Preventive Medicine 59 (2014) 42–46
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Diagnosis of Diabetes Mellitus or Cardiovascular Disease and lifestyle changes — The Doetinchem Cohort Study A. Manschot a,b, S.H. van Oostrom a,⁎, H.A. Smit c, W.M.M. Verschuren a,c, H.S.J. Picavet a a b c
Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands University of Utrecht, The Netherlands Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
a r t i c l e
i n f o
Available online 22 November 2013 Keywords: Prospective cohort study Diabetes Mellitus Cardiovascular disease Physical activity Weight Smoking Diet Alcohol
a b s t r a c t Objective. To study whether being diagnosed with a cardiovascular disease (CVD) or diabetes mellitus (DM) is associated with improvements in lifestyles. Methods. We used data from the Doetinchem Cohort Study, a prospective study among 6386 Dutch men and women initially aged 20–59 years who were examined four times over 15 years (1987–2007). Logistic and linear regression models were used to assess the effect of a self-reported diagnosis of CVD (n = 403) or DM (n = 221) on smoking, alcohol consumption, weight, diet and physical activity. Results. Self-reported diagnosis of CVD increased rates of smoking cessation (OR = 2.2, 95%CI 1.6 – 3.1). Adults reporting a diagnosis of DM (relatively) decreased weight (3.2%, 95%CI 2.2 – 4.2), (relatively) decreased energy intake (4.2%, 95%CI 0.7 – 7.7), decreased energy percentage from saturated fat (0.4%, 95%CI 0.0 – 0.9) and increased fish consumption (2.8 g/day, 95%CI 0.4 – 5.1). A self-reported diagnosis of CVD or DM was not associated with changes in physical activity. Conclusion. A diagnosis of CVD or DM may act, along with possible effects of medical treatment, as a trigger to adopt a healthier lifestyle in terms of smoking cessation, healthier diet and weight loss. © 2013 Elsevier Inc. All rights reserved.
Introduction A healthy lifestyle reduces the risk of developing chronic diseases, and therefore contributes to healthy ageing (Anderson et al., 2003; Ockene and Miller, 1997). It is common knowledge that smoking, obesity, unhealthy diet and low levels of physical activity induce health risks. Nevertheless, adopting a healthy lifestyle appears to be quite a challenge, shown by the high and still increasing prevalence of obesity (Ogden et al., 2006) and physical inactivity (Lindström et al., 2003). Many interventions have been developed aiming to change unhealthy lifestyles in different phases in life (Hardeman et al., 2000; Spring et al., 2009; Tripodi et al., 2010). One of many reasons of failure to adopt a healthy lifestyle, may be due to the lack of a sense of urgency. Signs of health problems, for instance being diagnosed with a chronic disease, may act as a trigger to take responsibility for one's own health. There are examples of studies investigating changes in lifestyle after diagnosis of a chronic disease (Bak et al., 2002; Falba, 2005; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Keenan, 2009; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997; Van Gool Abbreviations: CVD, Cardiovascular Disease; DM, Diabetes Mellitus; DCS, Doetinchem Cohort Study; BMI, Body Mass Index; GEE, Generalized estimating equations. ⁎ Corresponding author. Fax: +31 30 2744407. E-mail addresses: [email protected] (A. Manschot), [email protected] (S.H. van Oostrom), [email protected] (H.A. Smit), [email protected] (W.M.M. Verschuren), [email protected] (H.S.J. Picavet). 0091-7435/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.11.013
et al., 2007). Some studies found increased rates of smoking cessation after a diagnosis of cardiovascular disease (CVD) (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008). Also, in diabetes mellitus (DM) cases, increased weight loss has been observed (Falba, 2005; Keenan, 2009; Van Gool et al., 2007). However, most of the studies measured lifestyle changes retrospectively, thus running the risk of recall bias. Also a control group was often lacking, rendering it impossible to control for a general trend in lifestyle changing behaviour (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997). In the present study, we investigated whether adults who reported a diagnosis of CVD or DM were more likely to change their lifestyles (smoking, alcohol consumption, diet (vegetable, fruit, fish, saturated fat, and energy intake), physical activity and weight) than adults without such a diagnosis. We used data from the Doetinchem Cohort Study, a prospective cohort study in the general population in The Netherlands (Verschuren et al., 2008).
Methods Study design and study population The Doetinchem Cohort Study (DCS) (Verschuren et al., 2008) is an ongoing prospective study in The Netherlands. The first measurement was carried out in a random, general population sample of men and women aged 20–59 years
A. Manschot et al. / Preventive Medicine 59 (2014) 42–46
(1987–1991). The aim of the DCS was to study the impact of (changes in) lifestyle factors and biological risk factors on various aspects of health, such as the incidence of chronic diseases, physical and cognitive functioning, and quality of life. The cohort is re-examined every five years with questionnaires and a physical examination at the local health services. Four subsequent examination rounds were completed in the years 1987–1991 (r1), 1993–1997 (r2), 1998–2002 (r3), and 2003–2007 (r4). All participants gave written informed consent, and the study was approved according to the guidelines of the Helsinki Declaration by the Medical Ethics Committee of the Netherlands Organization of Applied Scientific Research. Details on the DCS have been extensively described elsewhere (Verschuren et al., 2008). For the present study we defined our baseline population as those who participated at the first (r1) and at the second examination round (r2), i.e. 6386 participants. Measurements and variables Chronic diseases CVD cases were defined on the basis of self-reported myocardial infarction (Did you ever had a heart attack?), self-reported coronary heart disease (Have you ever had bypass surgery?; have you ever had cardiac catheterization?; have you ever had coronary angioplasty?), and self-reported intermittent claudication, based on the WHO/Rose questionnaire (Rose et al., 1977). Diabetes Mellitus (DM) concerned people who reported positive to the simple question ‘Do you have diabetes?’