Published online Jan 15, 2019. doi: 10.4239/wjd.v10.i1.37
Peer-review started: November 26, 2018
First decision: December 9, 2018
Revised: December 20, 2018
Accepted: January 3, 2019
Article in press: January 4, 2019
Published online: January 15, 2019
BKL Walawalkar Hospital is situated near the village of Dervan in the Kokan region of the state of Maharashtra in India. A survey of 2200 surrounding villages showed 51.8% adults had body mass index (BMI) below <18.5 kg/m2 and only 4.5% were overweight. A survey of 11521 adolescent girls from rural schools showed 64% prevalence of thinness. In the same region, government survey reported the prevalence of diabetes around 7%, and 70% prevalence of leanness. This reinforced the fact that the overall population of Kokan is lean. Hence, we decided to investigate body composition of diabetic people from our hospital clinic by carrying out a clinic-based case control study.
To study body composition of diabetics in a rural clinic of Kokan.
In a case-control study, 168 type 2 diabetic patients (102 men) attending the outpatient department at a rural hospital and 144 non-diabetic controls (68 men) in the Chiplun area of the Kokan region were recruited. History of diabetes (age of onset, duration), anthropometric measurements (height, weight, waist and hip circumference) were recorded. Body composition was measured by bioimpedance using the TANITA analyzer.
More than 45% of diabetic subjects had a 1st degree family history of diabetes, and more than 50% had macrovascular complications. The average BMI in diabetic subjects was 24.3 kg/m2. According to World Health Organization standards, prevalence of underweight was 8% and that of normal BMI was around 50%. Underweight and normal diabetic subjects (men as well as women) had significantly lower body fat percentage, higher muscle mass percentage, lower visceral fat and lower basal metabolic rate when compared to their overweight counterparts.
The diabetic population in Kokan has near normal body composition, and BMI has considerable limitations in assessing body composition and it also lacks sensitivity for assessing risk for diabetes in this population. High prevalence of family history of diabetes may point towards genetic predisposition. Leanness is an inherent characteristic of this population and its metabolic significance needs further investigations with a larger sample size.
Core tip: As per government survey, leanness is widespread in Kokan but diabetes is also on the rise. We studied lean body mass in diabetics in our clinic. Lean individuals had lower body mass index but better percent muscle mass compared to overweight. This could be metabolic response to less caloric intake despite heavy physical activity. This mechanism needs to be clarified. The diabetic population in Kokan has near normal body composition and body mass index has considerable limitations. Therefore, the physiological process producing these deviations in body composition and its metabolic significance need further investigations on larger scale.
- Citation: Suvarna P, Shruti K, Maruti D, Charudatta J. Diabetes in the Kokan region of India. World J Diabetes 2019; 10(1): 37-46
- URL: https://www.wjgnet.com/1948-9358/full/v10/i1/37.htm
- DOI: https://dx.doi.org/10.4239/wjd.v10.i1.37
Recent years have seen a considerable increase in the burden of chronic non-communicable diseases (diabetes, hypertension and coronary heart disease) in clinical practice in urban India. Recent studies in urban populations have shown an unexpectedly high prevalence of diabetes, and the prevalence is rising rapidly[1]. Type 2 diabetes mellitus (T2DM), previously called non-insulin dependent diabetes mellitus (or NIDDM) is a familial disease, on the verge of becoming a pandemic in developing countries like India[2].T2DM is the most prevalent form of diabetes seen in India and constitutes more than 95% of the diabetic population[3]. Migrant Indians in Canada, Britain, the Netherlands, United States and Singapore also have a higher prevalence of diabetes compared to the native populations[4-8].
In contrast, the prevalence of diabetes and coronary heart disease in rural India has been shown to be low. However, there are very few prevalence studies in rural India[9-11] due to remoteness of the villages and lack of health infrastructure for epidemiological studies. Rapid socio-economic developments over the last 2 decades have made the rural population particularly vulnerable to non-communicable diseases. Therefore, there is a need to obtain reliable data on non-communicable diseases in rural India, study the risk factors, and plan effective preventive measures.
In Europe and America, the majority of patients with T2DM are obese. In 1965, Tripathyand Kar[12] highlighted leanness among elderly diabetics in India. Other studies in India have reported a prevalence of low body weight/lean T2DM ranging from 1.6% to 26%[13,14]. A review by Dulloo et al[15]highlighted limitations of body mass index (BMI) in assessment of body composition and lack of sensitivity for assessing disease risk, particularly in those who have normal or slightly elevated body weight.
BKL Walawalkar Hospital, situated near the village of Dervan in Ratnagiri district of the state of Maharashtra, has actively promoted rural health care through a variety of education and holistic outreach programs for more than 22 years. The hospital serves the poor socio-economic class populations of the adjoining villages. In 2003-2010 our hospital carried out house-to-house surveys of 2200 villages in the area. In this survey, 51.8% of the subject had BMI < 18.5 kg/m2 and only 4.5% were overweight, with BMI > 25 kg/m2. A survey of 11521 adolescent girls from rural schools conducted between 2011 and 2017 showed that 64% of the girls were in grade 1 to 3 of thinness, based upon International Obesity Task Force standards. Stunting was seen in 22% to 28% of the girls. Thus, the overall population of Kokan is lean in their body stature.
