Consideration of Anthropometric Measures in Cancer S. Lani Park April 24, 2009
Presentation outline Background in anthropometric measures in cancer Examples of anthropometric measures and investigating its associations in cancer Height BMI Weight and BMI Change
Why study Anthropometric factors in cancers? They are standardize measures which may serve as markers for exposures and/or indexes for adiposity
Types of anthropometric measures Height Sitting height Leg Length Weight BMI (kg/m 2 ) Waist-Hip-Ratios
Observational study designs used to investigate associations between anthropometric measures and cancer Ecological Cross-Sectional Case-Control Cohort
Example of Ecological study
Example of cross-sectional study
Markers for childhood exposures Leg length: marker for growth before puberty Sitting height: because growth of trunk can continue, sitting height may be an indicator for energy availability before age of 20. Height: potential marker for childhood exposures
Models for height and weight Hu FB, Obesity Epidemiology
Explanation to observed associations Chance, bias, confounding Height as a marker for other exposures Reduced dietary intake (short stature) Protects against cancer (Frankel, BMJ, 1998) Diets of affluence (tallness) increase risk of cancer Height as a biomarker for biologic mediators of risk
Example: Height and endometrial cancer, cohort study Table 2. Relative Risk (RRs) For Endometrial Cancer in Relation to Height in the Multiethnic Cohort No. Cases RR 1 (95%CI) RR 2 (95%CI) RR 3 (95% CI) Height at baseline (m) <1.57 117 1.00 1.00 1.00 1.57 to <1.60 85 1.43 (1.08, 1.90) 1.42 (1.07, 1.88) 1.21 (0.91, 1.61) 1.60 to <1.651 136 1.48 (1.16, 1.90) 1.44 (1.11, 1.88) 1.09 (0.84, 1.43) 1.651 154 1.56 (1.22, 1.98) 1.50 (1.13, 1.99) 0.88 (0.65, 1.18) 1 Age-adjusted RR 2 RRs were adjusted for age, ethnicity, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, oral contraceptive use, parity, smoking history, diabetes, hypertension, and baseline BMI. 3 RRs were adjusted for age, ethnicity, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, oral contraceptive use, parity, smoking history, diabetes, and hypertension, and baseline weight.
Example: UADT Cancers and height, multi-center case-control study Association between UADT cancer and height Height (cm) Overall Ca Co OR* 95% CI Quintile 1 545 443 1.21 ( 0.97-1.52 ) Quintile 2 428 488 0.93 ( 0.74-1.16 ) Quintile 3 362 369 1.00 Quintile 4 442 470 1.11 ( 0.89-1.39 ) Quintile 5 257 392 0.85 ( 0.66-1.09 ) Missing 12 11 Ptrend 0.0813 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Example 2: UADT Cancers and height, multi-center case-control study Association between UADT cancer and height, stratified by site Height (cm) Oral-oropharyngeal Hypopharynx Esophageal Ca Co OR 95% CI Ca Co OR 95% CI Ca Co OR 95% CI Quintile 1 246 443 1.23 (0.93-1.62) 243 443 1.03 (0.76-1.39) 33 409 1.56 (0.81-2.98) Quintile 2 205 488 0.97 (0.74-1.28) 156 488 0.73 (0.53-1.00) 38 440 1.32 (0.70-2.48) Quintile 3 175 369 1.00 149 369 1.00 21 318 1.00 