Modifiable Risk Factors Associated With Prediabetes in Men and Women

A Cross-sectional Analysis of the Cohort Study in Primary Health Care on the Evolution of Patients With Prediabetes (PREDAPS-Study)

Alicia Díaz-Redondo; Carolina Giráldez-García; Lourdes Carrillo; Rosario Serrano; Francisco Javier García-Soidán; Sara Artola; Josep Franch; Javier Díez; Patxi Ezkurra; José Manuel Millaruelo; Mateu Seguí; Javier Sangrós; Juan Martínez-Candela; Pedro Muñoz; Albert Goday; Enrique Regidor

Disclosures

BMC Fam Pract. 2015;16(5)

Discussion

This study showed that known cardiovascular risk factors, specifically abdominal obesity, hypertension and low HDL-Cholesterol levels, are independently associated with the presence of prediabetes in women and men alike. Additionally, general obesity in women and alcohol consumption in men are risk factors for prediabetes. General obesity was also associated with prediabetes in men, although the statistical significance disappeared after adjustment for all factors. The modifiable risk factors that showed the strongest association with prediabetes was abdominal obesity. The magnitudes of the associations were stronger for men than women. Smoking, physical activity, and diet habits not showed significant relationship with prediabetes.

As other studies, obesity in our study subjects –both general and, more specifically, abdominal– was associated with the presence of prediabetes.^[7,22] Moreover, when a wide number of risk factors had been examined simultaneously, as we have done in our study, waist circumference had showed the strongest direct effect on prediabetes.^[22] Although the mechanisms are not clear, excess adipose tissue has been reported to release fatty acids, something that induces resistance to insulin in the muscle and, in turn, leads to elevation of plasma glucose levels.^[13] Also, measures of abdominal obesity have been found as the strongest predictors of diabetes.^[23]

The association between hypertension/dyslipidemia and prediabetes has been reported previously.^[7,14,24] In our study, hypertension displayed an important association with prediabetes, particularly among men. Hypertriglyceridemia and low HDL-Cholesterol levels were also seen to be associated with prediabetes, though only the association with low HDL-Cholesterol levels proved to be significant in both sexes. Moreover, when the rest variables had been adjusted for, the magnitude of the association between these factors and prediabetes fell substantially in both sexes, though hypertension and low HDL-Cholesterol levels remain as independent risk factors for prediabetes. This weakening, in the association between dyslipidemia and hypertension with prediabetes, is basically due to the inclusion of obesity in the model. This is supported by the strong association existing between obesity and blood pressure, although the mechanisms are not yet fully known.^[25] Also, Bardenheier et al. found in their model that the direct effect of hypertension on prediabetes was confounded by waist circumference.^[22]

A number of studies have reported that alcohol consumption in men, and excessive consumption in particular, is associated with the appearance of prediabetes and type 2 diabetes, whereas alcohol consumption in women displays a protective effect for the appearance of these health problems.^[26,27] In our study, alcohol consumption was found as a modifiable risk factor for prediabetes in men. Likewise, a lower frequency of risky drinkers was observed among women with prediabetes than among those without glucose disorders, but the differences were not significant.

It has noted that frequency and quality of breakfast is related with regulation of appetite and control of plasma glucose levels.^[28] Also, positive associations between skipping breakfast and fasting glucose and fasting insulin have been observed.^[29] In our study, although the magnitude of this association was high in women, no statistically significant relationship was found between absent or incomplete breakfast and prediabetes. On the other hand, no relationship was found between consumption of other foods and the presence of prediabetes. This is consistent with the observed by others in relation to fruit and vegetables consumption,^[14] but it is contrary to the protective effect of foods such as fish, vegetables and legumes on glucose disorders that has been reported.^[30]

Although the physical exercise is known as a protective factor for the development of type 2 diabetes,^[31] the failure to follow the WHO physical-activity recommendations was not shown to be associated with the presence of prediabetes in our study. Other studies have obtained similar findings.^[14] In relation to smoking, it is a known risk factor of diabetes;^[32] however, there is inconsistent evidence about prediabetes. Some findings are agreed with ours,^[14] but in others smoking was reported as a risk factor.^[33] The criteria of prediabetes used in above studies differ from those we used in our study, and therefore, the groups formed in each study are not fully comparable to each other.

