Height, Socioeconomic and Subjective Well-Being Factors among U.S. Women, Ages 49–79 Grace Wyshak* Harvard Medical School, Department of Psychiatry and Harvard School of Public Health, Departments of Biostatistics and Global Health and Population, Boston, Massachusetts, United States of America Abstract Background: A vast literature has associated height with numerous factors, including biological, psychological, socioeconomic, anthropologic, genetic, environmental, and ecologic, among others. The aim of this study is to examine, among U.S. women, height factors focusing on health, income, education, occupation, social activities, religiosity and subjective well-being. Methods/Findings: Data are from the Women’s Health Initiative (WHI) Observational Study. Participants are 93,676 relatively healthy women ages 49–79; 83% of whom are White, 17% Non-White. Statistical analyses included descriptive statistics, chisquare and multivariable covariance analyses. The mean height of the total sample is 63.67 inches. White women are significantly taller than Non-White women, mean heights 63.68 vs. 63.63 inches (p = 0.0333). Among both Non-White and White women height is associated with social behavior, i.e. attendance at clubs/lodges/groups. Women who reported attendance ‘once a week or more often’ were taller than those who reported ‘none’ and ‘once to 3 times a month’. Means in inches are respectively for: White women–63.73 vs. 63.67 and 63.73 vs. 63.67, p = 0.0027. p = 0.0298; Non-White women: 63.77 vs. 63.61 and 63.77 vs. 63.60, p = 0.0050, P = 0.0094. In both White and Non-White women, income, education and subjective well-being were not associated with height. However, other factors differed by race/ethnicity. Taller White women hold or have held managerial/professional jobs–yes vs. no–63.70 vs. 63.66 inches; P = 0.036; and given ‘a little’ strength and comfort from religion’ compared to ‘none’ and ‘a great deal’, 63.73 vs. 63.66 P = 0.0418 and 63.73 vs. 63.67, P = 0.0130. Taller Non-White women had better health—excellent or very good vs. good, fair or poor–63.70 vs. 63.59, P = 0.0116. Conclusions: Further research in diverse populations is suggested by the new findings: being taller is associated with social activities –frequent attendance clubs/lodges/groups’’, and with ‘a little’ vs. ‘none’ or ‘great deal’ of strength and comfort from religion. Citation: Wyshak G (2014) Height, Socioeconomic and Subjective Well-Being Factors among U.S. Women, Ages 49–79. PLoS ONE 9(6): e96061. doi:10.1371/ journal.pone.0096061 Editor: Jerson Laks, Federal University of Rio de Janeiro, Brazil Received December 4, 2013; Accepted April 2, 2014; Published June 4, 2014 Copyright: ß 2014 Grace Wyshak. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The author has no funding or support to report. Competing Interests: The author has declared that no competing interests exist. * E-mail: Wyshak@hsph.harvard.edu Introduction Height has been a subject of interest, discussion and analyses as early as biblical times. For example, ‘‘In the first book of Samuel we read the account of Saul being selected king. While Saul’s qualifications for the job were not described in any detail, there is one attribute specifically mentioned: he was tall.’’ [1]. In the twenty first century (2012), Ozaltin outlined six mechanisms that account for the association between height and adult outcomes— genetic, biological, psychosocial, biomechanical, epigenetic, confounding or endogeniety [2]. Steckel examined the unique and valuable contributions of four biological measures—life expectancy, morbidity, stature, and certain features of skeletal remains—to understand levels and changes in human well-being [3]. In 2009 he notes the increasing interest in height (stature): ‘‘Since 1995 approximately 325 publications on stature have appeared in the social sciences, which is more than a four-fold increase in the rate of production relative to the period 1977–1994’’ [4]. The body of literature on height is global, vast and increasing [4]. Cited here are a selected number of papers that relate to height and a broad range of factors including: genetics, early life development, nutrition, biology, socioeconomic factors [5–9,14– 24,26–29]; medical conditions include infection [6], coronary heart diseases [5], cardiorespiratory disease and cancer mortality [9], dementia [28]; economic factors are income [7,10,15], wages [16,21], wealth [25]; education [8,10]; cognitive skills [7,13]; occupation/workplace, [11,12,15,20,21,29]; psychological factors—success [1,12],choices [13]; for women, reproduction [22] marriage [24], gender inequality [18]; comparisons at the country level [7,8,18,25]. Height, income and education are the primary variables analyzed from The Gallup-Healthways Well-Being Index daily poll of the US population [10]. The general conclusion from the literature cited is: Taller is associated with favorable early environment, nutrition, medical conditions, health, income and education in both men and women. However, there are exceptions: i) the significant PLOS ONE | www.plosone.org 1 June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors association of height and income were not found [14,16]; ii) taller women, but not men, had more upward mobility in both white and blue collar occupations [16]; iii) upward mobility was not associated with health [16]. By analyzing data from a survey of a diverse group of relatively healthy U.S. women, ages 49–79, this study adds to the substantial knowledge base on height and other outcomes. It suggests areas for further research, particularly by its new findings and insights on height with its associations with religiosity and with social behavior (here denoted by attendance at clubs)—two constructs, to my knowledge not heretofore cited in the literature or among the six mechanisms, outlined by Ozaltin, that account for the association between height and adult outcomes of height [2]. categories: 1) less than $10,000 (4.5%), 2) $10,000–19,999 (11.7%), 3) $20,000–34,999 (23.3%), 4) $35,000–49,999 (20.1%), 5) $50,000–74,999 (20.2%), 6) $75,000–99,999 (9,4%), 7) $100, 000–149,999 (6.8%), 8) $150,000 or more (3.9%); and 9) ‘‘Don’t know’’ (3%) and a category, missing (4%). The mode is in the $20,000–34,000 category, the median in the $35,000–49,999 category, interpolated median about $43,000. The eight categories, excluding missing and ‘‘Don’t know’’ were condensed to 5—1) less than $20,000 (16.16%), 2) $20,000–34,999 (23.31%), 3) $35,000–74,999 (40.24%), 4) $75,0000–99,999 (9.43%), 5) $100,000 or more (10.86%). 