View of Cross Sectional Study on Prevalence of Diabetes Mellitus and Associated High Risk Factors among the Age Group of Over 18 Years in Rural Community of Puducherry

(1)

1442 http://annalsofrscb.ro

Cross Sectional Study on Prevalence of Diabetes Mellitus and Associated High Risk Factors among the Age Group of Over 18 Years in Rural Community of

Puducherry

Vinothkumar¹, S. Gopalakrishnan²

1,2 Department of Community Medicine, Sri Lakshmi Narayana Institute of Medical SciencesAffiliated to Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India

e-mail id: ²[email protected]

ABSTRACT

Background: Diabetes mellitus is also known as a “Silent disease,” still now no symptoms were identified and progresses to severe target organ damage. The high risk factors are communicable diseases to non- communicable diseases indicate the rural populations in Diabetes mellitus. To assess the various environmental factors contributing the occurrence of the diseases.

Objective: This study was evaluated to determine the prevalence of the type 2 diabetes mellitus.

Methods: The present study was conducted in the high risk factors among the age group in rural community.

Results: Based on the above results indicated that prevalence rate was high.

Conclusion: Multidisciplinary approach targeting Keywords:

Type 2 diabetes mellitus, age group, sex

1. Introduction

Diabetes mellitus is a major lifestyle disorder and chronic metabolic disorder is a fast-growing global problem with huge social, health, and economic consequences and their major impact on the lives and well-being of individuals, families, and societies in Worldwide. The prevalence of Diabetes mellitus, chiefly by Type 2 Diabetes mellitus, is a global public health threat. The prevalence among adults aged 20-79 years is expected to rise from 382 million in 2013 to 592 million by the year 2035. While Type 2 Diabetes mellitus poses a huge economic burden to all nations, developing countries bear the highest burden since more than 80% of cases occur in these countries (1,2,3). The socio-economic growth and industrialization is rapidly occurring in many of Asian countries, which is adversely affecting the lifestyle of populations. Asians have a strong ethnic and genetic predisposition for Diabetes and have lower thresholds for the environmental risk factors (4). As a result, they develop Diabetes at a younger age and at a lower body mass index and waist circumference when compared with the Western population. Asian countries contribute to more than 60% of the world’s diabetic population (1,2).

The socio-economic growth and industrialization is rapidly occurring in many of Asian countries, which is adversely affecting the lifestyle of populations and environment. Asians have a strong ethnic and genetic predisposition for Diabetes and have lower thresholds for the environmental risk factors (4). As a result, they develop Diabetes at a younger age and at a lower body mass index and waist circumference when compared with the Western population. Asian countries contribute to more than 60% of the world’s diabetic population (1,2). South East Asian countries have the highest burden of Diabetes mellitus (5,6). International Diabetes Federation on the estimated projections regarding Diabetes mellitus and Impaired Glucose Tolerance (IGT) in South East Asians.

Prevalence estimates of Diabetes mellitus and Impaired glucose tolerance (IGT) are high for all Asian countries and are expected to increase further in the next two decades. The present trend

(2)

indicates that more than 60% of the world’s diabetic population will be in Asia (5). The adverse effect of physical inactivity and fatty food are manifested as the increasing rate of over weight and obesity. The so called “Asian Indian Phenotype” refers to certain unique clinical and biochemical abnormalities in Indians which include increased insulin resistance, greater abdominal adiposity i.e. higher waist circumference despite lower body mass index. This phenotype makes Asian Indians more prone to Diabetes mellitus (7). However, the primary driver of the epidemic of Diabetes mellitus is the rapid epidemiological transition associated with changes in dietary patterns and decreased physical activity as evident from the higher prevalence of Diabetes mellitus in the urban population (6). India comprises 85% of the adult population of South East Asia and therefore the major contribution to diabetic population in South East Asia is from India. India leads the world with largest number of diabetic subjects earning the dubious distinction of being termed the “Diabetes Capital of the World”. According to the Diabetes Atlas 2006 published by the International Diabetes Federation, the number of people with Diabetes mellitus in India currently around 40.9 million is expected to rise to 69.9 million by 2025 unless urgent preventive steps are taken (2,6,8).

Many studies have illustrated the impact of socioeconomic transition occurring in rural India and environment. There are three fold rises in the prevalence of Diabetes in rural southern India (9).

The transition had occurred during the last 14 years and the prevalence had risen from 2.4% to 6.4%. Some of the recent prevalence studies done in rural south India shown, prevalence was 5.8% (10), 8.32% (11) and 13.2% (12) and shows prevalence has increased in rural community of India also equal to urban. The contributing factors related were improved socioeconomic status which encompassed an increase in family income and educational status, motorized transport and a shift in occupational structure. Similar situation has been described from the neighboring countries such as Thailand, Malaysia, Bangladesh and Pakistan. This revelation of increasing prevalence of Diabetes mellitus is important as majority of population in developing countries live in rural area and therefore it would be a major contributor to the emerging epidemic of Diabetes mellitus in this part of the world (13).

Diabetes mellitus is one of the major causes of morbidity and mortality affecting youth and middle aged people. Diabetes mellitus also considered as a “silent disease,” exhibiting no symptoms until it progresses to severe target organs damaged. Because of increasing burden of the disease, its iceberg nature, its complications and potential to prevent these complications with earlier diagnosis and treatment; active and opportunistic efforts are required for early diagnosis of Diabetes mellitus by means of screening. Early identification of at-risk individuals and appropriate lifestyle intervention would help in preventing or postponing the onset of Diabetes mellitus (14).

A significant proportion of people with type 2 Diabetes mellitus presents with complications (both macro vascular and micro vascular), usually subclinical and asymptomatic at the time of diagnosis. Early diagnosis of Diabetes offers the chance of intervention and curbs the onward progression of complications. Hence it is imperative that to curtail the menace of complications, an early diagnosis of Diabetes mellitus and Pre-Diabetes is important. This also presents an opportunity to gauge the prevalence of risk factors for development of Diabetes mellitus in the said population and the opportunity to intervene in the high risk cases to prevent the development of Diabetes mellitus in an individual level (15). With this background, this study was undertaken to know the prevalence of Type 2 Diabetes mellitus and associated high risk factors among adults in rural community of Pondicherry.

