Philo4Thought Presents Healthy Lifestyle Series Pilot on April 24 – The National Herald

NEW YORK – Philo4Thought’s new Healthy Lifestyle Seminar Series focuses on adopting sound health and lifestyle habits for a better work-life experience. On Saturday, April 24, 11 AM-1 PM EDT, the Healthy Lifestyle Series Pilot takes place via Zoom.

Registration is required. More information is available on Eventbrite, search Healthy Lifestyle Series Pilot.

Since 2009, Philo4Thought’s goal has been to help emerging young professionals connect with viable career resources and opportunities. The organization has been particularly active in the months during the pandemic, lending support to struggling students, professionals, new entrepreneurs and local business owners.

Philo4Thought’s Spring 2021 instructional videos and panel-style seminars will focus on achieving work-life balance, aligning goals, spotting and assessing common setbacks/pitfalls that emerging professionals should anticipate, etc. Philo4Thought will also introduce great resources designed to get you on the right track for your optimal academic and professional advancement.

Philo4Thought is a 501(c)3 philanthropic educational nonprofit foundation that fosters positive, constructive career coaching and work-life mentoring for young professionals and new entrepreneurs. Services include the interactive webpage, one-on-one consultations, small group workshops, networking opportunities with seasoned professionals and an annual spring conference.

Annual and monthly activities are held both live and online to cater to Philo4Thought’s expanding network of 375,000+ clients served since 2009.

More information is available online:www.philo4thought.org.

Getting started on a healthy lifestyle with MS – Norton Healthcare

If you have multiple sclerosis, physical exercise can be an important part of your treatment. But don’t let that word — exercise — put you off.

“Everyone should be getting exercise, regardless of your disability level. How much exercise or what type will vary, but the message here is that everyone should be exercising,” Sara L. Perry, APRN, nurse practitioner with Norton Neuroscience Institute, told patients and caregivers during the 2020 Neuroscience Expo.

The National Multiple Sclerosis Society, which partnered with the Norton Neuroscience Institute Resource Center for presentations in the MS track of the Neuroscience Expo, recommends all people with MS complete at least 150 minutes of exercise or physical activity each week. You can break it down however you’d like as one long activity or multiple short activities, as long as you aim for 150 minutes — 2 1/2 hours — a week.

“This is going to look different for each person based on your current and changing ability levels, and some of you may require assistance from a trained assistant,” Sara said.

4 categories of exercise

  • Aerobic: Activities that increase your breathing and heart rate
    • Strategies: Two to three times per week for 10 to 30 minutes at moderate intensity. Those who can be more intense might do aerobics five times a week for up to 40 minutes. This could be high intensity interval training, running, walking, cycling.
  • Resistance: Exercises designed to increase the strength of bones, muscles and connective tissues
    • Strategies: Two to three times a week, five to 10 exercises, one to three sets with eight to 15 repetitions. This could include weight machines, free weights, resistance bands and body weight.
  • Flexibility: Exercises that stretch your muscles and can increase movement and decrease pain or discomfort
    • Strategies: Do those daily, two to three sets, holding for 30 to 60 seconds. This could include yoga or stretching.
  • Neuromotor: Exercises that improve balance, coordination, posture and trunk strength
    • Strategies: Three to six times per week for 20 to 60 minutes. This could be dance, tai chi, balance or yoga.

If you need some support, you can add in modifications such as a hand cycle, three-wheeled bike or walking poles. Aquatic exercises help you move in ways you may not be able to on land and keep your body cool. Seated exercises or movements may feel more comfortable and can help you maintain proper form and posture as well as help you tolerate longer periods of physical activity.

If you need a high level of support, consider a resistance breathing apparatus like an incentive spirometer that helps you take slow deep breaths to expand and fill your lungs. Do this every other day with three sets of 10 repetitions.

Flexibility — one time a day, 30 to 60 second holds with a focus on affected joints

  • Upper extremities — six three-minute intervals of actively taking a joint through its complete spectrum of movements
  • Lower extremities — three times a week, 30 minutes standing; could be with assistance or using a standing frame
  • Core — every one to two hours, posture exercises, hold 10 to 15 seconds, such as pulling shoulder blades back, head up, straightening back

Norton Neuroscience Institute Resource Center

The Norton Neuroscience Institute Resource Center in St. Matthews provides help with the day-to-day challenges of living with a neurological condition. It’s part of Norton Neuroscience Institute’s goal to care for the whole person, not just the condition.

Learn more

Lifestyle physical activity

These can be planned or unplanned activities that are a part of everyday life and can be achieved in short intervals. It does not need to be continuous or repetitive, so it may be easier to achieve than exercise. It’s the kind of things you’re probably already doing and not realizing you’re doing something so good for yourself.

Walking your dog, gardening or propelling your wheelchair — all are examples of lifestyle activity.

For those who need little to no support, lifestyle physical activity strategies include behavior change strategies like self-monitoring and setting alarms or calendar alerts, tracking activity through electronic devices or journaling, and increasing daily targets.

Those who need a moderate level of support can pursue those above, but modify them with equipment like walking poles to promote safety or participate in activities in a seated position.

Those who need a high level of support can consider functional movement of any kind like active weight shifting for pressure relief or participating in activities of daily living, propelling a manual wheelchair and using mobility aids such as a standing frame.


Neurosciences

Unhealthy lifestyle only explains small part of health – Big News Network

London [UK], April 17 (ANI): A recent study on UK and US adults states that unhealthy lifestyles alone only explain a small proportion of the socioeconomic inequity in health.

This is the suggestion of a large study published in the BMJ.

The findings show that the poorest individuals with the least healthy lifestyle are 2.7 to 3.5 times more at risk of death than the most affluent people with the healthiest lifestyle.

While healthy lifestyles play an important role in reducing disease burden, the researchers warn that healthy lifestyle promotion alone “might not substantially reduce the socioeconomic inequity in health, and other measures tackling social determinants of health are warranted.”It is well known that disadvantaged socioeconomic status (the measure of a person’s social and economic standing) and unhealthy lifestyles are linked to poor health.

Lifestyle factors are commonly viewed as mediators between socioeconomic status and health, but it’s not clear to what extent healthy lifestyles might alleviate the socioeconomic inequities in health.

To explore this further, an international research team used data from the US National Health and Nutrition Examination Survey (US NHANES) and UK Biobank to evaluate the complex relations of lifestyles and socioeconomic status with death and heart disease.

Their findings are based on 44,462 US adults aged 20 years or older and 399,537 UK adults aged 37-73 years.

Socioeconomic status was defined using family income, occupation or employment status, and education level in both groups, and health insurance in US participants. A healthy lifestyle score was derived using the information on smoking, alcohol consumption, physical activity and diet.

Medical records were then used to track deaths from any cause (“all-cause mortality”) among both US and UK adults, as well as cases of cardiovascular disease (CVD) and CVD deaths in UK adults.

Over an average follow-up of 9-11 years, US NHANES documented 8,906 deaths and UK Biobank documented 22,309 deaths and 6,903 CVD cases.

Among adults of low socioeconomic status, the age-adjusted risk of death was 22.5 and 7.4 per 1000 person-years in US NHANES and UK Biobank, respectively, and the age-adjusted risk of CVD was 2.5 per 1000 person-years in UK Biobank.

The corresponding risks among adults of high socioeconomic status were 11.4, 3.3, and 1.4 per 1000 person-years.

Compared with adults of high socioeconomic status, those of low socioeconomic status had consistently higher risks of mortality and CVD, and lifestyle factors only explained 3 per cent to 12 per cent of the excess risks. The highest risks of mortality and CVD were seen in adults of low socioeconomic status and with the least healthy lifestyles.

For example, compared with adults of high socioeconomic status and three or four healthy lifestyle factors, those with low socioeconomic status and no or one healthy lifestyle factor had 2.09-fold to 3.53-fold higher risks of mortality and CVD.

