Інформація призначена тільки для фахівців сфери охорони здоров'я, осіб,
які мають вищу або середню спеціальну медичну освіту.

Підтвердіть, що Ви є фахівцем у сфері охорони здоров'я.

Мобильная версия

Регистрация Забыли пароль?


Коморбідний ендокринологічний пацієнт
Коморбідний ендокринологічний пацієнт

Международный эндокринологический журнал Том 18, №5, 2022

Вернуться к номеру

Оцінка 10-річного серцево-судинного ризику і 8-річного ризику цукрового діабету з використанням Фремінгемської шкали в осіб із предіабетом

Оцінка 10-річного серцево-судинного ризику і 8-річного ризику цукрового діабету з використанням Фремінгемської шкали в осіб із предіабетом

Авторы: Neeta Kumari (1), Deepak Kumar Verma (2), B.K. Binawara (3)
(1) — Department of Physiology, S.M.M.H. Medical College, Saharanpur, C.C.S. University, Meerut, India
(2) — Department of Pharmacology, S.M.M.H. Medical College, Saharanpur, C.C.S. University, Meerut, India
(3) — Department of Physiology, S.P. Medical College, Rajasthan University of Health, Jaipur, India

Рубрики: Эндокринология

Разделы: Клинические исследования

Версия для печати


Резюме

Актуальність. Предіабет — це стан, що характеризується порушенням глікемії натще або порушенням толерантності до глюкози. Предіабет сприяє підвищеному ризику виникнення серцево-судинних ускладнень. Різноманітні фактори ризику є причиною прогресування серцево-судинних захворювань і цукрового діабету (ЦД) 2-го типу в осіб із предіабетом. Мета дослідження: визначення 10-річного серцево-судинного ризику і 8-річного ризику ЦД за допомогою Фремінгемської шкали в осіб із предіабетом. Матеріали та методи. Перехресне дослідження було проведено на кафедрі фізіології Медичного коледжу та Університетської лікарні у співпраці з діабетичним дослідницьким центром. Особи з предіабетом були ідентифіковані серед родичів першого ступеня пацієнтів із ЦД 2-го типу, зареєстрованих у дослідницькому центрі діабету. Особи з предіабетом (порушенням рівня глікемії натще, ПГН) були ідентифіковані на основі рівня глюкози в крові натще від 100 до 125 мг/дл і глікованого гемоглобіну HbA1c від 5,7 до 6,4 % згідно з рекомендаціями Американської діабетичної асоціації. Послідовний відбір проб проводився доти, доки розмір вибірки не став відповідати критеріям дослідження. До дослідження були включені суб’єкти вікової групи 20–74 роки, які мали ПГН від 100–125 мг/дл, HbA1c від 5,7 до 6,4 % і дали інформовану письмову згоду. Програма Pre-structured Performa використовувалася для збору загальної інформації, соціально-демографічної інформації, базових характеристик, особистих звичок, біохімічного аналізу й параметрів крові. 10-річний ризик розвитку серцево-судинних захворювань і 8-річний ризик розвитку цукрового діабету оцінювали за допомогою Фремінгемської шкали. Результати. Вік, професія, індекс маси тіла, дієта, куріння, алкоголь, вісцеральне ожиріння та сімейний анамнез цукрового діабету були вірогідно пов’язані з поширеністю цукрового діабету 2-го типу й предіабету, тоді як стать і грамотність — ні. Висновки. У цьому дослідженні було виявлено, що похилий вік, професійні зміни, індекс маси тіла, куріння, ожиріння, недостатня фізична активність, підвищений артеріальний тиск і сімейний анамнез діабету були значною мірою пов’язані з майбутнім ризиком розвитку цукрового діабету 2-го типу і серцево-судинних захворювань серед пацієнтів із предіабетом.