The National Family Health Survey[9] conducted by the government of India reported on the prevalence of diabetes in the same region based on random blood sugar as 9% among men and 5.8% among women. The same survey also reported more than 70% prevalence of leanness based on BMI among men as well as women. This again reinforced the leanness of the population of Kokan. Hence, we decided to investigate more about body composition of diabetic people from our hospital clinic by carrying out a clinic-based case control study. The health infrastructure in our hospital provided us the opportunity to study the profile of diabetic as well as non-diabetic subjects.
This study was carried out in the outpatient department of BKL Walawalkar Hospital and Rural Medical College in the Ratnagiri district.
Diabetic patients from the outpatient department were enrolled in the study. Non-diabetic control subjects were mostly spouses of the patients in the hospital or were from the hospital staff.
The following data was recorded from the clinical history for diabetic subjects: age at diagnosis of diabetes; family history of diabetes; and history of macrovascular complications (hypertension, ischemic heart disease, cardiovascular disease and cerebral vascular disease) and microvascular complications (nephropathy, neuropathy and retinopathy).
The following anthropometric parameters were measured on diabetic as well as non-diabetic subjects: height; weight; waist and hip circumferences. BMI and waist-to-hip ratio (commonly known as WHR) were calculated. Subjects were classified as underweight, normal and overweight using World Health Organization standards for BMI[16]. Those with BMI < 25 kg/m2, that is those who were underweight or normal, were classified as lean. We used International Diabetes Federation criteria[17] for the waist circumference to classify the subjects as centrally obese.
Body composition was assessed on all the subjects using the Tanita BC 420-MA analyzer (Tanita Corporation, Tokyo, Japan). It measured bioelectrical impedance by passing alternating current through the subject to measure the water content. Body composition measurements (fat mass, lean mass, total body water) were obtained as mass as well as percentage. In addition, we also obtained visceral fat, fat free mass, total body water (TBW) as mass as well as percentage, and basal metabolic rate (BMR).
In total, 201 diabetic subjects reported to the outpatient department of medicine. Those with diabetes with pregnancy, severe chronic illness, pancreatic disease and type-1 diabetes were excluded. After these, 168 diabetic subjects (102 men) were left to form the sample of diabetic subjects. We recruited 144 non-diabetic control subjects (68 men).
Data is presented as mean ± SD for continuous and as percent for categorical variables. Analysis of variance and χ2 test was used to compare continuous and categorical variables for differences in groups. Comparison of anthropometric parameters between diabetic and non-diabetic subjects was adjusted for current age. All analyses were performed using SPSS 16.0 (SPSS Inc., Chicago, IL, United States).
Informed and written consent was obtained from all the subjects for use of their data. Ethical approval from the institute’s ethics committee was also obtained for the data analysis.
Our institute’s ethics committee is registered with the government of India. Earlier, its registration number was EC/755/INST/MH/2015. The registration expired in August 2018 and was subsequently renewed, with the new registration number as EC/755/INST/MH/2015/RR-18.
The study was conducted from January 2018 to June 2018.
Table 1 shows clinical characteristics (age, anthropometry and body composition measurements) of subjects. Non-diabetic subjects (men as well as women) were significantly younger (P < 0.001). In diabetic subjects the mean age of diagnosis of diabetes was similar for men and women. Height was similar in both sexes, when comparing diabetic and non-diabetic. Diabetic women were heavier and had higher BMI. Diabetic women also had higher hip circumference. Both diabetic men and women had significantly higher WHR. Body fat percentage as well as mass was similar in diabetic and non-diabetic men but it was significantly higher in diabetic women. In both sexes the muscle mass percentage was similar between diabetics and non-diabetics but diabetic men had higher muscle mass. Diabetic women had higher visceral fat. Diabetic and non-diabetic subjects (men as well as women) had similar TBW and TBW% but BMR was higher in diabetic women compared to non-diabetic women.
