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The health of individual members has a direct effect on a family’s economic circumstances through higher medical costs and loss of income due to reduced productivity or death. The Family Health major index measures the combined impact of physical and mental health factors on economic prosperity in each state.
The worst outcome for family health is death. As such, it is important to measure how each state is doing in terms of preventing all forms premature death. The common measure for doing so is called Years of Productive Life Lost (YPLL). YPLL measures mortality after birth but before the age of 75 (the standard cut-off age). Put simply, a person who dies at 25 would have 50 years of productive life lost (75 – 25 = 50).
While not all forms of premature death can be prevented, such as cancer or other disease, many forms of premature death do come about because of risk behavior, such as drinking, smoking, and using illicit drugs, which are within the realm of personal and societal choice and government policy. (These are discussed more specifically below.)
The Surgeon General estimates that the total economic costs of smoking in 2009 were $289 billion—including $132.5 billion for direct medical care, $151 billion for lost productivity, and $5.6 billion for lost productivity due to secondhand smoke. The study also estimated that direct medical care costs would grow to $175.9 billion in 2012.
The total economic costs of excessive alcohol consumption in 2006 were $223.5 billion—including $161.3 billion for lost productivity and $24.6 billion for direct medical care. Most of the economic costs are due to binge drinking ($170.7 billion). Additionally, excessive drinking is punishable by criminal penalties, which lead to $73.3 billion of these economic costs being a result of victim costs, the criminal justice system, incarceration expenses, etc.
The obesity epidemic is relatively new, so the economic costs are still being compiled. One study that performed a thorough review of existing literature estimates that the economic costs of obesity exceed $215 billion per year. However, a more recent study suggests that direct medical costs alone are $190 billion per year. In any case, the costs of obesity have a significant impact on the economy and are climbing rapidly.
Illicit drug use is increasing in America and so are concerns about it. A 2016 Gallup poll found that 44 percent of Americans worry a great deal about drug use—an increase of 10 percentage points in only two years.
The economic burden on society caused by illicit drug use is substantial. A recent study by the National Drug Intelligence Center found that the total cost of illicit drug use in 2007 was $193 billion—crime ($113 billion), health ($11 billion), and productivity ($68 billion).
Unlike other health problems, besides excessive alcohol consumption, the most expensive aspect of illicit drug use is the cost of crime, prosecution, and incarceration. As discussed previously, the health and behavioral ramifications of consuming these substances also negatively impact family structure, thus creating a vicious cycle that must be broken.
Sexually transmitted diseases (STDs) are a silent epidemic whose reach is growing with every passing year. Consider these facts from the Centers for Disease Control and Prevention:
There are an estimated 20 million new infections every year—disproportionately affecting young people (between the ages of 15 and 24) who account for half of all new infections.
There have been an estimated 110 million infections—impacting approximately one out of every 3 Americans.
The direct healthcare costs of treating the eight most common STDs conservatively total $16 billion every year. This does not include other indirect costs such as lost productivity or infertility, which would dramatically increase the cost.
STDs account for 50 percent of all preventable infertility. In particular, chlamydia and gonorrhea cause pelvic inflammatory disease, which can lead to infertility.
More troubling is the rise in drug-resistant gonorrhea whose threat level, according to the CDC, has reached “urgent”—the highest threat level possible:
If cephalosporin-resistant N. gonorrhoeae becomes widespread, the public health impact during a 10-year period is estimated to be 75,000 additional cases of pelvic inflammatory disease (a major cause of infertility), 15,000 cases of epididymitis, and 222 additional HIV infections because HIV is transmitted more readily when someone is co-infected with gonorrhea. In addition, the estimated direct medical costs would total $235 million. Additional costs are anticipated to be incurred as a result of increased susceptibility monitoring, provider education, case management, and the need for additional course of antibiotics and follow-up.
The first year used for estimating the costs associated with abortion is 1973 as that was the year of the Roe v. Wade decision, which made abortion legal in all 50 states. Between 1973 and 2012, estimates suggest that approximately 54 million abortions have been performed.
