Introduction:
Globally, due to improvement in the standard of living of people, there is a trend towards an increase in non-communicable diseases and a paradigm shift is seen from the rise in communicable diseases to a rise in modern lifestyle diseases. The global prevalence of raised blood pressure in adults aged 18 years and over was around 22% in 2014.[1] In general, the prevalence of raised blood pressure was higher in low-income countries compared to middle-income and high-income countries.[1] The worldwide prevalence of obesity nearly doubled between 1980 and 2014.[1] In 2014, 11% of men and 15% of women worldwide were obese.[1] Thus, more than half a billion adults worldwide are classed as obese.[1] The global prevalence of diabetes was estimated to be 9% in 2014.[1]
Apart from the well-known risk factors of non-communicable diseases (NCDs), social determinants like occupational stress, education, etc. have recently been studied and found to be significantly associated with the occurrence of NCDs.[2–6] There are a very few published research on the social determinants of non-communicable diseases in urban slums of Gujarat. This study was conducted to gauge the magnitude of social determinants of diabetes and hypertension in an urban slum of Gujarat.
Methods:
Study design and setting: This was a cross-sectional study conducted in an urban slum, which is the field practice area of Urban Health Training Centre (UHTC) of Department of Community Medicine of Government Medical College Bhavnagar (Gujarat, India). UHTC of our department caters to a population of approximately 30000 with around 1500 households. The population belongs to low to middle socio-economic class with daily wage labor as their main occupation.
Study period: The study was carried out for 6 months from December 2015 to May 2016.
Sample size: Sample size of 251 was calculated with the help of Open Epi software version 2.2[7] considering 20.52% as the prevalence of diabetes in Gujarat as per the National Health Profile of India in 2015.[8]
Inclusion criteria: All patients above 18 years of age, suffering from either diabetes or hypertension (already diagnosed and taking medicines for these diseases), and giving written informed consent to participate in the study were included.
Exclusion criteria: Patients having both diabetes, as well as hypertension, were excluded from the study.
Sampling and selection of subjects: Non-communicable disease NCD clinic is being run in UHTC of our department on every Tuesday and Friday at 4-6 PM. A line-list of all 723 patients registered in the NCD clinic was prepared, which served as our sampling frame. A random sample of 251 was selected from our sampling frame by Simple Random Sampling using random numbers created with the help of Open Epi software version 2.2.[7]
The investigators then visited the patients at their home at the addresses obtained from the register. The patients were then interviewed and the questionnaire was filled up. Anthropometry (height, weight, waist circumference and hip circumference) was performed during the home visits.
Data collection: The data collection tool consisted of a pre-tested questionnaire with socio-demographic information, risk factors of non-communicable diseases and information regarding the lifestyle of the participants. The questionnaire was validated by face validity and content validity methods. The questionnaire was filled up by personal interview method.
Anthropometry method: Anthropometry was performed during the home visits of the study participants after taking written informed consent. The waist circumference and hip circumference was measured as per the World Health Organization’s consultation report.[9] The measure of waist circumference was made at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest (at the end of a normal expiration).[9] The hip circumference was measured around the widest portion of the buttocks.[9] The participant was made to stand with arms at the sides, feet positioned close together, and weight evenly distributed across the feet.[9] Height and weight were measured as per World Health Organization’s STEPS protocol.[10] Height was measured using a portable length board asking the study participants to remove their footwear and headgear; keeping their feet together, heels against the backboard, knees straight and asking the participants to look straight ahead.[10] Weight was measured using a portable adult weighing scale after asking the study participants to remove footwear, standing still, facing forward and placing their arms on their side.[10]
Anthropometric classifications: Obesity was calculated with the help of Body Mass Index (weight in kilograms divided by square of height in meters). Obesity was classified as per the BMI classification for South Asians as follows: normal 18-22.9; overweight 23-24.9 and obesity >25.[11] Abdominal obesity was classified based on waist circumference and waist-hip ratio. Abdominal obesity was said to be present when waist circumference was >90 cm among men and >80 cm among women.[11] For waist-hip ratio, abdominal obesity was said to be present when it was >0.9 for men and >0.8 among women.[12]
Statistical analysis: Data was entered and analyzed using Epi Info software version 7.1.4.0.[13] Simple proportions were calculated. Non-parametric chi-square also called as 2x1 contingency table analysis was applied to find out the difference between percentages within each variable. It has to be noted that 2x1 contingency chi-square is based on the assumption that the expected frequencies of each variable are 50% of the total.[14] It is a statistical test used to test the difference between percentages, with the higher percentage being significant. The difference was said to be significant when p-value <0.05.