| Diabetic | Non-diabetic | P for diabetic vs non-diabetic | ||||
| Men, n = 102 | Women, n = 66 | Men, n = 68 | Women, n = 76 | Men | Women | |
| Age | ||||||
| Current age | 55.2 (13.1) | 57.9 (9.5) | 41.7 (12.0) | 38.2 (10.2) | 0.000 | 0.000 |
| Age at diagnosis | 48.7 (12.1) | 50.9 (10.5) | ||||
| Anthropometry | ||||||
| Height, cm | 164.2 (6.4) | 151.1 (6.3) | 162.7 (8.4) | 152.1 (7.7) | 0.17 | 0.13 |
| Weight, kg | 64.7 (11.7) | 56.6 (12.1) | 59.9 (13.5) | 50.4 (11.9) | 0.27 | 0.001 |
| BMI, kg/m2 | 24.0 (3.9) | 24.7 (4.9) | 22.5 (4.3) | 21.7 (4.4) | 0.45 | 0.002 |
| Waist circumference,cm | 92.0 (9.9) | 87.5 (11.4) | 81.3 (12.6) | 76.0 (9.8) | 0.000 | 0.000 |
| Hip circumference, cm | 94.2 (9.2) | 97.3 (11.9) | 89.8 (10.3) | 89.4 (10.5) | 0.22 | 0.000 |
| WHR | 0.98 (0.08) | 0.90 (0.09) | 0.90 (0.09) | 0.85 (0.07) | 0.000 | 0.045 |
| Body composition by bio-impedance | ||||||
| Body fat, % | 22.6 (5.7) | 35.6 (6.8) | 21.3 (6.8) | 30.5 (7.2) | 0.87 | 0.026 |
| Body fat, kg | 15.2 (6.2) | 21.2 (8.4) | 14.1 (8.7) | 15.7 (6.3) | 0.89 | 0.000 |
| Muscle mass, % | 73.2 (5.4) | 60.7 (6.4) | 72.9 (8.7) | 64.4 (10.5) | 0.13 | 0.38 |
| Muscle mass, kg | 46.7 (5.9) | 33.6 (4.4) | 43.4 (8.1) | 33.4 (7.1) | 0.03 | 0.19 |
| Visceral fat level | 12.1 (4.4) | 7.2 (2.6) | 8.6 (5.3) | 4.6 (2.9) | 0.23 | 0.019 |
| Fat free mass, kg | 49.3 (6.3) | 35.6 (4.8) | 46.1 (8.2) | 34.8 (6.3) | 0.068 | 0.057 |
| TBW, % | 54.0 (3.6) | 46.7 (3.6) | 53.5 (3.5) | 48.3 (5.7) | 0.69 | 0.077 |
| TBW, kg | 34.7 (5.4) | 25.6 (4.0) | 31.8 (6.0) | 24.5 (4.6) | 0.12 | 0.056 |
| BMR, calories/time | 1350.2 (188.9) | 1059.8 (168.9) | 1291.0(231.4) | 1043 (185.6) | 0.30 | 0.004 |
Table 2 shows the categorical data. In diabetic subjects the proportion of those with 1st and 2nd degree family history of diabetes was similar in both sexes. No control subject had family history of diabetes. A substantial number (around 70%) of diabetic subjects reported macrovascular complications. Diabetics (men as well as women) had higher proportion of those overweight and centrally obese compared to their non-diabetic counterparts.
| Diabetic | Non-diabetic | P for diabetic vs non-diabetic | ||||
| Men, n = 102 | Women, n = 66 | Men, n = 68 | Women, n = 76 | Men | Women | |
| Diabetes history | ||||||
| Family history | ||||||
| 1st degree | 45 (44) | 34 (51) | ||||
| 2nd degree | 7 (7) | 9 (14) | ||||
| Complications | ||||||
| Macrovascular | 72 (69.9) | 47 (71.2) | ||||
| Microvascular | 13 (12.1) | 1 (1.5) | ||||
| Underweight | 8 (7.8) | 7 (10.6) | 13 (19.1) | 20 (26.3) | ||
| Normal | 54 (52.9) | 27 (40.9) | 35 (51.5) | 41 (53.9) | 0.07 | 0.001 |
| Overweight | 40 (39.2) | 32 (48.5) | 20 (29.4) | 15 (41.9) | ||
| Centrally obese | 59 (58) | 49 (74) | 19 (28.4) | 29 (39.7) | 0.000 | 0.000 |
In diabetic subjects of both sexes, those lean had significantly lower body fat (percentage as well as mass), lower muscle mass but high muscle mass percentage, lower visceral fat, lower fat free mass, higher total TBW%, but lower TBW and BMR compared to their overweight counterparts. Similar differences were observed in non-diabetic subjects between those lean and overweight of both sexes, except for TBW% which was similar in lean and overweight non-diabetic women (Tables 3 and 4).
