Increasing Burden of High Blood Pressure, Heart Diseases and Diabetes - - PDF document

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Increasing Burden of High Blood Pressure, Heart Diseases and Diabetes in India: Evidence from a panel study

Sayantani Chatterjee & Laxmi Kant Dwivedi International Institute for Population Sciences, Mumbai Background For centuries communicable diseases have been the major life-taking causes around the world. Many premature deaths had occurred by uncontrolled epidemics and pandemics. However, with the advancement of the medical facilities in terms of vaccinations, antibiotics along with improved living conditions such as better access to safe drinking water, using proper toilets could trickle down the odds of having communicable diseases. Following such advancements in medical research which could raise the average life expectancies quite as much, the industrialized or the developed countries had to fight against the vices of non-communicable

• diseases. Such a paradigm shift in the disease pattern is often termed as health/epidemiological

transition (Omran, 1971). Earlier, these non-communicable diseases were mostly associated with economic development and thus were considered as the diseases of the rich. But, by the inception of the third millennium, non-communicable diseases appear to sweep the entire

• globe. Moreover, the increasing trends of NCDs in the developing countries along with the

persistent communicable diseases have made the situation worse whereby the developing countries have to bear the dual burden of infective and non-infective diseases in a poor environment backed by not-so-developed health systems. Non-communicable diseases are by far the leading cause of death in the world, representing 63% of all annual deaths. The leading causes of NCD deaths in 2012 were cardiovascular diseases (17.5 million deaths, or 46.2% of NCD deaths or 31% of all global deaths), cancers (8.2 million, or 21.7% of NCD deaths), respiratory diseases, including asthma and chronic

• bstructive pulmonary disease (4.0 million, or 10.7% of NCD deaths) and diabetes (1.5 million,
• r 4% of NCD deaths). Thus, these four major NCDs were responsible for 82% of NCD deaths.

With that being said, around three quarters of these deaths occur in the low and middle income

• countries. These countries which are severely affected by the persistence of communicable

diseases, the emergence of non-communicable diseases worsens the situation. Deaths from non-communicable diseases under age 70 years create a havoc as 82% of the 16 million deaths are in less economically developing countries out of which 37% of the deaths are claimed by heart disease (WHO, 2015). Murray and Lopez (1996) estimated deaths from non- communicable diseases to climb from 28.1 million deaths in 1990 to 49 .7 million in 2020

• globally. With the onset of the new millennium, chronic diseases accounted for 60% of all

deaths worldwide, with 80% of those taking place in developing countries where they have taken a disproportionate toll during the ages of prime productivity (Narayan et al., 2010). Raised blood pressure is one of the leading risk factors for global mortality (Bromfield and Muntner, 2013) and is estimated to have caused 9.4 million deaths and 7% of disease burden – as measured in disability-adjusted life years − in 2010. Globally, the overall prevalence of raised blood pressure in adults aged 25+ years was around 40%. In absolute numbers, the number of people with uncontrolled hypertension rose from 600 million in 1980 to 1 billion in

2 2008.The leading NCD risk factor globally is raised blood pressure to which 13% of global deaths are attributed to (WHO, 2015). It forms to be one of the leading risk factors for morbidity and mortality across the globe (Boutayeb and Boutayeb, 2005; Llyod-Sherlock, 2010). It is a major risk factor for cardiovascular disease along with diabetes (World Health Statistics, 2015). Li and Kelly (2014) observed that the prevalence of high blood pressure is at a higher side among the economically advanced countries (about 333 million in developed countries) and is emerging in the developing countries as well (around 639 million). Diabetes was prevalent among 8.5% of the adults (18+ years) in 2014. In fact, in 2015 it was the direct cause of 1.6 million deaths. The number of people suffering from diabetes increased almost four fold between 1980 to 2014 across the globe (108 million in 1980 to 422 million in 2014). In 2003, 194 million people (aged 20 to 79 years) had diabetes mellitus, almost three quarters of them belong to the developing world. Almost one million people die because of diabetes each year with two-thirds in developing countries (Buowari, 2013). Like most of the developing countries, India too bears the dual burden of communicable and non-communicable disease. Even though India is showing declining morality and changing morbidity pattern, it still has the “unfinished agenda” to combat the infectious diseases. Besides, India has to deal with the “emerging agenda” which includes chronic and newer diseases kindled by changing age structure, changing lifestyle and environment pollution (Nongkynrih et al., 2004). The three leading chronic diseases in India, as measured by their prevalence, are in descending order: cardiovascular diseases (CVDs), diabetes mellitus, and chronic obstructive pulmonary disease (COPD) (Saikia and Ram, 2010; Upadhyay, 2012; Sharma, 2013). All of these diseases are projected to continue to increase in prevalence in the near future given the demographic trends and lifestyle changes underway in India (Shetty, 2002). India is currently experiencing an epidemic of Type 2 diabetes mellitus (T2DM) and has the largest number of diabetic patients in the world. Hence, it is often referred to as the ‘diabetes capital’ of the world. Diabetes is growing alarmingly in India, home to more than 65.1 million people with the disease, compared to 50.8 million in 2010 (International Diabetes Federation, 2015; Kaveeshwar and Cornwall, 2014; Akhtar and Dhillon, 2016). Modal age at death is increasing which ensures a shift in pattern of diseases mainly from acute to chronic

• nes. People are now living longer but are marked by chronic diseases and increasing disability

(Yadav and Arokiasamy, 2012). Many studies/reports give us definite ideas on how the levels of these diseases are increasing. Yet the plaucity of any large scale panel survey made it impossible to understand how these diseases behave in a larger scale of population. At least, it can provide a broader overview of how the diseases are distributed across the population. With that being said, the main objective

• f this paper is to examine the disease pattern of high blood pressure, heart disease and diabetes

across the population in a panel group. We would also endeavour to throw some light on factors influencing the onset and persistence of these diseases in a larger population. Also, there will be a brief overview of the treatment seeking behaviour and expenditure associated with these diseases. Sources of Data Data were taken from India Human Development Survey-I (IHDS-I) (2004-05) and India Human Development Survey-II (IHDS-II) (2011-12). The unit of analysis is individual-level. For the analysis, we have taken 15+ years population in IHDS I under consideration. The total sample size is 99,620 individuals.

3 Variables The head of the household was asked whether any of the family members were having any of the major diseases such as cataract, tuberculosis, high blood pressure, heart disease, diabetes, leprosy, cancer, asthma, polio, paralysis, epilepsy, mental illness, STD/AIDS or any other long term disease. Here, we have focused on high blood pressure, heart disease and diabetes. If a particular individual has a disease, then the dependent variable has been coded as Yes taking a value 1, else 0 if that disease is not present or has been cured. This has been followed in both the time periods. We have taken the 15+ (years) population in IHDS I. For IHDS I, the age groups considered are as follows 15-24, 25-39, 40-59 and 60+ years. Sex is a dichotomous variable comprising

• f male and female. The place of residence is classified as rural and urban. The completed years
• f schooling has been classified as None, till 5th standard, till 10th standard and post 10th
• standard. The marital status comprises of never married, married and widowed/ separated and
• divorced. As per the consumption quintile, individuals are classified as poor, middle and rich.

