Long-Term Effectiveness of a Lifestyle Intervention: A Pragmatic Community Trial to Prevent Metabolic Syndrome

Weight change and risk of incident type 2 diabetes: short, medium and long-term follow-up in tehran lipid and glucose study

BACKGROUND

Despite the high burden of obesity and Type 2 diabetes (T2DM) in the Middle East/West Asia region, the effect of weight change on the development of T2DM is poorly addressed. Therefore, we aimed to assess the impact of 3-year body weight change on incident of T2DM over 3-, 6-, and 9-year periods among Iranian adults.

METHODS

A total of 6930 participants (men = 2567) aged ≥ 20 years free of T2DM or cancer at baseline were included. Weight measurements were taken at baseline (2002-2005) and approximately 3 years later. Participants were categorized based on their weight change ratio into  ≥ 5% loss, stable (± 5%), and ≥ 5% gain. Generalized estimating equations (GEE), adjusted with age, sex, education levels, baseline measurements of fasting plasma glucose, weight, waist circumference, triglycerides to high-density lipoprotein cholesterol ratio, family history of diabetes, current smoker, hypertension, and prevalent cardiovascular disease were applied to estimate the Odds ratios (ORs) and 95% confidence intervals (CIs) of weight change categories for incident T2DM, considering stable weight as a reference.

RESULTS

During median follow-ups of 3-, 6-, and 9-year, 295, 505, and 748 cases of T2DM occurred, respectively. Weight gain of ≥ 5%, as compared to stable weight group (± 5%), was associated with increased T2DM risk, with ORs of 1.58 (95% CI 1.16-2.14), 1.76 (1.41-2.20), and 1.70 (1.40-2.05) for the 3-, 6-, and 9-year follow-ups, respectively, in multivariable analysis; corresponding values for weight loss ≥ 5% were 0.48 (0.29-0.80), 0.57 (0.40-0.81), and 0.51 (0.38-0.68), respectively. This association persisted even after adjusting for attained weight. Subgroup analysis showed consistent associations across age, gender, and body mass index categories.

CONCLUSION

Weight gain and loss of ≥ 5% were associated with increased and decreased risks of incident T2DM, respectively, regardless of attained weight. This association was consistent over various follow-up durations among the Iranian population as recommended by guidelines.

Trajectory patterns of metabolic syndrome severity score and risk of type 2 diabetes

BACKGROUND

The available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up.

METHODS

In a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20-60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner.

RESULTS

Among 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56-3.81) and 6.81 (95% CI: 4.07-10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05-12.52).

CONCLUSION

Although most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.

Ideal cardiovascular health status and risk of cardiovascular disease and all-cause mortality: over a decade of follow-up in the Tehran lipid and glucose study

Objective

To quantify the association between ideal cardiovascular health (CVH) metrics and incident cardiovascular disease (CVD) including different subtypes [coronary heart disease (CHD), stroke, and sudden death], and all-cause mortality in an Iranian population.

Methods

The study population included 6,388 participants (2,726 men) aged 48.0 ± 12.4 years free of CVD at baseline. We utilized the American Heart Association’s 2020 impact target criteria of ideal, intermediate, and poor CVH. The multivariate Cox proportional Hazard model, adjusted for age, sex, educational level, marital status, and family history of CVD, was applied to estimate the hazard ratio (HR) of outcomes per one additional metric of ideal CVH metrics. Furthermore, the risk was also calculated for ideal and intermediate categories considering poor category as a reference.

Results

During the median follow-up of 11.26 years, 692 CVD, 589 CHD, 130 stroke, 111 sudden death, and 519 all-cause mortality events were reported. All of the individual ideal CVH metrics were independent predictors except intermediate physical activity level for CVD, BMI < 25 kg/m2, and intermediate physical activity for all-cause mortality. Each additional metrics of ideal CVH decreased the risk by 31 (0.69, 0.65–0.73) for CVD, 32 (0.68, 0.64–0.73) for CHD, 31 (0.69, 0.60–0.80) for stroke, 25 (0.75, 0.64–0.88) for sudden death, and 13% (0.87, 0.81–0.93) for all-cause mortality events. Moreover, intermediate and ideal categories of CVH metrics were associated with lower risk for different CVD outcomes, i.e., 44 (0.56, 0.48–0.65) and 76% (0.24, 0.17–0.35) for CVD; 43 (0.57, 0.47–0.67) and 75% (0.25, 0.16–0.37) for CHD, 58 (0.42, 0.29–0.61) and 86% (0.14, 0.04–0.44) for stroke; 56 (0.44, 0.29–0.66) and 55% (0.45, 0.21–0.99) for sudden death; and 25 (0.75, 0.62–0.90) and 46% (0.54, 0.37–0.80) for all-cause mortality events, respectively. We also assessed the impact of changes in ideal CVH status from phase III to phase IV (2008–2011) on CVD events among 5,666 participants. Accordingly, compared to those remaining in the poor category, all of the changes in ideal CVH categories showed a lower risk for CVD events.