Ethical considerations: Ethical approval from the Institutional Review Board of a medical college in the western part of India was obtained prior to conducting the study. Informed written consent was taken from all the patients agreeing to participate in the study. All patients were then given health education regarding prevention of non-communicable diseases, regulation of blood pressure, maintenance of blood sugar and the importance of a healthy lifestyle.
Socio-economic classification: For socio-economic status, Modified Prasad’s classification was used taking All India Consumer Price Index for Industrial Workers (AICPI-IW) value of 268 for December 2015.[15, 16]
Results:
Among the 251 patients, the mean age of the patients was 56.47 (+10.9) years with a median of 58 years. Table 1 describes the socio-demographic profile of the patients with diabetes and hypertension. Among the 251 patients, 55.4% patients were above 56 years of age; 51% were female; 35.9% had a post-graduate degree; 11.6% were illiterate and 86.1% belonged to Hindu religion. Out of the 251 patients, 83.7% were married; 47.8% were daily wage laborers; 72.5% had an occupation requiring moderate activity; 64.1% were in class III of Modified Prasad’s socio-economic classification and 16.7% were in the upper socio-economic group (class IV and V). Among the 251 patients, 20.3% had diabetes; 79.7% had hypertension and 87.6% had obesity.
| Table 1: Socio-demographic profile of patients in an urban slum of Bhavnagar (n=251) |
| Age group (cut-off of 56 years as it is mean) |
Frequency (%) |
<56 years |
112 (44.6) |
>56 years |
139 (55.4) |
Gender |
Frequency (%) |
Male |
123 (49) |
Female |
128 (51) |
Education |
Frequency (%) |
Illiterate |
29 (11.6) |
Primary |
59 (23.5) |
Secondary |
48 (19.1) |
Higher secondary |
21 (8.4) |
Graduate |
4 (1.6) |
Post-graduate |
90 (35.9) |
Literacy status |
Frequency (%) |
Illiterate |
29 (11.6) |
Literate |
222 (88.4) |
Religion |
Frequency (%) |
Hindu |
216 (86.1) |
Muslim |
35 (13.9) |
Marital status |
Frequency (%) |
Currently single (includes the widow, widower, divorced) |
41 (16.3) |
Currently married |
210 (83.7) |
Occupational classification |
Frequency (%) |
Daily-wage laborers |
120 (47.8) |
Housewife |
62 (24.7) |
Private employer |
45 (17.9) |
Government employer |
12 (4.8) |
Diamond worker |
7 (2.8) |
Retired |
5 (2.0) |
Occupational classification by lifestyle |
Frequency (%) |
Sedentary occupations |
69 (27.5) |
Active occupations |
182 (72.5) |
Socio-economic status by Modified Prasad’s classification |
Frequency (%) |
I |
8 (3.2) |
II |
40 (15.9) |
III |
161 (64.1 ) |
IV |
40 (15.9) |
V |
2 (0.8) |
Socio-economic status (by lower and upper group) |
Frequency (%) |
Lower socio-economic group (I, II, III) |
209 (83.3) |
Upper socio-economic group (IV,V) |
42 (16.7) |
Table 2 demonstrates the social determinants and risk factors for diabetes. The social determinants significantly associated with diabetes were being literate, currently married, having an active occupation, belonging to Hindu religion, being in a higher socio-economic group, having financial crunch, having social conflicts at home and inability to perform daily work. Age, gender, professional stress, family history of diabetes, tobacco addiction, alcohol addiction, regular consumption of junk food, lack of fruits in diet and lack of green leafy vegetables in diet were the social determinants not significantly associated with diabetes. The risk factors significantly associated with diabetes were obesity by body mass index, abdominal obesity by waist circumference as well as by waist-hip ratio, sedentary lifestyle and no physical activity for at least 20 minutes a day. Inadequate sleep at night was the risk factor not significantly associated with diabetes.