1. Education: 1) Didn’t go to school (.09%), 2) Grade school (1–4 years) (.38%), 3) Grade school (5–8 years) (1.20%) 4) Some high school (9–11 years) (3.51%), 5) High school diploma or GED (16.15%). 6) Vocational or Training School (9.74%), 7) Some college or Associate Degree (26.49%), 8) College graduate or Baccalaureate Degree (11.39%). 9) Some Postgraduate or professional (11.76%), 10) Master’s degree (15.73%), 11) Doctoral Degree (Ph.D., M.D., J.D., etc.) (2.76%), Missing (0.79%). Condensed into 3 categories: 1) less than high school (22.12%). 2) high school to some college (47.63%) 3) college graduate or more (30.36%). 2. General health—‘‘In general, would you say your health is— on a five point scale: 1) excellent’, 17.7%, 2) very good, 40.2%, 3) good, 31.7%, 4) fair, 8.8%, 5) poor, 0.9%), ‘missing’ 0.7%.’’ 3. ‘‘Likelihood of Depression’’—scaled from 0 to 100—higher more likelihood. Likelihood of depression, a highly skewed continuous variable was dichotomized at less than or equal to the median (0.0073)/greater than the median. 4. ‘‘Religion gives strength and comfort’’—three categories–none 12.5%, a little 24.0%, a great deal 63.0%, missing, 0.5%. 5. ‘‘Attend clubs, lodges, etc.’’—6 categories—1) not at all in the past month, 43.9%; 2) once in the past month; 3) 2 or 3 times in the past month; 4) once a week 8.1%; 5} 2 or 6 times a week 5.6%; 6) every day 0.1%; missing 1.4%; condensed—none (43.89%), monthly (40.91%), weekly or more (13.84%). 6. Main job—present job or past job held the longest. Defined as ‘‘Managerial, professional specialty (Executive, managerial, administrative, professional occupations. Job titles include teacher, guidance counselor, registered nurse, doctor, lawyer, accountant, architect, computer/systems analyst, personnel manager, sales manager, etc.) Missing, 4.7%’’ No–54.02%, Yes—41.23%. 7. Pain– Quality of life subscale on pain. PAIN ranges from 0 to 100 with a higher score indicating a more favorable health state. From the Rand 36-Item Health Survey (SF-36). 8. Satisfied with quality of life, analogous to Cantril’s ladder, 0Satisfied to 10-Dissatisfied. 9. Rate quality of life, analogous to Cantril’s ladder, 0-worst, 10Best. ‘Happy’: During the past four weeks ‘Have you been happy’. Six point scale 1 = All, 2 = Most, 3 = A good bit, 4 = Some, 5 = A little bit, 6 = None of the time. (From 36/37). This scale was reversed: All = 6, Most = 5, Good Bit = 4, Some = 3, Little = 2, None = 1. 10. ‘Emotional well-being’, ranging from 0 to 100 with a higher score indicating a more favorable health state. The source of the scale is the Rand 36-Item Health Survey (SF-36). Computed from Form 36/37, questions 76, 77, 78, 80, and 82. Source: Rand 36-Item Health Survey (SF-36). Quality of life subscale on emotional well-being ranges from 0 to 100 with a higher score indicating a more favorable health state. 2 June 2014 | Volume 9 | Issue 6 | e96061 Materials and Methods My paper is data from the WHI Baseline Data Set of 10/16/ 2003, Women’s Health Initiative Observational Study, provided by the National Heart, Lung and Blood Institute; the data set was converted to a SAS file in 2013. This study examines the association between height and some of the factors cited in the literature such as demographics—age, gender, ethnicity, income, education, occupation–health, social, subjective well-being, among relatively healthy women, 49–79 years of age, who participated in the Women’s Health Initiative’s Observational Study (WHI OS). Its main purpose is to assess a wide variety of important clinical and public health issues. Enrollment was conducted at 40 centers throughout the US. The justification for the WHI study is: ‘‘There is a general recognition that few older women have been studied longitudinally and that major questions about prediction of chronic disease in postmenopausal women remain.’’ ‘‘Participants in the observational study were women aged 49–79 (mean age 63.62, standard deviation, 7.37), who were ineligible or unwilling to participate in the clinical trial component or were recruited through a direct invitation for screening into the observational study.’’ ‘‘Many potential participants in the clinical trial component of the study were already undertaking a low fat diet or were using hormone replacement therapy and therefore were excluded or declined to participate clinical trial component. These participants were then enrolled into the observational study. Previous research has demonstrated that at the time of WHI enrollment, women undertaking hormone replacement therapy and/or low fat diets generally had healthier lifestyles than those not possessing these behaviors. The effect of the selection process was that women enrolled in the observational study tended to have healthier lifestyles compared to those enrolled in the clinical trial.’’ The data set consists of 2022 variables including demographics, eligibility for selection, personal information, medical history, reproductive history, family history, personal habits, thoughts and feeling, and other areas. Participants are 93,676 women—83% (78,013) White, 17% Non-White– 8% Black (7,639), 4% Hispanic (2,623); the remaining 5% Asian/Pacific Islander, American Indian, and subjects of unknown race/ethnicity. Other demographic variables are age, employment, region of country, employment. Measurements and definitions of height, income, wages as well as other variables may vary in the vast literature and research conducted by economists, social scientists, psychologists, epidemiologists and others. Therefore, definitions in the WHI OS Data Set questionnaire for the major variables analyzed are shown as follows: N N Height, in inches at age 18 or tallest adult height. Income ‘‘total family income (before taxes) from all sources within your household in the last year’’ Income is coded in 9 PLOS ONE | www.plosone.org Table 1. Descriptive Data All Women and by Non-White/White. Univariate Means Non-White 62.23 ,0.0001 0.0330 16.16 23.31 40.24 9.43 10.86 10.31 15.87 40.19 23.12 23.35 40.25 9.41 10.97 16.85 16.02 ,$20k63.63 4.53 78.38 8.10 8.25 35.87 73.90 0.044 College Grad or More Health–Exc/VeryGood ‘ Means White 63.90 63.67 4.55 78.61 8.10 8.25 35.93 74.26 0.042 High Sch–Some College 47.63 30.26 57.92 ‘‘ Percentages P-Value Income # Continuous Variables All Categorical Variables All Non-White