Quintile 4 213 470 1.07 (0.81-1.41) 178 470 1.02 (0.75-1.38) 30 415 1.05 (0.55-2.00) Quintile 5 121 392 0.71 (0.52-0.97) 101 392 0.88 (0.62-1.24) 22 353 0.99 (0.50-1.97) Ptrend 0.010 0.998 0.132 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Limitations and strengths in using height Limitations Can represent a broad range of childhood exposures In our study examples, ideally it would be nice to have multiple measures of height particularly among >50 years of age Strength- Stable measure: Less likely to be affected by disease or its treatment. Within person variance of adult height is likely smaller than within person variance of adult weight
Adiposity and cancer
Markers for adiposity Weight: adulthood weight gain (age 18 to 55) usually reflects an increase in body fat. BMI: highly correlated with both absolute body fat and percent body fat. Waist-Hip-Ratio: measure for central adiposity
Why study BMI and cancer? (Renehan AG, Lancet, 2008)
Obesity and Cancer biomechanism Calle EE, Kaaks R. Nature, 2004
Hyperglycemia Results in increase of IGF1 levels Brownlee M, diabetes 2005
Statistical Models Hu FB, Obesity Epidemiology
Considerations for BMI in cancer Reverse causality Confounding variables Ethnic differences Self report validity, information bias
Example: Association between Leanness and UADT cancers BMI at study entry (kg/m 2 )** Overall Ca Co OR* 95% CI 13.0-18.4 137 46 1.84 ( 1.24-2.73 ) 18.5-24.9 914 670 1.00 25.0-29.9 486 768 0.55 ( 0.46-0.65 ) 30.0-53.0 173 277 0.54 ( 0.42-0.70 ) Missing 12 9 Ptrend <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Example: Association between Leanness and UADT cancers, earlier measure BMI at 2 years prior to interview (kg/m2) Overall Ca Co OR* 95% CI 13.0-18.4 57 23 2.14 ( 1.18-3.87 ) 18.5-24.9 786 688 1.00 25.0-29.9 614 863 0.74 ( 0.63-0.88 ) 30.0-53.0 249 361 0.74 ( 0.59-0.92 ) Missing 41 21 Ptrend <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
BMI at age 30 (kg/m 2 ) Example: Association between Leanness and UADT cancers, earlier measure Overall Ca Co OR* 95% CI 13.0-18.4 60 57 1.08 ( 0.70-1.66 ) 18.5-24.9 1066 1188 1.00 25.0-29.9 405 467 1.03 ( 0.85-1.24 ) 30.0-53.0 113 146 0.91 ( 0.67-1.23 ) Missing 103 98 Ptrend 0.677 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
BMI at age 21 (kg/m 2 ) Example: Obesity and endometrial cancer risk No. Cases RR 1 (95%CI) RR 2 (95%CI) Quartile 1: <18.840 89 1.00 1.00 Quartile 2: 18.840 to <20.216 120 1.32 (1.00, 1.73) 1.28 (0.97, 1.69) Quartile 3: 20.216 to <21.897 116 1.34 (1.01, 1.76) 1.27 (0.96, 1.68) Quartile 4: 21.897 167 1.98 (1.53, 2.56) 1.78 (1.36, 2.31) Ptrend <0.001 <0.001 BMI at baseline (kg/m 2 ) 3 <25 187 1.00 1.00 25 to <30 126 1.27 (1.02, 1.60) 1.29 (1.02, 1.65) 30 179 3.22 (2.62, 3.95) 3.22 (2.48, 4.18) Ptrend <0.001 <0.001 1 Age-adjusted RR. 2 RRs were adjusted for age, ethnicity, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, oral contraceptive use, parity, smoking history, diabetes, and hypertension. 3 Additionally adjusted for BMI at age 21 (quartiles).
