Assessment of Child and Adolescent Overweight and Obesity
-- Krebs et al. 120 (4): S193 -- Pediatrics
Here's a 36-page review, incl 336 citations. It purports to review assessment methods, and indeed it includes skinfolds and WC. But it avoids mentioning waist-to-height so far as I can tell.
I think that's strange for such a comprehensive review article.

Important REVIEW of Carbohydrates -- European Journal of Clinical Nutrition -- alert Volume 61 Issue S1

Joint FAO/WHO Scientific Update on Carbohydrates in Human Nutrition
Table of Contents
"As part of the normative work and the complimentary mandates of the two organizations to periodically update nutrient requirements and regularly develop related global guidelines, FAO and WHO have been exploring the possibility of holding an expert consultation to update the work of the 1997 Expert Consultation. Considered necessary given the developments and other relevant recommendations made during the intervening period, including those from the 2002 Joint WHO/FAO Expert Consultation (WHO, 2003), FAO and WHO agreed in 2005 to undertake a scientific update on some of the key issues related to carbohydrates in human nutrition. The key issues identified included terminology and classification, measurement, physiology, carbohydrates and diseases (that is, obesity, diabetes mellitus, cardiovascular diseases and cancer), and glycaemic index and glycaemic load. This update of existing knowledge and evidence relating to the current recommendations was viewed as essential in the process leading up to a forthcoming Expert Consultation on Carbohydrates in Human Nutrition."

Sweet, Sour, Salty, Bitter. and Umami

Sweet, Sour, Salty, Bitter… and Umami

So we have time to learn a Japanese word "Umani" (not a exactly word for delicious, I think), and look beyond. By the way, Umani in Chinese is "Xian"
The full story: Sweet sour salty bitter and Umami

Talking Too Much On a Job Interview May Kill Your Chance

Talking Too Much On a Job Interview May Kill Your Chance  
On the eve of Halloween, here's a scary thought: You can blow a promising opportunity by talking too much during a job interview.
That's how one facilities administrator ruined her employment chances at Clark Nuber, a small accounting firm in Bellevue, Wash. Asked to describe her strengths, the applicant delivered a long-winded reply focused on her cleaning of every cabinet in her home. "She probably went on for three to four minutes," recalls Tracy White, the firm's human-resources director. "I doubted she could get the job done in an eight-hour day."
Many nervous job seekers blabber endlessly about irrelevant information. They create a poor impression and cut short the hiring manager's time for further questions. "That official won't pay any attention to you unless you prove you're sharp during the first five minutes," cautions Robin Ryan, a career counselor, author and speaker in Newcastle, Wash.
"Oversharing in an interview is the most dangerous thing you can do," concurs Annie Stevens, a managing partner at ClearRock, a Boston executive-coaching and outplacement concern.
Don't despair. Here are four ways to steer clear of verbosity during a job hunt:
• Prepare short statements on how your background matches the job. Rehearse.
When a hiring manager says, "Tell me about yourself," you can offer a few war stories that recount a work problem, your corrective action and the measurable result. "The stories have to be powerful as well as engaging," lasting no longer than two minutes apiece, says Rich Gee, an executive coach in Stamford, Conn.
He helped Ward Smith, a talkative golf pro and instructor, to win a marketing spot with Black & Decker. During practice sessions with the coach, Mr. Smith supplied elaborate detail about the golf irons that he recommended to students. A hiring manager "doesn't need to know this," Mr. Gee interjected.
Mr. Smith soon realized he should translate "what I was doing into what Black & Decker was looking for," and keep it succinct. During his job interview, he used marketing lingo to describe briefly his teaching methods, explaining how he identified students' objectives, forged a rapport and enabled them to reach solutions. He now is an Atlanta field-marketing coordinator for a Black & Decker unit.
Embracing a similar approach, a jobless organizational-development consultant recently landed follow-up interviews with three possible employers. Callbacks rarely occurred when I "was running off at the mouth," he remembers. Defining yourself concisely also "builds an enormous amount of confidence for the next interview," he notes.
• Make sure you understand a question. Stop every couple of sentences to check.  
If the interviewer requests your career history, you might inquire, "Do you want me to start with my present situation or at the beginning?" This type of response demonstrates a candidate "is preparing mentally for what's he's going to give me," says Peter D. Crist, head of recruiters Crist Associates in Hinsdale, Ill.
Pausing after you speak lets you collect your thoughts -- and seek permission to continue. Before you resume, Ms. White suggests asking, "Did I answer your question enough? Do you want more examples?"
• Watch the interviewer's body language for hints that your answers are getting boring.  
He may stop taking notes, check his watch or glance at his computer. A loquacious middle manager ignored such warning signals after spending 15 minutes telling a West Coast recruiter about several extraneous issues, including her husband's problems with his boss.
"I was rolling my eyes and tapping my pen on her résumé to indicate we should get back to work here,'' the exasperated recruiter says. He finally cut her off because he had many more questions to pose.
• Solicit feedback following an interview.  
The West Coast recruiter decided against referring the middle manager to a client. "You had a number of stories to tell but they weren't relevant," he told her. "Use each minute to its best advantage to sell your background."
With practice, you'll be able to polish your pitch, adjusting the length of your responses until someone says, "You're hired!"