Conclusion

Among the Iranian population, meeting higher ideal CVH metrics is associated with a lower risk of different CVD events and mortality outcomes.

Dynamic prediction models improved the risk classification of type 2 diabetes compared with classical static models

OBJECTIVE

Dynamic prediction models use the repeated measurements of predictors to estimate coefficients that link the longitudinal predictors to a static model (i.e. Cox regression). This study aims to develop and validate a dynamic prediction for incident type 2 diabetes (T2DM) as the outcome.

STUDY DESIGN AND SETTING

Data from the Tehran lipid and glucose study was used to develop (n = 5291 individuals; phases 1 to 3) and validate (n = 3147 individuals; phases 3 to 6) the dynamic prediction model among individuals aged ≥ 20 years. We used repeated measurements of fasting plasma glucose (FPG) or waist circumference (WC) in the framework of the joint modeling (JM) of longitudinal and time-to-event analysis.

RESULTS

Compared with the Cox which used just baseline data, JM showed the same discrimination, better calibration, and higher clinical usefulness (i.e. with a net benefit considering both true and false positive decisions); all were shown with repeated measurements of FPG/WC. Additionally, in our study, the dynamic models improve the risk reclassification (net reclassification index 33% for FPG and 24% for WC model).

CONCLUSION

Dynamic prediction models, compared with the static one could yield significant improvements in the prediction of T2DM. The complexity of the dynamic models could be addressed by using decision support systems.

Sudden cardiac death among Iranian population: a two decades follow-up of Tehran lipid and glucose study

Sudden cardiac death (SCD) is described as death within one hour, if observed, from the onset of symptoms, and within 24 h of being alive and well if not observe. Study population includes 3705 men and 4446 women, aged ≥ 30 years. Multivariable Cox proportional hazard models were used to determine the risk factors associated with SCD. After a median follow-up of 17.9 years, 244 SCD (165 in males) occurred. The age-standardized incidence rate (95% confidence intervals (CI)) of SCD was 2.3 (2.1-2.7) per 1000 person-year. Current smoking [Hazard ratio (HR): 2.43, 95% CI: 1.73-3.42], high waist circumference [1.49: 1.04-2.12], hypertension [1.39: 1.05-1.84], type 2 diabetes mellitus [2.78: 2.09-3.69], pulse rate ≥ 90 beats per/minute [1.72: 1.22-2.42] and prevalent cardiovascular disease [1.75: 1.26-2.45] were significant risk factors. The corresponding population attributed fractions (PAF) were 14.30, 16.58, 14.03, 19.60, 7.62, and 8.30, respectively. Being overweight [0.58: 0.40-0.83] and obese [0.61: 0.38-0.98] decreased the risk of SCD. After excluding known diabetes cases from our data analysis, the newly diagnosed diabetes still showed an HR of 2.0 (1.32-3.00) with a PAF of 7.15% in the full adjustment model. To deal with sudden death as a catastrophic outcome, multi-component strategies by policy health makers are suggested.

Long-term effectiveness of a lifestyle intervention on the prevention of type 2 diabetes in a middle-income country

This study aims to assess the effects of a community-based lifestyle intervention program on the incidence of type 2 diabetes (T2D). For this purpose, three communities in Tehran were chosen; one community received a face-to-face educational session embedded in a long-term community-wide lifestyle intervention aimed at supporting lifestyle changes. We followed up 9,204 participants (control: 5,739, intervention: 3,465) triennially from 1999 to 2015 (Waves 1-5). After a median follow-up of 3.5 years (wave 2), the risk of T2D was 30% lower in the intervention community as compared with two control communities by (Hazard-ratio: 0.70 [95% CI 0.53; 0.91]); however, the difference was not statistically significant in the following waves. After a median follow-up of 11.9 years (wave 5), there was a non-significant 6% reduction in the incidence of T2D in the intervention group as compared to the control group (Hazard-ratio: 0.94 [0.81, 1.08]). Moreover, after 11.9 years of follow-up, the intervention significantly improved the diet quality measured by the Dietary Approaches to Stop Hypertension concordance (DASH) score. Mean difference in DASH score in the intervention group versus control group was 0.2 [95% CI 0.1; 0.3]. In conclusion, the intervention prevented T2D by 30% in the short-term (3.5 years) but not long-term; however, effects on improvement of the diet maintained in the long-term.Registration: This study is registered at IRCT, a WHO primary registry ( https://irct.ir ). The registration date 39 is 2008-10-29 and the IRCT registration number is IRCT138705301058N1.