Background. Prediabetes is a state characterized by impaired fasting glucose or impaired glucose to­lerance. This implies that prediabetes bears an increased risk of cardiovascular complications. Various risk factors are the reason of the progression of cardiovascular diseases and type 2 diabetes mellitus (T2DM) in prediabetics if factors are not overt. Hence, the present study was undertaken to determine the future 10-year cardiovascular and 8-year diabetic risk by using Framingham heart scale in prediabetic subjects. Materials and methods. Present cross-sectional study was carried out at Department of Physiology, S.P. Medical College & Hospital in collaboration with Diabetic Research Centre P.B.M. Hospital Bikaner (Rajasthan). Prediabetic subjects were identified from first-degree relatives of T2DM patients, enrolled in Diabetic Research Centre P.B.M. Hospital Bikaner. Prediabetics (impaired fasting glucose) subjects were identified on the basis of fasting blood glucose of 100 to 125 mg/dl and HbA1c (5.7 to 6.4 %) as per American Diabetes Association 2011 guidelines. Consecutive sampling was conducted till sample size satisfied during the period of study. Subjects of age group 20–74 years who had fasting blood glucose of 100–125 mg/dl, HbA1c of 5.7 to 6.4 % and gave informed written consent were included in study. Pre-structured performa was used to collect general information, sociodemographic information, baseline physical characteristics, personal habits, biochemical analysis, and for blood parameters. Future 10-year cardiovascular and 8-year diabetic risk were assessed by using Framingham heart scale. Results. Age, occupation, body mass index, diet, smoking, alcohol, truncal obesity and family history of diabetes were significantly associated with the prevalence of T2DM/prediabetes whereas gender and literacy were not. Conclusions. In the present study, it was observed that advanced age, occupational changes, body mass index, substance abuse like smoking, central obesity, exercise, blood pressure and family history of diabetes were highly associated with future risk of T2DM and cardiovascular diseases among prediabetic subjects of first-degree relatives.


Ключевые слова

предіабет; серцево-судинні захворювання; цукровий діабет 2-го типу; фактори ризику; Фремінгемська шкала

prediabetes; Framingham scale; cardiovascular disease; diabetes; risk factors

doi: http://dx.doi.org/10.22141/2224-0721.18.5.2022.1182

Introduction

Prediabetes is a state of abnormal glucose metabolism that can be documented years before the onset of overt type 2 diabetes mellitus (T2DM). Prediabetes can be grouped into impaired fasting glucose (IFG) or impaired glucose tolerance (IGT). The American Diabetes Association (ADA) defines prediabetes as a fasting glucose of 100 to < 126 mg/dl (IFG) or a 2 hour (2h) plasma glucose of 140 to < 200 mg/dl after a 75 g oral glucose tolerance test (IGT) or HbA1c 5.7 % (39 mmol/mol) to < 6.5 % (48 mmol/mol) [1]. 
However, a substantial number of subjects with either IFG or IGT will progress to overt T2DM within some years [2] if undiagnosed due to the continuous action of defects in insulin secretion or action [3]. As a consequence, when overt T2DM is diagnosed, clinical damage is commonly already established [4]. 
This implies that prediabetes bears an increased risk of cardiovascular complications. According to estimates in the United States, 40–50 % of individuals with IGT will develop T2DM within 10 years [5], while in the United Kingdom it is estimated that up to 12 % of adults with impaired glucose regulation will develop T2DM each year [6]. 
Cardiovascular disease is the leading cause of death and serious illness. The causes of cardiovascular disease are diverse but atherosclerosis and hypertension are the most common. In 1948, the Framingham Heart Study under the direction of the National Heart Institute (now known as the National Heart, Lung and Blood Institute or NHLBI) embarked on an ambitious project in Health Research. “Framingham Heart Study” is the longest running multigenerational longitudinal study in medical history. It has helped identify several risk factors and their cumulative [7].
Influence on the manifestation of cardiovascular disease. The term risk factor was coined by Framingham investigators. Framingham reported that blood pressure was directly associated with cardiovascular risk regardless of how labile. It was reported that isolated systolic hypertension was also a powerful predictor of cardiovascular disease [8].
The Framingham Risk Score is a gender-specific algorithm used to estimate the 10-year cardiovascular risk of an individual. The Framingham Risk Score was first developed based on data obtained from the Framingham Heart Study, to estimate the 10-year risk of developing coronary heart disease. In order to assess the 10-year cardiovascular disease risk, cerebrovascular events, peripheral artery disease and heart failure were subsequently added as disease outcomes for the 2008 Framingham Risk Score, on top of coronary heart disease. The 8-year diabetic risk will be assessed by using Framingham Risk Score [9, 10]. If we get the previous knowledge of the progression of cardiovascular disease (CVD) and DM and which factors are involved in may be helpful for clinicians to treat the patients with best strategies. So the aim of present study was assess the future 10-year cardiovascular and 8-year diabetic risk by using Framingham Heart Scale in prediabetic subjects. 

