Mortality in the United States, 2017

November 29, 2018

Questions and Answers from the authors of the recently released 2017 mortality data.  The data can be found in the following reports, “Mortality in the United States, 2017, ” “Drug Overdose Deaths in the United States, 1999–2017, ” and “Suicide Mortality in the United States, 1999–2017.”

Q: Why did life expectancy decline in 2017?

A: Mortality rates increased for 7 out of the 10 leading causes of death in the U.S., including a 5.9% increase in the flu/pneumonia death rate, a 4.2% increase in the accidental/unintentional injury death rate, and 3.7% in the suicide rate. Many of the accidental/unintentional deaths were from drug overdoses, which continued to increase in 2017.


Q: Isn’t this the third straight year that life expectancy declined?

A: Estimated life expectancy at birth in 2017 was 0.3 years lower than in 2014 and 0.1 years lower than in 2016. The 2016 life expectancy estimate was revised to 78.7 years, up from an estimated 78.6 years, which was reported a year ago. This means that the 2016 life expectancy estimate is the same as the 2015 estimate, which also was revised to 78.7 years, down from an estimated 78.8 years, originally reported two years ago. As a routine matter, for the highest degree of accuracy, NCHS blends Medicare data for people ages 66 and over with our vital statistics data to estimate life expectancy. However, the two data sets are released on different schedules. When Medicare data for a year aren’t available at the time we release our final mortality statistics, we use the most recent Medicare data available at the time. We later revise life expectancy estimates when updated Medicare data become available.


Q: How many deaths in 2017 were attributed to opioids?

A: In 2017, 47,600 drug overdose deaths mentioned involvement of any type of opioid, including heroin and illicit opioids, representing over two-thirds of all overdose deaths (68%).


Q: Why is the 70,237 number of overdose deaths smaller than what CDC has previously reported for 2017?

A: The 70,237 number is a final, official number of overdose deaths among U.S. residents for 2017 whereas the previously reported (and slightly higher) numbers were provisional estimates. In August of 2017, CDC began calculating monthly provisional data on counts of drug overdose deaths as a rapid response to this public health crisis, in order to provide a more accurate, closer to “real-time” look at what is happening both nationally and at the state level. These monthly totals are provisional counts, and they include all deaths occurring in the U.S. – which include deaths among non-residents (i.e., visitors here on business or leisure, students from abroad, etc). These counts also do not include deaths that are still under investigation. As a result, the monthly numbers are provisional or very preliminary, and the final 2017 number of 70,237 deaths is an official number that only include deaths among U.S. residents and account for any previously unresolved deaths that were under investigation.


Q: Does this mean that the 70,237 total does not include deaths to undocumented immigrants here in the U.S.?

A: We don’t get immigration status off the death certificates, so we wouldn’t know how many of the deaths were to undocumented immigrants.


Q: In comparing the 2017 numbers with 2016 and past years, is the crisis of drug overdose deaths growing or about the same?

A: From 2016 to 2017, the number of drug overdose deaths increased from 63,632 deaths to 70,237, a 10% increase, which is a smaller increase compared to the 21% increase from 2015 to 2016, when the number of drug overdose deaths increased from 52,404 deaths to 63,632 deaths. Over a longer period of time, from 1999 through 2017, the age-adjusted rate of drug overdose deaths increased on average by 10% per year from 1999 to 2006, by 3% per year from 2006 to 2014, and by 16% per year from 2014 to 2017. So the trend is continuing, although the increase in 2017 was not as large as in previous years.


Q: Are there any other trends of significance when looking at the types of drugs attributed to overdose deaths?

A: The rate of drug overdose deaths involving synthetic opioids other than methadone, which include drugs such as fentanyl, fentanyl analogs, and tramadol, increased 45% in one year, from 6.2 per 100,000 in 2016 to 9.0 per 100,000 in 2017. In 2017, 40%(?) of all drug overdose deaths mentioned involvement of a synthetic opioid other than methadone.


Q: Has fentanyl overtaken heroin as the major cause of overdose death?

A: The data brief on drug overdose deaths does not specifically address fentanyl. However the rate of drug overdose deaths involving synthetic opioids other than methadone, which includes fentanyl, increased 45% 2016 and 2017 whereas the overdose death rate from heroin did not change (4.9 deaths per 100,000).


Q: There is a lot of stark news in these three reports. Are there any positives to report?

A: The cancer mortality rate declined between 2016 and 2017, and although estimated life expectancy declined in 2017, life expectancy for people at age 65 actually increased. Also, regarding drug overdose deaths, the rate of increase in drug overdose deaths slowed between 2016 and 2017, although the increases that occurred were still very significant.

