Synergistic Effect of Family History of Diabetes and Dietary Habits on the Risk of Type 2 Diabetes in Central China.
1. IntroductionDiabetes is now seen as a global epidemic [1]. According to the statistics published by the World Health Organization (WHO) in 2011, the prevalence of diabetes around the world has reached 366 million and most of these patients have type 2 diabetes mellitus (T2DM) [2]. The prevalence of diabetes has increased significantly in recent decades and is now reaching epidemic proportions in China [3]. Compared with 1980, the prevalence of T2DM has increased by a factor of 3 in 1994 and has approximately doubled from 1994 to 2001 [3].
Dietary habits are well known to influence the risk of T2DM. A Western pattern diet (high consumption of red meat, processed meat, refined grains, French fries, high-fat dairy products, sweets and desserts, high-sugar drinks, and eggs) has been associated with an increased risk of T2DM in both men and women [4, 5]. The Chinese have a unique dietary pattern that might have protected them from T2DM in the past, but westernization of the dietary habits in China during the recent decades may participate in the obesity and T2DM epidemics observed in China [6-8]. Nevertheless, the exact relationship between T2DM and dietary habits in China is currently poorly understood.
Recent studies reported that family history of diabetes (FHD) is associated with an increased prevalence of T2DM [9-11]. Those with a parental history of diabetes are more susceptible to suffer from T2DM compared with those without parental history [9-11]. It is likely that this elevated risk of T2DM is mediated, in part, by both genetic and shared environmental components among family members [12], but whether the FHD has the same impact on the risk of T2DM is unclear. Similarly, although some previous studies revealed that anthropometric and lifestyle-related risk factors such as body mass index (BMI), waist circumference, and physical inactivity are major risk factors for T2DM [13-15] and that the aggregation of such traits among families may account for a portion of the excess risk attributable to FHD [16], the precise factors accounting for this increase in risk are poorly understood. Moreover, the current reports about the interaction of FHD with lifestyle risk factors are few. After a first-degree relative experiences T2DM, it might be expected that other family members would take this as a warning which might lead to changes in risk factor exposure. This might be reflected in differences in risk factor exposure and odds ratios (ORs) between individuals with and without FHD.
To answer these questions, the present study was carried out using data from Henan province's study sites of the Chinese Center for Disease Control and Prevention's (CDC's) National Disease Surveillance Point System. Differences in lifestyle were compared to FHD status in patients with T2DM and non-T2DM subjects for possible relationships. The interactions between them were also analyzed.
2. Methods
2.1. Study Design and Subjects. The present work was one part of the baseline survey from REACTION study investigating the association of diabetes and cancer, which was conducted among 259,657 adults, aged 40 years and older in 25 communities across mainland China, from 2011 to 2012 [17, 18]. All subjects' data were drawn from the REACTION study. This survey was conducted in four communities in Zhengzhou city, Henan province, from July 2010 to August 2010. In this previous cross-sectional study, a complex, multistage, probability sampling design was used to select participants. This process aimed to select a study sample that was representative of civilian, noninstitutionalized Chinese adults at each site. One individual of [greater than or equal to] 18 years of age was randomly selected from each household. If the selected individuals refused or were unavailable, a similar and previously unselected replacement household was selected in the same neighborhood.
The original study was approved by Ruijin Hospital Ethics Committee. Written informed consent was obtained from all study participants. The present study was approved by the same ethics committee, but the need for individual consent was waived because of the retrospective nature of the study.
2.2. Data Collection. A standard questionnaire was administered by trained staff to obtain information on demographic characteristics, personal and family medical history, and lifestyle risk factors [19]. A pilot study was first conducted on a small group of district residents to test the validity of the questionnaire. "Current smoking" was defined as having smoked 100 cigarettes in one's lifetime. Previous smoking was defined as having stopped smoking for at least 1 year. Similarly, "Current drinking" was defined as the consumption of at least 30 g of alcohol per week for 1 year or more. Consumption of milk, eggs, meat (chicken, beef, and pork), raw vegetables, fruits, and other dietary items was divided into two or three categories according to intake frequency. Information was obtained on the amount and type of alcohol that was consumed during the previous year.
Bodyweight and height were measured according to a standard protocol, and BMI was calculated as weight in kilograms divided by height in meters squared. Waist circumference was measured on standing participants midway between the lower edge of the costal arch and the upper edge of the iliac crest.
In this study, FHD was defined as positive if the subject had at least one parent or sibling or children who had been diagnosed with T2DM.
2.3. Statistical Analyses. The Pearson chi-square test was used to assess the differences in the frequency distribution of the categorical variables between T2DM and non-T2DM. The Mann-Whitney U test was used to assess the differences in non-normally distributed continuous variables between T2DM and non-T2DM. Multivariate logistic regression was performed to obtain OR estimates and their 95% confidence intervals (95% CI) for lifestyle factors on T2DM onset. The estimates were adjusted for age, sex, BMI, waist-to-hip ratio (WHR), and FHD. The biological interactions, defined by Rothman interactions [20], between FHD and each dietary factor were analyzed by using the synergy index (S) scores [19]. An S score of >1.0 indicates positive interaction and an S score of below <1.0 indicates an antagonistic effect [21]. All of the statistical tests were performed using SPSS 16.0 (IBM, Armonk, NY, USA). Two-sided P values <0.05 were considered statistically significant.
3. Results
3.1. Characteristics of the Patients. The present study included 9849 representative urban residents, including 1234 hospital-diagnosed patients with T2DM and 8615 non-T2DM individual. Compared with non-T2DM individuals, patients with T2DM showed a higher proportion of males (38.7% versus 31.4%, P <0.001), older age (median, 63 versus 58 years, P <0.001), higher BMI (median, 26.2 versus 25.7 kg/[m.sup.2], P < 0.001), and higher WHR (0.918 versus 0.896, P <0.001) (Table 1).