(3)

2. Material and Methods Description of study area

These are the common communicable (Acute respiratory infections, Acute diarrheal diseases, Tuberculosis, Malaria, Filaria, Enteric fever, Dengue,) and non-communicable (Hypertension, Diabetes Mellitus, IHD, Stroke, Cancer) diseases present in Pondicherry (100). There are 2 Government Hospitals, 3 Community Health Centers, 27 Primary Health Centers, 2 Government Medical Colleges and 7 Private Medical Colleges and 12 Private Nursing Homes present in Pondicherry District to provide and maintain good health. In recent times Type 2 Diabetes mellitus is a leading cause of morbidity in Pondicherry District. I have conducted my studies in the rural areas of Pondicherry as the prevalence studies are rare among the rural population compare to urban region. I have selected Pondicherry as my study area as my institution is situated here.

Study design and period

A cross sectional, descriptive, community based survey was undertaken in Pondicherry with the above mentioned objectives among rural community. The study was approved by the Institutional Ethical committee (Human studies) of the institute as shown in Annexure 2. The study period was between April 2014 to September 2014.

Survey settings

The data for this cross sectional survey was collected from rural community of Pondicherry.

There were 30 Primary Health Centers in Pondicherry, among the above Primary Health Centers 5 rural PHC were selected to represent each community so that the results may be provide generalized details. The consent from the respective participants was taken before starting the survey.

Selection of age groups Inclusion criteria:

 All people aged above 18 years in study population.

 All the Pre-Diabetes Subjects included based on available reports.

Exclusion Criteria

 All people aged below 18 years.

 Women with Gestational Diabetes Mellitus

 Individuals who declined for informed consent, and Not available at home even after repeat third visit.

Sample size and sampling techniques

The sample size was calculated using available recent prevalence studies (Samanth et al study shows 5.8% in Pondicherry-2012) in rural area of Pondicherry (10). The required sample size was 1624, we have taken it as 1821 with 20% non-response rate in this study. When prevalence/

proportion rate known, sample Size is calculated by following method (101).

When prevalence rate is known or proportion of occurrence is known, 𝑛 = 4𝑝𝑞

𝐿²

(4)

Where p = prevalence/proportion of an event, q = 1-p L2 = Permissible error in the estimate of p

Where p = 5.8, q = 100 – 5.8 = 94.2, L² = 20% (permissible error) = 1.3456 𝑛 = (4 × 5.8 × 94.2) ÷ 1.345 = 1624 (Sample size)

Sampling techniques

A multi-stage random sampling technique was applied in selection of 1624 sample subjects in the survey. In the first stage, all the 27 Primary Health Centers in the Pondicherry have been listed. 5 Primary Health Centers were selected using lot method in the Second stage. The names of the following Primary Health Centers are being selected by using lot method for data collection.

 Thirubuvanai (32,787 Population)

 Katterikuppam (12,443 Population)

 Nettapakkam (14,100 Population)

 Bahour (26,996 Population)

 Abishegapakkam (6,836 Population)

In the third stage, one village from each Primary Health Centers was selected as per the second stage by random. The following villages and samples aged above 18 years was surveyed by direct interview method by using pretested questionnaire were selected by lot methods.

3. Data collection procedure

First house was selected randomly selected village moved towards the right side of the first house till adequate sample sizes were obtained in particular villages. Procedure for the survey was explained to the participants in the local (Tamil) and English languages, assessing the potential respondents that the participation is voluntary and anonymous, assured them that their responses would be kept confidential. They were request to share the information by recollecting method on the variables mentioned in the questionnaire. The data have collected from participants along with consent forms and request to sign. No incentives of any kind were offered to the participants. The data was obtained from those who were present in the house at the time of survey and the data from those who were not present was collected later after giving prior information. All efforts were made to collect the data of the patient’s by visiting their houses on three occasions. Mostly data was collected early in the morning 6 to 8 AM and evening 18 to 21 PM which is convenient of the participants.

List of PHC’s List of Villages No. of houses to be surveyed

No. of individuals surveyed

Thirubuvanai Madagadipet (4,750) 120 416

Katterikuppam Mutrampet (2,102) 161 421

Nettapakkam Pandasozanallur (5,544) 103 352

Bahour Bahour (3,978) 79 241

Abishegapakkam Thimmanayakanpalayam

(2,833) 107 391

(5)

Variables

The survey instruments were anonymous in nature which was pre-tested, open ended questions consisted of variables in six sections is attached as Annexure 3.

1) Socio demographic factors

 Age

 Sex

 Religion

 Education status

 Occupation

 Family income

 Marital status

 H/o Diabetes

 Sibling Diabetes History

2) Risk factors of type 2 Diabetes Mellitus

 Tobacco usage (Smoking Tobacco, Chewing Tobacco and Both forms)

 Alcohol consumption (Daily-at least 80 ml, Regular-once in a week andOccasionally- once in a month)

 Physical activity / Exercise

 Diet habit

 Type of diet (Vegetarian / Mixed Vegetarian)

 Oil rich food habit

 Known Hypertension

 Known Dyslipedemia

3) Seeking of medical care among Diabetes Subjects

 Taking medical care or not

 Place of treatment

 Type of treatment

 Regularity of treatment

4) Co-Morbid Conditions among Diabetes

 Respiratory Infections

 Ischemic Heart Disease

 Gastro intestinal problem

 Hemipharesis

 Eye defects (Refractory errors / surgeries)

 Skin infections

 Any other complications like joint pain, Giddiness etc, 5) General and Clinical Examination

6) Anthropometric Examination done as per Annexure 4.

 Height

 Weight

 Body Mass Index calculation

Each questionnaire would take 15 minutes to complete by the investigator.

(6)

4. Data analysis and statistical tests

The data were analyzed using SPSS version 20 for Percentage, Proportion, Chi-square test, ANOVA, Student “t” test, Odds Ratio and significance of association at the level of p<0.05. We analyzed the waited prevalence, percentage and mean for this study.

