Abstract
Background:
In India, an estimated 77 million people above the age of 18 years suffer from diabetes (type 2), and nearly 25 million are prediabetic. More than 50% of people are unaware of their diabetic status that leads to health complications if not detected and treated early. The objective of this study was to assess the risk of diabetes among young adults using the Indian Diabetes Risk Score (IDRS).
Methods:
This cross-sectional study was conducted in the field area of a tertiary care hospital. The study included adults age group 20–40 years and excluded those unable to comprehend, bedridden patients, and those already diagnosed with type 2 diabetes mellitus. Sample size was 205. Data were collected using the IDRS scorecard and a pretested questionnaire. A house-to-house survey was conducted to collect data.
Results:
There were 205 study participants, of whom 99 (48.2%) were female and 106 (51.8%) were male. The mean age of the study population was 27.6 ± 5.74 years. Most of the study participants (97 [47.3%]) belongs to 20–25 years age group. According to the IDRS scoring, low risk was found in 95 (46.3%), medium risk in 40 (19.5%), and high risk in 70 (34.2%) study subjects.
Conclusion:
According to the total IDRS score, 46.3% of the study population was at low risk, 19.5% at moderate risk, and 34.2% at high risk. This study proves that there is a dire need for lifestyle changes for a better future. The population should be encouraged to maintain a healthy lifestyle.
Keywords: Indian diabetes risk score, rural area, screening, type 2 diabetes
INTRODUCTION
In India, an estimated 77 million people above the age of 18 years suffer from diabetes (type 2), and nearly 25 million are prediabetic. More than 50% of people are unaware of their diabetic status that leads to health complications if not detected and treated early. Between 2000 and 2019, there was a 3% increase in age-standardized mortality rates due to diabetes. In lower-middle-income countries, the mortality rate due to diabetes increased 13%.[1] India is deemed the world’s capital of diabetes. The diabetic population in the country is close to hitting the alarming mark of 69.9 million by 2025 and 80 million by 2030.[2] In India, 42.2 million people are undiagnosed diabetics. Therefore, early diagnosis of diabetes is necessary. Early diagnosis of diabetes or pre-diabetes helps individuals manage their blood glucose levels effectively. Monitoring blood glucose levels helps prevent diabetes complications. Early detection of diabetes will be helpful for patients as they can start with appropriate treatment of diabetes.[3]
The Indian Diabetes Risk Score (IDRS) helps in the diagnosis of diabetes risk. This score was developed by Dr. V. Mohan in 2005. Diabetes has several risk factors, such as age, family history of diabetes, abdominal obesity, physical inactivity, high blood pressure, unhealthy eating, smoking, and a history of gestational diabetes. The four important risk factors of diabetes- age, family history, physical activity, and abdominal obesity–are considered in the IDRS. It is simple, cost-effective, and easily applicable.[4] Screening for undetected diabetes primarily addresses the role of secondary diabetes prevention. Type 2 diabetes can be screened using risk assessment questionnaires, laboratory tests, and combinations of the two. This risk assessment tool used in diabetes screening is population-specific and can be used for population screening. The Madras Diabetes Research Foundation (MDRS) paved the way for the IDRS, which effectively screens those at high risk of developing diabetes. This score is based on an extremely large population-based study on diabetes in India, the “CURES.” This screening score has a sensitivity of 72.5% and a specificity of 60.1% in the Indian community. The advantages of this tool include no cost, non-invasiveness, simplicity, and easy applicability by the target population during mass screening programmers.[5] This study aimed to determine the risk factors among young adults in the rural population. The objectives of this study were to assess the risk of diabetes among young adults using the IDRS and to determine the factors associated with the IDRS in young adults.
METHODS
This was a cross-sectional study conducted in the field area of a tertiary care hospital. The study included adults age group 20–40 years and excluded those who were unable to comprehend, critically ill or bedridden patients, and those already diagnosed with type 2 or type 1 diabetes mellitus. Multistage sampling technique was used. The field practice area was selected conveniently; from within this area, one ward was selected by simple random sampling; and all households within the selected ward were surveyed.