Among the patients with T2DM, 332 (26.9%) were FHD+ compared with 1025 (11.9%) among non-T2DM individuals (P <0.001). Compared with non-T2DM individuals, patients with T2DM showed a higher proportion of patients with a history of smoking [greater than or equal to] 7 cigarettes/week (10.9% versus 7.3%, P < 0.001), a lower consumption of potatoes (P <0.001), pork (P <0.001), fresh fruits (P <0.001), and freshly squeezed fruits (P < 0.001), a higher consumption of poultry (P = 0.002), and a higher level of physical activity (P < 0.001) (Table 2).
3.2. Association between FHD and T2DM. After adjustment for age, gender, BMI, and WHR, a uniparental FHD (OR = 2.84, 95% CI: 2.36-3.42, P < 0.001), a paternal history of FHD (OR = 2.53, 95% CI: 1.91-3.35, P <0.001), a maternal history of FHD (OR = 3.27, 95% CI: 2.67-4.02, P < 0.001), a biparental history of FHD (OR = 5.26, 95% CI: 2.98-9.31, P < 0.001), and a FHD, irrespective of the parent (OR = 3.59, 95% CI: 3.08-4.17, P <0.001), were associated with T2DM onset (Table 3).
3.3. Effect of Lifestyle Factors on T2DM Onset. After adjustment for age, gender, BMI, and WHR, the consumption of potatoes (<15 g/d, OR= 1.49, 95% CI: 1.30-1.71, P <0.001), beef and mutton (<4 g/d, OR = 0.78, 95% CI: 0.68-0.91, P <0.001), fresh fruits (<85 g/d, OR = 2.34, 95% CI: 2.04-2.68, P <0.001), freshly squeezed juice (no, OR = 2.23, 95% CI: 1.86-2.68, P <0.001), and soy products ([greater than or equal to] 30 g/d, OR = 1.19, 95% CI: 1.04-1.37, P = 0.01), and days of walking/week (>3, OR = 1.29, 95% CI: 1.11-1.49, P = 0.001) were associated with T2DM onset (Table 4).
3.4. Interactions between Lifestyle Habits and FHD. As shown in Table 5, there were significant interactions between FHD and consuming < 15 g/d of potatoes (S =154, 95% CI: 1.12-2.12), <8 g/d of poultry (S = 1.51, 95% CI: 1.04-2.17), <85 g/d of fresh fruits (S = 2.17, 95% CI: 1.63-2.88), and no freshly squeezed juice (S = 2.25, 95% CI: 1.46-3.49).
4. Discussion
T2DM is a major public health problem in China [22, 23]. Fortunately, there are preventive measures, and persons at risk can be readily identified using a few common risk factors [24]. In this study, we conducted a study to identify lifestyle risk factors of T2DM and their interactions with FHD in a Chinese urban population.
After adjustment for age, gender, BMI, and WHR, a uniparental FHD, a paternal history of FHD, a maternal history of FHD, a biparental history of FHD, and a FHD, irrespective of the parent, were associated with T2DM onset. After adjustment for age, gender, BMI, and WHR, the consumption of potatoes, beef and mutton, fresh fruits, freshly squeezed juice, and soy products, and days of walking/week were associated with T2DM onset. There were significant interactions between FHD and consuming < 15 g/d of potatoes, <8 g/d of poultry, <85 g/d of fresh fruits, and no freshly squeezed juice.
This was a comprehensive investigation of the associations between dietary habits and T2DM in the Chinese. Potatoes have hypoglycemic activity in diabetic patients [25], and the present study showed an association between consuming < 15 g/d of potatoes and T2DM. High intake of red meat such as beef and mutton has been associated with T2DM [26], supporting the present study, that is, that consuming > 4 g/d of beef and mutton was associated with T2DM. The present study also showed that consuming < 85 g/d of fresh fruits and no freshly squeezed fruit and vegetable juices was associated with T2DM, which is supported by two European prospective studies [27, 28]. Although some clinical studies supported the antidiabetic effects of vegetables and soy products in Asians [29-31], the present study suggested that consuming > 30 g/d of soy products was associated with T2DM. This discrepancy may be explained by the facts that soy products are often cooked with red meat and drinking sweetened soybean milk in middle China.
This is the first study examining the interaction between dietary factors and FHD on T2DM onset. There were significant interactions between FHD and consuming < 15 g/d of potatoes, <8 g/d of poultry, <85 g/d of fresh fruits, and no freshly squeezed juice. Of course, the individual dietary habits are influenced by the familial dietary habits (PMID: 27050725) [32], and the present study could not tell the amplitude of this influence in relation to FHD. Nevertheless, the present study provides clues about possible changes in dietary habits in individual without T2DM but with FHD.
It was observed that patients with FHD had earlier age at onset of T2DM than those without, indicating that FHD might lead to earlier occurrence of the disease, suggesting genetic and environmental (family) influences on T2DM onset [12]. The proportion of female with FHD was higher than male in both T2DM and non-T2DM groups, which suggested positive FHD might have more influence for female who suffer from T2DM. In the present study, a biparental FHD was more strongly associated with the risk of T2DM, in agreement with earlier observations (in men and women combined) [15]. A higher risk of diabetes was observed in subjects with maternal history when compared with paternal history of diabetes. Previous study indicated that a stronger influence conferred by the mother compared to the father could be due to a larger contribution of diet, lifestyle factors, and adiposity from the mother [33].