| Diabetic, n = 168 | P-value for lean vs overweight | |||||
| Men, n = 102 | Women, n = 66 | Men | Women | |||
| Lean, n = 62 | Overweight, n = 40 | Lean, n = 34 | Overweight, n = 32 | |||
| Body fat, % | 19.6 (4.4) | 27.5 (4.0) | 30.6 (4.7) | 40.9 (4.1) | 0.000 | 0.000 |
| Body fat, kg | 11.5 (3.5) | 21.0 (5.1) | 15.3 (5.4) | 27.2 (6.7) | 0.000 | 0.000 |
| Musclemass, % | 76.2 (4.1) | 68.5 (3.8) | 65.4 (4.4) | 55.7 (3.9) | 0.000 | 0.000 |
| Musclemass, kg | 43.8 (4.7) | 51.3 (4.7) | 31.1 (2.9) | 36.3 (4.1) | 0.000 | 0.000 |
| Visceral fat level | 10.0 (3.9) | 15.3 (3.1) | 5.2 (1.6) | 9.3 (1.7) | 0.000 | 0.000 |
| Fat free mass, kg | 46.2 (4.9) | 54.1 (4.9) | 32.8 (3.2) | 38.5 (4.4) | 0.000 | 0.000 |
| TBW, % | 55.3 (3.6) | 52.0 (2.5) | 48.6 (3.5) | 44.5 (2.4) | 0.000 | 0.000 |
| TBW, kg | 31.9 (4.1) | 39.0 (4.4) | 23.1 (2.3) | 28.6 (3.6) | 0.000 | 0.000 |
| BMR, calories/time | 1251.6 (139.1) | 1502.3 (152.5) | 953.7 (100.8) | 1172.7 (153.3) | 0.000 | 0.000 |
| Non-diabetic, n = 144 | P-value for lean vs overweight | |||||
| Men, n = 68 | Women, n = 76 | Men | Women | |||
| Lean, n = 48 | Overweight, n = 20 | Lean, n = 61 | Overweight, n = 15 | |||
| Body fat, % | 18.8 (6.3) | 27.6 (2.6) | 28.4 (5.5) | 39.1 (6.9) | 0.000 | 0.000 |
| Body fat, kg | 11.0 (6.6) | 21.5 (9.1) | 13.6 (4.5) | 24.7 (5.4) | 0.000 | 0.000 |
| Musclemass, % | 75.5 (8.1) | 68.7 (7.1) | 65.9 (10.8) | 58.1 (6.4) | 0.000 | 0.000 |
| Musclemass, kg | 40.7 (6.0) | 50.1 (8.6) | 32.0 (6.2) | 38.9 (7.8) | 0.000 | 0.000 |
| Visceral fat level | 6.2 (4.3) | 14.3 (1.9) | 3.6 (1.9) | 8.8 (2.2) | 0.000 | 0.000 |
| Bone mass, kg | 2.2 (0.4) | 2.8 (0.3) | 1.8 (0.4) | 2.3 (0.5) | 0.000 | 0.000 |
| Fat free mass, kg | 42.7 (6.6) | 54.1 (5.7) | 33.3 (4.7) | 41.0 (8.5) | 0.000 | 0.000 |
| TBW, % | 54.6 (3.5) | 51.0 (1.9) | 48.8 (6.1) | 46.1 (3.1) | 0.000 | 0.075 |
| TBW, kg | 29.0 (4.3) | 38.5 (4.1) | 23.3 (3.3) | 29.4 (5.8) | 0.000 | 0.000 |
| BMR, calories/time | 1196.2 (185.2) | 1521.5 (159.6) | 1001.2 (148.4) | 1228.7 (221.8) | 0.000 | 0.000 |
There are many reports on the profile of diabetic subjects in rural regions of India[18-28] but this is the first report from the Ratnagiri district of the Kokan area. Although from a small sample size, our data demonstrated that more than 50% of the men as well as the women subjects with diabetes were lean with a BMI well below the normal BMI cutoff of 25 kg/m2. Our study is clinic-based and not community-based. The National Family Health Survey[9] conducted by the government of India determined the prevalence of diabetes in the same region based on random blood sugar, being 9% among men and 5.8% among women. The same survey also found more than 70% prevalence of leanness based on BMI among men as well as women. This could be because the population in this region is constitutionally small.
Body composition depends on genetic makeup, dietary habits, physical activities, and susceptibility to chronic illness. Lean diabetes has been described in many populations across the world[29,30], and there have been extensive reports on lean diabetes in India. A prospective study across nine centers in India found about one-fourth of T2DM patients to be lean or with BMI below 19 kg/m2. Prevalence of type 2 lean DM across the centers varied from 11% to 25%[13]. A recent report[31] showed significantly higher prevalence of T2DM without overweight and obesity in Indians compared to white Caucasians in the United States. Diabetes in lean patients has been described before[32,33]. There are reports on lean diabetes from other regions of South Asia, India, and Africa[29,34,35]. Populations described in these reports were lean, had a history of childhood malnutrition, and had poor socioeconomic status.
Another notable observation in our subjects was the increased muscle mass percentage but low BMR in lean subjects compared to those overweight subjects. Usually, BMR is directly proportional to muscle mass and as a metabolic response to starvation, the the primary concern is to supply energy to the brain[36]. In our study, the BMR was less in spite of better muscle mass. This could be because of less caloric intake despite heavy physical activity. Adverse intrauterine or early postnatal environment with insufficient nutrients has been suggested as a mechanism of beta cell failure in lean diabetics[29]. Another Indian study[37] found that type 2 diabetics had an unfavorable body fat distribution, with an increase in visceral fat compared to that in non-diabetics. However, there are differing opinions on the causality of this association[38,39].
Visceral fat is more important than total body fat, as excess visceral fat is a risk factor for both pre-diabetes and diabetes, being more so in Indians compared to other Asian populations. In our study, the diabetic subjects had higher visceral fat, and within the diabetics those who are lean had significantly lower visceral fat. Significantly higher muscle mass percentage in the low and normal BMI group of diabetics than in those overweight shows that BMI has limitations pertaining to detailing of body composition. This striking peculiarity in type 2 diabetics in our subjects is bound to influence the natural history of diabetes and it needs further study.
