{"id":49254,"date":"2023-06-30T10:48:57","date_gmt":"2023-06-30T10:48:57","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=49254"},"modified":"2023-07-11T06:25:23","modified_gmt":"2023-07-11T06:25:23","slug":"role-of-lifestyle-and-stress-on-diabetes-mellitus-a-case-control-study","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol16no2\/role-of-lifestyle-and-stress-on-diabetes-mellitus-a-case-control-study\/","title":{"rendered":"Role of Lifestyle and Stress on Diabetes Mellitus: A Case-Control Study"},"content":{"rendered":"\n

Introduction<\/strong><\/p>\n\n\n\n

Type-2 diabetes\nmellitus is a chronic, heterogeneous metabolic disease in which insulin\nresistance and reduced insulin paired with increased hepatic glucose production\nlead to hyperglycemia. 90-95% of adult cases are caused by type-2 diabetes\nmellitus. A pathophysiological viewpoint reveals that the three main\nabnormalities that a patient with type-2 diabetes mellitus demonstrates are:\nresistance to the action of insulin in peripheral tissues, particularly muscle,\nfat, and liver, defects in insulin secretion, particularly in response to a\nglucose stimulus and an increased glucose production by the liver. Many factors\nlead to the development of type-2 diabetes mellitus, such as an increase\nin calorie intake, an increase in fat mass and a sedentary lifestyle, the\ninability of beta cells in pancreatic cells to adapt to less insulin\nsensitivity or an increase in insulin resistance. The genetic predisposition\nto T2DM determines how frequently and which beta failure happens, but no single\ngenetic alteration has been identified that causes beta cell failure. Other\nfactors increase the burden on beta cells, like overeating, leading to weight\ngain, puberty, pregnancy and a sedentary lifestyle1<\/sup>.<\/p>\n\n\n\n

Some modifiable risk\nfactors include BMI, physical inactivity, diet, and non-modifiable variables\nsuch as genetic factors and age2<\/sup>. Obesity has been associated with\nType-2 Diabetes Mellitus for decades. Visceral\/intra-abdominal fat is known to\ncause insulin resistance alongside several other metabolic variables, such as\nelevated total plasma cholesterol, insulin, and glucose concentrations. It has\nalso been linked to high triglyceride and decreased plasma high-density\nlipoprotein cholesterol concentration. However, some studies have suggested\nthat subcutaneous fat helps against insulin resistance. On these grounds, the\nassociation between insulin resistance and abdominal fat is independent of\ntotal adiposity. The correlation between an abnormal metabolism and intra-\nabdominal fat has not yet been clearly defined, but several hypotheses have\nbeen proposed to explore this association2<\/sup>.<\/p>\n\n\n\n

A recent study on\nlifestyle’s effect on patients with diabetes mellitus found that people who\nconsumed alcohol had the highest HbA1c levels. In the case of patients who practiced\nsmoking, they had a higher risk of diabetes mellitus. However, light to\nmoderate consumption of alcohol showed decreased risk in the case of\ncardiovascular diseases3<\/sup>. In the case of diet, low salt consumption\nwas found effective in T2DM patients and also in managing the risk of cardiovascular\ndiseases. Exercises play a very important role in the management of diabetes mellitus3<\/sup>.\nSleep disturbances can also affect insulin action, alter leptin secretion and\nghrelin, stimulate appetite, increase inflammatory cytokine production, and alter\nother risk factors. It was found that the alterations in the normal feeding\npattern attuned to the circadian metabolism can change the relationship between\nthe nutrient-metabolizing and nutrient-appearance enzymes. The alterations in\nfatty acid appearance concerning the lipoprotein lipase activity can lead to\naltered partitioning of lipids concerning vulnerable tissues, further leading\nto lipotoxicity and decreased leptin secretion, thereby increasing appetite. Another\nrisk factor for insulin resistance and diabetes is Obstructive sleep apnea. Obstructive\nsleep apnea combines sleep fragmentation and hypoxemia. There is growing\nevidence of glucose control in patients with T2DM, which can be improved by\ntreating sleep apnea, though poor compliance to therapy is a major barrier to\nsuccess4<\/sup>.<\/p>\n\n\n\n