The number of risk factors of T2DM in the FHD+ group is less than that of the FHD-group after adjustment for age and sex, which is similar to previous investigations [34-36]. Some relatively hidden factors such as passive smoking might increase the risk of suffering type 2 diabetes for the FHD+ population. In addition, some common risk factors for T2DM such as smoking, drinking, and obesity might increase the risk of T2DM for people without FHD. Previous smoking but not current smoking was associated with T2DM, which suggested patients may quit smoking after diagnosis of T2DM. This study also indicated more walking and higher BMI in T2DM group. The patients may increase physical activity deliberately but not enough to lose weight. The value of health education should be noticed.
Nevertheless, some limitations of this study should also be noted. Most of the information was obtained through an interview, resulting in possible inaccuracy in the risk factor metrics. The potential for recall bias was the second limitation. In studies with a cross-sectional design, a common limitation is the potential reverse causation bias. Associations between some risk factors and T2DM were in unexpected directions, and it might be due to an uncertainty whether exposure preceded the outcome or not. On the other hand, the subjects in the control group could have parents of diabetics, so the exposure level of control group might be raised, which would generate bias in the analysis of infected factors associated T2DM. The last issue might be information bias. A lot of measures were taken to minimize the biases. For example, our questionnaires were administered and checked by well-trained interviewers to exclude inter-interviewer variation, and we conducted the questionnaire study before the diseases were identified.
5. Conclusions
FHD was significantly associated with the risk of diabetes. There was a clear positive interaction between daily intake of potatoes and FHD, while an antagonistic interaction was observed between freshly squeezed vegetables and juices and FHD. FHD could have an appreciable influence on risk factors for T2DM and support that Chinese individuals with FHD should improve their lifestyle before T2DM onset.
https://doi.org/10.1155/2017/9707284
Conflicts of Interest
The authors declare that there is no conflict of interest regarding the publication of this paper.
Authors' Contributions
The first authors Yanyan Zhao and Chunhua Song contributed equally to this work. All authors have conceived and designed the study, performed the experiments, analyzed the data, and written the paper.
Acknowledgments
The authors would like to thank Dr. Chunhua Song, Department of Epidemiology, School of Public Health of Zhengzhou University, Henan, China, for her advice on the study design. This study was supported by the REACTION study (NO12020340324) from the Chinese Medical Association and Chinese Society of Endocrinology. This study was supported by the grants from the Chinese Society of Endocrinology and the National Clinical Research Center for Metabolic Diseases (2013BAI09B13).
References
[1] R. Lozano, M. Naghavi, K. Foreman et al., "Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010," The Lancet, vol. 380, no. 9859, pp. 2095-2128, 2012.
[2] C. J. L. Murray, T. Vos, R. Lozano et al., "Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010," The Lancet, vol. 380, no. 9859, pp. 2197-2223, 2012.
[3] W. Yang, J. Lu, J. Weng et al., "Prevalence of diabetes among men and women in China," New England Journal of Medicine, vol. 362, no. 12, pp. 1090-1101, 2010.
[4] R. M. van Dam, E. B. Rimm, W. C. Willett, M. J. Stampfer, and F. B. Hu, "Dietary patterns and risk for type 2 diabetes mellitus in U.S. men," Annals of Internal Medicine, vol. 136, no. 3, pp. 201-209, 2002.
[5] T. T. Fung, M. Schulze, J. E. Manson, W. C. Willett, and F. B. Hu, "Dietary patterns, meat intake, and the risk of type 2 diabetes in women," Archives of Internal Medicine, vol. 164, no. 20, pp. 2235-2240, 2004.
[6] A. Astrup, J. Dyerberg, M. Selleck, and S. Stender, "Nutrition transition and its relationship to the development of obesity and related chronic diseases," Obesity Reviews, vol. 9, Supplement 1, pp. 48-52, 2008.
[7] Z. Sun, L. Zheng, R. Detrano et al., "Incidence and predictors of hypertension among rural Chinese adults: results from Liaoning province," Annals of Family Medicine, vol. 8, no. 1, pp. 19-24, 2010.
[8] X. Zhang, Z. Sun, X. Zhang et al., "Prevalence and associated factors of overweight and obesity in a Chinese rural population," Obesity (Silver Spring), vol. 16, no. 1, pp. 168-171, 2008.
[9] M. I. Schmidt, B. B. Duncan, H. Bang et al., "Identifying individuals at high risk for diabetes: The atherosclerosis risk in communities study," Diabetes Care, vol. 28, no. 8, pp. 2013-2018, 2005.
[10] C. Wikner, B. Gigante, M. L. Hellenius, U. de Faire, and K. Leander, "The risk of type 2 diabetes in men is synergistically affected by parental history of diabetes and overweight," PloS One, vol. 8, no. 4, Article ID e61763, 2013.
[11] P. F. Wilson, J. B. Meigs, L. Sullivan, C. S. Fox, D. M. Nathan, and R. B. D'Agostino, "Prediction of incident diabetes mellitus in middle-aged adults: the Framingham offspring study," Archives of Internal Medicine, vol. 167, no. 10, pp. 1068-1074, 2007.
[12] InterAct Consortium, "The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study," Diabetologia, vol. 56, no. 1, pp. 60-69, 2013.
[13] V. J. Carey, E. E. Walters, G. A. Colditz et al., "Body fat distribution and risk of non-insulin-dependent diabetes mellitus in women: the Nurses' Health Study," American Journal of Epidemiology, vol. 145, no. 7, pp. 614-619, 1997.
[14] J. E. Manson, M. J. Stampfer, G. A. Colditz et al., "Physical activity and incidence of non-insulin-dependent diabetes mellitus in women," The Lancet, vol. 338, no. 8770, pp. 774-778, 1991.
