The association of obesity with the likelihood of arrest for young adults.

This paper examines whether obesity is associated with the likelihood of arrest. We hypothesize that obese individuals are less likely to commit crime and be arrested because their body weights may prevent them from successfully engaging in certain criminal activities, particularly those that are physically intensive. To test this hypothesis, we use the National Longitudinal Survey of Youth 1997 and panel data techniques and find that obesity is negatively related to arrest. In one specification, for example, we found that the odds of an obese man being arrested are 64% of those of a healthy weight man. The social costs of obesity may be overstated if obesity reduces the likelihood of arrest because the obese are less criminally active.

Cooperation and conflict between very similar occupations: the case of anesthesia.

This article examines the features of a labor market in which there are two professional groups that both cooperate and directly compete with each other: certified registered nurse anesthetists (CRNAs) and anesthesiologists (MDAs). We examine how the relative numbers of these two types of anesthesia providers, and differences in regulation, affect the earnings of CRNAs, and the extent of supervision of CRNAs by MDAs. We find that both the earnings, and the likelihood of medical supervision of CRNAs, are closely determined by their market share. As the market share of CRNAs increases from 0% to 50%, the gains to MDAs from restricting competition increase; over this range the likelihood that CRNAs are supervised increases and their expected earnings decline. However, as the CRNAs' market share increases beyond 50%, the costs to MDAs of anticompetitive measures become too large, therefore, the probability of supervision declines, and the earnings of CRNAs increase.

Does education matter? Major League Baseball players and longevity.

The authors used duration analysis to examine the longevity of Major League Baseball players. Using data on players who were born between 1945 and 1964, the authors found that the hazard rate of death for players who only attended high school was almost 2.0 times higher than those players who attended a 4-year university, evidence that the educaton [sic]-health link applies to professional athletes. Another important determinant of longevity was race. In addition, a player's body mass index was positively associated with a higher hazard of death. Compared with the general population, the death rate of baseball players was lower--the observed number of deaths in the dataset was only 31% of the expected number. Findings in this article are likely attributable to education being correlated with other variables that affect longevity, most likely intelligence and time preference.

Income, employment and suicidal behavior.

BACKGROUND: Little is known about the labor market outcomes of people who have attempted suicide or thought about suicide. METHODS: We used micro-level data from the first wave of the National Epidemiologic Survey on Alcohol and Related Conditions 2001-2002 to examine the effects of suicidal behavior on income and employment. The data provide a representative sample of the U.S. population, with its primary purpose to provide information on alcohol use disorders for the civilian non-institutionalized population aged 18 and over. The data include employment, income, and other socioeconomic and demographic information on respondents. Since the survey included 43,093 people, the data include a large number of respondents who attempted suicide or thought about committing suicide. We estimated earnings regressions and logit and ordered logit employment regressions. We used methods of IV estimation as well as two stage linear probability models to address potential endogeneity of suicidal behavior while estimating regressions separately by sex, since there are significant differences in suicide rates, suicide attempts, and suicidal ideation between men and women. RESULTS: We find that suicide attempts and suicidal ideation are negatively related to personal income and the probability of employment. The effects differ by sex. Men and women who attempted suicide had mean earnings lower by 16 and 13 percent, respectively. This amount reflects the combined effect of suicidal behavior and mental illness. With instrumental variable regression, the magnitude of the effects becomes larger-for example, as much as 50 percent decrease in the income of males who attempted suicide. Thoughts of suicide negatively affect income but to a smaller extent. Logit and ordered logit regressions indicate that attempted suicide reduces the probability of fulltime employment by over 20 percentage points for men and approximately 17 percentage points for women. IMPLICATIONS: People who engaged in suicidal behavior reported significantly lower employment and earnings. Although data were insufficient to directly address the issue, it appears the effect may persist over a long period of time. This is particularly troubling since health insurance is closely tied to employment and without health insurance, treatment options may be limited.

The effect of state laws on the supply of advanced practice nurses.

This paper considers how the decision to enter advanced practice nursing (e.g., the occupations of nurse practitioner, certified nurse-midwife, nurse anesthetist, and clinical nurse specialist) is affected by State laws on the scope of practice of APNs. We find that enrollments in APN programs are 30 percent higher in States where APNs have a high level of professional independence. Our work differs from previous studies by estimating a fixed effects model on cross-sectional and time series data, to avoid problems of endogeneity of State laws.

