This paper reports the results of a secondary analysis of data from the REGARDS cohort. The REGARDS study is a prospective national cohort of 30,239 community-dwelling African-American and white adults ≥45 years of age from the 48 contiguous US states that was designed to examine regional and racial influences on stroke mortality [7, 8]. Full details are described elsewhere [7]. Briefly, participants—English-speaking adults aged 45 years or older—were enrolled between January 2003 and October 2007, with commercially available lists combining mail and telephone contacts used for recruitment. Race and sex were balanced by design, with oversampling from the south-eastern USA; the final cohort composition was 58% women and 42% African-American. Overall, 56% of participants resided in the stroke belt (NC, SC, GA, AL, MS, TN, AR and LA) with the rest from the other 40 contiguous states. An initial telephone interview was used to survey participants and establish eligibility. Following verbal consent, demographic information and medical history, including data on stroke risk factors and sociodemographic, lifestyle and psychosocial characteristics were collected via computer-assisted telephone interviews using validated questionnaires. Participants were asked to fast for 10–12 h and physical and physiological measures including BP, anthropometric measures, blood samples, urine samples, electrocardiogram and medication use by pill bottle review were collected during an in-home examination by trained staff following standardised, quality-controlled protocols. Blood and urine samples were shipped overnight on ice to the REGARDS central laboratory in Burlington, VT, USA. Participants were contacted via telephone at 6 month intervals to ascertain hospitalisations and vital status. A second in-person assessment was conducted 10 years (2013–2016) following baseline and included a telephone interview and an in-home examination to collect physical and physiological measures. Study methods were reviewed and approved by the institutional review board at the participating institutions and all participants gave written informed consent.

Exposure

The primary exposure was ideal CVH, assessed using six baseline metrics: cigarette smoking status; diet; physical activity; BMI; serum cholesterol; and blood pressure [4]. The blood glucose metric was excluded in the analyses, as diabetes was the outcome of interest. Each baseline metric was evaluated separately using poor, intermediate and ideal categories (electronic supplementary material [ESM] Table 1) [1]. Additionally, the number of ideal CVH metrics was summed across the six individual metrics and categorised as poor (0–1 ideal metrics), intermediate (2–3 ideal metrics) and ideal (4+ ideal metrics) CVH [4].

Cigarette smoking

Self-reported cigarette smoking was categorised as: current = poor; former ≤12 months (smoking at least 100 cigarettes in a lifetime) = intermediate; or never or quit ≥12 months = ideal.

Dietary intake

Dietary intake was assessed with the Block 98 food frequency questionnaire (FFQ), a validated semi-quantitative FFQ that assessed usual dietary intake of 110 food items (NutritionQuest, Berkeley, CA, USA) [9]. The FFQ was self-administered by participants after the baseline in-home visit and mailed to the REGARDS operations centre, where it was checked for completeness, scanned and forwarded to NutritionQuest for processing and analysis. The amounts of each food on the FFQ consumed by a participant were calculated by multiplying the frequency of consumption of that food by the usual amount consumed; the food groups were constructed as has been described previously [10]. The REGARDS questionnaire had some slight differences from the 2020 guidelines regarding units of servings, which required modification of the metrics. Components of the modified ideal diet score were: fruits and vegetables ≥4.5 cups/day; fish ≥2 × 98 g servings per week (non-fried); fibre-rich whole grains ≥3 × 28 g-equivalent servings/day; sodium <1500 mg/day; and sugar-sweetened beverages ≤1884 kJ/week. Participants were given one point per dietary component at goal for a total score ranging from 0 to 5. Participants were classified as ideal (4–5 of 5 components), intermediate (2–3 of 5 components) or poor (0–1 of 5 components).

Physical activity

Participants in REGARDS were asked ‘How many times per week do you engage in intense physical activity, enough to work up a sweat?’ We defined ideal physical activity as a frequency of four or more times per week, intermediate as 1–3 times per week, and poor as none, as previously [11].

Serum cholesterol, BMI, BP, plasma glucose

Serum concentrations of total cholesterol were measured using colorimetric reflectance spectrophotometry. Poor, intermediate and ideal levels of total cholesterol were categorised as ≥6.21 mmol/l, 5.18–<6.21 mmol/l or treated to goal, < 5.18 mmol/l, respectively. Calibrated devices were used to measure participants’ weight and height to calculate BMI as weight (kg)/height2 (m2). BMI was categorised as poor, intermediate and ideal as follows: ≥30 kg/m2, 25–29.9 kg/m2 and <25 kg/m2, respectively. Resting seated BP was measured following a standard protocol in the left arm. The average of two seated BP measurements was used for analysis. BPs were categorised as poor, intermediate and ideal as follows: systolic (S)BP ≥140 or diastolic (D)BP ≥90 mmHg, SBP 120–139 or DBP 80–89 mmHg or treated to goal, <120/<80 mmHg, respectively. Fasting plasma glucose was categorised as intermediate or ideal as 5.6–6.9 mmol/l and <5.6 mmol/l, respectively. Because participants with diabetes at baseline were excluded from this analysis, no participants were in the poor category for glucose (≥7.0 mmol/l).