[15] K. M. V. Narayan, J. P. Boyle, T. J. Thompson, E. W. Gregg, and D. F. Williamson, "Effect of BMI on lifetime risk for diabetes in the US," Diabetes Care, vol. 30, no. 6, pp. 1562-1566, 2007.
[16] E. Van't Riet, J. M. Dekker, Q. Sun, G. Nijpels, F. B. Hu, and R. M. van Dam, "Role of adiposity and lifestyle in the relationship between family history of diabetes and 20-year incidence of type 2 diabetes in U.S. women," Diabetes Care, vol. 33, no. 4, pp. 763-767, 2010.
[17] G. Ning and Reaction Study Group, "Risk evaluation of cAncers in Chinese diabetic individuals: a xxxxlONgitudinal (REACTION) study," Journal of Diabetes, vol. 4, no. 2, pp. 172-173, 2012.
[18] Y. Bi, J. Lu, W. Wang et al., "Cohort profile: risk evaluation of cancers in Chinese diabetic individuals: a longitudinal (REACTION) study," Journal of Diabetes, vol. 6, no. 2, pp. 147-157, 2014.
[19] R. V. Luepker, A. Evans, P. McKeigue, and K. S. Reddy, Cardiovascular Survey Methods, World Health Organization, Geneva, 3rd edition edition, 2004.
[20] T. Andersson, L. Alfredsson, H. Kallberg, S. Zdravkovic, and A. Ahlbom, "Calculating measures of biological interaction," European Journal of Epidemiology, vol. 20, no. 7, pp. 575-579, 2005.
[21] L. Kalilani and J. Atashili, "Measuring additive interaction using odds ratios," Epidemiologic Perspectives & Innovations, vol. 3, p. 5, 2006.
[22] E. Ahlqvist, T. S. Ahluwalia, and L. Groop, "Genetics of type 2 diabetes," Clinical Chemistry, vol. 57, no. 2, pp. 241-254, 2011.
[23] J. E. Shaw, R. A. Sicree, and P. Z. Zimmet, "Global estimates of the prevalence of diabetes for 2010 and 2030," Diabetes Research and Clinical Practice, vol. 87, no. 1, pp. 4-14, 2010.
[24] C. L. Gillies, K. R. Abrams, P. C. Lambert et al., "Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis," BMJ, vol. 334, no. 7588, p. 299, 2007.
[25] A. Chandrasekara and T. Josheph Kumar, "Roots and tuber crops as functional foods: a review on phytochemical constituents and their potential health benefits," International Journal of Food Science, vol. 2016, p. 3631647, 2016.
[26] C. Ekmekcioglu, P. Wallner, M. Kundi, U. Weisz, W. Haas, and H. P. Hutter, "Red meat, diseases and healthy alternatives: a critical review," Critical Reviews in Food Science and Nutrition, 2016.
[27] C. Heidemann, K. Hoffmann, J. Spranger et al., "A dietary pattern protective against type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study cohort," Diabetologia, vol. 48, no. 6, pp. 1126-1134, 2005.
[28] J. Mursu, J. K. Virtanen, T. P. Tuomainen, T. Nurmi, and S. Voutilainen, "Intake of fruit, berries, and vegetables and risk of type 2 diabetes in Finnish men: the Kuopio Ischaemic Heart Disease Risk Factor Study," The American Journal of Clinical Nutrition, vol. 99, no. 2, pp. 328-333, 2014.
[29] R. Villegas, Y. T. Gao, G. Yang et al., "Legume and soy food intake and the incidence of type 2 diabetes in the Shanghai Women's Health Study," The American Journal of Clinical Nutrition, vol. 87, no. 1, pp. 162-167, 2008.
[30] N. T. Mueller, A. O. Odegaard, M. D. Gross et al., "Soy intake and risk of type 2 diabetes in Chinese Singaporeans [corrected]," European Journal of Nutrition, vol. 51, no. 8, pp. 1033-1040, 2012.
[31] D. Y. Kwon, J. W. Daily 3rd, H. J. Kim, and S. Park, "Antidiabetic effects of fermented soybean products on type 2 diabetes," Nutrition Research, vol. 30, no. 1, pp. 1-13, 2010.
[32] S. M. Robson, S. C. Couch, J. L. Peugh et al., "Parent diet quality and energy intake are related to child diet quality and energy intake," Journal of the Academy of Nutrition and Dietetics, vol. 116, no. 6, pp. 984-990, 2016.
[33] A. Abbasi, E. Corpeleijn, Y. T. van der Schouw et al., "Maternal and paternal transmission of type 2 diabetes: influence of diet, lifestyle and adiposity," Journal of Internal Medicine, vol. 270, no. 4, pp. 388-396, 2011.
[34] S. Basu, D. Stuckler, M. McKee, and G. Galea, "Nutritional determinants of worldwide diabetes: an econometric study of food markets and diabetes prevalence in 173 countries," Public Health Nutrition, vol. 16, no. 01, pp. 179-186, 2013.
[35] G. A. Bray, K. A. Jablonski, W. Y. Fujimoto et al., "Relation of central adiposity and body mass index to the development of diabetes in the diabetes prevention program," The American Journal of Clinical Nutrition, vol. 87, no. 5, pp. 1212-1218, 2008.
[36] P. A. Sanz, C. D. Boj, L. I. Melchor, and G. R. Albero, "Sugar and diabetes: international recommendations," Nutricion Hospitalaria, vol. 28, Supplement 4, pp. 72-80, 2013.
