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A cross-sectional study of impact of lifestyle determinants on middle-aged male diabetic patients.


Diabetes mellitus, a noncommunicable disease which is spreading in pandemic proportions is posing a serious threat to humanity in the twenty-first century. [1] Diabetes prevalence across the globe for all given age groups was estimated to be 2.8% in 2000 and is said to rise to 4.4% in 2030. [2] In India, there are around 35 million diabetic patients, and this more than likely is a gross underestimation as the diagnosed cases are only a tip of the iceberg. Majority of the people are mostly unaware of their diabetes status. [3] The factors that have favored this pandemic outbreak in India are increase in lifespan, genetic background, sedentary lifestyle, urbanization, stressful jobs, and unhealthy eating practices. [1] Studies done on migrant Indians have shown that their genetic composition has made them more susceptible to this disease. [4] The "Asian Indian Phenotype" has been phrased to describe the unique combination of clinical and biochemical characteristics that place the Indians more at risk of developing this disease. [5]

It has been found that, for any given body mass index (BMI), the waist circumference and waist-hip ratio of an Indian is higher when compared with other ethnicities. [6] Studies also indicate that, for any given body fat, insulin resistance is higher among Indians. [7] This central type of fat distribution and increased insulin resistance are important risk factors for developing diabetes.

Cigarette smoking and alcohol consumption are social behaviors that are extensive among the Indian masses. Studies done on Western population showed that current and former smokers were at enhanced risk of developing diabetes subsequently. It was hypothesized that smoking has an acute effect on insulin sensitivity and exerts deleterious effect on insulin secretion in the long term. It was also observed that moderate alcohol consumption was actually beneficial to men and placed them at a lower risk of developing diabetes when compared with nonalcoholic subjects. [8] There is lack of such studies in the Indian settings. Smoking is associated with an increased risk of developing stroke, ischemic heart disease, and peripheral vascular disease among the diabetic patients. [9] The interactive effect of smoking and diabetes enhances the risk of developing cardiovascular disease by 14%, which is much more than their individual additive effect. [10]

When a study was done to determine the extent of tobacco use and the existence of awareness of harmful effects of smoking among South Indian diabetic patients, more than half the number of diabetic patients used tobacco, and there was a void in their knowledge about the same. Cessation of smoking was advised only to about half the number of diabetic patients studied, and more than half the sample population did not link smoking to complications of diabetes. [11] Thus, this study showed the appalling lack of awareness among the general population.

Hence, the aim of this study was to analyze the effect of these lifestyle determinants, namely cigarette smoking, alcohol consumption, and total energy consumption as risk factors for developing diabetes and, thereby, spread a strong message on the need for following healthy lifestyle practices. In addition, disease proportion is burdening the health-care facilities and available resources in our country. Simple lifestyle modifications, healthy eating practices, inculcating exercise routines, and maintaining normal body weight will go a long way in preventing this debilitating disease. [1]

Materials and Methods

A descriptive study was conducted on 100 middle-aged men aged between 30 and 50 years in the General Medicine Department of a private Medical College and Hospital of Karnataka, India, from June 2014 to August 2014. Purposive sampling was done. Of the 100 sample population, 50 were type II diabetic patients without any complications or other comorbidities and 50 healthy volunteers who accompanied the patients to the hospital. Ethical approval was obtained for this study from the Institutional Ethics review committee. Written informed consent was taken from each participant after describing in full detail the procedure and purpose of the study.

General physical examination, vital signs, and complete systemic examinations were done on all the subjects. A detailed history including diabetic history, personal history, drug history, and family history was taken. Their age, anthropometric measurements, blood pressure (BP) by JNC 7 criteria, BMI using Quetelet's formula, and fasting blood sugar (FBS) were recorded.

The BP was recorded by sphygmomanometric method in supine position (JNC 7 Criteria) in the right arm to the nearest 2 mm Hg using the mercury sphygmomanometer (Diamond Deluxe; Industrial Electronic and Products, Electronic Co-op. Estate, Pune, India). Two readings were taken 5 min apart, and the mean of two was taken as the BP. For those whose BP was a [greater than or equal to] 140/90 mm Hg, three BP recordings were recorded, with a gap of 1 day in between. The average of second and third was considered as the final BP.

Blood sample was collected under all aseptic conditions, and FBS levels were measured by glucose oxidase-peroxidase end point by Trinder's method using glucose reagent. (Transasia BioMedicals Ltd., Solan, Himachal Pradesh, India).