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Trends in Fertility and Mother’s Age at First Birth Among Rural and Metropolitan Counties: United States, 2007–2017

October 17, 2018

Questions for Danielle Ely, Health Statistician and Lead Author of “Trends in Fertility and Mother’s Age at First Birth Among Rural and Metropolitan Counties: United States, 2007–2017

Q: Why did you decide to look at fertility rates and mother’s age at first birth among rural and metropolitan U.S. counties?

DE: Rural and metropolitan counties have a variety of differences related to general health, birth outcomes, and mortality rates. However, we noticed that recent research did not focus on the overall fertility differences in these areas or maternal age, which can affect birth outcomes. Looking at these items can help us understand why we might see differences between rural and metro counties in births and birth outcomes.


Q: How did the findings vary by race?

DE: Patterns for total fertility rates were similar by race and Hispanic origin. There were higher total fertility rates in rural counties than in metropolitan counties among the three race and Hispanic origin groups in 2007. In 2017, this pattern was the same for non-Hispanic white and Hispanic women, but non-Hispanic black women had higher total fertility rates in small or medium metro counties compared with rural and large metro counties. Hispanic women had the highest total fertility rates for each urbanization level in both 2007 and 2017

Non-Hispanic white, non-Hispanic black and Hispanic women had lower ages at first birth in rural counties compared with both metro county types. This was true in both 2007 and 2017, and differences between county types widened over this time.


Q: How did the findings vary by mean age of mothers at first birth?

DE: Mean age at first birth was lower in rural counties than small or medium metro counties and large metro counties from 2007-2017. Each of the three race and Hispanic origin groups had lower mean age at first birth in rural counties compared with metropolitan counties.


Q: Is there any comparable trend data prior to 2007?

DE: We have not computed trend data on total fertility rates or mean age at first birth by urbanization level prior to 2007.


Q: What is the take home message in this report?

DE: The important message in this report is that there are differences in the fertility rates and mean age at first birth between rural and metro areas, and these differences have gotten larger over time. These trends are generally the same by race and Hispanic origin. Information on differences in birth rates and maternal age by urbanization level can inform decisions on resource allocation and ultimately lead to improvement in infant and maternal health.


Fast Food Consumption Among Adults in the United States, 2013-2016

October 3, 2018

Questions for Cheryl Fryar, M.S.P.H., Health Statistician and Lead Author of “Fast Food Consumption Among Adults in the United States, 2013-2016

Q: Of all the types of food that Americans eat, what made you decide to focus on fast food for this study?

CF: We focused on fast food for this report because fast food has played an important role in the American diet in recent decades. Fast food has been associated with poor diet and increased risk of obesity. In a previous report, we analyzed and described the percentage of calories consumed from fast food among adults. This current study looks at fast food consumption in a different way. We describe who is eating fast food on a given day. Specifically in this new report, we look at the percentage of adults who consume fast food overall as well as by sex, age group, race and Hispanic origin, family income level and eating occasion.


Q: Your new report measures fast food consumption “on a given day.” What does that mean exactly?

CF: Fast food consumption “on a given day” reflects the way respondents in the National Health and Nutrition Examination Survey reported all the foods and beverages they consumed in the previous 24 hours. The survey is designed to be representative of people anywhere in the United States at any time of the year, so “on a given day” refers to any day—so for example, on any day in the United States, approximately 37% of U.S. adults consume some fast food.

“Fast food” is defined as any food a respondent reported getting from a “restaurant fast food/pizza” outlet in the 2013-2016 National Health and Nutrition Examination Survey – often known as NHANES.


Q: What type of trend data do you have on eating fast food in the United States; for example, how has the consumption of fast food changed in the United States over the last 10 to 20 years?

CF: While we did not look at trend data for this report, dietary data collected from the National Health and Nutrition Examination Survey is a joint effort between the U.S. Department of Health and Human Services and the U.S. Department of Agriculture (USDA). The USDA has tables with calories (or energy) consumed from quick service restaurants – which includes fast food along with cafeterias and food trucks. These tables show that in 2015-2016, 15% of calories was from quick service restaurants compared to 16% in 2011-2012.


Q: Was there a finding in this new report on fast food that you hadn’t expected and that really surprised you?

CF:  While there really wasn’t anything in this report that I hadn’t expected to see or that was surprising to me, this report’s analysis does offer some new information. Results from this study were similar to what we found for youth in 2011-2012, where 34% of youth consumed fast food. A new contribution from this new research is reporting fast food consumption among non-Hispanic Asian American adults in comparison to other groups. A notable finding is that non-Hispanic Asian American adults consumed a lower percentage of fast food (30.6%) compared to non-Hispanic white (37.6%) and non-Hispanic black (42.4%) adults.


Q: What differences or similarities did you see between or among various demographic groups in this analysis of fast food consumption?