Table 1: Distribution of total population according to family size, number of families and aged above 18 years of subjects

Family size

Number of

families (%)

Total number of family members

(%) a

Aged 18 years and above Numbers

(%) b

≤2 153

(26.8)

284 (13.1)

281 (98.9)

3 131

(23)

345 (15.9)

316 (91.6)

4 115

(20.2)

512 (23.6)

435 (85)

5 88

(15.4)

440 (20.1)

344 (78.2)

>5 86 (15.1)

588 (27.1)

445 (75.7)

Total 570

(100)

2169 (100)

1821 (84)

(Percentage in bracket shows aged 18 years and above %=b/a)

Table 1 shows total numbers of houses surveyed in this study were 570. Total members were 2169, in that 1821 participants were equal and above the age group of 18 years. 588 (27.1%) members belongs to the family size 5 and above, 512 (23.6%) belongs to family size 4, 440 (20.3%) belongs to family size 5 and 629 (29%) belongs to family size 3 and below.

Table 2: Distribution of subjects according to Religion

Hindu (1780) Muslim (32) Christian (9)

Religion (N=1821)

(7)

Table 2 shows 1780 (97%) participants were Hindu, 32 (1.8%) were Muslims and 9 (0.5%) were Christians.

Table 3: Distribution of study population according to Age group in years and Gender

Age group in years

Male Numbers (%)

Female Numbers (%)

Total Numbers (%)

≤20 71

(8.1)

69 (7.2)

140 (7.7)

21 – 30 188

(21.8)

278 (28.9)

466 (25.6)

31 – 40 206

(24)

216 (22.5)

422 (23.2)

41 – 50 181

(21.1)

173 (18)

354 (19.4)

51 – 60 138

(16.1)

140 (14.6)

278 (15.3)

> 60 75

(8.7)

86 (8.9)

161 (8.8) Total

859 (100)

962 (100)

1821 (100)

Table 3 shows total eligible study population was 1821 of which males 859 (47.1%) and females 962 (52.8%) respectively. Age group between 21-30 years accounted 466 (25.6%), 31-40 years accounted 422 (23.2%), 41-50 years accounted 354 (19.4%), and age above 60 years 161 (8.8%).

Age group between 21-30 years’ females 278 (28.9%) were more than males 188 (21.8%) and age group between 41-50 years’ males 181 (21.1%) were more than females 173 (18%).

Table 4: Distribution of subjects according to and Marital Status and Sex wise

Marital Status

Male Numbers (%)

Married 627

(73.0)

688 (71.5)

1315 (72.2) Unmarried

222 (25.8)

149 (15.5)

371 (20.4) Divorced

3 (0.3)

5 (0.5)

8 (0.4) Widow/widower

7 (0.8)

120 (12.5)

127 (7) Total

859 (100)

962 (100)

1821 (100)

(8)

Table 4 shows 1315 (72.2%) were married, unmarried were 371 (20.4%), widow & widower were 127 (7%). Students group were come under the category of unmarried participants. Males (25.8%) were more than the females (15.5%) in unmarried group and no gender difference in other categories.

Table 5: Distribution of subjects according to Educational Status and Sex wise

Educational Status

Male Numbers (%)

Illiterate 129

(15.0)

287 (29.8)

416 (22.8)

Primary 63

(7.3)

99 (10.3)

162 (8.9)

Middle 106

(12.3)

129 (13.4)

235 (12.9)

High school 220

(12.1)

165 (17.2)

385 (21.1)

Higher secondary 140

(16.3)

129 (13.4)

269 (14.8)

Diploma 62

(7.2)

23 (24.0)

85 (4.7)

Graduate 107

(12.5)

106 (11.0)

213 (11.7)

Post graduate 32

(3.7)

24 (2.5)

56 (3.1)

Total 859

(100)

962 (100)

1821 (100)

Table 5 shows 416 (22.8%) participants were illiterate, 385 (21.1%) were studied till high school, 269 (14.8%) were finished higher secondary, 354 (19.4%) were graduates. Female (29.8%) illiterates are more than the males (15.0%) and female (37.5%) graduates were more than males (23.4%).

Table 6: Distribution of subjects according to Occupation and Sex wise

Occupation Male

Numbers (%)

Female Numbers (%)

Unemployed * 110

(12.8)

583 (60.6)

693 (38.1)

Daily wagers 193

(22.5)

181 (18.8)

374 (20.5)

Private 226

(26.3)

96 (10)

322 (17.7)

self-employment 127

(14.8)

11 (1.1)

138 (7.6)

Student 62

(7.2)

59 (6.1)

121 (6.6)

Business 69

(8.0)

3 (0.3)

72 (4)

Government 57

(6.6)

12 (1.3)

69 (3.8)

Retired 14

(1.6)

15 (1.6)

29 (1.6)

Total 859

(100)

962 (100)

1821 (100)

(* includes house wife)

(9)

Table 6 shows 374 (20.5%) were daily wagers, 322 (17.7%) were working in private and unemployed were 693 (38.1%) and house wives were included in the category of unemployed, so that 583 (32.0%) females were accounted and contributed more in unemployed group. Males were more than females as daily wagers (22.5% Vs 18.8%), government (6.6% Vs 1.3%), private (26.3% Vs 9.98%), and self-employment (14.9% Vs 1.4%). Students and retired population were almost same in both males and females.

Table 7: Distribution of Number of Families according to Family Income per month Family Income in rupees ( ) Number of Families (%)

≤ 10000 263 46.1

10001 – 20000 82 14.4

20001 – 30000 92 16.1

30001 – 40000 40 7.0

40001 – 50000 56 9.8

> 50000 37 6.5

Total 570 100

Table 7 shows 263 (46.1%) families monthly income were 10,000 and below and they accounted nearly half of the population. 174 (30.5%) were earning between 10001-30000, 96 (16.8%) were earning 30001-50000 and 37 (6.5%) were earning more than

50000. The above table indicates nearly 50% of the families come under the category of low and middle economic status of the family.

Table 8: Distribution of subjects according to Body Mass Index (BMI) and sex wise

∗ 𝐌𝐚𝐥𝐞𝐬 𝟐 = 𝟒𝟕. 𝟗𝟒𝟗, 𝒅𝒇 = 𝟏𝟓, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎#𝐅𝐞𝐦𝐚𝐥𝐞𝐬 𝟐 = 𝟓𝟗. 𝟎𝟎𝟗, 𝒅𝒇

= 𝟏𝟓, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎@𝐓𝐨𝐭𝐚𝐥 𝟐 = 𝟖𝟖. 𝟑𝟖𝟔, 𝒅𝒇 = 𝟏𝟓, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎 This table shows age group less than or equal to 20 years, females (10.1%) were overweight than males (5.6%), males (7.9%) were overweight than females (5.8%) in the age group of 21 to 30 years. Age group between 41 to 50 years and 51 to 60 years’ females (12.1% & 33.6%) obese than males (8.8% & 29.2%). 19.9%, 30.3%, 29.9% and 29.2% total subjects were overweight in the age group between 21 to 30, 31 to 40, 41 to 50 and above the age group of 60 years. 6.7% of

(10)

total subjects obese in the age group of 21 to 30 years. The difference between numbers of males, females and total subjects and BMI were found to be statistically significant (P<0.05).