This is an observational study, so can’t establish cause, and information on the socioeconomic level and lifestyle was self-reported, so may not have been completely accurate. Nevertheless, strengths included the large sample size from two well established nationwide databases, and results were similar after further analyses, suggesting they are robust.

Unhealthy lifestyles mediated a small proportion of the socioeconomic inequity in health in both US and UK adults; therefore, healthy lifestyle promotion, although essential, alone might not substantially reduce the socioeconomic inequity in health, and other measures tackling social determinants of health are warranted, say the researchers.

They call for government policies “to tackle upstream social and environmental determinants of health” but also point out that healthy lifestyles were associated with lower mortality and CVD risk in different socioeconomic groups, “supporting an important role of healthy lifestyles in reducing disease burden.” (ANI)

The Big Sleuth Gives People the Information and Support They Need to Maintain A Healthy Lifestyle – Benzinga

Birmingham, April 16, 2021 (GLOBE NEWSWIRE) — The COVID-19 pandemic has affected people’s health in numerous ways all over the world during the past year. With most gyms being closed and more of us being cooped up at home, maintaining daily routines and healthy lifestyles can feel impossible. This is why you need support and guidance from an external, reputable source.

The Big Sleuth is the ultimate online resource for people who want to lead a healthier, happier lifestyle. The site gives unbiased advice and guidance on a range of health and fitness related matters, paying particular attention to reviewing nutritional supplements. The Big Sleuth team work hard every day to ‘detect, inspect and review’ the most popular health products on the market and discover if they are worthwhile or not. In short, they do the hard work for you and spend hours researching the latest products so you don’t have to!

Unbiased information and support

The Big Sleuth team knows there is a lot of misinformation online these days, especially within the fitness industry, and they have made it their mission to sort through the noise and provide people with balanced guidance that people can trust.

The Big Sleuth takes great pride in providing consumers like you with unbiased information that actually helps you find the perfect supplement for your needs. They carefully analyse and review each supplement, conduct safety checks on the ingredients in question to ensure they aren’t linked to any harmful side effects, and even look at servings to ensure you’re getting a beneficial dose from each supplement.

When you regularly take a high-quality supplement alongside having a balanced diet and consistent exercise, the health benefits can be phenomenal. If you’d love to kickstart your healthy lifestyle, head over to The Big Sleuth’s website to find out what the team think of the latest nootropics or what brand they feel provides the best multivitamin UK.

Healthy living during a pandemic

It has been shown that a combination of a healthy diet, regular physical activity, a quality sleep schedule and time spent on self-care not only improves physical and mental health and wellbeing, but can also make us more resilient to COVID-19. The pandemic has definitely highlighted the importance of health, yet it can be overwhelming trying to maintain a healthy lifestyle with regular routines and habits going out the window.

The Big Sleuth is a valuable resource that can support you during these strange times and keep you on track with your fitness goals, offering lots of useful information and advice on maintaining a healthy lifestyle and reviews on health products. The Big Sleuth team have put together a collection of reviews of nutritional supplements and health consumables (https://thebigsleuth.co.uk/get-healthy/) including, but not limited to:

•           Sleep aids
•           Multivitamins
•           Digestive health
•           Joint care
•           Health foods

Everyone wants to stay as healthy as possible in their lives, especially when the world is fighting off a pandemic. By taking The Big Sleuth’s advice to find high-quality health supplements, you’re giving your body more of the nutrients it needs to function optimally during stressful, uncertain times.

More information

The Big Sleuth is an expanding health site that exists to give consumers the information they need on nutritional supplements and other wellbeing products so they can lead the healthiest lifestyle possible. You can check out the product reviews and health advice by visiting https://thebigsleuth.co.uk/. If you wish to get in touch with the team, you can do so by emailing contact@thebigsleuth.co.uk.

https://thenewsfront.com/the-big-sleuth-gives-people-the-information-and-support-they-need-to-maintain-a-healthy-lifestyle/

The Big Sleuth
11 St Paul's Square, Birmingham B3 1RB contact@thebigsleuth.co.uk https://thebigsleuth.co.uk/

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Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies – The BMJ

Abstract

Objective To examine whether overall lifestyles mediate associations of socioeconomic status (SES) with mortality and incident cardiovascular disease (CVD) and the extent of interaction or joint relations of lifestyles and SES with health outcomes.

Design Population based cohort study.

Setting US National Health and Nutrition Examination Survey (US NHANES, 1988-94 and 1999-2014) and UK Biobank.

Participants 44 462 US adults aged 20 years or older and 399 537 UK adults aged 37-73 years.

Exposures SES was derived by latent class analysis using family income, occupation or employment status, education level, and health insurance (US NHANES only), and three levels (low, medium, and high) were defined according to item response probabilities. A healthy lifestyle score was constructed using information on never smoking, no heavy alcohol consumption (women ≤1 drink/day; men ≤2 drinks/day; one drink contains 14 g of ethanol in the US and 8 g in the UK), top third of physical activity, and higher dietary quality.

Main outcome measures All cause mortality was the primary outcome in both studies, and CVD mortality and morbidity in UK Biobank, which were obtained through linkage to registries.

Results US NHANES documented 8906 deaths over a mean follow-up of 11.2 years, and UK Biobank documented 22 309 deaths and 6903 incident CVD cases over a mean follow-up of 8.8-11.0 years. Among adults of low SES, age adjusted risk of death was 22.5 (95% confidence interval 21.7 to 23.3) and 7.4 (7.3 to 7.6) per 1000 person years in US NHANES and UK Biobank, respectively, and age adjusted risk of CVD was 2.5 (2.4 to 2.6) per 1000 person years in UK Biobank. The corresponding risks among adults of high SES were 11.4 (10.6 to 12.1), 3.3 (3.1 to 3.5), and 1.4 (1.3 to 1.5) per 1000 person years. Compared with adults of high SES, those of low SES had higher risks of all cause mortality (hazard ratio 2.13, 95% confidence interval 1.90 to 2.38 in US NHANES; 1.96, 1.87 to 2.06 in UK Biobank), CVD mortality (2.25, 2.00 to 2.53), and incident CVD (1.65, 1.52 to 1.79) in UK Biobank, and the proportions mediated by lifestyle were 12.3% (10.7% to 13.9%), 4.0% (3.5% to 4.4%), 3.0% (2.5% to 3.6%), and 3.7% (3.1% to 4.5%), respectively. No significant interaction was observed between lifestyle and SES in US NHANES, whereas associations between lifestyle and outcomes were stronger among those of low SES in UK Biobank. Compared with adults of high SES and three or four healthy lifestyle factors, those with low SES and no or one healthy lifestyle factor had higher risks of all cause mortality (3.53, 3.01 to 4.14 in US NHANES; 2.65, 2.39 to 2.94 in UK Biobank), CVD mortality (2.65, 2.09 to 3.38), and incident CVD (2.09, 1.78 to 2.46) in UK Biobank.

Conclusions Unhealthy lifestyles mediated a small proportion of the socioeconomic inequity in health in both US and UK adults; therefore, healthy lifestyle promotion alone might not substantially reduce the socioeconomic inequity in health, and other measures tackling social determinants of health are warranted. Nevertheless, healthy lifestyles were associated with lower mortality and CVD risk in different SES subgroups, supporting an important role of healthy lifestyles in reducing disease burden.

Methods

Study population

US NHANES recruited a representative sample of civilian, community dwelling members of the US population using a complex, multistage probability design. The survey was conducted periodically before 1999 and continuously thereafter. Details of the study design and data collection have been previously described.9 Although US NHANES has released cross sectional questionnaire, examination, and laboratory data up to 2018, mortality data were updated to 31 December 2015. Accordingly, the current analysis included 61 202 participants who were aged 20 years and older and not pregnant at baseline in US NHANES III (1988-94) and continuous NHANES (1999-2014) surveys. Those with missing information on socioeconomic factors (n=6939), lifestyle factors (n=8156), other covariates (n=1619), and deaths (n=26) were excluded from the analysis. Overall, 44 462 participants from US NHANES were included (supplementary fig 1).