Religion is composed of Hindu, Muslim and Others. Here, the Others consider Christian, Sikh, Budhhist, Jain and other minorities. The caste variable has been classified as Other Backward Classes (OBC), Scheduled Castes and Scheduled Tribes (SC-STs) and Others including the Brahmins and other Forward castes. Apart from these, consumption of alcohol and tobacco are considered as risk factors for non-communicable diseases. These were also included as covariates in the analyses. These were coded as never, sometimes and daily. The head of the household was asked whether any member of the household was indulged in activities such as chewing tobacco, smoking tobacco or consuming alcohol. The occupation was split into agriculture and non-agriculture. The working hours per day was categorized as working less than 8 hours per day and working more than 8 hours per day. In the first round of IHDS, for presence of diseases, alcohol consumption, tobacco consumption etc were additioanlly categorised as valid blank, valid skip, invalid skip, out of range apart from the usual ues no etc to increase precision of the data presented. This substantially reduced the number of valid cases out of the total cases. However, in the second round, the skipped and missed categories were missing and these were appended to the no cases. For consistency, in the first round all these skipped cases were added to the no cases. Questions pertaining to the treatment/advice taken for the concerned diseases was asked in the last 12 months. If so, it was asked from whom the first treatment/advice was taken from. Here, the treatment/advice seeking behaviour was split into three categories- public comprises of doctors and doctors practising in public and private places, private comprises of private doctors and nurses and others include chemist shop, vaidhya/hakim, witch craft and others. For the major diseases concerned, the expenditure was given for fees of doctors, hospitalization, costs

• f medicines and travel costs in both the time periods have been calculated.

Statistical Approach The prevalence of any disease is defined as all the new and pre-existing cases of a specific disease during a given time interval in the total population at risk during the same time period. Similarly, the incidence of any disease is defined as all the new of a specific disease during a given time interval in the total population at risk during the same time period.

4 In the data structure of IHDS I in order to refine the filtering process, they had distinguished some of the variables among valid blank, valid skip, missing, out of range, no, yes and cured. Thus, this had substantially reduced the valid cases. however, valid blank, valid skip, missing,

• ut of range etc were combined and taken as no cases only. Thus, to maintain parity (and the
• perational definition uses the definition as total population in a group/sub-group), for valid

blank, valid skip, missing, out of range cases in the first round were combined with the no

• cases. This some-how elevated the denominator.

For the present study, the prevalence of a disease is based on all the yes cases in each of the time periods. A disease is said to be incident in the second round if that particular disease was absent in the first round but present in the second round. The prevalence and incidence of the diseases are expressed in percentages ie the total share of a specific disease in the population. Following Hausman test, a random effects logistic model was fit to the data as the dependent variable was dichotomous in nature including both time-variant and time-invariant covariates. The presence of a specific disease was coded as 1, else, if absent, is coded as 0. The regressions were run separately for each disease. Also, three separate models were fited to have a clear understanding of the factors associated with the presence of the diseases. Model 1 is a null model, Model 2 takes into account all the socio-economic and demographic variables (controlled for state variations) and Model 3 also includes some risk factors such as consumption of alcohol, chewing of tobacco, occupation type, working hours per day and presence of high blood pressure (for heart disease and diabetes). Likelihood ratio tests looked for the appropriateness of the fitted models. Mean expenditures for each of the diseases including fees of doctors, hospitalization, costs of medicines and travel costs in both the time periods was calculated. To compare the overall expenditure over time, it was first adjusted to uniform base year (2004-05) and then presented at 2011-12 prices using suitable deflator. Results Prevalence of high blood pressure in the matched cases by selected demographic-socio- economic conditions High blood pressure showed an increase from 1.91% to 5.16% over IHDS I to IHDS II (Table 1). The burden of high blood pressure steadily increased from 0.1 in the age group 15-24 years to 5.95% among the 60+ population in IHDS I. The same population in the age group 22-31 years in IHDS II showed an increase of prevalence of high blood pressure to 0.37 over time. The burden of high blood pressure thoroughly expanded for the 67+ years population showing an increase in prevalence to 12.32%. In both the rounds, the burden of high blood pressure was more among the rich compared to the poor. It varied from 0.72% (in IHDS I) to 2.57% (in IHDS II) among the poor whereas varied from 3.48% to 7.95% among the rich. The population completing education till 5th standard showed the highest prevalence of high blood pressure (2.31). However, the uneducated mass of population showed the highest increase of high blood pressure with a prevalence rate of 5.02% in IHDS II. The urban population showed an increase

• f prevalence of high blood pressure from 3.16% in IHDS I to 7.46% in IHDS II compared to

the rural population showing an increase from 1.49% in IHDS I to 4.11 in IHDS II. The burden

• f high blood pressure was found highest among the widowed/separated/divorced who showed

its increase at a much higher pace than the rest. The least rate of prevalence of high blood pressure was observed among the SC/STs and the pace of increase was also least among them

• ver time. Females were much more prone to high blood pressure than the males.

5 Spatial pattern of prevalence of high blood pressure in IHDS I and IHDS II The state-level distribution of high blood pressure in both the time periods (2004-05 and 2011- 12) are presented in Figure 1. While at the national level, India showed an overall increase of around 3.25% from 1.91 in IHDS I to 5.16% in IHDS II, there exists huge disparities in the distribution of high blood pressure in the states at both the time periods. Pondicherry witnessed the highest prevalence of high blood pressure (7.41%) in IHDS I whereas most of the north eastern states along with Daman and Diu and Dadra and Nagar Haveli exhibited very low prevalence of high blood pressure. In IHDS I, most of the states showed a prevalence percentage of high blood pressure ranging between 0 and 4. Most of the states showing a percent prevalence of high blood pressure of 0-4 showed an increase to 4-10 percent prevalence in IHDS II. While in IHDS II, the percent prevalence of high blood pressure in the category >10 is somewhat tricky. States/Union Territories like Punjab, Sikkim and Chadigarh showed very high increase in prevalence of high blood pressure (ranging from percent prevalence 0-4 in IHDS I to percent prevalence of >10 in IHDS II). Prevalence of heart disease in the matched cases by selected demographic-socio-economic conditions Increase in the prevalence of heart disease in India was noted to vary from 0.65 in IHDS I to 1.27% in IHDS II (Table 1). Like high blood pressure, heart disease also followed an increasing pattern with age. For 40-59 (47-66 years in IHDS II) years age group, it increased from 1.08 to 2.13 compared to the increase of the 60+ (67+ years in IHDS II) which increase to 2.98% in IHDS II from 1.46%. Heart disease had a higher pace of increase for the middle and the rich. The variation of heart disease was quite less among the people with different levels of

• education. However, people studying till 5th standard suffered maximum from heart disease.