Table 9: Distribution of subjects according to Tobacco usage and Sex wise

Tobacco Usage

Male Numbers (%)

No 731

(85.1)

924 (96.1)

1655 (90.9) Chewing Tobacco (CT)

5 (0.6)

38 (4)

43 (2.4)

Smoking Tobacco (ST) 114

(13.3) -

114 (6.3) Smoking &Chewing Tobacco (ST&CT) 9

(1.1) - 9(0.5)

Total 859

(100)

962 (100)

1821 (100)

Table 9 shows 1655 (90.9%) participants were not using any forms of tobacco, 166 (9.1%) were using different tobacco products. 114 (13.3%) were smokers, 43 (2.4%) were chewing tobacco and 9 (0.5%) were using both form of tobacco. Female 38 (4%) were using chewable form of tobacco more than the males.

Table 10: Distribution of subjects according to consumption of alcohol

Alcohol Consumption

Male Numbers (%)

No 675

(78.6)

1637 (89.9)

Daily (DA) 31

(3.6)

31 (1.7)

Occasionally (OC) 90

(10.5)

90 (5)

Regularly (RE) 63

(7.3)

63 (3.5)

Total 859

(100)

1821 (100)

Table 10 shows, 1637 (89.9%) were non-alcoholic and 184 (10.1%) were consuming alcohol. In that, 90 (10.5%) males were drinking alcohol occasionally (once in a month), 63 (3.5%) males were drinking regularly (once in a week) and 31 (1.7%) were drinking daily (at least 80 ml).

Females (962) were included in the total (1637) of not consuming alcohol.

(11)

Table 11: Prevalence of Diabetes mellitus in different age group among men and women

Male Female Total

Age

Group in years

Numbers (%) Numbers (%)

Numbers (%)

≤20 - -

21-30 1(0.4) 6(1.7) 7(1.2)

31-40 18(8.7) 22(10.2) 40(9.5)

41-50 33(18.2) 41(24.0) 74(21.0)

51-60 33(23.9) 47(34.0) 80(29.0)

> 60 26(34.7) 29(34.0) 55(34.2)

Total 111(12.9) 145(15.1) 256(14.0)

𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟐. 𝟗𝟖𝟕, 𝒅𝒇 = 𝟒, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟓𝟔

Table 11 shows the total prevalence was 14.0%, among males and females the prevalence of Diabetes mellitus was 12.9% (111) and 15.1% (145) respectively. Age 60 years and above the prevalence was 34.2% (55), age group between 51- 60 was 28.8% (80) and 41-50 was 20.9%

(74). Age group between 31-50 years accounted for 114 (30.4%) and it indicates most of Diabetics were in economically productive age group. Overall prevalence of females was affected by Diabetes mellitus than the males.

Table 12: Prevalence of Diabetes mellitus among men and women according to Body Mass Index (BMI)

Male Female Total Body Mass Index

BMI (Kg/m²) Numbers

(%) Numbers (%) Numbers (%)

≤18.5 5(6.5) 4(4.5) 9(5.4)

18.5-24.99 63 (12.6) 60(11.2) 123(11.9)

25-29.99 30(13.8) 57(22.9) 87(18.7)

≥30 13(20) 24(26.7) 37(23.9)

Total 111(12.9) 145(15.1) 256(14.0)

𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟕. 𝟒𝟒, 𝒅𝒇 = 𝟑, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟓

Table 12 shows the prevalence was high among overweight 18.7% (87) and obese 23.9% (37) than normal and malnourished. Even malnourished have prevalence of Diabetes 5.4% (9). The difference between BMI and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05).

(12)

Table 13: Distribution of number of families according to siblings with Diabetes among Diabetic families

Family size

Number of families N (%) (a)

Number of families with Diabetes (%) (b) #

Number of families among sibling with Diabetes (%) (c) *

≤2 153(26.8) 22(14.4) 7(31.8)

3 115(20.2) 23(20.0) 13(56.5)

4 128(22.5) 25(19.5) 13(52.0)

5 88(15.4) 35(6.1) 18(51.4)

>5 86(15.1) 23(4.0) 10(43.5)

Total 570(100) 128(22.5) 61(47.7)

(Percentage in () shows # No. of families with Diabetes = b/a, * Number of families among sibling with Diabetes = c/b)

Table 13 shows total number of families was 570 and 128 (22.5%) families having Diabetes subjects in their house. 61 (47.7%) families having sibling with Diabetes out of 128 Diabetes families. 86 (33.6%) Diabetes subjects were having more than one sibling with Type 2 Diabetes mellitus.

Table 14: Distribution of Diabetes persons according to number of siblings with Diabetes Number of Sibling

with Diabetes

Numbers Numbers Numbers

(%) (%) (%)

0 53(47.8) 77(53.1) 130(50.8)

1 14(12.6) 26(17.9) 40(15.7)

> 1 44(39.6) 42(29) 86(33.6)

Total 111 (100) 145(100) 256(100)

𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟑. 𝟔𝟐𝟔, 𝒅𝒇 = 𝟐, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟔𝟑

Table 14 shows 40 (15.7%) Diabetes subjects were having one sibling with diabetes and 86 (33.6%) Diabetes was having more than one sibling with diabetes.

Table 15: Distribution of Diabetes persons according to duration of Diabetes among men and women

Duration in Months

Numbers (%) Numbers (%) Numbers (%)

< 6 11(9.9) 25(17.2) 36(14.1)

7 to 24 33(29.7) 34(23.5) 67(26.2)

(13)

25 to 48 29(26.1) 23(15.9) 52(20.3)

49 to 72 13(11.7) 18(12.4) 31(12.1)

> 72 25(22.5) 45(31.0) 70(27.3)

Total 111 (100) 145 (100) 256 (100)

𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟖. 𝟑𝟎𝟑, 𝒅𝒇 = 𝟒, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟖𝟏

Table 15 shows 67 (26.2%) subjects were having Diabetes between 7-24 months, 52 (20.3%) subjects were having between 25-48 months and 70 (27.3%) were having more than 72 months.

