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Health Insurers Performance 2012-2014 OBAMACARE

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Over a third of the total sample (53 insurers, groups 1 and 2) were profitable in 2014; these insurers accounted for 41 percent of the total members in this sample (data not shown). The remainder were either unprofitable both years or moved from profit to loss. Medical claims, rather than administrative costs, were the main driver of the negative financial experiences.

Reinsurance

Most of insurers’ underestimated claims in 2014 were offset by $7.9 billion in reinsurance payments for high-cost patients from the federal government. The reinsurance program helps insurers transition to the new market rules, using federal funds collected through an earmarked fee on all health insurance, included self-funded plans, to pay a large portion of high-cost claims incurred in the individual market.

Insurers that turned profitable in 2014 (group 1) saw their medical costs decrease by almost 12 percentage points as a percentage of premium—that is, their MLR decreased. Coupled with a 1.4 point decline in the mean administrative cost ratio, these changes resulted in a substantial (13.2-point) rise in their overall profit margin to 7.6 percent, from a loss of 5.6 percent. In contrast, insurers that reported losses (groups 3 and 4) had substantially higher mean MLRs. Although they managed to reduce their administrative costs significantly, their MLR increased even more, producing a mean loss greater than 10 percent.

 CONCLUSION

 By subsidizing coverage, establishing insurance exchanges, and making insurance available to people with preexisting conditions, the ACA’s reforms changed market conditions in ways that insurers had difficulty predicting, at least initially. In 2014, the ACA’s reinsurance program offset much of insurers’ underestimated medical claims in the individual market. Also, despite overall losses in the individual market, the insurance industry as a whole earned modest operating profits (in addition to profits from investments).

 Only some insurers fared especially poorly. One-quarter of insurers underestimated medical claims in the individual market to a much greater extent than the rest. A fifth of insurers in the individual market substantially improved their financial performance between 2013 and 2014.

 All well-functioning markets have winners and losers, so it should be no surprise that some health insurers failed to succeed in the ACA’s reformed market, especially during the first year. As insurers gain greater experience with these new conditions, it can be expected that their actuarial precision will improve and that large differences in financial performance will diminish. Moreover, additional market stabilization can be expected as more previously insured people move out of grandfathered and transitional plans and into ACA-compliant coverage.

 However, improved financial performance will require increased premiums, especially as the ACA’s reinsurance component phases out, starting in 2017. This reinsurance has played a crucial role in helping insurers transition. Because this has taken longer than initially expected, policymakers should consider extending the ACA’s reinsurance program until the reformed market has matured.

 

What can I do to restore my lost ambition, energy, and enjoyment in life?

My answer to What can I do to restore my lost ambition, energy, and enjoyment in life?

Answer by Connie b. Dellobuono:

Motivation. What motivates you? Do you exercise and eat whole foods? Do you sleep well? Do you laugh easy? Do you find things around you as beautiful creation of the Creator?
Why do you what you are doing? Find a motivation. Volunteer and help others. Explore the world around you and find ways to participate in it.
Some people are motivated to work 3 jobs to send their children to college or help their parents or retire their mothers.

What can I do to restore my lost ambition, energy, and enjoyment in life?

Why is alcohol addictive?

stat alc

My answer to Why is alcohol addictive?

Answer by Connie b. Dellobuono:

