Activity 1

You are reading an interesting article called “EGF receptor is required for KRAS-induced pancreatic tumorigenesis” (Ardito et al. Cancer Cell. 2012; 22: 304–317). You would like to find more articles like this one. Using the Internet resources we discussed earlier, please find:

1. one more article similar to this one that is also published in Cancer Cell

2. two review articles related to this article, one in Cancer Cell and one in any other journal

Activity 2

From the abstract below, please answer the following questions.

1. What is the objective of the study? Please circle it in the abstract.

2. Did lifestyle intervention affect weight loss? If so, was the difference in weight loss greater at 1 year or at the end of the study?

3. What is the major conclusion? Did lifestyle intervention and weight loss reduce cardiovascular events in diabetic patients?

4. How many patients were enrolled? How many were men?

Weight loss is recommended for overweight or obese patients with type 2 diabetes on the

basis of short-term studies, but long-term effects on cardiovascular disease remain

unknown. We examined whether an intensive lifestyle intervention for weight loss would

decrease cardiovascular morbidity and mortality among such patients. In 16 study centers

in the United States, we randomly assigned 5145 overweight or obese patients with type 2

diabetes to participate in an intensive lifestyle intervention that promoted weight loss

through decreased caloric intake and increased physical activity (intervention group) or to

receive diabetes support and education (control group). The primary outcome was a

composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal

stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. The trial

was stopped early on the basis of a futility analysis when the median follow-up was 9.6

years. Weight loss was greater in the intervention group than in the control group

throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive

lifestyle intervention also produced greater reductions in glycated hemoglobin and greater

initial improvements in fitness and all cardiovascular risk factors, except for low-density-

lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the

intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-

years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval,

0.83 to 1.09; P=0.51). An intensive lifestyle intervention focusing on weight loss did not

reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes.

(Look AHEAD Research Group. N Engl J Med. 2013; 369: 145–154.)

Activity 3

You have 3 Introductions and 3 Discussions. After identifying the key information in each (circle the objectives and conclusions), match each Introduction with the appropriate Discussion.

Sugawara N, et al. BMC Psychiatry. 2013; 13: 108.

Pratt KJ, et al. Health and Quality of Life Outcomes. 2013; 11: 116.

Mohler-Kuo M, et al. BMC Public Health. 2013; 13: 1028.

Introduction 1

Obesity is a growing public health concern, as is becoming more prevalent among patients with schizophrenia

compared with the general population. Previous studies have shown that being overweight is a major risk

factor for metabolic syndrome, cardiovascular diseases, and premature death. Furthermore, this risk is nearly

twice that of the general population among patients with schizophrenia. In addition, obesity among patients

with schizophrenia is associated with high medication costs, low self-esteem, poor psychosocial adaptation,

non-compliance with an antipsychotic medication regime and reduced quality of life (QOL).

QOL can be defined as the impact of illness and condition on the physical and mental functioning from the

point of view of the patient. Patients with schizophrenia have low QOL. Previous studies of Western

populations have shown that the QOL of patients with schizophrenia further decreased with obesity. However,

we are not aware any study concerning this issue among Asian populations, who have a different obesity

prevalence and lifestyle from Western populations. QOL can be used to assess how patients feel and function

in their everyday life with regard to a treatment, and a good QOL may improve the measurement of treatment

efficacy. Directly treating QOL concerns can both improve a patient’s QOL and attenuate symptoms of the

disorder; thus, understanding the association between obesity and QOL would be useful.

This investigation evaluated the relationship between body weight and the self-reported QOL of XXXX

patients with schizophrenia. To our knowledge, this study is the first of this nature conducted with an XXXX

population.

