Background: About 1 in 3 American adults have prediabetes (pre-DM), which likely will progress to type 2 diabetes (T2D). Low testosterone may be a novel risk factor for pre-DM. We assessed ...associations between pre-DM and total serum testosterone (TT), and whether the associations were modified by population characteristics and lifestyle factors. Methods: Data from 5330 adults aged >=20 years who participated in the 2011-2016 National Health and Nutrition Examination Survey were used. Pre-DM was based on fasting plasma glucose, HbA1c, or OGTT cut points. TT was collected during the physical examination and divided into quartiles. Sociodemographic, obesity, co-morbidities, and lifestyle factors were included in logistic regression models. Sub-group analyses were stratified by age, race, socioeconomic status, weight status, and lifestyle factors. Results: A dose-response relationship between prediabetes and quartiles of testosterone was found. Odds ratio (OR and 95% CI) for prediabetes across the quartiles of TT were: 1.00, 0.68 (0.50 - 0.92), 0.51 (0.36 - 0.72), 0.48 (0.34 - 0.70) in men; and 1.00, 1.06 (0.81 - 1.40), 0.81 (0.61 - 1.06), 0.68 (0.49 - 0.93) in women, respectively. Results changed some if models were adjusted for additional variables like BMI. Subgroup analyses showed differences in the associations, which were stronger in some groups (for men: age <50, White and Black, overweight/obese, adequate physical activity, never-smoking; for women: age≥50, Black). Conclusions: Higher testosterone levels were associated with decreased risk of pre-DM among US adults. The associations varied by population characteristics, weight status, and lifestyle factors. Sex-specific differences exist in these associations.
Background: This abstract describes the results of process evaluation of a pilot randomized controlled lifestyle behavior intervention aimed to help pregnant women with overweight or obesity prevent ...excessive gestational weight gain. Methods: The 20-week intervention utilized goal-oriented episodic future thinking (picturing goal-relevant future events in one's life) delivered via web and health coaching. Web Part 1. Participants selected and picture (e.g.,) personal values, ways to increase confidence, immediate-and long-term benefits of making positive changes (pros and cons), and a pre-written goal followed by answering What, Why, Where, When, with Whom and How to accomplish their chosen goal (hereafter, plan). Web Part 2. Participants evaluated progress toward goal, received tailored feedback and identified success. The online individual health coaching sessions (45 min/session) focused on reinforcing Part I activities. We conducted semi-structured interviews to evaluate the intervention and applied qualitative analysis to identify common themes. Results: Facilitators. Participants unequivocally reported picturing a happy and healthy family (the most frequently chosen personal value) and weighing pros and cons as motivators to initiate plans. Participants enjoyed choosing from pre-written goals because they felt challenged to generate their own realistic goals. They consistently reported the learning as easy. The practical plans and picturing of plans motivated them to effect implementation. Barriers. Women did not enjoy typing responses and reading text in Web Part 1. Suggestions. Participants requested extending the intervention duration, shortening health coaching sessions, reducing the frequency of the (weekly) web intervention, and receiving a summary of their plans when they completed each part of the Web intervention. Conclusions: Results of the process evaluation can provide useful information for future lifestyle interventions for the target population.
Environmental and lifestyle changes, in addition to the ageing of populations, are generally believed to account for the rapid global increase in type 2 diabetes prevalence and incidence in recent ...decades.
In this review, we present a comprehensive overview of factors contributing to diabetes risk, including aspects of diet quality and quantity, little physical activity, increased monitor viewing time or sitting in general, exposure to noise or fine dust, short or disturbed sleep, smoking, stress and depression, and a low socioeconomic status. In general, these factors promote an increase in body mass index. Since loss of β-cell function is the ultimate cause of developing overt type 2 diabetes, environmental and lifestyle changes must have resulted in a higher risk of β-cell damage in those at genetic risk. Multiple mechanistic pathways may come into play.
Strategies of diabetes prevention should aim at promoting a 'diabetes-protective lifestyle' whilst simultaneously enhancing the resistance of the human organism to pro-diabetic environmental and lifestyle factors. More research on diabetes-protective mechanisms seems warranted.
