Top Nutritionists Answer Your Diet Questions

admin
Posted in Healthy lifestyle

As you make your way past 50 years of age, you might notice your jeans getting tighter, and the scale tipping in the wrong direction – even if you haven’t changed a thing about your diet or lifestyle.

You can thank nature for that. With age, particularly around age 50-60, your metabolism slows down, and you start to lose muscle mass as a result. This all starts a bad snowball effect of burning fewer calories, even though you haven’t changed anything about your exercise routine.

When you burn fewer calories, you have to eat less, and when you don’t account for that shift, you start to gain weight out of the blue.

We’ve spoken to a few nutritionists, and we have answers to your pressing questions about healthy eating after 60.

What foods should you eat?

It’s pretty obvious what types of foods you should avoid, because we’ve been hearing it for decades. Don’t eat processed food, and try to stay away from sugar.

But what foods should you be focusing your attention on, particularly as you start to age?

Miriam on staying healthy after 60
Miriam Amselem

Miriam Amselem, a Holistic Nutritionist, recommends 6 foods for healthy eating over 60, all which provide a unique benefit, especially benefits that help with aging.

  1. Eggs
  2. Fish, such as salmon
  3. Oat bran oatmeal
  4. Low-fat dairy foods
  5. Cinnamon
  6. Blueberries

Eggs are full of zinc, B-12, and protein, and they keep you feeling full for longer. Fish, especially salmon, is high in Omega 3, which helps concentration and protects the brain from dementia.

The oat bran oatmeal is loaded with fiber and wards off heart disease, and low-fat dairy foods are full of calcium that nourishes your bones and protects against osteoporosis.

Cinnamon can be added to that oatmeal, and it helps reduce blood sugar and blood pressure. Blueberries are loaded with antioxidants and may reduce the risk of dementia.

It’s also important to get plenty of calcium, vitamin D, and magnesium, so Miriam recommends taking daily supplements.

29 Healthy Foods and Snacks Under 100 Calories

Jill on healthy eating over 60
Jill McKay

Jill McKay, certified personal trainer and creator of Narrow Road Fitness has actually created a list of 29 healthy foods and snacks under 100 calories, so when you’re in need of a pick-me-up, consider one of the quick, easy items on this list.

1. Almonds

One almond is about 8-9 calories. A small handful will be about 100 calories, and the healthy fats in the almond help you feel full and sustained.

2. Dark chocolate chips or cocoa nibs

Dark chocolate has been shown to help with brain and heart health. Jill notes that it can also help with mood and energy. Chocolate is also rich in antioxidants, but be careful to avoid chocolate with added sugar. One tablespoon will run you about 70 calories.

3. Banana and peanut butter

A small banana is about 90 calories. If you like peanut butter, Jill suggests having half of a banana with a half teaspoon of peanut butter. It’s delicious and nutritious!

4. Beef jerky

While beef jerky is an excellent source of protein, it does have a high amount of sodium. Jill says, “It’s a great snack in a pinch, especially if you’re exercising, sweating, or need to replenish your salt intake.”

One large piece is about 75-85 calories.

5. Roasted chickpeas

“These are my go-to snack when I want an alternative to popcorn,” Jill says.

Just drain a can of chickpeas, also called garbanzo beans, and pat them dry. Sprinkle seasoning on them and roast in the oven or a toaster until they’re crispy, which takes about 20 minutes.

A fourth cup of this healthy snack is about 75 calories.

6. Frozen yogurt

Love sweets, but want to stay within your calorie goals? Go for frozen yogurt.

A 2-ounce scoop is just under 100 calories.

7. Vegetable soup

Vegetable soup as a healthy snack for people over 60

One can of vegetable soup is about 80 calories, but Jill advises that you keep an eye on the sodium content.

If you need a quick lunch, pick up a can from the grocery store, and look for a label that says “with water added.”

8. Sweet potato

A small sweet potato, baked or even microwaved, is about 100 calories. “Avoid the butter,” Jill says, “and season with your favorite spices.”

You’d be surprised – microwaving your sweet potato will have it ready to eat in no time.

9. Quinoa

Quinoa, pronounced keen-wah, is filled with protein and fiber, which is exactly what we need when we start losing our muscle mass with age.

Spices are your friend, as quinoa can be a bit flavorless by itself. Cooking the quinoa in chicken or vegetable broth instead of water can also elevate the flavor. A third cup is about 90 calories.

10. Sushi

A great on-the-go snack, if you like it, is sushi. One piece is about 45 calories, making it a healthy and quick snack for your midday munchies.

11. Pistachios

About 25 dry roasted, salted pistachios (in the shell) are about 100 calories. A perfect way to get your fats and feel full when you need it.

12. Energy balls

Energy balls good snack for those over age 60

“These taste like cookie dough,” says Jill, who advises these as a snack if you’re able to only eat one!

They’re made of dates, oatmeal, chia seeds, flax meal, or some combination of them.

You can find recipes for these online, and one energy ball is roughly 100 calories. These – you guessed it – give you that spike of energy you need throughout the day.

13. Dill pickles

Though high in salt, pickles are extremely low in calories, making it a perfect snack when you just need something to chew on.

“Believe it or not, 30 dill pickles are roughly 90 calories. I don’t recommend eating 30 dill pickles though,” Jill laughs.

14. Kale chips

Though you can find kale chips in the grocery store, Jill suggests you make them at home to save money (and have fresh kale chips of course!).

Roast the kale leaves in your oven with your favorite seasoning. If you season them yourself, you can control the salt content, which can get a bit out of hand when you purchase the pre-made stuff.

One cup of kale chips is about 60 calories, making it the perfect healthful alternative to potato chips.

15. Jicama with salsa

It’s as simple as it sounds. One cup of sliced jicama with some salsa for dipping is roughly 50 calories.

16. Cocktail shrimp in hot sauce

About a dozen shrimp is roughly 80-90 calories, making it a great way to get some protein without ruining your calorie goals.

17. Egg muffins

A quick, easy recipe for a breakfast snack that’s grab & go is 1 scrambled egg, spinach, and 1 Tbsp of cheese. Bake them ahead of time in muffin tins, and they’re ready to go.

One muffin is about 90 calories.

18. Stuffed mini bell peppers

Six to eight mini bell peppers stuffed with ½ cup of hummus makes for a colorful, healthy, and delicious snack. In total, this meal is about 75 calories.

19. Tuna lettuce wrap

Some dijon mustard, a pack of chunk light tuna in water, and some Bibb lettuce will give you a nice lunch snack for only 90 calories.

20. Ricotta-stuffed pita

Use half of a whole grain pita pocket and fill it with ½ oz of part skim ricotta cheese. It’s a great snack that gives you fiber and protein for only 100 calories.

21. Caprese salad

Caprese salad for healthy eating over 60

Tomato, fresh basil, balsamic vinegar, and an ounce of feta cheese makes a really healthy snack for about 100 calories. And it tastes delicious!

22. Cucumber with cream cheese

One cup of sliced cucumber and an ounce of cream cheese is quite possibly the easiest snack to make. (And it’s only 100 calories.)

23. Crackers with avocado

Two tablespoons of mashed avocado with 4 whole-grain saltine crackers is about 100 calories. Super simple, and very tasty.

24. Cheddar cheese

If you’re the type of person who can snack on cheese all day, consider ¾ cup of sharp cheddar cheese as a midday snack. It’s only about 90 calories.

25. Broccoli with ranch dip

One cup of fresh broccoli with 3 Tbsp of ranch dip is about 100 calories, and it also fits in some much-needed veggies to your diet.

26. Oatmeal raisin cookie

That sweet tooth still bothering you? One small, homemade oatmeal raisin cookie is about 100 calories. Go ahead. We won’t tell.

27. Dried cherries

Three tablespoons of dried, tart cherries is about 75 calories, and they’re as simple as grabbing and going.

28. Dried figs

Dried figs are also a yummy snack that require no preparation. Two medium dried figs are about 75 calories.

29. Sugar-free gum

When you know you’re not hungry, but you just need something to chew on, go for a stick of sugar-free gum. “It’s only 5 calories,” says Jill.

Eyeball Your Plate

Dr Barry Sears creator of Zone diet on healthy eating after 60
Dr. Barry Sears

If you don’t have time to plan out or really focus on what’s for dinner, Dr. Barry Sears, the creator of the Zone diet, suggests the following: “Try for 1/3 your plate consisting of low-fat protein about the size of the palm of your hand, the other 2/3 of the plate consisting of non-starchy vegetables. Have fruit for dessert.”

That way, you can mix and match what you have for dinner, but you’re keeping a consistently healthy ratio of nutrition on your plate.

Healthy Eating After 60 Dinner Ideas

For dinner, salmon is a fantastic choice for its protein content along with the Omega 3s. Grilled chicken is also a great meat option. For men, you want to aim for 6-7 ounces of meat, while women should aim for 4-5 ounces.