| Table 2: Social determinants and risk factors of diabetes in an urban slum of Bhavnagar (n=51) |
| Social determinants |
Frequency (%) |
2x1 chi-square value |
P-value |
Age >56 years |
32 (62.7) |
3.314 |
0.069 |
Male gender |
28 (54.9) |
0.49 |
0.484 |
Literate |
44 (86.2) |
26.843 |
<0.0011 |
Currently married |
39 (76.4) |
14.294 |
<0.0011 |
Active occupation |
35 (68.6) |
7.078 |
0.0088 |
Hindu religion |
42 (82.3) |
21.353 |
<0.0011 |
Higher socio-economic group |
44 (86.3) |
26.843 |
<0.001 |
Financial crunch |
49 (96) |
43.314 |
<0.001 |
Professional stress |
26 (50.9) |
0.02 |
0.889 |
Social conflicts at home |
39 (76.4) |
14.294 |
<0.001 |
Disease affecting the ability to perform daily work |
34 (66.6) |
5.667 |
0.017 |
Family history of diabetes |
3 (5.9) |
39.706 |
<0.001 |
Undesirable event in last one year |
0 (0) |
- |
- |
Addiction of any harmful substance |
14 (27.4) |
10.373 |
0.001 |
Tobacco addiction |
10 (19.6) |
18.843 |
<0.001 |
Alcohol addiction |
5 (9.8) |
36.255 |
<0.001 |
Regular consumption of junk food |
19 (37.2) |
3.314 |
0.069 |
Lack of fruits in diet |
17 (33.3) |
5.667 |
0.017 |
Lack of green leafy vegetables in diet |
28 (54.9) |
0.49 |
0.484 |
Risk factors |
Frequency (%) |
2x1 chi-square value |
P-value |
Obesity by Body Mass Index |
45 (88.2) |
29.824 |
<0.001 |
Abdominal obesity by waist circumference |
38 (74.5) |
12.255 |
<0.001 |
Abdominal obesity by waist-hip ratio |
38 (74.5) |
12.255 |
<0.001 |
Inadequate sleep at night (at least 6-8 hours) |
19 (37.2) |
3.314 |
0.069 |
Sedentary lifestyle |
45 (88.2) |
29.824 |
<0.001 |
No physical activity for at least 20 minutes per day |
39 (76.4) |
14.294 |
<0.001 |
Do not walk or cycle to nearby places |
0 (0) |
- |
- |
Table 3 elucidates the social determinants and risk factors associated with hypertension. The social determinants significantly associated with hypertension were being literate, currently married, having an active occupation, belonging to Hindu religion, being in a higher socio-economic group, having financial crunch, having professional stress, having social conflicts at home, inability to perform daily work and regular consumption of junk food. Age, gender, family history of hypertension, an undesirable event in last one year, tobacco addiction, alcohol addiction, lack of fruits in diet and lack of green leafy vegetables in diet were the social determinants not significantly associated with hypertension. The risk factors significantly associated with hypertension were obesity by body mass index, abdominal obesity by waist circumference as well as by waist-hip ratio, sedentary lifestyle and no physical activity for at least 20 minutes a day. Inadequate sleep at night and not walking/cycling to nearby places were the risk factors not significantly associated with hypertension.