Abortion impacts both America’s social and economic fabric. For instance, in pure economic terms, abortion eliminates a child’s future contributions to society in the form of work. A thorough analysis by the Marriage & Religion Research Institute found that abortion costs the economy between $70 billion and $135 billion every year, leading to a loss of $10 billion and $33 billion in tax revenue.
Yet, abortion does not just destroy a single person, but also that person’s entire future lineage. Many refer to “ghost abortions” when accounting for the lives lost indirectly from abortion. There are two forms of ghost abortions.
First, an aborted female never gets a chance to have a baby of her own. The average age at which a woman bears her first child is 26, which means all females born between 1973 and 1990 are assumed to have had at least one child. There were 25.4 million abortions over that time period. Assuming half of those abortions were female, 12.7 million people would constitute the population of ghost abortions. Of course, this is a very conservative estimate since some of the women in question could have had two or more children by now.
Second, abortion has been linked to a substantial rise in STDs. One study found that the availability of abortion, because it reduces the personal risk associated with sex, thus contributing to an increase in sexual activity, has caused gonorrhea and syphilis rates to increase by up to 25 percent. As noted in the STD section, gonorrhea is a prime cause of preventable infertility. As such, every baby not born because their would-be-mother was made infertile by the rising incidence of STDs is a member of the ghost abortion population.
An increase in the marriage rate would likely lead to a reduction in the number of abortions. According to the Centers for Disease Control and Prevention, in 2013, only 14.8 percent of all abortions were to married women with the remainder to unmarried women. The abortion ratio is also significantly lower among married women (46 abortions per 1,000 live births) than for unmarried women (387 abortions per 1,000 live births).
Infant mortality, incidences of which amount to a fraction of the number of abortions performed, generally doesn’t carry the moral stigma of abortion—with the possible exceptions of infant mortality due to illicit drug use, smoking, alcohol, and other detrimental activities that are harmful to the baby in utero and post neonatal.
Alarmingly, there are signs that previous reductions in infant mortality may be reversing. For example, between 2000 and 2014, Maine’s infant mortality rate increased by 36 percent—the highest increase of any state. One contributing factor is illustrated on Chart 59, which shows substance-exposed newborns in Maine, as a percent of births, between 2010 and 2015. Over that time period, the percentage of substance-exposed newborns jumped a startling 85 percent to 8 percent of all births in 2015 from 4.3 percent in 2010. At best, these babies will have life-long developmental issues or, at worst, they will face early mortality.
As shown in Chart 60 and Table 7:
STATE HIGHLIGHT: NEW HAMPSHIRE
New Hampshire’s elevated rate of illicit drug use imposes a significant economic and social burden on society. In particular, with the arrival of Demographic Winter (too few young people to maintain current population levels), New Hampshire must maximize the productivity of its existing labor force.
New Hampshire’s illicit drug use (as a percent of population) has always significantly exceeded the national average. In fact, New Hampshire has the 8th highest rate of drug use (10.8 percent), trailing regional neighbors Vermont (2nd, 12.6 percent), Rhode Island (3rd, 12.4 percent), Maine (5th, 11.7 percent), and Massachusetts (7th, 11.2 percent).
Overall, the data shows that the burden of illicit drug use in New Hampshire is not only one of the most substantial in the country, but it is also growing faster than in the rest of the nation. Lowering New Hampshire’s illicit drug use rate to the national average must be a priority. In human terms, that would mean 37,000 fewer Granite Staters using illegal drugs—falling from 144,000 people to 107,000 people.
Before such a reduction can be realized, New Hampshire’s political, business, civic, and religious leaders, as well as the citizens of the state, must have an understanding of the factors that lead people down the path of drug abuse.
Decline In Religiosity
A large and growing body of evidence shows that not only can religion help prevent people from using illicit drugs, but it also plays a strong role in effective treatment programs. Consider the findings of these two comprehensive studies.