四十岁的女人

１．四十岁的女人，子女尚未长大，老公已经开花。这是一个让女人最焦灼、困惑的年龄，也是女人一生中最敏感、关键的过渡。要开始修心养性，要做到语调平缓、目光柔和、神态优雅、举止从容。

２．四十岁的女人，在事业方面无须过于计较。有一份自己喜欢、愿意为之认真努力的工作便可。若非要在职场上与同龄男人拼个你死我活，那无异于将一辆QQ轿车驶向了F1赛道。

３．四十岁的女人，要有一两样经过岁月洗礼、可以寄托信念的物品。无论是祖辈相传还是定情信物，在你难过流泪的时候可以将它握在手中，当你孤独无助的时候有它相伴相随。

４．四十岁的女人，相当于一辆已经行驶了十四万公里的汽车。务必要做到每六个月检查一次身体，尽早发现如乳腺、卵巢、内分泌系统等疾病。

５．四十岁的女人，要抓紧补充钙质和营养，中年女性百分之七十都有不同性质的骨质疏松症状。胸部可以下垂，皮肤可以松懈，但切记：骨头一定要坚挺。这将使你在五、六十岁的时候受益无穷。

６．四十岁的女人，无论多少要藏一些私房钱，放在贴身隐秘的地方以备不时之需。万一碰到昔日恋人落难或者哪天离家出走不必再向老公伸手要钱。

７．四十岁的女人，可以不掌管经济大权，但要了解小钱的走向，尤其要注意男人的皮夹。譬如，经常晚上开会的丈夫为什么身上总是少个三五百，时不时连续加班的老公又在哪里"遗失"了一两千。

８．四十岁的女人，要将头发束起、衣领提高、裤腰收紧、裙摆放低。纵使身材依旧完好也无需显山露水、故意炫耀。要记住，身段在这个年龄能为你换来的东西已经非常有限。

９．四十岁的女人，不要再过多地涂脂抹粉，这些化妆品虽然在遮盖方面功能强大，却会摧毁你那历经岁月的皮肤。建议经常补充水份以舒缓纹理，多用保湿类和紧致类的护肤品方可延容益颜。

10．四十岁的女人，不要花枝招展、不要妖冶惑众，不要与你们的天敌（二、三十岁的女人）去一争高低。她们有她们的青春和活力，你有你的沉淀和修养。日月转换、江山多娇，此乃不可违抗的自然规律。

11. 四十岁的女人，不要再沉寂于"好男"、"快男"这些智障节目，也别再相信你是一位身份未明、不慎迷失，等待王子前来拯救的公主。水晶鞋穿了四十年也破了，南瓜马车坐了四十年也垮了，与其幻想与小白脸的爱情，不如认真经营自己的婚姻。

12. 四十岁的女人，要避免和男性在麻将桌上消磨时光，那里不但有碍健康，还是黄杏出墙的温床。洗牌时手指无心接触，打牌时腿脚有意碰撞，都是祸害的根源。有数据表明，在出轨中年女性中高达百分之二十五的比例是发生在麻将桌上的。

13. 四十岁的女人，独守空房催人老，孤影自怜心易碎。假如老公不喜欢回家，建议还是要每天烧好晚饭，将他的碗筷和他喜欢的老酒端正的供在桌前。如此持续一段时间，任何良知尚存的男人都会回心转意。

14. 四十岁的女人，如果怀疑老公出轨不要穷追猛打，也无须捉奸在床。身体和灵魂若能挽回其一最好拯救灵魂，如果两者皆飞那就要痛定思痛。真到了曲终人散、劳燕分飞的地步，要尽快找到一个可以救赎自己的方法。