Example: Obesity and endometrial cancer risk Race/Ethnicity African American Japanese Americans Latina White BMI at age 21 (kg/m 2 ) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) <19.35 20 1.00 39 1.00 16 1.00 44 1.00 19.25 to <21.23 27 1.52 (0.85, 2.71) 46 1.31 (0.86, 2.01) 17 0.88 (0.44, 1.74) 45 0.93 (0.61, 1.41) > 21.23 37 1.63 (0.94, 2.84) 51 1.84 (1.20, 2.81) 50 1.82 (1.02, 3.22) 51 1.25 (0.83, 1.89) P Trend 0.092 0.005 0.014 0.278 BMI at baseline (kg/m 2 ) <25 14 1.00 82 1.00 17 1.00 68 1.00 25 to <30 22 1.19 (0.60, 2.34) 30 1.26 (0.82, 1.93) 26 1.41 (0.76, 2.62) 35 1.21 (0.80, 1.83) 30 48 2.96 (1.58, 5.54) 24 4.24 (2.58, 6.97) 40 3.47 (1.91, 6.28) 37 2.47 (1.61, 3.78) P trend <0.001 <0.001 <0.001 <0.001
Ethnic differences between BMI and body fat Hu FB, Obesity Epidemiology
Validity of self-reported height and weight Hu FB, Obesity Epidemiology
Factors affecting body weight Genetic Endocrine/regulatory Behavioral Psychosocial Environmental
Factors to consider when investigating body weight change Reverse causality Confounding variables Ethnic differences Self report validity, information bias Energy Balance Food consumption Physical Activity Collinearity
Energy Balance The balance between energy taken in, generally by food and drink, and energy expended. Energy expenditure is influenced by genetics, body size and amount of muscle, and by physical activity. While calories are probably the most critical element in maintaining your energy balance, other factors in your diet such as how much fiber or calcium you eat may influence your energy expenditure and how much muscle and fat you have. Vaughn P, www.cancer.gov
Measuring Food Consumption
Example of Semi-quantitative FFQ DIETARY HABITS [Example, will need to adapt to each country] How often did you consume the following foods and beverages one year ago? Unit Food item How many times per day, week, month, year? (mark one column only) day week month year Never D1 1 portion Beef D2 1 portion Pork D3 1 portion Poultry D4 1 portion Other meat (lamb, etc.) D5 1 portion Fish D6 1 portion Ham, salami, sausages D7 1 portion Raw green vegetables and salads D8 1 portion Cooked green vegetables D9 1 portion Carrots D10 1 portion Fresh tomatoes D11 1 portion Pulses (peas, beans, etc.)
Example of a quantitative FFQ
Physical Activity
metabolic equivalents of energy expenditure (METs) METs= (sleeping [h/d]*0.91 + sitting [h/d]*1.0+ light activity [h/d]*2.4 + moderate activity [h/d]*4.0 + vigorous activity [h/d]*7.2)/24)
Example: Physical activity and endometrial cancer No. Cases RR 1 (95% CI) RR 2 (95% CI) RR 3 (95% CI) Physical activity (METs) 3 Quartile 1: <1.4015 Quartile 2: 1.4015 to <1.5900 134 123 1.00 0.86 (0.67,1.10) 1.00 0.86 (0.67, 1.10) 1.00 0.89 (0.70, 1.14) Quartile 3: 1.5900 to <1.7576 116 0.78 (0.61, 1.01) 0.81 (0.63, 1.05) 0.86 (0.67, 1.11) Quartile 4: 1.7576 P trend 119 0.81 (0.63, 1.04) 0.072 0.86 (0.67, 1.10) 0.198 0.92 (0.72, 1.19) 0.493 1 Age-adjusted RR. 2 RRs were adjusted for age, ethnicity, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, oral contraceptive use, parity, smoking history, diabetes, and hypertension. 3 Additionally adjusted for BMI at baseline (quartiles).