First, a study from The National Center on Addiction and Substance Abuse:
God, religion and spirituality are key factors for many in prevention and treatment of substance abuse and in continuing recovery . . . [A]dults who never attend religious services are almost twice as likely to drink, three time likelier to smoke, more than five times likelier to have used an illicit drug other than marijuana, almost seven times likelier to binge drink and almost eight time likelier to use marijuana than those who attend religious services at least weekly . . .
[T]eens who never attend religious services are twice as likely to drink, more than twice as likely to smoke, more than three times likelier to use marijuana and binge drink and almost four times likelier to use illicit drugs than teens who attend religious services at least weekly.
Second, a study from the Annie E. Casey Foundation:
Religion is an important protective factor against substance abuse and an important support for persons in recovery. Religious people are less likely than others to use drugs and less likely to experience negative drug-related consequences.
The importance of this is shown in Chart C, which plots the religious weekly attendance rate and the illicit drug use rate for the 50 states (as averaged between 2008 and 2014). The northeastern states dominate the upper left quadrant of the chart where low religiosity is correlated with high drug use, while deep southern states and Utah dominate the lower right quadrant where high religiosity is correlated with low drug use.
Additionally, religiosity significantly lowers the odds of a person using illicit drugs wherever they may live. In fact, Gallup performed an extensive analysis of its polling data on the rate of marijuana use among various subgroups and found:
Only 2% of weekly churchgoers and 7% of less frequent attenders say they use marijuana, but this rises to 14% of those who seldom or never attend a religious service.
This factor is especially problematic since New Hampshire ranks as the least religious state, based on weekly religious attendance (tied with Vermont), in the country.
Breakdown of the Family
The family plays a very important protective role in combatting illicit drug use because the groundwork for abuse is laid in childhood. In fact, according to The National Center on Addiction and Substance Abuse:
[A] child who gets through age 21 without smoking, using illegal drugs or abusing alcohol is virtually certain never to do so . . . [T]he good news is that parents have enormous power to be a healthy influence on their children, to help steer them from involvement with tobacco, alcohol and drugs. Parents who abstain from cigarettes and illegal drugs, drink responsibly, have high expectations for their children, monitor their whereabouts, know their friends and provide loving support and open communication are less likely to have children who smoke, drink and use drugs. Parents who consistently disapprove of tobacco, alcohol or drug use are much likelier to have teens who grow up drug free. Teens whose parents are ‘hands on’—engaged in their teens’ lives, supervising them, establishing rules and standards of behavior—are at one-fourth the risk of abusing substances. Teens from families where religion is important are less likely to smoke, drink and use drugs. Teens with an excellent relationship with either parent are at 25 percent lower risk for substance abuse; those with excellent relationships with both parents are at a 40 percent lower risk.
And, more specifically, the Center finds that instituting simple family routines, such as having family dinners, can confer this protective shield on their children.
Prison Time For Drug Users
America’s prison system is a revolving door of the incarceration and re-incarceration of people addicted to illicit drugs or subjected to their ill effects. Consider these facts from a comprehensive study published by The National Center on Addiction and Substance Abuse:
First, drug use plays a substantial role in determining whether an individual will end up in prison:
Illicit drugs are implicated in the incarceration of three-quarters (75.9 percent) of all inmates in America. In addition to the inmates who were convicted of a drug law violation, 54.3 percent of alcohol law violators, 77.2 percent of those who committed a property crime, 65.4 percent of inmates who committed a violent crime, and 67.6 percent of those who committed other crimes either committed their crime to get money to buy drugs, were under the influence of drugs at the time of the crime, had a history of regular drug use or had a drug use disorder.
Second, there is a strong correlation between illicit drug use and recidivism:
Substance-involved offenders are likelier to recidivate than those who are not substance-involved. Over half (52.2 percent) of substance-involved inmates have one or more previous incarcerations compared with 31.2 percent of inmates not substance-involved. High rates of recidivism translate into burdensome incarceration costs for society, averaging $25,144 per inmate, per year and ranging from a low of $10,700 in Alabama to a high of $65,599 in Maine. Breaking the cycle of re-arrests and re-incarceration requires breaking the cycle of addiction.