15. 四十岁的女人，可以豪爽但不要豪放，可以浪漫但不要浪荡。你路过了你理当路过的风景，也行驶了你应该行驶的里程。不要心有不甘，不要挂档倒退。把该记忆的记忆，该剔除的剔除。要让四十岁成为美丽的风景，而不是情欲的陷阱。

16. 四十岁的女人，不要大嘴长舌、在别人背后说三道四，也不要喋喋不休、将老公的耳膜击穿。有调查显示，喜欢唠叨的四十岁女性的离婚率是不喜欢唠叨的1.5倍。将唠叨减少一半，把声调降低一倍，会换来更和谐的婚姻和家庭，这其中的奥妙你一试便知。

17. 四十岁的女人，富有于心，成熟于智。要坦然面对这个年龄，不要为过去惆怅，也无需为将来迷茫。春去秋来、花开花落，冥冥之中早有安排。女人走好四十往后的道路有如好书合上、好戏落幕，将赋予此生更多地美感和质感。

18. 四十岁的女人，尽量少去伤肝动火，要宽容待人，要矜持有度，纵使本文作者在篇幅中有什么不当的言辞也不要跟帖骂人。
文章引用自： 朱威廉 http://blog.sina.com.cn/s/blog_4b7ab97601000af3.html

四十岁的男人

1． 四十岁的男人，如果还没有结婚，就别结了。无论你是一次未娶还是多次失败，你的身心已经到了不健康的地步，再把这种不健康带给别人是不负责任的。如果可以做到清心寡欲，独自漫步，也能活的自在。

2． 四十岁的男人，如果一事无成，就难成了。十几年的教育，二十几年的社会，这些都没整出点动静来，就不要为难自己了。当然，没出息的也有没出息的活法：好吸的抽两根小烟，好喝的咪两口小酒，好赌的打两副小牌，好色的看两张小碟。放低目标、摆平心态，日子也照样能过的舒舒服服。

3． 四十岁的男人，如果还没去过K房或者桑拿，最好抽空去一次。倘若有美色、美酒当前却依旧坐怀不乱，那么，你就真正达到了不惑的境界。不惑是一种高度，是一种层次，这其中的美妙待我四十岁时再与你细细道来。

4． 四十岁的男人，不要再像二、三十岁那样，目不斜视、直勾勾地盯着女士着装暴露的部位。纵使心里波涛起伏，也要注意形象得体。非礼勿视、若非要视、最好斜视。

5． 四十岁的男人，如果活得不开心，那估计是要把这份不开心带到棺材里去了。要放宽心胸，成就大小与金钱无关，是否风光无需载入史册。要记住：芸芸众生、人来人往，不是谁都能傲视天下，这其中有命、有运。走过、路过即可，不要耿耿于怀，更不要愤世嫉俗。

6． 四十岁的男人，成就过一两件事情很不容易，什么事情都没做成过更不容易。对于那些一事无成者虽然为时已晚，但大器晚成的例子从古至今、跨越东西也比比皆是。只要还相信自己，就值得再去放手一搏。

7． 四十岁的男人，别把自己的身材搞得一塌糊涂。臀部下垂和腹部隆起不是四十岁男人的专利。腾出些时间适当运动一下，譬如打打球、跑跑步都能对身心的抗老化起到积极的作用。

8． 四十岁的男人，当官的要清廉不垮，经商的要纳税守法，打工的切忌伸手乱拿。二、三十岁犯个什么错还能洗心革面、重新来过，四十岁再来次失足落马可就苦海无边、回天乏术了。

9． 四十岁的男人，应多尽些孝道，事业再怎么大，工作再怎么忙也要抽出些时间陪老人们吃吃饭、聊聊天，传承中华民族优秀精神的同时，也传递一个家庭互爱的传统，给后辈做出榜样。要记住：你怎么对待你的父母，你的后代就会怎么对待你。

10． 四十岁的男人，生活在一个瞬间万变、规则不明的巨大的时代反差里；在一个前不着村、后不着店的年龄中承担着心理和生理的双重变化难免有诸多的焦虑和烦恼。要注重内心修炼，要辨明是非取舍，要懂得照顾自己。

11． 四十岁的男人，纵使有钱到了令人发指的地步，也不要去包养什么二奶小蜜。不管是谁征服了谁，最终使坏的都是金钱。而金钱这东西虽然没有长腿，却和有腿的跑得一样快。除此以外，在这个时代，只要你身旁站着一个比你老婆光鲜靓丽却不是你老婆的女人你就会变得猥琐起来，在旁人看来这不是钱色交易就是权色交易。