Different measures of body weight change and cancer Weight difference BMI difference % change (weight or BMI) [(measure at baseline minus measure at age 21) / measure at age 21] 100 % Average annual BMI change % BMI change/(time between BMI measures)
Example of BMI change in UADT cancers, multicenter case-control study Percent BMI change from age 30 to study entry Overall Ca Co OR* 95% CI <-15% 169 79 1.52 ( 1.07-2.17 ) -15% BMI change <-5% 227 150 1.24 ( 0.93-1.67 ) -5% BMI change <5% 378 338 5% BMI change <15% 261 425 0.59 ( 0.46-0.76 ) 15% BMI change <25% 143 224 0.57 ( 0.43-0.77 ) BMI change 25% 153 261 0.59 ( 0.44-0.79 ) Missing 92 76 Ptrend <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Ptrend <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency. Example of BMI change in UADT cancers, multicenter case-control study, cont. Percent BMI change from age 30 to 2 years prior study entry Overall Ca Co OR* 95% CI <-15% 102 70 1.16 ( 0.80-1.69 ) -15% BMI change <-5% 176 132 1.12 ( 0.83-1.52 ) -5% BMI change <5% 570 501 5% BMI change <15% 347 522 0.73 ( 0.59-0.90 ) 15% BMI change <25% 226 325 0.74 ( 0.58-0.94 ) BMI change 25% 213 307 0.77 ( 0.60-0.99 ) Missing 113 99
Possible explanations: Reverse causality Residual confounding Alterations in smoking or drinking behaviors Smoking cessation results in weight gain Biological mechanism
Association may be due to smoking cessation Associations between BMI change and UADT SCCs, stratified by smoking Variable BMI change from age 30 to 2 years prior to study entry Loss (<-5%) Stable Gain ( +5%) Ptrend Smoking Status Never smoking case/controls 22/71 36/171 102/430 OR (95% CI)* 1.19 (0.62-2.26) 1.00 0.95 (0.60-1.51) 0.476 Former smoking case/controls 51/67 94/161 243/431 OR (95% CI)* 1.17 (0.72-1.91) 1.00 0.92 (0.66-1.27) 0.271 Current smoking case/controls 205/64 440/169 441/293 OR (95% CI)* 1.06 (0.74-1.52) 1.00 0.69 (0.46-0.76) <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Drinking Status Never drinking Associations between weight change and UADT cancers, stratified by UADT risk factors, cont Loss Stable Gain ptrend case/controls 14/40 23/54 53/138 OR (95% CI)* 0.62 (0.25-1.54) 1.00 0.82 (0.41-1.62) 0.689 Former drinking case/controls 53/32 86/39 112/106 OR (95% CI)* 0.76 (0.38-1.53) 1.00 0.46 (0.26-0.82) 0.041 Current drinking case/controls 210/123 461/410 629/917 OR (95% CI)* 1.32 (0.97-1.80) 1.00 0.78 (0.64-0.95) <0.001 *Adjusted for center, education, sex, age, fruit and vegetable intake, tobacco status/frequency, and alcohol frequency.
Loss Stable Gain Smoking and Drinking status Never smokes and drinks case/controls 6/22 9/36 22/93 never smoke and drink 0.97 (0.25-3.74) 1.00 0.95 (0.34-2.67) 0.946 No drinking but smokes case/controls 8/18 14/18 31/45 OR (95% CI)* 0.38 (0.09-1.50) 1.00 0.71 (0.24-2.09) 0.446 No smoking but drinks case/controls 16/47 28/134 80/340 OR (95% CI)* 1.20 (0.55-2.60) 1.00 0.93 (0.55-1.58) 0.495 Smokes and drinks Associations between weight change and UADT cancers, stratified by UADT risk factors, cont. case/controls 247/108 519/315 661/683 OR (95% CI)* 1.23 (0.92-1.64) 1.00 0.63 (0.52-0.77) <0.001
Rationale for leanness, UADT cancer association leanness UADT cancer Biological mechanism DNA damage Difference in mean BMI change between former and current smokers, where former smokers showed a greater BMI increase (p<0.001). Sensitivity test showed mean BMI change greater in those who claimed to stop smoking 3 years prior to BMI measure. (n= 51, 12.0% vs. 11.2%; ttest pvalue=0.1952).