| Table 3: Social determinants and risk factors of hypertension in an urban slum of Bhavnagar (n=200) |
| Social determinants |
Frequency (%) |
2x1 chi-square value |
P-value |
Age >56 years |
113 (56.5) |
3.38 |
0.066 |
Male gender |
95 (47.5) |
0.5 |
0.48 |
Literate |
178 (89) |
121.68 |
<0.001 |
Currently married |
171 (85.5) |
100.82 |
<0.001 |
Active occupation |
147 (73.5) |
44.18 |
<0.001 |
Hindu religion |
174 (87) |
109.52 |
<0.001 |
Higher socio-economic group |
165 (82.5) |
84.5 |
<0.001 |
Financial crunch |
192 (96) |
169.28 |
<0.001 |
Professional stress |
119 (59.5) |
7.22 |
<0.001 |
Social conflicts at home |
164 (82) |
81.92 |
<0.001 |
Disease affecting the ability to perform daily work |
148 (74) |
46.08 |
<0.001 |
Family history of hypertension |
29 (14.5) |
100.82 |
<0.001 |
Undesirable event in last one year |
4 (2) |
184.32 |
<0.001 |
Addiction of any harmful substance |
56 (28) |
38.72 |
<0.001 |
Tobacco addiction |
50 (25) |
50 |
<0.001 |
Alcohol addiction |
10 (5) |
165.62 |
<0.001 |
Regular consumption of junk food |
117 (58.5) |
5.78 |
0.016 |
Lack of fruits in diet |
70 (35) |
18 |
<0.001 |
Lack of green leafy vegetables in diet |
76 (38) |
11.52 |
0.001 |
Risk factors |
Frequency (%) |
2x1 chi-square value |
P-value |
Obesity by Body Mass Index |
175 (87.5) |
112.5 |
<0.001 |
Abdominal obesity by waist circumference |
157 (78.5) |
64.98 |
<0.001 |
Abdominal obesity by waist-hip ratio |
166 (83) |
87.12 |
<0.001 |
Inadequate sleep at night (less than 6-8 hours) |
72 (36) |
15.68 |
<0.001 |
Sedentary lifestyle |
176 (88) |
115.52 |
<0.001 |
No physical activity for at least 20 minutes per day |
153 (76.5) |
56.18 |
<0.001 |
Do not walk or cycle to nearby places |
10 (5) |
162 |
<0.001 |
Among the 51 diabetics, 82.4% followed the prescribed diet advised; 10% took a diet low in salt, and 6% each followed glucose control and stopped smoking. Among the diabetics, only 4% exercised regularly and only 2% reduced their weight since being diagnosed. Among the diabetics, 43.1% were using partially-hydrogenated vegetable oil (PHVO); 39.2% were using butter and 11.8% were using cheese while cooking. Among the 200 hypertensive patients, 72% followed the prescribed diet advised; 29% took a diet low in salt; and 9% each followed glucose control and exercised regularly. Among the hypertensive, only 4% stopped smoking and only 2% reduced their weight since being diagnosed. Among the hypertensive, the majority (57%) used PHVO while cooking, while 34% of them used butter and 16.5% of them used cheese while cooking. Junk food was being consumed by 37% of diabetics and 59% of hypertensive patients.
Table 4 explicates the details of addiction among the respondents. Among the 51 diabetics, 15.7% were tobacco smokers and 19.6% were regular consumers of oral tobacco. The mean age of beginning to smoke tobacco among the diabetics was 16.8 years and the mean number of times they smoked in a day was 8.2. Out of the five diabetics who consumed alcohol, 60% were regular consumers with a mean consumption of 280 milliliters per drink. Pan masala and mawa (areca nut + tobacco + slaked lime) were the most commonly consumed oral tobacco products by the patients suffering from diabetes with a mean consumption of 4.8 times in a day. Among the ten diabetics consuming oral tobacco, 50% accepted that their peers started chewing tobacco by seeing them. All the ten diabetics wanted to get free from the addiction of tobacco and had made a mean of 1.8 efforts to quit.