12． 四十岁的男人，大多已为人父，最好有一两件精彩的人生故事与你的子女分享。这些故事无需惊天动地、鬼哭神泣，但要让你的子女们知道他们有一个并不庸俗的父亲，身上流淌着不寻常的血液。这个信念在他们未来的人生当中会起到至关重要的作用。

13． 四十岁的男人，要多参加几次葬礼。人生至此已行将过半，在中途先参观一下终点可以让自己消除恐惧的心理，驱赶过一天算一天的麻痹，得以更加感激生命、感激生活、感激岁月。

14． 四十岁的男人，最好每年做两次体检。医疗保险和人寿保险至少要各买一份，要未雨绸缪的为妻子和子女做些安排。四十岁是男人病症高发期，万一不幸需要先行一步，至少能给亲人们留下一份嘱托和希望。

15． 四十岁的男人，要远离二十岁的女孩，无论她多么楚楚动人，无论她多么飞蛾扑火。她尚处桃李年华，而你理当知天命、知是非。若真心欢喜，就不要给她一条泥泞坎坷、异常艰辛的道路。

16． 四十岁的男人，要有肩膀，要扛得起风雨，要承担得起生活的重负。即使再苦再累，也要给妻子一床温暖的被褥，给孩子一个避风的港湾，给家庭一份不悔的承诺。

17． 四十岁的男人，应该去读一些佛法、圣经之类的书籍。要理解，这浩荡人世之外的玄妙；要领悟，这生命一次又一次的轮回；要看到，这滚滚红尘背后的因果；要畏惧，有一双神秘的眼睛，一直在注视着我们。

18．四十岁的男人，就算到四十了也别怕。如果碰到有80后嘲讽年龄，用王朔老师的一句话回击最淋漓至尽：你们牛B什么，不就年轻么？老子也年轻过，可你们老过么?

文章引用自： 朱威廉

Trends in Health and Aging

Trend Analysis

• Trend analysis is a statistical approach to evaluate the linear or nonlinear relationships between two variables. When we talk about the secular trend, one of those variables is time.
• Usually, I tabulate the estimates by grouped time periods at first
• Then, use a regression model [log(rate)] to evaluate trends with calendar time
• Or, Age-Period-Cohort model [log(rate)] to evaluate calendar time trends accounting for age or cohort effects
• We can also use ANOVA (ANalysis Of VAriance) with contrast coefficients (polynomial contrasts, orthogonal polynomial coefficient)
• NCHS (2018, No. 179). National Center for Health Statistics Guidelines for Analysis of Trends in "Series 2. Data Evaluation and Methods Research"
• Yin (2016). Statistical Methods and Software Package for Medical Trend Analysis in Health Rate Review Process
• HealthKnowledge: Time-trend analysis, time series designs
• NCI Software: Joinpoint is statistical software for the analysis of trends using joinpoint models. 
• Kim (2000). Permutation tests for joinpoint regression with applications to cancer rates
• Chandler (2011). Statistical methods for Trend Detection and Analysis in the Environmental Sciences

SUDAAN and Collinearity

Tips: SUDAAN and Collinearity

Dear B,

I have another question about SUDAAN. The following article states that -

"Although SUDAAN controls for collinearity by default, separate regression analyses were performed in each model with SAS (SAS Institute, Inc, Cary, NC) for statistical diagnosis."

Q1: Does SUDAAN really control for collinearity by default?
Q2: If not, how do I test it?

Again, I really appreciate your help.
X

Dear X,

Q1: Does SUDAAN really control for collinearity by default?

SUDAAN does not control for collinearity. When betas (coefficients) get too big or too small (e.g. in logistic) SUDAAN will output whatever answer it computes and also issues a warning message about the possible existence of collinear variables. As far as I know, no software available controls for multicollinearity either. There are statistics that you can request in some software (e.g. SAS) to assess multicollinearity and some actions that you can take in order to alleviate the problem.

Q2: If not, how do I test it?

As you may know, multicollinearity in logistic regression (I am assuming that you are working with logistic regression) models is a result of strong correlations between independent variables.

Effect of multicollinearity:

The existence of multicollinearity inflates the variances of the parameter estimates. That may result, particularly for small and moderate sample sizes, in lack of statistical significance of individual independent variables while the overall model may be strongly significant.