Confounding, by age Time to Disease Loss Stable Gain Ptrend Quartile 1 case/controls 50/41 166/129 126/210 OR (95% CI)* 0.79 (0.44-1.40) 1.00 0.50 (0.33-0.74) 0.009 Quartile 2 case/controls 88/42 176/139 236/327 OR (95% CI)* 1.65 (0.98-2.77) 1.00 0.78 (0.56-1.09) 0.002 Quartile 3 case/controls 68/41 128/114 220/313 OR (95% CI)* 1.25 (0.71-2.21) 1.00 0.77 (0.53-1.12) 0.038 Quartile 4 case/controls 72/78 100/117 204/304 OR (95% CI)* 1.00 (0.62-1.63) 1.00 0.91 (0.62-1.32) 0.591 ** Quartile 1: <22 years, quartile 2: 22<time to disease <30, quartile 3: 30< time to disease<38, and quartile 4: >38 years.
Example of another smoking related cancer Lung cancer, population based case-control study Association between BMI change and Lung cancer BMI change Case/ Control Crude OR (95% CI) Adjust OR 1 (95% CI) <5%Weight loss 64/47 1.74 (1.11, 2.72) 1.26 (0.73, 2.17) -5% loss to < 5% gain 113/144 1.00 1.00 5% to <15% 132/257 0.66 (0.47, 0.91) 0.80 (0.54, 1.18) 15% to <25% 113/215 0.67 (0.48, 0.94) 0.78 (0.52, 1.17) 25% to <35% 67/153 0.56 (0.38, 0.82) 0.58 (0.37, 0.91) >35% weight gain 122/224 0.69 (0.50, 0.97) 0.58 (0.39, 0.87) P trend 0.543 0.163
Causal diagram BMI change and endometrial cancer Confounding variables BMI change from age 21 to baseline r= 0.74?? Endometrial Cancer BMI at Age 21 BMI at baseline
Body weight change (%) Example of Collinearity using BMI change in Endometrial cancer No. Cases <-5 (weight loss) 21 1.43 (0.82, 2.50) - 5 to <+5 30 1.00 5 to <15 87 1.66 (1.09, 2.51) 15 to <25 86 1.67 (1.10, 2.54) 25 to <35 72 1.80 (1.17, 2.77) 35 196 3.10 (2.08, 4.62) P trend <0.001 RR 1 (95% CI) RR 2 (95% CI) RR 3 (95% CI) 0.98 (0.54, 1.76) 1.46 (0.83, 2.55) 1.00 1.00 1.70 (1.12, 2.58) 1.44 (0.83, 1.92) 1.76 (1.16, 2.67) 1.26 (0.75, 1.82) 1.94 (1.26, 2.98) 1.17 (0.75, 1.82) 3.55 (2.38, 5.29) 1.38 (0.89, 2.14) <0.001 0.429 1 RRs were adjusted for age, ethnicity, education, age at menarche, age at menopause, duration and type of hormone therapy, oral contraceptive use, parity, smoking history, diabetes, and hypertension. 2 Model 1 and adjusting for BMI at age 21 3 Model 1 and adjusting for BMI at baseline
Stratify by BMI measures BMI at 21 (kg/m 2 ) BMI Change Category 1 Category 2 (5% to <35%) Category 3 ( 35%) (<5%) 1 No. cases RR 2 No. cases RR 2 No. cases RR 2 Ptrend Tertile 1: <19.35 11 1.00 70 1.42 (0.75, 2.70) 49 1.96 (0.98, 3.93) 0.035 Tertile 2: 19.35 to <21.23 18 1.00 69 1.28 (0.75, 2.16) 57 3.15 (1.77, 5.61) <0.001 Tertile 3: 21.23 22 1.00 106 1.91 (1.20, 3.04) 90 3.83 (2.34, 6.28) <0.001 P interaction= 0.0968 BMI at baseline (kg/m 2 ) <25 45 1.00 133 1.48 (1.03, 2.13) 9 2.09 (0.95, 4.61) 0.018 25 6 1.00 112 1.43 (0.62, 3.27) 187 2.82 (1.23, 6.47) <0.001 P interaction= 0.6287
BMI change, stratified by ethnicity Race/Ethnicity African American Japanese Americans Latina White No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) BMI change (%) < +5% 3 1.00 21 1.00 4 1.00 20 1.00 5% to <20% 10 1.27 (0.35, 4.63) 62 2.04 (1.24, 3.37) 13 1.49 (0.48, 4.59) 39 1.32 (0.77, 2.27) 20% to <35% 16 1.51 (0.43, 5.23) 35 2.01 (1.16, 3.51) 25 2.63 (0.91, 7.61) 35 1.63 (0.93, 2.84) 35% 55 3.11 (0.95, 10.2) 18 2.46 (1.28, 4.73) 41 4.00 (1.41, 11.39) 46 2.51 (1.45, 4.34) P trend 0.001 0.009 <0.001 <0.001 2 Multivariate RRs were adjusted for age, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, duration and oral contraceptive use, parity, smoking history, diabetes, and hypertension and BMI at age 21.