Salmon dinner example for healthy meals over age 60

Pairing sweet potato, brown rice, or quinoa with your meat makes for a great side, which gives you your carbs.

And don’t forget about the veggies! Miriam says, “Get as many fresh greens as possible. For example, spinach, kale, romaine lettuces, spring mixes. You can put some lemon juice and olive oil on there, and it’s super nutritious.”

And don’t worry, if you need some kind of sauce with your meat, Miriam has some healthy alternatives to the prepackaged stuff. “You can cook salmon with some olive oil, garlic, lemon, and sundried tomato. It goes so beautifully with salmon, and it’s not as dry anymore.”

You can also make your own tomato sauce to add to the chicken. Sauteing mushrooms and adding that on top of the meat is also a delicious way to add flavor and moisture to your food.

If you’re rushed and don’t have much time, Miriam suggests low-sodium soy sauce.

What about butter?

And in case you were wondering, butter may not be all that bad for you when it’s eaten in moderation.

Miriam explains, “Butter is 100x better than margarine. I wouldn’t recommend using butter throughout the day, but up to a teaspoon of butter per day isn’t unhealthy. The key to everything is to know the portion.”

Is healthy eating different when you’re nearing age 60?

When you’re past the age of 60, the concepts of healthy eating don’t suddenly change, but the importance and focus does.

Eating healthily now can drastically change how the remainder of your years will progress – and how you’ll feel.

Miriam says that most people worry about getting cancer, but in reality, heart disease and diabetes should be more terrifying. “We have an obesity epidemic in our country. Heart disease is the No. 1 killer, and Type II diabetes is the second.”

It’s more important than ever to make sure that proper eating and nutrition is a top priority in your life.

Meal example for healthy eating after age 60

Maintaining muscle mass is more difficult as you age, and most nutritionists will advise seniors over the age of 60 to focus on 3 things:

  1. Get more protein into your diet
  2. Eat more fiber
  3. Focus on a healthy gut

Jill advises 20 grams of protein per meal along with 4-5 grams of fiber per meal. “There is a lot of research pointing to the importance of a healthy gut biome. Probiotics are good, but many probiotics are killed off by stomach acids before they reach the intestines. Fiber makes it deep into the intestines and feeds the healthy bacteria that live there.”

If meat is an issue, there are other protein-dense options, such as protein powders that are plant-based. “Talk to your doctor for recommendations,” Jill says.

Dr. Barry Sears says, “Non-starchy vegetables and fruits help with improved gut health, and a slight increase in your protein intake can help maintain muscle mass.”

Focusing so closely on your nutrition sounds nice, but what if you’re so busy that you don’t have time to prepare and cook healthy meals?

How do you eat healthily if you don’t have time to cook?

Staying healthy after 60 is hard enough, but finding time to cook can be a huge challenge!

Miriam suggests quick snacks that hit all the major food groups, such as an apple with some almond butter, Greek yogurt with a banana, or trail mix that has your essential vitamins and minerals.

Jill also suggests easy, healthy options if you’re short on time. Foods such as tuna fish, hard boiled eggs, salsa, black beans, and pre-cut fruit and veggies with hummus are nutritious, and they’re easy to eat on the go.

You can also refer back to her list of 29 quick, healthy foods and snacks if you want to pack a lunch in the morning that requires little to no effort or time.

Dr. Barry Sears recommends something pretty simple: the crockpot. “A crockpot is an easy way to make several meals at one time,” he says. You save a lot of time, and sometimes, crockpot meals are the tastiest!

We personally love this shredded chicken taco recipe from Tasty.

What should you eat if you’re eating or dining out?

Eating out can feel like a huge mystery – what on the menu is “safe” to eat?

Food menu can I eat healthy if I eat out

Jill suggests that you don’t get too worked up about it. “Eating out is wonderful. Keep in mind portions are usually too large. Ask for a to-go box with your meal and pack half of it away before you start to eat.”

Miriam also doesn’t see eating out as a scary thing – she explains, “Almost all restaurants have healthy food items to choose from like fish, sweet potatoes, fruit, and so on.”

More restaurants are also adding “healthier” menu options, which you can often find in a section near the back. These meals tend to be lower in calories and higher in healthful foods.

Dr. Barry Sears advises that you replace any bread or grains with extra vegetables – and for dessert, replace the chocolate cake with fresh fruit.

How do you know what your ideal macro or calorie intake should be?

Finally, the most confusing topic of all – we hear tons of different theories and suggestions from all over the place.

Some experts advise you to completely disregard calories and instead focus on your macros. Macros, or macronutrients, are what make up the actual calorie content of food. So, the three main categories of macros are carbs, fats, and proteins.

That brings in even more confusion – should I have more fat than carbs? Should I eat more protein than anything else? What’s a good balance?

While there is no one method that’s backed by all nutritionists, the concept of calories in versus calories out seems to be the one method that most experts can agree on.

“I personally am not a big fan of counting macronutrients,” says Jill. “There’s no real science that supports the benefits of more protein or more fat as being healthier than the other. The ketogenic fad is fading because it is not sustainable and most people do not truly get into ketosis. Aim for a well-balanced diet with plenty of vegetables is still key.”

For those who aren’t sure, ketosis is achieved when you eat more fat than protein, and you keep carbs to a very bare minimum.

In Miriam’s opinion, it’s all about keeping track of calories and making sure that the food you’re eating is generally healthy. “All calories are not created equal,” she says. “You can have a snickers bar or you can have a ton of broccoli. Those calories are not equal.”

It’s also important to note that the way you feel is extremely different if you’re eating mostly healthy foods instead of processed foods. Your energy levels will be higher, and you’ll avoid headaches and even disease if you’re focusing your calories on nutritious foods.

How many calories a day should a 60-year-old woman or man have?

One of the simplest ways a 60-year-old woman or man can find out how many calories they should have is to multiply their weight in kilograms by 29.

You can also use one of the many free apps available today to track your food and determine your ideal calorie intake. (We recommend MyFitnessPal, though there are a lot to choose from.) These online calculators factor in age, height, weight and activity level, which will give you the most accurate estimate.

My Fitness Pal app can help you track your calories

As a general rule of thumb, Jill says, “Always talk to your doctor, but generally speaking, adult women should not consume below 1200 to 1500 calories per day. Men should not go below 1500 to 1800 calories per day.”

Is there truly an accurate way to know how many calories I should eat?

If you really want to know how many calories you burn per day, you can go to a specialist and have a test done. One woman who wishes to remain anonymous says that she had a lot of weight to lose. She went to Physician’s Choice located in Forsyth, IL for their weight loss program, which is medically monitored.

“They hooked me up to this breathing apparatus. I don’t really know how it worked, but after about 20 minutes, it gave me information on my calorie usage at rest.”

The test showed that she should eat about 1650 calories per day. She knew if she wanted to lose weight, she’d need to eat less than that, but if she ate more than 1650 calories per day, she’d gain weight.

If you’re interested in this, we recommend giving Physician’s Choice a call or contacting your doctor.

Did you like this article? Check out “7 Ways to Prevent Heart Disease: Lifestyle and Diet Recommendations.”

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

admin
Posted in Healthy lifestyle

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

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*

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

“>Fig 1

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

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

10 superfoods to boost a healthy diet

admin
Posted in Healthy lifestyle

No single food — not even a superfood — can offer all the nutrition, health benefits, and energy we need to nourish ourselves. The 2015–2020 US Dietary Guidelines recommend healthy eating patterns, “combining healthy choices from across all food groups — while paying attention to calorie limits.”

Over the years, research has shown that healthy dietary patterns can reduce risk of high blood pressure, heart disease, diabetes, and certain cancers. Dietary patterns such as the DASH (Dietary Approaches to Stop Hypertension) diet and the Mediterranean diet, which are mostly plant-based, have demonstrated significant health benefits and reduction of chronic disease.

However, there are a few foods that can be singled out for special recognition. These “superfoods” offer some very important nutrients that can power-pack your meals and snacks, and further enhance a healthy eating pattern.

Superfoods list

Berries. High in fiber, berries are naturally sweet, and their rich colors mean they are high in antioxidants and disease-fighting nutrients.

How to include them: When berries are not in season, it is just as healthy to buy them frozen. Add to yogurt, cereals, and smoothies, or eat plain for a snack.

Fish. Fish can be a good source of protein and omega-3 fatty acids, which help prevent heart disease.

How to include it: Buy fresh, frozen, or canned fish. Fish with the highest omega-3 content are salmon, tuna steaks, mackerel, herring, trout, anchovies, and sardines.

Leafy greens. Dark, leafy greens are a good source of vitamin A, vitamin C, and calcium, as well as several phytochemicals (chemicals made by plants that have a positive effect on your health). They also add fiber into the diet.

How to include them: Try varieties such as spinach, swiss chard, kale, collard greens, or mustard greens. Throw them into salads or sauté them in a little olive oil. You can also add greens to soups and stews.