Finally, illicit drug use is at the root of an inter-generational incarceration problem:
In 2016, American prisons and jails held an estimated 1.0 million substance-involved parents with more than 2.2 million minor children; 73.7 percent (1.7 million) of these children are 12 years of age or younger. The minor children of inmates are at a much higher risk of juvenile delinquency, adult criminality and substance misuse than are minor children of parents who have not been incarcerated. Almost four-fifths of incarcerated mothers (77 percent in state prison and 83 percent in federal prison) reported being the primary daily caregiver for their children prior to their imprisonment compared with 26 percent of fathers incarcerated in state prisons and 31 percent incarcerated in federal prisons.
Self-Mortality – Drug Overdose or Suicide?
Complicating matters, there is a distinct relationship between suicide and drug overdoses. While suicide and drug overdoses appear to be unrelated issues, the fact is that many suicides are mistaken for drug overdoses. For instance, according to a recent study:
Official vital statistics indicate that suicide surpassed motor vehicle traffic crashes as the leading cause of injury mortality in the United States in 2009. However, this shift may actually have occurred several years earlier, even while it remained undetected. The rate of pharmaceutical and other drug-intoxication deaths rose by 125% between 2000 and 2013, with most being classified as accident (unintentional injury) or undetermined intent. Many of these deaths were likely misclassified suicides. Suicide is plausibly the most underestimated manner of death in both clinical medicine and public health, since it likely is often obfuscated by death investigations that are inadequate for validly differentiating manner.
More troubling, a new study by the Substance Abuse and Mental Health Services Administration found that in New Hampshire, 10.29 percent of young adults between the ages of 18 to 25 had serious thoughts of suicide (the highest level in the country) in 2013-2014. New Hampshire’s rate was 38 percent higher than the national average (7.44 percent). This suggests that New Hampshire’s suicide and/or drug overdose numbers will remain elevated in the near term.
New Hampshire’s suicide rate, as a percent of population, has not only been higher than the national average, but it is also growing at a faster rate. Between 2000 and 2015, New Hampshire’s suicide rate increased by 62 percent to 0.017 percent (18th highest) from 0.011 percent. Over the same time period, the national average grew by 32 percent to 0.014 percent from 0.01 percent.
New Hampshire’s drug overdose rate, as a percent of population, has also been higher than the national average, and it is also growing at a dramatically faster rate. Between 2000 and 2015, New Hampshire’s drug overdose rate increased by 724 percent to 0.033 percent (2nd highest) from 0.004 percent. Over the same time period, the national average grew by 148 percent to 0.017 percent from 0.007 percent.
Additionally, of particular interest is the fact that both suicides and drug overdoses spiked in New Hampshire between 2013 and 2015, which reinforces the conclusions of the above study showing that many suicides are mistaken for accidental overdoses.
In order for New Hampshire to improve its self-mortality score, it is imperative that policymakers gain a better understanding of the connection between its elevated accidental overdose and suicide rates. This will greatly inform the approach to bringing down both measures since suicide involves a long-term public health focus, whereas drug overdose would feature more of a drug treatment/law enforcement approach.
The Granite State has some deep-seated hopelessness, especially among the younger generations where 1 in 10 now seriously consider suicide. This is fertile ground for illicit drug abuse, which too often leads to overdoses – accidental, as well as intentional. But, it appears, drug overdoses may be the newest face of suicide.
The data suggests that much of this hopelessness may lie in the tremendous institutional flux that has occurred over the decades. Perhaps the most profound is the precipitous decline in religiosity as New Hampshire now ranks among the least religious states in the country. Yet, historically, churches have played a significant role in in the state’s communities as evidenced by the vast number of religious edifices, now standing mostly empty, that dot the landscape.
Drug treatment and law enforcement alone are not enough to curb New Hampshire’s drug epidemic. Granite Staters must figure out why so many of today’s youth find solace in illicit drug use and not in their families, churches, schools, and communities. Otherwise, treatment and enforcement will simply become a revolving door instead of a solution.