Participants were weighed in light clothing using a digital load cell balance (Soehnle, West Germany), which had a precision of 0.1 kg. The heights of the subjects were recorded without footwear, using a vertically mobile scale (Holtain, Crymych, United Kingdom) and expressed to the nearest 0.1 cm. BMI was calculated from the height and weight as follows: BMI = weight (kg)/[height.sup.2] (meters)-Quetelet's formula.

Their diet histories were collected with respect to the amount of daily food intake for 1 week for individual subjects. This includes the frequency and quantity of food consumption, type of food, vegetarian food, nonvegetarian food, milk, and other beverages. Quantification of the diet with respect to different food items consumed in grams/week was plotted. The intake of nutrients was computed by multiplying the frequency of consumption of each unit of food by its nutrient content.

Smoking history of all the participants was taken in detail. For former smokers, question such as years since quitting was asked. For each decade of life, average number of cigarettes smoked daily was tabulated. From these data, pack years of smoking were calculated. A pack year is defined as smoking 20 cigarettes daily for 1 year. [12]

Participants were asked about their alcohol consumption. They were asked "how often do you usually consume alcoholic beverages? The response categories listed were as follows: "rarely/never," "1-3/month," "1/week," "2-4/week," "5-6/week," "daily," and "2+/day". The responses were interpreted as the number of drinks consumed in specified period as first reported by Gaziano et al in 2000.

Responses of lifestyle determinants were analyzed among the participants statistically. Age, BP, BMI, and FBS parameters among the study group were analyzed by using the statistical software SPSS, version 17.0 and MS Excel. The [chi square]-test to compare the frequencies and unpaired f-test to check the significance were used. All tests were two-tailed, and p < 0.05 was considered as significant.


On comparing diabetes status with smoking status of the sample population, we found that a significant number of diabetic patients (56%) with a p value of < 0.05 were either former or current smokers. About 36% of diabetic patients had since quit smoking, and 20% of them continued to smoke [Table 1].

On comparing the diabetes status with smoking history [Table 2], there was no significant association found between the groups. There was, however, an increase in severity of clinical symptoms observed among the diabetic patients who were chronic smokers.

On comparing diabetes status with the alcohol consumption history [Table 3], it was found that there was no significant difference between them. But, 42% of people who consumed alcohol in moderation were found to be nondiabetic subjects when compared with 22% of diabetic patients consuming alcohol.

On comparing the status of diabetes with alcohol consumption history [Table 4], it was found that the percentage of diabetic patients was less when compared with healthy subjects in the occasional and moderate alcohol (60-120 mL/day) consumption category, although it was statistically not significant. However, diabetes was higher among people consuming larger portions of alcohol, which was again not statistically significant.

Total energy consumption among diabetic patients (1,392 [+ or -] 335 kcal/day) [Figure 1] was significantly higher (p < 0.05) than the normal subjects (1,062 [+ or -] 171 kcal/day).


We found a very strong association between history of smoking and occurrence of diabetes [Tables 1 and 2]. Significant number of diabetic patients showed a positive smoking history. About 36% of these diabetic patients have since quit smoking, and 20% of them still smoked. Certain clinical and experimental findings have shown that, following smoking, there is a reduction in insulin sensitivity or insufficient responses to compensatory insulin secretion, [13] thus leading to disruption in glucose and lipid metabolisms. This in turn leads to hyperglycemia, dyslipidemia, postprandial lipid intolerance and lowers HDL cholesterol. [14-17] Bruin et al, in their animal studies, recently found that, on exposure of fetal pancreatic tissue to maternally-derived nicotine, a loss of P cells occurred owing to oxidative stress and mitochondrial damage resulting in apoptosis mediated by nicotinic acetylcholine receptors. [18,19]

Our study failed to show any correlation between pack years of smoking and diabetes risk in contrast to earlier meta-analysis study. [13] This can be attributed to the smaller sample size. More such studies are required on a larger Indian population.

When we tried to find an association between alcohol consumption and diabetes status, nearly 64% of the diabetic patients were nonalcoholic subjects when compared with only 46% of the healthy subjects [Table 3]. This, however, was not a significant difference probably owing to smaller sample size. In addition, 22% of the subjects who consumed alcohol occasionally did not develop diabetes when compared with 12% of occasional diabetic alcohol consumers, which was again not significant [Table 4]. A Harvard study revealed that moderate alcohol consumption among healthy individuals reduces risk of developing diabetes [8] probably by increasing insulin sensitivity or reducing hepatic gluconeogenesis. [20] Shimomura and Wakabayashi [21] recently found an inverse linear relationship between alcohol intake and ratio of LDL cholesterol/HDL cholesterol in diabetic patients and a nonlinear inverse relationship between alcohol intake and ratio of triglyceride/HDL cholesterol. Thus, by altering the lipid profile, moderate alcohol consumption is beneficial to diabetic patients in preventing the atherosclerosis and other macrovascular complications. More studies are required to elucidate the molecular basis of this beneficial effect of moderate alcohol consumption among diabetic patients.