Estimating episode lengths when some observations are probably censored.

This paper analyses a case in censored failure time data problems where some observations are potentially censored. The traditional models for failure time data implicitly assume that the censoring status for each observation is deterministic. Therefore, they cannot be applied directly to the potentially censored data. We propose an estimator that uses resampling techniques to approximate censoring probabilities for individual observations. A Monte Carlo simulation study shows that the proposed estimator properly corrects biases that would otherwise be present had it been assumed that either all potentially censored observations are censored or that no censoring has occurred. Finally, we apply the estimator to a health insurance claims database.

Estimating Determinants of Multiple Treatment Episodes for Substance Abusers.

BACKGROUND: Health services researchers have increasingly used hazard functions to examine illness or treatment episode lengths and related treatment utilization and treatment costs. There has been little systematic hazard analysis, however, of mental health/substance abuse (MH/SA) treatment episodes. AIMS OF THE STUDY: This article uses proportional hazard functions to characterize multiple treatment episodes for a sample of insured clients with at least one alcohol or drug treatment diagnosis over a three-year period. It addresses the lengths and timing of treatment episodes, and the relationships of episode lengths to the types and locations of earlier episodes. It also identifies a problem that occurs when a portion of the sample observations is ǣpossibly censored. Failure to account for sample censoring will generate biased hazard function estimates, but treating all potentially censored observations as censored will overcompensate for the censoring bias. METHODS: Using insurance claims data, the analysis defines health care treatment episodes as all events that follow the initial event irrespective of diagnosis, so long as the events are not separated by more than 30 days. The distribution of observations ranges from 1 day to 3 years, and individuals have up to 10 episodes. Due to the data collection process, observations may be right censored if the episode is either ongoing at the time that data collection starts, or when the data collection effort ends. The Andersen-Gill (AG) and Wei-Lin-Weissfeld (WLW) estimation methods are used to address relationships among individuals multiple episodes. These methods are then augmented by a probit censoring model that estimates censoring probability and adjusts estimated behavioral coefficients and related treatment utilization and treatment costs. There has been little systematic hazard analysis, however, of mental health/substance abuse (MH/SA) treatment episodes. RESULTS: Five sets of variables explain episode duration: (i) individual; (ii) insurance; (iii) employer; (iv) binary, indicating episode diagnosis, location, and sequence; and (v) linkage, relating current diagnoses to previous diagnoses in a sequence. Sociodemographic variables such as age or gender have impacts at both the individual and at the firm level. Coinsurance rates and deductibles also have impacts at the individual and the firm levels. Binary variables indicate that surgical/outpatient episodes were the shortest, and psychiatric/outpatient episodes were the longest. Linkage variables reveal significant impacts of prior alcoholism, drug, and psychiatric episodes on the lengths of subsequent episodes. DISCUSSION: Health care treatment episodes are linked to each other both by diagnosis and by treatment location. Both the AG and the WLW models have merit for treating multiple episodes. The AG model permits more flexibility in estimating hazards, and allows researchers to model impacts of prior diagnoses on future episodes. The WLW model provides a convenient way to examine impacts of sociodemographic variables across episodes. It also provides efficient pooled estimates of coefficients and their standard errors. LIMITATIONS: The insurance claims data set covers 1989 through 1991, predating current managed care plans. It cannot identify untreated substance abusers, nor can it identify those with out-of-plan use. It provides treatment information only if services are covered by the insurance plan and are defined with a substance abuse diagnosis code. Like medical records, insurance claims will not specify substance abuse treatment received within the context of other health care (and thus identified by a non-substance abuse diagnosis code) or community services. IMPLICATIONS FOR POLICY AND RESEARCH: This article characterizes multiple health treatment episodes for a sample of insured clients with at least one alcohol or drug treatment diagnosis within a three-year period. We identify both individual and employer effects on episode length. We find that episode lengths vary by the diagnosis type, and that the lengths (and by inference cost and utilization) may depend on the treatments that occurred in previous episodes. We also recognize that health care or illness episodes may be ongoing at times of health care events prior to the ends of data collection periods, leading to uncertain episode lengths. Corresponding estimates of costs or utilization are also uncertain. We provide a method that adjusts the episode lengths according to the probability of censoring.