Yanyan Zhao, (1) Chunhua Song, (2) Xiaokun Ma, (1) Xiaojun Ma, (1) Qingzhu Wang, (1) Hongfei Ji, (1) Feng Guo, (1) and Guijun Qin (1)
(1) Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital, Zhengzhou University, Zhengzhou 450052, China
(2) Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450052, China
Correspondence should be addressed to Guijun Qin; hyqingj@zzu.edu.cn
Received 30 November 2016; Revised 24 February 2017; Accepted 19 March 2017; Published 13 April 2017
Academic Editor: Andrea Tura
Table 1: Characteristics of the participants.
T2DM
N (%)
Sex (male/female) 477/757
Age (median, range) 63 (36, 90)
[less than or equal to] 49 117 (9.5%)
50-59 336 (27.3%)
60-69 481 (39.0%)
70-79 268 (21.8%)
[greater than or equal to] 80 30 (2.4%)
BMI (median, range) 26.2 (15.8, 39.7)
<18.5 7 (0.6%)
18.5-23.9 283 (23.1%)
24-27.9 546 (44.6%)
[greater than or equal to] 28 388 (31.7%)
WHR (median, range) 0.918 (0.596, 1.600)
Non-T2DM P value
N (%)
Sex (male/female) 2705/5910 <0.001
Age (median, range) 58 (23, 101) <0.001
[less than or equal to] 49 1929 (22.4%) <0.001
50-59 2973 (34.5%) --
60-69 2508 (29.1%) --
70-79 1066 (12.4%) --
[greater than or equal to] 80 138 (1.6%) --
BMI (median, range) 25.7 (14.2, 39.6) <0.001
<18.5 77 (0.9%) <0.001
18.5-23.9 2534 (29.6%) --
24-27.9 3683 (43.0%) --
[greater than or equal to] 28 2282 (26.6%) --
WHR (median, range) 0.896 (0.420, 1.598) <0.001
BMI: body mass index; WHR: waist-to-hip ratio.
Table 2: FHD and lifestyle of the participants.
Variables T2DM Non-T2DM
N (%) N (%)
FHD Yes 332 (26.9%) 1025 (11.9%)
No 902 (73.1%) 7590 (88.1%)
Current smoking Never 1063 (86.2%) 7278 (84.6%)
<7 cigarettes/ 47 (3.8%) 285 (3.31%)
week
[greater than 123 (10.0%) 1037 (12.1%)
or equal to] 7
cigarettes/
week
Previous
smoking
Never 920 (81.9%) 6647 (86.3%)
<7 81 (7.2%) 496 (6.4%)
cigarettes/week
[greater than 123 (10.9%) 558 (7.3%)
or equal to] 7
cigarettes/week
Current Never 988 (80.1%) 6719 (78.1%)
drinking
< once/week 171 (13.9%) 1264 (14.7%)
[greater than 74 (6.0%) 616 (7.2%)
or equal to]
once/week
Grain (g/d) <300 249 (20.2%) 1682 (19.6%)
[greater than 984 (79.8%) 6915 (80.4%)
or equal to]
300
Potatoes (g/d) <15 761 (61.7%) 4328 (50.4%)
[greater than 472 (38.3%) 4263 (49.6%)
or equal to] 15
Pork (g/d) <15 759 (61.6%) 4856 (56.5%)
[greater than 473 (38.4%) 3735 (43.5%)
or equal to] 15
Beef and mutton <4 626 (50.8%) 4341 (50.5%)
(g/d)
[greater than 607 (49.2%) 4250 (49.5%)
or equal to] 4
Poultry (g/d) <8 713 (57.8%) 4568 (53.2%)
[greater than 520 (42.2%) 4024 (46.8%)
or equal to] 8
Fish and <7 724 (58.7%) 4943 (57.5%)
seafood (g/d)
[greater than 509 (41.3%) 3649 (42.5%)
or equal to] 7
Vegetable (g/d) <300 452 (36.7%) 3081 (35.9%)
[greater than 781 (63.3%) 5514 (64.2%)
or equal to]
300
Fresh fruits <85 834 (67.6%) 4126 (48.0%)
(g/d)
[greater than 399 (32.4%) 4466 (52.0%)
or equal to] 85
Freshly Yes 181 (14.7%) 2301 (26.8%)
squeezed
vegetable and No 1052 (85.3%) 6288 (73.2%)
fruit juices
Eggs (g/d) <50 491 (39.8%) 3611 (42.0%)
[greater than 743 (60.2%) 4982 (58.0%)
or equal to] 50
Soy products <30 779 (63.2%) 5569 (64.8%)
(g/d)
[greater than 454 (36.8%) 3025 (35.2%)
or equal to] 30
Days of <3 310 (25.1%) 2748 (31.9%)
walking/week
[greater than 924 (74.9%) 5867 (68.1%)
or equal to] 3
Sitting time on <3 290 (23.5%) 2116 (24.6%)
weekdays (h/d)
3-5 503 (40.8%) 3603 (41.8%)
>5 441 (35.7%) 2896 (33.6%)
Sitting time on <3 323 (26.2%) 2357 (27.4%)
weekend (h/d)
3-5 501 (40.6%) 3424 (39.7%)
>5 410 (33.2%) 2834 (32.9%)
Variables P value
FHD Yes <0.001
No
Current smoking Never 0.079
<7 cigarettes/
week
[greater than
or equal to] 7
cigarettes/
week
Previous <0.001
smoking
Never <0.001
<7 0.332
cigarettes/week
[greater than <0.001
or equal to] 7
cigarettes/week
Current Never 0.209
drinking
< once/week
[greater than
or equal to]
once/week
Grain (g/d) <300 0.603
[greater than
or equal to]
300
Potatoes (g/d) <15 <0.001
[greater than
or equal to] 15
Pork (g/d) <15 <0.001
[greater than
or equal to] 15
Beef and mutton <4 0.874
(g/d)
[greater than
or equal to] 4
Poultry (g/d) <8 0.002
[greater than
or equal to] 8
Fish and <7 0.430
seafood (g/d)
[greater than
or equal to] 7
Vegetable (g/d) <300 0.578
[greater than
or equal to]
300
Fresh fruits <85 <0.001
(g/d)
[greater than
or equal to] 85
Freshly Yes <0.001
squeezed
vegetable and No
fruit juices
Eggs (g/d) <50 0.137
[greater than
or equal to] 50
Soy products <30 0.265
(g/d)
[greater than
or equal to] 30
Days of <3 <0.001
walking/week
[greater than
or equal to] 3
Sitting time on <3 0.329
weekdays (h/d)
3-5
>5
Sitting time on <3 0.674
weekend (h/d)
3-5
>5
FHD: family history of diabetes.