Nuts. Hazelnuts, walnuts, almonds, pecans — nuts are a good source of plant protein. They also contain monounsaturated fats, which may be a factor in reducing the risk of heart disease.

How to include them: Add a handful to oatmeal or yogurt or have as a snack. But remember they are calorically dense, so limit to a small handful. Try the various types of nut butters such as peanut (technically a legume), almond, or cashew. Nuts are also a great accompaniment to cooked veggies or salads.

Olive oil. Olive oil is a good source of vitamin E, polyphenols, and monounsaturated fatty acids, all which help reduce the risk of heart disease.

How to include it: Use in place of butter or margarine in pasta or rice dishes. Drizzle over vegetables, use as a dressing, or when sautéing.

Whole grains. A good source of both soluble and insoluble fiber, whole grains also contain several B vitamins, minerals, and phytonutrients. They have been shown to lower cholesterol and protect against heart disease and diabetes.

How to include them: Try having a bowl of oatmeal for breakfast. Substitute bulgur, quinoa, wheat berries, or brown rice for your usual baked potato. When buying breads at the supermarket, look to see that the first ingredient is “100% whole wheat flour.”

Yogurt. A good source of calcium and protein, yogurt also contains live cultures called probiotics. These “good bacteria” can protect the body from other, more harmful bacteria.

How to include it: Try eating more yogurt, but watch out for fruited or flavored yogurts, which contain a lot of added sugar. Buy plain yogurt and add your own fruit. Look for yogurts that have “live active cultures” such as LactobacillusL. acidophilusL. bulgaricus, and S. thermophilus. You can use yogurt in place of mayonnaise or sour cream in dips or sauces.

Cruciferous vegetables. These include broccoli, Brussels sprouts, cabbage, cauliflower, collard greens, kale, kohlrabi, mustard greens, radishes, and turnips. They are an excellent source of fiber, vitamins, and phytochemicals including indoles, thiocyanates, and nitriles, which may prevent against some types of cancer.

How to include them: Steam or stir-fry, adding healthy oils and herbs and seasonings for flavor. Try adding a frozen cruciferous vegetable medley to soups, casseroles, and pasta dishes.

Legumes. This broad category includes kidney, black, red, and garbanzo beans, as well as soybeans and peas. Legumes are an excellent source of fiber, folate, and plant-based protein. Studies show they can help reduce the risk of heart disease.

How to include them: Add to salads, soups, and casseroles. Make a chili or a bean- based spread such as hummus.

Tomatoes. These are high in vitamin C and lycopene, which has been shown to reduce the risk of prostate cancer.

How to include them: Try tomatoes in a salad or as a tomato sauce over your pasta. You can also put them in stews, soups, or chili. Lycopene becomes more available for your body to use when tomatoes are prepared and heated in a healthy fat such as olive oil.


Image: marylina/Getty Images

As a service to our readers, Harvard Health Publishing provides access to our library of archived content.
Please note the date of last review or update on all articles. No content on this site, regardless of date,
should ever be used as a substitute for direct medical advice from your doctor or other qualified clinician.

Commenting has been closed for this post.

Family Matters – Issue 96 – The Triple P-Positive Parenting Program

admin
Posted in Healthy lifestyle

Why parenting programs are so important

The quality of parenting that children receive has a major influence on their development, wellbeing and life opportunities (Repetti, Taylor, & Seeman, 2002; Griffin, Botvin, Scheier, Diaz, & Miller, 2000). Parenting programs that seek to improve parenting practices while simultaneously enhancing child development are vital to establishing a nurturing environment that acts to offset the development of behavioural and psychological problems and lays the foundation for children to contribute to a healthy and functional society (Biglan, Flay, Embry, & Sandler, 2012). There is now broad scientific and interdisciplinary consensus that behaviourally oriented active skills training programs that teach parents positive parenting and contingency management skills are effective. Such programs have transformed child and family-focused mental health support and prevention services (Comer, Chow, Chan, Cooper-Vince, & Wilson, 2013; McCart, Priester, Davies, & Azen, 2006; Menting, de Castro, & Matthys, 2013).

Parenting programs are potentially powerful tools in the prevention and treatment of a range of child social, emotional and behavioural problems including challenging behaviour in children with developmental disabilities (Tellegen & Sanders, 2014; Whittingham, Sanders, McKinlay, & Boyd, 2014), persistent feeding problems (Adamson, Morawska, & Sanders, 2013), anxiety disorders (Rapee, Kennedy, Ingram, Edwards, & Sweeney, 2010), recurrent pain syndromes (Sanders, Cleghorn, Shepherd, & Patrick, 1996), and childhood obesity (West, Sanders, Cleghorn, & Davies, 2010). Positive intervention effects on child and parent outcome measures have been reported across diverse cultures (e.g., Mejia, Calam, & Sanders, 2014; Turner, Richards, & Sanders, 2007), family types (e.g., Stallman & Sanders, 2007), stages of child development (e.g., Salari, Ralph, & Sanders, 2014), and delivery settings (e.g., Morawska et al., 2011). Positive intervention effects have been found to be maintained over time (e.g., Heinrichs, Kliem, & Hahlweg, 2014) without the need for further booster sessions.

Recent research has also demonstrated how different parenting styles and strategies influence various aspects of brain development. One study showed how harsh parenting reduces telomere length in the brain (a biomarker for chronic stress; Mitchell et al., 2014); while another by Luby et al. (2013) demonstrated how even in environments of poverty, altering the ways children are raised can help alleviate some of the adverse effects of disadvantage and promote healthy brain development in children.

Available evidence about maltreating parents suggests that parent training leads to improvements in parenting competence and parent behaviour (Holzer, Higgins, Bromfield, & Higgins, 2006; Sanders & Pidgeon, 2010). These changes in parenting practice reduce the risks of further abusive behaviour towards children, referrals to protective agencies and visits to hospital. Beyond younger children, potentially modifiable parenting and family risk factors can also be targeted to reduce the rates of emotional and behavioural problems in adolescents (Dekovic, Janssens, & Van As, 2003).

Although studies on parenting programs for parents of teenagers are less extensive compared to studies with younger children (Kazdin, 2005), programs have been demonstrated to improve parent-adolescent communication and reduce family conflict (Barkley, Edwards, Laneri, Fletcher, & Metevia, 2001; Chu et al., 2013; Dishion & Andrews, 1995), and reduce the risk of adolescents developing and maintaining substance abuse, delinquent behaviour and other externalising problems (Connell, Dishion, Yasui, & Kavanagh, 2007; Mason, Kosterman, Hawkins, Haggerty, & Spoth, 2003). Parents of adolescents who have participated in parenting programs have reported higher levels of confidence and use of more effective parenting strategies (Spoth, Redmond, & Shin, 1998).

Traditional approaches to parent training involve working with individual families or small groups of parents; although effective, such programs reach relatively few parents and consequently are unlikely to reduce rates of serious child-development problems related to inadequate parenting (Prinz & Sanders, 2007). In a household telephone survey of 4,010 Australian parents with a child under the age of 12 years, 75% of respondents who had a child with an emotional or behavioural problem had not participated in a parenting program (Sanders, Markie-Dadds, Rinaldis, Firman, & Baig, 2007). In addition, the worldwide rate of child behavioural problems is approximately 20% (World Health Organization [WHO], 2005). Thus, the benefits derived from participating in parenting programs are seldom fully realised across communities (Prinz & Sanders, 2007).

A paradigm shift in the way evidence-based parenting interventions are developed, trialled and disseminated is currently underway. Fundamentally, the shift is away from a focus on the individual parent or family unit, towards a community-wide, population-level focus. Biglan et al. (2012) described the shift as being towards a public health paradigm that valued the prevalence of nurturing environments and has, at its core, multiple efforts that act to prevent most mental, emotional and behavioural disorders.

In an Australian context, there are increasing calls from respected researchers and institutions for a public health approach to parenting support. For example, Mullan and Higgins (2014) used data from the Longitudinal Study of Australian Children to explore how different types of family environments influenced child outcomes. The study demonstrated that there is a clear link between family environments and children’s social and emotional wellbeing, and greater emphasis is required to provide families with evidence-based solutions. The authors concluded by calling for the adoption of a public health approach to promoting safe and supportive family environments. Providing all parents, regardless of their circumstances, with access to reliable, evidence-based, easy-to-access support, is critical to this shift in focus.

There are many examples of evidence-based parenting programs that are available around the world. One such program is The Incredible Years, developed by Carolyn Webster-Stratton and colleagues at the University of Washington’s Parenting Clinic (Webster-Stratton, 1998). A core focus of the program is the relationship among parents, children and teachers, and the treatment of behavioural problems through a collaborative home and school environment. Other interventions offer more intensive support, such as The Nurse-Family Partnership established by David Olds, which incorporates a home-visit component to assist first-time mothers and their babies from birth, through to the age of two (Olds, 2006).