UK Biobank recruited more than 500 000 participants aged 37 to 73 years from 22 assessment centers across England, Scotland, and Wales between 2007 and 2010. Details of the study design and data collection have been described previously.10 Among the 502 492 participants, we excluded those with missing information on socioeconomic factors (n=77 962), lifestyle factors (n=20 029), and other covariates (n=4964). Overall, 399 537 participants were included (supplementary fig 1). For the analysis of incident CVD, we only included those without prevalent CVD (n=324 517) at baseline.

Assessment of SES

In US NHANES, self-reported family income level, occupation, education level, and health insurance were used to measure SES according to previous studies,711 and each factor was divided into three levels (low, medium, and high) with consideration of practical interpretation and sample size within levels. The family income level was operationalized using the family poverty to income ratio, which reflected the annual family income relative to the federal poverty level and was comparable across surveys since income thresholds were updated for inflation and family size each year.12 According to a published study and the Patient Protection and Affordable Care Act, we grouped participants according to the poverty to income ratio: low (≤1), middle (1-4), and high (≥4).12 Education was categorized into less than high school diploma, high school graduate or equivalent, and college or above.13 Occupation was classified based on the widely used socioeconomic index in the US,14 and each occupation was rated according to the employees’ earnings, education level, and prestige. The socioeconomic index ranged between 13.98 and 90.45,15 and occupation was categorized into upper (socioeconomic index ≥50), lower (socioeconomic index <50, including retirees16 and students), and unemployment. Health insurance was categorized into private health insurance (including any private health insurance, Medi-Gap, or single-service plan), public health insurance only (including Medicare, Medicaid, State Children’s Healthcare Plan, military healthcare, Indian Health Service, State Sponsored Health Plan, or other government programme), and no health insurance.17 An overall SES variable was created using latent class analysis based on family income level, occupation, education level, and health insurance (each factor had three levels).7 The latent class analysis, which uses multiple observed categorical variables to generate an unmeasured variable (ie, latent variable) with a set of mutually exclusive latent classes, was conducted using PROC LCA, a new SAS procedure.18 Three latent classes were identified, which respectively represented a high, medium, and low SES according to the item-response probabilities.19 The supplementary file describes the data collection and latent class analysis in US NHANES.

In UK Biobank, total household income before tax was obtained through questionnaires, and participants could choose an option from <₤18 000 ($25 000; €21 000), ₤18 000-£30 999, ₤31 000-£51 999, ₤52 000-£100 000, >₤100 000, do not know, or prefer not to answer. A total of 14.3% of participants chose the last two options and were excluded from the main analyses as missing values; however, we included them in sensitivity analyses when evaluating single socioeconomic factors, consistent with a previous study,20 on the basis that these participants might be more likely to have lower SES. Participants reported their education qualifications as college or university degree; A levels, AS levels, or equivalent; O levels, GCSEs, or equivalent; CSEs or equivalent; NVQ, HND, HNC, or equivalent; other professional qualifications; none of the above (equivalent to less than high school diploma); or prefer not to answer (which was excluded from our analyses as missing values). As UK Biobank only acquired employment status instead of information on specific occupation at baseline, we regrouped participants into two groups: employed (including those in paid employment or self-employed, retired, doing unpaid or voluntary work, or being full or part time students) and unemployed. Because the National Health Service, a publicly funded healthcare system aiming to provide comprehensive, universal and free services, is implemented in the UK,21 we did not consider health insurance as a component of SES in UK Biobank. An overall SES variable was created using latent class analysis based on three individual socioeconomic factors (household income, education level, and employment status). We did not regroup household income and education level into three groups as we did in US NHANES because of the larger sample size in UK Biobank and failure of model convergence owing to fewer observed groups if the two variables were regrouped. Three latent classes were identified, which respectively represented a high, medium, and low SES according to the item-response probabilities. Details are reported in the supplementary file.

In UK Biobank, Townsend deprivation index was available as an area level SES variable derived from national census data according to postcodes of residence, which considered car ownership, household overcrowding, owner occupation, and unemployment.22 A higher Townsend deprivation index denotes lower area level SES.22

Assessment of lifestyle factors and other covariates

Since multiple lifestyle factors are interrelated and are associated with mortality and morbidity, we constructed a healthy lifestyle score including cigarette smoking, alcohol consumption, physical activity, and diet according to a previous US NHANES study23 and that coincided with recommendations from the World Health Organization.24 All lifestyle factors were obtained through structured questionnaires and 24 hour dietary recalls. Never smoking was considered as a healthy level, which was defined in the questionnaire as smoking fewer than 100 cigarettes in life. Frequency and volume of current alcohol consumption were self-reported, and a healthy level was defined as daily consumption of one drink or fewer for women and two drinks or fewer for men, according to the dietary guidelines in the US and UK (one drink contains 14 g of ethanol in the US and 8 g in the UK).2526 For physical activity, different assessment questions were used between the US and UK studies, and questionnaires also varied in different survey years in US NHANES. Nevertheless, weekly metabolic equivalent hours of leisure time physical activity were calculated in US NHANES 1999-2014 and UK Biobank, whereas monthly frequency of leisure time physical activity was calculated in US NHANES 1988-94. To harmonize the data, we further classified the participants into thirds and defined the top third as a healthy level of physical activity.

In US NHANES, dietary quality was obtained from 24 hour dietary recalls and was assessed by healthy eating index (HEI) scores. The HEI-2015 was calculated for the 1999-2014 survey cycles, which aligns with the 2015-20 Dietary Guidelines for Americans.27 However, because food codes used in the 1988-94 cycles could not match those used in the 1999-2014 cycles, we used HEI-1995 for the 1988-94 cycles and the variable was directly provided by the original dataset. HEI-1995 aligns with the food guide pyramid released by the US Department of Agriculture in 1992.27 Supplementary table 1 provides details of constructions of HEI-1995 and HEI-2015, and both scores reflected the overall dietary quality according to the contemporary dietary guidelines. A healthy diet was defined as the health eating index in the top two fifths of distribution.28 In UK Biobank, dietary information was obtained through questionnaires and did not contain energy or salt intakes, thus we could not calculate the HEI scores. Instead, according to a previous UK Biobank study,29 we evaluated dietary quality using a more recent dietary recommendation for cardiovascular health, which considered adequate consumption of fruit, vegetables, whole grains, fish, shellfish, dairy products, and vegetable oils and reduced consumption of refined grains, processed meats, unprocessed meats, and sugar sweetened beverages. We defined a healthy diet as meeting at least five items of the recommendations (see supplementary table 2).

For each lifestyle factor, we assigned 1 point for a healthy level and 0 points for an unhealthy level. Thus, the healthy lifestyle score was the sum of the points and ranged between 0 and 4, with higher scores indicating healthier lifestyles. Although this simple additive method has been used widely,303132 the underlying assumption is that the associations between different lifestyle factors and the outcome were identical, which might not be true. Thus we also constructed a weighted lifestyle score, where each lifestyle factor was weighted by its association with the outcome. Body mass index (BMI) was not included in the lifestyle score given the concern that it could be an intermediate factor between behavioral factors and health outcomes. In addition, the obesity paradox is a concern,33 and overweight and obesity might not be strongly associated with mortality in older people.13 Nevertheless, we also included baseline BMI in the lifestyle score in a sensitivity analysis, and healthy bodyweight was defined as a BMI of 18.5-24.9.28

Other covariates were obtained through questionnaires, including age; sex; marital status (US NHANES only); assessment centers (UK Biobank only); self-reported race; an acculturation score based on the country of birth, length of time in the US or UK, and language spoken at home (see supplementary file);34 history of hypertension, diabetes, CVD, or cancer; and history of chronic bronchitis, emphysema, or chronic obstructive pulmonary disease (UK Biobank only). Diagnoses of CVD and cancer were also obtained through linked hospital admissions data and cancer registry in the UK Biobank. Bodyweight and height were measured at baseline, with BMI calculated as weight (kg)/(height (m)2).