Materials and methods

This cross-sectional study was carried out in the Department of Physiology, S.P. Medical College & Hospital in collaboration with Diabetic research centre P.B.M. hospital Bikaner (Rajasthan) and was approved by Institutional Ethical Committee (IEC). 
Prediabetic subjects were identified from first degree relatives of T2DM patients, enrolled in Diabetic research centre P.B.M. hospital Bikaner. Consecutive sampling was conducted till sample size (142) satisfied during the period of study. 
Subjects of age group 20–74 years having FPG between 100–125 mg/dl, HbA1c between 5.7 to 6.4 % and gave informed written consent was included in study. Prediabetic subjects were identified from first degree relatives T2DM patients, enrolled in Diabetic research centre P.B.M. hospital Bikaner. Prediabetic subjects (FBS 100–125 mg/dl) were identified by using glucometer. 
Tool of data collection: Pre-structured Performa was used to collect general information, sociodemographic information, baseline physical characteristics, personal habits, biochemical analysis, and for blood parameters.

Socioeconomic status

The participants were interviewed with a pretested questionnaire regarding identification, demographic details, behavioral components, social and biological variables. Education was classified based on International Standard Classification of Education. The occupation of study subjects was classified as workers and non-workers as per census of India 2001. Further workers were subdivided based on their occupation such as Skilled I to Skilled IV. Non-workers included house-wives and elderly persons who have stopped working [11].

Family history of DM

Detailed family history of T2DM was taken. This was verified either by blood glucose measurement of the parents or in the person’s absence, by other circumstantial evidences such as physician report, diet modifications, consumption of drugs. Known cases of T2DM were included in the study. Duration of DM and medication details were noted. In the present study, if the response was “diabetes status of parents not known”, it was assumed to be “no family history of DM” [12].

Smoking and alcohol

Smoking and alcohol were considered as risk factors. Smoking was measured in terms of frequency those who were smoking daily for 6 months and quantum tobacco chewing/beedies/cigarettes/cheroots per day. Based on tobacco content of Indian beedis, cigarettes and cheroots, Indian cigarette equivalents of beedi and cheroot were calculated. The alcohol consumption pattern (amount, type and frequency) of current drinkers and past drinkers (who have stopped before 12 months) was noted [13].

Demographical division

Subjects were divided in two categories rural and urban on the basis of their address. The weight (kg) and height (cm) were measured by using calibrated weighing machine and stadiometer respectively. BMI was calculated by using the formula weight (kg)/height2 (m2). Waist circumference was measured by using a measuring tape over the unclothed abdomen, with measurements made halfway between the lower border of the ribs and the highest point of iliac crest (at the umbilicus level) in the standing position. Hip circumferences was measured over light clothing at the widest point over the buttocks when viewed from the side [14].
Blood pressure (SBP/DBP) was measured by Sphygmomanometer Method of blood pressure measurement — for measurement of BP we allow the patient to sit comfortable on a chair for 5 minutes.

Biochemical parameters

Blood sample (5–6 ml) was collected with the help of lab technician and was sent to central laboratory for investigations:
1. Blood glucose: fasting blood glucose was determined by glucometer.
2. HbA1c: it is used routinely to monitor long term glycemic control in people with DM. HbA1c was measured by kit method using CCKA1C analyser. 
3. Serum Lipid Profile [15, 16]: Total cholesterol, Tryglyciride, HDL, LDL and VLDL.
10-years general cardiovascular risks will be assessed by using Framingham risk score based on a general cardiovascular risk profile for use in primary care (The Framingham Heart study, 2008) [17]. The risk prediction will be calculated by two methods: 1) Based on Body Mass Index; 2) Based on Lipid profile. Or can be calculated by: Lipid /BMI profile based Online Calculator for 10-year cardiovascular risk on https://www.framinghamheartstudy.org/risk-functions/cardiovascular-disease/10-year-risk.php.
The 8-year diabetic risk will be assessed by using Framingham Risk Score (based on: The Framingham Offspring Study, 2007) [18]. 
The risk prediction will be calculated by: Given total points from next table, there is an approximate Percentage Risk for Type 2 Diabetes in Middle-aged Adults. Or can be calculated by: Online Calculator for 8-year Diabetic risk on https://www.framinghamheartstudy.org/risk-functions/diabetes/index.php.