Nearly 60% of Diabetic patients suffering from Diabetes less than 48 months. 30% were diagnosed as diabetes less than 24 months, among them more males 33 (29.7) were diagnoses than females 34 (23.5%) last two years.

Table 16: Prevalence of Diabetes mellitus according to Occupation and Sex wise

Occupation

Numbers (%) Numbers (%) Numbers (%)

Unemployed 13(21) 89(15.3) 102(14.7)

Daily Wages 36(18.7) 45(24.9) 81(21.7)

Self-Employment 23(18.1) 2(18.2) 25(18.1)

Private 18(8.0) 2(2.1) 20(6.2)

Retired 6(42.9) 5(33.3) 11(37.9)

Government 7(12.3) 2(16.7) 9(13.0)

Business 8(11.6) - 8(11.1)

Total 111(12.9) 145(15.1) 256(14.0)

∗ 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟗𝟔. 𝟏𝟏𝟓, 𝒅𝒇 = 𝟔, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎

Table 16 shows prevalence of type 2 Diabetes mellitus was 37.9% (11) in retired, 21.7% (81) in daily wagers, 14.7% (102) in unemployed and 13.0% (9) in government servants. Prevalence of Diabetes were more in females (24.9%) 45 than males (18.7%) 36 in the category of daily wagers.

Table 17: Prevalence of Diabetes mellitus and association of various risk factors among subjects

Risk Factors

Numbers (%) Numbers (%) Numbers (%)

111 (12.9) 145 (15.1) 256 (14.0)

Total

Tobacco usage*

(14)

No 88 (11.2) 141 (16.3) 229 (13.8)

Chewing Tobacco (CT) 1 (5.9) 4 (16) 5 (11.9)

Smoking Tobacco (ST) 21 (42) - - 21 (18.3)

ST & CT (Smoking & Chewing Tobacco) 1 (25) - - 1 (11.1)

Alcohol Consumption ≠

No 80 (11.9) 145 (15.1) 225 (13.7)

Daily (DA) 5 (16.1) - - 5 (16.1)

Occasionally (OC) 15 (16.7) - - 15 (16.7)

Regularly (RE) 11 (17.5) - - 11 (17.5)

Physical Activity/

Exercise Ω

No 82 (10.4) 118 (12.8) 200 (11.7)

Yes 29 (39.1) 27 (64.3) 56 (48.3)

∗ 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟑𝟐. 𝟏𝟏, 𝒅𝒇 = 𝟑, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎

≠ 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟒𝟔. 𝟎𝟑, 𝒅𝒇 = 𝟑, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎

Ω 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟐. 𝟎𝟕𝟐, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟕𝟎

Table 17 shows 27 Diabetes subjects were using different forms of tobacco and prevalence was 16.3%. Prevalence of Diabetes were increased among smokers than the usage of chewable tobacco.

Table 18: Prevalence of Diabetes mellitus and association between each risk factor among subjects

Risk Factors

(N) (%) (N) (%) (N) (%)

Total 111 12.9 145 15.1 256 14.0

Diet Habit *

Vegetarian 13 (27.1) 15 (22.7) 28 (25)

Non vegetarian 98 (12.1) 130 (14.5) 228 (13.4)

Type of Diet ≠

Mixed 57 (12) 66 (13) 123 (13)

Carbohydrate 42 (12.1) 57 (14.3) 99 (13.3)

Protein 12 (33.3) 22 (40) 34 (37.4)

Fat rich foodΩ

No 40 (12.7) 49 (13.2) 89 (13)

(15)

Yes 71 (13.1) 96 (16.7) 167 (15)

∗ 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟐𝟎, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟑𝟕, ≠ 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟏. 𝟑𝟖𝟏, 𝒅𝒇 = 𝟐, 𝑷 𝒗𝒂𝒍𝒖𝒆

= 𝟎. 𝟓𝟎,

Ω 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟑𝟗, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟕𝟗𝟏

Table 18 shows Prevalence of Diabetes mellitus among vegetarians 24.6% (28) and non- vegetarians were 13.4% (228).

Prevalence of Diabetes mellitus was 13.3% (99) those eating carbohydrate diet, 12.5% (123) those food habit mixed diet and 37.4% (34) in those eating protein diet.

Table 19: Prevalence of Known Hypertension among Diabetes mellitus according to Sex wise

Risk Factors

(N) (%) (N) (%) (N) (%)

Total 111 (12.9) 145 (15.1) 256 (14.0)

Known Hypertension∗

No 80 (9.9) 93 (10.5) 173 (10.2)

Yes 31 (59.6) 52 (67.5) 83 (64.3)

Known Dyslipedemia#

No 101 (12.1) 133 (14.1) 234 (13.2)

Yes 10 (41.7) 12 (63.2) 22 (51.2)

∗ 𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟏. 𝟖𝟎𝟔, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟐𝟐𝟓

#𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟒𝟑, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟖𝟐𝟔

Table 19 shows prevalence of Known Hypertension among Diabetes was 64.34 (83).

Table 20: Mean duration of Diabetes in months and association of various risk factors according to sex wise

Risk Factors

Male Numbers (Mean ± SD)

Female Numbers (Mean ±SD)

Total Numbers (Mean ±SD)

Total 111(52.8±15.1) 145(52.6±13.1) 256 (52.7±15.1)

Tobacco Usage*

No 88(48.3±26.6) 141(56.7±26.7) 229(53.4±26.6)

Yes 23(67.1±28.1) 4(57±35.4) 27(65.6±28.1)

Alcohol Consumption#

No 80(56.0±26.7) 145(56.6±26.7) 225(56.4±26.7)

Yes 31(42.3±26.9) - 31(42.3±26.9)

Physical

Activity/Exercise@

(16)

No 82(49.5±26.8) 118(51.1±26.7) 200(50.5±26.7)

Yes 29(59.76±26.7) 27(80.7±28.5) 56(69.9±26.7)