Outcome ascertainment

Outcomes were classified using ICD-9 and ICD-10 (international classification of diseases, ninth and 10th revisions, respectively) codes. The primary outcomes included all cause mortality, CVD mortality, and incident CVD. In US NHANES, deaths were obtained through the National Death Index to 31 December 2015.35 In UK Biobank, deaths were obtained through death certificates held within the NHS Information Centre (England and Wales) and the NHS Central Register (Scotland) to 30 April 2020.36 CVD diagnoses, including myocardial infarction (ICD-9 codes 410-412 and 429.79; ICD-10 codes I21-I23, I24.1, and I25.2) and stroke diagnoses (ICD-9 codes 430, 431, 434, and 436; ICD-10 codes I60, I61, I63, and I64), were obtained through linked hospital admissions data including Hospital Episode Statistics-Admitted Patient Care (England), Scottish Morbidity Records-General/Acute Inpatient and Day Case Admissions (Scotland), and Patient Episode Database for Wales as well as death register data to 31 January 2018.3738 Secondary outcomes were mortality from heart disease (ICD-10 codes I00-I09, I11, I13, and I20-I51 in US NHANES), coronary heart disease (ICD-10 codes I20-I25 in UK Biobank), and stroke (ICD-10 codes I60, I61, I63, and I64 in UK Biobank), as well as incident myocardial infarction and stroke. Mortality from cerebrovascular disease or total CVD was not considered in NHANES because the US National Death Index matched mortality dataset stopped updating data on deaths from cerebrovascular diseases after 31 December 2011.

Statistical analysis

To estimate appropriate variance and statistics representative of US adults, our analysis in US NHANES considered the oversampling, stratification, and clustering according to the NHANES statistical analysis guideline.39 Baseline characteristics were described across different levels of SES, and differences among groups were tested by analysis of variance adjusted for sampling weights for continuous variables and Rao-Scott χ2 test for categorical variables in US NHANES, and by analysis of variance and χ2 test in UK Biobank.

We used Cox proportional hazard regression models to estimate the hazard ratios and 95% confidence intervals of outcomes associated with SES and lifestyle score. The proportional hazards assumption was examined by creating a product term of follow-up time and SES, and we found no significant deviation from the assumption.40 Person years were calculated from baseline until the date of death or diagnosis (for the incident CVD analysis), or end of follow-up, whichever occurred first. Based on previous researches,2023 model 1 included SES; age; sex; self-reported race; marital status (US NHANES only); assessment centers (UK Biobank only); acculturation; BMI; and history of hypertension, diabetes, CVD, cancer, chronic bronchitis, emphysema, or chronic obstructive pulmonary disease. Model 2 additionally included the healthy lifestyle score. We used the difference method to calculate the mediation proportion by the mediator (overall lifestyle) for the association between SES and each outcome—that is, comparing estimates from models with and without the hypothesized mediator.41 We additionally calculated the C statistics of the two models to compare the predictions with versus without the healthy lifestyle score.

We further conducted a stratified analysis by latent class of SES to investigate associations of the lifestyle score with health outcomes among adults in different socioeconomic subgroups. As only 838 (2.2%) and 3495 (9.4%) US adults had 0 and 4 points of healthy lifestyle score, and the corresponding numbers in the UK Biobank were 49 545 (12.4%) and 9841 (2.5%), we merged participants with 0 points and 1 point as well as those with 3 and 4 points to increase the statistical power. In this analysis, the reference group was set as the participants with unhealthy lifestyles (lifestyle scores of 0 or 1), and we examined whether adherence to healthy lifestyles was associated with protection against mortality and incident CVD across different SES subgroups. To quantify the additive and multiplicative interactions, we additionally included a product term of SES (low, medium, and high) and healthy lifestyle score (0 or 1; 2; and 3 or 4 points) in the model. The hazard ratio with its 95% confidence interval of the product term was the measure of interaction on the multiplicative scale. We used the relative excess risk due to interaction (RERI) and corresponding 95% confidence intervals as the measure of interaction on the additive scale, calculated using the coefficients and corresponding standard errors of the product term, SES, and lifestyle score, as well as covariance matrix.42

To assess the joint associations, we further classified participants into nine groups according to SES (low, medium, and high) and healthy lifestyle score (0 or 1; 2; and 3 or 4 points) and estimated hazard ratios of mortality and incident CVD in different groups compared with those with high SES and three or four healthy lifestyle factors.

To test the robustness and potential variations in different subgroups, we repeated all analyses stratified by sex (men and women), self-reported race (white and non-white participants), and age groups (<60, and ≥60, defined as elders by the World Health Organization43).

We conducted several sensitivity analyses. First, we repeated all analyses by substituting SES with each socioeconomic factor (ie, family income level, occupation or employment status, education level, and health insurance), and these factors were mutually adjusted in the models. Similarly, we also used the individual lifestyle factors instead of the score in the models to evaluate whether the estimated mediation proportion was similar to that of the main analysis. Second, a weighted healthy lifestyle score was constructed to account for varied magnitudes of the associations between different lifestyle factors and outcomes.44 Third, we constructed a lifestyle score including baseline BMI. Fourth, we excluded individuals with prevalent diabetes, CVD, cancer, chronic bronchitis, emphysema, or chronic obstructive pulmonary disease because both lifestyles and SES could be influenced by major chronic diseases. Fifth, we excluded events that occurred within the first three years of follow-up to reduce potential reverse causation. Sixth, we restricted the analysis to those aged 40 years or older in US NHANES to coincide with the age distribution in UK Biobank, and to reduce the concern that SES is prone to change and the risk of mortality due to lifestyles is relatively lower in younger adults. As only five participants in UK Biobank were aged less than 40 years, this sensitivity analysis was not performed in UK Biobank. Seventh, we used multiple imputation to impute all missing independent variables to test the influence of missing variables.45 Eighth, we assigned 0, 1, and 2 points to each low, medium, and high level socioeconomic factor (for employment status in UK Biobank, only 0 and 2 points were assigned for unemployed and employed status) and added the scores to get a socioeconomic score (range 0-8 in US NHANES and 0-6 in UK Biobank). As only 756 (0.9%) participants in US NHANES and 5000 (1.3%) in UK Biobank had a score of 0, we merged those with 0 or 1 point. The socioeconomic score was then used in all analyses instead of the latent class derived SES variable. Ninth, in the final model in UK Biobank we further included the Townsend deprivation index, a variable reflecting the area level SES, for two purposes: to evaluate whether the association between individual level SES and health outcomes remained robust when controlling for area level SES, and to repeat all the main analysis using Townsend deprivation index as the SES variable, instead of the individual level SES variable. Tenth, we additionally included quadratic terms of age in the models to consider the possible non-linear associations of age with health outcomes.

All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). We considered two sided P values <0.05 to be significant.

Patient and public involvement

The analyses were based on existing data of two cohort studies in general populations, US NHANES and UK Biobank, and we did not participate in the participant recruitment. To our knowledge, no patients were involved in the design, recruitment, or conduct of the studies. The research question and outcome measures of the present study were proposed by systematically reviewing the evidence of the associations between lifestyles and non-communicable diseases, and no patients were involved in the process. Participants from the two cohorts were deidentified, and thus we could not disseminate the results to each participant; however, the results will be disseminated to the public through broadcasts and popular science articles.