The urban population showed an increase in heart disease from 0.93% to 1.77% as compared to the rural population for whom it increased from 0.55% to 1.03%. Muslim were found to bear the burden of heart disease slightly higher than the Others in IHDS I. But, they showed higher increase in heart disease than the Others in IHDS II. Although, Others were found to have the highest burden of heart disease in both the rounds, OBCs witnessed the highest pace of increasing heart disease. Males, however, showed lower levels of heart disease than their counterparts, but heart disease increased in them at a higher pace. Spatial pattern of prevalence of heart disease in IHDS I and IHDS II The state-level distribution of heart disease in both the time periods (2004-05 and 2011-12) are presented in Figure 2. As India showed an increase in the prevalence of heart disease from 0.65% to 1.27% between IHDS I and IHDS at the national level, the states as well displayed wide variations in the prevalence of heart disease. States such as Jammu and Kashmir, West Bengal, Goa, Bihar, Manipur and Kerala experienced a prevalence of heart disease ranging between 0.75 to 2% in IHDS I. Most of the states displayed a prevalence of heart disease ranging between 0.75 to 2% in IHDS I. Jammu and Kashmir, Punjab, and Kerala exhibited a prevalence of heart disease which was >2 % in round II of IHDS. Kerala showed the highest prevalence of heart disease (4.37%) in IHDS II. On the contrary, most of the north-eastern states showed very low prevalence of heart disease in both the time periods. Prevalence of diabetes in the matched cases by selected demographic-socio-economic conditions

6 The prevalence of diabetes increased from 1.05% to 2.95% over IHDS I to IHDS II (Table 1). Diabetes was found to be the highest among 60+ years population in IHDS I (67+ years in IHDS II) followed by 40-59 years population in IHDS I (47-66 years in IHDS II). The rate of increase of diabetes was also highest in these two age groups. The rich bore the highest burden

• f diabetes which increased from 1.84% to 5% over time. Highest prevalence of diabetes was

found among people competing their education post 10th standard. However, people completing their education till 5th standard had slightly little less prevalence of diabetes in IHDS I. The prevalence of diabetes among people completing their education till 5th standard suppressed that of the people competing their education till 10th standard in IHDS II. The urban population were more prone to diabetes than their counterparts in both the rounds. Widowed/Separated/Divorced showed the highest prevalence of diabetes in both the rounds which varied from 3.07% to 4.77% from IHDS I to IHDS II. For the Others, the prevalence of diabetes was the highest. Even the rate of increase of diabetes was much higher for them. In the caste category, the others bore the highest burden of diabetes which increased from 1.37% to 3.98%. For the SC/STs, the prevalence of diabetes increased from 0.54% to 1.5%. The variation of diabetes among males and females was very less in both the rounds. While the prevalence of diabetes in the males increased from 1.1% to 2.98%, for females it increased from 0.99% to 2.91%. Spatial pattern of prevalence of diabetes in IHDS I and IHDS II The state-level distribution of diabetes in both the time periods (2004-05 and 2011-12) are presented in Figure 3. In the first round of IHDS, the southern states/ union territories such as Kerala, Tamil Nadu and Pondicherry displayed high prevalence of diabetes, Kerala showing the highest in round I (4.37%). Most of the norther states and southern states along with parts

• f some north eastern states showed prevalence of diabetes ranging between 2-6% in IHDS II.

Pondicherry showed the highest prevalence of diabetes in round II of IHDS (14.74%) followed by Kerala (14.41%). Incidence of high blood pressure, heart disease and diabetes in the matched cases by selected demographic-socio-economic conditions Table 2 shows the incidence of high blood pressure, heart disease and diabetes in IHDS II by selected demographic-socio-economic conditions. The incidence of all the concerned diseases followed an increasing pattern with increasing age. The incidence rate of high blood pressure varied from 2.36% to 6.98% between the poor and the rich. People who were educated upto 5th standard had the highest incidence of high blood pressure. High blood pressure had a higher incidence among the urban population. Those who were never married showed an incidence of 0.58% as compared to the widowed/separated/divorced showing an incidence of high blood pressure of 9.31%. The incidence of high blood pressure varied from 4.24 among the Hindus to 2.88% among the Muslims to 6.52% among the Muslims. For high blood pressure, SC/STs showed an incidence of 2.88 as compared to Others showing 6.24% and OBCs showing 4.59%. Females (5.71%) exhibited a higher incidence of high blood pressure than males (3.49%). The rich (1.82%) showed a higher incidence of high blood pressure than the poor (0.53%). The incidence of heart disease was highest among people completing their education till 5th

• standard. The incidence of heart disease was lesser in rural population (0.93%) than the urban

population (1.56%). The widowed/separated/divorced had the highest incidence of heart disease of 1.78%. Muslims exhibited the highest incidence of heart disease (1.91%). Others in

7 the caste category witnessed the highest incidence of heart disease (1.63%). A slight difference prevailed between the males and females in the incidence of heart disease. The incidence of diabetes varied from 0.91% among the poor to 4.05 among the rich. The incidence of diabetes was higher among the educated mass than the illiterates. The highest incidence of diabetes was observed among those having studied till 5th standard (3.02%). The urban population showed an incidence of 4.13 as compared to the rural population showing an incidence of 1.65%. The widowed/separated/divorced showed the highest incidence of diabetes

• f 4 as compared to 0.26% among the never married and 2.44% among the married. The Hindus

had an incidence of diabetes of 2.26%; for the Muslims it was 2.98% and for the Others it was highest showing an incidence of 3.7%. The Others in the caste category as well exhibited the highest burden of diabetes showing an incidence of 3.34%. The incidence of diabetes varied a little between males (2.46%) and females (2.39%) in IHDS II. Spatial pattern of incidence of high blood pressure, heart disease and diabetes in IHDS II The incidence of high blood pressure, heart disease and diabetes in IHDS II in the different states of India is displayed in Figure 4. The incidence of high blood pressure, heart disease and diabetes in IHDS II were 4.57%, 1.13% and 2.43% respectively. The highest incidence of high blood pressure was noted in Chandigarh (16.79%). Apart from it, Punjab, Kerala and Sikkim had more than 10% incidence of high blood pressure. The extreme north, most of the southern states, Gujarat and few of the north eastern states of India shoed an incidence of high blood pressure ranging between 4-10%. Kerala exhibited the highest incidence of heart disease in IHDS II (3.78%). Other than Kerala, Jammu and Kashmir, Punjab, NCT of Delhi and Dadra and Nagar Haveli experienced more than 2% incidence of heart disease. The incidence of diabetes in IHDS II was highest in Pondicherry (11.55%) followed by Kerala (11.49%). The incidence of diabetes varied between 2-5% in the states of Jammu and Kashmir, Himachal Pradesh, Punjab, NCT of Delhi, Arunachal Pradesh, Manipur, West Bengal, Karnataka, Goa and Tamil Nadu. Incidence of high blood pressure, heart disease and diabetes in IHDS II based on drinking pattern of alcohol in IHDS I The incidence of high blood pressure, heart disease and diabetes among alcohol drinkers in IHDS I was around 4% ,1.1% and 2.2% respectively. Men who drank occasionally or daily were at higher risks of attaining high blood pressure. However, the bivariate association between drinking alcohol in IHDS I and incidence of heart disease in IHDS II was inconclusive. Those who drank occasionally in IHDS II were more prone to the incidence of diabetes in IHDS II. Incidence of high blood pressure, heart disease and diabetes in IHDS II based on chewing of tobacco in IHDS I The incidence of high blood pressure, heart disease and diabetes among those who chew tobacco in IHDS I was around 3.9% ,0.9% and 1.9% respectively (Figure 6). The habit of chewing tobacco is higher among women. Occasional chewing of tobacco among women seemed more harmful. However, the pattern of chewing of tobacco and incidence of heart disease was ambiguous. Also, the incidence of diabetes was higher among those with the habit

• f occasional chewing of tobacco in IHDS I.