Higher stress levels\nare attributable to diabetes displayed in both cross-sectional and longitudinal\nrelationships with HbA1c. Stress is a potential contributor to chronic\nhyperglycemia in diabetes. Stress has long been shown to have major effects on\nmetabolic activity. Stress stimulates the release of various hormones, resulting\nin elevated blood glucose levels. Although this is of adaptive importance in a\nhealthy organism, in diabetes,stress-induced glucose increases\ncannot be metabolized properlydue to the relative or absolute lack\nof insulin.<\/p>\n\n\n\n

Furthermore,\nregulation of these stress hormones may be abnormal in diabetes5<\/sup>. Although\nhuman studies on the role of stress in the onset and course of type II diabetes\nare few6<\/sup>. IL-6 is a protein the body produces to stimulate immune\nresponse and healing. It is a biomarker of acute and chronic stress that also\nhas been associated with a greater likelihood of diabetes and high blood\nglucose7<\/sup>. Literature showed individuals with low inhibition were\nmore likely to have diabetes than those with high inhibition due to the pathway\nfrom high anxiety5<\/sup>. This research is aimed to determine the\nassociation between diabetes mellitus and, stress and lifestyle among residents\nof UAE.<\/p>\n\n\n\n

Materials and methods<\/strong><\/strong><\/p>\n\n\n\n

This case-control study was conducted among the\nresidents of Ajman, UAE, within the age group of 35-70 years. The study setting\nwas Thumbay University Hospital, Ajman. Both male and female patients of all\nnationalities were included; pregnant women and patients with other disease\nconditions, such as cardiovascular diseases and cancer, were excluded. The\nminimum required sample obtained was 195 (65 cases and 130 controls), but collected\ndata from 71 cases and 134 controls. This research was approved by the\nInstitution Review Board of Gulf Medical University. Written consent was taken\nfrom the participants. Participants were provided with a brief description of\nthe purpose of this research. Anonymity, privacy and confidentiality were\nmaintained.  <\/p>\n\n\n\n

A draft questionnaire was developed and sent to the\nexperts for content validation. The suggestions of the experts were included in\nthe questionnaire before finalizing. The \u2018Perceived stress scale\u2019, a global\nself-assessment tool, analyzed the patient’s stress. The smoking and alcohol levels were also inquired\nin the questionnaire; the ex-user is defined as anyone who previously abstained\nfrom drinking alcohol and smoking for more than six months. The final\nquestionnaire was distributed to the selected participants and asked to\ncomplete the information. Data were then entered into the Excel sheet, after\nwhich the analysis was done. This was recorded in the Excel sheet and then\ncoded into SPSS version 27 for analysis. The descriptive statistics such as\nfrequency, percentage, mean and SD was calculated. To assess the association,\nthe Chi-Square test was used, t-test was also used to test the mean of the\ncontinuous variables. Simple and multiple logistic regression analyses were\nused to get the factors.<\/strong><\/p>\n\n\n\n

Results <\/strong><\/strong><\/p>\n\n\n\n

This study included 71 cases and 134 controls, out of which 43 controls and 7 cases were below 40 years of age, 85 controls and 57 cases were between 40-59 years of age and 5 cases and seven controls were over the age of 60.  Sixty-six controls and 39 cases were male, while 68 controls and 32 cases were female. Ten controls and five cases were single; 66 cases and 124 controls were married. Fourteen controls and 16 cases had a below-graduate level of education. Twenty-nine cases and 54 controls were graduates, whereas 66 controls and 26 cases were postgraduates. Fifty-six controls and 31 cases earned less than 4000 USD per month and 23 cases and 54 controls earned more than 4000 USD per month. Thirty-three controls and 12 cases were gold-collar workers, and 37 cases and 61 controls were white-collar workers. Eleven controls and seven cases were blue-collar workers, 27 controls and 15 cases said they were unemployed. The Chi-square test showed that the participant’s age and the presence of diabetes mellitus were associated (P <0.001). A statistically significant association was observed with education (P<0.05); cases were more in the higher education group compared to the control group. There was no statistically significant association between gender, marital status, income, occupation, and diabetes mellitus (table 1).<\/p>\n\n\n\n

Table 1: Association of diabetes mellitus and sociodemographic variables<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Variable<\/strong><\/p>\n<\/td>\n