CF: We found some differences in the percentage of U.S. adults who consume fast food. For example, fast food consumption decreased with age and increased with increasing income. About 45% of young adults consumed fast food compared to just over 24% of older adults. About 32% of adults in the lowest income group consumed fast food compared to 42% of adults in the highest income group. And a lower percentage of non-Hispanic Asian adults (30.6%) consumed fast food compared to non-Hispanic white (37.6%) and non-Hispanic black (42.4%) adults.

Also, among those who consumed fast food, men were more likely than women to eat fast food at lunch, but women were more likely than men to report eating fast food as a snack.


Q: What would you say is the take-home message of this report?

CF: The take-home message of this report is that overall more than one-third of U.S. adults and 45% of young adults consume fast food on a given day. Fast food restaurants can vary, though consumers can find nutritional information, such as calories, on the menu in most fast food establishments and restaurants.


Fact or Fiction: Do One in Three U.S. Adults Eat Seafood at Least Two Times Per Week?

September 28, 2018

SOURCE: National Health and Nutrition Examination Survey, 2013–2016.

https://www.cdc.gov/nchs/data/databriefs/db321.pdf


Seafood Consumption in the United States, 2013–2016

September 28, 2018

Questions for Ana Terry, Health Statistician and Lead Author of “Seafood Consumption in the United States, 2013–2016

Q: What surprised you most about the findings in your report?

AT: Although the findings were not necessarily surprising, we found that seafood consumption was more than twice as high among non-Hispanic Asian adults compared with adults of other race and Hispanic-origin groups.  More than 40% of non-Hispanic Asian adults consumed seafood at least twice per week compared to about 19% of non-Hispanic white, 23% of non-Hispanic black, and 15% of Hispanic  adults.  This is consistent with other studies, which have found that people of Asian descent living in the U.S. consume seafood more frequently, in greater variety, and in greater quantity than non-Asian Americans (Liu et al, Environmental Research, October 2017).


Q: Do we know why there is such a disparity between US Asians and other race/ethnic groups when it comes to consuming the recommended amount of seafood?

AT: We analyzed data from the 2013-2016 National Health and Nutrition Examination Survey that was collected by a food frequency questionnaire in which persons were asked about the frequency and type of fish and shellfish they consumed in the previous 30 days.  The questionnaire did not ask for the reasons why individuals consumed or did not consume seafood. Other studies have found that diet patterns in Asian countries include fish and shellfish intake levels greater than the average seafood consumption worldwide and that the food choices of people of Asian descent living in the U.S. , are influences by Asian dietary patterns (Liu et al, Environmental Research, October 2017).


Q: Does the fact that seafood consumption has declined mean the population is at less of a risk for mercury exposure?

AT: We did not assess mercury exposure in this report.


Q: What are the health benefits to eating seafood?

AT: The Dietary Guidelines for Americans recommend for the general population consumption of about 8 oz per week of a variety of seafood. Fish and shellfish are excellent sources of high quality protein, are low in saturated fat, are rich in minerals and vitamins, and provide certain omega-3 fatty acids (EPA and DHA) that the body cannot make and are important for normal growth and development.  Seafood and omega-3 fatty acids have been shown to protect against health problems.


Q: What kinds of seafood are most healthy to eat?

AT: Cold water oily fish have the highest levels of omega-3 fatty acids but lower in methyl mercury (according to the 2015-2020 Dietary Guidelines for Americans). Cold water oily fish include:  Salmon, Anchovies, Herring, Shad, Atlantic and Pacific mackerel


Beverage Consumption Among Youth in the United States, 2013-2016

September 13, 2018

Kirsten A. Herrick, Ph.D., M.Sc, NCHS Epidemiologist

Questions for Kirsten A. Herrick, Ph.D., M.Sc, Epidemiologist and Lead Author of “Beverage Consumption Among Youth in the United States, 2013-2016

Q: What made you decide to focus on what children in the United States drink for this study?

KH: In a previous report, we described the consumption of sugar-sweetened beverages among youth. This current study looks at beverage consumption in a different way. We are looking at all types of beverages, rather than focusing on only those that contain sugar or calories (energy.) Specifically in this new report, we look at beverage types by amount (grams) rather than by calories.


Q: Was there a finding in your new report that you hadn’t expected and that really surprised you?

KH: While there was nothing in this report that I hadn’t expected to see or that was surprising to me, the data results in this analysis do offer some new perspective. A new contribution from this research is a look at beverage consumption among non-Hispanic Asian youth and how this compares to other race and Hispanic origin groups. A notable finding is that non-Hispanic Asian youth drink more water compared to other groups.


Q: What differences or similarities did you see between or among various demographic groups in this analysis?