White P-Value# Age 63.62 Height Inches 63.67 PLOS ONE | www.plosone.org Happy (1–5)* 4.55 $20k$35k_ $75K$100kEducation ,High School 22.12 22.34 47.72 29.94 56.94 41.23 40.75 Emotional Well-being (0–100) 78.57 Satisfied with Life (11 Dissat-Sat) 8.10 Quality of Life (11 Worst-Best) 8.25 0.0128 Social Support (9–45) 35.92 Pain Construct (0–100)** 74.20 22.07 47.61 30.32 58.12 41.33 0.0151 Likelihood of Depression (0–100) 0.042 Managerial/Professional Job Clubs None Monthly Weekly Strength/Religion None A Little A Great Deal Likelihood Depression None#Median Yes,Median 3 43.89 40.91 13.84 43.85 41.01 13.81 43.90 40.89 13.84 12.51 24.01 62.98 11.86 24.01 63.60 12.64 24.00 62.86 0.0209 55.38 44.62 55.43 44.57 55.37 44.63 ‘ Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 * Parentheses show scale. ** Higher–Less Pain. # Blank Not significant. vs.Good/Fair/Poor. vs. No Mang Job. P-Values denote Non-White vs. White differences. doi:10.1371/journal.pone.0096061.t001 ‘‘ Table 2. Mean Height in Inches. All Mean Mean 63.63 2.49 2.49 63.67 Std. Dev. P-Value Mean Std. Dev. 63.67 2.49 Std. Dev. P-value # # Non-White P-value# White Variables Age 63.67 63.66 63.67 2.50 63.59 2.45 63.68 2.51 2.48 63.65 2.52 63.67 2.48 2.48 63.62 2.48 63.68 2.48 PLOS ONE | www.plosone.org 63.63 2.50 2.47 2.49 2.49 2.48 63.60 2.56 63.66 2.41 63.64 2.49 63.68 63.69 63.67 63.66 2.48 63.70 2.52 63.70 63.67 63.68 63.66 0.0134* 63.53 0.0489* 63.65 2.49 2.47 2.49 2.51 2.46 0.0723* 63.67 63.67 63.66 2.50 63.61 2.52 2.48 63.64 2.48 2.48 63.62 2.50 63.68 63.67 63.67 2.47 2.49 2.49 63.66 63.65 2.48 2.49 63.65 63.62 63.68 0.0723 2.49 2.50 2.49 63.56 2.51 63.68 63.66 63.69 2.49 2.48 2.49 63.67 63.65 2.49 2.49 2.48 0.0023** 63.66 63.73 0.0015** 63.60 63.61 63.77 2.53 63.86 2.52 2.50 2.50 2.48 0.0050** 0.0094** 63.63 63.67 63.67 63.73 2.53 2.48 2.49 2.48 0.0272** 0.0298** 63.75 63.65 2.49 ‘ 50–59 60–69 70–79 Income ,$20k $ 20K- $35K- $75K- $$100K Education ,High School High Sch–Some College 4 2.69 0.0843 64.21 63.67 63.64 0.0133*** 63.64 2.88 2.50 2.49 2.49 63.66 63.65 63.71 63.66 2.65 2.49 2.48 2.48 0.0175*** 0.0398 ‘ College Grad or More Managerial/Professional Job Missing No Yes Attend Club/Lodges/Groups Missing None Monthly Weekly or more Religion–Strength/Comfort Missing None 63.70 2.48 2.48 63.65 A little A great deal General Health 63.67 63.66 2.50 2.48 63.67 63.56 2.48 2.51 0.0058 63.67 63.68 2.48 2.50 Excellent/Very Good Good/Fair/Poor Happy 63.67 2.48 63.59 2.51 63.69 2.48 Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 No Table 2. Cont. All Mean 63.67 2.49 63.64 2.48 63.67 2.49 Std. Dev. P-value # Non-White Mean Std. Dev. P-Value # White Mean Std. Dev. P-value# Yes Social Support–Median* 63.67 63.67 2.48 63.66 2.50 63.67 2.48 2.49 63.61 2.49 63.68 2.49 PLOS ONE | www.plosone.org 63.67 63.67 2.48 63.66 2.48 63.67 2.49 63.59 2.50 63.68 2.49 2.48 63.67 63.66 2.49 63.61 2.51 2.49 63.64 2.48 63.68 63.67 2.49 2.48 63.68 63.66 2.49 63.62 2.49 2.49 63.64 2.49 63.68 63.67 2.49 2.48 Above At or Below Emotional Well-being–Median* Above At or Below Satisfaction with Life–Median* Above At or Below Quality of Life–Median* Above At or Below # 5 Blank Not Significant. * $20k- taller then ,$20k. ‘A little taller than ‘None’. ** ‘Weekly taller than ‘Non’ and ‘Monthly’. *** ‘A Little’ taller than ‘A great deal’. Univariate Covariance Analyses. doi:10.1371/journal.pone.0096061.t002 ‘ Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors Table 3. Multivariable Covariance Analyses – Mean Heights. Pair Wise Comparisons All Women Mean Height 0 Non-White/White Non-White White 1 Income 1–5 1 ,$20k 2 $ 20K3 $35K4 $75K5 $$100K 2 Education 1–3 1 ,High School 2 High School–Some College 3 College Graduate or More 3 Managerial/Professional Job No Yes 4 Attend Club/Groups None Monthly Weekly 5 Strength/Comfort Religion None A Little A Great Deal 6 General Health Good/Fair/Poor Excellent/Very Good 7 BMI Quartiles* 1 2 3 4 Non-White Mean Height P-values 1 Income 1–5 1 ,$20k 2 $ 20K3 $35K4 $75K5 $$100K 2 Education 1–3 1 ,High School 2 High School–Some College 3 College Graduate or More 3 Managerial/Professional Job No 63.878 NS 63.657 0.0360 63.875 63.861 63.822 63.772 63.892 63.870 63.889 63.841 NS 63.699 63.688 63.674 NS 63.666 63.718 63.685 63.691 63.675 NS 63.952 63.758 63.619 63.467 White Mean Height P-values NS 63.657 63.668 ,0.0001 63.673 63.730 63.676 NS 63.678 63.693 63.770 None vs Little 0.0524 Little vs Great Deal 0.0074 63.678 63.724 None vs. Weekly 0.0005 Monthly vs Weekly 0.0039 63.713 63.702 63.683 0.0296 63.668 63.732 63.701 63.709 63.687 NS 63.669 63.724 1 vs 2 0.0210 0.0164 P-values PLOS ONE | www.plosone.org 6 June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors Table 3. Cont. Non-White Mean Height P-values Yes 4 Attend Club/Groups None Monthly Weekly 5 Strength/Comfort Religion None A Little A Great Deal 6 General Health Good/Fair/Poor Excellent/Very Good 7 BMI Quartiles* 1 2 3 4 64.095 63.903 63.756 63.656 63.594 63.702 ,0.0001 63.813 63.826 63.779 0.0116 63.793 63.833 63.985 NS 63.910 None vs Weekly Monthly vs Weekly 0.0031 0.0201 White Mean Height P-values 63.705 None vs. Weekly Monthly vs Weekly 63.675 63.685 63.745 None vs Little 63.664 63.730 63.675 NS 63.690 63.681 ,0.0001 63.942 63.748 63.611 63.448 0.0418 Little vs Great Deal 0.0130 0.0137 0.0357 * Significant Trend P,0.0001 Lowest BMI Highest Height. doi:10.1371/journal.pone.0096061.t003 11. ‘Social support’ is the sum of nine components. Scores range from 9 to 45, higher scores more support. The 9 components, each ranging from 1) None, 2) A little, 3) Some, 4) most, 5) All–of the time, are: Someone - a) ‘to listen when need to talk’, b) ‘to give good advice’; c) ‘who can take you to the doctor’, d) ‘to have a good time with’, e) ‘to help understand a problem when you need it’, f) ‘to help with daily chores if you are sick’, g) ‘to share your private worries’, h) ‘to do something fun with’, i) ‘to love you and make you feel wanted’. White women. However, in the two lowest income categories–, $20,000 and $20,000–$34,999–the height differences were great- Statistical methods Descriptive statistics (means and standard deviations), chisquare analyses for categorical data, linear regression and multivariable analyses of covariance (GLM) were carried out. Multivariable GLM analyses yielded means, standard errors, and p-values controlling for covariates, and pair-wise p-values by class. Results Descriptive data from univariate analyses are in Table 1. The mean