\n

Group<\/strong><\/p>\n<\/td>\n

\n

Control<\/strong><\/p>\n<\/td>\n

\n

Cases<\/strong><\/p>\n<\/td>\n

\n

Total<\/strong><\/p>\n<\/td>\n

\n

P<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

No.<\/strong><\/p>\n<\/td>\n

\n

%<\/strong><\/p>\n<\/td>\n

\n

No.<\/strong><\/p>\n<\/td>\n

\n

%<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Age<\/p>\n<\/td>\n

\n

<40<\/p>\n<\/td>\n

\n

43<\/p>\n<\/td>\n

\n

32.1<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

9.8<\/p>\n<\/td>\n

\n

50<\/p>\n<\/td>\n

\n

<0.001<\/p>\n<\/td>\n<\/tr>\n

\n

40 -59<\/p>\n<\/td>\n

\n

86<\/p>\n<\/td>\n

\n

64.2<\/p>\n<\/td>\n

\n

57<\/p>\n<\/td>\n

\n

80.3<\/p>\n<\/td>\n

\n

143<\/p>\n<\/td>\n<\/tr>\n

\n

>=60<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

3.7<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

9.5<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n<\/tr>\n

\n

Gender<\/p>\n<\/td>\n

\n

Male<\/p>\n<\/td>\n

\n

66<\/p>\n<\/td>\n

\n

49.3<\/p>\n<\/td>\n

\n

39<\/p>\n<\/td>\n

\n

54.9<\/p>\n<\/td>\n

\n

105<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Female<\/p>\n<\/td>\n

\n

68<\/p>\n<\/td>\n

\n

50.7<\/p>\n<\/td>\n

\n

32<\/p>\n<\/td>\n

\n

45.1<\/p>\n<\/td>\n

\n

100<\/p>\n<\/td>\n<\/tr>\n

\n

Marital Status<\/p>\n<\/td>\n

\n

Single<\/p>\n<\/td>\n

\n

10<\/p>\n<\/td>\n

\n

92.5<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

15<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Married<\/p>\n<\/td>\n

\n

124<\/p>\n<\/td>\n

\n

7.5<\/p>\n<\/td>\n

\n

66<\/p>\n<\/td>\n

\n

93<\/p>\n<\/td>\n

\n

190<\/p>\n<\/td>\n<\/tr>\n

\n

Education<\/p>\n<\/td>\n

\n

Below Graduate<\/p>\n<\/td>\n

\n

14<\/p>\n<\/td>\n

\n

10.4<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

22.5<\/p>\n<\/td>\n

\n

30<\/p>\n<\/td>\n

\n

<0.05<\/p>\n<\/td>\n<\/tr>\n

\n

Graduate<\/p>\n<\/td>\n

\n

54<\/p>\n<\/td>\n

\n

40.3<\/p>\n<\/td>\n

\n

29<\/p>\n<\/td>\n

\n

40.8<\/p>\n<\/td>\n

\n

83<\/p>\n<\/td>\n<\/tr>\n

\n

Postgraduate<\/p>\n<\/td>\n

\n

66<\/p>\n<\/td>\n

\n

49.3<\/p>\n<\/td>\n

\n

26<\/p>\n<\/td>\n

\n

36.6<\/p>\n<\/td>\n

\n

92<\/p>\n<\/td>\n<\/tr>\n

\n

Income<\/p>\n<\/td>\n

\n

No income<\/p>\n<\/td>\n

\n

24<\/p>\n<\/td>\n

\n

17.9<\/p>\n<\/td>\n

\n

17<\/p>\n<\/td>\n

\n

43.7<\/p>\n<\/td>\n

\n

41<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

<15000<\/p>\n<\/td>\n

\n

56<\/p>\n<\/td>\n

\n

41.8<\/p>\n<\/td>\n

\n

31<\/p>\n<\/td>\n

\n

32.4<\/p>\n<\/td>\n

\n

87<\/p>\n<\/td>\n<\/tr>\n

\n

> 15000<\/p>\n<\/td>\n

\n

54<\/p>\n<\/td>\n

\n

40.3<\/p>\n<\/td>\n

\n

23<\/p>\n<\/td>\n

\n

32.4<\/p>\n<\/td>\n

\n

77<\/p>\n<\/td>\n<\/tr>\n

\n

Occupation<\/p>\n<\/td>\n

\n

Gold Collar<\/p>\n<\/td>\n

\n

33<\/p>\n<\/td>\n

\n

25.0<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n

\n

16.9<\/p>\n<\/td>\n

\n

45<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

White Collar<\/p>\n<\/td>\n

\n

61<\/p>\n<\/td>\n

\n

46.2<\/p>\n<\/td>\n

\n

37<\/p>\n<\/td>\n

\n

52.1<\/p>\n<\/td>\n

\n

98<\/p>\n<\/td>\n<\/tr>\n

\n

Blue-collar<\/p>\n<\/td>\n

\n

11<\/p>\n<\/td>\n

\n

8.3<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

9.9<\/p>\n<\/td>\n

\n

18<\/p>\n<\/td>\n<\/tr>\n

\n

Unemployed<\/p>\n<\/td>\n

\n

27<\/p>\n<\/td>\n

\n

20.5<\/p>\n<\/td>\n

\n

15<\/p>\n<\/td>\n

\n

21.1<\/p>\n<\/td>\n

\n

42<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

The chi-square test was used to assess the association.<\/p>\n\n\n\n