Drug of abuse , alcohol, stress , and addiction
Neuroplasticity, the putative mechanism underlying learning and memory, is modified by drugs of abuse, alcohol and may contribute to the development of the eventual addicted state. Innovative treatments directly targeting these drug-induced changes in brain reward components and circuits may be efficacious in reducing drug use and relapse.
Nicotine promotes glutamatergic synaptic plasticity in dopaminergic (DA) neurons in the ventral tegmental area (VTA), which is thought to be an important mechanism underlying nicotine reward. However, it is unclear whether exposure of nicotine alone to VTA slice is sufficient to increase glutamatergic synaptic strength on DA neurons and which nicotinic acetylcholine receptor (nAChR) subtype mediates this effect. Here, we report that the incubation of rat VTA slices with 500 nM nicotine induces glutamatergic synaptic plasticity in DA neurons. We measure the ratio of AMPA and NMDA receptor-mediated currents (AMPA/NMDA) and compare these ratios between nicotine-treated and -untreated slices. Our results demonstrate that the incubation of VTA slices with 500 nM nicotine for 1 h (but not for 10 min) significantly increases the AMPA/NMDA ratio when compared with controls. Preincubation with 10 nM of the α7-nAChR antagonist, methyllycaconitine (MLA) but not 1 μM α4-containing nAChR antagonist, dihydro-β-erythroidine (DHβE) prevents nicotinic effect, suggesting that α7-nAChRs are mainly mediated this nicotinic effect. This finding is further supported by the disappearance of this nicotinic effect in nAChR α7 knockout (KO) mice. Furthermore, nicotine reduced paired-pulse ratio (PPR) of evoked excitatory postsynaptic potential (eEPSP) in the VTA slices prepared from wild-type (WT) mice but not α7 KO mice. Collectively, these findings suggest that exposure of smoking-relevant concentrations of nicotine to VTA slices is sufficient to increase glutamatergic synaptic strength on DA neurons and that α7-nAChRs likely mediate this nicotinic effect through increasing presynaptic release of glutamate. Synapse, 2011. © 2010 Wiley-Liss, Inc.
Alterations in neuronal activity can elicit long-lasting changes in the strength of synaptic transmission at excitatory synapses and, as a consequence, may underlie many forms of experience-dependent plasticity, including learning and memory. The best-characterized forms of such synaptic plasticity are the long-term depression (LTD) and long-term potentiation (LTP) observed at excitatory synapses in the CA1 region of the hippocampus. It is now well accepted that the trafficking of AMPA receptors to and away from the synaptic plasma membrane plays an essential role in both LTP and LTD, respectively.
In an ever-changing environment, animals must learn new behavioral strategies for the successful procurement of food, sex, and other needs. Synaptic plasticity within the mesolimbic system, a key reward circuit, affords an animal the ability to adapt and perform essential goal-directed behaviors. Ironically, drugs of abuse can also induce synaptic changes within the mesolimbic system, and such changes are hypothesized to promote deleterious drug-seeking behaviors in lieu of healthy, adaptive behaviors. In this review, we will discuss drug-induced neuroadaptations in excitatory transmission in the ventral tegmental area and the nucleus accumbens, two critical regions of the mesolimbic system, and the possible role of dopamine receptors in the development of these neuroadaptations. In particular, we will focus our discussion on recent studies showing changes in AMPA receptor function as a common molecular target of addictive drugs, and the possible behavioral consequences of such neuroadaptations.
The main characteristics of cocaine addiction are compulsive drug use despite adverse consequences and high rates of relapse during periods of abstinence. A current popular hypothesis is that compulsive cocaine use and cocaine relapse is due to drug-induced neuroadaptations in reward-related learning and memory processes, which cause hypersensitivity to cocaine-associated cues, impulsive decision making and abnormal habit-like learned behaviours that are insensitive to adverse consequences. Here, we review results from studies on the effect of cocaine exposure on selected signalling cascades, growth factors and physiological processes previously implicated in neuroplasticity underlying normal learning and memory. These include the extracellular signal-regulated kinase (ERK) signalling pathway, brain-derived neurotrophic factor (BDNF), glutamate transmission, and synaptic plasticity (primarily in the form of long-term potentiation and depression, LTP and LTD). We also discuss the degree to which these cocaine-induced neuroplasticity changes in the mesolimbic dopamine system mediate cocaine psychomotor sensitization and cocaine-seeking behaviours, as assessed in animal models of drug addiction. Finally, we speculate on how these factors may interact to initiate and sustain cocaine psychomotor sensitization and cocaine seeking.