Years of Productive Life Lost (YPLL)
As shown in Chart 61, the Years of Productive Life Lost (per 100,000 population) decreased nationally by 4 percent to 7,030 in 2015 from 7,345 in 2000. In 2015, West Virginia had the highest YPLL at 10,622, while California had the lowest at 5,377—a difference of 98 percent.
Overall, for the YPLL sub-index, California had the top score (8.07), followed by New York (7.98), New Jersey (7.74), Hawaii (7.65), and Minnesota (7.63). West Virginia had the lowest score (1.20), followed by Mississippi (1.35), Kentucky (1.66), Alabama (1.79), and Louisiana (2.11).
Charts 62, 63, 64, 65, and 66 show the variance in common health measures—including obesity rate, tobacco use, alcohol use, marijuana use, and illicit drug use other than marijuana—nationally and in the 50 states from 2000 to 2014 for obesity rate and 2002 to 2014 for the other variables.
As shown on Chart 62, the obesity rate (as a percent of the population) increased nationally by 48 percent to 29.6 percent in 2014 from 20 percent in 2000. In 2014, Arkansas had the highest obesity rate at 35.9 percent, while Colorado had the lowest rate at 21.3 percent—a difference of 69 percent.
As shown on Chart 63, the tobacco use rate (as a percent of population) decreased nationally by 16 percent to 21 percent in 2014 from 24.9 percent in 2002. In 2014, West Virginia had the highest tobacco use rate at 31.6 percent, while Utah had the lowest rate at 13.7 percent—a difference of 131 percent.
As shown in Chart 64, the alcohol use rate (as a percent of population) increased nationally by 4 percent to 43.4 percent in 2014 from 41.6 percent in 2002. In 2014, New Hampshire had the highest alcohol use rate at 55.3 percent, while Utah had the lowest rate at 24.7 percent—a difference of 124 percent.
As shown in Chart 65, the marijuana use rate (as a percent of population) increased nationally by 30 percent to 6.6 percent in 2014 from 5.1 percent in 2002. In 2014, Colorado had the highest marijuana use rate at 12.2 percent, while South Dakota had the lowest rate at 3.9 percent—a difference of 216 percent.
As shown in Chart 66, the illicit drug use other than marijuana rate (as a percent of population) decreased nationally by 11 percent to 2.7 percent in 2014 from 3.1 percent in 2002. In 2014, Colorado had the highest illicit drug use other than marijuana rate at 3.4 percent, while Wyoming had the lowest rate at 1.7 percent—a difference of 101 percent.
Overall, for the risk behavior sub-index, Utah had the top score (7.37), followed by Hawaii (6.98), Idaho (6.76), South Dakota (6.49), and Texas (6.42). Arkansas had the lowest score (3.49), followed by Delaware (3.85), Vermont (3.86), Mississippi (3.91), and Wisconsin (3.94).
Note: The obesity rate, tobacco use rate, alcohol use rate, marijuana use rate, and illicit drug use other than marijuana rate were all weighted equally in the risk behavior sub-index.
Sexually Transmitted Disease
Charts 67, 68, 69 and 70 show the variance in sexually transmitted diseases—including gonorrhea, chlamydia, syphilis, and HIV diagnoses—nationally and in the 50 states from 2000 to 2015 for gonorrhea, chlamydia, and syphilis, and from 2008 to 2014 for HIV diagnoses.
As shown in Chart 67, the gonorrhea rate (as a percent of the population) decreased nationally by 4 percent to 0.12 percent in 2015 from 0.13 percent in 2000. In 2015, Louisiana had the highest gonorrhea rate at 0.22 percent, while New Hampshire had the lowest rate at 0.02 percent—a difference of 1,096 percent.
As shown in Chart 68, the chlamydia rate (as a percent of the population) increased nationally by 89 percent to 0.47 percent in 2015 from 0.25 percent in 2000. In 2015, Alaska had the highest chlamydia rate at 0.77 percent, while New Hampshire had the lowest rate at 0.23 percent—a difference of 230 percent.