The Kokan region is characterized by mountainous terrain with poor soil quality, hot humid weather, poverty and deep-rooted superstitions which have led to widespread malnutrition amongst people[40]. Our hospital is located in a remote, rural area, and our study population is from a tribal region. A study from our center on 1290 school-going rural adolescents found underweight prevalence of 72%[41]. In a pilot study on adolescent girls from Kokan, a high prevalence of micronutrient deficiencies was also found. More than 65% were deficient in calcium, zinc and folic acid, and were malnourished[42]. In our hospital, 41.9% of the babies delivered were low birth weight (birth weight < 2500 g)[43]. The Tata Memorial Rural Out Reach Program (known as TMCROP) was implemented by our hospital in all 2200 villages in Kokan, and all villagers were screened for cancer by household survey. In that survey, 51.7% population had a BMI less than 18.5 kg/m2and only 4.5% could be classified as obese. These findings highlighted the leanness of the population of Kokan.
In our current study, more than 40% had family history for diabetes, which may suggest genetic predisposition; although, we do not have any genetic data on our subjects. Inadequacy of BMI in distinguishing leanness has suggested future studies should investigate the role of body composition in the development of lean diabetes[44].
Our study has some notable strengths. It has yielded the first report from the Kokan region, where malnutrition is very much prevalent. Unlike many other reports on diabetic subjects from other regions of India[18-28], we have collected the data on body composition. There are, also, many limitations to our study. The sample size is small and it used cross-sectional data from a rural diabetic clinic. No sample size calculations were done. We were only able to recruit a smaller number of controls, making the study prone to bias. We were constrained by the remoteness of the area where the hospital is situated. We could not use Dual-Energy X-Ray Absorptiometry (commonly known as DEXA; the current gold standard for body composition) because of the high equipment costs. We measured the body composition by bioelectrical impedance, using the TANITA body composition analyzer, which is a low cost, convenient and noninvasive technology, but concerns have been raisedin the past about the validity of the analyzer[45,46] and there is an urgent need to develop an ethnicity-specific equation for the Asian Indian population. We could not report on other cardiovascular risk markers (lipids, blood pressure) nor on the socioeconomic status of the participants as very little data were available as a part of patient history. We are aware of the fact that these subjects were diagnosed with diabetes at much earlier age. Recruitment of controls from the hospital setting has induced inherent selection bias. Thus, there is a need for a large community-based prospective study investigating the role of lean mass in development of diabetes in this region.
To conclude, we attempted to investigate the role of lean body mass in development of diabetes in the predominantly underweight diabetic population of Kokan. The underlying mechanism of lean diabetes has not yet been fully explored and more studies are needed. The diabetic population in Kokan has near-normal body composition, and BMI has considerable limitations. Therefore, the physiological process producing these deviations in body composition and its metabolic significance need further investigations using larger sample sizes.
Recent years have seen a considerable increase in the burden of diabetes, hypertension and coronary heart disease in clinical practice in urban India. Recent studies in urban populations have shown an unexpectedly high prevalence of diabetes, and the prevalence is rising rapidly.
BKL Walawalkar Hospital carried out house-to-house surveys of 2200 villages in 2003-2010. In that survey, 51.8% of the subjects hadbody mass index (BMI) < 18.5 kg/m2 and only 4.5% were overweight, with BMI > 25 kg/m2. Another survey of 11521 adolescent girls from rural schools that was conducted in 2011-2017 showed that 64% of the girls had grade 1 to 3 thinness, based on the International Obesity Task Force standards, and stunting was seen in 22% to 28% of the girls. Thus, the overall population of Kokan is lean in their body stature. The same survey also found a more than 70% prevalence of leanness based on BMI among men as well as women. This, again, reinforced the leanness of the population of Kokan.
In order to investigate body composition of diabetic people from the BKL Walawalkar Hospital Clinic, a clinic-based case control study was carried out.
One hundred sixty-eight type 2 diabetic patients (102 men) attending the outpatient department at a rural hospital and 144 non-diabetic controls (68 men) in the Chiplun area of the Kokan region were recruited. History of diabetes and anthropometric measurements were recorded, and body composition was measured by bioimpedance using the TANITA analyzer. All analyses were performed using SPSS 16.0 statistical software.
In this study, more than 45% of diabetic subjects had a 1st degree family history of diabetes, and more than 50% had macrovascular complications. The average BMI in the diabetic subjects was 24.3 kg/m2. Underweight and normal diabetic subjects (men as well as women) had significantly lower body fat percentage, higher muscle mass percentage, lower visceral fat and lower basal metabolic rate compared to their overweight counterparts. Our data pave the way for a new theory of undernutrition as a risk factor in predisposing the Kokan population to diabetes.
Undernutrition should also be considered as a risk factor for diabetes in lean patients. The molecular basis and physiological adaptations to undernutrition need to be explored.
Lean diabetics had significantly lower body fat percentage, higher muscle mass percentage, lower visceral fat and lower basal metabolic rate compared to overweight diabetics. This could indicate a metabolic response to less caloric intake despite heavy physical activity, and this mechanism needs to be investigated. The diabetic population in Kokan has near-normal body composition and BMI has considerable limitations. Therefore, the physiological process producing these deviations in body composition and its metabolic significance need further investigations on a larger scale.