Eligible study participants in households were interviewed; if multiple eligible participants were found within the household, the eldest participant was selected.
The sample size was calculated using the prevalence of medium to high risk (23%) among study participants from the study by Singh et al.[6] The calculated sample size was 197, with 6% absolute precision and 80% power at a 95% confidence interval, and the collected sample was 205.
Method of data collection
Selected adults were interviewed using the card for the Indian Diabetic Risk Score[4,5] and a pretested questionnaire with variables such as details of diet, sleep habits, alcohol consumption, smoking habits, and comorbidities.
Operational definition
IDRS score[4,5]: As per the IDRS score, for age, <35 years score is 0, 35–49 years score is 20, and ≥50 years score is 30. For abdominal obesity, waist circumference of female <80 cm and male <90 cm, the score is 0, female 80–89 cm, male 90–99 cm, the score is 10; female ≥90 cm and male ≥100 cm, the score is 20. For physical activity, the scores were as follows: vigorous exercise or strenuous work = 0, moderate exercise at work/home = 10, mild exercise at work/home = 20, and no exercise and sedentary at work/home = 30. Under family history, a score of 0 was assigned if both parents were non-diabetic, a score of 10 was assigned if either parent was diabetic, and a score of 20 was assigned if both parents were diabetic. Therefore, the maximum score is 100 and the minimum score is 0. If the score is ≥60: high risk of having diabetes. 30–50: The risk of having diabetes is moderate. <30: Risk of having diabetes is low.[7]
Statistical analysis
The data were coded and entered in a Microsoft Excel sheet and analyzed using Jamovi 2.3.28. The baseline characteristics of the study participants were expressed as frequencies, percentages, mean, and standard deviations. Frequencies and percentages were expressed for each variable. The Chi-square statistical test was used to test the significance of the differences between the variables. The level of significance was estimated with 95% confidence intervals and P values of <0.05.
Ethics declaration
Approval from the Institutional Research Committee and Institutional Ethics Committee clearance were obtained before the study was conducted. All participants and their guardians provided informed consent prior to the study. Data confidentiality and participant anonymity were strictly maintained during the study. The consent to participate and patient information sheet were aligned with ICMR guidelines and international standards, such as the Declaration of Helsinki.
RESULTS
Demographic details
There were 205 study participants, of whom 99 (48.2%) were female and 106 (51.8%) were male. Mean age of the study population is 27.6 ± 5.74 years. Most of the study participants that is 97 (47.3%) belongs to 20–25 years age group. The least number of participants, 30 (14.6%), belonged to the age group 36–40 years. 55 (55.5%) females belong to 20–25 years and 42 (39.6%) males belong to 20–25 years. Regarding the education of the study participants, most of them were graduates (110 [53.6%]), 44 (21.4%) had high school education, and 36 (17.5%) had intermittent/diploma level education. Most of the study participants were unemployed (96 [46.8%]), and 45 (21.9%) were professionals, 22 (10.7%) were skilled workers/shop/sales workers, and 16 (7.8%) were elementary workers.
Dietary and physical activity details
Among the study population, 189 (92.2%) followed a mixed diet, and 16 (7.8%) followed a vegetarian diet. Among the study subjects, 71 (34.6%) consumed fast food every day, and 64 (31.2%) consumed fast food weekly. Regarding sugar snacks, 41 (20%) of them consumed them every day, and 92 (44.8%) of them consumed it every 2–3 days. When it comes to oily snack consumption, 37 (18%) of them have it every day, and 81 (39.5%) consume it every 2–3 days. Regarding fruit consumption, 40 (19.5%) consumed it every day, 68 (33.1%) consumed every 2–3 days and 45 (25.8%) consumed it weekly. Regarding physical activity, 98 (47.8%) of them performed physical activity, and 107 (52.2%) did not. Among them, 37 (18%) performed vigorous exercise, and 16 (7.8%) performed mild exercise.