Synaptic plasticity in the ventral tegmental area (VTA) is modulated by drugs of abuse and stress and is hypothesized to contribute to specific aspects of addiction.
Both excitatory and inhibitory synapses on dopamine neurons in the VTA are capable of undergoing long-term changes in synaptic strength. While the strengthening or weakening of excitatory synapses in the VTA has been widely examined, the role of inhibitory synaptic plasticity in brain reward circuitry is less established. Here, we investigated the effects of drugs of abuse, as well as acute stress, on long-term potentiation of GABAergic synapses onto VTA dopamine neurons (LTPGABA). Morphine (10 mg/kg i.p.) reduced the ability of inhibitory synapses in midbrain slices to express LTPGABA both at 2 and 24 h after drug exposure but not after 5 days. Cocaine (15 mg/kg i.p.) impaired LTPGABA 24 h after exposure, but not at 2 h. Nicotine (0.5 mg/kg i.p.) impaired LTPGABA 2 h after exposure, but not after 24 h. Furthermore, LTPGABA was completely blocked 24 h following brief exposure to a stressful stimulus, a forced swim task. Our data suggest that drugs of abuse and stress trigger a common modification to inhibitory plasticity, synergizing with their collective effect at excitatory synapses. Together, the net effect of addictive substances or stress is expected to increase excitability of VTA dopamine neurons, potentially contributing to the early stages of addiction.
What to eat to prevent drug and alcohol negative effects? Dietary Amino Acids
Hypothalamic orexin/hypocretin (orx/hcrt) neurons regulate energy balance, wakefulness, and reward; their loss produces narcolepsy and weight gain. Glucose can lower the activity of orx/hcrt cells, but whether other dietary macronutrients have similar effects is unclear. We show that orx/hcrt cells are stimulated by nutritionally relevant mixtures of amino acids (AAs), both in brain slice patch-clamp experiments, and in c-Fos expression assays following central or peripheral administration of AAs to mice in vivo. Physiological mixtures of AAs electrically excited orx/hcrt cells through a dual mechanism involving inhibition of KATP channels and activation of system-A amino acid transporters. Nonessential AAs were more potent in activating orx/hcrt cells than essential AAs. Moreover, the presence of physiological concentrations of AAs suppressed the glucose responses of orx/hcrt cells. These results suggest a new mechanism of hypothalamic integration of macronutrient signals and imply that orx/hcrt cells sense macronutrient balance, rather than net energy value, in extracellular fluid.
Nutritionally Relevant Mixes of Amino Acids Excite orx/hcrt Neurons In Situ
To test whether the activity of orx/hcrt cells is modulated by dietary amino acids (AAs), we first used a mixture of amino acids (“AA mix”; see Table S1 available online) based on microdialysis samples from the rat hypothalamus (Choi et al., 1999). Whole-cell patch-clamp recording showed that orx/hcrt cells depolarized and increased their firing frequency in response to the AA mix (Figure 1A; all statistics are given in the figure legends unless stated otherwise). The latency of response onset was 66 ± 5 s (n = 25). This response was unaffected by blockers of ionotropic glutamate, GABA, and glycine receptors (Figure 1B), or by blockade of spike-dependent synaptic transmission with tetrodotoxin (Figure 1C). We did not observe such AA responses in neighboring lateral hypothalamic GAD65 neurons (Figures 1D and 1F; see Experimental Procedures), or in cortical pyramidal cells (Figures 1E and 1F).
Highlights
► Brain orexin/hypocretin cells are stimulated by dietary amino acids (AAs) ► AA sensing involves K-ATP channels and system-A transporters ► Nonessential AAs stimulate orexin/hypocretin cells more than essential AAs ► AA presence prevents glucose from blocking orexin/hypocretin cells