Results

The present study was conducted in department of physiology in collaboration with Diabetic Research Centre P.B.M. hospital associated with Sardar Patel Medical College, Bikaner Rajasthan.
A total of 142 subjects either sex or adult age group, who full filled inclusion criteria ware included in this study.
Table 1 depicts the distribution of prediabetic subjects on the basis of baseline sociodemographic division. It shows the division of groups on the basis of gender, age, socioeconomic status, occupation, literacy, BMI, smoking status, locality, exercise and blood pressure.
Table 2 depicts the gender wise distribution in prediabetic subjects. Out of 142 prediabetic subjects 91 (64.08 %) were male and 51 (35.92 %) were females.
Table 3 depicts the anthropometric measurements of the subjects with prediabetes (n = 142). The Mean ± SD levels of BMI (kg/m2) 25.18 ± 4.76, Waist Circumference (cm) 92.33 ± 13.20, Waist & Hip Ratio 0.9195 ± 0.09, Systolic blood pressure 130.06 ± 14.38 mm Hg, Diastolic blood pressure 82.26 ± 7.09 mm Hg were found.
Table 4 shows the Mean ± SD levels of Fasting Glucose (FBS) (116.92 ± 6.14 mg/dl), Triglycerides (TG) (3.50 ± 0.81 mg/dl), Total Cholesterol (TC) (186.57 ± ± 20.53 mg/dl), LDL-C (109.66 ± 22.13 mg/dl), VLDL-C (30.84 ± 3.88 mg/dl), HDL-C (3.50 ± 0.81 mg/dl), HbA1C (6.03 ± 0.27 %), FBS (116.92 ± 6.14 mg/dl), TG/HDL Ratio 3.50 ± 0.81, LDL/HDL Ratio 2.48 ± 0.78 were found.
Table 5 depicts the 10-year cardiovascular risk and 8-years diabetic risk in 142 prediabetic subjects. In our study, we observed 7.00 ± 6.42 Mean ± SD for 10-year cardiovascular risk on the basis of lipid and 7.27 ± 6.22 Mean ± SD for 10-year cardiovascular risk on the basis of BMI. We also observed 17.07 ± 10.32 Mean ± SD for 8-year diabetic risk.

