A 36 yr old saves $100 every month for her retirement

A $100 per month saved and paid as a premium for an Index Universal Life Insurance ( IUL) plan can yield good retirement money for a 36 yr old female with death benefit of $300,000. In this plan, there is a flexibility to save more each month on top of the monthly premium.

My son is saving at 2% in his credit union because he wants to help his sister move to another city. Do allocate around 5-10% of your income for a cash accumulation IUL or other retirement plan early on, to allow enough time to grow at 8% or higher rate with no downside market participation.

My daughter saves her money for a house at age 24 and had been going to thrift stores most of the time. As a teacher, she still can buy school supplies for her students as an art teacher.

Here is a sample quote for a 36 yr old female with death benefit of $300k:


My 83-yr old mother’s fight against liver cancer

She does not want to be bed ridden or be dependent on others but she is always feeling fatigue, nauseous, itchy skin, constipated, have diarrhea, severe headache and in severe body pain.

After working for more than 18 years in the bay area in home care setting, she is now fighting liver cancer.  We wanted to not let her know of the liver cancer diagnosis but she was adamant. She knows her body well.

We use the following holistic healing ways with combination medical treatment to cleanse her body from liver cancer:

  • Prescribed meds for pain, constipation, diarrhea
  • IV of Vitamin C
  • Supplements
  • Whole foods
  • Massage
  • Sunshine
  • Fresh ocean air
  • Sleep
  • De-stressing tools

nay 1

card mother


The World’s smoking population

smoking poptobaccoCountries with large smoking populations

In 2015, there were 933·1 million (95% UI 831·3–1054·3) daily smokers in the world, 82·3% of whom were men (768·1 million [690·1–852·2]). The ten countries with the largest number of smokers together accounted for 63·6% of the world’s daily smokers. China, India, and Indonesia, the three leading countries in total number of male smokers, accounted for 51·4% of the world’s male smokers in 2015. On the other hand, the USA, China, and India, which were the leading three countries in total number of female smokers, accounted for only 27·3% of the world’s female smokers. Together, these results suggest that the tobacco epidemic is less geographically concentrated for women than for men.

Among the ten countries with the largest number of total smokers in 2015, seven recorded significant decreases in male smoking prevalence and five had significant decreases in female smoking prevalence since 1990 (table 2). Of these countries, Brazil recorded the largest overall reduction in prevalence for both male and female daily smoking, which dropped by 56·5% (51·9–61·1) and 55·8% (48·7–61·9), respectively, between 1990 and 2015. Indonesia, Bangladesh, and the Philippines did not have significant reductions in male prevalence of daily smoking since 1990, and the Philippines, Germany, and India had no significant decreases in smoking among women. All of the three countries with female age-standardised smoking prevalence less than 3·0% (China, India, and Bangladesh) succeeded in keeping smoking prevalence low in women. Notably, female prevalence of daily smoking significantly increased in Russia and Indonesia since 1990 (table 2).


Delving into the smoking patterns of adolescents can shed light on trends in smoking initiation.47Between 1990 and 2015, the global prevalence of daily smoking for this age group significantly decreased for each sex, falling from 16·1% (95% UI 14·4–18·0) to 10·6% (9·3–12·1) for men and from 4·8% (4·3–5·6) to 3·0% (2·6–3·7) for women (table 2). Despite global decreases, several countries still had a high prevalence of smoking among individuals aged between 15 and 19 years. In 2015, there were 22 countries with female smoking prevalence in this age group higher than 15·0%, 18 of which were located in western or central Europe. Countries with high male smoking prevalence were much more dispersed. Of the 24 countries with male smoking prevalence higher than 20·0%, six were in eastern Europe, and the remainder were spread across ten other regions (appendix pp 13, 14). The rank of countries with the largest smoking populations for the 15–19 years age group was mostly consistent with the rank for all-age smoking populations (table 2).

Although no country had a significant increase for men or women in this age group since 2005, only three countries saw smoking prevalence in 15 to 19 year-olds significantly drop for both men and women since 2005 (New Zealand, Iceland, and the USA). Iceland had the largest significant decrease among men, decreasing from 14·8% (95% UI 11·7–18·5) in 2005 to 9·0% (5·6–13·3) in 2015. New Zealand had the largest significant decline among women, decreasing from 20·8% (18·1–23·8) in 2005 to 12·5% (10·1–15·5) in 2015 (available to view through GHDx).