Alcohol and smoking habits of study population
Most of the study participants did not consume alcohol (149 [72.6%]), however, 22 (10.7%) consumed it weekly, and 5 (2.7%) consumed it every day and at least one PEG every day. Regarding smoking among the study participants, 162 (79.2%) did not smoke, 25 (12.2%) smoked every day with a minimum of two cigarettes, 5 (2.4%) smoked every 2–3 days, and 9 (4.3%) smoked weekly.
Sleep habits of study population
A total of 106 (51.7%) of the study population slept for 7–8 hours daily, 89 (43.5%) slept for 4–6 hours, more than 8 hours sleep for 9 (4.4%), and only one participant (0.4%) slept for less than 3 hours. With respect to difficulty falling asleep, 169 (82.5%) of them did not have any difficulty, but 36 (17.5%) of them did. Of the study participants, 152 (74.1%) felt refreshed after a night’s sleep, although 53 (25.9%) felt tired. 156 (76.1%) of the participants were satisfied with their sleep and 49 (23.9%). Six (2.9%) of the study subjects always felt mentally exhausted, 80 (39%) of the study subjects felt mental exhaustion sometimes, and 53 (26%) of the study subjects never felt exhaustion.
Morbidities among study participants
Regarding illness among the study participants, 21 (15%) had illnesses such as polycystic ovarian disease (PCOD), asthma, ITP, gout, and migraine, for which they all followed modern medicine for treatment. Of these, 184 (85%) did not have any illness that required daily medication. Five (2.4%) participants had childhood illnesses such as asthma[4] and immune thrombocytopenia (ITP),[1] and 200 (97.6%) did not have any childhood illnesses.
Anthropometric measurements of study participants
The mean waist circumference of the study participants was 87.3 ± 9.61 cm. Their mean height was 166 ± 8.63 cm and mean weight was 64.8 ± 12.9 kg. With respect to BMI classification according to the WHO, 19 (9.2%) of the participants were underweight, 111 (54.1%) had normal weight, 58 (28.2%) were overweight, and 17 (8.5%) were obese class 1.
Indian diabetic risk score and its criteria of study participants
As per Table 1, there were 133 (64.8%) study participants with age >35 years (score 0) and 72 (35.2%) of them belonged to 35–40 years (score 20). Regarding waist circumference, 93 (45.3%) subjects scored 0 (females <80 cm, male <90 cm), 69 (33.6%) subjects scored 10 (Female 80–89 cm, male 90–99 cm), and 43 (21.1%) subjects scored 20 (Female ≥90 cm, male ≥100 cm). Regarding the exercise criterion of IDRS scoring, 37 (18%) subjects scored 0 (vigorous exercise/strenuous at work), 45 (21.9%) subjects scored 10 (moderate exercise at work/home), 16 (7.8%) subjects scored 20 (mild exercise at work/home), and 107 (52.3%) subjects scored 30 (no exercise and sedentary at work/home). Regarding family history, 43 (20.9%) subjects scored 0 (two non–diabetic parents), 145 (70.7%) subjects scored 10 (either parent diabetic), and 17 (8.4%) subjects scored 20 (both parents diabetic). Therefore, low risk was found in 95 (46.3%) subjects, medium risk in 40 (19.5%) subjects, and high risk in 70 (34.2%) subjects. According to Table 2, a statistical association was found between sex distribution and IDRS score with an odds ratio of 0.230. Only sex showed a statistically significant association with IDRS risk; BMI class, diet preference, and sleep duration did not. Females were more likely to fall into the medium–high IDRS risk group, while males are more likely to be in the lowrisk group, with a highly significant P value (<0.001). Body mass index (BMI) (normal vs. obese) and diet (mixed vs vegetarian) have similar proportions of low and medium–high risk, with P values >0.05 and odds ratios whose confidence intervals include 1. Sleep duration (<7 vs. ≥7 hours) showed a nonsignificant trend toward association with IDRS risk (P ≈ 0.076).