Results

Population characteristics

Table 1 shows baseline characteristics of participants from US NHANES and UK Biobank. Among 44 462 participants from US NHANES (mean age 46.5 years, 48.7% men), 10 469 (33.6%) were of high SES, 20 729 (46.4%) of medium SES, and 13 264 (20.0%) of low SES. Among 399 537 participants from UK Biobank (mean age 56.1 years, 47.5% men), 79 697 (19.9%) were of high SES, 210 935 (52.8%) of medium SES, and 108 905 (27.3%) of low SES. Adults of low SES were more likely to be women, non-white people, not married, unemployed, and less educated, and to have low income, public or no health insurance, and a higher prevalence of comorbidities. Unhealthy levels of cigarette smoking, leisure time physical activity, and BMI were more prevalent among adults of low SES. Participants excluded from the current analysis owing to missing information were older, of low SES, and more likely to be women, non-white people, not married, and less accultured (see supplementary table 3).

Table 1

Baseline characteristics of participants from US National Health and Nutrition Examination Survey (US NHANES) and UK Biobank according to socioeconomic status (SES).* Values are numbers (percentages) unless stated otherwise

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Mediation analysis of lifestyle on associations of SES with mortality and incident CVD

In US NHANES, 8906 deaths were recorded (1889 from heart disease) during a mean follow-up of 11.2 years. In UK Biobank, 22 309 deaths (4537 from CVD; a mean follow-up of 11.0 years) and 6903 incident CVD cases (4414 myocardial infarction and 2645 stroke; a mean follow-up of 8.8 years) were recorded. After adjusting for lifestyle score and other covariates, including age, sex, self-reported race, marital status, assessment centers, acculturation, BMI, and history of comorbidities, the hazards ratios when adults of low SES were compared with adults of high SES were 2.13 (95% confidence interval 1.90 to 2.38) for all cause mortality in US NHANES, and 1.96 (1.87 to 2.06) for all cause mortality, 2.25 (2.00 to 2.53) for CVD mortality, and 1.65 (1.52 to 1.79) for incident CVD in UK Biobank (table 2). The hazard ratios without adjustment for lifestyle score were larger. Each additional healthy lifestyle factor was associated with 11% to 17% lower risks of mortality and incident CVD (supplementary table 4). When low SES was compared with high SES, the proportion mediated by the lifestyle score was 12.3% (10.7% to 13.9%) for all cause mortality in US NHANES, and 4.0% (3.5% to 4.4%) for all cause mortality, 3.0% (2.5% to 3.6%) for CVD mortality, and 3.7% (3.1% to 4.5%) for incident CVD in UK Biobank (table 2). When the socioeconomic score was used to investigate more extreme socioeconomic disparities, the hazard ratios for the lowest compared with highest socioeconomic score were 2.87 and 3.23 for all cause mortality in US NHANES and UK Biobank, respectively, and 3.37 for CVD mortality and 2.46 for incident CVD in UK Biobank. However, the mediation proportion attributed to lifestyle remained similar to that of the main analyses (supplementary table 5). Additional inclusion of the healthy lifestyle score did not improve the prediction of all outcomes (supplementary table 6).

Table 2

Associations of socioeconomic status (SES) with incident cardiovascular disease (CVD) and mortality and mediation proportion of socioeconomic inequity in health attributed to lifestyle*

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When low SES levels were compared with high SES levels, each individual socioeconomic factor was associated with higher risks of all primary outcomes, and the hazard ratios ranged from 1.13 to 2.09 (supplementary table 7). The proportion of the association between individual socioeconomic factors and mortality mediated by lifestyles ranged from less than 1% for household income in UK Biobank to 22.2% for education attainment in both cohorts. When the Townsend deprivation index was simultaneously included in the final model in UK Biobank, the associations of individual level SES with primary outcomes were not materially changed. In general, the associations between Townsend deprivation index and health outcomes were weaker compared with individual level SES (supplementary fig 2). Results of all sensitivity analyses were largely consistent, except that the mediation proportion increased when the healthy lifestyle score was substituted by four individual lifestyle factors in UK Biobank (supplementary table 5).

Supplementary table 8 shows the results for the mortality and morbidity of CVD subtypes. The hazard ratios when low SES was compared with high SES ranged from 1.45 for incident stroke to 2.62 for coronary heart disease mortality, and the mediation proportion by lifestyle ranged from 2.8% to 8.2%.

Interaction and joint analysis of lifestyle and SES with mortality and incident CVD

No significant interaction was found between lifestyle and SES on all cause mortality in US NHANES, whereas both multiplicative and additive interactions were observed between lifestyle and SES on all primary outcomes in UK Biobank (all P for interaction <0.02; fig 1). A healthier lifestyle score was associated with lower risks of all primary outcomes among individuals of various SES subgroups in both cohorts, whereas the associations were stronger among those from a low SES subgroup in UK Biobank (fig 1). For example, in UK Biobank, the hazard ratios for those with three or four healthy lifestyle factors compared with no or one healthy lifestyle factor for all cause mortality were 0.86 (0.76 to 0.96) among individuals of high SES, 0.70 (0.66 to 0.74) among those of medium SES, and 0.56 (0.52 to 0.59) among those of low SES. Similar patterns were found for total CVD mortality and incident CVD (fig 1), and when CVD subtypes were used as the outcomes (supplementary fig 3), as well as when the area level Townsend deprivation index was used as the SES variable (supplementary fig 2). The results remained similar in all sensitivity analyses (supplementary table 9).

Fig 1

Associations of healthy lifestyle score with mortality and incident cardiovascular disease (CVD) by socioeconomic status (SES). In the US National Health and Nutrition Examination Survey (US NHANES), models included US population and study design weights to account for the complex survey design. Hazard ratios were adjusted for age, sex, marital status (US NHANES only), self-reported race, acculturation, study center (UK Biobank only), body mass index, and prevalent comorbidities (including history of hypertension, diabetes, CVD, cancer, chronic bronchitis, emphysema, or chronic obstructive pulmonary disease). Only those free from CVD at baseline were included in the analysis for incident CVD. Multiplicative interaction was evaluated using hazard ratios for the product term between the healthy lifestyle score (0 or 1 point v 3 or 4 points) and SES (low v high), and the multiplicative interaction was statistically significant when its confidence interval did not include 1. Additive interaction was evaluated using relative excess risk due to interaction (RERI) between the healthy lifestyle score (0 or 1 point v 3 or 4 points) and SES (low v high), and the additive interaction was statistically significant when its confidence interval did not include 0

Figure 2 shows the joint association of lifestyles and SES on the primary outcomes, and hazard ratios for individuals of low SES and no or one healthy lifestyle factor compared with those with high SES and three or four healthy lifestyle factors were 3.53 (3.01 to 4.14) for all cause mortality in US NHANES, and 2.65 (2.39 to 2.94) for all cause mortality, 2.65 (2.09 to 3.38) for CVD mortality, and 2.09 (1.78 to 2.46) for incident CVD in the UK Biobank. Results were not materially changed in all sensitivity analyses (supplementary table 10), and similar patterns were found when using individual socioeconomic factors in the analysis (supplementary fig 4), as well as when using the area level Townsend deprivation index in the UK Biobank (supplementary fig 2).

Fig 2

Joint associations of healthy lifestyle score and socioeconomic status with mortality and incident cardiovascular disease (CVD). In the US National Health and Nutrition Examination Survey (US NHANES), models included US population and study design weights to account for the complex survey design. Hazard ratios were adjusted for age, sex, marital status (US NHANES only), self-reported race, acculturation, study center (UK Biobank only), body mass index, and prevalent comorbidities (including history of hypertension, diabetes, CVD, cancer, chronic bronchitis, emphysema, or chronic obstructive pulmonary disease). Only those free from CVD at baseline were included in the analysis for incident CVD

Lifestyle and socioeconomic inequity in health among subpopulations

Supplementary tables 11 and 12 and supplementary figure 5 show results stratified by sex, self-reported race, and age group. The socioeconomic inequity in all cause mortality and the joint associations of lifestyles and SES with all cause mortality were stronger in men than in women, and in younger than older adults in both cohorts (P for interaction <0.03). The results were not substantially different between white and non-white people. The proportions of socioeconomic inequity in health mediated by lifestyles were all modest (all <20%; data not shown) and similar to those of the main analyses.