This study showed the likelihood of diabetes increases as age increases. Figure 1 shows the association between age and diabetes. The yellow colour represents those with diabetes and the blue represents those without diabetes. A significant association was found between age and diabetic status (P<0.001). An increase in age showed an increase in the prevalence of diabetics by several folds. The adjusted OR observed was 4.2 and 9.7, respectively. <\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure 1: Association between age and diabetes among cases and control.<\/strong><\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

In Figure 2, the yellow colour represents those with diabetes and the blue represents those without diabetes. As seen, there is a significant association between stress and diabetes (P<0.05), i.e., an increase in stress levels and an increase in the prevalence of diabetes was observed. Stress significantly increases glucose concentrations in patients with Type-2 diabetes. <\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure 2: Association between stress and diabetes <\/strong>among cases and control.<\/strong><\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Figure 3 shows the combined impact of stress and age on diabetes. This graph is split into four quadrants based on the median age and median stress. The four quadrants are those with High stress with older age, high stress with younger age, low stress with old age and low stress with older age. The highest prevalence of diabetes is seen in those with high stress and old age, while the lowest prevalence is seen in the quadrant with low stress and younger age. This shows that age and stress increase the prevalence of diabetes independently, but those of older age with increased stress levels increase the prevalence of diabetes by further folds.<\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Figure 3: Prevalence of diabetes by categorizing in terms of stress and age <\/strong>among cases and control.<\/strong><\/p>\n

Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

The study investigated the association between various\nlifestyle factors and diabetes. This study observed an association between\nfast-food consumption and diabetes mellitus (P<0.01). Among the cases, about\n20% used to take fast food more than once a week, whereas, in the control\ngroup, it was only 13%. Among the participants without diabetes, 26.9% had low\nstress and 73.1% had high stress, whereas, among the participants with diabetes,\n11.3% had low stress and 88.7% had high stress. The results showed no association between smoking habits,\nalcohol consumption, type of diet, consumption of foods with high sugar\ncontent, carbonated drinks, and coffee\/tea consumption with the status of the\ndisease. However, there was an inverse association between fast food\nconsumption and disease status (P<0.001). The consumption of white rice was\nnot associated with the status of the disease. <\/p>\n\n\n\n

The study categorized the participants into a control group and a case group. In the control group, 36 participants reported low-stress levels, while 98 reported high-stress levels. In contrast, in the cases group, only 8 participants reported low-stress levels, while 63 reported high-stress levels. The study found a statistically significant association between stress levels and disease status (P<=0.05), suggesting that higher stress levels may be a risk factor for developing diabetes (Table 2).<\/p>\n\n\n\n

Table 2: Association of diabetes mellitus and other variables<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Variable<\/strong><\/p>\n<\/td>\n