Introduction 2

Childhood obesity is identified as a nationwide epidemic that affects youth regardless of gender, age, race or

ethnic group. Current statistics show that 31.8% of youth between the ages of 2 to 19 are diagnosed as

overweight (having a BMI above the 85th percentile for their sex and age) and 16.9% are diagnosed as obese

(having a BMI above the 95th percentile for their sex and age). This epidemic has prompted development of a

set of recommendations for treating obesity in youth. The report, entitled Expert Committee

Recommendations Regarding the Prevention, Assessment, and Treatment of Child and Adolescent

Overweight and Obesity summarizes the findings of the currently accepted practices for childhood obesity

prevention, assessment, intervention, and treatment. The report details four stages of childhood obesity

treatment: 1) prevention plus; 2) structured weight management; 3) comprehensive, multidisciplinary

intervention, and 4) tertiary care intervention. These recommendations incorporate several elements such as

family involvement and the inclusion of multidisciplinary providers in order to provide optimal

biopsychosocial care for youth and families. Clinically, for youth who have been gaining weight up until they

initiate treatment, decreases in weight gain, leveling of current weight, and subsequent weight loss are all

considered successes. These “successes” are considered clinically significant as progress in treatment, even

though over a short time period they may not be statistically significant or yet large enough yet to impart

substantial decrease in health risk.

One method to comprehensively evaluate how weight may impact youth both biologically (or physically) and

psychosocially is to formally assess quality of life (QOL) using standardized inventories such as the Pediatric

Quality of Life Inventory™ (PedsQL). The PedsQL inventory is used to assess the respondent’s quality of life

by measuring physical, emotional, social, and school functioning, thus providing physical and psychosocial

outcomes in one tool. The PedQL is used both as a research assessment and a clinical tool for treatment teams

who are working with overweight youth. Clinically, it is important to measure QOL in both the overweight

youth and their caregiver since often perceptions differ regarding how the youth is doing physically,

emotionally, socially, and in school. Providers can talk about the discrepancy in youth and caregiver QOL

reports to gauge more accurately where to focus efforts and goals. Often youth have a difficult time talking

about areas of QOL where they may have impairments; the PedQL can be a tool to note specific areas where

the treatment team may be able to focus on goals or make appropriate referrals. For example, if a youth

mentions they often feel down or low (emotional domain), the treatment team can discuss the youth’s

response, get their caregiver’s perspective of the youth’s emotional health, and determine how to incorporate

or refer out to address this issue. When investigating the relationship between obesity and QOL in youth some

researchers have concluded that there is not an impaired QOL, but most report that QOL is inversely related

to weight. As a youth’s weight increases, his or her QOL decreases, so the most overweight youth have the

most significantly impaired QOL. Schwimmer et al. found that obese youth are 5.5 times more likely than

healthy youth to have impaired QOL, making QOL for an obese youth similar to that of a youth diagnosed

with cancer.

In addition to impaired QOL, it is known that youth who are obese have increased likelihood for

psychological problems that may persist into adulthood as compared to youth who are not obese. Overweight

treatment seeking youth report more depressive symptoms compared with their normal weight and non

treatment seeking peers. Obese youth with increased depressive symptoms reported lower QOL. Due to the

lack of longitudinal data, it is unclear how specific psychological issues (e.g., youth and maternal depression)

influence QOL over time and/or with treatment for obesity. This exploratory study follows a cohort of obese

youth and their caregivers during treatment and assesses for changes in and associations with QOL,

depression and body mass index (BMI) z-score.

We sought to understand further how patient QOL and depression change over time with treatment for obesity.

Our purpose is to describe the changes during treatment from youth and caregiver baseline variables in QOL,

teen depression status, and youth (child/teen) BMI and BMI z-score from baseline through two follow-up

visits.

Introduction 3

Excessive weight, and especially obesity, is a major public health concern for several reasons. First, the

number of individuals who are either overweight or obese has reached epidemic proportions in the United

States and many European countries. Relative to other industrialized countries, Switzerland’s prevalence of

excess weight is relatively low, but nevertheless has increased over the years. In a recent Swiss Health Survey

(SHS 2007), 30.4 % of the total adult population were overweight and an additional 8.5 % obese. Second,

excessive weight is associated with increased morbidity and mortality.