To help professionals working in the field navigate the programs available, several groups have established “evidence-based parenting clearinghouses” that offer a summary of all the available parenting programs in a particular region or area. Examples of clearinghouses include The California Evidence-Based Clearinghouse (www.cebc4cw.org), and Blueprints for Violence Prevention (www.colorado.edu/cspv/blueprints/index.html). These sites typically sort programs via topic area (e.g., child welfare) and provide key information about each program including cost-effectiveness data, a rating of program evidence and how the program is delivered.

A recent analysis of parenting programs with Australian evaluation data identified 109 programs that targeted a combination of child, parent and family outcomes (Wade, Macvean, Falkiner, Devine & Mildon, 2012). The review used a Rapid Evaluation Assessment (REA) methodology that determined which parenting programs reporting parent, child or family outcomes had been evaluated in Australia and to identify the evidence for those programs. The effectiveness of each program was based on evidence from all papers found in the REA process. The evidence rating scale extended along a continuum from 1 to 6, where a 1 denoted Concerning Practice (“There is evidence of harm or risk to participants OR the overall weight of the evidence suggests a negative effect concerning practice on participants”), and 6 denoted Well Supported (“At least two RCTs have found the program to be significantly more effective than the comparison group”).

Of all programs included in the analysis, the Triple P-Positive Parenting Program and its sister program, Stepping Stones Triple P, were the only programs to receive the highest rating of “well supported”. The Triple P-Positive Parenting Program adopts a public health framework and, combined with the strength of evidence supporting it, provides an ideal case study for how to design and disseminate a system of parenting support within a public health framework in an Australian setting.

Triple P: Parenting as a public health priority

The Triple P-Positive Parenting program (Triple P) was developed by Sanders and colleagues at The University of Queensland. Triple P is built on the premise that there is no more important potentially modifiable target of preventive intervention and conceivably no more powerful means of enhancing the health and wellbeing of a community than evidence-based parenting practices. Triple P seeks to promote warm, responsive, consistent parenting that provides boundaries and contingent limits for children in a low-conflict family environment.

Triple P is built on the principle of proportionate universalism (Marmot, 2010) whereby it works as both an early intervention and prevention model to help create a society of healthy, happy, well-adjusted individuals with the skills and confidence they need to do well in life. To achieve this, Triple P targets the multiple factors that lay the foundation for lifelong prosperity for both the individual and broader community.

Triple P employs an iterative, consumer engagement model of program development to develop a range of evidence-based tailored variants and flexible delivery options (see Pickering & Sanders, 2013). The program targets children at five different developmental stages: infants, toddlers, pre-schoolers, primary schoolers and teenagers. Within each developmental period the reach of the intervention can vary from being very broad (targeting an entire population) to quite narrow (targeting only vulnerable high-risk children or parents). The five levels of Triple P incorporate universal media messages for all parents (Level 1), low intensity large group (Level 2), topic-specific parent discussion groups and individual programs (Level 3), intensive groups and individual programs (Level 4), and more intense offerings for high-risk or vulnerable parents (Level 5). Figure 1 and Table 1 describe Triple P’s multilevel system of parenting support geared towards normalising and destigmatising parental participation in parenting education programs.

Figure 1: The Triple P model of graded reach and intensity of parenting and family support services

Figure 1: The Triple P model of graded reach and intensity of parenting and family support services - as described in text

Note: Only program variants that have been trialled and are available for dissemination are included.

Source: Sanders, M. R. (2012)

Table 1: The Triple P system of parenting and family support
Level of intervention Intensity Program variant Target population Modes of delivery Intervention methods used
Level 1
Media and communication strategy on positive parenting Very low intensity Stay Positive All parents and members of the community interested in information about parenting to promote children’s development and prevent or manage common social, behavioural and emotional problems. Website to promote engagement. May also include television programming, public advertising, radio spots, newspaper and magazine editorials. Coordinated media and promotional campaign to raise awareness of parent issues, destigmatise and encourage participation in parenting programs. Involves electronic and print media.
Level 2
Brief parenting interventions Low intensity Selected Triple P
Selected Teen Triple P
Selected Stepping Stones Triple P
Parents interested in general parenting information and advice or with specific concerns about their child’s development or behaviour. Series of 90-minute stand-alone, large group parenting seminars; or one or two brief individual face-to-face or telephone consultations (up to 20 minutes). Parenting information promoting healthy development or advice for a specific developmental issue or minor behavioural problem (e.g., bedtime difficulty).
Level 3
Narrow focus parenting programs Low-moderate intensity Primary Care Triple P
Primary Care Teen Triple P
Primary Care Stepping Stones Triple P
Parents with specific concerns, as above, who require brief consultations and active skills training. Brief program (about 80 minutes) over three to four individual face-to-face or telephone sessions; or series of 2-hour stand-alone group sessions dealing with common topics (e.g., disobedience, hassle-free shopping). Combination of advice, rehearsal and self-evaluation to teach parents to manage discrete child problems.
Brief topic-specific parent discussion groups.
Level 4
Broad focus parenting programs Moderate-high intensity Standard Triple P
Group Triple P
Self-Directed Triple P
Standard Teen Triple P
Group Teen Triple P
Self-Directed Teen Triple P
Online Triple P
Parents wanting intensive training in positive parenting skills. Intensive program (about 10 hours) with delivery options including ten 60-minute individual sessions; or five 2-hour group sessions with three brief telephone or home visit sessions; or ten self-directed workbook modules (with or without telephone sessions); or eight interactive online modules. Broad focus sessions on improving parent-child interaction and the application of parenting skills to a broad range of targeted behaviours. Includes generalisation enhancement strategies.
Standard Stepping Stones Triple P
Group Stepping Stones Triple P
Self-Directed Stepping Stones Triple P
Parents of children with disabilities who have, or who are at risk of developing, behavioural or emotional problems. Targeted program involving ten 60-90 minute individual sessions or 2-hour group sessions. Parallel program with a focus on parenting children with disabilities.
Level 5
Intensive family interventions High intensity Enhanced Triple P Parents of children with behavioural problems and concurrent family dysfunction such as parental depression or stress, or conflict between partners. Adjunct individually tailored program with up to eight individual 60-minute sessions (may include home visits). Modules include practice sessions to enhance parenting; mood management and stress-coping skills; and partner support skills.
Pathways Triple P Parents at risk of maltreating their children. Targets anger management problems and other factors associated with abuse. Adjunct program with three 60-minute individual sessions or 2-hour group sessions. Modules include attribution retraining and anger management.
Lifestyle Triple P Parents of overweight or obese children. Targets healthy eating and increasing activity levels as well as general child behaviour. Intensive 14-session group program (including telephone consultations). Program focuses on nutrition, healthy lifestyle and general parenting strategies.
Family Transitions Triple P Parents going through separation or divorce. Intensive 12-session group program (including telephone consultations). Program focuses on coping skills, conflict management, general parenting strategies and developing a healthy co-parenting relationship.

The evidence supporting Triple P

Triple P is built on more than 35 years of program development and evaluation. A recent meta-analysis of Triple P (Sanders, Kirby, Tellegen, & Day, 2014) looked at 101 studies (including 62 randomised controlled trials) involving more than 16,000 families. Studies were included in the analyses if they reported a Triple P evaluation, reported child or parent outcomes, and provided sufficient original data. In these analyses, significant moderate effect sizes were identified for children’s social, emotional and behavioural outcomes (d = 0.473), parenting practices (d = 0.578), and parenting satisfaction and efficacy (d = 0.519). Significant small-to-moderate effects were also found for the distal outcomes of parental adjustment (d = 0.340) and parental relationship (d = 0.225). Significant positive effect sizes were found for each level of the Triple P system for children’s social, emotional and behavioural outcomes, although greater effect sizes were found for the more intense interventions (levels 4 and 5). These results support the effectiveness of light-touch interventions (levels 1, 2 and 3) as affecting key parenting outcomes independently. Significant moderate to large effects were also found for various delivery modalities, including group, individual, phone and online delivery.

Targeting entire communities can be effective in changing population-level indices of children’s social, emotional and behavioural problems. The approach, which involves targeting a geographically defined community and introducing the intervention model, has been carried out in several large-scale evaluations, several of which are in an Australian setting.

Sanders et al. (2008) implemented and evaluated the Every Family project. Every Family targeted parents of all 4-7 year old children in 20 geographical catchment areas in Australia. All parents in 10 geographic catchment areas could participate in various levels (depending on need and interest) of the multilevel Triple P suite of interventions. Interventions consisted of a media and communication strategy, parenting seminars, parenting groups and individually administered programs. These parents were then compared to a sample of parents from the other 10 care-as-usual geographical catchment areas. The evaluation of population-level outcomes was through a household survey of parents using a structured computer-assisted telephone interview. Following a 2-year intervention period, parents in the Triple P communities reported a greater reduction in behavioural and emotional problems in children, coercive parenting and parental depression and stress.