Effects of Physiological Amino Acid Mixes on the Membrane Potential of orx/hcrt and Other Central Neurons

(A) Effect of “AA mix” (see Table S1) on orx/hcrt cells (n = 25). Membrane potential during AA application (−39.4 ± 0.8 mV) was higher than preapplication (−51.8 ± 0.6 mV, p < 0.0001) or postapplication (−51.0 ± 1.1 mV, p < 0.0001).

(B) Same with synaptic blockers (see Experimental Procedures, n = 5). Membrane potential during AA application (−40.1 ± 1.1 mV) was depolarized relative to preapplication (−50.4 ± 0.5 mV, p < 0.002) or postapplication (−48.0 ± 1.6 mV, p < 0.02).
(C) Same as A with tetrodotoxin (0.5 μM, n = 5). Membrane potential during AA application (−42.2 ± 1.4 mV) was higher than preapplication (−53.5 ± 0.8 mV, p < 0.002) or postapplication (−51.2 ± 1.0 mV, p < 0.001).

(D) Effect of “AA mix” on non-orx/hcrt lateral hypothalamic neurons expressing GAD65 (n = 7, see Experimental Procedures). Membrane potential during AA application (−46.6 ± 1.2 mV) was not different from preapplication (−48.8 ± 1.0 mV, p > 0.15) or postapplication (−47.5 ± 1.7 mV, p > 0.6).

(E) Effect of “AA mix” on neurons from secondary somatosensory cortex layer 2-4 (n = 7). Membrane potential during AA application (−49.1 ± 0.8 mV) was not different from preapplication (−49.6 ± 0.6 mV, p > 0.3) or postapplication (−48.8 ± 1.1 mV, p > 0.8).

(F) Depolarization (means ± SEM) caused by the AA mix in different conditions, evoked from the same baseline of −50 mV (∗∗∗ = p < 0.001; n.s. = p = 0.24).

(G) Left, effect of switching from “low AA mix” to “AA mix” (see Table S1) on orx/hcrt cells (n = 6, quantified in F). Right, dose-response (means ± SEM) of AA-induced depolarization. Total concentration of AA mix was changed while proportions of AAs were kept same as in “AA mix” in Table S1. EC50 value (see Experimental Procedures) = 438.2 μM (equivalent to 0.66-fold of “AA mix” in Table S1).

(H) Effects of AAs in cell-attached recording mode (left, frequency histogram; right, raw trace, n = 6). Firing rate was higher in AA (6.6 ± 0.5 Hz) than in low AA (3.0 ± 0.3 Hz, p < 0.001).

Effects of Individual Amino Acids

To explore whether orx/hcrt cells are more sensitive to particular AAs, we first examined their membrane current responses to individual AAs applied at high concentration (5 mM). In this voltage-clamp assay, nonessential AAs elicited large responses, with a relative potency order glycine > aspartate > cysteine > alanine > serine > asparagine > proline > glutamine, while essential AAs were much less effective (Figures 3A and 3B). Because leucine has been suggested previously to be sensed in the hypothalamus (Cota et al., 2006), we investigated its effect across a broad concentration range in comparison with alanine (Figure 3C). Across all concentrations tested, leucine (0.02–10 mM) did not induce any detectable membrane currents, whereas alanine dose-dependently stimulated currents with an EC50 of 3.19 mM (Figure 3C).

Source: http://www.sciencedirect.com/science/article/pii/S0896627311007823

Amino acid Alanine food sources: Good sources of alanine include. Animal sources: meat, seafood, caseinate, dairy products, eggs, fish, gelatin, lactalbumin. Vegetarian sources: beans, nuts, seeds, soy, whey, brewer’s yeast, brown rice, bran, corn, legumes, whole grains.

Note that per gram of protein, eggs and egg whites provide the highest levels of BCAAs. Eggs again are also marginally superior when it comes to leucine content. This should be of interest to you because leucine is the main driver of muscle protein synthesis.

Why is alcohol addictive?

How often do women die giving birth?

My answer to How often do women die giving birth?

Answer by Connie b. Dellobuono:

Where there is no medical care and in countries where there is war, famine and pestilence.
After the war, when laboring women cared for in the hospital beside dead bodies without using gloves (septicemia).
When young drug addicted women failed to get prenatal and proper medical care.
When infection sets in and was too late to get medical care.
When the laboring woman is on her 5th pregnancy with poor health condition and poor prenatal care.
When the fetus is not completely formed and complications arise during pregnancy and birth.
Medical error during C-section (anesthesia, surgery related)
During ectopic pregnancies, fetus formed outside the womb.
And many more cases in the developing and war torn countries where maternal mortality is high. See WHO health statistics.

How often do women die giving birth?

What is the best way to get high with the least damage to the body?

My answer to What is the best way to get high with the least damage to the body?

Answer by Connie b. Dellobuono:

Be in love. First dates. Chocolates. Successful endeavors. Solving a problem. Helping someone. Being adored by people. Completing a competition. Being massaged. Eating happy foods. Nature walks. Receiving a lump sum of money. Waking up and well rested. Dancing. And many more.

What is the best way to get high with the least damage to the body?