. Because of the age range of the population, we expect the majority of the DM cases to be type 2. Lifestyle-related characteristics Body Mass Index (BMI) was calculated by height and body weight, which were measured by trained staff in each examination round. Overweight was defined as a BMI between 25 and 30 kg/m2, and obesity was defined as a BMI equal to or above 30 kg/m2. Those who lost weight were defined as participants who changed to a lower BMI category (from obese to overweight or normal weight, or from overweight to normal weight) between two subsequent measurements. Relative weight loss among participants with a BMI equal to or above 25, was expressed as a percentage of weight at the beginning of each wave. Physical activity during leisure time was measured from 1994 (r2) onwards with an extensive self-administered questionnaire that includes questions on time spent walking, cycling, doing odd jobs, gardening, and sports activities in a regular week during the previous year (Picavet et al., 2011). The questionnaire was designed and validated for the international European Prospective Investigation Into Cancer and Nutrition study and extended with a question on sports and other strenuous leisure-time physical activities (Pols et al., 1997). To determine whether individuals reached the Dutch physical activity recommendations, defined as moderate or vigorous intensity activities for a minimum of half an hour a day for at least five days a week (Ainsworth et al., 2000; Kemper et al., 2000), the total time (hours/week) spent on moderate-tovigorous leisure time physical activities was calculated. Activities included in this calculation were cycling, gardening and sports (≥ 4.0 MET). The cut-off point for adhering to the recommended levels was set at 3.5 h a week, a conservative level to correct for overestimation of physical activity (Wilcox and King, 2000). Smoking of cigarettes, cigars and/or pipes was measured in all rounds. We considered participants to be smokers when they indicated to smoke cigarettes, cigars and/or pipes, irrespective of the frequency or quantity. Alcohol consumption, defined as the total number of glasses of beer, wine, and liquor drank per week, was measured in all measurement rounds. Alcohol guideline followers were based on the Dutch healthy nutrition guidelines (Dutch Health Counsil, 2006), i.e. a maximum of one consumption per day for women and of two consumptions per day for men. From round two (r2) onwards, an extensive food frequency questionnaire was included in the Doetinchem study (Ocké et al., 1997a,b). Based on this questionnaire several indicators of healthy food consumption were calculated: the fruit, vegetable and fish consumption expressed in grams per day, and the total daily energy intake. BMI, smoking and alcohol consumption were assessed at all four measurement rounds and changes in these variables were studied over three 5-year periods. Physical activity, and fruit, vegetable, fish and saturated fat consumption were assessed at three measurement rounds, changes in these variables were studied over two 5-year periods. Socio-demographic characteristics Age was classified into four categories of ten years at baseline. Educational level was assessed as the highest level reached at baseline and classified into
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three categories: low (intermediate secondary education or less), medium (intermediate vocational or higher secondary education) and high (higher vocational education or university). Data analyses Differences in adopting a healthy lifestyle were studied between adults with an unhealthy lifestyle at baseline who reported and did not report a diagnosis of DM or CVD within a 5-year period, excluding prevalent cases of DM or CVD. Smoking cessation was studied among smokers. Unhealthy alcohol consumption and physical activity were defined according to the relevant recommendations: for alcohol consumption ≥ 1 consumption per day for women and ≥2 consumptions per day for men (Dutch Health Counsil, 2006); for physical activity no moderate or vigorous levels of activity for at least 30 min a day at least 5 days/week (Ainsworth et al., 2000; Kemper et al., 2000). Weight loss and reduced energy intake were measured in those who were overweight (BMI ≥25). Fruit, vegetable, fish and saturated fat consumption was measured in the total population, since almost all participants' diets did not contain the recommended amounts (Dutch Health Counsil, 2006). Data on changes in physical activity and saturated fat consumption were available for two 5-year periods and for the other lifestyles, data were available for three 5-year periods. All analyses of lifestyle changes based on a dichotomous variable were performed with logistic regression analyses using generalized estimating equations (GEE) with an autoregressive correlation structure. Linear regression analyses using generalized estimating equations were performed to find out whether those who reported or did not report a diagnosis of CVD or DM differed in their change in daily vegetable, fruit, fish, and saturated fat consumption, relative weight, and total energy intake. GEE analyses were used to take into account the correlation between repeated measurements within individuals. In both logistic and linear regression analyses the reported diagnosis of DM or CVD was used as independent variables and changes in lifestyles were used as dependent variables. All analyses were adjusted for age, gender and educational level. Interactions between lifestyle changes and sex, age or educational level were studied among the significant associations. SAS software version 9.3 (Statistical Analysis System; SAS Institute, Inc., Cary, North Carolina) was used to perform the statistical analyses.
Results The study population consisted of 2994 men and 3392 women with a mean age of 37.8 years at r1 (Table 1). Baseline prevalences of unhealthy lifestyles were 34.1% for overweight, 6.8% for obesity, 37.1% for smoking, 21.8% for drinking more alcohol than guideline recommendations (measured at r1) and 18.3% for physical inactivity (measured at r2). Mean intake of dietary components at baseline was 112.4 g of vegetables per day, 168.5 g of fruit per day, and 9.3 g of fish per day. In total, 403 participants reported to be diagnosed with CVD and 221 with DM between r1 and r4. Participants who reported a diagnosis of CVD stopped smoking more frequently than participants who did not (OR 2.2, 95%CI 1.6 – 3.1) (Table 2). No statistically significant differences in weight loss, total energy intake, becoming physically active, fruit, vegetable, fish, and saturated fat consumption and alcohol intake were found between participants who reported a diagnosis of CVD and those who did not report CVD (Table 2 and 3). Participants who reported a diagnosis of DM more often changed BMI category (OR 2.8, 95%CI 1.9 – 4.0) (from obese to overweight or normal weight, or from overweight to normal weight) than those who did not report DM (Table 2). They showed a relative decrease in weight of 3.2% (95%CI 2.2 – 4.2). Participants who reported a diagnosis of DM decreased on average 1.6% in weight whereas those who did not report DM increased on average 2.1% in weight (Table 3). A relative decrease in total energy intake of 4.2% (95%CI 0.7 – 7.7), a decrease in the amount of energy derived from saturated fat of 0.4% (95%CI 0.0 – 0.9), and an increase in fish consumption (2.8 g/day, 95%CI 0.4 – 5.1) were shown for participants who reported a diagnosis of DM compared to those who did not report DM. No statistically significant differences for smoking cessation, becoming physically active, or for fruit, vegetable and alcohol consumption were found between participants who reported DM and those who did not.