Table 3: Associations of T2DM with a parental history of T2DM.
Crude OR 95% CI P value
Uniparental FHD 2.022 (1.698, 2.408) <0.001
Paternal FHD 1.851 (1.416, 2.421) <0.001
Maternal FHD 2.319 (1.913, 2.812) <0.001
Biparental FHD 3.53 (2.029, 6.143) <0.001
FHD 2.726 (2.366, 3.141) <0.001
Adjusted OR * 95% CI P value
Uniparental FHD 2.841 (2.358, 3.423) <0.001
Paternal FHD 2.530 (1.911, 3.349) <0.001
Maternal FHD 3.274 (2.669, 4.016) <0.001
Biparental FHD 5.264 (2.975, 9.314) <0.001
FHD 3.586 (3.082, 4.173) <0.001
* Adjusted OR for age, gender, body mass index, and waist-to-hip
ratio. FHD: family history of diabetes.
Table 4: Multivariate analysis of associations between T2DM and
lifestyle.
Variables N Crude OR
Age
BMI
WHR Unit = 0.1
FHD Yes versus no
Sex Male versus
female
Current smoking Never 8305 --
<7 330 1.28
cigarettes/week
[greater than 1156 0.831
or equal to] 7
cigarettes/week
Never 7679 --
Current <once/week 1426 0.889
drinking
[greater than 686 0.798
or equal to]
once/week
Grain (g/d) [greater than 7877 --
or equal to]
300
<300 1914 1.001
Potatoes (g/d) [greater than 4720 --
or equal to] 15
<15 5071 1.411
Pork (g/d) [greater than 4199 --
or equal to] 15
<15 5592 1.121
Beef and mutton [greater than 4836 --
(g/d) or equal to] 4
<4 4955 0.768
Poultry (g/d) [greater than 4529 --
or equal to] 8
<8 5262 1.116
Fish and [greater than 4144 --
seafood (g/d) or equal to] 7
<7 5647 0.876
Vegetable (g/d) [greater than 6274 --
or equal to]
300
<300 3517 0.973
Fresh fruits [greater than 4846 --
(g/d) or equal to] 85
<85 4945 2.483
Freshly Yes 2478 --
squeezed
vegetable and No 7313 2.429
fruit juices
Egg (g/d) <50 3380 --
[greater than 706 1.185
or equal to] 50
Soy products <30 5705 --
(g/d)
[greater than 6325 1.244
or equal to] 30
Days of [less than or 1510 --
walking/week equal to] 3
>3 1956 1.418
Sitting time on <3 3040 --
weekdays (h/d)
3-5 6751 0.981
>5 2380 1.367
Sitting time on <3 4086 --
weekend (h/d)
3-5 3325 1.046
>5 2650 0.826
Variables 95% CI P
Age
BMI
WHR Unit = 0.1
FHD Yes versus no
Sex Male versus
female
Current smoking Never -- --
<7 (0.912, 1.794) 0.153
cigarettes/week
[greater than (0.661, 1.045) 0.114
or equal to] 7
cigarettes/week
Never -- --
Current <once/week (0.734, 1.078) 0.232
drinking
[greater than (0.601, 1.061) 0.12
or equal to]
once/week
Grain (g/d) [greater than -- --
or equal to]
300
<300 (0.852, 1.175) 0.993
Potatoes (g/d) [greater than -- --
or equal to] 15
<15 (1.236, 1.61) <0.001
Pork (g/d) [greater than -- --
or equal to] 15
<15 (0.978, 1.284) 0.1
Beef and mutton [greater than -- --
(g/d) or equal to] 4
<4 (0.667, 0.884) <0.001
Poultry (g/d) [greater than -- --
or equal to] 8
<8 (0.968, 1.287) 0.13
Fish and [greater than -- --
seafood (g/d) or equal to] 7
<7 (0.762, 1.008) 0.065
Vegetable (g/d) [greater than -- --
or equal to]
300
<300 (0.849, 1.114) 0.687
Fresh fruits [greater than -- --
(g/d) or equal to] 85
<85 (2.175,2.835) <0.001
Freshly Yes -- --
squeezed
vegetable and No (2.035, 2.899) <0.001
fruit juices
Egg (g/d) <50 -- --
[greater than (1.043, 1.346) 0.009
or equal to] 50
Soy products <30 -- --
(g/d)
[greater than (1.089, 1.42) 0.001
or equal to] 30
Days of [less than or -- --
walking/week equal to] 3