Table 1.
IDRS criteria and scoring of study participants
| Criteria of IDRS | Score 0 (%) | Score 10 (%) | Score 20 (%) | Score 30 (%) |
|---|---|---|---|---|
| Age | >35 years | - | 35–40 | ≥50 years |
| 133 (64.8) | - | 72 (35.2) | - | |
| Waist circumference | Female ˂80 cm, male <90 cm | Female 80-89 cm, male 90–99 cm | Female ≥90 cm, male ≥100 cm | - |
| 93 (45.3) | 69 (33.6) | 43 (21.1) | - | |
| Exercise | Vigorous exercise/strenuous at work | Moderate exercise at work/home | Mild exercise at work/home | No exercise and sedentary at work/home |
| 37 (18) | 45 (21.9) | 16 (7.8) | 107 (52.3) | |
| Family history | Two non-diabetic parents | Either parent diabetic | Both parents’ diabetic | - |
| 43 (20.9) | 145 (70.7) | 17 (8.4) | - | |
| Total score | Low risk ≤30 (%) | Medium risk 30–50 (%) | High risk ≥60 (%) | - |
| 95 (46.3) | 40 (19.5) | 70 (34.2) | - |
IDRS=Indian Diabetes Risk Score
Table 2.
Association of IDRS risk categories and various variables of study participants
| Variable | Categories | Low risk (%) | Medium-high risk (%) | P | Odd’s ratio |
|---|---|---|---|---|---|
| BMI class | Normal | 60 (46.2) | 70 (53.8) | 0.943 df=1 X2=7.91 | 0.980 CI=0.554–1.73 |
| Obese | 35 (46.7) | 40 (53.3) | |||
| Sex | Female | 28 (28.2) | 71 (71.8) | *<0.001 df=1 X2=25.1 | 0.230 CI=0.127–0.414 |
| Male | 67 (63.2) | 39 (36.8) | |||
| Diet preference | Mixed | 91 (46.2) | 106 (53.8) | 0.862 df=1 X2=0.03 | 1.14 CI=0.250–5.25 |
| vegetarian | 3 (42.9) | 4 (57.1) | |||
| Sleep hours | ≥7 | 47 (40.9) | 68 (59.1) | 0.076 df=1 X2=3.15 | 0.605 CI=0.347–1.06 |
| <7 | 48 (53.3) | 42 (46.7) |
*Significant association. IDRS=Indian Diabetes Risk Score
DISCUSSION
This study was conducted to determine the diabetes risk using the Indian diabetic risk score among 205 young adults in a rural area. Other variables such as details of diet, sleep habits, alcohol consumption, smoking habits, and comorbidities were also assessed among the adults. The study population contained more males (51.8%) than females (48.2%) compared to a study done in Chennai to assess IDRS, which had 39% females and 61% males.[8] 53.6% of the study population had a graduate level of education. Of the study population, 46.8% were unemployed, as most of them were students.