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Table 1 Characteristics of the study population of the Doetinchem Cohort Study (1987–2007)a. % or means Total number of participants
n = 6386
Sociodemographic characteristics (at r1) Age (mean)
39.9 (10.2)
Gender Men Women Educational level Low level Medium level High level Living situation Living together Living alone
46.9% 53.1% 62.2% 21.4% 16.1% 84.3% 15.4%
Lifestyle-related characteristics Weight BMI (kg/m2) at baseline (mean) Obese at baseline (bmi ≥ 30kg/m2) Overweight at baseline (25 ≤ bmi b 30 kg/m2) Declined in weight category at least once in a 5-year period between r1 and r4 b Adherence to physical activity recommendations c Physical inactivity according to guideline at baseline (r2) Became physically active at least once in a 5-year period between r2 and r4 Smoking Smokers at baseline Stopped smoking at least once in a 5-year period between r1 and r4 Alcohol Alcohol consumers at baseline Consumptions per week per drinker at baseline (mean) Alcohol consumption exceeding guideline recommendations at baseline d Became guideline followers at least once in a 5-year period, between r1 and r4 Diet Relative saturated fat consumption of total daily energy intake (%) (mean) Vegetable consumption in grams/day at baseline (r2) (mean) Fruit consumption in grams/day at baseline (r2) (mean)
24.6 (3.5) 6.8% 34.1% 10.1%
19.1% 13.9%
37.1% 16.1%
86.2% 10.8 (9.7) 21.8% 21.9%
15.0 (2.4) 112.4 (45.0) 168.5 (128.1) 9.3 (9.4)
Fish consumption in grams/day at baseline (r2) (mean) Incidence of diseases between r1 and r4 Cardiovascular disease e Diabetes mellitus (type I and II) Both diabetes mellitus and cardiovascular disease
n = 403 n = 221 n = 21
6.3% 3.5% 0.3%
a Means and standard deviations for continuous variables, frequencies and percentages for categorical variables. b From obese to overweight or normal weight and from overweight to normal weight; r1 is the first measurement in the Doetinchem study. c The Dutch physical activity guidelines recommend adults to be physically active at moderate or vigorous levels for at least 30 min a day at least 5 days/week. Physical activity was measured since r2. d The guideline for healthy nutrition from the Dutch Health Counsel (Gezondsheidsraad) recommends maximal 1 consumption of alcohol per day for women and maximal 2 consumptions of alcohol per day for men. e Including myocardial infarction (n = 148), coronary heart disease (n = 299) and intermittent claudication (n = 25).
Interactions between lifestyle changes and sex, age or educational level were not found. Discussion We observed that adults who reported a diagnosis of CVD or DM more often adopted a healthy lifestyle compared to adults who did not report either of these diagnoses. Those with incident DM more often
lost weight, reduced their energy intake and saturated fat consumption and increased their fish consumption and those with incident CVD stopped smoking more often. The finding that more participants with CVD stopped smoking and more participants with DM lost weight might be explained by general common knowledge: we believe that the Dutch laymen population generally knows that DM is often partly due to overweight and CVD relates to smoking. Decreasing weight for DM and smoking cessation for CVD are therefore the most obvious lifestyle changes. The lifestyle changes observed are comparable to findings in a large US study by Keenan (Keenan, 2009). Keenan observed an even stronger association with smoking cessation after a self-reported diagnosis of CVD (OR 5.2, 95%CI 3.9 – 6.8) than we found and showed a statistically significant decrease in weight in those who reported a diagnosis of CVD. Several other studies also showed the diagnosis of CVD to be associated with smoking cessation (Falba, 2005; Van Gool et al., 2007). In addition to Keenan we analysed the effect of a self-reported diagnosis of CVD or DM on diet, alcohol consumption and physical activity. We found no changes in alcohol consumption and physical activity after a self-reported diagnosis of DM or CVD. Earlier, one study among Dutch elderly found a significant decrease in (excessive) alcohol consumption after a self-reported diagnosis of CVD (from 23.7% pre-CVD to 17.2% post-CVD), and an increase in physical activity (from 24.2% pre-CVD to 37.1% post-CVD) (Van Gool et al., 2007). Another study on CVD patients suggested a reduction in physical activity because of the diagnosis, but lifestyle was retrospectively assessed in this study (Newens, 1997). The findings suggest that those with a chronic disease more often adopt a healthy lifestyle compared to those who do not have a disease. Keenan et al. concluded the same based on a cluster of diseases consisting of CVD, DM, stroke, cancer, and lung disease (Keenan, 2009). Changes in lifestyle may be the effect of medical treatment, but another explanation could be that the diagnosis acts as a trigger for people to take (more) responsibility for their own health. It is however, almost impossible to separate these effects because lifestyle advices are usually part of the treatment for those with DM or CVD (Dutch Organisation for General Practitioners, 2010a,b). Yet, the benefits of a healthy lifestyle are widespread disseminated, but the sense of urgency due to a chronic disease diagnosis may act as an important trigger for people to change their unhealthy lifestyle. Also other health warnings are suggested to result in lifestyle changes, e.g. one study showed that being told to have hypertension was associated with increased physical activity and smoking cessation (Neutel and Campbell, 2008). This suggests that a diagnosis or other health warning may act as a window of opportunity for changing unhealthy lifestyles, which is used by medical professionals. Despite the urgency of lifestyle change because of a CVD or DM diagnosis, no increase was observed in physical activity. This may suggest that adopting a healthy lifestyle in terms of stopping smoking, eating more healthily and losing weight is easier than becoming more physically active. The prospective nature of the present study is a major advantage compared to other studies (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Newens, 1997). Lifestyles post diagnosis could be compared with lifestyles pre diagnosis, resulting in less diagnosis-related reporting bias compared to retrospective studies. In addition, in our cohort a group without the analysed diagnosis could be used to control for the general trend in changing lifestyles. This is an important strength compared to studies that are based on patient populations with a specific chronic disease and do not have a control group without the disease (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997). Other strengths of our study are the long follow-up time and the availability of several lifestyle measures including diet. Our study has a number of limitations. We compared lifestyle changes over the same 5-year period in which DM and CVD were reported to
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Table 2 Odds ratio for lifestyle changes in 5-year periods in participants with compared to participants without incident disease; results of logistic GEE-analyses in the Doetinchem Cohort study (1987–2007). Cardiovascular diseasea Lifestyle changes d
Declined in weight category Became physically activee Stopped smoking Adhered to alcohol guidelinef
Diabetes mellitus
CVD or DM
CVD − c
CVD + c
ORb
CI
DM − c
DM + c
ORb
CI
ORb
CI
10.3% 49.5% 21.3% 22.7%