A further promising finding for Triple P in an Australian context emerged from a service-based evaluation of Triple P in New South Wales (Gaven & Schorer, 2013). The evaluation showed that children whose parents attended a Triple P course experienced significant behavioural and emotional improvements. There was a reduction in the number of children with clinically elevated scores on the Strengths and Difficulties Questionnaire (SDQ; Goodman & Goodman, 2009), with approximately 10% of children moving from the clinical to the non-clinical range after Triple P. Practitioner reports of their experience in using Triple P were overwhelmingly positive. The practitioners identified that Triple P had helped them to do their job better, enhanced the services they could offer clients and increased their confidence in helping families. The study found that approximately 90% of practitioners would recommend Triple P to their colleagues.

Prinz, Sanders, Shapiro, Whitaker, & Lutzker (2009) conducted a ground-breaking study linking Triple P to the reduction of child maltreatment at a population level. The study involved randomising 18 counties in South Carolina (USA) to either the Triple P system or to care-as-usual control. Following intervention, the Triple P counties had lower rates of founded cases of child maltreatment, hospitalisations and injuries due to maltreatment and out-of-home placements due to maltreatment. This was the first time a parenting intervention has shown positive population-level effects on child maltreatment in a randomised design, and provides great promise for the potential value of a population approach to parenting support. It also demonstrates to policy-makers the potential of positive parenting programs to enhance the lives of individuals within the community and also the fabric of the community more broadly.

Two additional recent studies investigated the effects of Triple P as a public-health intervention. Sarkadi, Sampaio, Kelly, & Feldman (2014) evaluated Triple P when delivered in preschools in the form of large group seminars (Level 2) along with brief individual primary-care consultations (Level 3). They reported significantly greater health gains (12%) than preschools without the program (3%).

Fives, Pursell, Heary, Gabhainn, and Canavan (2014) evaluated a population-level rollout of Triple P. Approximately 1,500 families were selected at random from two Irish Midlands counties and interviewed before and after the implementation of Triple P. A feature of this evaluation was that the interviewed families may or may not have directly accessed Triple P. Results from these interviews were then compared with results from interviews with 1,500 families selected at random from a large, similarly matched county where Triple P was not delivered. Counties were matched on several criteria including socio-economic status, urban or rural setting, previous availability of parenting programs in the area and proximity to the intervention counties.

Significant population-level impacts were recorded across a range of child outcomes including clinically elevated emotional symptoms (29.7% decrease), conduct problems (30% decrease), peer problems (14% decrease), hyperactivity (27% decrease) and prosocial behaviour such as helping others (35% increase). A number of significant gains were also made at the population level for parenting outcomes and strategies. In the Triple P counties, the number of parents reporting psychological distress decreased by 32%, significantly more parents reported a good relationship with their child and significantly more reported using appropriate parenting strategies. In the Triple P counties, significantly more parents reported they were likely to use appropriate discipline following the implementation of Triple P and less likely to use inappropriate discipline for anxious behaviour.

How a public health approach to parenting support works

The rationale behind a public health approach to parenting support is that there are differing levels of dysfunction and behavioural disturbance in children and adolescents, and parents have different needs and preferences regarding the type, intensity and mode of assistance they may require. The multilevel approach of Triple P adopts the position of flexible delivery, tailoring the intensity of intervention to suit need, and selecting the “minimally sufficient” intervention as a guiding principle to serving the needs of parents in order to maximise efficiency, contain costs and ensure that the program becomes widely available to parents in the community. The model avoids a one-size-fits-all approach by using evidence-based tailored variants and flexible delivery options (e.g., web, group, individual, over the phone, self-directed) targeting diverse groups of parents. The multi-disciplinary nature of the program involves the use of the existing professional workforce in the task of promoting competent parenting.

The public health approach emphasises the universal relevance of parenting assistance so that the larger community of parents embraces and supports parents being involved in parenting programs. From a population-level perspective, intervention developers must consider how their program fits with local needs and policy, and be mindful of the cost-effectiveness of their proposed solution. Improved parenting is a potentially powerful cornerstone of any prevention and early intervention strategy designed to promote positive outcomes for children and the community. However, an effective parenting support strategy needs to address a number of significant challenges within a robust implementation framework in order to succeed (Damschroder & Hagedorn, 2011).

Parenting interventions need to be delivered in a non-stigmatising way. Currently, parenting interventions are perceived by many vulnerable and at-risk parents as only being for inadequate, ignorant, failed or wayward parents. To be effective, a whole-of-population approach to parenting support has to emphasise the universal relevance of parenting assistance so that the larger community of parents embraces and supports parents being involved in parenting programs. An example of a non-stigmatised program is prenatal (birth) classes, which parents across a broad array of economic and cultural groups (and family configurations) find useful and do not perceive as stigmatising. Parenting programs must be considered equally as “routine” as undertaking prenatal classes and preparing for life as a parent.

Parenting support needs to be flexible with respect to delivery formats (e.g., group, individual, online) to meet the needs of parents in the child welfare system. Having every family receive an intensive intervention at a single location is not only cost ineffective but also unnecessary and undesirable from a family’s perspective. A careful consideration of the cost-effectiveness of interventions is essential when developing and disseminating programs at a population level.

Based on two economic analyses of the Triple P system, it is clear that a public health approach can be cost-effective. In one of the analyses (Aos et al., 2014), it was found that every $1 invested in the Triple P system (i.e., implementation of levels 1-5) yielded a $9 return in terms of reduced costs of children in the welfare system. In the other (Foster, Prinz, Sanders, & Shapiro, 2008), the infrastructure costs associated with implementing the Triple P system (i.e., levels 1-5) in the United States (Prinz et al., 2009) was $12 per participant, a cost estimated to be recoverable in a year by as little as a 10% reduction in the rate of abuse and neglect. Although these savings are striking, it is unclear who absorbs the cost of delivering parenting programs such as Triple P to the community.

Federal and state governments can choose to directly invest in these programs as part of their social welfare and mental health policies. However, in an environment of intense competition for public funds and resources, sustained investment in parenting programs is ultimately a matter of priority, which points to the importance of continued advocacy by researchers, agencies and consumers for government investment in prevention programs. Flexibility of program offering will also make the intervention useful for mandated services – parenting support for foster and adoptive parents and support for families within the child welfare system who are not involved with child protective services.

Investment in a population-wide rollout of Triple P would enable every Australian family to access quality evidence-based parenting information and support when needed, regardless of where they live. Under a population rollout, the vast majority of families would be able to access all the help they need through the multilevel suite of programs contained within the Triple P system media and communications campaigns, seminars, discussion groups and more intensive variants. The various programs that make up the Triple P system could be delivered by non-government organisations and community organisations as an additional tool under their existing Commonwealth and state funding and support programs. It could be promoted through non-stigmatising, universal access points such as day care services, kindergartens, playgroups, schools, churches and other community groups. Australian families would be free to choose whether they take advantage of the Triple P services.

Reliable measurement of population-level effects

There is a need for a national survey of parenting practices and child wellbeing outcomes in Australia using brief, reliable measures that are sensitive to change to document population-level program effects on children and parents. Such a survey would be valuable in documenting the impact of policy-level changes and in determining whether specific investments in programs achieved desired outcomes.

The survey would complement the Longitudinal Study of Australian Children by extending the scope to focus on measuring the targets of parenting interventions. Such data would enable community prevalence-rate data on positive and negative parenting practices and the community context of family functioning to be tracked over time. These epidemiological data would provide a valuable planning tool as well as allowing changes in parenting practices (improvements or deterioration) to be monitored over time.

From a policy perspective a regularly conducted comprehensive national parenting survey is consistent with goals of the National Framework for Protecting Australian Children and provides a direct means to describe the experiences of Australian parents in raising their children. The survey could be conducted every three years on a representative sample of Australian children aged 2-12 years and their parents. It could be designed to capture a range of child and parent variables that might be expected to change directly as a result of parenting interventions (e.g., parenting practices) or via changes in policy affecting families (e.g., financial stress) or be a predictor of change (e.g., socio-economic status, gender, family structure or changes in community context).

The development and implementation of a national parenting survey as an epidemiological tool to help evaluate the effects of policy-led changes in services to parents and families is essential. Such an instrument will provide a means for parents to express their opinions about the challenges they face raising their children, the type of help parents would find useful and the value they attach to the help received via parenting programs and the forms of family support. Reliable and change-sensitive measurement of parenting and child behaviour is crucial to the fidelity of a public health approach to parenting support.

Conclusion

There is clear evidence that the early years of children’s lives shape their future, including their physical and mental health, learning capacity, social and emotional wellbeing and life opportunities. All aspects of adult human capital, from workforce skills to cooperative and lawful behaviour, build on capabilities developed during the childhood years. While all parents want the best for their child, many lack the tools to parent effectively.