In the current study, only 7.8% of the study participants followed a vegetarian diet compared to 32.8% in a study conducted by the South Asian Network for Chronic Diseases in different cities, such as Nagpur, Lucknow, Hyderabad, and Bangalore. In our study, the proportion of vegetarians was comparable to that of Hyderabad that was 10.1%.[9] In this study, 19.5% of the study subjects had fruits daily compared to 10% of sample in a study done in New Delhi by Agrawal S under South Asian Network for Chronic Diseases.[10] In this study 34.6% of them consumed fast food everyday compared to a study was conducted in Puducherry by Rajini et al.[11] where only 4.2% consumed fast food every day. The comparatively high proportion of fast food consumption may be because the majority of the population were college graduates, and their main meals and snacks must be from nearby restaurants or coffee shops, which explains the high percentage of oily food consumption (39.5%) every 2–3 days a week and consumption of sugar snacks (44.8%) every 2–3 days a week. Regarding physical activity, 18% of the study subjects follow vigorous physical activity and more than half of the study participants does not follow any physical activity, compared to a study was conducted in Kerala among rural population by Saju et al.[12] where 15.9% of them practiced vigorous physical activity and in a study done in Delhi where only 23% of study participants did not exercise at all, also compared to the study done in Delhi where only 23% of study population did not exercise at all.[9]
Considering alcohol consumption, 72.6% of the participants did not consume any amount of alcohol compared to 66.95% of participants, who did not consume alcohol in a study conducted in New Delhi by the South Asian Network for Chronic Diseases.[10] In our study, 2.7% of the participants consumed at least one PEG every day compared to 1.7% of the participants in the same study conducted by the South Asian Network for Chronic Diseases.[10] In this study, 12.2% of the participants smoked every day and 79.2% did not smoke at all, compared to the study conducted in Kerala among the rural population by Saju et al.,[12] where 13.6% smoked and 86.4% of the participants did not smoke at all. In this study, 28.2% of the study population was overweight, and 54.1% had a normal BMI, compared to a study was conducted in Pondicherry, where 41.2% had a normal BMI.[8] According to IDRS, this study showed, 46.3% had low risk, 19.5% had medium risk and 34.2% had high risk compared to a study conducted among college students in New Delhi, 77% had low risk, 22% had medium risk and 1% had high risk.[9] Also compared to a study done by Jain et al.[13] in an urban area of Jhalawar, 12.7% subjects were in low risk, 59.1% subjects were in medium risk and 28.2% were in high risk. According to the IDRS criteria, age and family history are non-modifiable risks, and waist circumference and exercise are criteria that can be modified; hence, the risk calculated as high or medium can be changed to low risk by following physical activities.
CONCLUSION
This study proves that there is dire need for change in lifestyle for the better future. The importance of physical activity must be given as health education to the population and reinforced to carry out exercises for at least 30–60 min of daily activity. Our population needs to increase their intake of seasonal fruits, vegetables, and whole grains, and limit their intake of unhealthy fats, such as fried food items. It is better to aim for a low-sodium diet and limit processed foods. sugar intake. Quitting smoking and alcohol consumption are some of the most impactful actions that can improve health and prevent diseases. In addition, the population should be encouraged to maintain a healthy weight along with good quality sleep each night for optimum health. There should be an emphasis on the significance of concentrating and stepping up health promotion, information education, and communication efforts among the youth population to lower the burden of disease in the future. To prevent or delay the onset of diabetes mellitus and its complications in later life, it is imperative that at-risk populations are identified and awareness is raised among the young population. Better implementation and encouragement of making healthier choices can be achieved by enacting measures such as a sugar tax or imposing behavior change communication and fat tax. Limitations: There may be observational errors in the measurement of weight, height, and waist circumference.
Author contributions
JRJ: Concepts, design, definition of intellectual content, literature search, data acquisition, data analysis, statistical analysis, manuscript preparation, manuscript editing, manuscript review. SGI: Concepts, design, definition of intellectual content, manuscript editing, manuscript review. NKS: Data analysis, statistical analysis. AGC, AG, AR, VM, STK, AA, AS, and KR: Literature search, data acquisition, manuscript preparation, manuscript editing, manuscript review.
Ethics approval and consent to participate
Ethics approval obtained from Institutional Ethics Committee, IEC no. AAMC/IEC/2023-2024/2. Consent to participate was obtained from participants and their legal guardians. This study was conducted in accordance with the principles outlined in the ICMR guidelines and Declaration of Helsinki for research involving human subjects.
Conflict of interest
Nil.
Data availability statement
Data will be made available from the corresponding author on request.
Funding Statement
Nil.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data will be made available from the corresponding author on request.