As shown in Chart 69, the syphilis rate (as a percent of the population) increased nationally by 110 percent to 0.0232 percent in 2015 from 0.011 percent in 2000. In 2015, Louisiana had the highest syphilis rate at 0.0528 percent, while Wyoming had the lowest rate at 0.0017 percent—a difference of 2,993 percent.
As shown in Chart 70, the HIV diagnoses rate (as a percent of the population) decreased nationally by 22 percent to 0.0122 percent in 2015 from 0.0157 percent in 2008. In 2015, Louisiana had the highest HIV diagnoses rate at 0.0242 percent, while New Hampshire had the lowest rate at 0.0017 percent—a difference of 1,365 percent.
Overall, for the sexually transmitted diseases sub-index, New Hampshire had the best score (7.28) followed by Vermont (6.82), Maine (6.74), Wyoming (6.63), and West Virginia (6.48). Louisiana had the lowest score (1.45), followed by Georgia (2.67), North Carolina (3.03), Mississippi (3.39), and Florida (3.39).
Note: The gonorrhea rate, chlamydia rate, syphilis rate, and HIV diagnoses rate were all weighted equally in the sexually transmitted diseases sub-index.
Charts 71 and 72 show the variance in infant survival—including abortion and infant mortality—nationally and in the 50 states from 2000 to 2013 for abortions, and 2000 to 2014 for infant mortality.-
As shown in Chart 71, the abortion rate (as a percent of births) decreased nationally by 26 percent to 24.3 percent in 2013 from 32.7 percent in 2000. In 2013, New York had the highest abortion rate at 50.8 percent, while Wyoming had the lowest rate at 1.8 percent—a difference of 2,701 percent.
As shown in Chart 72, the infant mortality rate (as a percent of births) decreased nationally by 17 percent to 0.59 percent in 2014 from 0.7 percent in 2000. In 2014, Alabama had the highest infant mortality rate at 0.88 percent, while New Hampshire had the lowest rate at 0.43 percent—a difference of 106 percent.
Overall, for the infant survival sub-index, South Dakota had the top score (7.00) followed by Utah (6.79), Missouri (6.51), Kentucky (6.42), and Idaho (6.33). Maryland had the lowest score (1.51), followed by New York (1.72), Florida (2.83), Delaware (3.35), and New Jersey (3.44).
Note: The abortion rate was weighted 90 percent and the infant mortality rate was weighted 10 percent in the infant survival sub-index.
The time-series abortion data from the Guttmacher Institute was provided sporadically from 2000 to 2011. Missing years (2001, 2002, 2003, 2006, and 2009) were linearly interpolated.
The time-series was extended to 2012 by using new CDC data. Growth rates between the 2011 and 2013 CDC data were applied to the Guttmacher Institute data. However, four states do not report abortion data to the CDC—California, Maryland, New Hampshire, and Wyoming—so their 2012 and 2013 data is based on a 5-year linear extrapolation.
Charts 73 and 74 show the variance in self-mortality—including suicide and drug-induced deaths—nationally and in the 50 states from 2000 to 2015.
As shown in Chart 73, the suicide rate (as a percent of the population) increased nationally by 32 percent to 0.0138 percent in 2015 from 0.0104 percent in 2000. In 2015, Alaska had the highest suicide rate at 0.0272 percent, while New York had the lowest rate at 0.0083 percent—a difference of 226 percent.
As shown in Chart 74, the drug-induced death rate (as a percent of the population) increased nationally by 148 percent to 0.0173 percent in 2015 from 0.007 percent in 2000. In 2015, West Virginia had the highest drug-induced death rate at 0.0407 percent, while Nebraska had the lowest rate at 0.0073 percent—a difference of 455 percent.
Overall, for the self-mortality sub-index, Nebraska had the best score (6.92), followed by New York (6.85), California (6.73), Texas (6.60), and New Jersey (6.34). West Virginia had the lowest score (2.60), followed by Alaska (2.65), New Mexico (2.98), Wyoming (3.15), and New Hampshire (3.16).
Note: The suicide rate and drug overdose rate were weighted equally in the self-mortality sub-index.