8 Incidence of high blood pressure, heart disease and diabetes in IHDS II based on chewing of tobacco in IHDS I The incidence of high blood pressure, heart disease and diabetes among those who smoke tobacco in IHDS I was around 4.4%, 1.5% and 1.5% respectively (Figure 7). Smoking of tobacco was more among males. Daily smoking habits in IHDS I was associated with higher risk of incidence of high blood pressure, heart disease and diabetes among men. Association between prevalence of high blood pressure, heart disease and diabetes and working hours/day and occupation In most of the occasions, working for >8 hours and prevalence of diseases were positively

• associated. However, the prevalence of high blood pressure for those working <8 hours/day

rose to 3.02% (IHDS I) from 1.25% (in IHDS II) which was higher than the increase for the group working > 8hours/day which changed from 1.37% to 2.89% over time. The increase in the prevalence of heart disease was higher for those working for more than 8 hours/day. This change was in fact higher for diabetes. The prevalence of diabetes in IHDS I for those working for <8 hours/day rose from 0.7% to 1.67% in IHDS II. But, it increased from 1% to 2.54% for those working for more than 8 hours/day over IHDS I and IHDS II (Figure 8). For those engaged in agriculture, the prevalence of high blood pressure increased from 0.86% to 4.68& over IHDS I to II. For those in the non-agricultural sector, it rose from 2.22% to 5.86% over time. The increase of heart disease was also higher for those engaged in non- agricultural sectors over time. The prevalence of diabetes increased from 0.35% to 1.37% for people associated with agriculture while it increased from 1.2% to 3.33% for those engaged in non-agricultural sector over time (Figure 9). Figure 10 shows the change in prevalence of high blood pressure, heart disease and heart disease by working hours per day and by occupation. For people engaged in agricultural sector and working for <8 hours/day, the prevalence of high blood pressure increased from 0.82% to 2.16% as compared to the increase of prevalence of high blood pressure from 1.75% to 4.16% (from IHDS I to IHDS II) for people <8 ours/day in non-agricultural field. The prevalence of heart disease increased more for people engaged in non-agricultural sector than working in the agricultural land. For people engaged in non-agricultural sector and working for >8 hours/day, the prevalence of diabetes increased from 1.19% to 3.5% as compared to the increase of prevalence of diabetes from 1.08% to 2.65% (from IHDS I to IHDS II) for people <8 ours/day in non-agricultural sector. Multivariate association between the prevalence of diseases and demographic, socio-economic and risk factors Table 3 shows the results of multivariate association between the prevalence of the diseases and the covariates. Model 1 is the null model, Model 2 incorporates the demographic and socio- economic variables whole controlling for state. In Model 3, the risk factors such as consumption of alcohol, chewing of tobacco and the presence of high blood pressure (for heart disease and diabetes only) are incorporated. Age was found to be significantly associated with all the three diseases (p<0.001). From the analysis, it was found that females were significantly more likely to suffer from high blood

9 pressure, heart disease and diabetes (p<0.01). The prevalence of all the diseases was positively associated with the completed years of schooling. Compared to the never-married people, currently married people and widowed/separated/divorced people were more likely to bear the burden of the diseases. In the religion category, Muslims had higher odds of suffering from these diseases. However, SC/STs were lesser likely than the OBCs in the caste category to bear the burden of these diseases. But, the others in the caste category had higher risks of suffering from these diseases than the OBCs. The urban population has significant higher odds of suffering from these diseases (p<0.01) than their counterparts in the rural places. Concentrating solely on the risk factors included in Model 3 for each of the diseases, it was found that consumption of alcohol (sometimes or daily) was positively associated with high blood pressure in the multivariate framework. Whatsoever, a negative association was observed between drinking alcohol and the prevalence of heart disease and diabetes (separately). Those who sometimes chew tobacco were at higher risks of having heart disease. People suffering from high blood pressure were about 5 odds times more likely to suffer from heart disease. Consumption of alcohol sometimes was positively linked with diabetes. Much like heart disease, people having high blood pressure were 8 odds times more likely to attain diabetes. Those engaged in non-agricultural sectors were at higher risks of having the concerned

• diseases. Similarly, those who worked more than 8 hours a day had higher likelihood to bear

the burden of high blood pressure and diabetes. The comorbidities of high blood pressure, heart disease and diabetes in IHDS I and IHDS II Out of the total 99620 matched cases in both the rounds of IHDS, 634 (0.65%) had heart disease, 2001 (1.91%) had high blood pressure and 988 (1.02%) had diabetes. Among those who had high blood pressure in IHDS I, 158 (7.9%) of them developed heart disease and 394 (18.09%) developed diabetes. 65 (42.29%) of them developed both heart disease and diabetes in IHDS II. Change in treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes over IHDS I and IHDS II The treatment seeking behaviour from public places have increased from 27.4% to 30.45% for high blood presure and from 26.41% to 29.74% for heart disease over time. However, the treatment seeking behaviour for diabetes from public places decreased from 35.59% to 33.85%. Also, the treatment seeking behaviour for diabetes from private places increased from 59.13% to 61.45% (Figure 12). Figure 13 shows the treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes in IHDS I and IHDS II by place of residence. The treatment/advice seeking behaviour for all the concerned diseases was mostly lesser in rural places than urban places for both the time periods from both public and privtae places. In the rural sector, the treatment/advice seeking behaviour from public sources for high blood pressure increased whereas it decreased from 40.94% (in IHDS I) to 33.26% (in IHDS I) for diabetes. For urban places, the treatment seeing behaviour from private places for high blood pressure and diabetes declined whereas for heart disease, it increased from 63.32% to 66.47% over time. Figure 14 shows the treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes in IHDS I and IHDS II by sex. A mixed pattern was observed in the treatment seeking behaviour for the concerned disease for male and female over time. It was found that

10 the treatment seeking behaviour from private places for high blood pressure declined for both male and female over time. However, the treatment seeking behaviour from public places for high blood pressure increased from 26.92% to 32.79% over time for men. The tendency to seek treatment/advice from private places for heart disease for men increased from 62.03% to 64.95% over time. On the contrary, the same declined for women from 70.34% (in IHDS I) to 66.06% (in IHDS II). For diabetes, the treatment/advice seeking behaviour from private places increased from 55.23% (in IHDS I) to 63.03% (in IHDS II). However, for female it declined from 63.69% to 59.77% over time. But, the treatment seeking behaviour from public places for women increased to 35.82% (in IHDS I) from 30.13% (in IHDS I). Expenditure incurred for high blood pressure, heart disease and diabetes The mean expenditure incurred for high blood pressure increased from INR 5752.11 (in IHDS I) to INR 10151.06 (in IHDS II); for heart disease it changed from INR 12266.77 to INR 23909.37 over time; and for diabetes it rose INR 8110.04 in IHDS I to INR 11673.42 in IHDS II (Table 4). The mean expenditure for all the concerned diseases was highest for the 60+ (years) population in IHDS I (67+ years in IHDS II). Also, the relative percent increase for high blood pressure was highest among the 60+ population (in IHDS I). However, the relative percentage increase was highest among 40-59 yrs population (in IHDS I) and was highest among the 25-39 years population (in IHDS I) for diabetes. The mean expenditure incurred by the men was higher than women for all the concerned diseases. The rural poulation had a higher mean expenditure for heart diseases with a relative percent increase of 109.9% changing from INR 12005.6 in IHDS I to INR 25195.31 in IHDS II. The others in the religion category had the highest increase in mean expenditure for high blood pressure (from INR 6204.433 in IHDS I to INR 12938.83 in IHDS II). Although the mean expenditure for heart disease and diabetes as well was highest among the others in the religion category, the relative increase (in percentage) was highest among the Hindus. For all the concerned diseases, the amount incurred by the others in the caste category was highest. The relative increase in mean expenditure for high blood pressure and heart disease was highest among the OBC. Those completing their education till 10th standard had to bear the highest relative increase in mean expenditure for high blood pressure and heart disease. Although the mean expenditure for all the concerned diseases was highest among the rich section, the relative increase in cost for heart disease was highest for the poor. For all the concerned, the mean expenditure in the private places was much higher than the public or other places. Nevertheless, for both heart disease and diabetes, the relative increase in mean expenditure over time was highest in the public places. Discussion and Conclusion This paper aimed at providing with an overall situation of the increasing pattern of high blood pressure, heart disease and diabetes in India. The increasing trends and patterns of the aforesaid diseases have been studied in the light of a panel data which offers a scope to examine the evolving nature of the diseases in the same population. The prevalence of non-communicable diseases along with their potential risk factors are escalating due to rapid development, changing nature of life style and spread of urbanization (Khan et al., 2013; Yach, 2004). Many of the findings are well anticipated but the essence lies in the fact that it has been studied at a panel structure. All are well versed with the fact that the onset of non-communicable diseases advents with increasing age (Llyod-Sherlock et al., 2014; Naseem et al., 2016; Fatema et al., 2016). Most studies in developing countries have reported direct (positive) or no associations between SES and blood pressure. Although a number of studies have reported