Faculty of Medicine Department, BKL Walawalkar Rural Medical College.
Manuscript source: Unsolicited manuscript
Specialty type: Endocrinology and metabolism
Country of origin:India
Peer-review report classification
Grade A (Excellent): 0
Grade B (Very good): 0
Grade C (Good): C, C
Grade D (Fair): D, D
Grade E (Poor): 0
P- Reviewer: Avtanski D, Beltowski J, Koch TR, Surani S S- Editor: Ma YJ L- Editor: Filipodia E- Editor: Wu YXJ
| 1. | Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004;27:1047-1053. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 9344] [Cited by in F6Publishing: 8746] [Article Influence: 437.3] [Reference Citation Analysis (1)] |
| 2. | International Diabetes Federation. IDF Diabetes Atlas. Brussels: International Diabetes Federation 2017; . [Cited in This Article: ] |
| 3. | India State-Level Disease Burden Initiative Diabetes Collaborators. The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990-2016. Lancet Glob Health. 2018;6:e1352-e1362. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 256] [Cited by in F6Publishing: 227] [Article Influence: 37.8] [Reference Citation Analysis (0)] |
| 4. | Anand SS, Yusuf S, Vuksan V, Devanesen S, Teo KK, Montague PA, Kelemen L, Yi C, Lonn E, Gerstein H, Hegele RA, McQueen M. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet. 2000;356:279-284. [PubMed] [Cited in This Article: ] |
| 5. | Hanif MW, Valsamakis G, Dixon A, Boutsiadis A, Jones AF, Barnett AH, Kumar S. Detection of impaired glucose tolerance and undiagnosed type 2 diabetes in UK South Asians: an effective screening strategy. Diabetes ObesMetab. 2008;10:755-762. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 20] [Cited by in F6Publishing: 21] [Article Influence: 1.3] [Reference Citation Analysis (0)] |
| 6. | Chandie Shaw PK, Vandenbroucke JP, Tjandra YI, Rosendaal FR, Rosman JB, Geerlings W, de Charro FT, van Es LA. Increased end-stage diabetic nephropathy in Indo-Asian immigrants living in the Netherlands. Diabetologia. 2002;45:337-341. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 54] [Cited by in F6Publishing: 47] [Article Influence: 2.1] [Reference Citation Analysis (0)] |
| 7. | Mohanty SA, Woolhandler S, Himmelstein DU, Bor DH. Diabetes and cardiovascular disease among Asian Indians in the United States. J Gen Intern Med. 2005;20:474-478. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 62] [Cited by in F6Publishing: 61] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
| 8. | Tan CE, Emmanuel SC, Tan BY, Jacob E. Prevalence of diabetes and ethnic differences in cardiovascular risk factors. The 1992 Singapore National Health Survey. Diabetes Care. 1999;22:241-247. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 145] [Cited by in F6Publishing: 150] [Article Influence: 6.0] [Reference Citation Analysis (0)] |
| 9. | International Institute of Population Sciences. National Family Health Survey, India: Key Findings from NFHS-4. Available from: http://rchiips.org/nfhs/factsheet_NFHS-4.shtml. [Cited in This Article: ] |
| 10. | Geldsetzer P, Manne-Goehler J, Theilmann M, Davies JI, Awasthi A, Vollmer S, Jaacks LM, Bärnighausen T, Atun R. Diabetes and Hypertension in India: A Nationally Representative Study of 1.3 Million Adults. JAMA Intern Med. 2018;178:363-372. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 169] [Cited by in F6Publishing: 197] [Article Influence: 32.8] [Reference Citation Analysis (0)] |
| 11. | Anjana RM, Deepa M, Pradeepa R, Mahanta J, Narain K, Das HK, Adhikari P, Rao PV, Saboo B, Kumar A, Bhansali A, John M, Luaia R, Reang T, Ningombam S, Jampa L, Budnah RO, Elangovan N, Subashini R, Venkatesan U, Unnikrishnan R, Das AK, Madhu SV, Ali MK, Pandey A, Dhaliwal RS, Kaur T, Swaminathan S, Mohan V. Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR-INDIAB population-based cross-sectional study. Lancet Diabetes Endocrinol. 2017;5:585-596. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 397] [Cited by in F6Publishing: 403] [Article Influence: 57.6] [Reference Citation Analysis (0)] |
| 12. | Tripathy BB, Kar BC. Observations on Clinical Patterns of Diabetes Mellitus in India. Diabetes. 1965;14:404-412. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 38] [Cited by in F6Publishing: 40] [Article Influence: 0.7] [Reference Citation Analysis (0)] |
| 13. | Das S. Lean Type 2 Diabetes Mellitus; profile, peculiatites and paradox. Med Update. 2008;18:94-103. [Cited in This Article: ] |
| 14. | Barma PD, Ranabir S, Prasad L, Singh TP. Clinical and biochemical profile of lean type 2 diabetes mellitus. Indian J Endocrinol Metab. 2011;15:S40-S43. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 18] [Cited by in F6Publishing: 21] [Article Influence: 1.6] [Reference Citation Analysis (0)] |