Hypertension, the leading risk factor for cardiovascular disease, originates from combined genetic, environmental, and social determinants. Environmental factors include overweight/obesity, unhealthy ...diet, excessive dietary sodium, inadequate dietary potassium, insufficient physical activity, and consumption of alcohol. Prevention and control of hypertension can be achieved through targeted and/or population-based strategies. For control of hypertension, the targeted strategy involves interventions to increase awareness, treatment, and control in individuals. Corresponding population-based strategies involve interventions designed to achieve a small reduction in blood pressure (BP) in the entire population. Having a usual source of care, optimizing adherence, and minimizing therapeutic inertia are associated with higher rates of BP control. The Chronic Care Model, a collaborative partnership among the patient, provider, and health system, incorporates a multilevel approach for control of hypertension. Optimizing the prevention, recognition, and care of hypertension requires a paradigm shift to team-based care and the use of strategies known to control BP.
To review the contribution of the Nurses' Health Studies (NHS and NHS II) in addressing hypotheses regarding risk factors for and consequences of obesity.
Narrative review of the publications of the ...NHS and NHS II between 1976 and 2016.
Long-term NHS research has shown that weight gain and being overweight or obese are important risk factors for type 2 diabetes, cardiovascular diseases, certain types of cancers, and premature death. The cohorts have elucidated the role of dietary and lifestyle factors in obesity, especially sugar-sweetened beverages, poor diet quality, physical inactivity, prolonged screen time, short sleep duration or shift work, and built environment characteristics. Genome-wide association and gene-lifestyle interaction studies have shown that genetic factors predispose individuals to obesity but that such susceptibility can be attenuated by healthy lifestyle choices. This research has contributed to evolving clinical and public health guidelines on the importance of limiting weight gain through healthy dietary and lifestyle behaviors.
The NHS cohorts have contributed to our understanding of the risk factors for and consequences of obesity and made a lasting impact on clinical and public health guidelines on obesity prevention.
A better understanding of the Chinese consumption of luxury fashion brands may assist the fashion industry when targeting China as the soon-to-be largest consumer market. This study aims to examine ...Chinese consumers' willingness to pay for luxury fashion brands related to their fashion lifestyle and perceived value. Practicality fashion lifestyle, perceived social/emotional value, perceived utilitarian value, and perceived economic value were found to have a significant influence on the willingness of Chinese consumers to pay for luxury fashion brands in a multiple regression model (n=480). This research also examines the different effects of fashion lifestyles and perceived value on willingness to pay among four groups characterized by different previous genuine and counterfeit purchasing experiences. This study deepens understanding of consumer perceptions and behaviors relating to luxury fashion brands in China.
Whether a healthy lifestyle impacts longevity in the presence of multimorbidity is unclear. We investigated the associations between healthy lifestyle and life expectancy in people with and without ...multimorbidity.
A total of 480,940 middle-aged adults (median age of 58 years range 38-73, 46% male, 95% white) were analysed in the UK Biobank; this longitudinal study collected data between 2006 and 2010, and participants were followed up until 2016. We extracted 36 chronic conditions and defined multimorbidity as 2 or more conditions. Four lifestyle factors, based on national guidelines, were used: leisure-time physical activity, smoking, diet, and alcohol consumption. A combined weighted score was developed and grouped participants into 4 categories: very unhealthy, unhealthy, healthy, and very healthy. Survival models were applied to predict life expectancy, adjusting for ethnicity, working status, deprivation, body mass index, and sedentary time. A total of 93,746 (19.5%) participants had multimorbidity. During a mean follow-up of 7 (range 2-9) years, 11,006 deaths occurred. At 45 years, in men with multimorbidity an unhealthy score was associated with a gain of 1.5 (95% confidence interval CI -0.3 to 3.3; P = 0.102) additional life years compared to very unhealthy score, though the association was not significant, whilst a healthy score was significantly associated with a gain of 4.5 (3.3 to 5.7; P < 0.001) life years and a very healthy score with 6.3 (5.0 to 7.7; P < 0.001) years. Corresponding estimates in women were 3.5 (95% CI 0.7 to 6.3; P = 0.016), 6.4 (4.8 to 7.9; P < 0.001), and 7.6 (6.0 to 9.2; P < 0.001) years. Results were consistent in those without multimorbidity and in several sensitivity analyses. For individual lifestyle factors, no current smoking was associated with the largest survival benefit. The main limitations were that we could not explore the consistency of our results using a more restrictive definition of multimorbidity including only cardiometabolic conditions, and participants were not representative of the UK as a whole.
In this analysis of data from the UK Biobank, we found that regardless of the presence of multimorbidity, engaging in a healthier lifestyle was associated with up to 6.3 years longer life for men and 7.6 years for women; however, not all lifestyle risk factors equally correlated with life expectancy, with smoking being significantly worse than others.
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