age for all women is 62.62 years; for Non-White, 62.32, for White 62.90, a significant difference, P,0.0001. Height in inches differs by race/ethnicity—Non-White 63.63, White 63.67, P = 0.033. Compared to Non-White women, White women’s income was higher, P = 0.0128; self-reported general health was better, P = 0.0012; and fewer reported a great deal of strength and comfort from religion—63.6% vs., 62.9%, P = 0.0290. Subjective well-being and demographic variables did not differ. (Table 1). Univariate and multivariable covariance analyses for height as the outcome were carried out for the 93,676 participants into three groups a) all, b) Non-White and c) White women. Univariate means for height by demographic, behavioral and subjective wellbeing variables are in Table 2. Income and club attendance were significantly associated with height among all, Non-White and PLOS ONE | www.plosone.org 7 est. Means for subjective well-being variables tended to be high among all women–in the top quintile, but they were not related to height. Multivariable analyses included height and seven covariates. Table 3 shows pair-wise P-values as follows: 1) income—all, ,$20 vs. $20k- P = 0.020; 2) education—none significant; 3) job—all women P = 0.0296, Non-White NS, White, P = 0.0360; 4) clubs— all, Non-White, White with weekly attendance were taller than none or monthly—for all, P = 0.0005 and P = 0.0039; Non-White, P = 0.0031 and 0.0201; White, P = 0.0137 and 0.0357; 5) religion—all and White women reporting ‘a little’ vs. ‘none’, and ‘a little’ vs. ‘a great deal’ were taller—all P = 0.0522 and P = 0.0039, White P = 0.0418 and P = 0.0130, Non-White NS; 6) general health–White women NS, Non-White women with excellent very good health were taller, P = 0.0116; 7). Taller women had a lower BMI; P,0.0001. Notably, results from univariate covariance analyses (Table 2) and multivariable covariance analyses (Table 3) show minor differences. Table 4 shows full results of the GLM multivariable covariance analyses for a) all women, b) Non-White women and c) White women. Height and subjective well-being—happiness, emotional well-being, satisfaction with life, quality of life, social support, general health and likelihood of depression—dichotomized at the median were not associated; with the exception, general health among Non-White women. (Table 5). Income and education as predictors of subjective well-being, club attendance and religion revealed both congruencies and differences among Non-White and White women. Among White women, income and the subjective well-being variables—happiness, emotional well-being, happiness, satisfaction with life, quality of life and social support—and general health were significantly associated. These variables were also associated with education, June 2014 | Volume 9 | Issue 6 | e96061 Table 4. Results of Multivariable Covariance Analyses–Outcome Height—a: All Women, b: Non-White Women, c: White Women. a: All Women 2 5 3 3 4 4 63.7318 63.7007 63.7091 63.6867 1 63.7128 0.0428 0.0443 0.0454 0.6351 0.2963 1 63.6957 63.6783 63.7236 0.0564 0.0412 0.0419 0.6812 0.5264 1 63.6556 63.6784 2 Monthly 63.6932 3 Weekly or more63.7695 5 Religion ,.0001 Pr.F 0.0168 0.2077 0.58 2.37 4.16 0.5574 0.0937 0.0059 0 Missing 1 None 2 A Little 3 A Great Deal 6 General Health 1 G/F/P 63.6570 0.0406 63.7178 63.6729 63.7304 63.6756 0.1274 0.0490 0.0459 0.0436 0.7535 0.9294 0.7653 1 0.0524 0.9172 2 0.5293 0.0074 3 0.3246 0.0756 0.0469 0.0471 0.0507 0.7840 0.6511 0.1811 1 0.4238 0.0005 2 0.7535 0.0039 3 0.9294 0.0524 4 0.7653 0.9172 0.0074 0.0296 2 0.7840 3 0.6511 0.4238 4 0.1811 0.0005 1 None 0.0039 0.3882 2 0.6812 3 0.5264 0.0296 0.0487 0.5887 0.0495 0.2535 0.0430 0.2060 0.0443 0.0210 0.1662 0.4977 0.1606 2 0.6351 0.7859 0.6325 3 0.2963 0.3882 0.5540 3 4 DF 20 85128 85148 Coeff Var 3 Coll Grad or More 63.6829 3 Manag/Prof Job Pr.F 0 Missing 1 No 2 Yes 4 Clubs 0 Missing 0.0162 0.1639 0.9992 0.1047 0.0092 0.050 0.5013 3.892905 Type I SS 35.484644 40.026382 0.009905 27.73049 70.745207 47.895507 8.486091 2739.40779 Type III SS 35.112271 36.17002 7.18059 29.096621 76.594946 25.531649 14.54831 3.590295 9.042505 1.47 35.112271 5.72 Mean Sq F Value 913.135932 148.63 4.243046 0.69 15.965169 2.6 23.581736 3.84 13.865245 2.26 0.004952 0 10.006595 1.63 35.484644 5.78 Mean Sq F Value 2.478633 63.67053 RtMSE SumSq 525964.0745 2 Hi Schl–Some Coll63.7019 522994.2884 6.1436 1 ,High School 2969.786 148.4893 24.17 2 Education 1–3 SumSq Mean Sq F Value 5 $$100K 1234 4 $75K123 3 $35K0123 2 $ 20K0123 1 ,$20k 63.6677 0.0457 0.0210 012 1 Income 1–5 1 2 3 0.2060 0.1662 123 1 White 63.7264 0.0413 4 0.2535 0.4977 0.7859 12345 0 Non-White 63.6720 0.0453 0.0168 01 0 Non-White/ White 0 1 Class Levels Values Mean Height Std Error P- values 0 Non-White/White 0/1 1 1 Income 1–5 2 PLOS ONE | www.plosone.org 5 0.5887 0.1606 0.6325 0.5540 2 Education 1–3 3 3 Managerial/ Professional Job 4 4 Attend Clubs/Groups 5 5 Strength/Comfort Religion 6 6 General Health* 7 7 BMI Quartiles 8 Source Model Error CorrTot R Sq 8 0.005646 Source DF 0 Non-White/White 0/1 1 1 Income 1–5 4 2 Education 1–3 2 3 Managerial/ Professional Job 2 4 Attend Clubs/Groups 3 5 Strength/Comfort Religion 3 6 General Health* 2 7 BMI Quartiles 3 Source DF 0 Non-White/White 0/1 1 1 Income 1–5 4 2 Education 1–3 2 3 Managerial/ Professional Job 2 Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 4 Attend Club/Groups 3 Table 4. Cont. a: All Women 47.462193 7.817281 2739.40779 ,.0001 1 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 P- values 1 63.7721 63.8922 63.8697 63.8892 63.8405 0.1013 0.1171 0.1160 0.1043 0.1073 0.0758 0.1253 0.1848 0.4326 1 0.10680 63.86066 63.82214 0.10008 0.10458 0.7945 0.4484 1 0 Missing 1 No F Value 1.25 0.18 0.72 3.35 7.2802 36.4494 1.18 5.89 Pr.F 0.288 0.833 0.4855 0.0181 20.7365 0.31680 0.0028 2 Yes 4 Clubs 0 Missing 1 None 2 Monthly 3 Weekly or more 5 Religion 63.8000 63.7928 63.8335 63.9847 0.1872 0.1131 0.1137 0.1228 0.973 0.876 0.3996 1 0.3712 0.0031 2 0.0201 3 4 63.76961 63.87821 63.91039 0.13465 0.09654 0.09782 0.2954 0.1919 1 0.53 2 0.973 3 0.876 0.3712 4 0.3996 0.0031 0.0201 0.4747 2 0.2954 3 0.1919 0.53 0.6839 0.9706 0.5207 2 0.7945 0.7955 0.6917 3 0.4484 0.4747 0.6038 4 2 0.0758 3 0.1253 0.6839 4 0.1848 0.9706 0.7955 2 3 4 Levels 5 3 3 4 4 3 4 DF 19 ,.0001 14200 14219 Coeff Var RtMSE 3.9088 DF 4 2 2 3 3 2 72.8989 21.8405 62.2094 8.9379 4.4689 2.2607 1.1304 30.8849 7.7212 Type I MeanSq 2.4870 63.6249 SumSq 88417.5061 87827.4650 6.1850 