When we compared the total calorie intake between diabetic patients and normal subjects, there was significantly higher intake among diabetic patients. Studies have shown that high calorie intake on a long-term basis is associated with a significant decrease in insulin sensitivity and [beta]-cell compensation. [22] Other mechanisms such as lipotoxicity [23] and inflammation [24] resulting owing to high calorie intake are also likely causes of decline in p-cell functioning. High fat diet is said to interfere in insulin action and thus alters glucose tolerance. [25] On the other hand, calorie restriction was shown to reverse the decline in p-cell functioning and enhance the hepatic insulin sensitivity. [26] Furthermore, Weiss et al have recently found that calorie restriction combined with exercise among sedentary diabetic patients showed additive beneficial effects in glucoregulation. There was also a significant reduction in postprandial glucagon-like peptide-1 in them.

Smaller sample size and area of study restricted to one place are the limitations of this study. As this study highlights the importance of promoting healthy lifestyle interventions, [27] including a larger sample among different age group at different setting forms the future scope of the study. Further studies are required to elucidate the various molecular mechanisms of cell dynamics, which are affected by smoking and alcohol consumption on a larger sample size. We also found that the energy consumption of diabetic patients was significantly more than that of normal subjects. Awareness among the masses to alter their sedentary lifestyle and inculcate healthy eating practices is the need of the hour to control this pandemic outbreak in our country.


This study concludes that the occurrence of diabetes was more prevalent among people with history of smoking. There was no significant association between alcohol consumption and diabetes, although moderate alcohol consumption was numerically more among the healthy subjects. In addition, we found an excess calorie intake among the diabetic patients.

DOI: 10.5455/ijmsph.2016.04102015199


We are grateful to ICMR-STS 2014 for funding this project.


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Padmini Thalanjeri (1), Egla Inasu (2), Aswini Dutt Raghavendra (1), Shobith Bangera (1)

(1) Department of Physiology, Yenepoya Medical College, Mangalore, Karnataka, India.

(2) II MBBS Student, Yenepoya Medical College, Mangalore, Karnataka, India.

Correspondence to: Aswini Dutt R, E-mail:

Received October 4, 2015. Accepted October 12, 2015
Table 1: Comparison of diabetes status with smoking status
of the study group (n = 100)

                        Nonsmoker   Former    Current   P
                                    smoker    smoker

                        N    %      N    %    N    %

Non diabetic subjects   25   50     7    14   18   36   0.026
Diabetic subjects       22   44     18   36   10   20

Table 2: Comparison of diabetes status with smoking history
of the study group (n = 100)

Diabetes       Nonsmoker   Occasional   Former    Former
status         (%)         (%)          smoker,   smoker,
                                        <1 year   2-3 years
                                        (%)       (%)

Non diabetic      48           4           2          4

Diabetic          48           --         10          8

Diabetes       Former      Current    Current     P
status         smoker,     smoker,    smoker,
               4-5 years   one pack   2-3 pack
               (%)         year (%)   years (%)

Non diabetic       6          24         12       0.25

Diabetic          10          12         12

p < 0.05 is considered significant.

Table 3: Comparison of diabetes status with alcohol status
of the study group (n = 100)

Diabetes status         Nonalcoholic   Former    Current     P
                        (%)            alcohol   alcoholic
                                       intake    (%)

Non diabetic subjects        46          12         42       0.09
Diabetic subjects            64          14         22

p <0.05 is considered significant.

Table 4: Comparison of diabetes status with alcohol consumption
history of the study group (n = 100)

Diabetes      Nonalcoholic   Former,     Former,         Occasional
status        (%)            3-4 years   2-3 years (%)   (%)

Nondiabetic        48            8             4             22
Diabetic           64            6             6             12

Diabetes      60-120 mL/day   180-300 mL/day   500-700      P
status        (%)             (%)              mL/day (%)

Nondiabetic        12               2              4        0.32
Diabetic            2               4              6

p < 0.05 is considered significant.

Figure 1: Energy consumption of study group
(kcal/day), n = 100.

Diabetics       1392
Non-diabetics   1062

Note: Table made from bar graph.
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Article Details
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Title Annotation:Research Article
Author:Thalanjeri, Padmini; Inasu, Egla; Raghavendra, Aswini Dutt; Bangera, Shobith
Publication:International Journal of Medical Science and Public Health
Article Type:Report
Geographic Code:9INDI
Date:Jul 1, 2016
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