>3 (1.231, 1.634) <0.001
Sitting time on <3 -- --
weekdays (h/d)
3-5 (0.781, 1.232) 0.869
>5 (1.018, 1.836) 0.038
Sitting time on <3 -- --
weekend (h/d)
3-5 (0.838, 1.305) 0.692
>5 (0.618, 1.104) 0.197
Variables N Adjusted OR *
Age 1.045
BMI 1.022
WHR Unit = 0.1 1.554
FHD Yes versus no 3.509
Sex Male versus 1.381
female
Current smoking Never 8254 --
<7 327 1.026
cigarettes/week
[greater than 1150 0.734
or equal to] 7
cigarettes/week
Never 7630 --
Current <once/week 1418 0.785
drinking
[greater than 683 0.672
or equal to]
once/week
Grain (g/d) [greater than 7832 --
or equal to]
300
<300 1899 1.04
Potatoes (g/d) [greater than 4692 --
or equal to] 15
<15 5039 1.489
Pork (g/d) [greater than 4175 --
or equal to] 15
<15 5556 1.051
Beef and mutton [greater than 4801 --
(g/d) or equal to] 4
<4 4930 0.782
Poultry (g/d) [greater than 4503 --
or equal to] 8
<8 5228 1.1
Fish and [greater than 4120 --
seafood (g/d) or equal to] 7
<7 5611 0.847
Vegetable (g/d) [greater than 6236 --
or equal to]
300
<300 3495 0.921
Fresh fruits [greater than 4818 --
(g/d) or equal to] 85
<85 4913 2.339
Freshly Yes 2464 --
squeezed
vegetable and No 7267 2.232
fruit juices
Egg (g/d) <50 3358 --
[greater than 700 1.122
or equal to] 50
Soy products <30 5673 --
(g/d)
[greater than 6282 1.191
or equal to] 30
Days of [less than or 1506 --
walking/week equal to] 3
>3 1943 1.29
Sitting time on <3 3022 --
weekdays (h/d)
3-5 6709 0.99
>5 2363 1.385
Sitting time on <3 4069 --
weekend (h/d)
3-5 3299 0.986
>5 2638 0.747
Variables 95% CI P
Age (1.038, 1.053) <0.001
BMI (1.003, 1.042) 0.021
WHR Unit = 0.1 (1.386, 1.742) <0.001
FHD Yes versus no (2.999, 4.107) <0.001
Sex Male versus (1.165, 1.637) <0.001
female
Current smoking Never -- --
<7 (0.719, 1.463) 0.888
cigarettes/week
[greater than (0.574, 0.939) 0.014
or equal to] 7
cigarettes/week
Never -- --
Current <once/week (0.636, 0.968) 0.024
drinking
[greater than (0.498, 0.906) 0.009
or equal to]
once/week
Grain (g/d) [greater than -- --
or equal to]
300
<300 (0.879, 1.229) 0.649
Potatoes (g/d) [greater than -- --
or equal to] 15
<15 (1.297, 1.709) <0.001
Pork (g/d) [greater than -- --
or equal to] 15
<15 (0.911,1.212) 0.495
Beef and mutton [greater than -- --
(g/d) or equal to] 4
<4 (0.675, 0.907) 0.001
Poultry (g/d) [greater than -- --
or equal to] 8
<8 (0.947,1.277) 0.211
Fish and [greater than -- --
seafood (g/d) or equal to] 7
<7 (0.731,0.98) 0.026
Vegetable (g/d) [greater than -- --
or equal to]
300
<300 (0.8, 1.061) 0.255
Fresh fruits [greater than -- --
(g/d) or equal to] 85
<85 (2.038, 2.684) <0.001
Freshly Yes -- --
squeezed
vegetable and No (1.86, 2.679) <0.001
fruit juices
Egg (g/d) <50 -- --
[greater than (0.981, 1.283) 0.092
or equal to] 50
Soy products <30 -- --
(g/d)
[greater than (1.037,1.368) 0.013
or equal to] 30
Days of [less than or -- --
walking/week equal to] 3
>3 (1.114,1.494) 0.001
Sitting time on <3 -- --
weekdays (h/d)
3-5 (0.779,1.258) 0.934
>5 (1.015,1.888) 0.04
Sitting time on <3 -- --
weekend (h/d)
3-5 (0.781,1.245) 0.905
>5 (0.551,1.014) 0.061
* Adjusted OR for age, gender, body mass index, waist-to-hip ratio,
and family history of diabetes.
Table 5: Interaction effects between FHD and dietary factors.