8.6% 50.0% 38.0% 28.6%
1.0 1.0 2.2 1.3
(0.6–1.6) (0.6–1.8) (1.6–3.1) (0.8–2.1)
9.9% 49.3% 21.5% 22.6%
21.7% 60.0% 32.8% 26.9%
2.8 1.5 1.7 1.3
(1.9–4.0) (0.8–2.6) (1.0–2.9) (0.7–2.4)
1.8 1.3 2.1 1.3
(1.3–2.5) (0.8–2.0) (1.6–2.8) (0.9–1.9)
a
Including myocardial infarction, coronary heart disease, and intermittent claudication. Adjusted for gender, age, and educational level. c Crude percentages for participants with and without incident disease; CVD − = participants without CVD; CVD + = participants with CVD incident; DM − = participants without DM; DM + = participants with DM incident. d From obese to overweight or normal weight and from overweight to normal weight. e The Dutch physical activity guidelines recommend adults to be physically active at moderate or vigorous levels for at least 30 min a day at least 5 days/week. Physical activity has been measured since r2. f The guideline for healthy nutrition from the Dutch Health Counsel (Gezondsheidsraad) recommends maximal 1 consumption of alcohol per day for women and maximal 2 consumptions of alcohol per day for men. b
have been diagnosed. We do not have information on the sequence of events within this period, i.e. we do not know whether the diagnosis preceded the lifestyle change or not. Another limitation is that physical activity and alcohol, saturated fat, vegetable and fruit consumption were measured in amounts per week, while guideline levels are presented in amounts per day. Therefore the amount per day was estimated on basis of amounts per week and used as a proxy for meeting the guideline levels or not. A third limitation might be that we rely on self-report of the diagnosis. However for our research question selfreported diagnoses are more appropriate since only participants who are aware of a chronic disease can change their lifestyle because of this diagnosis. The self-reporting of the diseases seems to be quite valid: around 90% of the self-reported DM cases were supported by information from medical files (Sluijs et al., 2010). A final limitation is that our study population is from a specific area in The Netherlands and therefore the results may be not completely representative of the entire Dutch population. The main findings of this study suggest that a self-reported diagnosis of CVD is associated with smoking cessation and a diagnosis of DM is associated with weight loss, lower consumption of saturated fat, and lower energy intake. Reporting a diagnosis of CVD or DM was not associated with changes in physical activity levels. The use of prospective
data to study lifestyle changes after diagnosis of a chronic disease is relatively new. The investigation of the possible effects of health diagnosis on lifestyle changes and potential interactions with culture, age group, sex, or socioeconomic subgroup is of interest and should be investigated further in prospective studies.
Conflict of Interest The authors declare there is no conflict of interest.
Acknowledgments The Doetinchem Cohort Study is carried out by the National Institute for Public Health and the Environment which works under the authority of the Ministry of Health, Welfare and Sport of The Netherlands. The funding source had no involvement in analyses and interpretation of the data, writing of the report, or decision to submit the paper. The authors would like to thank the epidemiologists and fieldworkers of the Municipal Health Service in Doetinchem for their contribution to the data collection for this study.
Table 3 Lifestyle differences in 5-year periods between participants with and without incident disease; results of linear GEE-analyses in the Doetinchem Cohort Study (1987–2007). Cardiovascular disease a
Diabetes mellitus Adjusted b
CVD or DM Adjusted b
Adjusted b
Lifestyle changes
Non-incident CVDc
Incident CVDc
Β b, d
CI
Non-incident DMc
Incident DMc
Β b, d
CI
Β b, d
CI
Relative decrease in weight (%)e Relative decrease in total energy intake (%)e Increase in vegetable intake in grams/day Increase in fruit intake in grams/day Increase in fish intake in grams/day Decrease in saturated fat consumption (%)f
−2.0 2.3 −0.1 6.2 2.5 0.4
−2.2 3.5 2.9 1.7 3.3 0.3
−0.7 1.3 3.0 −3.3 1.1 0.04
−1.4 – 0.0 −1.6 – 4.3 −2.7 – 8.6 −16.9 – 10.2 −0.5 – 2.6 −0.2 – 0.3
−2.1 2.2 −0.03 6.3 2.4 0.4
1.6 6.5 2.6 9.0 5.3 0.9
3.2 4.2 4.8 −1.2 2.8 0.4
2.2 – 4.2 0.7– 7.7 −1.4 – 11.0 −18.4 – 15.9 0.4 – 5.1 0.0 – 0.9
1.1 2.6 3.0 −2.8 1.8 0.2
0.5−1.8 0.3–5.0 −1.3–7.3 −13.7–8.1 0.5–3.2 0.0–0.4
a
Including myocardial infarction, coronary heart disease, and intermittent claudication. Adjusted for gender, age, and educational level. c Crude average values for participants with and without incident disease (in % or grams/day); non-incident CVD or DM = participants who did not report a diagnosis of CVD or DM in a 5-year period. Incident CVD or DM = participants who reported a diagnosis of CVD or DM in a 5-year period; e.g. participants with no reported DM decreased their energy intake by 2.2% while participants who reported DM decreased their energy intake by 6.5%. d Difference in lifestyle change (in % or grams/day) for participants with incident disease compared to those without the disease; e.g. participants with incident CVD decreased their weight 0.7% less than those without CVD; participants with incident DM decreased their weight 3.2% more than those without DM; participants with incident CVD increased their vegetable consumption 3.0 g/day more than those without CVD. e Among participants with BMI ≥ 25. f Decrease in saturated fat intake as a proportion (%) of total daily energy intake. b
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Contents lists available at ScienceDirect
Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Diagnosis of Diabetes Mellitus or Cardiovascular Disease and lifestyle changes — The Doetinchem Cohort Study A. Manschot a,b, S.H. van Oostrom a,⁎, H.A. Smit c, W.M.M. Verschuren a,c, H.S.J. Picavet a a b c
Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands University of Utrecht, The Netherlands Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
a r t i c l e
i n f o
Available online 22 November 2013 Keywords: Prospective cohort study Diabetes Mellitus Cardiovascular disease Physical activity Weight Smoking Diet Alcohol
a b s t r a c t Objective. To study whether being diagnosed with a cardiovascular disease (CVD) or diabetes mellitus (DM) is associated with improvements in lifestyles. Methods. We used data from the Doetinchem Cohort Study, a prospective study among 6386 Dutch men and women initially aged 20–59 years who were examined four times over 15 years (1987–2007). Logistic and linear regression models were used to assess the effect of a self-reported diagnosis of CVD (n = 403) or DM (n = 221) on smoking, alcohol consumption, weight, diet and physical activity. Results. Self-reported diagnosis of CVD increased rates of smoking cessation (OR = 2.2, 95%CI 1.6 – 3.1). Adults reporting a diagnosis of DM (relatively) decreased weight (3.2%, 95%CI 2.2 – 4.2), (relatively) decreased energy intake (4.2%, 95%CI 0.7 – 7.7), decreased energy percentage from saturated fat (0.4%, 95%CI 0.0 – 0.9) and increased fish consumption (2.8 g/day, 95%CI 0.4 – 5.1). A self-reported diagnosis of CVD or DM was not associated with changes in physical activity. Conclusion. A diagnosis of CVD or DM may act, along with possible effects of medical treatment, as a trigger to adopt a healthier lifestyle in terms of smoking cessation, healthier diet and weight loss. © 2013 Elsevier Inc. All rights reserved.