11 negative relationship (Dressler, 1992; Colhoun and Poulter, 1998; Gupta, 1999; Addo et al., 2009; Ghosh et al., 2013; Garg et al., 2014; Bansal et al., 2012). Tenkorang and Kuuire (2016) showed that a negative relationship exists between SES and the risks of living with non- communicable diseases. Reddy et al. (2002) found that higher SES groups have greater prevalence of coronary heart disease than lower SES groups. Few studies, if any, have explicitly examined whether relationships are non-linear, or examined joint effects of income and education. The prevalence of high blood pressure and other non-communicable diseases increases with age which is somewhat a treatable risk factor for other morbidities such as stroke, ischaemic heart disease, renal failure and even dementia (Steyn et al., 2005; Ferri et al., 2011). A premature onset of non-communiacble disease is evinced by the nation. A higher burden of the diseases of high blood pressure, heart disease and diabetes were found more among the women than the men. A recent study by Patra and Bhise (2016) examined the current scenario of the self-reported prevalence of non-communicable diseases In India and states and pointed out that women are more susceptible to non-communicable diseases than men. Also, women are more susceptible to hypertension (Kusuma et al. 2004, Schall, 1995). Hinduism is the most followed religion in India. The socio-economic inequalities ascribed to caste system among the Hindus is quite prevalent till date. The others comprising of the Brahmins and other Forward castes in the caste category were found to bear the highest burden

• f the concerned diseases. This calls for a social gradient to health in the Indian scenario which

implies that people’s state of health is dependent on their social status (Borooah, 2012) in terms

• f caste and religion. The SC/STs were found to have lesser burden of these diseases. Since,

they are not so privileged, it might happen that the diagnosis and awareness regarding these diseases is lesser in them (Negi et al., 2016). There is a consistent inverse relationship between cardiovascular diseases, especially coronary heart disease and various dimesions of socio economic status (Pearson, 1999; Singh et al., 2000). The principal measures of socio-economic status have been education, income, occupation and the combination of these. It was found that people educated upto primary section were at the maximum risk of suffering from all the diseases than the uneducated mass or peole completing their education till and post 10th

• standard. Wang et al. (2006) found out that lower level of education was associated with higher

risk of hypertension in the urban population. They argued that education, may, in part, exert its influence through lifestyle and dietary habits. On the contrary, lower levels of education may be associated with not only unhealthy diet, but a lack of consistent and meaningful physical activity accompanied by increased consumption of alcohol. It is also possible that increased educational level is associated with increased awareness, treatment, and control of

• hypertension. People completing more levels of education tend to have higher income, live in

a safer environment with greater access to quality fruits and vegetables. However, the inverse relationship between education and disease-pattern is quite obscure. Higher paid jobs come handy with more tension, stress which severely affect the health. These might impel individuals to develop risky behaviours such as smoking and alcohol consumption. Nevertheless, whether years of education or quality education act as a matter of fact for health status cannot be judged. The levels of hypertension were elevated in low and high income groups (Miranda et al., 2008) found that. They also found that low income was associated with reduced awareness, treamtent and control in males and females. Although, alcohol and tobacco consumption are treated as harmful and risky for the commencement of non-communicable diseases. In the present study the relationship between consumption of alcohol and tobacco and the disease pattern is rather inconclusive. Several studies found a negative relationship between alcohol drinking and the risk of coronary heart disease but whether any specific type of alcohol drink has a particular benefit is difficult to

12 judge (Moore et al., 1986; Rimm et al., 1996; Corrao et al., 2004). In a large scale population survey, smokers showed the lowest prevalence of hypertension (Bolinder et al., 1992). Moderate alcohol drinking was found to be associated with a decreased incidence of diabetes mellitus and a decreased incidence of heart disease in persons with diabetes (Howard et al., 2004; Koppes et al., 2005). Taylor et al. (1992) concluded that smoking tobacco increases the risk of heart diseases. However, Critchley et al. (2004) from a systematic review concluded about a plausible connection between smokeless tobacco and heart disease. Smoking of tobacco could be more severe compared to smokeless tobacco consumption (Bolinder et al., 1994). Cross-sectional studies cannot establish the causality effect. However, longitudinal studies do have that scope to look for causality effects. The present study, although is a panel study could not establish the proper relationship between indulging in these risky behaviours and the incidence of the concerned diseases. This could happen due to some confounding effects due to omission of certain potential characteristics and interaction effect which couldn’t be

• measured. Also, a lapse of seven years could be too less to assess anything about the incidence
• f any of the concerned diseases without any proper surveillance (as in the case control studies,

clinical trials etc) in a country where a large section of the population is not well equipped or knowledgable about diseases and go for regular checkups and diagnosis of diseases. The treatment/advice seeking behaviour, on an average, remained same in both the rounds. However, mixed patterns were noted in the treatment seeking behaviour by sex and by place

• f residence. The mean expenditure increased for all the diseases taken in the study. However,

the financial burden was more among the less privileged masses. Like any other studies based on survey data, this study too has certain limitations. The individuals interviewed for the purpose are subject to recall bias or rendering socially desirable

• answers. Body mass index, a very potential risk factor for any non-communiacble disease could

not be used in the analysis because anthropometric measures were collected only from ever- married women in the age group 15-49 years, children under age 5 years and between 8 to 11 years in IHDS I and from ever-married women in the age group 15-49 years, children between ages 0 to 18 years and heads of the households. The heads of the households being asked the questions about the prevalence of morbidity among household members could be under

• reported. The answers of heads of the households were taken as proxies for the patterns of

drinking alcohol and consuming tobacco each of the household members. In Indian settings, these behaviours are viewed as taboos to many, so the heads of the households might not be well informed about these behaviours especially about the young people and hence be under

• reported. The definitions used for the diseases could suffer from non-uniformity as the

questions were asked only for the presence of the diseases and no defined measurement could be incorporated. High blood pressure could be anything above the minimum, its severity could not be measured, heart disease simimarly could be anything varying from coronary heart disease, ischaemic heart disease etc and diabetes could be type1 or 2 in nature. Environmental factors and eating practices affecting these diseases were absent in the data. Policy recommendations From policy point of view, this paper might be useful as it provides a brief overview of three major non-communicable diseases viz. high blood pressure, heart disease and diabetes in India from a panel data. A better understanding of pathways relating the emergence of non- communicable diseases and socio-economic environment is essential for designing and targeting interventions to reduce/control the rapid spread of these diseases in the country.