∗ 𝐌𝐚𝐥𝐞𝐬 𝒕 = 𝟏. 𝟔𝟕, 𝒅𝒇 = 𝟏𝟎𝟗, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟗𝟖 ∗ 𝐅𝐞𝐦𝐚𝐥𝐞𝐬𝒕 = 𝟎. 𝟎𝟏𝟑, 𝒅𝒇

= 𝟏𝟒𝟑, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟗𝟗𝟎

∗ 𝐓𝐨𝐭𝐚𝐥 𝒕 = 𝟏. 𝟐𝟎𝟒, 𝒅𝒇 = 𝟐𝟓𝟒, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟐𝟑𝟎

#𝐌𝐚𝐥𝐞𝐬 𝒕 = 𝟏. 𝟑𝟕, 𝒅𝒇 = 𝟏𝟎𝟗, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟖𝟓 #𝐓𝐨𝐭𝐚𝐥 𝒕 = 𝟏. 𝟒𝟕𝟕, 𝒅𝒇

= 𝟐𝟓𝟒, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟏𝟒𝟏

@𝐌𝐚𝐥𝐞𝐬 𝒕 = 𝟎. 𝟗𝟕𝟔, 𝒅𝒇 = 𝟏𝟎𝟗, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟑𝟑𝟏 @𝐅𝐞𝐦𝐚𝐥𝐞𝐬 𝒕 = 𝟐. 𝟕𝟗𝟐, 𝒅𝒇

= 𝟏𝟒𝟑, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟔

@𝐓𝐨𝐭𝐚𝐥 𝒕 = 𝟐. 𝟔𝟎𝟒, 𝒅𝒇 = 𝟐𝟓𝟒, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟏𝟎

Table 20 shows mean duration of Diabetic subject according to sex wise in moths. Mean duration of 256 Diabetic subjects were (52.7±15.1) of which males 111 (52.8±15.1) and females were (52.6±13.1) respectively. Mean duration of 229 non-tobacco users were (53.4±26.7) and 27 tobacco users were (65.6±28.1). Mean duration of 23 male tobacco users were (67.1±28.1) and 4 female tobacco users were (57±35.4). Mean duration of Diabetes in months of males, females and total among tobacco users and non-tobacco users were not found statistically significant (P>0.05).

Mean duration of 31 alcohol users were (42.4±26.9). Mean duration of 200 subjects those who were not done any kind of physical activity (50.5±26.7) and 56 subjects those who were doing physical activity (69.9±26.7).

Mean duration of 29 male subjects those who were doing physical activity (59.8±26.7) and 27 females those who were doing physical activity were (80.7±28.5).

Table 21: Distribution of Medical Care according to Place, Type and Regularity of Treatment

Medical Care

Numbers Numbers Numbers

(%) (%) (%)

Total* 111 (100) 145 (100) 256 (100)

Yes 95(85.6) 121(83.5) 216(84.4)

No 16(14.4) 24(16.6) 40(15.6)

Place of Treatment

Government 61(55) 87(60.0) 148(57.8)

Private 34(30.6) 31(21.4) 65(25.4)

Both - 3(2.07) 3(1.2)

No 16(14.4) 24(16.6) 40(15.6)

Treatment Type

Allopathic 94(84.7) 120(82.8) 214(83.6)

Ayurvedhic - 1(0.7) 1(0.4)

Siddha 1(0.9) - 1(0.4)

No 16(14.4) 24(21.4) 40(15.6)

(17)

Regularity of Treatment#

Regular 84(75.7) 111(76.6) 195(76.2)

Irregular 11(9.9) 20(13.8) 21(8.2)

No 16(14.4) 24(16.6) 40(15.6)

Duration of Blood Investigation

0 89(80.2) 112(77.2) 201(78.5)

< 6 21(18.9) 31(21.4) 52(20.3)

> 6 1(0.9) 2(0.8) 3(1.8)

(∗)𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟐𝟖𝟎, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟕𝟐𝟗 (#)𝝌^𝟐𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟖𝟖𝟔, 𝒅𝒇 = 𝟐, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟔𝟒𝟐

Table 21 shows Percentage of seeking medical care among Diabetes subjects. 216 (84.4%) subjects were taking medical care and 40 (15.6%) subjects were not taking treatment. 148 (57.8%) were taking treatment in government and 65 (25.4%) were taking treatment in private.

214 (83.6%) of subjects taking allopathic treatment. 195 (76.2%) subjects were taking treatment regularly and 8.2% were irregular on treatment. Nearly 55 (21.5%) subjects were undergoing blood investigation regularly in every 6-12 months’ period.

Table 22: Distribution of present Co-Morbid Condition among Diabetes Subjects Co-Morbid

Condition Number of persons %

No 216 84.4

Giddiness 17 6.6%

Joint Pain 10 3.9%

Eye Defect 9 3.5%

Diabetic Foot 2 0.8

Skin Infection 1 0.4

Hemipharesis 1 0.4

Table 22 shows 216 (84.4%) Diabetes subjects not having any complication and 40 (15.6%) subjects having Co-Morbid Condition like giddiness, joint pain, eye defect, diabetic foot, skin infection, Hemipharesis. 10 (3.9%) were having joint pain, 9 (3.5%) were having eye defect and 17 (6.6%) having giddiness.

Table 23: Numbers of males and females in different age group among Diabetes and Non- Diabetes subjects

Age group in years

Diabetics Non Diabetics Total

Number Number Number

≤20 - 140(9) 140(7.7)

21 – 30 7(2.7) 459(29.3) 459(25.2)

31 – 40 40(15.6) 382(24.4) 422(23.2)

(18)

41 – 50 74(28.9) 280(17.9) 354(19.4)

51 – 60 80(31.3) 198(12.7) 278(15.3)

> 60 Total

55(21.5) 256 (100)

106(6.8) 1565 (100)

161(8.8) 1821(100) 𝐀𝐠𝐞 𝐕𝐬 𝐃𝐢𝐚𝐛𝐞𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐍𝐨𝐧 𝐃𝐢𝐚𝐛𝐞𝐭𝐢𝐜𝐬 𝐞𝐱𝐜𝐥𝐮𝐝𝐞𝐬 ≤ 𝟐𝟎𝐲𝐞𝐚𝐫𝐬 𝟐 = 𝟐𝟎𝟖. 𝟒𝟔, 𝒅𝒇

= 𝟓, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎

Table 23 shows 7 diabetics (2.7%) in the age group of 21-30 years, 40 diabetics (15.6%) in the age group of 31-40 years, 74 diabetics (28.9%) were in the age group of 41-50 years, 80 diabetics (31.3%) were in the age group of 51-60 years and 55 diabetics (21.5%) were above 60 years.