Multicollinearity may also result in wrong signs and magnitudes of regression coefficient estimates, and consequently in incorrect conclusions about relationships between independent and dependent variables.

How to detect multicollinearity?

1-Start with examining the correlations (continuous and ordinal variables) and associations (nominal variables) between independent variables.

However, in some situation, when no pair of variables is highly correlated, but several variables are involved in interdependencies, it may not be sufficient.

2-It is better to use multicollinearity diagnostic statistics produced by linear regression analysis (PROC REG with options VIF TOL in SAS). 

For nominal independent variables, create dummy variables for each category except one (it will become a reference category). Use the dependent variable from logistic regression analysis or any other variable that is not one of the independent variables, as a dependent variable in the linear regression. The collinearity diagnostic statistics are based on the independent variables only, so the choice of the dependent variable does not matter.

Examine Tolerance and Variance Inflation Factor for each variable. Since for each independent variable, Tolerance = 1 – Rsq, where Rsq is the coefficient of determination for the regression of that variable on all remaining independent variables, low values indicate high multivariate correlation. 

The Variance Inflation Factor (VIF) is 1/Tolerance, it is always >= 1 and it is the number of times the variance of the corresponding parameter estimate is increased due to multicollinearity as compared to as it would be if there were no multicollinearity. 

There is no formal cutoff value to use with VIF for determining presence of multicollinearity. Values of VIF exceeding 10 are often regarded as indicating multicollinearity, but in weaker models, which is often the case in logistic regression, values above 2.5 may be a cause for concern (Reference: P.D. Allison, Logistic Regression Using the SAS System, SAS Institute).

What to do about multicollinearity?

In some cases, variables involved in multicollinearity can be combined into a single variable. If combining variables does not make sense, then some variables causing multicollinearity need to be dropped from the model.

Examining the correlations between variables and taking into account practical aspects and importance of the variables help in making a decision what variables to drop from the model.

Hope it helps.

Best,

B

  

The Annals of Internal Medicine - Statistical Guidelines (from 2006)

The Annals of Internal Medicine - Statistical Guidelines

http://www.annals.org/shared/author_info_stats.html

Advice for Students: Taking Notes that Work - lifehack.org
lifehack.org - They offer up advice and tips on how to make the best use of your time and how to accomplish things without spending a fortune. They are also are platform agnostic and always recommend interesting and helpful apps for Windows, Mac, and Linux users to try out, though their focus is not on software. Content is upbeat, lively, and constantly changing. And when we say constantly we mean it, every day they seem to post yet another useful essay or article. Really great stuff, and written always in a straightforward non-hyped way, with almost no fluff.

The Rise and Fall of Epidemiology Revisited

The rise and fall of epidemiology, 1950 2000 A.D.
Kenneth J Rothman
Int. J. Epidemiology. 2007 36: 708-710.
http://ije.oxfordjournals.org/cgi/content/full/36/4/708?etoc

Commentary: Epidemiology still ascendant
Kenneth J Rothman
Int. J. Epidemiol. 2007 36: 710-711.
http://ije.oxfordjournals.org/cgi/content/full/36/4/710?etoc

Commentary: Epidemiology and futurology why did Rothman get it wrong?
Cesar G Victora
Int. J. Epidemiol. 2007 36: 712-713.
http://ije.oxfordjournals.org/cgi/content/full/36/4/712?etoc

Commentary: The rise and rise of corporate epidemiology and the narrowing
of epidemiology's vision
Neil Pearce
Int. J. Epidemiol. 2007 36: 713-717.
http://ije.oxfordjournals.org/cgi/content/full/36/4/713?etoc

Commentary: Epidemiology needs the patients to survive
J W W Coebergh
Int. J. Epidemiol. 2007 36: 717-719.
http://ije.oxfordjournals.org/cgi/content/full/36/4/717?etoc

Commentary: Is epidemiology really dead, anyway? * A look back at Kenneth
Rothman's 'The rise and fall of epidemiology, 1950 2000 AD'
Michel P Coleman
Int. J. Epidemiol. 2007 36: 719-723.
http://ije.oxfordjournals.org/cgi/content/full/36/4/719?etoc

Parables of the River - The end of Type 2 Diabetes?

The end of Type 2 Diabetes?

I REALLY like this story forwarded by LG (below the video). Here is ideo (Pablo & Bruno).