Discussion

In these two large US and UK cohorts, low SES was associated with higher risks of mortality and CVD, and 3.0% to 12.3% of the associations were mediated by lifestyle factors. In UK Biobank, significant interactions were found between lifestyle factors and SES on all primary outcomes, and the associations between lifestyle factors and health outcomes were stronger among those of low SES. The highest risks of mortality and CVD were seen in adults of low SES and with the least healthy lifestyles.

Comparison with other studies

Socioeconomic inequity in mortality has been widely discussed. A large multicohort study with 1.7 million participants from the US, Europe, and Australia found that low SES was associated with a 26% higher risk of mortality and 2.1 years of life lost between ages 40 and 85 years, and low SES might respectively contribute to 15.3% and 18.9% of deaths among women and men.1 Moreover, socioeconomic inequity in mortality has continuously widened in the US. From 2001 to 2014, longevity increased by 2.34 and 2.91 years, respectively, among the wealthiest 5% of US men and women, whereas only 0.32 and 0.04 years among the poorest 5% of US men and women.46 Similar trends were also observed in the UK, or when high education levels were compared with low education levels.23 Our analysis confirmed the socioeconomic disparity in mortality and extended the findings to CVD morbidity and mortality. Thus, exploring the possible methods to reduce socioeconomic inequity in health is urgently needed.

The current evidence indicates causal relations between SES and death,47 and SES could affect individuals’ access to multitudinous resources (eg, knowledge, wealth, power, prestige, and advantageous social connections) and protective factors (eg, healthy lifestyle and healthcare services). Many studies have investigated the contribution of health behaviors to socioeconomic inequity in health outcomes, including mortality and CVD. A systematic review of 31 studies6 reported that about 20% to 30% of the socioeconomic inequity in health outcomes were explained by lifestyle factors. However, substantial heterogeneity was reported, with a minimum of −59% to a maximum of 75%. Therefore, firm conclusions cannot be made, and there are several potential reasons why this is not possible. First, most studies investigated a single socioeconomic factor, and studies examining an overall individual level SES were limited. Although different socioeconomic factors might correlate with each other, they reflected different domains of SES or social class and should not be simply replaced by others. Second, most previous studies examined single or limited numbers of lifestyle factors, and only five studies considered all lifestyle factors (smoking, alcohol consumption, physical activity, and diet) in the models.4849505152 Third, the characteristics of study populations (eg, age, sex composition, race or ethnicity, regions, SES levels, health status), study design (cross sectional or longitudinal, and follow-up duration if a cohort study), data collection methods, and statistical methods (such as adjustment for covariates) varied widely.

Our study found that in US and UK adults only up to 12.3% of the association between SES and mortality was explained by lifestyle factors. The results are consistent with several other studies in various populations.535455 In the longitudinal analyses on 22 194 participants in the Moli-sani study, Italy, participants of poor SES in childhood (assessed by a score of three variables: housing tenure, access to hot water, and overcrowding in household) but an upward trajectory in both education attainment and material circumstances had lower risks of total and cause specific mortality, whereas health related behaviors explained less than 10% of the association.56 The low mediation proportion indicated that substantial reductions of the socioeconomic inequity in health could not be achieved through promoting healthy lifestyles alone, and other measures to tackle the social determinants of health are still needed.

In our study, we also confirmed that healthy lifestyles were associated with lower risks of mortality and incident CVD in the two cohorts, regardless of SES. In addition, significant interactions were observed in the UK study, and the protective associations of healthy lifestyles and health outcomes were stronger among those of low SES, which highlighted the necessity of lifestyle modification, especially among those of low SES who were more vulnerable to unhealthy lifestyles. This is consistent with a previous analysis in the UK Biobank study,20 which also found that combinations of unhealthy lifestyle factors were associated with disproportionate harm in deprived populations, as assessed by the Townsend deprivation index, an area level SES variable. However, we found no significant interaction between lifestyles and SES on total mortality in the US study, similar to an analysis of education attainment and lifestyles with CVD mortality in Japan.57 Another study in a generally low income population in the US even found a weaker association between lifestyles and mortality among men with relatively low incomes, but not among women.44 The exact reasons for the inconsistent findings were unclear, but might depend on the definition of SES and lifestyle factors as well as the population characteristics. More studies are still needed to understand the complex relations between lifestyle factors and SES on health.

We also compared the overall individual level SES variable and Townsend deprivation index in the UK Biobank and found that the associations of individual level SES with outcomes were stronger than those of area level SES, and similar patterns were observed for the joint associations of lifestyle factors and SES. Besides, effect sizes of individual level SES were not attenuated after adjusting for Townsend deprivation index. Accordingly, it is necessary to construct an overall individual level SES variable because postcode derived area level SES reflects different aspects and has several problems, such as inability to determine social causes of health, inability to distinguish individual differences, confusion with other environmental health determinants, unreliability when populations are heterogeneous or change quickly, and inapplicability to mobile communities.58

Strengths and limitations of this study

Major strengths of this study are the large sample size from two well established nationwide cohorts in the US and UK—the findings are generally consistent within the two cohorts except for the interaction between lifestyle factors and SES on health outcomes. The large sample size also allowed us to perform the joint and stratified analyses with sufficient statistical power. In addition, we constructed an overall SES variable and healthy lifestyle score to comprehensively evaluate the complex relations of lifestyle factors and SES with mortality and incident CVD. We also conducted a series of sensitivity analyses to show the robustness of the findings, and evaluated individual socioeconomic and lifestyle factors.

Nevertheless, we also acknowledge several limitations. First, information on socioeconomic level and lifestyle was mainly self-reported and was only measured once, thus measurement errors were inevitable. Besides, we could not capture the long term SES trajectories as well as lifestyle changes during adulthood. Future studies with repeated measurements are preferred. Second, the SES variable was constructed differently in the two cohorts. For example, health insurance scheme was included as a component in the US study but not in the UK study, and occupational information was not collected at baseline in the UK Biobank and thus we could only use employment status. Third, a lifestyle score derived from a sum of the number of healthy lifestyle factors assumed that all lifestyle factors had equal effects on health outcomes, which might not be true. Although we constructed a weighted lifestyle score in the sensitivity analysis and found similar results, the weighted score still cannot fully account for the complex interactions between lifestyle factors, and the weights were study specific. Fourth, the follow-up duration is relatively short (mean 8.8-11.2 years), and those who died during the study period might have had serious diseases at baseline. Both lifestyle behaviors and SES could be influenced by disease status. Although our main analysis of adjusting comorbidities at baseline and sensitivity analysis of excluding those with major chronic diseases at baseline generated robust results, the possibility of reverse causation and residual confounding (many other diseases were not measured or considered) cannot be fully eliminated. Fifth, those excluded from the analysis because of missing covariates were more likely to be of lower SES; therefore, the socioeconomic inequity in health outcomes might be underestimated in our study. Nevertheless, the results remained similar after imputing missing covariates. Sixth, owing to the nature of post hoc subgroup analyses, sample size in each subgroup was not calculated before data collection. Especially, the number of participants and events might be insufficient among the non-white subgroup in the UK Biobank, and the results should be cautiously interpreted. Finally, although we controlled for key personal characteristics and comorbidities, residual confounding was still possible and causal inference cannot be made because of the nature of observational studies.

Conclusions

Based on two large nationwide US and UK cohorts, low SES was found to be significantly associated with higher risks of mortality and incident CVD, and the associations were modestly mediated by lifestyle factors. Therefore, promoting healthy lifestyles alone might not substantially reduce the socioeconomic inequity in health without other social determinants of health being considered. The finding argues for government policies to tackle upstream social and environmental determinants of health.59 Nevertheless, individuals with disadvantaged SES and unhealthy lifestyles had the highest risks of mortality and incident CVD, which highlights the importance of lifestyle modification in reducing disease burden for all people, especially those of low SES in the UK.