However, deviations from normal weight might not only affect the physical health of a person, but also more

psychosocial domains. In order to comprehensively understand a person’s subjective perspective on all these

multiple life domains, the concept of health- related quality of life (HRQOL) can be used. Published studies

that have utilized this outcome indicate that being overweight or at least being obese (mostly assessed via

body mass index; BMI) is related to compromised HRQOL.

In addition to BMI and waist circumference, health-risk behaviors contribute further to the prediction of

reduced HRQOL. This has been demonstrated repeatedly for low physical activity. To date, other health-risk

behaviors, such as substance use, have infrequently been (thoroughly) considered as covariates. Furthermore,

it is evident that investigators who included such health-risk behaviors primarily focused on smoking

cigarettes, whereas other substances like alcohol were only rarely incorporated. Concurrently including

multiple health-risk behaviors (i.e., not only physical inactivity but also substance use), while studying the

associations between BMI categories and HRQOL, might be especially important among young men, because

risky substance use is quite common in this age-sex-group [39]. Furthermore, the just-mentioned health-risk

behaviors seem to be associated with BMI, as well as with negative HRQOL.

Besides not including a broad range of health-risk behaviors, existing studies about the association between

BMI and HRQOL are limited, because they often relied upon clinical samples, which might have led to an

overestimation of the negative effect of excessive weight on HRQOL. Furthermore, underweight individuals

were often neglected, even though they also suffer from compromised HRQOL, an effect that seems to be

especially pronounced among men.

Due to the above-mentioned limitations, the main aim of the present analysis was to examine associations

between BMI (from underweight through obesity) and HRQOL, while thoroughly considering multiple

health-risk behaviors (low physical activity, risky alcohol consumption, daily cigarette smoking, frequent

cannabis use) in a population-based sample of young XXXX men.

Discussion 1

In order to explore longitudinal changes, we assessed QOL, depressive symptoms, and BMI z-score indicators

for overweight youth over time. Overall, across three visits (V1-V2-V3), our results indicated youth’s BMI z-

score decreased slightly, their QOL significantly increased, and teen depression level improved. Likewise,

caregivers’ perception of their youth’s QOL increased across three visits.

Interestingly, youth from V1 to V2 and V1 toV3 had significant improvements in their QOL, despite their

BMI z-score and the majority of our sample being either obese or severely obese. This is especially important

to consider, given that other researchers have reported that quality of life is inversely related to weight; as a

youth’s weight increased, his/her QOL decreased, suggesting that the most overweight youth have the most

significantly impaired QOL. In a cross-sectional study, Williams et al. compared youth of different BMI

categories (normal, overweight, obese). In that research, obese youth were found to have a lower QOL than

their normal and overweight peers. However, previous longitudinal research focusing on differences between

youth in different severity categories of obesity (i.e., obese vs. severely obese) has not been done; our results

indicate that even those who are most obese (severely obese or ≥ 99th percentile) had positive results in QOL

with treatment, even with only modest improvements in BMI and no change in weight category.

After adjusting for time, improvement in teen depression (PHQ9A score) was strongly related to QOL

improvement. This result emphasizes potential value in assessing for depression (in the teen and caregiver) in

tandem with a QOL inventory. While past researchers have assessed for youth or caregiver depression or for

QOL, none published to date have assessed for youth depression longitudinally in tandem with a QOL

inventory. In light of our observed significant association between QOL and PHQ9A, our results suggest that

with treatment using an integrated model emphasizing both physical and psychosocial factors, in obese youth

both QOL and depression can improve even when BMI change is modest. In childhood obesity treatment,

BMI improvement is ultimately the goal; however after youth make improvements in QOL and depression

they may be more able and confident to adopt and work toward goals that result in weight-loss.