13 Finally, the prevalence of high blood pressure in India has risen dramatically in recent years, further increases are anticipated with improvements in life expectancy and continued

• development. Since, it is one of the root causes of many of the non-communicable diseases,

effective primordial prevention is needed to mitigate this growing epidemic. This study underscores the need for policies targeted at specific socio-economic groups such as the poor and middle classes, the SC/STs, the OBCs and other religious minorities. It is also important for the interventions to move beyond biomedical solutions which put more emphasis on epidemiological risk factors to strategies that are psychosocial-oriented. There is an urgent need for launching community health education activities for creating awareness about health risk behaviours and their health consequences. People should be made aware of the importance of measuring blood pressure and blood glucose periodically. The primary health care services should be strengthened for opportunistic screening for high risk groups and their evidence based management. There should be initiatives to make the treatment system more pocket- friendly for the not-so-privileged sections of the population. Reference Addo, J., Smeeth, L., & Leon, D. A. (2009). Socioeconomic position and hypertension: a study

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World Health Organization. (2015). WHO report on the global tobacco epidemic 2015: raising taxes on tobacco. World Health Organization. Yach, D., Corinna, H., Linn, G. C., & Hofman, K.J. (2004). The global burden of chronic diseases: overcoming impediments to prevention and control. JAMA J Am Med Assoc., 291(21),2616–22. Yadav, S., & Arokiasamy, P. (2014). Understanding epidemiological transition in India. Global health action, 7. Appendix 1 Table 1: Prevalence of high blood pressure, heart disease and diabetes in IHDS-I (2005) and IHDS-II (2011-12) by selected demographic-socio-economic conditions

17

Background variables Diseases high bp (IHDS I) high bp (IHDS II) heart disease (IHDS I) heart disease (IHDS II) diabetes (IHDS I) diabetes (IHDS II) Age (in years) 15-24 (22-31) 0.1 0.37 0.14 0.18 0.01 0.14 25-39 (32-46) 0.76 3.18 0.35 0.73 0.3 1.41 40-59 (47-66) 3.13 8.64 1.08 2.13 1.75 5.58 60+ (67+) 5.95 12.32 1.46 2.98 3.66 6.57 MPCE Poor 0.72 2.57 0.26 0.58 0.36 1.06 Middle 1.53 4.97 0.53 1.16 0.94 2.79 Rich 3.48 7.95 1.16 2.06 1.84 5 Completed years of education None 1.75 5.02 0.63 1.2 0.76 2.01 Till 5th Standard 2.31 6.38 0.73 1.7 1.28 3.75 Till 10th Standard 1.88 5.12 0.66 1.25 1.15 3.51 Post 10th Standard 1.95 4.29 0.57 1.01 1.38 3.29 Place of Residence Rural 1.49 4.11 0.55 1.03 0.82 1.99 Urban 3.16 7.46 0.93 1.77 1.73 5.04 Marital Status Never married 0.11 0.62 0.19 0.24 0.07 0.33 Married 2.01 4.88 0.69 1.27 1.06 2.98 Widowed/Separate d/Divorced 4.86 10.59 1.21 2.02 3.07 4.77 Religion Hindu 1.81 4.78 0.63 1.12 1.01 2.76 Muslim 2.07 6.73 0.77 2.12 0.89 3.51 Others 3.11 7.53 0.73 1.64 1.96 4.55 Caste OBC 1.84 5.15 0.58 1.18 1.16 3.22 SC ST 1.14 3.19 0.37 0.76 0.54 1.5 Others 2.77 7.13 1.01 1.89 1.37 3.98 Sex Male 1.37 3.86 0.49 1.22 1.1 2.98 Female 2.47 6.51 0.82 1.31 0.99 2.91 Total 1.91 5.16 0.65 1.27 1.05 2.95

Table 2: Incidence of high blood pressure, heart disease and diabetes in IHDS-II (2011-12) by selected demographic-socio-economic conditions

Background variables high bp heart disease diabetes Age (in years) 15-24 (22-31) 0.36 0.18 0.14 25-39 (32-46) 3 0.67 1.24

18

40-59 (47-66) 7.71 1.91 4.62 60+ (67+) 10.64 2.53 5.18 MPCE Poor 2.36 0.53 0.91 Middle 4.44 1.04 2.34 Rich 6.98 1.82 4.05 Completed years of education None 4.54 1.08 1.74 Till 5th Standard 5.53 1.57 3.02 Till 10th Standard 4.49 1.08 2.83 Post 10th Standard 3.8 0.88 2.69 Place of Residence Rural 3.71 0.93 1.65 Urban 6.5 1.56 4.13 Marital Status Never married 0.58 0.2 0.26 Married 4.36 1.14 2.44 Widowed/Separated/Divorced 9.31 1.78 4.00 Religion Hindu 4.24 1 2.26 Muslim 5.98 1.91 2.98 Others 6.52 1.43 3.7 Caste OBC 4.59 1.07 2.57 SC ST 2.88 0.71 1.29 Others 6.24 1.63 3.34 Sex Male 3.49 1.1 2.46 Female 5.71 1.16 2.39 Total 4.57 1.13 2.43

Table 3: Results of logistic regression (random effects) with the prevalence of high blood pressure, heart disease and diabetes and diabetes as the dependent variables

Backg round variab les High blood pressure Heart disease Diabetes Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Odds ratio (Robust SE) Const ant 0.035***(0.0 07) 0.0002 0.0001***(0. 0001) 0.009***(0.0 03) 0.002***(0.0 0007) 0.0004***(0. 00004) 0.18***(0.00 4) 0.00003***(. 0000105) .00003***(.0 0003) Age 2.63***(0.13 5) 2.59***(0.21 7) 2.23***(0.07 1) 1.72***(0.242) 3.04***(0.25 3) 2.58***(0.29 7) Sex Male 1 1 1 1 1 1 Femal e 1.9***(0.022 ) 2.73***(0.49 9) 1.15***(0.05 8) 1.77*(0.577) 1.17***(0.01 3) 1.36(0.432) Completed years of education None 1 1 1 1 1 1

19

Till 5th Standard 1.53***(0.01 ) 1.25(0.192) 1.35***(0.89 ) 1.1(0.279) 1.75***(0.99 0) 1.83***(0.40 7) Till 10th Standard 1.46***(0.58 ) 1.51***(0.21 9) 1.2***(0.078 ) 1.09(0.271) 2.06***(0.23 3) 2.45***(0.52 0) Post 10th Standard 1.37***(0.56 ) 2.04***(0.36 3) 1.87(0.236) 1.26(0.402) 2.04***(0.24 7) 4.1***(0.994 ) Marital Status Never married 1 1 1 1 1 1 Marrie d 3.49**(0.316 ) 2.12(1.245) 2.19***(0.34 9) 1.46*(0.622) 3.48***(0.06 1) 1.64(1.181) Widowed/Separated/Di vorced 3.63***(1.07 8) 2.49***(1.54 2) 2***(0.352) 1.48(1.669) 3.02***(0.16 6) 2.24(1.744) Religi