590.0410 31.0548 5.02 SumSq MeanSq F Value P-value 1234 2 Education 1–3 1 ,High School 63.87542 2 Hi Schl–Some Coll 3 Coll Grad or More 3 Manag/Prof Job 123 5 $$100K 0123 4 $75K0123 3 $35K012 2 $ 20K123 1 ,$20k 12345 1 Income 1–5 Values Mean Height Std Error 63.4671 0.0442 63.6190 0.0444 63.7583 0.0444 63.9523 0.0443 913.135932 148.63 7 BMI Quartiles 1 2 3 ,0.0001 ,0.0001 3.90864 0.64 0.5293 3 Missing 63.7727 0.1063 0.3246 0.3717 4 ,0.0001 ,0.0001 ,0.0001 15.820731 2.58 0.052 2 Exc/VG 63.6679 0.0399 0.5293 0.3717 Class Levels Values Mean Height Std Error P- values 5 Strength/comfort Religion 3 6 General Health* 2 PLOS ONE | www.plosone.org 5 0.4326 0.6917 0.6038 7 BMI Quartiles 3 b: Non-White Class 1 Income 1–5 1 2 Education 1–3 2 3 Managerial/Professional Job 3 4 Attend Clubs/Groups 4 9 5 Strength/Comfort Religion 5 6 General Health* 6 7 BMI Quartiles 7 Source Model Error CorrTot R Sq 0.006673 Source 1 Income 1–5 1 2 Education 1–3 2 3 Managerial/Professional Job 3 4 Attend Clubs/Groups 4 5 Strength/Comfort Religion 5 Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 6 General Health* 6 Table 4. Cont. b: Non-White 3 ,.0001 Pr.F 1 None 2 A Little 3 A Great Deal 63.7786 6 General Health 1 G/F/P 2 Exc/VG 3 Missing 7 BMI Quartiles 1 2 3 4 Levels 5 3 3 4 4 3 4 DF 19 70909 70928 Coeff Var 3.88964 DF 4 Type I 21.1670 2.4769 RtMSE 437511.084 SumSq 63.6797 MeanSq 5.2918 F Value 0.86 Pr.F 0.4855 435032.898 6.135 2478.186 130.431 21.26 SumSq MeanSq F Value 1234 P-value ,.0001 123 0123 0123 3 $35K4 $75K5 $$100K 2 Education 1–3 1 ,High School 63.6992 2 Hi Schl–Some Coll 3 Coll Grad or More 3 Manag/Prof Job 0 Missing 1 No 2 Yes 4 Clubs 63.6992 63.6570 63.7048 0.0615 0.0447 0.0454 0.3648 0.9078 1 0.0360 2 3 4 63.6882 63.6736 0.0494 0.0465 0.0480 0.6616 0.4131 1 0.5435 2 0.3648 3 0.9078 0.0360 012 2 $ 20K123 1 ,$20k 12345 1 Income 1–5 63.6657 63.7179 63.6854 63.6914 63.6747 0.0497 0.0481 0.0466 0.0539 0.0529 0.0860 0.4905 0.5170 0.8138 1 0.1850 0.4694 0.2174 2 0.6616 0.8586 0.7380 3 0.4131 0.5435 0.6861 Values Mean Height 63.6563 0.1042 Std Error 1 2 0.0860 63.7562 0.1047 63.9033 0.1044 64.0951 0.1036 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 P- values 3 0.4905 0.1850 4 0.5170 0.4694 0.8586 1 64.2619 0.2551 0.0195 63.7019 0.0955 0.0116 0.0498 2 ,0.0001 3 ,0.0001 ,0.0001 4 63.5944 0.0972 0.0116 1 2 3 0.0195 0.0498 0.1054 0.5428 0.6092 0.3414 63.8263 0.1104 0.6371 0.8534 63.8126 0.1192 0.6129 0.8534 0.4494 0.7135 0.4158 0.0318 0.7247 0.0042 ,.0001 DF 4 2 2 3 3 2 3 391.0087 130.3362 21.07 67.6623 33.8311 5.47 8.1560 2.7187 0.44 54.5662 18.1887 2.94 10.8563 5.4282 0.88 4.1767 2.0883 0.34 22.8336 5.7084 0.92 Type III MeanSq F Value 391.0087 130.3362 21.07 0 Missing 63.9935 0.3136 0.6129 0.6371 0.5428 0.6092 0.3414 Class Levels Values Mean Height Std Error P- values 7 BMI Quartiles 7 Source PLOS ONE | www.plosone.org ,0.0001 ,0.0001 ,0.0001 5 0.8138 0.2174 0.7380 0.6861 1 Income 1–5 1 2 Education 1–3 2 3 Managerial/Professional Job 3 4 Attend Clubs/Groups 4 5 Strength/Comfort Religion 5 6 General Health* 6 7 BMI Quartiles 7 10 C: White Class 1 Income 1–5 1 2 Education 1–3 2 3 Managerial/Professional 3 Job 4 Attend Clubs/Groups 4 5 Strength/Comfort Religion 5 6 General Health* 6 7 BMI Quartiles 7 Source Model Error CorrTot R Sq 0.005664 Source Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 1 Income 1–5 1 Table 4. Cont. C: White 2 2 3 3 2 3 ,.0001 Pr.F 1 None 2 A Little 3 A Great Deal 63.6747 6 General Health 1 G/F/P 2 Exc/VG 3 Missing BMI Quartiles 1 2 3 4 63.9416 63.7480 63.6105 63.4479 0.0482 0.0481 0.0482 0.0480 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 ,0.0001 63.6893 63.6814 63.6903 0.0437 0.0429 0.1167 0.0116 0.0195 1 0.0498 2 ,0.0001 3 ,0.0001 ,0.0001 4 1 0.0471 0.9794 63.7303 0.0497 0.739 63.6645 0.0530 0.9277 0.0418 0.7236 2 0.0116 0.0130 3 0.0195 0.0498 0.4658 0.7093 0.0955 0.0907 0.0709 0.8976 ,.0001 DF 4 2 2 3 3 2 3 2347.7145 782.5715 127.56 1.3257 0.6629 0.11 43.1498 14.3833 2.34 39.7157 13.2386 2.16 28.8171 14.4086 2.35 4.2149 2.1074 0.34 21.9645 5.4911 0.9 Type III MeanSq F Value 2347.7145 782.5715 127.56 0 Missing 63.6786 0.1392 0.9277 0.8823 0.4412 0.07 0.9306 5 Religion 1 2 42.8023 14.2674 2.33 0.0727 3 Weekly or more 63.7455 0.0550 0.2695 0.0137 36.9570 12.3190 2.01 0.1105 2 Monthly 63.6847 0.0510 0.6465 0.6184 0.0357 3 0.739 0.0418 4 0.9794 0.7236 0.0130 28.0657 14.0329 2.29 0.1015 1 None 63.6746 0.0508 0.7288 0.6184 0.5972 0.2986 0.05 0.9525 0 Missing 63.6433 0.0822 0.7288 0.6465 0.2695 0.0137 0.0357 Class Levels Values Mean Height Std Error P- values 2 Education 1–3 2 3 Managerial/Professional 3 Job PLOS ONE | www.plosone.org ,0.0001 ,0.0001 ,0.0001 4 Attend Clubs/Groups 4 5 Strength/Comfort Religion 5 6 General Health* 6 7 BMI Quartiles 7 Source 1 Income 1–5 1 2 Education 1–3 2 3 Managerial/Professional 3 Job 4 Attend Clubs/Groups 4 5 Strength/Comfort Religion 5 11 6 General Health* 6 7 BMI Quartiles 7 General Health–Good/Fair/Poor vs Excellent Very Good. Note: Missing data included in Multivariable Analyses–for *Job, Club, Religion, Health (less than 1% for these variables). doi:10.1371/journal.pone.0096061.t004 Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 Table 5. Height and Subjective Well-Being Variables. All #Median .Median Missing 63.666 ‘ P-value* 0.9734 63.643 64.156 0.8051 63.659 63.874 0.5363 63.612 64.160 ‘ Non-White 63.586 63.670 63.560 63.680 63.669 63.672 0.0582 63.678 63.671 63.674 63.683 63.672 ‘ P-value* 0.0318 63.687 0.3905 White P-value* Happiness 63.670 63.665 PLOS ONE | www.plosone.org #Median .Median Missing 63.708 63.671 63.661 63.755 63.675 63.663 63.818 63.668 63.669 63.613 63.658 63.671 63.792 63.657 63.675 63.651 0.5345 63.616 63.640 63.581 64.296 63.671 ‘‘ Emotional Well-Being 63.664 63.668 63.588 0.0594 0.8429 Satisfaction with Life #Median .Median Missing #Median .Median Missing 64.250 0.5343 63.658 63.520 0.3236 63.559 0.0004 63.607 0.2914 #Median .Median Missing #Median .Median Missing #Median .Median Missing 63.619 0.2192 63.635 0.0200 63.636 0.9280 Quality of Life 0.7529 63.727 63.607 63.658 63.520 63.679 63.671 63.686 0.9144 0.6522 Social support General Health 12 Likelihood of Depression 0.7771 63.666 63.682 63.667 0.3590 0.6496 ‘ * P-values ,0.05 Bold. Missing differs from ,Median and .Median. ,Median and .Median Differ, Missing Differs from ,Median and .Median. doi:10.1371/journal.pone.0096061.t005 ‘‘ Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 Table 6. Subjective Well-Being Means by Income