Strengths and Limitations

The main strength of the present study is the focus on the prediabetes state. Also, we have included a large number of participants from across Spain from primary care setting. However, when it comes to interpreting the findings, some limitations must be borne in mind. First, this study should be consider as a cross-sectional in design, since it was based on data collected during the baseline stage of a follow-up study. Hence, one cannot exclude the possibility that subjects with prediabetes might have modified their lifestyles and acquired healthier habits. Second, this study included subjects with prediabetes based on HbA1c and FPG criteria, the exclusion of oral glucose overload as criteria for prediabetes was due to it is an expensive and impractical procedure at a primary health-care level. The two criteria used (FPG and HbA1c) have been widely accepted by the American Diabetes Association.^[8] Third, the number of patients included in the prediabetes cohort is greater than the number of patients included in the cohort of subjects without glucose metabolism disorders. Many physicians included patients with normal FPG levels in the second cohort without waiting for the result of the HbA1c analytical tests, when the HbA1c results arrived, some patients were found to be prediabetic and were changed to the prediabetes cohort. Fourth, in our study subjects were health service users, this mean that it would be expected that subjects without glucose metabolism disorders display a higher frequency of risk factors than would the general population; thus, the possibility of identifying risk factors associated with prediabetes would be correspondingly lower than in population-based studies.

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Table 1. Percent distribution of sociodemographic characteristics and family history of diabetes mellitus in men and women
Characteristics	Men			Women
Characteristics	With prediabetes N = 595	Without glucose metabolism disorders N = 388	p-value	With prediabetes N = 589	Without glucose metabolism disorders N = 450	p-value
Age
30–49 years	16.5	22.4	0.013	15.1	25.3	<0.001
50–64 years	50.4	51.8		49.1	46.4
65–74 years	33.1	25.8		35.8	28.2
Educational level ^*
Low	59.0	52.3	0.042	70.1	59.6	<0.001
High	41.0	47.7	0.042	29.9	40.4	<0.001
Marital status
Without partner	15.8	18.3	0.337	27.5	27.1	0.944
Married or with partner	84.2	81.7	0.337	72.5	72.9	0.944
Region of residence ^†
North	41.5	39.4	0.131	36.2	36.0	0.955
Centre	30.4	36.3		33.6	34.4
South	28.1	24.2		30.2	29.6
Family history of diabetes ^‡
Yes	43.4	33.8	0.003	50.6	34.2	<0.001
No	56.6	66.2	0.003	49.4	65.8	<0.001

Data are showed in percentages.
*Low educational level: lower than secondary (equivalent to less than 12 years of education); high educational level: secondary or higher (equivalent to 12 years or more of education).
^†North: Galicia, Asturias, Cantabria, Basque Country, Navarre, La Rioja, Aragon, Catalonia; Centre: Castile- León, Madrid, Extremadura, Castile-La Mancha; South: Andalusia, Murcia, Valencia, Balearic Isles, Canary Islands.
^‡Family history of diabetes in father, mother, siblings or children.

Table 2. Percent distribution of modifiable risk factors present in men and women
Risk factors	Men			Women
Risk factors	With prediabetes N = 595	Without glucose metabolism disorders N = 388	p-value	With prediabetes N = 589	Without glucose metabolism disorders N = 450	p-value
Smoking habit
Current smoker	18.7	24.7	0.003	14.6	20.2	0.580
Alcohol consumption
Risky drinker	34.1	31.2	0.015	12.7	12.9	0.469
Physical activity
WHO recommendations not followed	38.4	37.4	0.788	51.2	49.6	0.617
Diet
Incomplete or absent breakfast	16.3	15.7	0.859	10.9	8.0	0.137
Non-daily fruit consumption	26.6	25.8	0.824	17.7	20.0	0.377
Non-daily vegetable consumption	49.6	52.1	0.473	36.7	37.1	0.897
Fish consumed <3 times per week	57.6	61.1	0.289	52.8	54.9	0.530
Legumes consumed <3 times per week	64.4	68.0	0.243	69.1	70.2	0.734
Blood pressure
Hypertension^*	72.3	51.3	<0.001	61.6	44.2	<0.001
Lipids
Hypercholesterolemia^†	11.3	12.9	0.481	16.6	14.7	0.440
Hypertriglyceridemia^‡	14.6	10.4	0.064	10.9	6.2	0.011
Low HDL-Cholesterol^§	20.4	12.2	0.001	28.3	18.9	0.001
Obesity
General obesity^\|\|	42.4	23.2	<0.001	43.6	25.1	<0.001
Abdominal obesity^¶	59.4	33.0	<0.001	75.2	52.2	<0.001

Data are showed in percentages.
*Hypertension: mean systolic pressure ≥140 mmHg, or mean diastolic pressure ≥90 mmHg, or being under treatment with antihypertensive drugs, or a personal history of arterial hypertension.
^†Hypercholesterolemia: plasma total cholesterol ≥250 mg/dl.
^‡Hypertriglyceridemia: plasma triglycerides ≥200 mg/dl.
^§Low HDL-Cholesterol: plasma High-Density Lipoprotein cholesterol <40 mg/dl in men, and <50 mg/dl in women.
^||General obesity: Body Mass Index ≥30 kg/m².
^¶Abdominal obesity: waist circumference ≥102 cm in men, and ≥88 cm in women.