Introduction A healthy lifestyle reduces the risk of developing chronic diseases, and therefore contributes to healthy ageing (Anderson et al., 2003; Ockene and Miller, 1997). It is common knowledge that smoking, obesity, unhealthy diet and low levels of physical activity induce health risks. Nevertheless, adopting a healthy lifestyle appears to be quite a challenge, shown by the high and still increasing prevalence of obesity (Ogden et al., 2006) and physical inactivity (Lindström et al., 2003). Many interventions have been developed aiming to change unhealthy lifestyles in different phases in life (Hardeman et al., 2000; Spring et al., 2009; Tripodi et al., 2010). One of many reasons of failure to adopt a healthy lifestyle, may be due to the lack of a sense of urgency. Signs of health problems, for instance being diagnosed with a chronic disease, may act as a trigger to take responsibility for one's own health. There are examples of studies investigating changes in lifestyle after diagnosis of a chronic disease (Bak et al., 2002; Falba, 2005; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Keenan, 2009; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997; Van Gool Abbreviations: CVD, Cardiovascular Disease; DM, Diabetes Mellitus; DCS, Doetinchem Cohort Study; BMI, Body Mass Index; GEE, Generalized estimating equations. ⁎ Corresponding author. Fax: +31 30 2744407. E-mail addresses: [email protected] (A. Manschot), [email protected] (S.H. van Oostrom), [email protected] (H.A. Smit), [email protected] (W.M.M. Verschuren), [email protected] (H.S.J. Picavet). 0091-7435/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.11.013
et al., 2007). Some studies found increased rates of smoking cessation after a diagnosis of cardiovascular disease (CVD) (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008). Also, in diabetes mellitus (DM) cases, increased weight loss has been observed (Falba, 2005; Keenan, 2009; Van Gool et al., 2007). However, most of the studies measured lifestyle changes retrospectively, thus running the risk of recall bias. Also a control group was often lacking, rendering it impossible to control for a general trend in lifestyle changing behaviour (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997). In the present study, we investigated whether adults who reported a diagnosis of CVD or DM were more likely to change their lifestyles (smoking, alcohol consumption, diet (vegetable, fruit, fish, saturated fat, and energy intake), physical activity and weight) than adults without such a diagnosis. We used data from the Doetinchem Cohort Study, a prospective cohort study in the general population in The Netherlands (Verschuren et al., 2008).
Methods Study design and study population The Doetinchem Cohort Study (DCS) (Verschuren et al., 2008) is an ongoing prospective study in The Netherlands. The first measurement was carried out in a random, general population sample of men and women aged 20–59 years
A. Manschot et al. / Preventive Medicine 59 (2014) 42–46
(1987–1991). The aim of the DCS was to study the impact of (changes in) lifestyle factors and biological risk factors on various aspects of health, such as the incidence of chronic diseases, physical and cognitive functioning, and quality of life. The cohort is re-examined every five years with questionnaires and a physical examination at the local health services. Four subsequent examination rounds were completed in the years 1987–1991 (r1), 1993–1997 (r2), 1998–2002 (r3), and 2003–2007 (r4). All participants gave written informed consent, and the study was approved according to the guidelines of the Helsinki Declaration by the Medical Ethics Committee of the Netherlands Organization of Applied Scientific Research. Details on the DCS have been extensively described elsewhere (Verschuren et al., 2008). For the present study we defined our baseline population as those who participated at the first (r1) and at the second examination round (r2), i.e. 6386 participants. Measurements and variables Chronic diseases CVD cases were defined on the basis of self-reported myocardial infarction (Did you ever had a heart attack?), self-reported coronary heart disease (Have you ever had bypass surgery?; have you ever had cardiac catheterization?; have you ever had coronary angioplasty?), and self-reported intermittent claudication, based on the WHO/Rose questionnaire (Rose et al., 1977). Diabetes Mellitus (DM) concerned people who reported positive to the simple question ‘Do you have diabetes?’. Because of the age range of the population, we expect the majority of the DM cases to be type 2. Lifestyle-related characteristics Body Mass Index (BMI) was calculated by height and body weight, which were measured by trained staff in each examination round. Overweight was defined as a BMI between 25 and 30 kg/m2, and obesity was defined as a BMI equal to or above 30 kg/m2. Those who lost weight were defined as participants who changed to a lower BMI category (from obese to overweight or normal weight, or from overweight to normal weight) between two subsequent measurements. Relative weight loss among participants with a BMI equal to or above 25, was expressed as a percentage of weight at the beginning of each wave. Physical activity during leisure time was measured from 1994 (r2) onwards with an extensive self-administered questionnaire that includes questions on time spent walking, cycling, doing odd jobs, gardening, and sports activities in a regular week during the previous year (Picavet et al., 2011). The questionnaire was designed and validated for the international European Prospective Investigation Into Cancer and Nutrition study and extended with a question on sports and other strenuous leisure-time physical activities (Pols et al., 1997). To determine whether individuals reached the Dutch physical activity recommendations, defined as moderate or vigorous intensity activities for a minimum of half an hour a day for at least five days a week (Ainsworth et al., 2000; Kemper et al., 2000), the total time (hours/week) spent on moderate-tovigorous leisure time physical activities was