Shifts in patterns of smoking across cohorts

Parsing out daily smoking prevalence by age group and birth cohort allows for a more fine-grained examination of smoking prevalence, age patterns, and temporal trends by level of development (figure 2). Male age patterns of smoking were fairly consistent across levels of SDI, with prevalence generally peaking between the ages of 25 and 35 years. For women, however, age patterns varied more by SDI; female smoking prevalence typically peaked around age 25 years for high and high-middle SDI countries, while prevalence generally increased until age 60 years in low to middle SDI countries. Across birth cohorts, smoking prevalence decreased by age group, sex, and SDI level. The most notable decreases were recorded in high and high-middle SDI countries for men, where sizeable reductions in smoking prevalence in 15 to 24 year-olds occurred across birth cohorts. Middle SDI countries, which have the highest levels of daily smoking among men, had minimal changes in prevalence across birth cohorts, suggesting far less progress in curbing smoking initiation or promoting cessation. For women, prevalence is consistently lower than in men; nevertheless, reductions in smoking prevalence across birth cohorts generally were smaller than those recorded for men.

Deaths and disease burden attributable to smoking

In 2015, 6·4 million deaths (95% UI 5·7–7·0) were attributable to smoking worldwide, representing a 4·7% (1·2–8·5) increase in smoking-attributable deaths since 2005. More than 75% of these deaths were in men, and 52·2% took place in four countries (China, India, the USA, and Russia). Smoking was the second-leading risk factor for attributable mortality among both sexes in both 2005 and 2015, following high-systolic blood pressure.1 The relative ranking of smoking-attributable disease burden, as measured in DALYs, increased from third to second between 2005 and 2015. In 2015, there were 148·6 million (95% UI 134·2–163·1) smoking-attributable DALYs worldwide, and smoking was the leading risk factor for attributable disease burden in 24 countries, an increase from 16 countries in 1990 (figure 3). Further, smoking was ranked among the leading five risk factors for 109 countries in 2015. Between 2005 and 2015, only Egypt recorded a significant increase in the age-standardised smoking-attributable mortality rate among both sexes, increasing by 11·4% (95% UI 0·3–24·7) over that time period. On the other hand, 82 countries had significant decreases in their age-standardised smoking-attributable mortality rates since 2005.

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Figure 3

Rankings of smoking as a risk factor for all-cause, all-age attributable DALYs for both sexes combined in 2015

DALYs=disability-adjusted life-years. ATG=Antigua and Barbuda. VCT=Saint Vincent and the Grenadines. LCA=Saint Lucia. TTO=Trinidad and Tobago. TLS=Timor-Leste. FSM=Federated States of Micronesia.

Overall, in 2015, cardiovascular diseases (41·2%), cancers (27·6%), and chronic respiratory diseases (20·5%) were the three leading causes of smoking-attributable age-standardised DALYs for both sexes. Of all risk factors, smoking was the leading risk factor for cancers and chronic respiratory diseases, but only the ninth leading risk factor for cardiovascular diseases.1 The appendix shows the 30 leading causes of DALYs attributable to smoking, including changes over time (pp 19, 20). For women, the leading cause of smoking-attributable DALYs was COPD, whereas the leading cause for men was ischaemic heart disease.

Decomposing changes in attributable burden due to smoking

Relative to changes in smoking exposure, the main drivers of overall changes in attributable burden due to smoking varied by both sex and SDI level (figure 4). Since 2005, all-cause DALYs attributable to smoking for men decreased by 11·8% (95% UI 10·0–13·9) in high-SDI countries, the only SDI level with a significant decrease in attributable burden for men. For women, only middle-SDI countries had a significant reduction in all-cause DALYs attributable to smoking (a 22·6% decrease [9·0–32·8]) between 2005 and 2015. In both instances, a combination of reduced smoking exposure and reduced risk-deleted DALY rates contributed to overall reductions. Conversely, all-cause burden due to smoking significantly increased in low SDI and low-middle SDI countries since 2005 for men. This rise in attributable DALYs was driven mainly by a combination of population growth and population ageing for both sexes. In women, while rising exposure to smoking has resulted in increased DALYs due to smoking for low-middle SDI countries, this increase was not significant. Generally, population growth was the leading factor for increasing attributable burden due to smoking among the low SDI countries between 2005 and 2015. For countries of middle to high SDI, more pronounced sex differences emerged. For instance, decreases in male smoking prevalence propelled an overall reduction in attributable burden for high SDI countries, whereas changes in smoking exposure had minimal effects on overall burden for women at similarly high levels of SDI.