KH: We observed quite a few variations among demographic groups in our analysis of what youth in the United States are drinking. One interesting observation was that the contribution of milk and 100% juice to all beverage consumption, decreased with age—while the contribution of water and soft-drinks increased with age. While the types of beverages boys and girls drink are similar, we found that for Asian youth water accounted for the largest share of all beverages consumed compared with other race groups. The amount of beverages consumed as soft drinks was largest for non-Hispanic Black youth compared with other race groups, and the contribution of milk to overall beverage consumption is lowest among non-Hispanic Black youth in America.


Q: What would you say is the take-home message of this report?

KH: I think the real take-home message of this report is that beverage consumption is not the same for all U.S. youth. Since beverages contribute to hydration, energy and vitamin and mineral intake, these choices can impact diet quality and total caloric intake. It is very valuable for the U.S. Public Health Community to have this information, which can help guide their important work throughout America. I think it’s valuable information for families to have as well—and for youth in the U.S. to also be aware of the potential impact of these choices.


Q: What type of trend data do you have for U.S. children’s beverage consumption, and how has it changed over time, for example the last 20 years?

KH: While this report did not look at trends, the reason it does not present trends can tell us a lot about beverage consumption analysis over the years. The types of beverages available today are different than 20 years ago or in other years past. So trends wouldn’t strictly be comparing the same things over time.

Plus, this new report isn’t directly comparable with previous reports. For example, in this new Data Brief we looked at soft drinks and defined them as diet and non-diet forms of soda and fruit drinks. So this soft drink category is not equivalent to sugar-sweetened beverages—which has been the focus of some of our earlier analyses. Also, many past reports where we might have looked for trends—were interested in the energy from beverages. But water, an important beverage for hydration, doesn’t have calories, and therefore is often left out of earlier discussions and analyses about beverage consumption. In our new report we looked at total beverage consumption by amount (in grams) so we could include ALL beverages, not just those that contribute to calorie consumption.


High-deductible Health Plan Enrollment Among Adults Aged 18-64 With Employment-based Insurance Coverage

August 9, 2018

Questions for Robin Cohen, Ph.D. and Lead Author of “High-deductible Health Plan Enrollment Among Adults Aged 18-64 With Employment-based Insurance Coverage

Q: What made you decide to put together a report about high and low deductible health plans for adults with employment-based coverage?

RC: We decided to produce an analysis focusing on high-deductible health plans (HDHPs) after observing how enrollment in HDHPs has increased over the past decade. In addition, HDHP enrollment growth has been faster among those with employment-based coverage than among those with directly-purchased coverage, so it also made sense to highlight employment-based insurance plans in this study. This report examines differences in the demographic characteristics for those with employment-based coverage by plan type.    


Q: Was there a finding in your new report that really surprised you?

RC: It was the dramatic increase in high-deductible health plan (HDHP) enrollment in recent years that really surprised us. We hadn’t expected to see such a large jump, which was most notable among those with a health savings account (HSA). The percentage of adults aged 18 to 64 enrolled in an HDHP with an HSA more than quadrupled in the past decade from 4.2% to 18.9%.


Q: What differences or similarities did you see between or among various demographic groups in this analysis?

RC: Both the differences among age groups and the lack of variance by sex in this study’s findings are notable. Among adults aged 18 to 64 with employment-based coverage, there were no differences in the type of health insurance plan by sex. Enrollment in a high-deductible health plan with a health savings account was higher among adults aged 30 to 44 than those aged 18 to 29 and 45 to 64.


Q: What is the significance of having a health savings account and not having one when you have a high-deductible health insurance plan?

RC: A health savings account (HSA) allows pretax income to be saved to help pay for the higher costs associated with a high-deductible health plan (HDHP). However, this report did not examine the association of having an HDHP — coupled with an HSA — on service use and financial burden for medical care.

 

Q: Is it a choice for Americans to have a health savings account? Can anyone have one?

 

RC: A health savings account (HSA) must be coupled with a high-deductible health plan (HDHP), but not everyone enrolled in an HDHP has an HSA. High-deductible health plans with HSAs are offered to individuals both by employers and in the direct-purchase health insurance market.

Q: What would you say is the take-home message of this report?

 

RC: I think the real take-home message in this Data Brief is the role that education and income play in health insurance coverage with these types of high-deductible health plans (HDHPs). More highly educated and affluent adults were more likely to enroll in an HDHP with a health savings account (HSA) and less likely to enroll in a traditional plan or an HDHP without an HSA — than their less educated and less affluent counterparts. The National Health Interview Survey will continue to monitor different types of private health insurance, and the survey can be used to examine further differences according to plan type.

Q: Do you have trend data on high-deductible health plans going back further than 2007?

RC: No, we don’t have earlier than 2007 trend data on high-deductible health plans (HDHPs). The National Health Interview Survey began to collect data on enrollment in HDHPs starting in 2007.