and Education. Row 1 Non-White ,$20K P-Value Income Education Row 2 White $20K- $35K- $75K- $$100K High School,High School Some College College Grad or More P-Value Happy 4.522 4.516 4.543 4.557 4.549 4.567 0.0019 4.531 4.554 4.552 4.536 4.533 4.513 4.567 0.6584 4.491 4.545 4.541 0.0299 0.0501 PLOS ONE | www.plosone.org 78.012 78.059 78.635 78.741 78.576 78.781 0.0006 78.315 78.660 78.356 78.462 78.770 78.512 0.6150 77.649 78.708 78.408 78.736 0.0027 0.0113 8.030 8.043 8.084 8.103 8.120 8.167 0.0003 8.089 8.111 8.105 8.083 8.153 0.3637 7.997 8.124 8.107 8.126 8.091 0.3638 0.4675 8.149 8.191 ,0.0001 8.247 8.259 8.283 8.303 8.233 8.248 8.262 8.279 8.303 0.0095 8.164 8.266 8.263 8.285 8.253 0.0008 0.0169 35.299 35.531 35.753 36.000 36.139 36.294 ,0.0001 35.888 36.004 35.797 36.332 0.0007 35.673 35.858 35.906 35.933 35.969 35.961 0.2252 0.4196 2.425 2.394 2.351 2.336 2.312 2.293 2.381 2.345 2.325 2.357 0.0018 ,0.0001 2.407 2.365 2.361 2.341 2.347 2.325 ,0.0001 0.0097 0.0482 0.0438 0.0435 0.0411 0.0413 0.0413 0.0433 0.0432 0.0410 0.0462 0.4714 0.1909 0.0462 0.0424 0.0427 0.0420 0.0455 0.0422 0.4196 0.9394 1 2 Emotional Well-Being 1 2 Satisfaction with Life 1 2 Quality of Life 1 2 Social Support 1 13 2 General Health* 1 2 Likelihood of Depression** 1 2 Women 49–79 Height Socioeconomic Factors *Low values better health – 1 = Excellent-5 = Poor. ** Low values less likelihood. doi:10.1371/journal.pone.0096061.t006 June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors Table 7. Subjective Well-Being Variables by Strength and Comfort from Religion. Women All Means Non-White Means White Means Happy None A Little A Great Deal Emotional Well-Being None A Little A Great Deal Satisfaction with Life None A Little A Great Deal Quality of Life Life None A Little A Great Deal Social Support None A Little A Great Deal General Health* None A Little A Great Deal Likelihood of Depression** None A Little A Great Deal 0.044 0.0474 0.0403 0.0452 0.0498 0.0421 0.0438 0.0469 0.0399 2.143 2.316 2.397 2.15 2.31 2.428 2.142 2.317 2.391 35.097 34.945 36.456 35.094 34.89 36.397 35.097 34.956 36.468 7.796 7.788 8.277 8.056 8.023 8.37 8.05 8.016 8.385 7.796 7.788 8.277 7.797 7.784 8.271 7.796 7.789 8.278 77.82 76.884 79.364 77.25 76.592 79.272 77.927 76.943 79.382 4.409 4.42 4.621 4.379 4.402 4.609 4.415 4.424 4.623 *Low values Better. General Health 1 = Excellent–5 = Poor. ** Low values less likelihood. N.B. P,0.0001 for all groups and variables except Non-White Likelihood of Depression–P = 0.0334. doi:10.1371/journal.pone.0096061.t007 with the exception of satisfaction with life. In contrast, Non-White women’s subjective well-being variables—emotional well-being, happiness, and satisfaction with life—were not associated with income except for quality of life, P = 0.0095 and social support, P = 0.0007. Associations with education were significant for variables: happiness, emotional well-being and quality of life; satisfaction with life, but not significant for social support. (Table 6) An additional finding of interest is that measures of the likelihood of depression, unlike general health, showed no disparities by NonWhite/White and no associations with height, (Tables 2 and 3) with income, and with education. (Table 6). ‘Strength and comfort from religion’—‘a great deal’–was associated with depression and the subjective well-being variables. Those with ‘a great deal’ had the highest values (means) from the subjective well-being variables. In contrast, those with ‘a great deal’ had poorer general health. (Table 7). Interestingly, income and education were associated with religion among White women. Those with higher income and with higher education were more likely to report ‘none’ and less likely to report ‘a great deal’ (Chi-square P,0.0001). Among NonWhite religion and income and religion and education were not significantly associated. (Table 8). In sum, new findings from this study of US women, 49–79, are: a) taller Non-White and White women engaged in more frequently in social activities, e.g., such as club attendance; b) taller White women had reported significantly more ‘a little’ strength and comfort from religion compared to ‘none’ and compared to ‘a great deal’. Other major findings are: c) taller Non-White and Whites did not have higher incomes or more education; d) taller White women with present or past managerial/professional jobs; e) taller Non-White women had better general health. Discussion A vast and global literature examines the relation of height with numerous factors, including, but not limited to psychological, social, economic, anthropologic, genetic, gender, environmental, ecologic, behavioral, nutritional, infection and other constructs. 14 June 2014 | Volume 9 | Issue 6 | e96061 PLOS ONE | www.plosone.org Table 8. Strength and Comfort from Religion by Income and by Education for All, Non-White, White Women Percentages for None, A Little and A Great Deal. Income All Women Education All Women High School Some College 12.36 23.9 63.24 P,0.0001 13.30 24.12 62.08 College Grad or More ,$20k ,High School 11.76 24.06 63.66 12.37 23.46 63.58 Chi-square Non-White Non-White P,0.0001 62.77 61.71 60.92 24.25 24.19 25.01 12.5 13.54 13.68 $20k- $35k $75K $$100k None 11.72 PLOS ONE | www.plosone.org A Little 23.37 A Great Deal 64.43 ,$20k ,High School 11.69 24.58 63.33 11.91 23.59 63.87 12.22 22.72 64.37 Chi-square White White P = 0.1272 63.23 61.00 61.63 24.8 25.54 25.07 11.58 12.95 12.63 $20k- $35k $75K $$100k High School Some College College Grad or More 11.78 23.95 63.73 P = 0.6029 None 11.33 A Little 23.16 A Great Deal 64.89 ,$20k 12.4 23.61 63.42 Chi-square P,0.0001 62.67 61.86 60.79 24.14 23.92 25.00 12.69 13.66 13.88 11.78 23.95 63.73 $20k- $35k $75K $$100k ,High School High School Some College College Grad or More 12.46 23.97 63.11 P,0.0001 13.57 24.10 61.83 15 None 11.80 A Little 23.42 A Great Deal 64.34 doi:10.1371/journal.pone.0096061.t008 Women 49–79 Height Socioeconomic Factors June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors This study examined data from relatively healthy women ages 49– 79, from a range of race/ethnic groups—dichotomized Non-white 17% and White 83% of the sample of 93,676 women. It focused on height and variables including income, education, general health, social activities, and subjective well-being. Two major findings emerge: 1) taller Non-White and White women engaged social activities, viz. attended clubs/lodge/groups, more frequently than those who did not attend or attended less frequently. Attendance at clubs is one among a variety of social activities. Notably, this finding is in accord with Persico et al. [21], who related social activities, such as athletics, to height and wages–one of the few papers to analyze social activities. 