To improve uptake of programs, a public health approach to parenting support is required. The Triple P system represents a transformational approach to improving the health and wellbeing of the community at large. To our knowledge, the Triple P system is the only parenting program shown to improve parenting practices and child development outcomes when evaluated at a population level. However, strengthening parenting and family relationships across the entire population can only occur if developers work synergistically with practitioners, agencies and policy-makers. When parents are empowered with the tools for personal change they require to parent their children positively, the resulting benefits for children, parents and the community are immense.

References

  • Adamson, M., Morawska, A., & Sanders, M. R. (2013). Childhood feeding difficulties: A randomized controlled trial of a group-based parenting intervention. Journal of Developmental & Behavioral Pediatrics, 34(5), 293-302. doi:210.1097/DBP.1090b1013e3182961a3182938
  • Aos, S., Lee, S., Drake, E., Pennuci, A., Klima, T., Miller et al. (2014). Return on investment: Evidence-based options to improve statewide outcomes (Document No. 11-07-1201). Olympia, WA: Washington State Institute of Public Policy.
  • Barkley, R. A., Edwards, G., Laneri, M., Fletcher, K., & Metevia, L. (2001). The efficacy of problem-solving communication training alone, behavior management training alone, and their combination for parent-adolescent conflict in teenagers with ADHD and ODD. Journal of Consulting and Clinical Psychology, 69(6), 926-941.
  • Biglan, A., Flay, B. R., Embry, D. D., & Sandler, I. N. (2012). The critical role of nurturing environments for promoting human well-being. American Psychologist, 67, 257-271. doi:10.1037/a0026796
  • Chu, J. T. W., Farruggia, S. P., Sanders, M. R., & Ralph, A. (2012). Towards a public health approach to parenting programmes for parents of adolescents. Journal of Public Health, 34(S1), i41-i47. doi:10.1093/pubmed/fdr123
  • Comer, J. S., Chow, C., Chan, P., Cooper-Vince, C., & Wilson, L. A. S. (2013). Psychosocial treatment efficacy for disruptive behavior problems in young children: A meta-analytic examination. Journal of the American Academy of Child and Adolescent Psychiatry, 52, 26-36.
  • Connell, A. M., Dishion, T. J., Yasui, M., & Kavanagh, K. (2007). An adaptive approach to family intervention: Linking engagement in family-centered intervention to reductions in adolescent problem behavior. Journal of Consulting and Clinical Psychology, 75(4), 568-579.
  • Damschroder, L. J., & Hagedron, H. J. (2011). A guiding framework and approach for implmentation research in substance use disorders treatment. Psychology of Addictive Behaviors, 25(2), 194-205. doi:http://dx.doi.org/10.1037/a0022284
  • Dekovic, M., Janssens, J. M. A. M., & Van As, N. M. C. (2003). Family predictors of antisocial behavior in adolescence. Family Process, 42(2), 223-235.
  • Dishion, T. J., & Andrews, D. W. (1995). Preventing escalation in problem behaviors with high-risk young adolescents: Immediate and 1-year outcomes. Journal of Consulting and Clinical Psychology, 63(4), 538-548.
  • Fives, A., Pursell, L., Heary, C., Nic Gabhainn, S., & Canavan, J. (2014). Evaluation of the Triple P programme in Longford and Westmeath. Athlone, Ireland: Longford Westmeath Parenting Partnership.
  • Foster, E. M., Prinz, R. J., Sanders, M. R., & Shapiro, C. J. (2008). The costs of a public health infrastrucure for delivering parenting and family support. Children and Youth Services Review, 30, 493-501. doi:10.1016/j.childyouth.2007.11.2002
  • Gaven, S., & Schorer, J. (2013). From training to practice transformation: Implementing a public health parenting program. Family Matters, 93, 50-57.
  • Goodman, A., & Goodman, R. (2009). Strengths and difficulties questionnaire as a dimensional measure of child mental health. Journal of the American Academy of Child and Adolescent Psychiatry, 48, 400-403.
  • Griffin, K. W., Botvin, G. J., Scheier, L. M., Diaz, T., & Miller, N. L. (2000). Parenting practices as predictors of substance use, delinquency and aggression among urban minority youth: Moderating effects of family structure and gender. Psychology of Addictive Behaviors, 14(2), 174-184. doi:10.1037//0893-164X.14.2.174
  • Heinrichs, N., Kliem, S., & Hahlweg, K. (2014). Four-year follow-up of a randomized controlled trial of Triple P group for parent and child outcomes. Prevention Science, 15(2), 233-245. doi:10.1007/s11121-012-0358-2
  • Holzer, P., Higgins, J. R., Bromfield, L., & Higgins, D. (2006). The effectiveness of parent education and home visiting child maltreatment prevention programs. National Child Protection Clearinghouse, 24, 1-24.
  • Kazdin, A. E. (2005). Parent management training: Treatment for oppositional, aggressive, and antisocial behavior in children and adolescents. New York: Oxford University Press.
  • Luby, J., Belden, A., Botteron, K., Marrus, N., Harms, M. P., Babb, C., et al. (2013). The effects of poverty on childhood brain development: The mediating effect of caregiving and stressful life events. JAMA Pediatrics, 167(12), 1135-1142. doi:10.1001/jamapediatrics.2013.3139
  • Marmot, M. (2010). Fair society health lives. London: The Marmot Review.
  • Mason, W. A., Kosterman, R., Hawkins, J. D., Haggerty, K. P., & Spoth, R. L. (2003). Reducing adolescents’ growth in substance use and delinquency: Randomized trial effects of a parent-training prevention intervention. Prevention Science, 4(3), 203-212.
  • McCart, M. R., Priester, P. E., Davies, W. H., & Azen, R. (2006). Differential effectiveness of behavioral parent training and cognitive-behavioral therapy for antisocial youth: A meta-analysis. Journal of Abnormal Child Psychology, 34, 527-543.
  • Mejia, A., Calam, R., & Sanders, M. R. (2014). Examining delivery preferences and cultural relevance of an evidence-based parenting program in a low-resource setting of Central America: Approaching parents as consumers. Journal of Child and Family Studies, No Pagination Specified. doi:10.1007/s10826-014-9911-x
  • Menting, A. T. A, de Castro, B. A., & Matthys, W. (2013). Effectiveness of the Incredible Years parent training to modify disruptive and prosocial child behavior: A meta-analytic review. Clincial Psychology Review, 33, 901-913. doi:10.1016/j.cpr.2013.07.006
  • Mitchell, C., Hobcraftb, J., McLanahanc, S. S., Siegeld, S. R., Bergd, A., Brooks-Gunne, J., et al. (2014). Social disadvantage, genetic sensitivity, and children’s telomere length. Proceedings of the National Academy of Sciences, 111(16), 5944-5949. doi:10.1073/pnas.1404293111
  • Morawska, A., Sanders, M. R., Goadby, E., Headley, C., Hodge, L., McAuliffe, C., et al. (2011). Is the Triple P-positive parenting program acceptable to parents from culturally diverse backgrounds? Journal of Child and Family Studies, 20, 614-622. doi:10.1007/s10826-010-9436-x
  • Mullan, K., & Higgins, D. (2014). A safe and supportive family environment for children: Key components and links to child outcomes (DSS Occasional Paper No. 52.). Canberra: Department of Social Services.
  • Nowak, C., & Heinrichs, N. (2008). A comprehensive meta-analysis of Triple P-Positive Parenting Program using hierarchical linear modeling: Effectiveness and moderating variables. Clinical Child and Family Psychology Review, 11, 114-144. doi:10.1007/s10567-008-0033-0
  • Olds, D. L. (2006). The Nurse-Family Partnership: An evidence-based preventive intervention. Infant Mental Health Journal, 27, 5-25. doi:10.1002/imhj.20077
  • Pickering, J. A. & Sanders, M. R. (2013). Enhancing communities through the design and development of positive parenting interventions. Journal of Applied Research on Children: Informing Policy for Children at Risk, 4(2), Article 18. Retrieved from .
  • Prinz, R. J., Sanders, M. R., Shapiro, C. J., Whitaker, D. J., & Lutzker, J. R. (2009). Population-based prevention of child maltreatment: The U.S. Triple P system population trial. Prevention Science, 10, 1-12. doi:10.1007/s11121-009-0123-3
  • Prinz, R. J., & Sanders, M. R. (2007). Adopting a population-level approach to parenting and family support interventions. Clinical Psychology Review, 27, 739-749.
  • Rapee, R. M., Kennedy, S. J., Ingram, M., Edwards, S. L., & Sweeney, L. (2010). Altering the trajectory of anxiety in at-risk young children. American Journal of Psychiatry, 167, 1518-1525. doi:10.1176/appi.ajp.2010.09111619
  • Repetti, R. L., Taylor, S. E., & Seeman, T. E. (2002). Risky families: Family social environments and the mental and physical health of offspring. Psychological Bulletin, 128(2), 330-366. doi:10.1037//0033-2909.128.2.330
  • Salari, R., Ralph, A., & Sanders, M. R. (2014). An efficacy trial: Positive parenting program for parents of teenagers. Behaviour Change, 31(1), 34-52. doi:10.1017/bec.2013.31
  • Sanders, M. R. (2012). Development, evaluation, and multinational dissemination of the Triple P-Positive Parenting Program. Annual Review of Clinical Psychology, 8, 345-379. doi:10.1146/annurev-clinpsy-032511-143104
  • Sanders, M. R., & Pidgeon, A. (2011). The role of parenting programmes in the prevention of child maltreatment. Australian Psychologist, 46, 199-209. doi:10.1111/j.1742-9544.2010.00012.x
  • Sanders, M. R., Cleghorn, G. J., Shepherd, R. W., & Patrick, M. (1996). Predictors of clinical improvement in children with recurrent abdominal pain. Behavioural and Cognitive Psychotherapy, 24(1), 27-38.
  • Sanders, M. R., Markie-Dadds, C., Rinaldis, M., Firman, D., & Baig, N. (2007). Using household survey data to inform policy decisions regarding the delivery of evidenced-based parenting interventions. Child: Care, Health and Development, 33, 768-783.
  • Sanders, M. R., Ralph, A., Sofronoff, K., Gardiner, P., Thompson, R., Dwyer, S., & Bidwell, K. (2008). Every family: A population approach to reducing behavioral and emotional problems in children making the transition to school. Journal of Primary Prevention, 29, 197-222. doi:10.1007/s10935-008-0139-7
  • Sanders, M. R., Kirby, J. N., Tellegen, C. L., & Day, J. J. (2014). Towards a public health approach to parenting: A systemtic review and meta-analysis of the Triple P-Positive Parenting Program. Clinical Psychology Review, 32, 337-357. doi:10.1016/j.cpr.2014.04.003
  • Sarkadi, A., Sampaio, F., Kelly, M. P., & Feldman, I. (2014). Using a population health lens when evaluating public health interventions: Case example of a parenting program. Journal of Clinical Epidemiology, 67(7), 785-792. doi:10.1016/j.jclinepi.2013.12.012.
  • Spoth, R. L., Redmond, C., & Shin, C. (1998). Direct and indirect latent-variable parenting outcomes of two universal family-focused preventive interventions: Extending a public health-oriented research base. Journal of Consulting and Clinical Psychology, 66(2), 385-399.
  • Stallman, H. M., & Sanders, M. R. (2007). “Family Transitions Triple P”: The theoretical basis and development of a program for parents going through divorce. Journal of Divorce & Remarriage, 47(3-4), 133-153. doi:10.1300/J087v47n03_07
  • Tellegen, C. L. & Sanders, M. R. (2014). A randomized controlled trial evaluating a brief parenting program with children with autism spectrum disorders. Journal of Consulting and Clinical Psychology, 82(6), 1193-2000. doi:10.1037/a0037246
  • Turner, K. M. T., Richards, M., & Sanders, M. R. (2007). Randomised clinical trial of a group parent education programme for Australian indigenous families. Journal of Paediatrics and Child Health, 43, 429-437. doi:10.1111/j.1440-1754.2007.01053.x
  • Wade, C., Macvean, M., Falkiner, J., Devine, B., & Mildon, R. (2012). Evidence review: An analysis of the evidence for parenting interventions in Australia. Melbourne: Parenting Research Centre.
  • Webster-Stratton, C. (1998). Preventing conduct problems in Head Start children: Strengthening parenting competencies. Journal of Consulting and Clinical Psychology, 66, 715-730.
  • West, F., Sanders, M. R., Cleghorn, G. J., & Davies, P. S. W. (2010). Randomised clinical trial of a family-based lifestyle intervention for childhood obesity involving parents as the exclusive agents of change. Behaviour Research and Therapy, 48(12), 1170-1179. doi:10.1016/j.brat.2010.08.008
  • Whittingham, K., Sanders, M. R., McKinlay, L., & Boyd, R. N. (2014). Interventions to reduce behavioral problems in children with cerebral palsy: An RCT. Pediatrics. doi:10.1542/peds.2013-3620
  • Wilson, P., Rush, R., Hussey, S., Puckering, C., Sim, F., Allely, C. S., et al. (2012). How evidence-based is an ‘evidence-based parenting program’? A PRISMA systematic review and meta-analysis of Triple P. BMC Medicine, 10, 130. doi:10.1186/1741-7015-10-130
  • World Health Organization. (2005). Child and adolescent mental health policies and plans. Geneva, Switzerland: WHO.