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Figure 4

Decomposition of changes in all-cause DALYs attributable to smoking from 2005 to 2015, by SDI, for men (A) and women (B)

Changes due to population growth, population ageing, risk exposure (smoking prevalence), and the risk-deleted DALY rate are shown. Locations are reported in order of the number of attributable DALYs for both sexes in 2015. DALYs=disability-adjusted life-years. SDI=Socio-demographic Index.

A complete dataset of all results by geography, year, sex, and age group can be downloaded through GHDx, and an interactive data visualisation of smoking prevalence results can be found online.


Despite more than half a century of unequivocal evidence of the harmful effects of tobacco on health,48, 49 in 2015, one in every four men in the world was a daily smoker. Prevalence has been, and remains, significantly lower in women—roughly one in every 20 women smoked daily in 2015. Nonetheless, much progress has been accomplished in the past 25 years. Specifically, the age-standardised global prevalence of daily smoking fell to 15·3% (95% UI 14·8–15·9), a 29·4% (27·1–31·8) reduction from 1990, with smoking rates decreasing from 34·9% (34·1–35·7) to 25·0% (24·2–25·7) in men and from 8·2% (7·9–8·6) to 5·4% (5·1–5·7) in women. These reductions were especially pronounced in high SDI countries and Latin America, probably reflecting concerted efforts to implement strong tobacco control policies and programmes in Brazil and Panama, among others.

Yet amid these gains, many countries with persistently high levels of daily smoking recorded marginal progress since 2005, and smoking remained among the leading risk factors for early death and disability in more than 100 countries in 2015, accounting for 11·5% of global deaths (95% UI 10·3–12·6) and 6·0% (5·3–6·8) of global DALYs. Smoking patterns diverged by geography, level of development, sex, and birth cohort, emphasising the need for tailored approaches to change smoking behaviours. Although male smoking prevalence still far exceeded that of female smokers in 2015, the most pronounced reductions in smoking prevalence since 1990 were generally found for men—and more places saw minimal changes or increases in smoking among women. These trends highlight how the tobacco epidemic, and corresponding industry forces, has expanded beyond a male-centred health challenge.

Low to middle SDI countries saw increased disease burden attributable to smoking since 2005, a trend that that occurred despite variable decreases in smoking prevalence and risk-deleted DALY rates. Population growth or ageing, or a combination of both, ultimately contributed to increased disease burden attributable to smoking in these countries. In higher SDI countries, population growth and ageing offset the potential for larger gains in places where notable declines in smoking prevalence and risk-deleted DALY rates occurred. This finding points to a crucial challenge ahead for tobacco control: unless progress in reducing current smoking and preventing initiation can be substantially accelerated, demographic forces, which are far less amenable to immediate intervention, are poised to heighten the disease burden associated with smoking’s global toll.

Since 2005, the year when the FCTC entered into force, it has redefined global, regional, and national approaches to tobacco control and policy.50, 51 Case studies point to the successful uptake and enforcement of FCTC components in many countries with especially prominent reductions in smoking prevalence. Pakistan, Panama, and India stand out as three countries that have implemented a large number of tobacco control policies over the past decade and have had marked declines in the prevalence of daily smoking since 2005, compared with decreases recorded between 1990 and 2005.52, 53, 54 At the same time, many countries, including Australia, Brazil, Canada, South Korea, and the USA, among others, achieved sizeable declines in smoking prevalence well before FCTC adoption.15, 56, 57, 58 Altogether, 18 countries recorded a faster annualised rate of decline from 1990 to 2005 than from 2005 to 2015.