| Table 4: Details of addiction of respondents in an urban slum of Bhavnagar |
| Addiction type |
Diabetics (% out of 51) |
Hypertensive (% out of 200) |
Tobacco smoking |
8 (15.7) |
27 (13.5) |
Regular tobacco consumption |
10 (19.6) |
50 (25) |
Details of tobacco smoking |
Diabetics |
Hypertensive |
Mean age of starting in years |
16.8 |
17.3 |
Mean no. of times per day |
8.2 |
10.6 |
Details of alcohol consumption |
Diabetics (% out of 5) |
Hypertensive (% out of 10) |
Regular consumption |
3 (60) |
4 (40) |
Once or twice a week |
2 (40) |
6 (60) |
Mean amount in milliliter per consumption |
280 |
410 |
Details of oral tobacco consumption |
Diabetics (% out of 10, multiple answers) |
Hypertensive (% out of 50, multiple answers) |
Pan masala quid (areca nut + condiments + tobacco) |
4 (40) |
33 (66) |
Gutka (areca nut + tobacco + condiments + flavors) |
1 (10) |
5 (10) |
Snuff |
1 (10) |
1 (2) |
Tobacco + slaked lime (khaini) |
0 (0) |
3 (6) |
Pan with tobacco |
0 (0) |
8 (16) |
Areca nut + tobacco + slaked lime (mawa) |
4 (40) |
23 (46) |
Peers started chewing because of you |
5 (50) |
21 (42) |
Want to be tobacco free |
10 (100) |
47 (94) |
Mean no. of times per day |
4.8 |
4.9 |
Mean no. of efforts to stop tobacco |
1.8 (all 10 made efforts to stop) |
1.8 (46 out of 50 made efforts to stop) |
Reasons to make efforts to stop oral tobacco chewing |
Diabetics (% out of 10, multiple answers) |
Hypertensive (% out of 50, multiple answers) |
Health |
10 (100) |
43 (86) |
Financial situation |
2 (20) |
24 (48) |
Bad odour |
0 (0) |
2 (4) |
Social rejection |
1 (10) |
4 (8) |
Among the 200 patients with hypertension, 13.5% were tobacco smokers and 25% regularly consumed oral tobacco. The mean age of starting to smoke among the hypertensive was 17.3 years with a mean frequency of 10.6 bouts of smoking in a day. Out of the ten patients with hypertension who had an alcohol addiction, 40% were regular drinkers with a mean of 410 milliliters per consumption. Among the 50 patients with hypertension who consumed oral tobacco, 66% consumed pan masala and 46% consumed mawa (areca nut + tobacco + slaked lime) with a mean consumption of 4.9 times in a day. Among the 50 hypertensive patients consuming oral tobacco, 42% agreed that their peers started chewing tobacco by seeing them. Among the 50 hypertensive patients, 94% wanted to be free from tobacco and had made a mean of 1.8 efforts to quit. Harmful effect on health and deteriorating financial situation were the primary reasons behind making efforts to quit oral tobacco among both diabetics and hypertensive.
Discussion:
There is a need to shift the focus on the binding of the social determinants of health (SDH) on the non-communicable diseases like diabetes and hypertension. The present study highlights the SDH approach for addressing the surge in cases of non-communicable diseases. The present study attempted to explore the socio-demographic correlates significantly associated with diabetes and hypertension among people residing in an urban slum of Bhavnagar.
A study conducted in an urban area of Rajasthan reported that age >40 years, family history, higher socio-economic status, sedentary lifestyle, smoking, and alcohol use were significantly associated with diabetes.[17] A meta-analysis on the impact of social determinants of health on diabetes found that these determinants had a significant impact on glycemic control, the progression of diabetes and quality of life.[18] A report of the World Health Organization published in 2007 states that physical inactivity and low physical fitness are independent predictors of mortality in people with type 2 diabetes.[19] They further highlighted that obesity is strongly related to raised blood pressure and type 2 diabetes.[19] They also stated that weight reduction, physical activity, and dietary manipulation reduced the incidence of type 2 diabetes in people at risk of developing it.[19] The current study supports the existing evidence linking social determinants of health to diabetes. However, the present study did not find a significant association of age and family history with diabetes. The present study also found an association between being married and having an active occupation with diabetes, suggesting that these determinants might be working in tandem in increasing the stress levels among the patients.
A study conducted in an urban area of Rajasthan reported that age >50 years, family history, higher socio-economic status, sedentary lifestyle, and smoking were significantly associated with hypertension.[17] A meta-analysis on the risk factors of hypertension in Indian population reported that age, alcohol, smoking and chewing tobacco, BMI, central obesity (defined as waist circumference>90cm in men and >80cm in women), consumption of low vegetables/fruits, high consumption of dietary fat and salt, and sedentary activity were the significant risk factors for hypertension.[20] A study involving a representative population of India showed that hypertension was more common in the urban population than in the rural population.[21] Their research also highlighted that obesity, larger waist circumference, and sedentary occupation were significant predictors of hypertension.[21] A study conducted in Central India identified increasing age, parental history of hypertension, tobacco smoking, tobacco chewing, physical inactivity, high estimated per capita salt consumption, and BMI =27.5 kg/m2 as independent predictors for hypertension in the urban population.[22] The present study also implicates similar social determinants of health with hypertension, except age, gender and family history.