In order to address the different ways obesity affects both physical and psychosocial variables for youth and

their family, these findings suggest benefit to using brief validated measures, such as the PedsQL to explore

youth and caregiver perceptions of youth’s QOL and the PHQ9A to assess depression in teens and caregivers.

In addition, there may be additional benefit to clinicians and researchers tracking youth longitudinally

throughout treatment to investigate the relationship between youth’s QOL and those who level or decline in

BMI verses those who increase or gain; specifically, to help determine if there is a certain QOL threshold that

youth may reach before they begin to show signs of weight loss. Addressing both physical and psychosocial

variables within medical treatment, as now recommended in care recommendations, is one way to incorporate

these factors into the complex care of obese youth and their families and hopefully enhance overall success of

treatment.

Overall, across three visits our results indicated youth’s BMI z-score decreased slightly, their QOL

significantly increased, and teen depression level improved. Likewise, caregivers’ perception of their youth’s

QOL increased across three visits. Youth in our study, despite their BMI z-score, had significant

improvements in QOL. Given that the majority of our sample was obese or severely obese, this is an

important point that contests previous research which suggests that the most overweight youth have the most

significantly impaired QOL. Additionally, after adjusting for time, improvement in teen depression was

strongly related to QOL improvement which punctuates the value in assessing for depression simultaneously

with a QOL inventory.

Discussion 2

In the present population-based study, 76.3 % of young XXXX men were of normal weight, whereas 3.3 %

were underweight, 16.5 % overweight and an additional 3.9 % obese, percentages that are similar to those

identified in the 2007 XXXX Health Survey among males in the same age range (18 to 31 years:

underweight: 2.1 %; normal weight: 69.8 %; overweight: 24.2 %; obese: 3.9 %). In terms of how weight

affects HRQOL, we found that deviations from normal weight in both directions were associated with

compromised HRQOL. Both overweight and obese men claimed reduced physical HRQOL relative to normal

weight individuals, whereas underweight conscripts suffered from compromised mental HRQOL.

Surprisingly, obese men reported better mental HRQOL. Health-risk behaviors as well as socio-demographic

characteristics contributed to the prediction of HRQOL, as well.

Consistent with previous studies, we found that low levels of physical activity are associated with a less

favorable BMI (i.e., lower prevalence of normal weight; and with worse HRQOL. Regarding alcohol, various

studies indicate that drinking large quantities on a single occasion is associated with an increased BMI. Our

results differ from this pattern, possibly because men with a risky drinking pattern were physically more

active than men who did not report at-risk RSOD (results not shown; comparable to). In other words, it is

possible that men with a risky drinking pattern did not gain weight because they participated in moderate to

high-level physical activity. That a risky drinking pattern only is associated with compromised HRQOL in the

mental but not physical domain is consistent with the results of other studies.

Daily smokers were, in our sample, more often overweight or obese than non- or occasional smokers, a result

that also has been observed in other studies that included young adults. The reduced physical HRQOL among

smokers also has been reported previously, one potential explanation for it being the negative effect this

health-risk behavior has on respiratory function. Initially, the crude OR indicated that daily cigarette smoking

was associated with reduced mental HRQOL. However, the association became non-significant after we

adjusted for other covariates. This result contradicts earlier findings. However, the non-significant result was

primarily due to adjusting for other covariates like the risky use of cannabis. Lastly, that at-risk cannabis

users both had a lower prevalence of excessive weight and reduced mental well-being is consistent with

earlier studies.

These limitations notwithstanding, among young men living in XXXX, it appears that being overweight or

obese is associated with compromised physical HRQOL, while being underweight is associated with reduced

mental HRQOL. These findings hold true even after controlling for important health-risk behaviors and socio-

demographic characteristics. Hence, preventive programs should aim not just to promote weight loss in those

who are overweight, but weight gain in those whose weights are below normal. This being said, it also must

be kept in mind that obese young men might tend to appraise their mental HRQOL positively, an effect that

could be explained by response shift. Such a change in the appraisal of one’s HRQOL might reduce an obese

man’s willingness to lose weight.