Brazil, which has achieved the third largest significant decline in age-standardised smoking prevalence since 1990, is a noteworthy success story. Brazil accomplished this reduction through a combination of tobacco control policies that began with advertising restrictions and smoking bans in some public places starting in 1996 and culminated with Brazil achieving the highest level of achievement in all MPOWER measures except for monitoring by 2011. Policies were comprehensive and were supplemented with fiscal interventions that included raising taxes and establishing minimum prices for tobacco products. Finally, Brazil has achieved high levels of compliance through enforcement.20, 59, 60, 61, 62

Critics of the FCTC argue that the treaty’s effectiveness may be limited in various settings, especially since compliance has lagged in many countries.63, 64, 65 The FCTC, while necessary and vital for creating the policy environment for more effective tobacco control worldwide, is not sufficient to fully address each country’s tobacco control needs. Rather, countries will need to both implement FCTC-stipulated measures and supplement such policies and programmes with strong enforcement and high rates of compliance. For example, India, where 11·2% of the world’s smokers live, supplemented the Cigarettes and Other Tobacco Products Act (COTPA) with the creation of a National Tobacco Control Programme (NTCP) in 2007. NTCP was created to strengthen implementation and enforcement of the various provisions of COTPA at the state and district level. It has been rolled out in phases and currently covers about 40% of all districts in India.66

Despite concerted efforts to control tobacco around the world, there remain a number of countries where current levels and recent trends raise concern. For example, Indonesia, a country with very high levels of smoking, particularly among men, has not yet ratified the FCTC and scores very poorly on the MPOWER indicators.18 Also, in Russia, prevalence among women has been increasing, and, until recently, there were very few laws related to tobacco control.67 Russia passed a comprehensive tobacco control policy in 2014 and has the potential to achieve progress on tobacco control.68 As a region, eastern Europe has seen a statistically significant increase in smoking prevalence among women since 1990. Increases among women, along with a sustained high prevalence of male smokers, can be linked to tobacco industry targeting during the 1990s.6 The tobacco industry is now turning its focus toward emerging markets in sub-Saharan Africa, seeking to exploit the continent’s patchwork tobacco control regulations and limited resources to combat industry marketing advances.69, 70 Given the large effects of population growth and ageing on smoking-attributable disease burden—and Africa’s rapidly changing demographic profile—a renewed dedication to strong, proactive tobacco policies and monitoring will be vital for the continent.71

The 2030 agenda features tobacco control as a key component to sustainable development, with SDG Target 3.a calling for stronger FCTC implementation.24 Nonetheless, the utility and potential impact of the SDGs on tobacco control may be hindered by the vagueness of Target 3.a (“Strengthen the implementation of the WHO FCTC in all countries, as appropriate”) and absence of defined targets for reducing smoking prevalence by 2030. Ultimately, to move all countries toward stronger tobacco control by 2030, improvements in policy formulation, enforcement and compliance, and the routine monitoring of smoking behaviour are urgently needed. Without valid and reliable data, these efforts risk being more aspirational than grounded in evidence-informed action. Multi-country survey series have substantially improved data availability on smoking prevalence, yet the disadvantages associated with such surveys—high cost, time lags, inconsistent questions across survey series, sample restrictions for young populations, and a reliance on self-reported smoking behaviour—necessitate the development of robust, locally focused, timely, objective, and low-cost methods of tracking smoking trends. Supplementing surveys with biomarker collection is essential because self-reported smoking prevalence is believed to be severely underestimating true smoking prevalence,72,73, 74, 75 especially in population subgroups or places where tobacco use may not be culturally acceptable.

Our findings should be interpreted taking into consideration the study’s limitations. First, our exposure estimation focused on smoked tobacco and did not include smokeless tobacco products and e-cigarettes. Second, our definition of smoking exposure pertained to current daily smokers, and did not include occasional or former smokers, which might underestimate the attributable disease burden to smoking, especially in populations who tend to be less likely to smoke every day, such as women, children and young adults, and individuals with less disposable income. Third, we did not account for the intensity or duration of smoking. Fourth, the study relied on self-reported data, and it is possible that reporting biases varied across countries and over time. Fifth, for long-term effects of smoking on cancers and chronic respiratory diseases, we used the smoking impact ratio method, which estimates the lifetime cumulative effect of cigarette smoking using the proxy of recorded lung cancer mortality rates. This method provides robust estimates of the burden of cancers and chronic respiratory diseases related to tobacco but is not fully consistent with the GBD approach of estimating exposure independently of the outcomes affected by exposure. Also, the smoking impact ratio method is based on the cumulative effect of cigarette smoking rather than all types of tobacco smoking, and might be less robust for geographies in which non-smoker lung cancer might be significantly affected by air pollution or other factors. Sixth, our estimates of DALYs are probably underestimates because relative risk values used for estimating population attributable fractions might not fully represent all possible risk-outcome pairs experienced by sex, age group, and over time.76 Also, burden estimates did not account for the effect of both indoor and outdoor air pollution potentiating risks. Finally, minimal risk-outcome data were available for populations younger than 30 years, and therefore burden attribution was limited to age groups 30 years and older.