\n

Group<\/strong><\/p>\n<\/td>\n

\n

Control<\/strong><\/p>\n<\/td>\n

\n

Cases<\/strong><\/p>\n<\/td>\n

\n

Total<\/strong><\/p>\n<\/td>\n

\n

P<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

No.<\/strong><\/p>\n<\/td>\n

\n

%<\/strong><\/p>\n<\/td>\n

\n

No.<\/strong><\/p>\n<\/td>\n

\n

%<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

FH of diabetes<\/p>\n<\/td>\n

\n

No<\/p>\n<\/td>\n

\n

35<\/p>\n<\/td>\n

\n

26.1<\/p>\n<\/td>\n

\n

15<\/p>\n<\/td>\n

\n

21.1<\/p>\n<\/td>\n

\n

50<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/p>\n<\/td>\n

\n

99<\/p>\n<\/td>\n

\n

73.9<\/p>\n<\/td>\n

\n

56<\/p>\n<\/td>\n

\n

78.9<\/p>\n<\/td>\n

\n

155<\/p>\n<\/td>\n<\/tr>\n

\n

Exercise<\/p>\n<\/td>\n

\n

No<\/p>\n<\/td>\n

\n

44<\/p>\n<\/td>\n

\n

32.8<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n

\n

35.2<\/p>\n<\/td>\n

\n

69<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Yes<\/p>\n<\/td>\n

\n

90<\/p>\n<\/td>\n

\n

67.2<\/p>\n<\/td>\n

\n

46<\/p>\n<\/td>\n

\n

64.8<\/p>\n<\/td>\n

\n

136<\/p>\n<\/td>\n<\/tr>\n

\n

BMI<\/p>\n<\/td>\n

\n

Normal Weight<\/p>\n<\/td>\n

\n

32<\/p>\n<\/td>\n

\n

23.9<\/p>\n<\/td>\n

\n

22<\/p>\n<\/td>\n

\n

31.0<\/p>\n<\/td>\n

\n

54<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Overweight<\/p>\n<\/td>\n