John A. Pickering is Head of the Triple P Innovation Precinct, Parenting and Family Support Centre, and Professor Matthew R. Sanders is Professor of Clinical Psychology and Director of the Parenting and Family Support Centre, both at The University of Queensland.

Disclosure statement: The Triple P Positive Parenting Program is owned by The University of Queensland (UQ). The university, through its main technology transfer company UniQuest Pty Limited, has licensed Triple P International Pty Ltd to disseminate the program worldwide. Royalties stemming from this dissemination activity are distributed to the Parenting and Family Support Centre, School of Psychology, UQ; Faculty of Health and Behavioural Sciences; and contributory authors. Matthew Sanders is the founder and an author on various Triple P programs and a consultant to Triple P International. No author has any share or ownership in Triple P International Pty Ltd.

Carbohydrates: How carbs fit into a healthy diet

admin
Posted in Healthy lifestyle

Carbohydrates: How carbs fit into a healthy diet

Carbohydrates aren’t bad, but some may be healthier than others. See why carbs are important for your health and which ones to choose.

By Mayo Clinic Staff

Carbohydrates often get a bad rap, especially when it comes to weight gain. But carbohydrates aren’t all bad. Because of their numerous health benefits, carbohydrates have a rightful place in your diet. In fact, your body needs carbohydrates to function well.

But some carbohydrates might be better for you than others. Understand more about carbohydrates and how to choose healthy carbohydrates.

Understanding carbohydrates

Carbohydrates are a type of macronutrient found in many foods and beverages. Most carbohydrates occur naturally in plant-based foods, such as grains. Food manufacturers also add carbohydrates to processed foods in the form of starch or added sugar.

Common sources of naturally occurring carbohydrates include:

  • Fruits
  • Vegetables
  • Milk
  • Nuts
  • Grains
  • Seeds
  • Legumes

Types of carbohydrates

There are three main types of carbohydrates:

  • Sugar. Sugar is the simplest form of carbohydrate and occurs naturally in some foods, including fruits, vegetables, milk and milk products. Types of sugar include fruit sugar (fructose), table sugar (sucrose) and milk sugar (lactose).
  • Starch. Starch is a complex carbohydrate, meaning it is made of many sugar units bonded together. Starch occurs naturally in vegetables, grains, and cooked dry beans and peas.
  • Fiber. Fiber also is a complex carbohydrate. It occurs naturally in fruits, vegetables, whole grains, and cooked dry beans and peas.

More carbohydrate terms: Net carbs and glycemic index

Terms such as “low carb” or “net carbs” often appear on product labels. But the Food and Drug Administration doesn’t regulate these terms, so there’s no standard meaning. Typically “net carbs” is used to mean the amount of carbohydrates in a product excluding fiber, or excluding both fiber and sugar alcohols.

You probably have also heard talk about the glycemic index. The glycemic index classifies carbohydrate-containing foods according to their potential to raise your blood sugar level.

Weight-loss diets based on the glycemic index typically recommend limiting foods that are higher on the glycemic index. Foods with a relatively high glycemic index ranking include potatoes and white bread, and less healthy options such as snack foods and desserts that contain refined flours.

Many healthy foods, such as whole grains, legumes, vegetables, fruits and low-fat dairy products, are naturally lower on the glycemic index.

How many carbohydrates do you need?

The Dietary Guidelines for Americans recommends that carbohydrates make up 45 to 65 percent of your total daily calories.

So, if you get 2,000 calories a day, between 900 and 1,300 calories should be from carbohydrates. That translates to between 225 and 325 grams of carbohydrates a day.

You can find the carbohydrate content of packaged foods on the Nutrition Facts label. The label shows total carbohydrates — which includes starches, fiber, sugar alcohols, and naturally occurring and added sugars. The label might also list separately total fiber, soluble fiber and sugar.

Carbohydrates and your health

Despite their bad rap, carbohydrates are vital to your health for a number of reasons.

Providing energy

Carbohydrates are your body’s main fuel source. During digestion, sugars and starches are broken down into simple sugars. They’re then absorbed into your bloodstream, where they’re known as blood sugar (blood glucose).

From there, glucose enters your body’s cells with the help of insulin. Glucose is used by your body for energy, and fuels all of your activities — whether it’s going for a jog or simply breathing. Extra glucose is stored in your liver, muscles and other cells for later use, or is converted to fat.

Protecting against disease

Some evidence suggests that whole grains and dietary fiber from whole foods help reduce your risk of cardiovascular diseases. Fiber may also protect against obesity and type 2 diabetes. Fiber is also essential for optimal digestive health.