Medicare billing cost for chest pain per state

medicare cost for chest pain.JPG

Governing compiled average hospital costs for various treatments, ranking states by cost. The following states were found to have the highest average aggregate rankings, indicating the most expensive medical costs:

1. California
2. New Jersey
3. Nevada
4. Florida
5. Pennsylvania
6. Texas
7. Alaska
8. Colorado
9. Arizona
10. South Carolina

http://www.governing.com/gov-data/health/average-medical-hospital-costs-by-state-map.html

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Most expensive: cardiac surgery, brain hemorrhage, septicimea, kidney, GI, vascular-circulatory

Blood tests cost

Blood tests can measure cells, lipids, proteins, sugars, hormones, tumor markers and other blood components. They are used to diagnose and treat of many diseases including diabetes, high cholesterol, thyroid disease and cancer.Typical costs:
  • CostHelper readers with insurance report out-of-pocket costs of $283-$675 for blood tests, with an average of $432; total billed costs were $312-$1,200 (averaging $755), with the insurance either paying or discounting the total cost by $29-$525.
  • For patients covered by health insurance, out-of-pocket costs for blood work typically consist of a copay ranging from nothing to $30 or more, or coinsurance of 10%-50% or more; deductibles and out-of-pocket maximums will apply.
  • Blood tests are often covered by health insurance for preventive, diagnostic or treatment purposes, but coverage depends on the individual case and the terms of the health insurance plan.
  • CostHelper readers without health insurance report total costs of $700-$2,589, averaging $1,543. For patients not covered by health insurance, total costs can be $100-$3,000 or more, depending on the number and type of tests ordered; the cost of any doctor visits to order and interpret the tests; and whether the tests are done on an emergency basis.
  • Routine blood work done as part of an annual physical or a new patient exam can cost $100-$1,000 or more. Often ordered in connection with an annual physical, a complete blood count (CBC) test alone can cost $10-$150 or more.
  • Depending on the patient’s symptoms, doctors typically order multiple tests to check for a number of conditions; comprehensive panels of tests can cost $80-$1,500 or more, and combining several testing packages can bring total costs to $1,500-$2,700 or more.

Related articles: Antibody Test, PSA Test

What should be included:
  • Before any blood test, the patient typically will be given instructions to follow, such as fasting for a certain number of hours. The medical provider then draws blood and sends it to a laboratory for analysis. Results usually are provided to the patient and/or their doctor within a few days to a week.
  • The National Institutes of Health lists types of common blood tests[1] .

Additional costs:

  • Depending on the results, the doctor may recommend additional testing.

Discounts:

  • The U.S. Department of Health and Human Services offers a locator [2] for clinics providing services on an income-based sliding scale.
  • Many hospitals offer discounts of up to 50% for uninsured/self-paying patients. For example, St. Joseph Hospital[3] in Orange, CA discounts its billed charges by 45%.

Shopping for blood tests:

  • Patients with health insurance that requires them to use “in network” providers should check whether a specific lab is within the network; a doctor who works within an insurance plan might, without checking, refer patients to a lab that isn’t covered under that plan. Always double-check for insurance coverage before any blood work is done.
  • Blood tests can be done at the office of a primary care provider or specialist, in a clinic or in a hospital.
  • For patients who want anonymity or do not wish to go through a doctor, companies such as LabCorp[4] , Quest Diagnostics[5] and Health Testing Centers[6] offer laboratory testing direct to patients. However, it is important to seek the advice of a doctor for any health concerns.
Material on this page is for informational purposes only and should not be construed as medical advice. Always consult your physician or pharmacist regarding medications or medical procedures.

Your total costs for health care

When choosing a plan, it’s a good idea to think about your total health care costs, not just the bill (the “premium”) you pay to your insurance company every month.

Other amounts, sometimes called “out-of-pocket” costs, have a big impact on your total spending on health care – sometimes more than the premium itself.

Beyond your monthly premium: Deductible and out-of-pocket costs

  • Deductible: How much you have to spend for covered health services before your insurance company pays anything (except free preventive services)
  • Copayments and coinsurance: Payments you make each time you get a medical service after reaching your deductible
  • Out-of-pocket maximum: The most you have to spend for covered services in a year. After you reach this amount, the insurance company pays 100% for covered services.

