
Literate | .115 | .769 | .022 | 1 | .881 | 1.122 | |
Illiterate | 0b | . | . | 0 | . | . | |
Substance abuse Yes | 1.707 | .853 | 4.000 | 1 | .046 | 5.512 | |
Substance abuse- No | 0b | . | . | 0 | . | . | |
Junk food Yes | .668 | .847 | .623 | 1 | .430 | 1.951 | |
Junk food No | 0b | . | . | 0 | . | . | |
Physica 1 activity No | -.960 | .779 | 1.520 | 1 | .218 | .383 | |
Physical activity Yes | 0b | . | . | 0 | . | . | |
Pre-HTN | |||||||
Intercept | -4.961 | 2.578 | 3.703 | 1 | .054 | ||
AGE | .100 | .025 | 16.031 | 1 | .000 | 1.106 | |
Percapita income | .000 | .000 | 3.036 | 1 | .081 | 1.000 | |
BMI | -.005 | .083 | .004 | 1 | .953 | .995 | |
WC(cm) | .007 | .031 | .053 | 1 | .818 | 1.007 | |
Male | 1.570 | .553 | 8.071 | 1 | .004 | 4.805 | |
Female | 0b | . | . | 0 | . | . | |
Literate | -.520 | .578 | .808 | 1 | .369 | .595 | |
Illiterate | 0b | . | . | 0 | . | . | |
Substance abuse Yes | -.941 | .671 | 1.968 | 1 | .161 | .390 | |
Substance abuse- No | 0b | . | . | 0 | . | . | |
Junk food Yes | 3.449 | .666 | 26.814 | 1 | .000 | 31.453 | |
Junk food No | 0b | . | . | 0 | . | . | |
Physica 1 activity No | -3.106 | .561 | 30.685 | 1 | .000 | .045 | |
Physical activity Yes | 0b | . | . | 0 | . | . |
Model fitting information:
Chi-square value at df 18 was 161.3 which was statistically significant (p=0.000). Independent variables could explain 5.40 to 6.19% variation
Results:
Dataset of 208 study subjects were analyzed. Table 1 revealed that 16.8% of the populations were diagnosed as having Hypertension whereas a large proportion of the study subjects were suffering from Pre-hypertension (43.8%). The study also revealed that major proportion of the study subjects were female (55.8%) and maximum of the population were Literate (70.7%). 66.3% of them were physically active and 73.1% of the study people were devoid of any substance abuse though consumption of junk food (64.4%) was high among them. Mean age of the study population as shown in Table 2, was 37.81 years. Mean waist circumference was 79.98 cm.
It can be seen from Table 3 that Males had more proportion of HTN (29.3%) and Pre-HTN (46.7%). The same table also revealed that HTN was more among people with substance abuse (46.4%). 19% of Literates and 11.5% of Illiterates were suffering from HTN whereas 59% of Illiterates were having Pre-HTN. Table 3 also revealed 50% of junk food consumers were suffering from pre-HTN and only 12.7% of them had of dependent variable as revealed from cox and snell pseudo r[2] nagelkerke R square statistic. Per-capita income and substance abuse was independent risk factors for HTN (p value <0.05) whereas age, male gender, substance abuse, physical inactivity and junk food consumers were independent risk factors for pre-HTN (p value <0.05)
Discussion:
The study revealed a very common and matching result in terms of proportion of HTN i.e., 16.8% which was as par with many studies[3-6] but the study revealed another interesting result regarding proportion of pre-HTN. Pre-HTN was surprisingly high (43.8%) in this study as compared to 35% by Wang R et al[11]. Very soon, if no intervention provided or taken may be converted to HTN in a large proportion and there are very few studies existing that revealed proportion of pre-HTN. Proportion of HTN & pre-HTN were statistically more among males, few other studies reported similar results[11-12]. It might be due to the more risk factors among males like substance abuse. Result may be because of geographical and cultural variation between the two study countries. 70.7% of the study population was Literate which was a bit less than national standard (74%)[13]. 19% of literates and 11.5% of illiterates were suffering from HTN whereas in case of pre- HTN, illiterates were more sufferers which were statistically significant. It was seen that 64.4% of the study population were consuming any kind of junk food. Though HTN was only 12.7% among them it should be considered that many more will be in that zone in very near future as proportion of pre- HTN was very high among them (50%). Junk food mainly contains trans fat and more salts, which are proven risk factors[14,15] for proportion of pre-HTN. Proportion of HTN was quite high among people with substance abuse (46.4%) which was similar to a study finding by a study by Puddey et al[16] which showed impact of Alcohol in Blood pressure, only hope was that maximum study people were devoid of any substance abuse (73.1%). HTN was relatively low among physically active study subjects which was as par with many studies[17-18]
Multivariate logistic regression model revealed that Per- capita income and substance abuse was independent risk factors for HTN whereas age, male gender, substance abuse, physical inactivity and junk food consumers were independent risk factors for pre-HTN.
Conclusion:
Proportion of HTN was high among attendees of UHTC but proportion of pre-HTN was even much higher. Age, per capita income, gender, substance abuse, junk food consumption and physical inactivity had an impact on proportion of HTN and pre-HTN.
Recommendation:
Special awareness generation initiative programme should be undertaken to address junk food consumption, Substance abuse control, lifestyle changes. Government, NGO and individual level approach at solo patient care center and community care setting should be very aggressive to detect HTN and Pre-HTN at earliest.
Acknowledgements:
Sincere thanks to Diabetes Awareness and You (DAY), Kolkata, a social welfare organization, for their unrestricted support (Human resource).
Conflict of Interest:
None declared
Source of support:
Nil
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