Another study conducted with the support of Indian Council of Medical Research reported that age, male gender, urban residence, generalized obesity, diabetes, physical inactivity, salt intake >6.5 g per day and alcohol consumption were significantly associated with hypertension.[23] A research in an urban slum of West Bengal found that 39% of the hypertensive were current smokers and 29% were alcoholics.[24] They also highlighted that central obesity by waist circumference among hypertensive was significantly higher in females than in males and that 22% of hypertensive did not consume fruits in their diet.[24] A study in Kerala among adolescents found that low fruit consumption was one of the risk factors of pre-hypertension.[25] The current study also incriminates these risk factors with hypertension, except age, gender, and low fruit/vegetable consumption. Another study reported age >40 years as a significant risk factor for hypertension, but could not find a difference with gender.[21] Similar to the present study, their research also did not find a significant association between family history and hypertension.[21]
A study from western Uttar Pradesh reported that the prevalence of hypertension increased with age and had a preponderance among males.[26] They also highlighted a higher prevalence of hypertension in urban areas and that people in higher socio-economic groups in urban areas and those who were retired/unemployed were more likely to get hypertension, as stated in the current study.[26] The present study was also conducted in the urban area and found a higher proportion of hypertensive belonging to the higher socio-economic group. A report of the World Health Organization highlighted that obesity is a significant predictor of hypertension and weight reducing diets combined with exercise improves control of blood pressure.[19] A systematic review of the effect of nutrition and physical activity suggested a positive effect of these interventions on systolic and diastolic blood pressure.[27] The current study also highlighted that a significant proportion of hypertensive was consuming junk food and was using partially hydrogenated vegetable oil for cooking.
Though the investigators employed quality control measures in the measurement of parameters, the study has a number of limitations. Firstly, the study did not employ a comparison group. It has only highlighted the proportion of social determinants and risk factors of diabetes and hypertension among already diagnosed patients. Thus, the social determinants identified in the study cannot be conclusively proved. Secondly, since the study was conducted in a single urban slum of Bhavnagar city, it’s generalizability to a larger population is questionable. Nevertheless, the investigators believe that the study findings confirms and reiterates the existing knowledge on the subject and draws attention to the SDH approach to non-communicable diseases.
Conclusion:
Literacy, marital status, occupation, religion, socio-economic status, income, professional stress, social support, inability to perform work due to disease and consumption of junk food are the significant social determinants for diabetes and hypertension. Central and abdominal obesity, sedentary lifestyle and lack of physical activity are the significant risk factors for these diseases. While assessing the patients with hypertension and diabetes in their clinics, clinicians are advised to address the social determinants of health as well.
Acknowledgements:
The authors thank the participants for their support during the study.
Conflicts of Interest: None
Funding: None
References:
- World Health Organization. Global status report on noncommunicable diseases 2014: attaining the nine global noncommunicable diseases targets; a shared responsibility.
Geneva, 2014. Available at
http://www.searo.who.int/nepal/documents/noncommunicable_diseases/ncd_global_status_report_2014.pdf
- Walker RJ, Gebregziabher M, Martin-harris B, et al. Relationship between social determinants of health and processes and outcomes in adults with type 2 diabetes: validation of a conceptual framework. BMC Endocr Disord 2014;14:82.
- Mccarthy M. Tackling social factors is key in reducing cardiovascular disease , say US heart doctors. Br Med J 2015;351:h4333.
- Walker RJ, Gebregziabher M, Martin-harris B, et al. Independent Effects of Socioeconomic and Psychological Social Determinants of Health on Self-Care and Outcomes in Type 2 Diabetes. Gen Hosp Psychiatry 2014;36:662–668.