Despite more than 50 years of anti-tobacco efforts, smoking remains a leading global risk factor. Its toll will remain substantial without more concerted policy initiatives, policy compliance and enforcement, and sustained political will to offset commercial interests. Despite progress in some settings, the war against tobacco is far from won, especially in countries with the highest numbers of smokers. The staggering toll of smoking on health echoes well beyond the individual, especially as tobacco threatens to exact long-term financial and operational burdens on already resource-constrained health systems. To significantly and permanently bend the global tobacco epidemic’s trajectory, a renewed and sustained focus is needed on comprehensive tobacco control policies around the world. Success is possible, but requires effective and aggressively enforced policies and laws. Intensified efforts are also greatly needed to keep smoking prevalence rates low in populations which have not experienced a devastating epidemic yet, and to prevent children, adolescents, and young adults from starting to smoke.

smoking pop 2


Sex differences in human lifespan and healthspan

Aging is characterized by decreasing physiological integration, reduced function, loss of resilience and increased risk of death. Paradoxically, although women live longer, they suffer greater morbidity particularly late in life.

These sex differences in human lifespan and healthspan are consistently observed in all countries and during every era for which reliable data exist.

While these differences are ubiquitous in humans, evidence of sex differences in longevity and health for other species is more equivocal. Among fruit flies, nematodes and mice, sex differences in lifespan vary depending on strain and treatment.

In this review, we focus on sex differences in age-related alterations in DNA damage and mutation rates, telomere attrition, epigenetics, and nuclear architecture.

We find that robust sex differences exist, for example the higher incidence of DNA damage in men compared to women, but sex differences are not often conserved between species.

For most mechanisms reviewed here, there are insufficient data to make a clear determination regarding the impact of sex, largely because sex differences have not been analyzed. Overall, our findings reveal an urgent need for well-designed studies that explicitly examine sex differences in molecular drivers of aging.


Puberty Hormones Trigger Changes in Youthful Learning

Summary: A new study demonstrates changes in cortical neurotransmission due to hormones at puberty.

Source: UC Berkeley.

Brain study of mice has broad implications for the health and education of young girls.

A University of California, Berkeley, study of mice reveals, for the first time, how puberty hormones might impede some aspects of flexible youthful learning.

“We have found that the onset of puberty hits something like a ‘switch’ in the brain’s frontal cortex that can reduce flexibility in some forms of learning,” said study senior author Linda Wilbrecht, an associate professor of psychology and neuroscience at UC Berkeley.

While gleaned from young female mice, the findings, published in the June 1 issue of the journal Current Biology, may have broad educational and health implications for girls, many of whom are entering the first stage of puberty as young as age 7 and 8.

“Puberty onset is occurring earlier and earlier in girls in modern urban settings – driven by such factors as stress and the obesity epidemic – and has been associated with worse outcomes in terms of school and mental health,” said Wilbrecht, a researcher at the campus’s Center on the Developing Adolescent.

Wilbrecht and her laboratory team at UC Berkeley and UCSF discovered significant changes in neural communication in the frontal cortices of female mice after they were exposed to pubertal hormones. The changes occurred in a region of the frontal brain that is associated with learning, attention and behavioral regulation.

“To our knowledge, this study is the first to demonstrate changes in cortical neurotransmission due to hormones at puberty,” said study lead author David Piekarski, a post-doctoral researcher in Wilbrecht’s lab.

Overall, children have been found to have greater brain flexibility or “plasticity” than adults, enabling them to more easily master multiple languages and other elementary scholastic pursuits.