What is already known on this topic

  • Disadvantaged socioeconomic status (SES) and unhealthy lifestyles have been associated with higher risks of mortality and incident cardiovascular disease (CVD)

  • Studies found that individual lifestyle factors might mediate the associations between single socioeconomic factors and health; however, the results are not consistent, and to what extent lifestyle factors mediate the associations of overall SES with mortality and incident CVD remains unclear

  • Little is known about the interaction and joint associations of lifestyles and SES with mortality and incident CVD

What this study adds

  • In two nationwide cohort studies in US and UK adults, those of low SES had higher risks of mortality and CVD, and overall lifestyle only explained 3.0% to 12.3% of the excess risks

  • Significant interactions were found between lifestyle factors and SES on mortality and incident CVD in UK adults, and the associations between healthy lifestyles and outcomes were stronger among those of low SES

  • Compared with those of high SES and the healthiest lifestyle, those of low SES and the least healthy lifestyle had 2.09-fold to 3.53-fold risks of mortality and incident CVD

This One Thing Wards Off “Deadly” Prostate Cancer, New Study Finds | Eat This Not That – Eat This, Not That

Following a healthy lifestyle—such as eating well and doing regular exercise—might reduce the chances of developing fatal prostate cancer in men who are genetically predisposed to it, a new study suggests. Read on—and to ensure your health and the health of others, don’t miss these Signs Your Illness is Actually Coronavirus in Disguise.

Following a healthy lifestyle can reduce your risk, new study shows

Researchers from Brigham and Women’s Hospital and Harvard T. H. Chan School of Public Health in Boston looked at the genetic data of nearly 10,500 men—2,100 who developed prostate cancer over a median follow-up period of 18 years, and almost 240 whose prostate cancer proved lethal over a median follow-up of 22 years.

The study divided the participants into four equal groups. Men with the highest genetic risk were 5.4 times more likely to develop prostate cancer, and 3.5 times more likely to die of it, than men with the lowest genetic risk. 

Researchers found that by following a healthy lifestyle, men at the highest genetic risk of fatal prostate cancer could slash their risk in half: High-risk men who had a healthy lifestyle when the study began had a lifetime lethal prostate cancer incidence of 3%, compared to 6% for high-risk men with the least healthy lifestyle, and 3% for all participants in the study.

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Men at risk benefit from screening, diet

The findings were presented last week during the annual meeting of the American Association for Cancer Research (AACR). “The excess genetic risk of lethal prostate cancer could be offset by adhering to a healthy lifestyle,” said study co-lead author Anna Plym. “Our findings add to current evidence suggesting that men with a high genetic risk may benefit from a targeted prostate cancer screening program, aiming at detecting a potentially lethal prostate cancer while it is still curable.”

Genetics are believed to account for 58% of prostate cancer risk. According to the American Cancer Society, other risk factors include age (it’s more common in men after age 50, with 60% of cases found after age 65) and race or ethnicity (African-American and Caribbean men have a greater risk). Potential risk factors such as diet, weight, chemical exposures, and sexually transmitted infections, are less clear. 

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What are the symptoms of prostate cancer?

The Centers for Disease Control and Prevention says that 13 out of 100 American men will develop prostate cancer during their lifetime. Symptoms of prostate cancer include difficulty or pain while urinating, frequent urination, blood in the urine or semen, painful ejaculation, or pain in the back, hips or pelvis that doesn’t go away. And to get through this pandemic at your healthiest, don’t miss these 35 Places You’re Most Likely to Catch COVID.

Healthy Lifestyle May Offset Risk of Lethal Prostate Cancer – Cancer Health Treatment News

Men who had a high genetic risk of developing prostate cancer were less likely to develop a lethal form of the disease if they maintained a healthy lifestyle, according to results presented during Week 1 of the virtual AACR Annual Meeting 2021, held April 10-15.

Prostate cancer is the most common non-skin cancer detected in men, and the second leading cause of cancer deaths in men, after lung cancer. Genetic factors account for approximately 58 percent of the variability in prostate cancer risk, explained one of the study’s lead authors, Anna Plym, PhD, a postdoctoral research fellow at Brigham and Women’s Hospital and Harvard T. H. Chan School of Public Health.

In this study, Plym and colleagues sought to evaluate whether increased genetic risk of prostate cancer could be offset by following a healthy lifestyle. Using a validated polygenic risk score for overall prostate cancer, the researchers quantified the genetic risk of prostate cancer in 10,443 men in the Health Professionals Follow-up Study for whom genotype data was available. They applied a validated lifestyle score for lethal prostate cancer which encompassed healthy weight, vigorous physical activity, not smoking, and high consumption of tomatoes, fatty fish, and reduced intake of processed meat.

In a median follow-up period of 18 years for overall prostate cancer and 22 years for lethal prostate cancer, the researchers identified 2,111 overall prostate cancer cases and 238 lethal prostate cancer cases. The study showed that men in the highest risk quartile according to their polygenic risk score were 5.4 times more likely to develop prostate cancer and 3.5 times more likely to develop lethal prostate cancer than those in the lowest risk quartile.

The researchers then measured the effect of adhering to a healthy lifestyle, and found that among men in the highest-risk quartile, those with the highest healthy lifestyle scores had about half the risk of developing lethal prostate cancer compared with those with the least healthy lifestyle. In this high-risk group, having a healthy lifestyle at the time of study entry was associated with a lifetime cumulative lethal prostate cancer incidence of 3 percent, compared with 6 percent for high-risk men having the least healthy lifestyle and 3 percent for the study population as a whole.

“The decreased risk of aggressive disease in those with a favorable lifestyle may suggest that the excess genetic risk of lethal prostate cancer could be offset by adhering to a healthy lifestyle,” Plym said.

Adhering to a healthy lifestyle was not associated with a decreased risk of overall prostate cancer, nor did it affect men in the lower genetic risk quartiles. Plym said further research is necessary to determine why the benefit was limited to lethal prostate cancer risk in men with the highest genetic risk; one possible explanation is that the genetic variants that contribute to a high polygenic risk score are also the variants with the strongest interaction with lifestyle factors. 

The study adds to a wide body of cancer prevention research that shows the benefit of a healthy lifestyle, including not smoking, maintaining a healthy weight, getting regular exercise, and eating a healthy diet.

Plym added that the results of this study underscore the importance of surveillance for those with a genetic predisposition to develop prostate cancer.

“Our findings add to current evidence suggesting that men with a high genetic risk may benefit from a targeted prostate cancer screening program, aiming at detecting a potentially lethal prostate cancer while it is still curable,” Plym said.

Plym noted that the study is observational, and therefore the association between healthy lifestyles and prostate cancer may not be a causal link.

This study was funded by the DiNovi Family Foundation, the National Cancer Institute at the National Institutes of Health, the William Casey Foundation, the Swedish Society for Medical Research, and the Prostate Cancer Foundation. Plym declares no conflicts of interest.

This news release was originally published on April 10, 2021, by the American Institute for Cancer Research. It is republished with permission.


AACR: Healthy Lifestyle May Counter High Genetic Risk for Lethal Prostate Cancer – HealthDay News

MONDAY, April 12, 2021 (HealthDay News) — Genetic factors are associated with an increased risk for overall and lethal prostate cancer, and adherence to a healthy lifestyle can reduce the risk for lethal disease among men in the highest genetic risk quartile, according to a study presented during Week 1 of the annual meeting of the American Association for Cancer Research, held virtually from April 10 to 15.

Anna Plym, Ph.D., from Brigham and Women’s Hospital in Boston, and colleagues used a validated polygenic risk score (PRS) for overall prostate cancer to quantify the genetic risk for prostate cancer in 10,443 men in the Health Professionals Follow-up Study. A validated lifestyle score was applied for lethal prostate cancer, and the incidence of overall and lethal prostate cancer was examined during follow-up.