| 15. | Dulloo AG, Jacquet J, Solinas G, Montani JP, Schutz Y. Body composition phenotypes in pathways to obesity and the metabolic syndrome. Int J Obes (Lond). 2010;34 Suppl 2:S4-17. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 167] [Cited by in F6Publishing: 165] [Article Influence: 12.7] [Reference Citation Analysis (0)] |
| 16. | WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157-163. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 7065] [Cited by in F6Publishing: 7498] [Article Influence: 374.9] [Reference Citation Analysis (0)] |
| 17. | Alberti KG, Zimmet P, Shaw J. Metabolic syndrome--a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 2006;23:469-480. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 3852] [Cited by in F6Publishing: 3943] [Article Influence: 219.1] [Reference Citation Analysis (0)] |
| 18. | Nadarajan B, Saya GK, Krishna RB, Lakshminarayanan S. Prevalence of Diabetic Retinopathy and its Associated Factors in a Rural Area of Villupuram District of Tamil Nadu, India. J Clin Diagn Res. 2017;11:LC23-LC26. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 0.9] [Reference Citation Analysis (0)] |
| 19. | Venkatesan M, Dongre AR, Ganapathy K. A Community-Based Study on Diabetes Medication Nonadherence and its Risk Factors in Rural Tamil Nadu. Indian J Community Med. 2018;43:72-76. [PubMed] [DOI] [Cited in This Article: ] [Cited by in F6Publishing: 8] [Reference Citation Analysis (0)] |
| 20. | Vibha SP, Kulkarni MM, KirthinathBallala AB, Kamath A, Maiya GA. Community based study to assess the prevalence of diabetic foot syndrome and associated risk factors among people with diabetes mellitus. BMC EndocrDisord. 2018;18:43. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 30] [Cited by in F6Publishing: 26] [Article Influence: 4.3] [Reference Citation Analysis (0)] |
| 21. | Kumar SP, Sandhya AM. A study on the glycemic, lipid and blood pressure control among the type 2 diabetes patients of north Kerala, India. Indian Heart J. 2018;70:482-485. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 20] [Cited by in F6Publishing: 13] [Article Influence: 2.2] [Reference Citation Analysis (0)] |
| 22. | Hussain S, Habib A, Singh A, Akhtar M, Najmi AK. Prevalence of depression among type 2 diabetes mellitus patients in India: A meta-analysis. Psychiatry Res. 2018;270:264-273. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 35] [Cited by in F6Publishing: 41] [Article Influence: 6.8] [Reference Citation Analysis (0)] |
| 23. | Shrivastava SR, Ghorpade AG. High prevalence of type 2 diabetes melitus and its risk factors among the rural population of Pondicherry, South India. J Res Health Sci. 2014;14:258-263. [PubMed] [Cited in This Article: ] |
| 24. | Safraj S, Anish T, Vijayakumar K, Kutty VR, Soman CR. Socioeconomic position and prevalence of self-reported diabetes in rural Kerala, India: results from the PROLIFE study. Asia Pac J Public Health. 2012;24:480-486. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 15] [Cited by in F6Publishing: 19] [Article Influence: 1.4] [Reference Citation Analysis (0)] |
| 25. | Maiya AG, Gundmi S, Matpady P, Jadhav R, Lingadakai R, Hande M, Kamath VG, Shivashankar KN, Chinmayee P, Hazari A, Shastri N, Hande R, Loftager MM, Veluswamy SK, Jude E. Prevalence of Foot Complications in People With Type 2 Diabetes Mellitus: A Community-Based Survey in Rural Udupi. Int J Low Extrem Wounds. 2018;17:169-175. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 14] [Cited by in F6Publishing: 15] [Article Influence: 2.5] [Reference Citation Analysis (0)] |
| 26. | Kapil U, Khandelwal R, Ramakrishnan L, Khenduja P, Gupta A, Sareen N, Pandey RM, Sati HC, Belwal RS. Prevalence of metabolic syndrome and associated risk factors among geriatric population living in a high altitude region of rural Uttarakhand, India. J Family Med Prim Care. 2018;7:709-716. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 1.5] [Reference Citation Analysis (0)] |
| 27. | Lone S, Lone K, Khan S, Pampori RA. Assessment of metabolic syndrome in Kashmiri population with type 2 diabetes employing the standard criteria's given by WHO, NCEPATP III and IDF. J Epidemiol Glob Health. 2017;7:235-239. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 14] [Cited by in F6Publishing: 18] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
| 28. | Mokta J, Mokta K, Ranjan A, Garg M. Prevalence of Cardiovascular Risk Factors among Diabetic Population and Awareness of Diabetes among Diabetic Patients: A Population Based Himalayan Study. J Assoc Physicians India. 2017;65:48-52. [PubMed] [Cited in This Article: ] |
| 29. | Balasubramanyam A, Yajnik CS, Tandon N. Non-traditional forms of diabetes worldwide: Implications for translational investigation. Trans EndocrinolMetab. 2011;2:43–67. [DOI] [Cited in This Article: ] [Cited by in Crossref: 14] [Cited by in F6Publishing: 15] [Article Influence: 1.2] [Reference Citation Analysis (0)] |