Discussion

Epidemiological proofs propose that the complications of diabetes start early in the progression from normal glucose tolerance to frank DM. Prediabetes raises short-term outright danger of T2DM by 3- to 10-fold [19]. 
Early documentation and efforts to improve glycemia in persons with prediabetes have the possibility to decrease or postponement the development to diabetes and related cardiovascular diseases [20]. To meet the sample size, we approached approx 140 families of T2DM and screened out 410 first degree relatives (FDR). Out of 410 FDR, 142 subjects (34.63 %) were identified as prediabetic on the basis of impaired fasting plasma glucose level (100–125 mg/dl) by digital glucometer and 11 individuals were newly diagnosed T2DM. In present study gender wise distribution, out of 142 prediabetic subjects 91 (64.08 %) were male and 51 (35.92 %) were females (Table 2). Prevalence of prediabetes in first degree relatives of T2DM was similar to study undertaken by Asha Shrivastava et al. [21] where they showed that out of 230 first degree relatives of T2DM subjects, 60 (26.08 %) individuals had prediabetes. 
Similarly, Inderamohan Bisht et al. [22] also found 25 % (n = 20) prediabetics subjects out of 80 individuals. Similarly, Sanjay Bhalerao et al. [23] also investigated that the prevalence of T2DM was 86.1 % among subjects having family history of DM. 
Prevalence of T2DM was more in those who had maternal history of diabetes (53.43 %) than paternal history (17.15 %). We further carried out our study to identify the presence of hypertension and smoking habits in prediabetic subjects of FDR of T2DM. Out of 142 prediabetics subjects, there were 54 (38.03 %) smokers (Table 1). That shows smoking is also one of the important risk factor for prediabetes. Among 142 prediabetic subjects, 27 (19.01 %) were normotensive followed by 79 (55.63 %) prehypertensive and 36 (25.35 %) hypertensive (Table 1). That shows prehypertensive subjects are prone for prediabeties. 
Similarly, G. Ramaswamy et al. [24] also investigated the prevalence of prediabetes in the FDR of patients with T2DM and reported the high prevalence of prediabetes among the family members of individuals with diabetes. They showed that out of total 873 FDR, 7.3 % tobacco user, 5.2 % alcohol user, 16 % high salt intake, 32 % prediabetic, 2.2 % diabetic, 20.6 % hypertensive and 17 individuals were newly diagnosed T2DM. In present study the age distribution was done among the prediabetics group. Out of 142 prediabetic subjects majority of them 48 (33.80 %) belongs to the age group of 30–34 years, followed by 29 (20.42 %) to the age group 35–39 years, 17 (11.97 %) to the age group 40–44 years, 5 (3.52 %) to the age group 60–64 years and 65–69 years while only 2 (1.41 %) to the age group ≥ 70 years (Table 1). We found maximum participants educated up to secondary level 65 (45.77 %). While only 17 (11.97 %) were illiterates. We also observed 42 (29.58 %) graduates and 18 (12.68 %) educated up to primary level (Table 1). In occupation, out of 142 prediabetic subjects maximum were skilled II type 48 (38.0 %) while minimum were skilled — IV type 13 (9.15 %). We found 40 (28.17 %) non-worker.
Similarly, Inderamohan Bisht et al. [22] also found that most of the cases of prediabetes were seen in the age group of 46–56 years. Similarly, Sanjay Bhalerao et al. [23] also showed the prevalence of DM increased significantly with age. The increased prevalence was observed in the middle age group 40–49 years (30.4 %) and in the old age group above 60 years age group (37.8 %) The prevalence of T2DM among gender was observed elevated in females (64.6 %) compared to males (35.4 %). The prevalence of T2DM in association with literacy observed in this study was Illiterate group (47.3 %), Primary education group (19.2 %), Secondary school group (28.7 %) and Graduation and above group (4.9 %). The prevalence stratified by occupation ranged from 11.7 % (skilled I) to 23.4 % (non-workers). In our study, we observed n = 54, 38.02 % smokers and n = 88, 61.97 % non smokers prediabetic subject among first degree relatives of T2DM. 
Prediabetic patients had the same cardiovascular risk as patients with overt DM, and since metabolic syndrome patients have multiple risk factors. Moderately elevated levels of triglyceride-rich lipoproteins and low levels of HDL cholesterol are the signature lesions of obesity and prediabetes (Tables 3, 4).
In present study we calculated the Mean ± SD values of 10-year cardiovascular risk on the basis of Lipid and BMI and 8-year diabetic risk in normotensive, prehypertensive and hypertensive prediabetic subjects (n = 142) among first degree relative of T2DM by using Framingham Scoring as a tool [17]. Student t-test was performed and p value < 0.0001, < 0.001and < 0.005 was taken as statistically significant (Table 3). 
In the present study, 10-year cardiovascular risk on the basis of Lipid and BMI and 8-year diabetic risk was assessed using Framingham Scoring as a tool. We found highly significant relations for 10- year cardiovascular risk on the basis of BMI and Lipid between the smokers and non smokers. However for 8-year diabetic risk we did not found any significant relationship. In our study out of (n = 54) smokers we found 61.11 % with metabolic and 38.88 % with non metabolic syndrome. For non smokers (n = 88) we found 60.22 % with metabolic and 39.77 % with non metabolic syndrome in prediabetic subjects among first degree relatives T2DM. 
The present study showed that smoking is associated with diabetes. Smoking habits were associated with 1.94 times odds for incident T2DM. This finding agrees with several other cohort studies [25, 26]. The present study showed a significant association between risk factors and risk for prediabetes and metabolic syndrome (Table 5). This is probably due to the development of insulin resistance, which is a key factor in the pathogenesis of prediabetes among metabolic syndrome subjects. Heavy smoking with metabolic syndrome has been shown by some studies to be mediated by increased obesity, especially abdominal obesity. Literature showed varied association of smoking and increased risk of diabetes [27, 28].

Conclusions

In the present study it was observed that advanced age, occupational changes, BMI, substance abuse like smoking, central obesity, exercise, blood pressure and family history of diabetes were highly associated with future risk of T2DM and CVD among prediabetic subjects in FDR of T2DM whereas most of the blood parameters showed no association. This study created awareness of diabetes and CVD and its complications among the population of this region.
 