While they continue to learn after puberty, their cognitive focus in adolescence is often redirected to peer relationships and more social learning. If hormonal changes start as early as second or third grade, when children are tasked with learning basic skills, a shift in brain function could be problematic, Wilbrecht said.

“We should be more thoughtful about aligning what we know about biology and education to accommodate the fact that many girls’ brains are shifting to this adolescent phase earlier than expected,” she said.

For the study, researchers induced puberty in some young female mice by injecting them with pubertal hormones such as estradiol and progesterone, and blocked puberty in others by removing their ovaries.

In measuring the electrical activity of brain cells in the frontal cortices of post-pubertal mice, they observed significant changes in the synaptic activity thought to regulate brain plasticity.

They also compared the higher-order learning strategies of pre-pubertal and post-pubertal mice by testing their ability to find Cheerios hidden in bowls of wooden shavings scented with licorice, clove, thyme or lemon.

After each mouse figured out which scent was paired with the Cheerio, that pairing was changed so the mice had to use trial and error to adapt to the change and learn the new rule.

Image shows mice and a prefrontal cortex slice.

Overall, researchers found that the post-pubertal mice had a harder time adapting to the rule changes than their pre-pubertal counterparts.

“These data demonstrate that puberty itself, not just age, plays a role in frontal cortex maturation,” the study concluded.

The study notes that future studies on male mice will be needed to determine if the present results apply to the male brain.


Source: Yasmin Kirsten Anwar – UC Berkeley
Image Source: NeuroscienceNews.com image is credited to Jon Wilbrecht.
Original Research: Abstract for “Ovarian Hormones Organize the Maturation of Inhibitory Neurotransmission in the Frontal Cortex at Puberty Onset in Female Mice” by David J. Piekarski, Josiah R. Boivin, and Linda Wilbrecht in Current Biology. Published online June 1 2017 doi:10.1016/j.cub.2017.05.027

UC Berkeley “Puberty Hormones Trigger Changes in Youthful Learning.” NeuroscienceNews. NeuroscienceNews, 2 June 2017.


Ovarian Hormones Organize the Maturation of Inhibitory Neurotransmission in the Frontal Cortex at Puberty Onset in Female Mice

•Inhibitory neurotransmission increases in the frontal cortex after puberty
•Pre-pubertal, but not post-pubertal, gonadectomy blocks this increase
•Pre-pubertal hormone treatment accelerates maturation of tonic and phasic inhibition
•Hormone treatment, which drives early puberty, impacts behavioral flexibility

The frontal cortex matures late in development, showing dramatic changes after puberty onset, yet few experiments have directly tested the role of pubertal hormones in cortical maturation. One mechanism thought to play a primary role in regulating the maturation of the neocortex is an increase in inhibitory neurotransmission, which alters the balance of excitation and inhibition. We hypothesized that pubertal hormones could regulate maturation of the frontal cortex by this mechanism.

Here, we report that manipulations of gonadal hormones do significantly alter the maturation of inhibitory neurotransmission in the cingulate region of the mouse medial frontal cortex, an associative region that matures during the pubertal transition and is implicated in decision making, learning, and psychopathology. We find that inhibitory neurotransmission, but not excitatory neurotransmission, increases onto cingulate pyramidal neurons during peri-pubertal development and that this increase can be blocked by pre-pubertal, but not post-pubertal, gonadectomy. We next used pre-pubertal hormone treatment to model early puberty onset, a phenomenon increasingly observed in girls living in developed nations.

We find that pre-pubertal hormone treatment drives an early increase in inhibitory neurotransmission in the frontal cortex, but not the somatosensory cortex, suggesting that earlier puberty can advance cortical maturation in a regionally specific manner.

Pre-pubertal hormone treatment also accelerates maturation of tonic inhibition and performance in a frontal-cortex-dependent reversal-learning task.

These data provide rare evidence of enduring, organizational effects of ovarian hormones at puberty and provide a potential mechanism by which gonadal hormones could regulate the maturation of the associative neocortex.

“Ovarian Hormones Organize the Maturation of Inhibitory Neurotransmission in the Frontal Cortex at Puberty Onset in Female Mice” by David J. Piekarski, Josiah R. Boivin, and Linda Wilbrecht in Current Biology. Published online June 1 2017 doi:10.1016/j.cub.2017.05.027