\n

65<\/p>\n<\/td>\n

\n

48.5<\/p>\n<\/td>\n

\n

30<\/p>\n<\/td>\n

\n

42.3<\/p>\n<\/td>\n

\n

95<\/p>\n<\/td>\n<\/tr>\n

\n

Obese<\/p>\n<\/td>\n

\n

37<\/p>\n<\/td>\n

\n

27.6<\/p>\n<\/td>\n

\n

19<\/p>\n<\/td>\n

\n

26.8<\/p>\n<\/td>\n

\n

56<\/p>\n<\/td>\n<\/tr>\n

\n

Smoking habit<\/p>\n<\/td>\n

\n

Current User<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n

\n

9<\/p>\n<\/td>\n

\n

10<\/p>\n<\/td>\n

\n

14.1<\/p>\n<\/td>\n

\n

22<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Ex-User<\/p>\n<\/td>\n

\n

8<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

9.9<\/p>\n<\/td>\n

\n

15<\/p>\n<\/td>\n<\/tr>\n

\n

Never User<\/p>\n<\/td>\n

\n

114<\/p>\n<\/td>\n

\n

85.1<\/p>\n<\/td>\n

\n

54<\/p>\n<\/td>\n

\n

76.1<\/p>\n<\/td>\n

\n

168<\/p>\n<\/td>\n<\/tr>\n

\n

Alcohol use<\/p>\n<\/td>\n

\n

Current User<\/p>\n<\/td>\n

\n

29<\/p>\n<\/td>\n

\n

21.6<\/p>\n<\/td>\n

\n

11<\/p>\n<\/td>\n

\n

15.5<\/p>\n<\/td>\n

\n

40<\/p>\n<\/td>\n

\n

NS<\/p>\n<\/td>\n<\/tr>\n

\n

Ex-User<\/p>\n<\/td>\n

\n

13<\/p>\n<\/td>\n

\n

9.7<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

18<\/p>\n<\/td>\n<\/tr>\n

\n

Never User<\/p>\n<\/td>\n

\n

92<\/p>\n<\/td>\n

\n

68.7<\/p>\n<\/td>\n

\n

55<\/p>\n<\/td>\n

\n

77.5<\/p>\n<\/td>\n

\n

147<\/p>\n<\/td>\n<\/tr>\n

\n

Consumption of fast food<\/p>\n<\/td>\n

\n

Never<\/p>\n<\/td>\n

\n

18<\/p>\n<\/td>\n

\n

13.4<\/p>\n<\/td>\n

\n

23<\/p>\n<\/td>\n

\n

32.4<\/p>\n<\/td>\n

\n

41<\/p>\n<\/td>\n

\n

<0.001<\/p>\n<\/td>\n<\/tr>\n

\n

Once a week<\/p>\n<\/td>\n

\n

99<\/p>\n<\/td>\n

\n

73.9<\/p>\n<\/td>\n

\n

34<\/p>\n<\/td>\n

\n

47.9<\/p>\n<\/td>\n

\n

133<\/p>\n<\/td>\n<\/tr>\n

\n

> Once a week<\/p>\n<\/td>\n

\n

17<\/p>\n<\/td>\n

\n

12.7<\/p>\n<\/td>\n

\n

14<\/p>\n<\/td>\n

\n

19.7<\/p>\n<\/td>\n

\n

31<\/p>\n<\/td>\n<\/tr>\n

\n

Stress<\/p>\n<\/td>\n

\n

Low Stress<\/p>\n<\/td>\n

\n

36<\/p>\n<\/td>\n

\n

26.9<\/p>\n<\/td>\n

\n

8<\/p>\n<\/td>\n

\n

11.3<\/p>\n<\/td>\n

\n

44<\/p>\n<\/td>\n

\n

<0.05<\/p>\n<\/td>\n<\/tr>\n

\n

High Stress<\/p>\n<\/td>\n

\n

98<\/p>\n<\/td>\n

\n

73.1<\/p>\n<\/td>\n

\n

63<\/p>\n<\/td>\n

\n

88.7<\/p>\n<\/td>\n

\n

161<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

The chi-square test was used to assess the association.<\/p>\n\n\n\n

Crude and adjusted OR of variables associated with Diabetes Mellitus: <\/strong><\/p>\n\n\n\n

The study found that age and stress were significant risk factors for developing the disease. The crude OR for the age group between the age of 40 to 59 shows four times increase in the chance of developing diabetes mellitus, while those greater than or equal to 60 show nine times. Concerning stress, the crude OR shows three times increase in the likelihood of diabetes mellitus among those with stress. The adjusted OR for the age group between 40 to 59 also shows a four times higher chance and those above 60 show an almost ten times higher likelihood of developing diabetes mellitus. The study found that people between the ages of 40 and 59 were four times more likely to develop the disease than younger people. Similarly, people over 60 were nine times more likely to develop the disease than younger people. The study also found that people with high stress were three times more likely to develop the disease than those with low stress. This means that stress was a significant risk factor for developing the disease. (Table 3).  <\/p>\n\n\n\n

Table 3: Crude and adjusted Odds Ratio<\/strong>.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
\n

Variable<\/strong><\/p>\n<\/td>\n

\n

Group<\/strong><\/p>\n<\/td>\n

\n

Crude<\/strong><\/p>\n<\/td>\n

\n

Adjusted<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

OR<\/strong><\/p>\n<\/td>\n

\n

CI<\/strong><\/p>\n<\/td>\n

\n

OR<\/strong><\/p>\n<\/td>\n

\n

CI<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Age<\/p>\n<\/td>\n

\n

<40<\/p>\n<\/td>\n

\n

1<\/p>\n<\/td>\n

\n

—<\/p>\n<\/td>\n

\n

1<\/p>\n<\/td>\n

\n

—<\/p>\n<\/td>\n<\/tr>\n

\n

40-59<\/p>\n<\/td>\n

\n

4.1<\/p>\n<\/td>\n

\n

1.7-9.7<\/p>\n<\/td>\n

\n

4.2<\/p>\n<\/td>\n

\n

1.8-10.1<\/p>\n<\/td>\n<\/tr>\n

\n

>=60<\/p>\n<\/td>\n

\n

8.6<\/p>\n<\/td>\n

\n

2.1-34.9<\/p>\n<\/td>\n

\n

9.7<\/p>\n<\/td>\n

\n

2.3-40.6<\/p>\n<\/td>\n<\/tr>\n

\n

Stress<\/p>\n<\/td>\n

\n

Low stress<\/p>\n<\/td>\n

\n

1<\/p>\n<\/td>\n

\n

—<\/p>\n<\/td>\n

\n

1<\/p>\n<\/td>\n

\n

—<\/p>\n<\/td>\n<\/tr>\n

\n

High stress<\/p>\n<\/td>\n

\n

2.8<\/p>\n<\/td>\n

\n

1.3-6.6<\/p>\n<\/td>\n

\n

3.1<\/p>\n<\/td>\n

\n

1.3-7.3<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Discussion<\/strong><\/p>\n\n\n\n