Race/Ethnicity African American Japanese Americans Latina White Body weight change (%), ethnic specific tertiles 3 No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) No. Ca RR 2 (95% CI) Tertile 1 17 1.00 31 1.00 15 1.00 35 1.00 Tertile 2 22 1.34 (0.70, 2.54) 53 1.84 (1.17, 2.88) 27 1.97 (1.04, 3.72) 45 1.32 (0.84, 2.06) Tertile 3 45 2.75 (1.53, 4.94) 52 1.86 (1.17, 2.96) 41 3.17 (1.72, 5.86) 60 1.75 (1.13, 2.70) P trend <0.001 0.010 <0.001 0.011 2 Multivariate RRs were adjusted for age, education, age at menarche, menopausal status, age at menopause, duration and type of hormone therapy, duration and oral contraceptive use, parity, smoking history, diabetes, and hypertension and BMI at age 21. 3 Tertile distribution for African Americans: <23.59%, 23.59% to <42.80%, and 42.80%; Japanese Americans: <8.18%, 8.18% to <20.10%, > 20.10%; Latinas: <18.46%, 18.46% to <35.45%, > 35.45%; Whites: <10.00%, 10.00% to 26.19%, > 26.19%
Average annual weight change, example using endometrial cancer data Average annual weight change (%/year) No. Cases RR (95% CI) < 0.25 (weight loss) 9 0.98 (0.49, 1.95) 0.25 to < +0.25 84 1.00 0.25 to <0.50 78 1.12 (0.82, 1.52) 0.50 to <0.75 79 1.37 (1.00, 1.87) 0.75 to <1.0 58 1.44 (1.02, 2.04) 1.0% 184 2.53 (1.90, 3.38) Ptrend <0.001 Assumptions: Weight cycling is not a factor in endometrial cancer risk
Molecular approach Measure inflammatory markers Measure IGF1 and IGFBP3 levels Genotype sometimes correlates to phenotype (Cheng I, 2007; Al-Zahrani A, 2006) Calle EE, Kaaks R. Nature, 2004
Relationship between IGF1 and BMI Native Hawaiian African American White Latino Japanese American Henderson KD, et al., CEBP, 2006
Conclusions Limitations and Strengths Summary Future Directions
Limitations and Strengths, case control design Limitations Recall bias Reverse causation Strengths Ability to study associations with anthropometric measures in rare cancers More likely to have in-person questionnaire interviews to obtain additional anthropometric measures ie WHR Potential for specific questionnaire design Potentially providing ability to control residual confounding
Limitations and strengths of cohort design Limitations Potential for nonspecific questionnaires Strengths Reduction of temporal ambiguity. Potential for multiple weight measures
In Summary The study of anthropometric measures is necessary in cancer. Anthropometric measures are fairly valid, cost-effective means to measure adiposity. As of now weight maintenance is an effective means of prevention against obesity related cancer
Future Directions Improving epidemiological measures to reducing residual confounding and information bias of our anthropometric measures. Measures of WHR would assist further understanding the observed associations between BMI change and cancer. Further investigating the genetic and biological relationships between obesity and cancer would be beneficial.