Jump to Section:
 “The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General” U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2014. http://www.surgeongeneral.gov/library/reports/50-years-of-progress/full-report.pdf
 Bouchery, Ellen E., Brewer, Robert D., Harwood, Henrick J., Sacks, Jeffrey J., and Simon, Carol J., “Economic Costs of Excessive Alcohol Consumption in the U.S., 2006,” American Journal of Preventive Medicine, Vol. 41, No. 5, 2011. http://www.ajpmonline.org/article/S0749-3797(11)00538-1/pdf
 Hammond, Ross A. and Levine, Ruth, “The Economic Impact of Obesity in the United States,” Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 2010:3, pp. 285-295. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3047996/pdf/dmso-3-285.pdf
 Cawley, John and Meyerhoefer, Chad, “The Medical Care Costs of Obesity: An Instrumental Variables Approach,” Journal of Health Economics, Vol. 31, No. 1, January 2012, pp. 219-230.
 Davis, Alyssa, “In U.S., Opioids Viewed as Most Serious Local Drug Problem,” Gallup, July 29, 2016. http://www.gallup.com/poll/194042/opioids-viewed-serious-local-drug-problem.aspx
 “The Economic Impact of Illicit Drug Use on American Society,” U.S. Department of Justice: National Drug Intelligence Center, April 2011. http://www.justice.gov/archive/ndic/pubs44/44731/44731p.pdf
 “Incidence, Prevalence, and Cost of Sexually Transmitted Infections in the United States,” Centers for Disease Control and Prevention, CDC Fact Sheet, February 2013. http://www.cdc.gov/std/stats/sti-estimates-fact-sheet-feb-2013.pdf
 Ibid. Due to the possibility of a person having multiple infections, 110 million infections does not translate directly into 110 million people infected.
 Gerberding, Julie Louise, “Report to Congress: Infertility and Prevention of Sexually Transmitted Diseases 2000 – 2003,” Centers for Disease Control and Prevention, November 2004. http://www.cdc.gov/std/infertility/ReportCongressInfertility.pdf
 “Antibiotic Resistance Threats in the United States, 2013,” U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, pp. 55-56, September 16, 2013. http://www.cdc.gov/drugresistance/threat-report-2013/index.html
 Data from the Guttmacher Institute: http://www.guttmacher.org/datacenter/table.jsp Missing years were linearly interpolated. 2012 abortion estimate was based on data from the Centers for Disease Control and Prevention (see section on Infant Survival for details).
 Higgins, Anna and Potrykus, Henry, “Abortion: Decrease of the U.S. Population & Effects on Society,” Marriage & Religion Research Institute, January 22, 2014. http://downloads.frc.org/EF/EF14A55.pdf
 Hamilton, Brady E. and Matthews, T.J., “Mean Age of Mothers is on the Rise: United States, 2000-2014,” Centers for Disease Control and Prevention, NCHS Data Brief, No. 232, January 2016. http://www.cdc.gov/nchs/data/databriefs/db232.pdf
 Klick, Jonathan and Stratmann, Thomas, “The Effect of Abortion Legalization on Sexual Behavior: Evidence from Sexually Transmitted Diseases,” Journal of Legal Studies, Vol. 32, June 2003, pp. 407-433. https://www.law.upenn.edu/fac/jklick/32JLS407.pdf
 Ewing, Alexander, Jamieson, Denise J., Jatlaoui, Tara C., Mandel, Michele G., Pazol, Karen, Simmons, Katharine B., and Suchdev, Danielle B., “Abortion Surveillance – United States, 2013,” Centers for Disease Control and Prevention, Morbidity and Mortality Weekly Report, Surveillance Summaries, Vol. 65, No. 12, November 25, 2106. https://www.cdc.gov/mmwr/volumes/65/ss/ss6512a1.htm
 Davis, Thomas, Delucchi, Kevin L., Guydish, Joseph, Wolfe, Ellen L., “Mortality Risk Associated with Perinatal Drug and Alcohol Use in California,” J Perinatol, Vol 25, No. 2, 2005, pp. 93-100. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3349286/pdf/nihms374014.pdf
 Data provided via email request to the Maine Office of Child and Family Services. Note: *These numbers reflect the number of infants born in Maine where a healthcare provider reported to the Office of Child and Family Services that there was reasonable cause to suspect the baby may be affected by illegal substance abuse or demonstrating withdrawal symptoms resulting from prenatal exposure (illicit or prescribed appropriate under a physician’s care for the mothers substance abuse treatment) or who have fetal alcohol spectrum disorders.