calculated. Activities included in this calculation were cycling, gardening and sports (≥ 4.0 MET). The cut-off point for adhering to the recommended levels was set at 3.5 h a week, a conservative level to correct for overestimation of physical activity (Wilcox and King, 2000). Smoking of cigarettes, cigars and/or pipes was measured in all rounds. We considered participants to be smokers when they indicated to smoke cigarettes, cigars and/or pipes, irrespective of the frequency or quantity. Alcohol consumption, defined as the total number of glasses of beer, wine, and liquor drank per week, was measured in all measurement rounds. Alcohol guideline followers were based on the Dutch healthy nutrition guidelines (Dutch Health Counsil, 2006), i.e. a maximum of one consumption per day for women and of two consumptions per day for men. From round two (r2) onwards, an extensive food frequency questionnaire was included in the Doetinchem study (Ocké et al., 1997a,b). Based on this questionnaire several indicators of healthy food consumption were calculated: the fruit, vegetable and fish consumption expressed in grams per day, and the total daily energy intake. BMI, smoking and alcohol consumption were assessed at all four measurement rounds and changes in these variables were studied over three 5-year periods. Physical activity, and fruit, vegetable, fish and saturated fat consumption were assessed at three measurement rounds, changes in these variables were studied over two 5-year periods. Socio-demographic characteristics Age was classified into four categories of ten years at baseline. Educational level was assessed as the highest level reached at baseline and classified into
43
three categories: low (intermediate secondary education or less), medium (intermediate vocational or higher secondary education) and high (higher vocational education or university). Data analyses Differences in adopting a healthy lifestyle were studied between adults with an unhealthy lifestyle at baseline who reported and did not report a diagnosis of DM or CVD within a 5-year period, excluding prevalent cases of DM or CVD. Smoking cessation was studied among smokers. Unhealthy alcohol consumption and physical activity were defined according to the relevant recommendations: for alcohol consumption ≥ 1 consumption per day for women and ≥2 consumptions per day for men (Dutch Health Counsil, 2006); for physical activity no moderate or vigorous levels of activity for at least 30 min a day at least 5 days/week (Ainsworth et al., 2000; Kemper et al., 2000). Weight loss and reduced energy intake were measured in those who were overweight (BMI ≥25). Fruit, vegetable, fish and saturated fat consumption was measured in the total population, since almost all participants' diets did not contain the recommended amounts (Dutch Health Counsil, 2006). Data on changes in physical activity and saturated fat consumption were available for two 5-year periods and for the other lifestyles, data were available for three 5-year periods. All analyses of lifestyle changes based on a dichotomous variable were performed with logistic regression analyses using generalized estimating equations (GEE) with an autoregressive correlation structure. Linear regression analyses using generalized estimating equations were performed to find out whether those who reported or did not report a diagnosis of CVD or DM differed in their change in daily vegetable, fruit, fish, and saturated fat consumption, relative weight, and total energy intake. GEE analyses were used to take into account the correlation between repeated measurements within individuals. In both logistic and linear regression analyses the reported diagnosis of DM or CVD was used as independent variables and changes in lifestyles were used as dependent variables. All analyses were adjusted for age, gender and educational level. Interactions between lifestyle changes and sex, age or educational level were studied among the significant associations. SAS software version 9.3 (Statistical Analysis System; SAS Institute, Inc., Cary, North Carolina) was used to perform the statistical analyses.
Results The study population consisted of 2994 men and 3392 women with a mean age of 37.8 years at r1 (Table 1). Baseline prevalences of unhealthy lifestyles were 34.1% for overweight, 6.8% for obesity, 37.1% for smoking, 21.8% for drinking more alcohol than guideline recommendations (measured at r1) and 18.3% for physical inactivity (measured at r2). Mean intake of dietary components at baseline was 112.4 g of vegetables per day, 168.5 g of fruit per day, and 9.3 g of fish per day. In total, 403 participants reported to be diagnosed with CVD and 221 with DM between r1 and r4. Participants who reported a diagnosis of CVD stopped smoking more frequently than participants who did not (OR 2.2, 95%CI 1.6 – 3.1) (Table 2). No statistically significant differences in weight loss, total energy intake, becoming physically active, fruit, vegetable, fish, and saturated fat consumption and alcohol intake were found between participants who reported a diagnosis of CVD and those who did not report CVD (Table 2 and 3). Participants who reported a diagnosis of DM more often changed BMI category (OR 2.8, 95%CI 1.9 – 4.0) (from obese to overweight or normal weight, or from overweight to normal weight) than those who did not report DM (Table 2). They showed a relative decrease in weight of 3.2% (95%CI 2.2 – 4.2). Participants who reported a diagnosis of DM decreased on average 1.6% in weight whereas those who did not report DM increased on average 2.1% in weight (Table 3). A relative decrease in total energy intake of 4.2% (95%CI 0.7 – 7.7), a decrease in the amount of energy derived from saturated fat of 0.4% (95%CI 0.0 – 0.9), and an increase in fish consumption (2.8 g/day, 95%CI 0.4 – 5.1) were shown for participants who reported a diagnosis of DM compared to those who did not report DM. No statistically significant differences for smoking cessation, becoming physically active, or for fruit, vegetable and alcohol consumption were found between participants who reported DM and those who did not.