Parables of the River
I have been working on introductions to learning modules for a community organizing course I will be teaching online in the Fall. One of the things I wanted to include was what some community organizers call the “Parable of the River” (or sometimes a waterfall) that is often attributed to Saul Alinsky. I was searching across the Internet to find a good representation of the parable and found a wide range of different versions. (To avoid writing introductions, I seem to have ended up writing this post . . . .) Interestingly, it seems like there are versions of this parable with a different perspective than that used by community organizers. And this different version seems somewhat more prevalent among those oriented towards more traditional social service.

First an example of a “community organizing” version of the parable:

Once upon a time there was a small village on the edge of a river. The people there were good and life in the village was good. One day a villager noticed a baby floating down the river. The villager quickly swam out to save the baby from drowning. The next day this same villager noticed two babies in the river. He called for help, and both babies were rescued from the swift waters. And the following day four babies were seen caught in the turbulent current. And then eight, then more, and still more!
The villagers organized themselves quickly, setting up watchtowers and training teams of swimmers who could resist the swift waters and rescue babies. Rescue squads were soon working 24 hours a day. And each day the number of helpless babies floating down the river increased. The villagers organized themselves efficiently. The rescue squads were now snatching many children each day. While not all the babies, now very numerous, could be saved, the villagers felt they were doing well to save as many as they could each day. Indeed, the village priest blessed them in their good work. And life in the village continued on that basis.

One day, however, someone raised the question, "But where are all these babies coming from? Let’s organize a team to head upstream to find out who’s throwing all of these babies into the river in the first place!"

Now a different version of this parable:

While walking along the banks of a river, a passerby notices that someone in the water is drowning. After pulling the person ashore, the rescuer notices another person in the river in need of help. Before long, the river is filled with drowning people, and more rescuers are required to assist the initial rescuer. Unfortunately, some people are not saved, and some victims fall back into the river after they have been pulled ashore. At this time, one of the rescuers starts walking upstream

“Where are you going?” the other rescuers ask, disconcerted. The upstream rescuer replies, “I’m going upstream to see why so many people keep falling into the river.” As it turns out, the bridge leading across the river up- stream has a hole through which people are falling. The upstream rescuer realizes that fixing the hole in the bridge will prevent many people from ever falling into the river in the first place.

In both parables, the key issue is that those trying to rescue the drowning people are making an error by focusing on the current emergency rather than on what is causing the emergency. As a result, they have no hope of actually solving the problem.

A key distinction between them is that in the first parable an agent is assumed to be causing the babies to fall in the river. In the second the problem is simply technical, with no agent attached. The bridge “has” a hole (note the passive voice).

This tendency to obscure the agents behind oppression and social harm may be a key difference between what I would term a “community organizing” approach and more familiar “social service” and “social science” approaches. From social service and social science perspectives there simply are these problems that need to be solved. The highest level of action is identifying and addressing the (usually impersonal) causes of shared problems.
Importantly, this approach generally obscures the activity of the agents who are perpetuating social challenges through their action or inaction.

Perhaps some of the tendency to avoid seeking out responsible agents is a result of the enormous challenges involved in identifying someone or some institution that one can definitively say is causing a particular problem. But maybe part of the problem is this focus on “causes” in the first place. In fact, the “cause” question can become a pretty complex, ultimately unsolveable existential challenge with no clear solution. Is the cause of pollution from a coal plant the owners of the plant, or bad government standards, or perverse incentives that make clean production unprofitable, or any of an innumerable set of other influences? What is the “cause” of the fact that so many poor kids have difficulty reading?
In my experience, as social scientists, most educational scholars tend to draw from the second version of this parable rather than the first. There “are” problems and we need technical solutions to solve them. In fact, to the many scholars who tend to avoid thinking about “causes,” even the limited insights of the second parable seem like a revelation.
In contrast, when organizers are looking for targets (see earlier post) they aren’t really worried about who or what is the “cause” of a problem. Instead, they try to figure out who can or should be made responsible for the problem now that we have it. In other words, the challenge for a community organizer is to identify the agent that can be induced to solve the problem, regardless of the vast chain of influences that produced it. The aim is to build a coherent link between specific agents and a specific social problem, and the substance of such a link can vary widely.

From an organizing perspective, many people and institutions have resources that are not fairly shared, and the aim is to find ways to force some subset of these agents to use their resources in more equitable ways.

