12 research outputs found
Knee pain and radiographic osteoarthritis interact in the prediction of levels of self-reported disability
Objective To determine predictors of disability depending on whether joint deformity and pain reporting exist independently or concurrently. Methods Subjects were 154 volunteers for an osteoarthritis screening examination. Eligible subjects completed questionnaires for physical function, pain, and depressive symptoms; underwent evoked pain testing for tenderness assessment; and had anteroposterior and lateral radiographs taken of both knees. Two blinded rheumatologists scored the images using Kellgren-Lawrence criteria to determine presence of deformity. Results Subjects were divided into 3 subgroups based on radiographic evidence of deformity and self-reported pain. Disability was greatest when pain and deformity occurred together (F[2,151] = 18.8, P < 0.0001). Self-reported disability in the absence of deformity was predicted by body mass index, pain threshold, and anxiety symptoms; disability was predicted by the number of osteophytes and depressive symptoms when pain and deformity occurred together. Conclusion Self-reported disability in osteoarthritis of the knee is greatest with concurrent pain and joint deformity. When pain and deformity do not cooccur, disability appears to be related to separate factors, including anxiety and pain threshold (e.g., tenderness).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34314/1/20537_ftp.pd
A cross-sectional investigation of regional patterns of diet and cardio-metabolic risk in India
<p>Abstract</p> <p>Background</p> <p>The role of diet in India's rapidly progressing chronic disease epidemic is unclear; moreover, diet may vary considerably across North-South regions.</p> <p>Methods</p> <p>The India Health Study was a multicenter study of men and women aged 35-69, who provided diet, lifestyle, and medical histories, as well as blood pressure, fasting blood, urine, and anthropometric measurements. In each region (Delhi, n = 824; Mumbai, n = 743; Trivandrum, n = 2,247), we identified two dietary patterns with factor analysis. In multiple logistic regression models adjusted for age, gender, education, income, marital status, religion, physical activity, tobacco, alcohol, and total energy intake, we investigated associations between regional dietary patterns and abdominal adiposity, hypertension, diabetes, and dyslipidemia.</p> <p>Results</p> <p>Across the regions, more than 80% of the participants met the criteria for abdominal adiposity and 10 to 28% of participants were considered diabetic. In Delhi, the "fruit and dairy" dietary pattern was positively associated with abdominal adiposity [highest versus lowest tertile, multivariate-adjusted OR and 95% CI: 2.32 (1.03-5.23); P<sub>trend </sub>= 0.008] and hypertension [2.20 (1.47-3.31); P<sub>trend </sub>< 0.0001]. In Trivandrum, the "pulses and rice" pattern was inversely related to diabetes [0.70 (0.51-0.95); P<sub>trend </sub>= 0.03] and the "snacks and sweets" pattern was positively associated with abdominal adiposity [2.05 (1.34-3.14); P<sub>trend </sub>= 0.03]. In Mumbai, the "fruit and vegetable" pattern was inversely associated with hypertension [0.63 (0.40-0.99); P<sub>trend </sub>= 0.05] and the "snack and meat" pattern appeared to be positively associated with abdominal adiposity.</p> <p>Conclusions</p> <p>Cardio-metabolic risk factors were highly prevalent in this population. Across all regions, we found little evidence of a Westernized diet; however, dietary patterns characterized by animal products, fried snacks, or sweets appeared to be positively associated with abdominal adiposity. Conversely, more traditional diets in the Southern regions were inversely related to diabetes and hypertension. Continued investigation of diet, as well as other environmental and biological factors, will be needed to better understand the risk profile in this population and potential means of prevention.</p
Multi-center feasibility study evaluating recruitment, variability in risk factors and biomarkers for a diet and cancer cohort in India
<p>Abstract</p> <p>Background</p> <p>India's population exhibits diverse dietary habits and chronic disease patterns. Nutritional epidemiologic studies in India are primarily of cross-sectional or case-control design and subject to biases, including differential recall of past diet. The aim of this feasibility study was to evaluate whether a diet-focused cohort study of cancer could be established in India, providing insight into potentially unique diet and lifestyle exposures.</p> <p>Methods</p> <p>Field staff contacted 7,064 households within three regions of India (New Delhi, Mumbai, and Trivandrum) and found 4,671 eligible adults aged 35-69 years. Participants completed interviewer-administered questionnaires (demographic, diet history, physical activity, medical/reproductive history, tobacco/alcohol use, and occupational history), and staff collected biological samples (blood, urine, and toenail clippings), anthropometric measurements (weight, standing and sitting height; waist, hip, and thigh circumference; triceps, sub-scapula and supra-patella skin fold), and blood pressure measurements.</p> <p>Results</p> <p>Eighty-eight percent of eligible subjects completed all questionnaires and 67% provided biological samples. Unique protein sources by region were fish in Trivandrum, dairy in New Delhi, and pulses (legumes) in Mumbai. Consumption of meat, alcohol, fast food, and soft drinks was scarce in all three regions. A large percentage of the participants were centrally obese and had elevated blood glucose levels. New Delhi participants were also the least physically active and had elevated lipids levels, suggesting a high prevalence of metabolic syndrome.</p> <p>Conclusions</p> <p>A high percentage of participants complied with study procedures including biological sample collection. Epidemiologic expertise and sufficient infrastructure exists at these three sites in India to successfully carry out a modest sized population-based study; however, we identified some potential problems in conducting a cohort study, such as limited number of facilities to handle biological samples.</p