From a practical/interventional standpoint, the present study provided insights that may be used for the

conceptualization of public health programs. For example, promoting a moderate to high physical activity

level could be a potent starting point for such a program, because this health-promoting behavior not only

positively affects BMI, it also enhances physical and mental HROQL. Furthermore, we found that excessive

weight and frequent smoking often co-occur among young men; hence, both these major health-risk factors

must be targeted. Lastly, programs targeting weight normalization should especially focus upon people of low

socio-economic status, because they are characterized by a worse distribution of BMI and particularly

compromised HRQOL.

With respect to future research, the present investigation demonstrates how important it is to include multiple

health-risk behaviors when studying the relationship between BMI and HRQOL. Especially when studying

young men, such associations must be taken into account.

Discussion 3

The present study is the first to examine the association between obesity and the QOL of patients diagnosed

with schizophrenia in an XXXX population. In this sample, 16.4% of participants with schizophrenia were

obese. After adjusting for confounds, three domains of mental health and the MCS score were significantly

and positively associated with an overweight status. In addition, obesity was significantly and negatively

associated with two domains of physical health, two domains of mental health, and the PCS score in the same

model.

Previous studies have found a relationship between obesity and QOL among patients with schizophrenia in

XXXX populations. Allison and colleagues investigated the relationship between QOL and weight gain

among 286 patients with schizophrenia. After adjusting for confounds, they found that weight gain was

significantly associated with a poorer overall QOL score according to a 16-item scale. Another study from the

XXXX used the SF-36 and found an association between obesity and some QOL items among 143 patients

with schizophrenia. Worse physical functioning, general health, role emotional functioning, and a lower PCS

score were observed among obese participants. Faulkner and colleagues reported that a PCS score of SF-12

was associated with BMI and waist circumference among 90 patients with schizophrenia. Furthermore,

Kolotkin and colleagues studied 111 patients with schizophrenia and 100 patients with bipolar disorder and

found that obese patients had poorer vitality, social functioning, role emotional functioning, and mental health

and lower MCS scores than those patients who were not obese. The contradictory results concerning the

overweight group in our study may be due to cultural or ethnic differences. XXXX participants who were

overweight may have fewer negative attitudes regarding their weight than XXXX participants of a similar

weight. Another explanation is that the prevalence of obesity in our study was lower than that of the studies of

XXXX populations. In addition, some studies have compared each QOL domain among patients with

schizophrenia using a mixed subject pool of patients who were either overweight or obese.

Our findings have implications for clinicians who treat patients with schizophrenia. First, obesity adds to the

burden of schizophrenia not only via physical health risks but also reduced health-related QOL. The cause of

obesity among patients with schizophrenia has not been determined completely. However, patients with

schizophrenia are at risk for developing obesity due to poor dietary habits, lower resting energy expenditures,

a lack of exercise, and limited activity due to their negative symptoms. Previous studies have shown that non-

pharmacological interventions can reduce body weight. Effective treatments are necessary, and these range

from nutritional interventions to cognitive behavioral therapy. Second, a pervasive impairment in QOL among

patients with schizophrenia may cause poor adherence or even premature discontinuation of treatment

because of weight gain. A previous study of patients with schizophrenia showed that both BMI and subjective

distress from weight gain predicted noncompliance with medications even after adjusting for other possible

confounds. Obese patients are also more than twice as likely as those patients with normal BMIs to report

noncompliance with medication.

Obesity has a significant and negative impact on the QOL of patients with schizophrenia regardless of

symptom severity and their attitudes toward antipsychotics. Previous studies suggest that long-term programs

that incorporate nutrition, exercise, and behavioral interventions can prevent weight gain among patients with

schizophrenia. An intervention program aimed at reducing obesity has the potential to improve patient health-

related QOL among patients with schizophrenia.