 “The Economic Impact of Illicit Drug Use on American Society,” U.S. Department of Justice: National Drug Intelligence Center, April 2011. http://www.justice.gov/archive/ndic/pubs44/44731/44731p.
 The full New Hampshire study can be found here: http://www.familyprosperity.org/application/files/6814/7346/9685/NH-Illicit-Drug-Use-Study-WEBrev2.pdf
 “So Help Me God: Substance Abuse, Religion and Spirituality,” The National Center on Addiction and Substance Abuse, November, 2001. http://www.centeronaddiction.org/download/file/fid/1198
 Myers, Valerie L., Osai, Esohe, and Wallace John M., “Faith Matters: Race/Ethnicity, Religion and Substance Abuse,” The Annie E. Casey Foundation, January, 2005. http://www.aecf.org/m/resourcedoc/aecf-faithmattersRaceReligionUse-2004.pdf
 McCarthy, Justin, “One in Eight U.S. Adults Say They Smoke Marijuana,” Gallup, August 8, 2016. http://www.gallup.com/poll/194195/adults-say-smoke-marijuana.aspx
 “Family Matters: Substance Abuse and The American Family,” The National Center on Addiction and Substance Abuse, March, 2005, pgs. i, ii. http://www.centeronaddiction.org/download/file/fid/1191
 “The Importance of Family Dinners VIII,” The National Center on Addiction and Substance Abuse, September, 2012. http://www.centeronaddiction.org/download/file/fid/378
 “Behind Bars II: Substance Abuse and America’s Prison Population,” The National Center on Addiction and Substance Abuse, February, 2010. http://www.centeronaddiction.org/download/file/fid...
 Ibid, pg. 13.
 Ibid, pg. 5.
 Ibid, pg. 4.
 Rockett, Ian R. H.; Hobbs, Gerald R.; Wu, Dan; Jia, Haomiao; Nolte, Kurt B.; Smith, Gordon S.; Putnam, Sandra L.; and Caine, Eric D., “Variable Classification of Drug-Intoxication Suicides across US States: A Partial Artifact of Forensics?” PLoS One, August 21, 2015. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546666/
 Hughes, Arthur; Lipari, Rachel N.; and Williams, Matthew, “State Estimates of Past Year Serious Thoughts of Suicide Among Young Adults: 2013 and 2014,”Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration, June 16, 2016. http://www.samhsa.gov/data/sites/default/files/report_2387/ShortReport-2387.pdf
 U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, Substance Abuse and Mental Health Services Administration: Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health (http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33).
 U.S. Department of Health & Human Services: Centers for Disease Control and Prevention (http://www.cdc.gov/brfss/brfssprevalence/) and Substance Abuse and Mental Health Services Administration: Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health (http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33).
 U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) Atlas. http://www.cdc.gov/NCHHSTP/Atlas/
 Abortion data from Guttmacher Institute (http://www.guttmacher.org/datacenter/trend.jsp) and U.S. Department of Health & Human Services: Centers for Disease Control and Prevention, Abortion Surveillance (http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6410a1.htm?s_cid=ss6410a1_e).
 Infant mortality data from U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, National Center for Health Statistics. The data was extracted from the Kids Count Data Center published by the Annie E. Casey Foundation. http://datacenter.kidscount.org/data/tables/6051-infant-mortality?loc=1&loct=2#detailed/2/2-52/false/36,868,867,133,38/any/12718,12719
 U.S. Department of Health & Human Services: Centers for Disease Control and Prevention, National Center for Health Statistics, Underlying Cause of Death 1999-2014 on CDC Wonder Online Database. http://wonder.cdc.gov/