Table 3. Association between modifiable risk factors and presence of prediabetes in men
Risk factors	Model 1		Model 2
Risk factors	OR	(95% CI)	OR	(95% CI)
Smoking habit
Current smoker vs. never smoker	0.94	(0.65–1.37)	0.77	(0.51–1.16)
Consumption of alcohol
Risky drinker vs. abstinent	1.58	(1.09–2.28)	1.49	(1.00–2.24)
Physical activity
WHO recommendations not followed vs. followed	1.13	(0.86–1.48)	1.10	(0.82–1.49)
Breakfast
Incomplete or absent vs. complete	1.12	(0.78–1.60)	1.10	(0.75–1.63)
Consumption of fruit
Non-daily vs. daily consumption	1.16	(0.86–1.57)	1.26	(0.89–1.77)
Consumption of vegetables
Non-daily vs. daily consumption	0.96	(0.74–1.25)	0.88	(0.65–1.19)
Consumption of fish
Consumption of <3 vs. >3 times per week	0.88	(0.67–1.16)	0.91	(0.68–1.23)
Consumption of legumes
Consumption of <3 vs. >3 times per week	0.87	(0.66–1.14)	0.84	(0.63–1.13)
Blood pressure
Hypertension^* vs. no hypertension	2.33	(1.76–3.08)	1.86	(1.39–2.51)
Lipids
Hypercholesterolemia^† vs. no hypercholesterolemia	0.85	(0.57–1.27)	0.99	(0.64–1.53)
Hypertriglyceridemia^‡ vs. no hypertriglyceridemia	1.61	(1.07–2.42)	1.19	(0.75–1.90)
Low HDL-Cholesterol^§ vs. high HDL-Cholesterol	1.94	(1.34–2.82)	1.88	(1.23–2.88)
Obesity
General obesity^\|\| vs. no general obesity	2.51	(1.88–3.36)	1.43	(0.99–2.06)
Abdominal obesity^¶ vs. no abdominal obesity	2.87	(2.19–3.77)	1.98	(1.41–2.79)

Data are showed in odds ratios (OR) and 95% confidence intervals (95% CI). Model 1 is adjusted for age, educational level, marital status, region of residence, and family history of diabetes. Model 2 is adjusted for all the variables in the table plus age, educational level, marital status, region of residence, and family history of diabetes. Data in bold indicate statistically significant associations.
*Hypertension: mean systolic pressure ≥140 mmHg, or mean diastolic pressure ≥90 mmHg, or being under treatment with antihypertensive drugs, or a personal history of arterial hypertension.
^†Hypercholesterolemia: plasma total cholesterol ≥250 mg/dl.
^‡Hypertriglyceridemia: plasma triglycerides ≥200 mg/dl.
^§Low HDL-Cholesterol: plasma High-Density Lipoprotein cholesterol <40 mg/dl.
^||General obesity: Body Mass Index ≥30 kg/m².
^¶Abdominal obesity: waist circumference ≥102 cm.

Table 4. Association between modifiable risk factors and presence of prediabetes in women
Risk factors	Model 1		Model 2
Risk factors	OR	(95% CI)	OR	(95% CI)
Smoking habit
Current smoker vs. never smoker	0.82	(0.57–1.17)	0.75	(0.50–1.11)
Consumption of alcohol
Risky drinker vs. abstinent	1.00	(0.66–1.50)	1.13	(0.72–1.76)
Physical activity
WHO recommendations not followed vs. followed	1.15	(0.89–1.48)	1.04	(0.79–1.37)
Breakfast
Incomplete or absent vs. complete	1.48	(0.95–2.30)	1.43	(0.89–2.30)
Consumption of fruit
Non-daily vs. daily consumption	1.06	(0.76–1.48)	0.94	(0.65–1.37)
Consumption of vegetables
Non-daily vs. daily consumption	0.98	(0.75–1.27)	0.93	(0.70–1.24)
Consumption of fish
Consumption of <3 vs. >3 times per week	0.95	(0.73–1.23)	0.94	(0.71–1.26)
Consumption of legumes
Consumption of <3 vs. >3 times per week	0.94	(0.71–1.23)	0.88	(0.66–1.19)
Blood pressure
Hypertension* vs. no hypertension	1.79	(1.37–2.35)	1.44	(1.07–1.92)
Lipids
Hypercholesterolemia^† vs. no hypercholesterolemia	1.04	(0.74–1.48)	1.13	(0.78–1.65)
Hypertriglyceridemia^‡ vs. no hypertriglyceridemia	1.58	(0.98–2.54)	1.08	(0.64–1.80)
Low HDL-Cholesterol^§ vs. high HDL-Cholesterol	1.82	(1.33–2.49)	1.58	(1.12–2.23)
Obesity
General obesity^\|\| vs. no general obesity	2.26	(1.71–2.99)	1.42	(1.01–1.98)
Abdominal obesity^¶ vs. no abdominal obesity	2.55	(1.94–3.35)	1.89	(1.36–2.62)