To simplify the distinction I am making, here, one might say that social scientists and social service people tend to focus on “what” caused a problem and “how” to solve the problem, while organizers focus on “who” can solve the problem. And in many cases, answering “what” and “how” questions seem like pre-organizing issues. Sometimes, of course, getting people to figure out the answers to these questions themselves in a collective manner can be tools for engaging, educating, and organizing them, but often this does not seem to be the case.

One limitation of a focus on causes and solutions without focusing on agents is that each agent will be linked to different resources and different possible actions. In other words, different agents imply different solutions. Perhaps more problematically, failing to focus on the identification of realistic agents of change often creates an enormous unbridgeable gulf between theoretical solutions and actual solutions.

Here is a somewhat relevant example that indicates some of the differences between the social science approach and the organizing approach: We have been working on the beginnings of an effort to transform dental care for low-income urban children. For a range of reasons, we want to fight for a school-based dental treatment program. And we have identified an agent and avenue of change—the state health department and the state health insurance program. But there is no clear established “blue chip” model or “solution” to fight for. So we have stepped back, and I have been working with the state dental school and local district officials to get a pilot school-based services project funded. A local “proof of concept” effort would provide the basis for a program blueprint that we could then fight for on a state level. To a large extent, however, this social science investigation work is “pre-organizing.”

Two final observations:
First, there is a key problem with this parable in both of its versions. It represents those who are harmed as powerless victims, often babies. But people are rarely entirely powerless, and organizers never approach people as if they were powerless or babies. It seems odd that this central parable used by many organizers contains such a disempowering metaphor at its core.

Second, it is interesting to note that in a version that Stanley Cohen says he got from Alinsky, “a fisherman is rescuing drowning people from a river. Finally, he leaves the next body to float by while he sets off upstream ‘to find out who the hell is pushing these poor folks into the water.’ According to Cohen, Alinsky used this story to make a further ethical point: ‘While the fisherman was so busy running along the bank to find the ultimate source of the problem, who was going to help those poor wretches who continued to float down the river?’”

An interesting website

A new kind of surveillance system?

http://whoissick.org/sickness/

Endocrine Regulation of Energy Metabolism by the Skeleton Cell -- Lee et al.

Endocrine Regulation of Energy Metabolism by the Skeleton

http://www.cell.com/content/article/fulltext?uid=PIIS0092867407007015

The regulation of bone remodeling by an adipocyte-derived hormone implies that bone may exert a feedback control of energy homeostasis. To test this hypothesis we looked for genes expressed in osteoblasts, encoding signaling molecules and affecting energy metabolism. We show here that mice lacking the protein tyrosine phosphatase OST-PTP are hypoglycemic and are protected from obesity and glucose intolerance because of an increase in β-cell proliferation, insulin secretion, and insulin sensitivity. In contrast, mice lacking the osteoblast-secreted molecule osteocalcin display decreased β-cell proliferation, glucose intolerance, and insulin resistance. Removing one Osteocalcin allele from OST-PTP-deficient mice corrects their metabolic phenotype. Ex vivo, osteocalcin can stimulate CyclinD1 and Insulin expression in β-cells and Adiponectin, an insulin-sensitizing adipokine, in adipocytes; in vivo osteocalcin can improve glucose tolerance. By revealing that the skeleton exerts an endocrine regulation of sugar homeostasis this study expands the biological importance of this organ and our understanding of energy metabolism.

Updated Physical Activity Guidelines

INDIANAPOLIS – All healthy adults ages 18 to 65 years need moderate-intensity aerobic physical activity for at least 30 minutes on five days each week or vigorous-intensity aerobic physical activity for at least 20 minutes on three days each week, according to updated physical activity guidelines released today by the American College of Sports Medicine (ACSM) and the American Heart Association (AHA).

Further, adults will benefit from performing activities that maintain or increase muscular strength and endurance for at least two days each week. It is recommended that 8-10 exercises using the major muscle groups be performed on two non-consecutive days. To maximize strength development, a resistance (weight) should be used for 8-12 repetitions of each exercise resulting in willful fatigue.

1. Moderate-intensity physical activity has been clarified.

2. Vigorous-intensity physical activity has been explicitly incorporated into the recommendation.

3. Specified: Moderate- and vigorous-intensity activities are complementary in producing health benefits, and a variety of activities can be combined to meet the recommendation.

4. Specified: Aerobic activity is needed in addition to routine activities of daily life.

5. More is better.

6. Short bouts of exercise are OK.

7. A muscle-strengthening recommendation is now included.

8. Wording has been clarified.

For detail click here

How to test whether the change among surveys in one group is equal to the change in the other groups?