Received 24.06.2022
Revised 27.07.2022
Accepted 07.08.2022

Список литературы

  1. American Diabetes Association Professional Practice Committee. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022. 45 (Suppl. 1). S17-S38. doi: 10.2337/dc22-S002. 
  2. van Herpt T.T.W., Ligthart S,. Leening M.J.G., van Hoek M., Lieverse A.G., Ikram M.A., Sijbrands E.J.G. et al. Lifetime risk to progress from pre-diabetes to type 2 diabetes among women and men: comparison between American Diabetes Association and World Health Organization diagnostic criteria. BMJ Open Diabetes Res Care. 2020. 8(2). e001529. doi: 10.1136/bmjdrc-2020-001529. 
  3. Nasykhova Y.A., Tonyan Z.N., Mikhailova A.A., Danilova M.M., Glotov A.S. Pharmacogenetics of Type 2 Diabetes-Progress and Prospects. Int. J. Mol. Sci. 2020. 21(18). 6842. doi: 10.3390/ijms21186842. 
  4. Bhutta Z.A., Salam R.A., Gomber A., Lewis-Watts L., Narang T., Mbanya J.C., Alleyne G. A century past the discovery of insulin: global progress and challenges for type 1 diabetes among children and adolescents in low-income and middle-income countries. Lancet. 2021. 398(10313). 1837-1850. doi: 10.1016/S0140-6736(21)02247-9. 
  5. Hu H., Wang J., Han X., Li Y., Miao X., Yuan J., Yang H., He M. Prediction of 5-year risk of diabetes mellitus in relatively low risk middle-aged and elderly adults. Acta Diabetol. 2020. 57(1). 63-70. doi: 10.1007/s00592-019-01375-w. 
  6. Rodgers L.R., Hill A.V., Dennis J.M., Craig Z., May B., Hattersley A.T., McDonald T.J. et al. Choice of HbA1c threshold for identifying individuals at high risk of type 2 diabetes and implications for diabetes prevention programmes: a cohort study. BMC Med. 2021. 19(1). 184. doi: 10.1186/s12916-021-02054-w. 
  7. Preis S.R., Pencina M.J., Mann D.M., D’Agostino R.B. Sr, Savage P.J., Fox C.S. Early-adulthood cardiovascular disease risk factor profiles among individuals with and without diabetes in the Framingham Heart Study. Diabetes Care. 2013. 36(6). 1590-6. doi: 10.2337/dc12-1121. 
  8. Fox C.S. Cardiovascular disease risk factors, type 2 diabetes mellitus, and the Framingham Heart Study. Trends Cardiovasc. Med. 2010. 20(3). 90-5. doi: 10.1016/j.tcm.2010.08.001. 
  9. Bitton A., Gaziano T.A. The Framingham Heart Study’s impact on global risk assessment. Prog. Cardiovasc. Dis. 2010. 53(1). 68-78. doi: 10.1016/j.pcad.2010.04.001. 
  10. Mahmood S.S., Levy D., Vasan R.S., Wang T.J. The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective. Lancet. 2014. 383(9921). 999-1008. doi: 10.1016/S0140-6736(13)61752-3. 
  11. Ramachandran A., Snehalatha C., Vijay V., King H. Impact of poverty on the prevalence of diabetes and its complications in urban southern India. Diabet Med. 2002. 19(2). 130-5. doi: 10.1046/j.1464-5491.2002.00656.x. 
  12. Das M., Pal S., Ghosh A. Family history of type 2 diabetes and prevalence of metabolic syndrome in adult Asian Indians. J. Cardiovasc. Dis. Res. 2012. 3(2). 104-8. doi: 10.4103/0975-3583.95362. 
  13. Tripathy J.P., Thakur J.S., Jeet G., Chawla S., Jain S., Pal A. et al. Prevalence and risk factors of diabetes in a large community-based study in North India: results from a STEPS survey in Punjab, India. Diabetol. Metab. Syndr. 2017. 9. 8. doi: 10.1186/s13098-017-0207-3. 
  14. Fryar C.D., Carroll M.D., Gu Q., Afful J., Ogden C.L. Anthropometric Reference Data for Children and Adults: United States, 2015–2018. Vital Health Stat. 3. 2021. 36. 1-44. PMID: 33541517.