• n

Hindu 1 1 1 1 1 1 Musli m 1.5**(0.316) 1.37*(0.230) 1.73***(0.11 1) 0.88(0.270) 1.48***(0.65 ) 1.01(2.419) Others 1.58***(0.03 4) 0.953(0.191) 1.33***(0.10 5) 0.61(0.283) 1.68***(0.04 0) 0.867(0.234) Caste OBC 1 1 1 1 1 1 SC/ST 0.85***(0.02 4) 1.03***(0.12 7) 0.84**(0.058 ) 0.69*(0.151) 0.76***(0.01 9) 0.97(0.277) Others 1.14***(0.00 8) 1.486***(0.1 88) 1.23***(0.06 5) 1.25(0.273) 1.06(0.043) 1.23(0.201) Place of Residence Rural 1 1 1 1 1 1 Urban 1.59***(0.03 ) 1.36***(0.15 8) 1.53***(0.07 5) 1.01*(0.211) 1.79***(0.05 0) 1.26**(0.185 ) Consumption quintile Poor 1 1 1 1 1 1 Middl e 1.7***(0.017 ) 2.18***(0.33 3) 1.8***(0.127 ) 1.73**(0.426) 1.92***(0.03 1) 1.32(0.277) Rich 2.58***(0.28 5) 3.66***(0.56 4) 2.88***(0.21 4)) 2.41***(0.618) 3.07***(0.17 5) 2.3***(0.469 ) Consumption of alcohol Never 1 1 1 Somet imes 1.21*(0.140) 0.81(0.169) 0.85(0.128) Daily 1.48**(0.243 ) 0.98(0.294) 0.59**(0.155 ) Chewing of tobacco Never 1 1 1 Somet imes 0.81(0.148) 1.13(0.322) 0.66*(0.162) Daily 0.77***(0.08 4) 0.669(0.131) 0.622***(0.0 90) Having BP No

• 1

1 Yes

• 4.99***(1.273)

8.03***(1.37 ) Occupation Agricu lture 1 1 1 Non-agriculture 1.18(0.156) 1.33(0.297) 2.01***(0.39 5) Working hours/day <8 hours 1 1 1 >8 hours 1.03(0.141) 0.72(0.196) 1.34*(0.222)

Note: ***, **, ** imply p<0.01, p<0.05 & p<0.1 respectively. Models 2 & 3 controlled for state.

Table 4: Mean expenditure (in INR) for high blood pressure, heart disease and diabetes by selected demographic and socio-economic characteristics

20

Background variables mean expenditure for high blood pressure (in INR) mean expenditure for heart disease (in INR) mean expenditure for diabetes (in INR) IHDS I IHDS II Relative % increase IHDS I IHDS II Relative % increase IHDS I IHDS II Relative % increase Age (in years) 15-24 (22-31) 2797.23 5337.32 90.8 7306.63 15673.68 114.5 4974.54 8475.94 70.4 25-39 (32-46) 3887.51 7125.76 83.3 9035.865 18353.48 103.1 6132.33 11947.52 94.8 40-59 (47-66) 5964.2 10624.79 78.1 11440.17 24680.84 115.74 7444.78 11351.96 52.5 60+ (67+) 6327.96 12313.82 94.6 17610.25 28342.65 60.9 9315.0 12527.1 34.5 Sex Male 6065.37 13114.47 116.2 15274.6 29913.68 95.8 8401.09 12171.55 44.9 Female 5570.16 8330.23 49.6 10395.72 18138.02 74.5 7770.56 11144.77 43.4 Place of Residence Rural 6073.08 10657.86 75.5 12005.6 25195.31 109.9 9384.18 14137.56 50.7 Urban 5300.12 9540.84 80.0 12731.79 22270.54 74.9 6312.17 9542.75 51.2 Religion Hindu 5673.23 9882.79 74.2 12113.32 24678.46 103.7 7367.55 11075.41 50.3 Muslim 5919.15 9898.62 67.2 10077.56 19650.14 95.0 8500.59 11693.28 37.6 Others 6204.433 12938.83 108.5 18994.73 26994.84 42.1 13434.49 16671.97 24.1 Caste OBC 4645.21 10794.28 132.4 9184.484 25620.1 178.9 7043.9 10822.8 53.6 SC/ST 5733.07 7658.94 33.6 10087.81 21648.88 114.6 5634.60 13064.81 131.9 Others 6878.22 10607.61 54.2 15779.8 23377.97 48.1 10490.38 13064.81 24.5 Completed years of education None 5080.1 8459.59 66.5 10005.64 22580.1 125.7 7642.71 11033.47 44.4 Till 5th Standard 6445.02 7800.97 21.0 12083.1 22572.07 86.8 9272.85 11171.11 20.5 Till 10th Standard 5939.38 13724.32 131.1 12137.65 25253.4 108.1 7685.5 12142.14 58.0 Post 10th Standard 6104.24 10577.4 73.3 20391.57 26917.21 32.0 8372.39 12269.69 46.5 Consumption quintile Poor 2666.75 3422.92 28.4 4047.34 12247.34 202.6 5669.07 6158.49 8.6 Middle 3780.65 6821.97 80.4 6325.87 13659.4 115.9 5387.37 7853.96 45.8 Rich 7257.4 14412.75 98.6 16806.15 32982.48 96.2 9980.9 14955.23 49.8 Place of treatment Public 4813.61 7395.81 53.6 10957.3 24056.65 119.55 7306.04 10641.17 45.7 Private 6667.31 12280.86 84.2 13585.68 25092.47 84.7 9088.98 12672.11 39.4 Others 2560.66 4479.58 74.9 6517.11 8195.77 25.76 4557.06 5176.59 13.6 Total 5752.11 10151.06 76.5 12266.77 23909.37 94.91 8110.04 11673.42 43.9

21

22 Appendix 2

23

24 Figure 5: Incidence of high blood pressure, heart disease and diabetes in IHDS II based on the pattern of consumption of alcohol in IHDS I Figure 6: Incidence of high blood pressure, heart disease and diabetes in IHDS II based on the pattern of chewing of tobacco in IHDS I

3.8 5.3 1.2 1.3 3.0 3.0 4.5 4.4 1.0 1.0 3.4 3.6 4.1 4.0 1.1 1.1 2.1 2.2 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Male Total Male Total Male Total High blood pressure Heart disease Diabetes Never Sometimes Daily

4.0 6.5 5.4 1.3 1.3 1.3 3.2 3.0 3.1 4.3 7.9 5.0 1.6 1.3 1.6 3.4 3.2 3.4 3.3 6.0 3.9 0.9 1.1 0.9 2.0 1.6 1.9

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Male Female Total Male Female Total Male Female Total High blood pressure Heart disease Diabetes Never Sometimes Daily

25 Figure 7: Incidence of high blood pressure, heart disease and diabetes in IHDS II based on the pattern of Smoking of tobacco in IHDS I Figure 8: Change in prevalence of high blood pressure, heart disease and diabetes in IHDS I and IHDS II by working hours per day Figure 9: Change in prevalence of high blood pressure, heart disease and diabetes in IHDS I and IHDS II by occupation

3.7 6.6 5.4 1.12 1.2 1.1 1.2 4.0 7.9 4.2 1.2 1.2 1.2 1.2 4.4 4.5 4.4 1.5 1.5 1.5 1.5 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Male Female Total Male Total Male Total High blood pressure Heart disease Diabetes Never Sometimes Daily 1.25 3.02 0.5 0.72 0.7 1.67 1.37 2.89 0.42 0.81 1 2.54 0.5 1 1.5 2 2.5 3 3.5 IHDS 1 IHDS 2 IHDS 1 IHDS 2 IHDS 1 IHDS 2 High blood pressure Heart disease Diabetes <8 hours >8 hours 0.86 4.68 0.39 0.75 0.35 1.37 2.22 5.86 0.74 1.29 1.2 3.33 1 2 3 4 5 6 IHDS 1 IHDS 2 IHDS 1 IHDS 2 IHDS 1 IHDS 2 High blood pressure Heart disease Diabetes Agriculture Non-agriculture