Table 24: Mean age of male and female and its association among Diabetes and Non-Diabetes subjects

∗ 𝒕 = 𝟏𝟓. 𝟐𝟖𝟕 , 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎# 𝒕 = 𝟗. 𝟗𝟎𝟐 , 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎𝝈 𝒕 = 𝟏𝟏. 𝟔𝟗𝟕 , 𝑷 𝒗𝒂𝒍𝒖𝒆

= 𝟎. 𝟎𝟎𝟎

Table 24 shows that the mean age of total 1821 was (40.1±26.6) of which 256 Diabetic subjects were (52.67±15.1) and 1565 Non-Diabetic subjects were (38.0±15.1). The difference between mean age of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05).

The mean age of a total of 859 males were (40.4±15.1), of this 111 were diabetics (52.8±1.2) and Non –Diabetics (38.5±0.5). The difference between mean age of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05).

The mean age of a total of 962 females were (39.8±15.1), of which 145 were Diabetics (52.6±13.1) and 817 were Non-Diabetics (37.5±14.5). The difference between mean age of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05).

Risk Factors

Diabetics Number (Mean Age±SD)

Non-Diabetics Number (Mean Age±SD)

Total Number (Mean Age±SD)

Total∗ 256

(52.7±15.1)

1565 (38.0±15.1)

1821 (40.1±26.6)

Male#

111 (52.8±1.2)

748 (38.5±0.5)

859 (40.4±15.1)

Female 𝝈

145 (52.6±13.1)

817 (37.5±14.5)

962 (39.8±15.1)

(19)

Table 25: Gender wise comparison of Diabetes and Non-Diabetes subjects according to BMI

² = 5.925, df = 3, P value = 0.115 **² = 35.26, df = 3, P value = 0.000 ***² = 34.806, df

= 3, P value = 0.000

Table 25 shows 9 Diabetics (3.5%) and 157 Non Diabetics (10.0%) were less than or equal to the BMI of 18.50, 123 Diabetics (48.1%) and 911 Non Diabetics (58.2%) were between 18.51 to 24.99, 87 Diabetics (34%) and 379 Non Diabetics (24.2%) were between the BMI of 25 to 29.99, 37 Diabetics (14.5%) and 118 Non Diabetics (7.5%) were more than the BMI of 30. An overall evaluation revealed in the overweight category numbers of females (57) were more than males (30) and similarly in the obese category numbers of females (24) were more than males (13).

The difference between BMI of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were not found to be statistically significant in males (P>0.05).

Table 26: Comparison of risk factor of dietary pattern among Diabetes and Non-Diabetes according to sex wise

Risk Factors Diabetic Non Diabetic Odds ratio (OR) P Value Total 256(100) 1565(100)

Food Habit

Vegetarian 28 (10.9) 86 (5.5) 1.839 P=0.002

Non vegetarian 228 (89.1) 1479 (94.5)

Type of Diet

Mixed 123 (48.1) 860 (55) - P=0.000

Carbohydrate 99 (38.7) 648 (41.4) Protein 34 (13.3) 57 (3.6)

Fat rich food

No 89 (34.8) 614 (39.2) 0.848 P=0.188

Yes 167 (65.2) 951 (60.8)

Table 26 shows 28 Diabetics (10.9%) and 86 Non Diabetics (5.5%) were vegetarians, 228 Diabetics (89.1%) and 1479 Non Diabetics (94.5) were non-vegetarians and also both are

Body Mass Index BMI (Kg/m²) *Male Number

(%)

**Female Number

(%)

***Total Number (%)

Diabetic Non Diabetic Diabetic Non Diabetic Diabetic Non Diabetic

≤ 18.5 5

(4.5)

72 (9.6)

4 (2.8)

85 (10.4)

9 (3.5)

157 (10.0)

18.5-24.99 63

(56.8)

437 (5.8)

60 (41.4)

474 (51.0)

123 (48.1)

911 (58.2)

25-29.99 30

(27.0)

187 (25.0)

57 (39.3)

192 (23.5)

87 (34)

379 (24.2)

≥ 30 13

(11.7)

52 (7)

24 (16.6)

66 (8.1)

37 (14.5)

118 (7.5)

Total 111

(100)

748 (100)

145 (100)

817 (100)

256 (100)

1565 (100)

(20)

statistically significant (P<0.05). Those who are eating non-vegetarian 1.84 times having higher risk of getting Diabetes compare to vegetarians.

123 Diabetics (48.1%) and 860 Non Diabetics (55%) were mixed diet, 99 Diabetics (38.7%) and 648 Non Diabetics (41.4%) were carbohydrate rich diet, 34 Diabetics (13.3%) and 57 Non Diabetics (3.6%) were eating protein rich diet, the difference between type of food of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05). 89 Diabetics (34.8%) and 614 Non Diabetics (39.2%) were not eating any type of oil rich foods, 167 Diabetics (65.2%) and 951 Non Diabetics (60.8%) were eating oil rich foods regularly.

Table 27: Comparison of known Hypertension and Known Dyslipedemia among Diabetes and Non-Diabetes according to sex wise

Risk Factors Male

Number (%)

Female Number (%)

Total Number (%) Diabetic

Non

Diabetic Diabetic

Non

Diabetic Diabetic

Non Diabetic

Total 111(100) 748(100) 145(100) 817(100) 256(100) 1565(100)

Known

Hypertension*

No 80

(72.1)

727 (97.2)

93 (64.1)

792 (96.9)

173 (67.6)

1519 (97.1) Yes

31 (27.9)

21 (2.8)

52 (35.9)

25 (3.1)

83 (32.4)

46 (2.9) Known

Cholesterol#

No 101

(9.1)

734 (98.1)

133 (91.7)

810 (99.1)

234 (91.41)

1544 (98.7)

Yes 10

(9.0)

14 (1.9)

12 (8.3)

7 (0.9)

22 (8.6)

22 (1.4)