Number of OR of diabetes
exposed
Exposure cases
Grain [greater than or equal to] 6818
300 without FHD (reference)
Grain < 300 without FHD 1659 1.061 (0.894, 1.26)
Grain [greater than or equal to] 1081 2.791 (2.382, 3.27)
300 with FHD
Grain < 300 with FHD 272 2.672 (2.001, 3.568)
Pork [greater than or equal to] 3560
15 without FHD (reference)
Pork < 15 without FHD 4912 1.306 (1.131, 1.507)
Pork [greater than or equal to] 648 2.876 (2.316, 3.571)
15 with FHD
Pork < 15 with FHD 703 3.557 (2.905, 4.356)
Potatoes [greater than or equal 4066
to] 15 without FHD (reference)
Potatoes < 15 without FHD 4405 1.599 (1.388, 1.843)
Potatoes [greater than or equal 669 2.694 (2.161, 3.358)
to] 15 with FHD
Potatoes < 15 with FHD 684 4.529 (3.713, 5.525)
Beef and mutton [greater than or 4132
equal to] 4 without FHD
(reference)
Beef and mutton < 4 without FHD 4339 1.002 (0.873, 1.151)
Beef and mutton [greater than or 725 2.537 (2.08, 3.096)
equal to] 4 with FHD
Beef and mutton < 4 with FHD 628 2.974 (2.426, 3.645)
Poultry [greater than or equal 3841
to] 8 without FHD (reference)
Poultry < 8 without FHD 4631 1.215 (1.056, 1.398)
Poultry [greater than or equal 703 2.545 (2.063, 3.139)
to] 8 with FHD
Poultry < 8 with FHD 650 3.649 (2.981, 4.465)
Fish and seafood [greater than or 3546
equal to] 7 without FHD
(reference)
Fish and seafood < 7 without FHD 4926 1.048 (0.91, 1.206)
Fish and seafood [greater than or 612 2.585 (2.081, 3.212)
equal to] 7 with FHD
Fish and seafood < 7 with FHD 741 2.999 (2.463, 3.652)
Vegetable [greater than or equal 5400
to] 300 without FHD (reference)
Vegetable < 300 without FHD 3075 1.055 (0.915, 1.217)
Vegetable [greater than or equal 895 2.744 (2.302, 3.273)
to] 300 with FHD
Vegetable < 300 with FHD 458 2.875 (2.288, 3.613)
Fresh fruits [greater than or 4166
equal to] 85 without FHD
(reference)
Fresh fruits < 85 without FHD 4307 2.222 (1.918, 2.574)
Fresh fruits [greater than or 699 2.505 (1.979, 3.172)
equal to] 85 with FHD
Fresh fruits < 85 with FHD 653 6.91 (5.651, 8.451)
Freshly squeezed juice (yes) 2210
without FHD (reference)
Freshly squeezed juice (no) 6259 1.922 (1.599, 2.31)
without FHD
Freshly squeezed juice (yes) with 272 2.005 (1.349, 2.98)
FHD
Freshly squeezed juice (no) with 1081 5.342 (4.313, 6.616)
FHD
Egg < 50 without FHD (reference) 3560
Egg [greater than or equal to] 50 4915 1.102 (0.957, 1.268)
without FHD
Egg < 50 with FHD 1081 2.833 (2.263, 3.548)
Egg [greater than or equal to] 50 810 2.934 (2.419, 3.559)
with FHD
Soy products < 30 without FHD 5506
(reference)
Soy products [greater than or 1659 1.03 (0.892, 1.19)
equal to] 30 without FHD
Soy products < 30 with FHD 842 2.629 (2.194, 3.149)
Soy products [greater than or 511 2.989 (2.409, 3.707)
equal to] 30 with FHD
S (95% CI)
Exposure
Grain [greater than or equal to]
300 without FHD (reference)
Grain < 300 without FHD
Grain [greater than or equal to]
300 with FHD
Grain < 300 with FHD 0.902 (0.547, 1.489)
Pork [greater than or equal to]
15 without FHD (reference)
Pork < 15 without FHD
Pork [greater than or equal to]
15 with FHD
Pork < 15 with FHD 1.172 (0.83, 1.657)
Potatoes [greater than or equal
to] 15 without FHD (reference)
Potatoes < 15 without FHD
Potatoes [greater than or equal
to] 15 with FHD
Potatoes < 15 with FHD 1.539 (1.117, 2.121)
Beef and mutton [greater than or
equal to] 4 without FHD
(reference)
Beef and mutton < 4 without FHD
Beef and mutton [greater than or
equal to] 4 with FHD
Beef and mutton < 4 with FHD 1.282 (0.856, 1.919)
Poultry [greater than or equal
to] 8 without FHD (reference)
Poultry < 8 without FHD
Poultry [greater than or equal
to] 8 with FHD
Poultry < 8 with FHD 1.505 (1.044, 2.171)
Fish and seafood [greater than or
equal to] 7 without FHD
(reference)
Fish and seafood < 7 without FHD
Fish and seafood [greater than or
equal to] 7 with FHD
Fish and seafood < 7 with FHD 1.224 (0.821, 1.824)
Vegetable [greater than or equal
to] 300 without FHD (reference)
Vegetable < 300 without FHD
Vegetable [greater than or equal
to] 300 with FHD
Vegetable < 300 with FHD 1.042 (0.693, 1.566)
Fresh fruits [greater than or
equal to] 85 without FHD
(reference)
Fresh fruits < 85 without FHD
Fresh fruits [greater than or
equal to] 85 with FHD
Fresh fruits < 85 with FHD 2.167 (1.633, 2.877)
Freshly squeezed juice (yes)
without FHD (reference)
Freshly squeezed juice (no)
without FHD
Freshly squeezed juice (yes) with
FHD
Freshly squeezed juice (no) with 2.253 (1.456, 3.487)
FHD
Egg < 50 without FHD (reference)
Egg [greater than or equal to] 50
without FHD
Egg < 50 with FHD
Egg [greater than or equal to] 50 0.999 (0.681, 1.467)
with FHD
Soy products < 30 without FHD
(reference)
Soy products [greater than or
equal to] 30 without FHD
Soy products < 30 with FHD
Soy products [greater than or 1.199 (0.803, 1.79)
equal to] 30 with FHD
FHD: family history of diabetes.
 Printer friendly
 Cite/link
 Email
 Feedback
| |
| Title Annotation: | Research Article |
|---|---|
| Author: | Zhao, Yanyan; Song, Chunhua; Ma, Xiaokun; Ma, Xiaojun; Wang, Qingzhu; Ji, Hongfei; Guo, Feng; Qin, G |
| Publication: | International Journal of Endocrinology |
| Article Type: | Report |
| Geographic Code: | 9CHIN |
| Date: | Jan 1, 2017 |
| Words: | 7132 |
| Previous Article: | Thyroid Imaging Reporting and Data System Score Combined with the New Italian Classification for Thyroid Cytology Improves the Clinical Management of... |
| Next Article: | Ultrasound-Guided Percutaneous Microwave Ablation for Solid Benign Thyroid Nodules: Comparison of MWA versus Control Group. |
| Topics: | |