During median follow-ups of 18 and 22 years, the researchers identified 2,111 prostate cancer and 238 lethal prostate cancer events, respectively. According to risk stratification with the PRS, men in the highest versus the lowest genetic risk quartile had an increased risk for overall prostate cancer and lethal prostate cancer (hazard ratios, 5.39 and 3.53, respectively). Adherence to a healthy lifestyle versus the least healthy lifestyle was significantly associated with a reduced risk for lethal prostate cancer among men in the highest genetic risk quartile (hazard ratio, 0.54). There was no association noted for adherence to a healthy lifestyle with a decreased risk for overall prostate cancer.

“The decreased risk of aggressive disease in those with a favorable lifestyle may suggest that the excess genetic risk of lethal prostate cancer could be offset by adhering to a healthy lifestyle,” Plym said in a statement.

Press Release

More Information

Healthy lifestyle may help men with high genetic risk avoid lethal prostate cancer – Urology Times

Maintaining a healthy lifestyle lowered the likelihood of developing metastatic disease or dying of prostate cancer among men with high genetic risk, according to findings shared during the 2021 American Association for Cancer Research (AACR) Virtual Annual Meeting.1

The research also showed, however, that maintaining a healthy lifestyle was not associated with a lower risk of overall prostate cancer among patients in any of the 4 genetic risk categories defined by the study.

“In our study, a healthy lifestyle did not attenuate genetic risk of overall prostate cancer. However, a healthy lifestyle did attenuate the genetic risk of lethal disease in men at highest genetic risk,” one of the study’s lead authors, Anna Plym, PhD, a postdoctoral research fellow at Brigham and Women’s Hospital and Harvard T. H. Chan School of Public Health, said when presenting the results during the AACR meeting.

“While further studies are needed, this suggests that modifiable factors can mitigate the consequences of having a genetic susceptibility to prostate cancer,” added Plym.

The study included 10,443 men with available genotype data from the Health Professionals Follow-up Study, a prospective cohort study that accrues data from participating healthcare professionals. The investigators quantified the genetic risk of prostate cancer in these men using a validated polygenic risk score (PRS) for overall prostate cancer. The researchers then applied a validated lifestyle score for lethal prostate cancer. Elements factored into the score included healthy weight, vigorous physical activity, not smoking, reduced intake of processed meat, and high consumption of tomatoes and fatty fish.

The investigators assessed the incidence of overall prostate cancer and lethal prostate cancer (metastatic disease or prostate cancer-specific death). Men were followed from the date of DNA collection (1993-1994 or 2005-2006) until prostate cancer event or death.

“To account for the genotype sampling strategy within the Health Professionals Follow-up Study, in which not all recruited men were genotyped, we applied an inverse probability weighted Cox regression model, adjusting for [several] factors, including [age, year of inclusion, genetic ancestry, PSA screening, other cancers, diabetes, medication use, and total energy intake,” said Plym.

Using multivariable Cox proportional hazards models, the investigators estimated the overall and lethal prostate cancer risk by joint categories of a time-varying lifestyle score and genetic risk (PRS quartiles). The investigators used both inverse probability weighted (IPW) and unweighted models for their analysis, and estimated lifetime cumulative incidence using regression standardization.

At a median follow-up of 18 years, there were 2111 prostate cancer events; at a median follow-up of 22 years there were 238 lethal prostate cancer events.

The risk of overall prostate cancer was 5.4 times higher in men whose PRS score placed them in the highest genetic risk quartile versus those in the lowest genetic risk quartile (HRipw, 5.39; 95% CI, 4.59-6.33). The risk of lethal prostate cancer was 3.5 times higher in the highest versus the lowest genetic risk quartile (HRipw, 3.53, 95% CI, 2.34-5.32) compared with men in the lowest genetic risk quartile.

Maintaining a healthy lifestyle was significantly associated with a reduced risk of developing lethal prostate cancer compared with men living the least healthy lifestyle (HRipw, 0.54; 95% CI, 0.31- 0.94). In contrast, there was no link between maintaining a healthy lifestyle and a reduced risk of overall prostate cancer (HRipw, 1.01; 95% CI, 0.84-1.22).

Also of note, among men maintaining a healthy lifestyle at study entry who had the highest genetic risk, there was a 3% lifetime cumulative occurrence of lethal prostate cancer. This was half of the 6% lifetime cumulative incidence for men with the least healthy lifestyle. It is also comparable to the 3% population average.

In a statement included in a press release made available during the AACR meeting, Plym stated, “Our findings add to current evidence suggesting that men with a high genetic risk may benefit from a targeted prostate cancer screening program, aiming at detecting a potentially lethal prostate cancer while it is still curable.”2

Commenting on the results during the AACR meeting, moderator Charles Swanton MBPhD, FRCP, FMedSci, FRS, FAACR, Royal Society Napier Professor, The Francis Crick Institute and UCL Cancer Institute, Cancer Evolution and Genome Instability Lab, London, England, said, “Healthy lifestyle did not associate with prostate cancer risk overall, but was associated with lethal prostate disease in those with the highest PRS risk. So, the question is, why did a healthy lifestyle only protect those in the highest PRS category? And so I think we need future validation in larger cohorts using similar thresholds and a biological mechanism that might explain an interaction between the healthy lifestyle and a highest genetic risk and the risk of lethal prostate cancer.”

References

1. Plym A, Zhang Y, Stopsack K, et al. Can the genetic risk of prostate cancer be attenuated by a healthy lifestyle? Presented at: 2021 AACR Virtual Annual Meeting Week 1; April 10-15, 2021. Abstract 822.

2. Healthy Lifestyle May Offset Risk of Lethal Prostate Cancer in Men With High Genetic Risk. Published online April 10, 2021. Accessed April 10, 2021.

Colorado Spirit offers healthy lifestyle tips for resiliency this spring – by Hannah Harn – The Ark Valley Voice

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As spring rolls into the Rockies, the warm weather is accompanied by pandemic recovery. Vaccine distribution continues to expand, with those age 16 and up now eligible for COVID-19 vaccination across the state. 

Courtesy of Solvista Health and the Colorado Spirit Program.

Solvista Health’s Colorado Spirit program is continuing to provide counseling and other support services to individuals, families, agencies, and businesses as they navigate the pandemic. Colorado Spirit’s team can help businesses and their employees balance their work and personal life, adjust to pandemic-related changes, and new norms in the workplace. The team is also assisting at multiple vaccination sites in Chaffee, Custer, Fremont, and Lake Counties to support local agencies. 

Colorado Spirit offers a number of services to those in need, from self-care resources and tips to free counseling and support. Their online tool, MyStrength, offers resources that help users handle stress and anxiety, recharge their mood, and engage with their goals. 

As communities recover from the COVID-19 pandemic mentally as well as physically, Colorado Spirit and Solvista are focused on resilience, setting four starting steps: 

  • Build connections and relationships with others: Prioritize spending time with friends and family, or consider joining a group with whom you share beliefs, interests, or purpose. 
  • Establish healthy physical and mental habits: Keeping active is a good way to improve mental and physical health, so try setting aside 30 minutes each day to move. Make sure your diet is consistent and balanced, including protein, healthy carbs, fruits, vegetables, and lots of water. Practice staying in the present by making time to put aside your phone and other distractions. Focus on your thoughts and feelings without judging yourself and consider trying journaling, meditation, breathing exercises, or prayer to establish a sense of self-awareness.
  • Avoid negative outlets: Focus on establishing healthy habits and connections that support coping and growth through difficult periods. While alcohol, drugs, and other substances may be tempting, they don’t support healthy navigation through hardships.
  • Set goals: Set reachable goals that give you something to work on each day, even if they’re small steps, to get closer to your goal. 

Community members can visit Solvista Health’s Facebook page to watch two recent programs centered on resilience and healthy habits. Solvista Health also offers a Mental Health First Aid course to introduce participants to risk factors and warning signs of mental health issues.

Those interested should call to talk with a counselor or schedule a virtual presentation. For more information or to connect with the Colorado Spirit Team, visit their website, https://solvistahealth.org/colorado-spirit/, or call 719-275-2351.