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A. Manschot et al. / Preventive Medicine 59 (2014) 42–46
Table 1 Characteristics of the study population of the Doetinchem Cohort Study (1987–2007)a. % or means Total number of participants
n = 6386
Sociodemographic characteristics (at r1) Age (mean)
39.9 (10.2)
Gender Men Women Educational level Low level Medium level High level Living situation Living together Living alone
46.9% 53.1% 62.2% 21.4% 16.1% 84.3% 15.4%
Lifestyle-related characteristics Weight BMI (kg/m2) at baseline (mean) Obese at baseline (bmi ≥ 30kg/m2) Overweight at baseline (25 ≤ bmi b 30 kg/m2) Declined in weight category at least once in a 5-year period between r1 and r4 b Adherence to physical activity recommendations c Physical inactivity according to guideline at baseline (r2) Became physically active at least once in a 5-year period between r2 and r4 Smoking Smokers at baseline Stopped smoking at least once in a 5-year period between r1 and r4 Alcohol Alcohol consumers at baseline Consumptions per week per drinker at baseline (mean) Alcohol consumption exceeding guideline recommendations at baseline d Became guideline followers at least once in a 5-year period, between r1 and r4 Diet Relative saturated fat consumption of total daily energy intake (%) (mean) Vegetable consumption in grams/day at baseline (r2) (mean) Fruit consumption in grams/day at baseline (r2) (mean)
24.6 (3.5) 6.8% 34.1% 10.1%
19.1% 13.9%
37.1% 16.1%
86.2% 10.8 (9.7) 21.8% 21.9%
15.0 (2.4) 112.4 (45.0) 168.5 (128.1) 9.3 (9.4)
Fish consumption in grams/day at baseline (r2) (mean) Incidence of diseases between r1 and r4 Cardiovascular disease e Diabetes mellitus (type I and II) Both diabetes mellitus and cardiovascular disease
n = 403 n = 221 n = 21
6.3% 3.5% 0.3%
a Means and standard deviations for continuous variables, frequencies and percentages for categorical variables. b From obese to overweight or normal weight and from overweight to normal weight; r1 is the first measurement in the Doetinchem study. c The Dutch physical activity guidelines recommend adults to be physically active at moderate or vigorous levels for at least 30 min a day at least 5 days/week. Physical activity was measured since r2. d The guideline for healthy nutrition from the Dutch Health Counsel (Gezondsheidsraad) recommends maximal 1 consumption of alcohol per day for women and maximal 2 consumptions of alcohol per day for men. e Including myocardial infarction (n = 148), coronary heart disease (n = 299) and intermittent claudication (n = 25).
Interactions between lifestyle changes and sex, age or educational level were not found. Discussion We observed that adults who reported a diagnosis of CVD or DM more often adopted a healthy lifestyle compared to adults who did not report either of these diagnoses. Those with incident DM more often
lost weight, reduced their energy intake and saturated fat consumption and increased their fish consumption and those with incident CVD stopped smoking more often. The finding that more participants with CVD stopped smoking and more participants with DM lost weight might be explained by general common knowledge: we believe that the Dutch laymen population generally knows that DM is often partly due to overweight and CVD relates to smoking. Decreasing weight for DM and smoking cessation for CVD are therefore the most obvious lifestyle changes. The lifestyle changes observed are comparable to findings in a large US study by Keenan (Keenan, 2009). Keenan observed an even stronger association with smoking cessation after a self-reported diagnosis of CVD (OR 5.2, 95%CI 3.9 – 6.8) than we found and showed a statistically significant decrease in weight in those who reported a diagnosis of CVD. Several other studies also showed the diagnosis of CVD to be associated with smoking cessation (Falba, 2005; Van Gool et al., 2007). In addition to Keenan we analysed the effect of a self-reported diagnosis of CVD or DM on diet, alcohol consumption and physical activity. We found no changes in alcohol consumption and physical activity after a self-reported diagnosis of DM or CVD. Earlier, one study among Dutch elderly found a significant decrease in (excessive) alcohol consumption after a self-reported diagnosis of CVD (from 23.7% pre-CVD to 17.2% post-CVD), and an increase in physical activity (from 24.2% pre-CVD to 37.1% post-CVD) (Van Gool et al., 2007). Another study on CVD patients suggested a reduction in physical activity because of the diagnosis, but lifestyle was retrospectively assessed in this study (Newens, 1997). The findings suggest that those with a chronic disease more often adopt a healthy lifestyle compared to those who do not have a disease. Keenan et al. concluded the same based on a cluster of diseases consisting of CVD, DM, stroke, cancer, and lung disease (Keenan, 2009). Changes in lifestyle may be the effect of medical treatment, but another explanation could be that the diagnosis acts as a trigger for people to take (more) responsibility for their own health. It is however, almost impossible to separate these effects because lifestyle advices are usually part of the treatment for those with DM or CVD (Dutch Organisation for General Practitioners, 2010a,b). Yet, the benefits of a healthy lifestyle are widespread disseminated, but the sense of urgency due to a chronic disease diagnosis may act as an important trigger for people to change their unhealthy lifestyle. Also other health warnings are suggested to result in lifestyle changes, e.g. one study showed that being told to have hypertension was associated with increased physical activity and smoking cessation (Neutel and Campbell, 2008). This suggests that a diagnosis or other health warning may act as a window of opportunity for changing unhealthy lifestyles, which is used by medical professionals. Despite the urgency of lifestyle change because of a CVD or DM diagnosis, no increase was observed in physical activity. This may suggest that adopting a healthy lifestyle in terms of stopping smoking, eating more healthily and losing weight is easier than becoming more physically active. The prospective nature of the present study is a major advantage compared to other studies (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Newens, 1997). Lifestyles post diagnosis could be compared with lifestyles pre diagnosis, resulting in less diagnosis-related reporting bias compared to retrospective studies. In addition, in our cohort a group without the analysed diagnosis could be used to control for the general trend in changing lifestyles. This is an important strength compared to studies that are based on patient populations with a specific chronic disease and do not have a control group without the disease (Bak et al., 2002; Gall et al., 2009; Havik and Maeland, 1988; Ives et al., 2008; Koikkalainen et al., 2002; Looker et al., 2001; Newens, 1997). Other strengths of our study are the long follow-up time and the availability of several lifestyle measures including diet. Our study has a number of limitations. We compared lifestyle changes over the same 5-year period in which DM and CVD were reported to