Diabetes mellitus and Age<\/strong><\/p>\n\n\n\n

The OR observed for\nthe variable age showed a high likelihood compared to other factors; the onset\nof diabetes is closely related to the ageing process. In the last few decades,\nthe elderly population has increased worldwide, resulting in a high prevalence\nof diabetes mellites. Age was the most significant variable in this study. An\nincrease in age showed an increase in the prevalence of diabetics by several\nfolds6,7<\/sup>. The adjusted OR observed was 4.2 and 9.7, respectively. A\nsystematic review of the studies from the Arabic countries reported that more\nthan 50% of the studies agree that age is one of the main determinants of\nType-2 DM8<\/sup>. Older people have more chances to practice a sedentary\nlifestyle which may also lead to obesity and T2DM9<\/sup>.<\/p>\n\n\n\n

Diabetes mellitus and stress<\/strong><\/p>\n\n\n\n

The present study observed an association between stress and\nthe status of diabetes mellitus. A Swiss study also supports the finding of the\ncurrent study10<\/sup>. A study from the USA also observed the same\nfinding; the study reported that as the levels of depression, distress and\nanxiety decreased, a downward trend was observed in the levels of HbA1c11<\/sup>.These studies were conducted in different populations and reported the\nsame results. Growing evidence suggests that stress is associated with an\nincreased risk of developing diabetes. A study investigated the relationship\nbetween stress and diabetes and found that chronic stress may contribute to developing\nthe disease12<\/sup>. It\nis possible to conclude that there is an association between stress and\nDiabetes Mellitus.<\/p>\n\n\n\n

Diabetes mellitus and fast-food consumption<\/strong><\/p>\n\n\n\n

The present study observed an association between fast food\nconsumption and diabetes mellitus; patients who had diabetes consumed less fast\nfood. A study from Cambridge University found that more fast-food outlets\nincreased the odds of diabetes cases; for every additional two outlets per\nneighborhood can expect one additional diabetes case11,12<\/sup>.<\/p>\n\n\n\n

Another study also\nreported a strong positive association between weight gain and insulin\nresistance, suggesting that fast food increases the risk of obesity and type-2\ndiabetes13,14<\/sup>. Most\nstudies show a significant association between fast food and diabetes, while\nour study shows an inverse association. This could be because of the diet\nadvised by their physician to maintain and improve their blood glucose levels,\nas the cases included were prevalent. Most studies attempt to establish a\nrelationship between fast food consumption and diabetes, suggesting that fast\nfood contributes to the disease’s development. However, my study indicates an\ninverse relationship between fast food intake and the incidence of diabetes15,16<\/sup>.\n<\/p>\n\n\n\n

. This unexpected finding suggests that the relationship\nbetween fast food consumption and diabetes may not be as straightforward as\npreviously assumed and warrants further investigation. A Systematic Review\nobserved that statistically significant association between diabetes mellitus\nand age. The disease’s prevalence was higher among older age groups in urban\ndominance17.18<\/sup>.These studies concur with our study and\nshow a significant association between age and the prevalence of diabetes\nmellitus. <\/p>\n\n\n\n

Diabetes mellitus and, family history and BMI<\/strong><\/p>\n\n\n\n

This study did not observe any statistically\nsignificant association with a family history of diabetes mellitus, even though\nstudies have found that family history is an important risk factor for prediabetes,\nespecially for combined impaired glucose tolerance and impaired fasting glucose9,16<\/sup>.\nAlthough there was no association between BMI and Diabetes in the present\nstudy, a study in India found that the likelihood of being diabetic is higher\namong overweight and obese individuals than among non-overweight individuals19,20<\/sup>.<\/p>\n\n\n\n

Conclusion<\/strong><\/p>\n\n\n\n

This study observed a significant association between age and stress to type 2 diabetes mellitus. Based on this study, it can be inferred that age and stress are both factors associated with the development of diabetes. Specifically, the study suggests that individuals who experience high levels of stress may have an increased risk of developing diabetes and that older individuals may also be at a greater risk for developing the condition. These findings highlight the importance of managing stress and maintaining healthy lifestyle habits as people age, to reduce the risk of developing diabetes.<\/p>\n\n\n\n

Conflict of Interest<\/strong><\/p>\n\n\n\n

There is no conflict of interest.<\/p>\n\n\n\n

Funding sources<\/strong><\/p>\n\n\n\n

There are no funding sources<\/p>\n\n\n\n

References<\/strong><\/strong><\/p>\n\n\n\n

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