- Havranek EP, Mujahid MS, Barr DA, et al. Social Determinants of Risk and Outcomes for Cardiovascular Disease A Scientific Statement From the American Heart Association. Circulation 2015;132:873–898.
- Walker RJ, Gebregziabher M. Quantifying Direct Effects of Social Determinants of Health on Glycemic Control in Adults with Type 2 Diabetes. Diabetes Technol Ther 2015;17:80–87.
- Sullivan K, Dean A, Soe MM. OpenEpi: A Web-based Epidemiologic and Statistical Calculator for Public Health. Public Health Rep 2009;124:471–474.
- Central Bureau of Health Intelligence. National Health Profile 2015. New Delhi, 2015.
- World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation.
Geneva, 2008. Available at
https://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf?sequence=1
- World Health Organization. World Health Organization STEPS manual Section 3: Guide to Physical Measurements. Geneva.
2008. Available at
http://www.who.int/chp/steps/Part3_Section3.pdf.
- Misra A, Shrivastava U. Obesity and dyslipidemia in South Asians. Nutrients 2013;5:2708–2733.
- Bhalwar R. Non-communicable diseases. In: Rajvir B (ed) Textbook of Community Medicine. New Delhi: United India Periodicals Pvt Ltd., 2013, p. 586.
- Dean AG, Arner T, Sunki G, et al. Epi Info, a database and statistics program for public health professionals.
CDC, Atlanta, GA, USA, 2011
- Daniel WW, Cross CL. Biostatistics: A foundation for analysis in health sciences.
10th ed. New Jersey: John Wiley & Sons, 2013.
- Pradeep K. Social classification - need for constant updating. Indian J Community Med 1993;18:2–4.
- Labour Bureau. Government of India. Statistics. All-India Average Consumer Price Index (AICPI) Numbers for Industrial Workers.
New Delhi, Government of India. 2017. Available at
http://labourbureau.nic.in/indtab.htm.
- Nagar SR, Jain M, Sharma S. A Study To Identify Socio-Demographic and Lifestyle Risk Factors Associated With Type 2 Diabetes Mellitus and Hypertension. Natl J Community Med 2016;7:155–159.
- Walker RJ, Smalls BL, Campbell JA, et al. Impact of social determinants of health on outcomes for type 2 diabetes: A systematic review. Endocrine 2014;47:29–48.
- World Health Organization. Prevention of cardiovascular disease: Guidelines for assessment and management of cardiovascular risk. Geneva, 2007.
- Anchala R, Kannuri NK, Pant H, et al. Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens 2014;32:1170–1177.
- Farag YMK, Mittal B V, Keithi-Reddy SR, et al. Burden and predictors of hypertension in India?: results of SEEK (Screening and Early Evaluation of Kidney Disease ) study. BMC Nephrol 2014;15:1–10.
- Bhadoria AS, Kasar PK, Toppo NA, et al. Prevalence of hypertension and associated cardiovascular risk factors in Central India. J Family Community Med 2014;21:29–38.
- Bhansali A, Dhandania VK, Deepa M, et al. Prevalence of and risk factors for hypertension in urban and rural India: the ICMR-INDIAB study. J Hum Hypertens 2014;1–6.
- Acharyya T, Kaur P, Murhekar M V. Prevalence of behavioral risk factors, overweight and hypertension in the urban slums of North 24 Parganas District, West Bengal, India, 2010. Indian J Public Health 2014;58:195–198.
- Amma G, Vasudevan B, Akshayakumar S. Prevalence and Determinants of Pre-Hypertension and Hypertension among Adolescents?: A School based Study in a Rural area of Kerala, India. Int J Res Med Sci 2015;3:58–64.
- Singh R, Agarwal R, Singh S, et al. A cross- sectional study on prevalence of hypertension and its relationship with selected demographic factors in western Uttar Pradesh. Indian J Community Heal 2014;26:10–14.
- Rahmati-Najarkolaei F, Ghaffarpasand E, Gholami Fesharaki M, et al. Nutrition and Physical Activity Educational Intervention on CHD Risk Factors: A Systematic Review Study. Arch Iran Med 2015;18:51–57.
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