2) Strength and comfort from religion was associated not only with height, but also with subjective well-being, general health, income and education. (Tables 1—4, 7–8). The association of religion and income has been discussed by Barro and McCleary [30]; and religion and health have many citations in the medical literature [31]. However, to my knowledge, religion and height have not been investigated. Occupation and height of men and women have been examined by many investigators [7,10,14,19,21], as well as others. In particular, the paper of Case and Paxon, based on data from cohort (longitudinal) studies, concluded that taller adults select into occupations that have higher cognitive skill requirements and lower physical skill demands [7]. Case, Paxon and Islam confirm these results using longitudinal data from the BHPS (British Household Pane Survey [32]. In this study, taller White women had managerial/professional jobs, and taller Non-White women did not have managerial/professional jobs; but they had better general health–results consistent with the effects of genetics, environment, poverty, medical conditions, nutrition and cognitive skills. However, height was not significantly associated with income nor with and education among both Non-white and White. This is in contrast to findings of Deaton and Arora, who analyzed the Analysis of the Gallup-Healthways Well-Being Index daily poll of the US population [10]. They reported ‘‘taller people lead better lives on average’’–findings ‘‘almost entirely explained by the positive association between height and both income and education’’. These differences in results may be accounted for by social and cultural factors in both White and Non-White women such as: a) in the U.S., women’s incomes continue to lag those of men, for this reason, taller White women may lead better lives by virtue of their managerial/professional positions rather than by income or education; and b) Non-Whites with better health were taller; early environmental or genetics factors may have prevented some Non-Whites from reaching their full physical and mental development [7,10]. It is noteworthy that, though not related to height, subjective well-being variables are significantly associated with income and education among White women. Hence, higher income and better educated women may lead better lives, but not because they are taller; findings that differ from Deaton and Arora [10]. A new area examined in this study is religiosity as measured as ‘strength and comfort from religion’ classified as ‘none’, ‘a little’ and ‘a great deal’. Overall results are the percentage of women reporting—12% ‘none’, 24% ‘a little’ and 63% ‘a great deal’, and 0.5% missing data. Analyses of this construct, both as a covariate and as a outcome, (to my knowledge has not examined in the literature on height), was related to height, as well as health, subjective well-being, income and education (Tables 2 and 3), Although measures and definitions of ‘religion/religiosity’ may differ among investigators, my findings on religion and income are in accord with Barro and McCleary [30]. Their findings reveal an PLOS ONE | www.plosone.org 16 overall pattern in which economic development is associated with less religiosity, measured by church attendance or religious beliefs. They conclude: ‘‘This pattern can be seen in simple relations between a measure of religiosity and per capita GDP, which we take as the basic indicator of economic development.’’ (Their future research plans include an assessment of the effects of religiosity on political and social variables, including democracy, the rule of law, fertility, and health. P 38). To my knowledge height and religion have not been investigated. Health and religion/religiosity are of increasing interest in the medical literature. November 18, 2013PUBMED search for ‘religion’ yielded 50054 hits. Koenig, Director, Center for Spirituality, Theology and Health at Duke University. ‘‘Reviews. Religion, Spirituality, and Health: the research and clinical implications’’ [31]. Interestingly, while weight is discussed, no mention of height is found in the text or among the 596 references. Further research, suggested by my findings, on height and other factors are the following: 1) Occupation–indicated by the finding that taller White women had managerial/professional jobs presently or in the past. In the WHI data ‘managerial/professional job’ covers a range of occupations’. It is defined as ‘‘Managerial, professional specialty (Executive, managerial, administrative, professional occupations. Job titles include teacher, guidance counselor, registered nurse, doctor, lawyer, accountant, architect, computer/systems analyst, personnel manager, sales manager, etc.)’’. To understand better the association of height and the components of ‘managerial/professional specialty need more detailed classifications. 2) Social activities—here denoted by attendance at clubs/ lodges/groups—a construct significantly associated with height among Non-White and White. What constitutes social activities and how to measure them needs further work. 3) ‘Strength and comfort from religion’, and important construct in this study, was associated with height, income, education and health. Women who reported ‘a little’ vs. ‘none’ or vs. ‘a great deal’ were taller, had higher incomes and better education, but those with ‘none’ had better health. Importantly, as far as I am aware, religion/religiosity and height have not been previously examined. Replication and validation in other groups are suggested. A possible limitation of this study is that the data are from a cross-section observational study, which may not be sufficient for analyzing changes over time or causal inference. The strengths of this study are the large sample size and reliability and validity of the questionnaire. In conclusion, among relatively healthy U.S. women, 17% NonWhite and 83% White, ages 49–79, height and income, and height and education, were not associated. However, taller White women had better jobs, and taller Non-White had better health. In addition, two new results emerged—first, taller Non-White and White