Data are showed in odds ratios (OR) and 95% confidence intervals (95% CI). Model 1 is adjusted for age, educational level, marital status, region of residence, and family history of diabetes. Model 2 is adjusted for all the variables in the table plus age, educational level, marital status, region of residence, and family history of diabetes. Data in bold indicate statistically significant associations.
*Hypertension: mean systolic pressure ≥140 mmHg, or mean diastolic pressure ≥90 mmHg, or being under treatment with antihypertensive drugs, or a personal history of arterial hypertension.
^†Hypercholesterolemia: plasma total cholesterol ≥250 mg/dl.
^‡Hypertriglyceridemia: plasma triglycerides ≥200 mg/dl.
^§Low HDL-Cholesterol: plasma High-Density Lipoprotein cholesterol <50 mg/dl. ^||General obesity: Body Mass Index ≥30 kg/m².
^¶Abdominal obesity: waist circumference ≥ 88 cm.

Authors and Disclosures

Alicia Díaz-Redondo¹, Carolina Giráldez-García^2*, Lourdes Carrillo³, Rosario Serrano⁴, Francisco Javier García-Soidán⁵, Sara Artola⁶, Josep Franch⁷, Javier Díez⁸, Patxi Ezkurra⁹, José Manuel Millaruelo¹⁰, Mateu Seguí¹¹, Javier Sangrós¹⁰, Juan Martínez-Candela¹², Pedro Muñoz¹³, Albert Goday¹⁴ and Enrique Regidor^2,15

¹Department of Preventive Medicine and Public Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain. ²Department of Preventive Medicine, Public Health (History of Science), Universidad Complutense de Madrid, Madrid, Spain. ³La Victoria de Acentejo Health Centre, Santa Cruz de Tenerife, Spain. ⁴Martin de Vargas Health Centre, Madrid, Spain. ⁵Porriño Health Centre, Pontevedra, Spain. ⁶Hereza Health Centre, Madrid, Spain. ⁷Raval-Sud Primary Care Team, Barcelona, Spain. ⁸Tafalla Health Centre, Navarra, Spain. ⁹Zumaia Health Centre, Guipúzcua, Spain. ¹⁰Torrero-La Paz Health Centre, Zaragoza, Spain. ¹¹Es Castell Basic Health Unit, Islas Baleares, Spain. ¹²Yecla Health Centre, Murcia, Spain. ¹³Family & Community Medicine Teaching Unit, Cantabria, Spain. ¹⁴Endocrinology & Nutrition Department, Del Mar Hospital, Barcelona, Spain. ¹⁵Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Madrid, Spain

*Correspondence
cvalle.giraldez@gmail.com

Competing interests
The authors declare that they have no competing interests. Funding was obtained from Sanofi and Novartis to support the development of the data collection platform, the meetings of researchers, and the monitoring of the information collected at baseline. Sanofi and Novartis had no role in the study design, analysis, interpretation of data, writing the manuscript, nor the decision to submit the manuscript for publication.

Authors' contributions
A D-R was the primary responsible for the statistical data analysis and draft the manuscript. CG-G participated in analysis and interpretation of data, and helped to draft the manuscript. JG-S, and RS contributed to conception and design of the study, acquisition of data, and helped to draft discussion section. LC, SA, JD, PE, JMM, MS, FJS, and JM-C participated in acquisition of data as regional coordinators, and review the initial manuscript. JF contributed to design the study, acquisition of data, and reviewed the initial manuscript. AG and PM contributed to design the study, research of data, and reviewed the initial manuscript. ER conceived and designed the study, and supervised the project, the statistical analysis, and the manuscript writing. All authors read and approved the final manuscript.