26 Figure 10: Change in prevalence of high blood pressure, heart disease and diabetes in IHDS I and IHDS II classified by occupation and working hours per day

0.82 1.75 2.16 4.16 0.4 0.55 0.47 1.07 0.34 1.08 1.06 2.65

1.19 1.47 1.87 3.75 0.29 0.5 0.59 0.95 0.51 1.19 1.39 3.5

0.5 1 1.5 2 2.5 3 3.5 4 4.5 IHDS 1 IHDS 1 IHDS 2 IHDS 2 IHDS 1 IHDS 1 IHDS 2 IHDS 2 IHDS 1 IHDS 1 IHDS 2 IHDS 2 agri non-agri agri non-agri agri non-agri agri non-agri agri non-agri agri non-agri High blood pressure Heart disease Diabetes <8 hours >8 hours

3.25%)

27 Figure 12: Treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes in IHDS I and IHDS II Figure 13: Treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes in IHDS I and IHDS II by place of residence Figure 14: Treatment/advice seeking behaviour for high blood pressure, heart disease and diabetes in IHDS I and IHDS II by sex

27.4 30.45 26.41 29.74 35.59 33.85 65.02 61.76 67.17 65.52 59.13 61.45 3.52 2.91 3.46 1.3 2.95 2.11 10 20 30 40 50 60 70 IHDS 1 IHDS 2 IHDS 1 IHDS 2 IHDS 1 IHDS 2 High blood pressure Heart disease Diabetes Public Private Others 27.91 26.67 31.37 29.35 22.78 32.87 29.9 28.03 40.94 28.03 33.26 34.37 63.68 66.91 59.74 64.19 69.33 63.32 66.13 66.47 53.94 66.47 61.52 61.38 4.03 2.81 2.74 3.11 4.19 2.16 0.18 2.74 2.36 3.8 1.74 2.42 10 20 30 40 50 60 70 Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban IHDS 1 IHDS 2 IHDS 1 IHDS 2 IHDS 1 IHDS 2 High blood pressure Heart disease Diabetes Public Private Others 26.92 27.68 32.79 29.02 31.6 23.17 31.53 28.02 40.27 30.13 32 35.82 64.59 65.27 60.05 62.81 62.06 64.95 66.06 55.23 63.69 63.03 59.77 3.53 3.52 2.78 2.99 2.44 4.1 0.86 1.73 2.41 3.58 2.38 1.81 10 20 30 40 50 60 70 Male Female Male Female Male Female Male Female Male Female Male Female IHDS 1 IHDS 2 IHDS 1 IHDS 2 IHDS 1 IHDS 2 High blood pressure Heart disease Diabetes Public Private Others

28 Appendix 3 Table 3a: State-wise prevalence of high blood pressure, heart disease and diabetes in IHDS-I (2005) and IHDS-II (2011-12)

State Diseases high bp (IHDS I) high bp (IHDS II) heart disease (IHDS I) heart disease (IHDS II) diabetes (IHDS I) diabetes (IHDS II) Jammu & Kashmir 4.37 9.55 1.72 3.41 0.86 3.2 Himachal Pradesh 1.83 8.13 0.74 1.66 0.6 2.65 Punjab 2.88 11.26 0.66 2.37 0.91 4.3 Chandigarh 3.52 18.31

• 1.41

2.82 8.45 Uttaranchal 0.7 3.94 0.39 1.44 0.42 1.98 Haryana 0.49 3.79 0.17 1.35 0.2 2.4 Delhi 2.88 6.09 0.64 2.29 0.78 4.28 Rajasthan 1.22 4.18 0.29 0.88 0.27 1.1 Uttar Pradesh 0.51 3.4 0.6 1.46 0.31 1.55 Bihar 1.72 3.22 1.23 1.03 0.6 1.75 Sikkim

• 14.11
• 0.14

0.59 4.38 Arunachal Pradesh

• 1.29
• 0.25
• 2.07

Nagaland

• 0.45
• Manipur

1.91 5.57 1.91

• 2.9

3.78 Mizoram 0.51

• Tripura
• 2.72

0.52 0.42 1.27 1.85 Meghalaya 0.22 0.27 0.22

• 0.22
• Assam

0.03 7.33 0.03 1.03 0.35 1.81 West Bengal 3.17 5.75 1.26 1.78 1.01 2.6 Jharkhand 1.37 1.09 0.26 0.48 0.6 1.22 Orissa 2.46 4.84 0.15 0.34 0.56 1.79 Chhattisgarh 0.61 3.3 0.17 0.8 0.53 2.22 Madhya Pradesh 0.64 4.17 0.18 1.25 0.21 1.62 Gujarat 0.34 4.88 0.65 0.96 0.89 2.79 Daman & Diu

• 0.85

0.56

• 0.97

1.99 Dadra & Nagar Haveli

• 7.92
• 2.8
• 5.84

Maharashtra 1.32 3.76 0.41 0.56 0.52 1.42 Andhra Pradesh 3.83 6.26 0.72 1.38 1.39 2.33 Karnataka 1.58 5.98 0.62 1 0.76 4.14 Goa 6 3.68 1.05 0.63 2.84 2.74 Kerala 7.07 16.22 1.39 4.37 5.57 14.41 Tamil Nadu 3.37 6.21 0.92 1.03 4.13 7.81 Pondicherry 7.41 11.18 0.7

• 5.34

14.74 Total 1.91 5.16 0.65 1.27 1.05 2.95 Note: ‘-‘ implies very low.

29 Table 3b: Incidence of high blood pressure, heart disease and diabetes in IHDS II

State high bp heart disease diabetes Jammu & Kashmir 8.41 3 2.82 Himachal Pradesh 7.39 1.43 2.17 Punjab 10.14 2.19 3.61 Chandigarh 16.79 1.41 7.25 Uttaranchal 3.68 1.24 1.65 Haryana 3.65 1.27 2.28 Delhi 5.77 2.06 4.24 Rajasthan 3.64 0.8 0.9 Uttar Pradesh 3.32 0.14 1.42 Bihar 2.81 0.25 1.37 Sikkim 14.11 0.14 4.38 Arunachal Pradesh 1.29 0.25 2.07 Nagaland 0.45

• Manipur

5.67

• 3.65

Mizoram

• Tripura

2.72 0.42 1.21 Meghalaya 0.27

• Assam

7.33 1.03 1.81 West Bengal 4.84 1.58 2.11 Jharkhand 0.99 0.46 1.06 Orissa 4.01 0.31 1.42 Chhattisgarh 2.78 0.7 1.81 Madhya Pradesh 3.85 1.17 1.43 Gujarat 4.78 0.84 2.4 Daman & Diu 0.85

• 0.86

Dadra & Nagar Haveli 7.92 2.8 5.84 Maharashtra 3.47 0.49 1.27 Andhra Pradesh 5.33 1.21 1.96 Karnataka 5.45 0.94 3.72 Goa 3.8 0.63 2.65 Kerala 13.47 3.78 11.49 Tamil Nadu 5.23 0.91 5.84 Pondicherry 8.6

• 11.55

India 4.57 1.13 2.43 Note: ‘-‘ implies very low.