| 30. | Coleman NJ, Miernik J, Philipson L, Fogelfeld L. Lean versus obese diabetes mellitus patients in the United States minority population. J Diabetes Complications. 2014;28:500-505. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 40] [Cited by in F6Publishing: 34] [Article Influence: 3.4] [Reference Citation Analysis (0)] |
| 31. | Gujral UP, Mohan V, Pradeepa R, Deepa M, Anjana RM, Narayan KM. Ethnic differences in the prevalence of diabetes in underweight and normal weight individuals: The CARRS and NHANES studies. Diabetes Res ClinPract. 2018;146:34-40. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 36] [Cited by in F6Publishing: 35] [Article Influence: 5.8] [Reference Citation Analysis (0)] |
| 32. | Hugh-Jones P. Diabetes in Jamaica. Lancet. 1955;269:891-897. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 88] [Cited by in F6Publishing: 100] [Article Influence: 1.4] [Reference Citation Analysis (0)] |
| 33. | Tulloch JA, Macintosh D. "J"-type diabetes. Lancet. 1961;2:119-121. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 20] [Cited by in F6Publishing: 21] [Article Influence: 0.3] [Reference Citation Analysis (0)] |
| 34. | Abu-Bakare A, Taylor R, Gill GV, Alberti KG. Tropical or malnutrition-related diabetes: a real syndrome? Lancet. 1986;1:1135-1138. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 87] [Cited by in F6Publishing: 97] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
| 35. | Ahuja MM. Diabetes-special problems in developing countries. Bull Deliv Health Care Diabetics Devel Countries. 1980;1:5–6. [Cited in This Article: ] |
| 36. | Emery PW. Metabolic changes in malnutrition. Eye (Lond). 2005;19:1029-1034. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 47] [Cited by in F6Publishing: 47] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
| 37. | Solanki JD, Makwana AH, Mehta HB, Gokhale PA, Shah CJ. Body Composition in Type 2 Diabetes: Change in Quality and not Just Quantity that Matters. Int J Prev Med. 2015;6:122. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 20] [Cited by in F6Publishing: 26] [Article Influence: 2.9] [Reference Citation Analysis (0)] |
| 38. | Lebovitz HE, Banerji MA. Point: visceral adiposity is causally related to insulin resistance. Diabetes Care. 2005;28:2322-2325. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 207] [Cited by in F6Publishing: 206] [Article Influence: 10.8] [Reference Citation Analysis (0)] |
| 39. | Miles JM, Jensen MD. Counterpoint: visceral adiposity is not causally related to insulin resistance. Diabetes Care. 2005;28:2326-2328. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 57] [Cited by in F6Publishing: 62] [Article Influence: 3.3] [Reference Citation Analysis (0)] |
| 40. | Patil S. Holistic antenatal care for rural areas challenges and solutions. Int J Curr Res. 2017;9:53151-53153. [Cited in This Article: ] |
| 41. | Pevekar KS, Patil SN, Chavan AJ. Psychsocial study of adolescent girls from rural Konkan region (Maharashtra). Int J Res Med Sci. 2015;3:2745-2750. [DOI] [Cited in This Article: ] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.3] [Reference Citation Analysis (0)] |
| 42. | Patil S, Joglekar C, Desai M, Yadav A, Sonawane S, Chavan R, Mohite R. Nutritional Status and Psychological Impairment in Rural Adolescent Girls: Pilot Data From "KOKAN" Region of Western India. Front Public Health. 2018;6:160. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 1.7] [Reference Citation Analysis (0)] |
| 43. | Patil SN, Desai MB, Patil NR. A fetal growth trajectory in antenatal period and its relation to birthweight. A record based analysis from rural KOKAN of western Maharashtra. J Evolution Med Dent Sci. 2017;6:2676-2679. [Cited in This Article: ] |
| 44. | George AM, Jacob AG, Fogelfeld L. Lean diabetes mellitus: An emerging entity in the era of obesity. World J Diabetes. 2015;6:613-620. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 95] [Cited by in F6Publishing: 96] [Article Influence: 10.7] [Reference Citation Analysis (4)] |
| 45. | Chiplonkar S, Kajale N, Ekbote V, Mandlik R, Parthasarathy L, Khadilkar V, Khadilkar A. Validation of Bioelectric Impedance Analysis against Dual-energy X-Ray Absorptiometry for Assessment of Body Composition in Indian Children Aged 5 to 18 Years. Indian Pediatr. 2017;54:919-924. [PubMed] [Cited in This Article: ] |
| 46. | Nigam P, Misra A, Colles SL. Comparison of DEXA-derived body fat measurement to two race-specific bioelectrical impedance equations in healthy Indians. Diabetes MetabSyndr. 2013;7:72-77. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 24] [Cited by in F6Publishing: 22] [Article Influence: 2.0] [Reference Citation Analysis (0)] |