How to estimate your total costs of care

In order to pick a plan based on your total costs of care, you’ll need to estimate the medical services you’ll use for the year ahead. Of course it’s impossible to predict the exact amount. So think about how much care you usually use, or are likely to use.

If you preview plans and prices before logging into HealthCare.gov, you can choose each family member’s expected medical use as low, medium, or high. When you view plans, you’ll see an estimate of your total costs — including monthly premiums and all out-of-pocket costs — based on your household’s expected use of care.

Your actual expenses will vary, but the estimate is useful for comparing plans’ total impact on your household budget. This will help you pick a plan — and a plan category — based on the total costs of care you expect, not just your monthly premium.

Total costs & “metal” categories

When you compare plans in the Marketplace, the plans appear in 4 “metal” categories: Bronze, Silver, Gold, and Platinum. The categories are based on how you and the health plan share the total costs of your care.

Generally speaking, categories with higher premiums (Gold, Platinum) pay more of your total costs of health care. Categories with lower premiums (Bronze, Silver) pay less of your total costs. (But see the exception about Silver plans below.)

So how do you find a category that works for you?

  • If you expect a lot of doctor visits or need regular prescriptions: You may want a Gold plan or Platinum plan. These plans generally have higher monthly premiums but pay more of your costs when you need care.
  • If you don’t expect to use regular medical services and don’t take regular prescriptions: You may want a Silver, Bronze, or Catastrophic plan. These plans cost you less per month, but pay less of your costs when you need care.
  • If you qualify to save on out-of-pocket costs: Silver plans may offer the best value. If you qualify for “cost-sharing reductions” based on your income, you can have a lower deductible and pay lower out-of-pocket costs when you get care — but only if you enroll in Silver plan.

Mobile application developers and health sales needed

Motherhealth is developing a Health Mobile Outpatient application and needs investing partners, doctors, developers and health sales (part time).

Goal: Reduce chronic health care costs, create mobile outpatient clinics, increase the number of connected patients globally, promote wellness, reduce health insurance costs, reward healthy population, empower health promotion and enlist all care providers as co-owners of this Health Mobile Outpatient application.

Email motherhealth@gmail.com

Developers must have the following skill set:

5+ years of Java development     

The right combination of experience in many of these technologies and a desire to master them all (most desirable listed first):

  • Modern Java frameworks (Spring Boot preferred)
  • Relational database design and query via both SQL and ORM
  • Proficiency in modern JavaScript frameworks (React preferred)
  • ElasticSearch or other document-oriented database
  • Microservice architecture, including REST API design
  • Asynchronous data pipelines using Kafka or similar modern messaging framework
  • AWS or other public cloud environment

150 min of moderate-intensity exercise per week

500 metabolic equivalents per week (MET/week)  or 150 min of moderate-intensity exercise per week reduces the occurrence of major cancers by 20%.

METs and MET-minutes

A well-known physiologic effect of physical activity is that it expends energy. A metabolic equivalent, or MET, is a unit useful for describing the energy expenditure of a specific activity. A MET is the ratio of the rate of energy expended during an activity to the rate of energy expended at rest. For example, 1 MET is the rate of energy expenditure while at rest. A 4 MET activity expends 4 times the energy used by the body at rest. If a person does a 4 MET activity for 30 minutes, he or she has done 4 x 30 = 120 MET-minutes (or 2.0 MET-hours) of physical activity. A person could also achieve 120 MET-minutes by doing an 8 MET activity for 15 minutes.

MET-Minutes and Health Benefits

A key finding of the Advisory Committee Report is that the health benefits of physical activity depend mainly on total weekly energy expenditure due to physical activity. In scientific terms, this range is 500 to 1,000 MET-minutes per week. A range is necessary because the amount of physical activity necessary to produce health benefits cannot yet be identified with a high degree of precision; this amount varies somewhat by the health benefit. For example, activity of 500 MET-minutes a week results in a substantial reduction in the risk of premature death, but activity of more than 500 MET-minutes a week is necessary to achieve a substantial reduction in the risk of breast cancer.

Dose Response

The Advisory Committee concluded that a dose-response relationship exists between physical activity and health benefits. A range of 500 to 1,000 MET-minutes of activity per week provides substantial benefit, and amounts of activity above this range have even more benefit. Amounts of activity below this range also have some benefit. The dose-response relationship continues even within the range of 500 to 1,000 MET-minutes, in that the health benefits of 1,000 MET-minutes per week are greater than those of 500 MET-minutes per week.