A. Manschot et al. / Preventive Medicine 59 (2014) 42–46
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Table 2 Odds ratio for lifestyle changes in 5-year periods in participants with compared to participants without incident disease; results of logistic GEE-analyses in the Doetinchem Cohort study (1987–2007). Cardiovascular diseasea Lifestyle changes d
Declined in weight category Became physically activee Stopped smoking Adhered to alcohol guidelinef
Diabetes mellitus
CVD or DM
CVD − c
CVD + c
ORb
CI
DM − c
DM + c
ORb
CI
ORb
CI
10.3% 49.5% 21.3% 22.7%
8.6% 50.0% 38.0% 28.6%
1.0 1.0 2.2 1.3
(0.6–1.6) (0.6–1.8) (1.6–3.1) (0.8–2.1)
9.9% 49.3% 21.5% 22.6%
21.7% 60.0% 32.8% 26.9%
2.8 1.5 1.7 1.3
(1.9–4.0) (0.8–2.6) (1.0–2.9) (0.7–2.4)
1.8 1.3 2.1 1.3
(1.3–2.5) (0.8–2.0) (1.6–2.8) (0.9–1.9)
a
Including myocardial infarction, coronary heart disease, and intermittent claudication. Adjusted for gender, age, and educational level. c Crude percentages for participants with and without incident disease; CVD − = participants without CVD; CVD + = participants with CVD incident; DM − = participants without DM; DM + = participants with DM incident. d From obese to overweight or normal weight and from overweight to normal weight. e The Dutch physical activity guidelines recommend adults to be physically active at moderate or vigorous levels for at least 30 min a day at least 5 days/week. Physical activity has been measured since r2. f The guideline for healthy nutrition from the Dutch Health Counsel (Gezondsheidsraad) recommends maximal 1 consumption of alcohol per day for women and maximal 2 consumptions of alcohol per day for men. b
have been diagnosed. We do not have information on the sequence of events within this period, i.e. we do not know whether the diagnosis preceded the lifestyle change or not. Another limitation is that physical activity and alcohol, saturated fat, vegetable and fruit consumption were measured in amounts per week, while guideline levels are presented in amounts per day. Therefore the amount per day was estimated on basis of amounts per week and used as a proxy for meeting the guideline levels or not. A third limitation might be that we rely on self-report of the diagnosis. However for our research question selfreported diagnoses are more appropriate since only participants who are aware of a chronic disease can change their lifestyle because of this diagnosis. The self-reporting of the diseases seems to be quite valid: around 90% of the self-reported DM cases were supported by information from medical files (Sluijs et al., 2010). A final limitation is that our study population is from a specific area in The Netherlands and therefore the results may be not completely representative of the entire Dutch population. The main findings of this study suggest that a self-reported diagnosis of CVD is associated with smoking cessation and a diagnosis of DM is associated with weight loss, lower consumption of saturated fat, and lower energy intake. Reporting a diagnosis of CVD or DM was not associated with changes in physical activity levels. The use of prospective
data to study lifestyle changes after diagnosis of a chronic disease is relatively new. The investigation of the possible effects of health diagnosis on lifestyle changes and potential interactions with culture, age group, sex, or socioeconomic subgroup is of interest and should be investigated further in prospective studies.
Conflict of Interest The authors declare there is no conflict of interest.
Acknowledgments The Doetinchem Cohort Study is carried out by the National Institute for Public Health and the Environment which works under the authority of the Ministry of Health, Welfare and Sport of The Netherlands. The funding source had no involvement in analyses and interpretation of the data, writing of the report, or decision to submit the paper. The authors would like to thank the epidemiologists and fieldworkers of the Municipal Health Service in Doetinchem for their contribution to the data collection for this study.
Table 3 Lifestyle differences in 5-year periods between participants with and without incident disease; results of linear GEE-analyses in the Doetinchem Cohort Study (1987–2007). Cardiovascular disease a
Diabetes mellitus Adjusted b
CVD or DM Adjusted b
Adjusted b
Lifestyle changes
Non-incident CVDc
Incident CVDc
Β b, d
CI
Non-incident DMc
Incident DMc
Β b, d
CI
Β b, d
CI
Relative decrease in weight (%)e Relative decrease in total energy intake (%)e Increase in vegetable intake in grams/day Increase in fruit intake in grams/day Increase in fish intake in grams/day Decrease in saturated fat consumption (%)f
−2.0 2.3 −0.1 6.2 2.5 0.4
−2.2 3.5 2.9 1.7 3.3 0.3
−0.7 1.3 3.0 −3.3 1.1 0.04
−1.4 – 0.0 −1.6 – 4.3 −2.7 – 8.6 −16.9 – 10.2 −0.5 – 2.6 −0.2 – 0.3
−2.1 2.2 −0.03 6.3 2.4 0.4
1.6 6.5 2.6 9.0 5.3 0.9
3.2 4.2 4.8 −1.2 2.8 0.4
2.2 – 4.2 0.7– 7.7 −1.4 – 11.0 −18.4 – 15.9 0.4 – 5.1 0.0 – 0.9
1.1 2.6 3.0 −2.8 1.8 0.2
0.5−1.8 0.3–5.0 −1.3–7.3 −13.7–8.1 0.5–3.2 0.0–0.4
a
Including myocardial infarction, coronary heart disease, and intermittent claudication. Adjusted for gender, age, and educational level. c Crude average values for participants with and without incident disease (in % or grams/day); non-incident CVD or DM = participants who did not report a diagnosis of CVD or DM in a 5-year period. Incident CVD or DM = participants who reported a diagnosis of CVD or DM in a 5-year period; e.g. participants with no reported DM decreased their energy intake by 2.2% while participants who reported DM decreased their energy intake by 6.5%. d Difference in lifestyle change (in % or grams/day) for participants with incident disease compared to those without the disease; e.g. participants with incident CVD decreased their weight 0.7% less than those without CVD; participants with incident DM decreased their weight 3.2% more than those without DM; participants with incident CVD increased their vegetable consumption 3.0 g/day more than those without CVD. e Among participants with BMI ≥ 25. f Decrease in saturated fat intake as a proportion (%) of total daily energy intake. b
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