Outcome

The primary outcome was incident diabetes, defined as fasting glucose ≥7.0 mmol/l, non-fasting glucose ≥11.1 mmol/l or diabetes medication use at the follow-up examination in those without prevalent diabetes at baseline. Glucose was measured using colorimetric reflectance spectrophotometry on the Ortho Vitros 950 IRC Clinical Analyzer (Johnson & Johnson Clinical Diagnostics, Rochester, NY, USA) with a coefficient of variation of 1% [12].

Covariates

Age, race, sex, annual household income and education were self-reported. Self-reported alcohol use was categorised as none, moderate (1–7 drinks/week for women or 1–14 drinks/week for men) or heavy (>7 drinks/week for women or >14 drinks/week for men) [7]. Estimated GFR (eGFR) was calculated according to the 2012 Chronic Kidney Diseases Epidemiology Collaboration (CKD-EPI) equation, which includes both creatinine and cystatin C, and urinary albumin concentrations [13]. Serum creatinine was measured and calibrated to isotope dilution mass spectrometry-traceable methods [13]. Cystatin C was measured by means of a particle-enhanced immunonephelometry assay (N Latex Cystatin C on a BNII nephelometer [Siemens, Munich, Germany]) [13]. Urine albumin was measured by nephelometry using a BNII ProSpec nephelometer (Siemens) and urine creatinine was measured by the rate Jaffe method using the Modular-P chemistry analyser (Roche/Hitachi, Basel, Switzerland) [13] to calculate the urinary albumin-to-creatinine ratio (ACR). High-sensitivity C-reactive protein (hsCRP) was measured by particle-enhanced immunonephelometry using the BNII nephelometer (N High Sensitivity CRP; Siemens) with interassay coefficients of variation of 2.1–5.7%.

Statistical analysis

In this secondary analysis using data collected from the REGARDS cohort, we included participants who completed the follow-up visit or computer-assisted telephone interview (n = 16,150), then excluded participants with diabetes at baseline (n = 2729) and those who were missing diabetes status at baseline (n = 521), diabetes status at follow-up (n = 1580), one of the CVH metrics (n = 3202) or data on baseline covariates (n = 360) (ESM Fig. 1). The 5663 participants excluded because of missing diabetes and covariate status had a higher percentage of African-Americans, higher BMI, higher smoking, higher blood pressure, lower education and were less physically active (all p < 0.01; ESM Table 2). Descriptive statistics were used to compare the baseline characteristics overall and by baseline glycaemic status and race (Table 1; ESM Table 3). Risk ratios (RR) for incident diabetes were calculated using modified Poisson regression adjusting for age, sex, race, education, income, alcohol use, eGFR, ACR and hsCRP.

Table 1 Characteristics of participants, by fasting glucose status in REGARDS Full size table

The number of ideal CVH components and each CVH metric separately were evaluated to estimate the proportion of cases in the population that might be attributable to suboptimal levels of CVH (population-attributable risk [PAR]%). The PAR% was calculated using the formula p(RR − 1)/(1 + p[RR − 1]), where p is the prevalence of individuals not in the low-risk group and RR is the associated multivariable-adjusted relative risk of those individuals. Upper and lower 95% CIs of the PAR% were derived using this formula and the upper and lower 95% CI estimates of the multivariable-adjusted RR [14]. Given that the association of ideal CVH with diabetes risk may differ by age, sex, race, glycaemic status (normal <5.6 mmol/l vs IFG 5.6–6.9 mmol/l) and history of coronary heart disease, we tested for interaction by these factors with CVH measures by inserting an interaction term in the model and using the likelihood ratio test.

We performed sensitivity analyses (ESM Tables 4–8) to confirm the robustness of our findings. These analyses included: (1) adjusting for baseline fasting glucose in the main analysis (ESM Table 4); (2) using the World Health Organization classification of IFG (<6.1 mmol/l vs 6.1–6.9 mmol/l in stratified models (ESM Table 5); (3) examining RRs for incident dysglycaemia (IFG and diabetes combined [ESM Table 6]; IFG only [ESM Table 7]) among participants with normal fasting glucose at baseline; and (4) performing the main analysis with full adjustment except for eGFR, ACR and hsCRP, as these may be in the pathway from risk to diabetes (ESM Table 8). Statistical significance was defined as two-sided α < 0.05 for all analyses except for interactions (p < 0.10). Analyses were performed using SAS 9.4 (SAS, Cary, NC, USA).