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

BACKGROUND

The health behaviors of young adults lag behind those of other age groups, and active health management is needed to improve health behaviors and prevent chronic diseases. In addition, developing good lifestyle habits earlier in life could reduce the risk of metabolic syndrome (MetS) later on.

OBJECTIVE

The aim of this study is to investigate the effects of the e-Motivate4Change program, for which health apps and wearable devices were selected based on user needs. The program was developed for the prevention and management of MetS in young adults.

METHODS

This experimental study used a nonequivalent control group. In total, 59 students from 2 universities in Daegu, Korea participated in the study (experimental group n=30; control group n=29). Data were collected over 4 months, from June 1 to September 30, 2018. The experimental group received a 12-week e-Motivate4Change program intervention, and the control group received MetS education and booklets without the e-Motivate4Change program intervention.

RESULTS

After the program, the experimental group had significantly higher scores for health-related lifestyle (t=3.86; P<.001) and self-efficacy (t=6.00; P<.001) than did the control group. Concerning BMI, there were significant effects by group (F=1.01; P<.001) and for the group × time interaction (F=4.71; P=.034). Concerning cholesterol, there were significant main effects for group (F=4.32; P=.042) and time (F=9.73; P<.001).

CONCLUSIONS

The e-Motivate4Change program effectively improved participants' health-related lifestyle scores and self-efficacy, and significantly reduced their BMI and cholesterol levels. The program can be used to identify and prevent MetS among young adults.

Ethnicity and Metabolic Syndrome: Implications for Assessment, Management and Prevention

The metabolic syndrome (MetS) is a constellation of cardiometabolic risk factors that identifies people at increased risk for type 2 diabetes and cardiovascular disease. While the global prevalence is 20%–25% of the adult population, the prevalence varies across different racial/ethnic populations. In this narrative review, evidence is reviewed regarding the assessment, management and prevention of MetS among people of different racial/ethnic groups. The most popular definition of MetS considers race/ethnicity for assessing waist circumference given differences in visceral adipose tissue and cardiometabolic risk. However, defining race/ethnicity may pose challenges in the clinical setting. Despite 80% of the world’s population being of non-European descent, the majority of research on management and prevention has focused on European-derived populations. In these studies, lifestyle management has proven an effective therapy for reversal of MetS, and randomised studies are underway in specific racial/ethnic groups. Given the large number of people at risk for MetS, prevention efforts need to focus at community and population levels. Community-based interventions have begun to show promise, and efforts to improve lifestyle behaviours through alterations in the built environment may be another avenue. However, careful consideration needs to be given to take into account the unique cultural context of the target race/ethnic group.

Metabolic health in the Middle East and north Africa

The Middle East and north Africa are home to different populations with widely varying cultures, histories, and socioeconomic settings. Hence, their health status, health management, and access to appropriate health care differ accordingly. In this Review, we examine data on the historical and prospective status of metabolic diseases in this region including obesity, diabetes, hypertension, dyslipidaemia, and non-alcoholic fatty liver disease. Women in the Middle East and north Africa have the highest risk of metabolic diseases of all women globally, whereas men rank second of all men in this respect. Metabolic risk factors are responsible for more than 300 deaths per 100 000 individuals in this region, compared with a global mean of fewer than 250. Physical inactivity, especially in women, and an unhealthy diet (ie, low consumption of whole grains, nuts, and seafoods) stand out. More than one in every three women are obese in most countries of the region. Prevention programmes have not fully been achieved in most of these countries and the projected future is not optimistic. Comprehensive surveillance and monitoring of metabolic diseases, robust multisectoral systems that support primordial and primary preventions, continuous education of health-care providers, as well as collaboration between countries for joint projects in this region are urgently needed to overcome the paucity of data and to improve the metabolic health status of inhabitants in the Middle East and north Africa.