1. Scenery

We have a table below:

	NHES (S1)	N I (S2)	N II (S3)	N III (S4)	N IV (S5)	Change (C)
BMI Group	High Cholesterol (%> 240 mg/dl)
< style=""> (G1)	27.1	22.3	22.1	13.8	15.2	-11.9 (C1)
25.0 – (G2)	39.2	33.1	31.2	23.3	18.7	-20.5 (C2)
> 30 (G3)	38.9	33.1	31.5	23.0	17.9	-21.0 (C3)

Age and sex-adjusted trends in CVD risk factors, by level of obesity and survey year in the

We want to know: Ho: C1 = C3.

2. Algorithm Solution

Recall:

Y= α*(S5, G1) + β₁*(S1) + β₂*(S2) + β₃*(S3) + β₄*(S4) + β₅*(G2) + β₆*(G3)

+ β₇*(S1, G2) + β₈* (S1, G3) + β₉*(S2, G2) + β₁₀*(S2, G3) + β₁₁*(S3, G2)

+ β₁₂*(S3, G3) + β₁₃*(S3, G2) + β₁₄*(S3, G3)

And: Prevalence of high cholesterol in NHES (S1) among persons with normal BMI (G1)

[S1-G1] = α + β₁ = 27.1, and

[S5-G1] = α = 15.2, then

C1 = [S5-G1] - [S1-G1] = 15.2 – 27.1 = -11.9

Also:

[S1-G3] = α + β₁ + β₆ + β₈ = 38.9, and

[S5-G3] = α + β₆ = 17.9, then

C3 = [S5-G3] - [S1-G3] = -21.0

So:

When we test whether C1 = C3, we are going to test:

α - (α + β₁) = (α + β₆) – (α + β₁ + β₆ + β₈),

i.e. β₈ = 0

Same for others:

To test C1 = C2, we are going to test, β₇ = 0

3. Implementation

Using PROC RLOGIST:

proc rlogist data= all;

  nest survey3 strata3 psu3/psulev=3 MISSUNIT;

  weight mecwgt3;

  subpopn age >19;

  subgroup bmigrp agegrp sex survey3 WHITE BMIADHOC;

  levels 3 3 2 5 2 2;

  model High_chol = bmigrp agegrp sex survey3 bmigrp*survey3;

  reflevel survey3 =5 agegrp =1 bmigrp=1;

  pred_eff bmigrp=(1,0,0)*survey3=(1,0,0,0,-1) /name="Survey: first versus last in BMI<25";

  pred_eff bmigrp=(0,1,0)*survey3=(1,0,0,0,-1)/name="Survey: first versus last in 25<BMI<30";

  pred_eff bmigrp=(0,0,1)*survey3=(1,0,0,0,-1)/name="Survey: first versus last in BMI>30";

  PREDMARG BMIGRP SURVEY3 BMIGRP*SURVEY3;

  PRINT BETA P_BETA PREDMRG SEPRDMRG P_PMCON PRMGCON SEPMCON

  /PREDMRGFMT=f7.3 PRMGCONFMT=F7.3 SEPMCONFMT=F7.3;

RUN;

SUDAAN will give us these beta and p value for beta:

-------------------------------

variable beta p value

-------------------------------

BMIGRP,

BY NHES & NHANES

1, 1 0.00 .

1, 2 0.00 .

1, 3 0.00 .

1, 4 0.00 .

1, 5 0.00 .

2, 1 0.33 0.0483 <- b=""> ß7

2, 2 0.32 0.0414

2, 3 0.24 0.1284

2, 4 0.41 0.0130

2, 5 0.00 .

3, 1 0.37 0.0181 <- b=""> ß8

3, 2 0.38 0.0156

3, 3 0.30 0.0350

3, 4 0.44 0.0021

3, 5 0.00 .

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Life course epidemiology
by Yoav Ben-Shlomo

This edition of the International Journal of Epidemiology has four papers and accompanying commentaries that can be conveniently clustered under the heading of life course epidemiology. In the concluding chapter of ‘A life course approach to chronic disease epidemiology’, Diana Kuh and I raised several emerging and common themes that we felt needed to be addressed by future research. These were (i) understanding heterogeneity, (ii) going beyond repeat measures to understand trajectories, (iii) the role of accelerated postnatal weight and height gain and (iv) the use of life cohort cohorts and less conventional designs. All of these topics are addressed to some degree by these publications. ...
for full text article click here