∗ 𝐌𝐚𝐥𝐞𝐬 𝟐 = 𝟏𝟎𝟕. 𝟐𝟓, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝟎. 𝟏𝟔𝟔,∗ 𝐅𝐞𝐦𝐚𝐥𝐞𝐬 𝟐

= 𝟏𝟕𝟗. 𝟗𝟒, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝟎. 𝟏𝟓𝟔

*Total 𝟐 = 𝟐𝟗𝟎. 𝟓𝟑, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝟎. 𝟏𝟓𝟗

#𝐌𝐚𝐥𝐞𝐬 𝟐 = 𝟏𝟖. 𝟏𝟑𝟎, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝑶. 𝟐𝟗𝟎, #𝐅𝐞𝐦𝐚𝐥𝐞𝐬𝟐 = 𝟑𝟓. 𝟎𝟏, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝟎. 𝟐𝟐𝟎

#𝐓𝐨𝐭𝐚𝐥 𝟐 = 𝟓𝟎. 𝟏𝟖𝟒, 𝒅𝒇 = 𝟏, 𝑷 𝒗𝒂𝒍𝒖𝒆 = 𝟎. 𝟎𝟎𝟎, 𝑶𝑹 = 𝟎. 𝟐𝟓𝟕

Table 27 shows 83 Diabetics (32.4%) having known hypertension in that females 52 (35.9%) more than males 31 (27.9%). 22 Diabetics (8.6%) having known Dyslipedemia and the difference between known Dyslipedemia of Diabetics and Non-Diabetics and Prevalence of Type 2 Diabetes mellitus were found to be statistically significant (P<0.05). Total numbers of houses in five number of villages, under five number of PHC surveyed in this study were 570. Total members were 2169 and 1821 participants were equal and above the age group of 18 years.

The total eligible study population was 1821 of which males 859 (47.1%) and females 962 (52.8%) respectively as shown Table 3. In other studies, the population selected in rural areas were 1403 and 616 respectively (10,43). Age group between 21-30 years accounted 466 (25.6%), 31-40 years accounted 422 (23.2%), 41-50 years accounted 354 (19.4%), and age above 60 years 161 (8.8%). The cumulative age of 1821 participants was 72,941 years (males 72851 years &

females 72893) years accounting as mean age of the participants was 40.1±26.6 years and males

& females were 40.4±15.1 (859) & 39.8± 15.1(962) years respectively.

The prevalence of Diabetes mellitus among 1821 was 14.0% which is high among females 15.1%

(962) than males 12.9% (859). Prevalence of Diabetes was more among females than the males.

Total prevalence of similar studies conducted elsewhere as shown with the similar range of

(21)

prevalence in rural area are 18.17% and 9.2% (9,51) compare to urban areas elsewhere conducted showing higher prevalence of Diabetes mellitus 4.6% and 9% (4,7). Table 24 shows, the mean age of Diabetics of 256 was (52.7±15.1) years, males (111) and females (145) were (52.8±15.1) and (52.6±13.1) years respectively. Shabana et al study was found to be mean age of Diabetes with similar (102). The mean age of Non-Diabetics of 1565 was found to be (38.0±15.1) years, males (748) and females (817) were (38.5±0.5) and (37.5±14.5) years.

Age group between 41-50 & 51-60 the prevalence of Type 2 Diabetes mellitus was more in Females (23.7%) & (33.6%) than males (18.2%) & (23.9%). Prevalence of Type 2 Diabetes mellitus was more in 60 (34.2%) years and above, age group between 51-60 (28.8%) and 41-50 (20.9%) shows in Table 11. The prevalence of Type 2 Diabetes mellitus was increasing as their age increases was not found to be statistically significant (P>0.05). Similarly, previous studies shown increase in prevalence of Diabetes as age increases (3,7,14,55). Previously reported higher prevalence in females compare to males (3,56,103,104).

The subjects in this study based on their education status as illiterates accounted 416 (22.8%) which is higher. Female illiterates (29.8%) were more than males (15.0%). Degree holders accounted 19.4% and 57.7% subjects accounted together under the category of primary, middle, high and higher secondary school. Diploma graduate women (24.0%) were more than male graduates (7.2%) shows in Table 6 (3,7,14,55).

Table 16 shows nearly 39% accounted under the unemployed category which included house wives. Daily wagers were 20.5% and this shows that in the rural areas most of them were illiterates and persons who had reached or completed schooling. Arora v et al, Reshma S Patil et al, Shiju TM et al, Rao C R et al studies were categorized similarly (3,7,14,55).

Table 8 shows 19.9%, 30.3%, 29.9% and 29.2% total subjects were overweight in the age group between 21 to 30, 31 to 40, 41 to 50 and above the age group of 60 years. 6.7% of total subjects obese in the age group of 21 to 30 years. There is a statistically significant difference among BMI of males and females in different age group in this study (P<0.05) and which interestingly BMI were also found to be difference among age group of males and females respectively. Similarly, BMI was categorized in previous studies (11,14,46,51,55).

The prevalence of Diabetes mellitus among lean Diabetics was 5.4% in 18.5 Kg/m², 11.8% and 48.4% among normal BMI and overweight or obese subjects. Prevalence of overweight & obese females (22.8% & 26.6%) was more than males (13.82% & 20.0%). Table 25 shows differences were found to be statistically significant among female subjects and total participants in this study (P<0.05). More number of diabetic men and women was 11.7% and 16.6% over the BMI of 30 Kg/m² in this study.

Central obesity is one of the important risk factor for prevalence of Diabetes mellitus. Rao and co-workers and Bener co-workers were found association between Diabetes and abdominal obesity like current study (55,104). Ramchandran et al, also reported significant association of central obesity with Diabetes (13,44). Table 9 and 10 shows 166 (9.1%) were using tobacco products and none of the females were smokers in this study, 184 (10.1%) were consuming alcohol and none of the females were consuming alcohol, and 1705 (93.6%) were not doing physical activity or exercise in this study.

The prevalence of type 2 Diabetes mellitus among tobacco users, alcoholics and lack of physical activity or exercise was found to be 18.3%, 16.3% and 11% respectively as shown in the Table 17. Previous studies also reported the association between prevalence of Diabetes and tobacco, alcohol and physical inactivity were found to be statistically significant (P<0.05) (11,14,46,49,51,55,59,66,67,72,73).