Controlling weight

Evidence shows that eating plenty of fruit, vegetables and whole grains can help you control your weight. Their bulk and fiber content aids weight control by helping you feel full on fewer calories. Contrary to what low-carb diets claim, very few studies show that a diet rich in healthy carbohydrates leads to weight gain or obesity.

Choose your carbohydrates wisely

Carbohydrates are an essential part of a healthy diet, and provide many important nutrients. Still, not all carbs are created equal.

Here’s how to make healthy carbohydrates work in a balanced diet:

  • Emphasize fiber-rich fruits and vegetables. Aim for whole fresh, frozen and canned fruits and vegetables without added sugar. Other options are fruit juices and dried fruits, which are concentrated sources of natural sugar and therefore have more calories. Whole fruits and vegetables also add fiber, water and bulk, which help you feel fuller on fewer calories.
  • Choose whole grains. Whole grains are better sources than refined grains of fiber and other important nutrients, such as B vitamins. Refined grains go through a process that strips out parts of the grain — along with some of the nutrients and fiber.
  • Stick to low-fat dairy products. Milk, cheese, yogurt and other dairy products are good sources of calcium and protein, plus many other vitamins and minerals. Consider the low-fat versions, to help limit calories and saturated fat. And beware of dairy products that have added sugar.
  • Eat more legumes. Legumes — which include beans, peas and lentils — are among the most versatile and nutritious foods available. They are typically low in fat and high in folate, potassium, iron and magnesium, and they contain beneficial fats and fiber. Legumes are a good source of protein and can be a healthy substitute for meat, which has more saturated fat and cholesterol.
  • Limit added sugars. Added sugar probably isn’t harmful in small amounts. But there’s no health advantage to consuming any amount of added sugar. The Dietary Guidelines for Americans recommends that less than 10 percent of calories you consume every day come from added sugar.

So choose your carbohydrates wisely. Limit foods with added sugars and refined grains, such as sugary drinks, desserts and candy, which are packed with calories but low in nutrition. Instead, go for fruits, vegetables and whole grains.

.

OLTD 512 – MS. THOMSON

admin
Posted in Healthy lifestyle
These sketchnotes were created in OLTD 512 during a week where we researched free resources and open education resources (OER). They were created using the Paper 53 App, one of the free resources I explored in detail. The content is an outline or overview of my unit design, also created in OLTD 512.
 
According to the Institute for the Study of Knowledge Management in Education, OER are in the public domain and “have been released under an intellectual property license that permits their free use and re-purposing by others”. Free resources are of course also free, but one major distinguishing factor is that free resources are not able to be freely modified, adapted or redistributed without permission (Institute for the Study of Knowledge Management in Education). Paper 53 is a free resource that is easy to use and fun. Although it doesn’t require great artistic ability, it does require a bit of practice. As a teacher I would use it to present overviews of courses, units, or lessons. It would also make your website more visually appealing if teaching online. As a student you could use it to create outlines for assignments, as I have done here. As our lessons shift from content-driven to process-driven, we are spending less time creating power points full of information, and more time providing platforms for students to create their own material. Part of this is learning about and understanding the resources available to students.
 
In David Wiley’s keynote speech on Open Education, he states that openness is not a technology problem, it’s a policy problem. The technology exists for education to be open, but policy prevents this. In our schools, tools used need to meet privacy policies, and if they don’t you need parent permission for students to use them. Finding good resources is already time consuming, and this adds the additional steps of first reading terms and conditions, and then asking for parent permission when necessary. Wiley also talks about the “daily divide” and how school differs greatly from a student’s daily life. The world is changing, but education is slow to keep up. Wiley mentions several ways the world is changing, including from being isolated to connected, tethered to mobile, consuming to creating, and closed to open.  As a result of this change, some learning theorists believe a new learning theory is necessary for online learning. George Siemens (2004) states that a new learning theory for the digital age is needed in order to develop resources for the networked world (As cited in Ally, 2008). Connectivism is a learning theory that encompasses global, connected learning (Ally, 2008). According to the theory of connectivism, students need to have effective research skills, the ability to learn and unlearn information and the ability to recognize invalid or old information (Ally, 2008).
 
OLTD Learning Outcomes:
Plan learning opportunities most suitable to particular learning environments.
Develop skills to optimize learning experiences.
Analyse resources for their purpose in engaging and supporting learning.
 
References:
 Ally, M. (2008). Foundations of education theory for online learning. In Theory and practice of online learning (1). Retrieved from http:www.aupress.ca/index.php/books/120146

Frequently Asked Questions” by Institute for the Study of Knowledge Management in Education. Licensed under CC BY 4.0 International License. It was adapted from “#GoOpen: OER for K-12 Educators” (www.tinyurl.com/GoOpen) by Doug Levin, also available under a CC BY license.

Wiley, D. (2009, May 6). TLT Symposium 2009: David Wiley’s keynote on Open Education. [Video file]. Retrieved from https://www.youtube.com/watch?v=VcRctjvIeyQ
 

Back to Top

All images are my own and represent my personal learning metaphor: learning is natural.

Valley Medical Center | Lifestyle Medicine Programs

admin
Posted in Healthy lifestyle

Evidence shows the best option for improving your current health and reducing your risk of future illness is a structured program of physical activity and nutrition change. Our customized Healthy Foundations program meets you where you are on your path to wellness and takes the guesswork out of improving your fitness and what you eat. With the help of expert healthcare providers including registered dietitians, certified nutritionists, physical therapists and exercise specialists, Pinnacle Medical Wellness and Valley Medical Center have teamed up to offer an intensive, 16 week lifestyle modification program to help you get strong, healthy and build positive lifestyle habits.

What is included in the Healthy Foundations program?

  •     1:1 Nutritional counseling
  •     Meal Planning
  •     Physical therapy evaluation, consultation and treatment
  •     Prescriptive exercise program with biometric measurements and SMART goal setting
  •     4 month Fitness Center membership at any of our Lifestyle Medicine locations 
  •     Grocery store tour and restaurant field trip
  •     Group support and education series

How long is the program?

   Healthy Foundations is a 16-week lifestyle modification program that addresses Food Education,  Lifestyle Modification & Goal Setting, Exercise as Medicine, and Psychology of Eating. 

How much does it cost?

   The price varies based in your insurance benefits / plan coverage. We also offer financial insurance, insurance subsidy and payment plans. Participants’ fee will be a minimum of $500 and can total up to $1500, which can be made in payments. 50% of the fee is due prior to the start date, with the remaining amount deducted with arrangements with the Healthy Foundations Coordinator. In addition, you will be responsible for any co-pays, co-insurance, and insurance deductibles, in addition to any out of pocket cost according to your insurance benefits. 

Who will I be working with? 

    A team composed of Dietitians, Physical Therapists, and Exercise Specialists will be helping you on your journey. Our Dietitians will coach you through the program with nutrition therapy, not only find what tools will best react with your body type or medical conditions, but they will also give you the tools and resources to help prepare you for success. Our Physical Therapists will help you identify imbalances in your body. As you increase your activity you avoid injury, and have a comprehensive understanding of your bodies mechanics. And lastly, our Exercise Specialists are the experts in movement. They will create exercise programs for you and adapt it to your progress. 

 

 

To Register:

 Phone: 425.690.3520 

Fax: 425.690.9520

Email: healthy_foundations@valleymed.org

 

 

 

 

    We believe exercise is medicine, in the same way you would allow your doctor to prescribe you medication, allow our experts in exercise to prescribe the right types of exercises. With the correct dosage and frequency, exercise can have a tremendous impact on the body. Lifestyle 365 has been created to provide its members with programming that takes the guesswork out of fitness. No longer will you go to the gym unsure of where to start. Time is precious and we ensure our members receive a quality thought out plan, to achieve tremendous fitness results based on your goals.  

     Members will receive full access to
their ES through the MyWellness cloud, with monthly biometric assessments and
progress evaluations. In addition to the exercise prescription, Lifestyle 365
members will receive access to our monthly nutrition workshop in which members can ask
questions about diet and nutrition and receive advice from our Registered
Dietician at no additional fee.

    Lifestyle 365© includes the Technogym® SmartKey, which delivers your fitness program with recommended durations and speed, along with strength training volumes and intensities. Your assigned Exercise Specialist will provide you with extensive training on the SmartKey and the Technogym® equipment included in your workout. 

What assessments are involved?

      Lifestyle 365© begins with screening and assessment which involve baseline measurements of: Height & Weight, Body Composition, Blood Pressure, 7-site Circumference Measurement, Aerobic Capacity as well as Strength and Flexibility. SMART Goals are also assessed, ensuring that you are continually progressing toward and meeting your goals.

 

How do I get started? 

    Sign up at the front desk of the Valley Lifestyle Medicine & Fitness Center, located on the first floor of the Talbot Professional Center (4011 Talbot Road South Renton, WA 98055) and tell the wellness coordinator that you want to sign up for Lifestyle 365©!  

For more information visit… Lifestyle 365

Healthy Foundations Banner 2