women attended clubs/groups more frequently. Second, taller women reported ‘a little’ comfort from religion (vs. ‘none’ and vs. ‘a great deal’)–they add to the vast literature on height and its relation with human behavior and with well-being. Whether these findings are generalizable globally to diverse populations and a range of demographics– including age, gender, culture, socioeconomics, psychosocial, among others–raise important questions in search of answers. June 2014 | Volume 9 | Issue 6 | e96061 Women 49–79 Height Socioeconomic Factors Acknowledgments I acknowledge the support of the NHLBI (National Heart, Lung and Blood Institute) for providing the WHI Baseline Data Set 10/16/2003, Women’s Health Initiative’s Observational Study (WHI OS). Author Contributions Conceived and designed the experiments: GW. Performed the experiments: GW. Analyzed the data: GW. Contributed reagents/materials/ analysis tools: GW. Wrote the paper: GW. References 1. Hensley WE, Cooper R (1987) Height and occupational success: a review and critique. Psychol Rep Jun; 60 (3 Pt 1):843–9. Review. ¨ 2. Ozaltin E (2012) Commentary: the long and short of why taller people are healthier and live longer. Int J Epidemiol Oct; 41(5):1434–5. 3. Steckel RH (2008) Biological Measures of the Standard of Living. Journal of Economic Perspectives Winter: 22(1):129–152. 4. Steckel RH (2009) Heights and Human Welfare: Recent Developments and New Directions. NBER Working Paper No. 14536 2008 Dec, Revised 2009 Jan; 1–66 JEL No. N00,O1. 5. Batty GD, Shipley MJ, Gunnell D, Huxley R, Kivimaki M et al. (2009) Height, wealth, and health: an overview with new data from three longitudinal studies. Econ Hum Biol Jul;7(2): 137–52. 6. Beard AS, Blaser MJ (2002) The ecology of height: the effect of microbial transmission on human height. Perspect Biol Med Fall;45(4):475–98. 7. Case A, Paxson C (2008) Stature and status: height, ability, and labor market outcomes. Journal of Political Economy 116 (3): 499–532. 8. Cavelaars AE, Kunst AE, Geurts JJ, Crialesi R, Grotvedt L et al. (2000) ¨ Persistent variations in average height between countries and between socioeconomic groups: an overview of 10 European countries. Ann Hum Biol Jul– Aug; 27(4): 407–21. 9. Davey Smith G, Hart C, Upton M, Hole D, Gillis C et al.(2000) Height and risk of death among men and women: aetiological implications of associations with cardiorespiratory disease and cancer mortality J Epidemiol Community Health 54(2):97–103. 10. Deaton A, Arora R (2009) Life at the top: the benefits of height. Econ Hum Biol Jul; 7(2):133–6. 11. Hensley WE (1993) Height as a measure of success in academe. Psychology: A Journal of Human Behavior 30:40–46. 12. Hensley WE (1992) Why Does the Best-Looking Person in the Room Always Seem to be Surrounded by Admirers. Psychological Reports April: 70(2); 457– 458. 13. Huang TL, Carlson MC, Fitzpatrick AL, Kuller LH, Fried LP (2008) Knee height and arm span: a reflection of early life environment and risk of dementia. Neurology May 6;70(19 Pt 2):1818–26. 14. Judge TA, Cable DM (2004) The effect of physical height on workplace success and income: preliminary test of a theoretical model. J Appl Psychol Jun;89(3): 428–41. 15. Kortt M, Leigh A (2010) Does Size Matter in Australia? The Economic Record, vol. 86, no. 272, March, 71–83. 16. Kuh DL, Power C, Rodgers B (1991) The effect of physical height on workplace success and income: preliminary test of a theoretical model. Int J Epidemiol Dec; 20(4):1001–9. 17. Langenberg C, Shipley MJ, Batty GD, Marmot MG (2005) Adult socioeconomic position and the association between height and coronary heart disease 18. mortality: findings from 33 years of follow-up in the Whitehall Study. Am J Public Health Apr; 95(4): 628–32. Mark QJ (2012) Global Variance in Female Population Height: The Influence of Education, Income, Human Development, Life Expectancy, Mortality and Gender Inequality in 96 Nations. J Biosoc Sci Apr 2:1–15. (Epub ahead of print) Marmot MG, Smith GD, Stansfeld S, Patel C, North F, et al. (1991) Health inequalities among British civil servants: the Whitehall II study. Lancet 337:1387–1393. Novak M, Ahlgren C, Hammarstrom A (2012) Social and health-related correlates of intergenerational and intragenerational social mobility among Swedish men and women. Public Health Apr; 126(4):349–57. Persico N, Postlewaite A, Sliverman D (2004) The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height. Journal of Political Economy, 112(5):1019–1053. Pollet TV, Nettle D (2008) Taller women do better in a stressed environment: height and reproductive success in rural Guatemalan women. Am J Hum Biol May–Jun; 20(3):264–9. Silventoinen K, Lahelma E, Rahkonen O (1999) Social background, adult bodyheight and health. Int J Epidemiol Oct;28(5):911–8. Smits J, Monden CW (2012) Taller Indian women are more successful at the marriage market. Am J Hum Biol Jul–Aug; 24(4):473–8. ¨ Subramanian SV, O zaltin E, Finlay JE (2011) Height of nations: a socioeconomic analysis of cohort differences and patterns among women in 54 low- to middle-income countries. PLoS One Apr 20; 6(4):e18962. Tucker-Seeley RD, Subramanian SV (2011) Childhood circumstances and height among older adults in the United States. Econ Hum Biol Mar;9 (2):194– 202. Walker M, Shaper AG, Wannamethee G (1988) Height and social class in middle-aged British men. J Epidemiol Community Health Sep; 42(3):299–303. Beeri MS, Davidson M, Silverman JM, Noy S, Schmeidler J, et al. (2005) Relationship between body height and dementia. Am J Geriatr Psychiatry 13:116–123. Fogel RW, Engerman SL, Trussel J (1982) Exploring the Uses of Data on Height: The Analysis of Long-Term Trends in Nutrition, Labor Welfare, and Labor Productivity, Social Science History, Vol. 6, No. 4, Trends in Nutrition, Labor, Welfare, and Labor Productivity Autumn, pp. 401–421. Barro RJ, McCleary RM (2003) Religion and Economic Growth, NBER Working Paper No. 9682, May, JEL No. O1, O4, Z1. PP. 1–52. Koenig HG (2012) Review Article. Religion, spirituality, and health: the research and clinical implications. ISRN Psychiatry Dec 16; 2012:278730. doi: 10.5402/2012/278730. 33 pages. Case A, Paxson C, Islam M (2009) Making sense of the labor market height premium: Evidence from the British Household Panel Survey Econ Lett March; 102(3): 174–176. doi:10.1016/j.econlet.2008.12.011. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. PLOS ONE | www.plosone.org 17 June 2014 | Volume 9 | Issue 6 | e96061