Two Methods of Assessing Aerobic Intensity

The intensity of aerobic physical activity can be defined in absolute or relative terms.

Absolute Intensity

The Advisory Committee concluded that absolute moderate-intensity or vigorous-intensity physical activity is necessary for substantial health benefits, and it defined absolute aerobic intensity in terms of METs:

  • Light-intensity activities are defined as 1.1 MET to 2.9 METs.
  • Moderate-intensity activities are defined as 3.0 to 5.9 METs. Walking at 3.0 miles per hour requires 3.3 METs of energy expenditure and is therefore considered a moderate-intensity activity.
  • Vigorous-intensity activities are defined as 6.0 METs or more. Running at 10 minutes per mile (6.0 mph) is a 10 MET activity and is therefore classified as vigorous intensity.

Relative Intensity

Intensity can also be defined relative to fitness, with the intensity expressed in terms of a percent of a person’s (1) maximal heart rate, (2) heart rate reserve, or (3) aerobic capacity reserve. The Advisory Committee regarded relative moderate intensity as 40 to 59 percent of aerobic capacity reserve (where 0 percent of reserve is resting and 100 percent of reserve is maximal effort). Relatively vigorous-intensity activity is 60 to 84 percent of reserve.

To better communicate the concept of relative intensity (or relative level of effort), the Guidelines adopted a simpler definition:

  • Relatively moderate-intensity activity is a level of effort of 5 or 6 on a scale of 0 to 10, where 0 is the level of effort of sitting, and 10 is maximal effort.
  • Relatively vigorous-intensity activity is a 7 or 8 on this scale. This simplification was endorsed by the American College of Sports Medicine and the American Heart Association in their recent guidelines for older adults.1 This approach does create a minor difference from the Advisory Committee Report definitions, however. A 5 or 6 on a 0 to 10 scale is essentially 45 percent to 64 percent of aerobic capacity reserve for moderate intensity. Similarly, a 7 or 8 on a 0 to 10 scale means 65 percent to 84 percent of reserve is the range for relatively vigorous-intensity activity.

Obesity ages the brain by 10 yrs

obese brain 10yrs older.JPG

The team then calculated how white matter volume related to age across the two groups. They discovered that an overweight person at, say, 50 years old had a comparable white matter volume to a lean person aged 60 years, implying a difference in brain age of 10 years.

Strikingly, however, the researchers only observed these differences from middle-age onwards, suggesting that our brains may be particularly vulnerable during this period of ageing.

“As our brains age, they naturally shrink in size, but it isn’t clear why people who are overweight have a greater reduction in the amount of white matter,” says first author Dr Lisa Ronan from the Department of Psychiatry at the University of Cambridge, “We can only speculate on whether obesity might in some way cause these changes or whether obesity is a consequence of brain changes.”

Senior author Professor Paul Fletcher, from the Department of Psychiatry, adds: “We’re living in an ageing population, with increasing levels of obesity, so it’s essential that we establish how these two factors might interact, since the consequences for health are potentially serious.

“The fact that we only saw these differences from middle-age onwards raises the possibility that we may be particularly vulnerable at this age. It will also be important to find out whether these changes could be reversible with weight loss, which may well be the case.”

Despite the clear differences in the volume of white matter between lean and overweight individuals, the researchers found no connection between being overweight or obese and an individual’s cognitive abilities, as measured using a standard test similar to an IQ test.

Co-author Professor Sadaf Farooqi, from the Wellcome Trust–Medical Research Council Institute of Metabolic Science at Cambridge, says: “We don’t yet know the implications of these changes in brain structure. Clearly, this must be a starting point for us to explore in more depth the effects of weight, diet and exercise on the brain and memory.”

The research was supported by the Bernard Wolfe Health Neuroscience Fund, the Wellcome Trust and the Biotechnology and Biological Sciences Research Council.

Reference
Ronan, L et al. Obesity associated with increased brain-age from mid-life. Neurobiology of Aging; e-pub 27 July 2016; DOI: 10.1016/j.neurobiolaging.2016.07.010