  15. Sarkar D., Latif S.A., Uddin M.M., Aich J., Sutradhar S.R., Ferdousi S. et al. Studies on serum lipid profile in hypertensive patient. Mymensingh Med. J. 2007. 16(1). 70-6. doi: 10.3329/mmj.v16i1.252. PMID: 17344784.
  16. Nigam P.K. Serum Lipid Profile: Fasting or Non-fasting? Indian J. Clin. Biochem. 2011. 26(1). 96-7. doi: 10.1007/s12291-010-0095-x. 
  17. D’Agostino R.B. Sr, Vasan R.S., Pencina M.J., Wolf P.A., Cobain M., Massaro J.M., Kannel W.B. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008. 117(6). 743-53. doi: 10.1161/CIRCULATIONAHA.107.699579. 
  18. Wilson P.W., Meigs J.B., Sullivan L., Fox C.S., Nathan D.M., D’Agostino R.B. Sr. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch. Intern. Med. 2007. 167(10). 1068-74. doi: 10.1001/archinte.167.10.1068. 
  19. Chodick G., Elchalal U., Sella T., Heymann A.D., Porath A., Kokia E., Shalev V. The risk of overt diabetes mellitus among women with gestational diabetes: a population-based study. Diabet Med. 2010. 27(7). 779-85. doi: 10.1111/j.1464-5491.2010.02995.x.
  20. Beulens J., Rutters F., Rydén L., Schnell O., Mellbin L., Hart H.E., Vos R.C. Risk and management of pre-diabetes. Eur. J. Prev. Cardiol. 2019. 26 (Suppl. 2). 47-54. doi: 10.1177/2047487319880041. PMID: 31766914.
  21. Asha Shrivastava, Namit Garg, Rashmi Dave. HbA1c: Future Diabetic and Cardiovascular Risk in First Degree Relatives of Type 2 Diabetes Mellitus. IJBAP. 2013. 2(1). 79-82. DOI: 10.5281/zanodo.4483066.
  22. Bisht Inderamohan, Dhanda Saurabh, Chauhan Suman, Yadav Rajinder, Yadav Suman. Prevalence of prediabetes in apparently healthy population of Tehsil Kangra and adjoining areas. International Journal of Community Medicine and Public Health. 2018. 5. 4916. Doi: 10.18203/2394-6040.ijcmph20184596.
  23. Bhalerao Sanjay, Somannavar Manjunath, Vernekar Sunil, Rajashree R., Shivaprasad Goudar. Risk factors for type 2 diabetes mellitus in rural population of North Karnataka: A community-based cross-sectional study. International Journal of Pharma Medicine and Biological Sciences. 2014. 3(1). 1-14.
  24. Ramaswamy G., Chinnakali P., Selvaraju S., Nair D., Thekkur P., Selvaraj K. et al. High prevalence of prediabetes among the family members of individuals with diabetes. Findings from targeted screening program from south India. Diabetes Metab. Syndr. 2019. 13(1). 866-872. doi: 10.1016/j.dsx.2018.12.001. 
  25. Maddatu J., Anderson-Baucum E., Evans-Molina C. Smoking and the risk of type 2 diabetes. Transl. Res. 2017 Jun. 184. 101-107. doi: 10.1016/j.trsl.2017.02.004. 
  26. Campagna D., Alamo A., Di Pino A., Russo C., Calogero A.E., Purrello F., Polosa R. Smoking and diabetes: dangerous liaisons and confusing relationships. Diabetol. Metab. Syndr. 2019. 11. 85. doi: 10.1186/s13098-019-0482-2. 
  27. Cai X., Chen Y., Yang W., Gao X., Han X., Ji L. The association of smoking and risk of diabetic retinopathy in patients with type 1 and type 2 diabetes: a meta-analysis. Endocrine. 2018. 62(2). 299-306. doi: 10.1007/s12020-018-1697-y. 
  28. Yuan S., Xue H.L., Yu H.J., Huang Y., Tang B.W., Yang X.H. et al. Cigarette smoking as a risk factor for type 2 diabetes in women compared with men: a systematic review and meta-analysis of prospective cohort studies. J. Public Health (Oxf.). 2019. 41(2). e169-e176. doi: 10.1093/pubmed/fdy106. PMID: 29901755.

Вернуться к номеру