Shahid Kamal

Risk factors for breast cancer in Pakistani women aged less than 45 years

Background: There has been an increase in the incidence of breast cancer in previously low-risk Asian countries. It is important to identify the risk factors for Asian women, as little information currently exists for this population. Aim: The objective of the study was to determine risk factors for breast cancer among Pakistani women. Subjects and methods: 498 cases younger than 45 years were interviewed from 1 July 1997 to 31 December 1998 at two major cancer hospitals. Age-matched population-based controls were selected from two cities and two villages to represent urban and rural areas. For the variables under study, cases and controls were compared by t-test. Conditional multiple logistic regression models were applied to the data set. Results: Women with BMI ≥ 30, with a family history of breast cancer and who were parous were at increased risk. Among parous women risk factors included BMI ≥ 30, being in a consanguineous marriage, later age at menarche, later age at first full-term pregnancy, high parity and a history of abortion. Conclusion: The risk factors identified for Pakistani women below 45 years were similar to those observed in other studies. However, obesity in pre-menopausal women and late menarche were not protective and consanguinity was identified as a risk.

Multi-response optimization of rhamnolipid production using grey rational analysis in Taguchi method

Highlights • Optimization of rhamnolipid production under integrated Taguchi design and GRA.• The results were analyzed by using grey relational analysis.• In doing this, volumetric productivity of the process improved by 142%.• Total sugars concentration was the most influencing parameter.• This is a biocompatible production via sustainable technology.

Using PCA, Poisson and Negative Binomial Model to Study the Climatic Factor and Dengue Fever Outbreak in Lahore

Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan. The study aims to understand, explore and compare the climatic factors of Karachi and Lahore that causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. Principal component analysis (PCA) is performed for the purpose of finding if there is/are any general environmental factor/structure which could be considered as Pakistani climate. We developed an early warning model for the prediction of dengue outbreak in Lahore. This has been done by using Poisson regression and Negative binomial regression model. For this purpose we use daily, weekly and monthly data of Lahore. The negative binomial model with lag (28) for Lahore daily data for climatic variable is best model. Lahore daily and weekly maximum temperature effect negatively and for the past 28 days it is estimated to negatively influence on the dengue occurrence by 26.1% times. Daily wind speed is effecting negatively by 14.7% times and minimum temperature effect positively for the past 28 days by 86.7%times.

Mixed Portmanteau Test for Diagnostic Checking of Time Series Models

Model criticism is an important stage of model building and thus goodness of fit tests provides a set of tools for diagnostic checking of the fitted model. Several tests are suggested in literature for diagnostic checking. These tests use autocorrelation or partial autocorrelation in the residuals to criticize the adequacy of fitted model. The main idea underlying these portmanteau tests is to identify if there is any dependence structure which is yet unexplained by the fitted model. In this paper, we suggest mixed portmanteau tests based on autocorrelation and partial autocorrelation functions of the residuals. We derived the asymptotic distribution of the mixture test and studied its size and power using Monte Carlo simulations.

Psychometric Analysis of Depression, Anxiety and Stress Among Women of Wazirabad City

In this paper psychometric analysis of Depression, Anxiety and Stress among Women living in Wazirabad City has been explored. Cluster sampling technique was used to collect a sample of size 334. For this purpose Urdu version of Depression, Anxiety and Stress (DASS-21) questionnaire was administered along with 10 demographic. DASS-21 data has been analyzed to study the relationship between “depression”, “anxiety” and “stress” across various demographic characteristics. DASS-21 shown good internal consistency (Cronbach’s alpha 0.86) and Confirmatory Factor Analysis showed consistency with previously found factor structures. Strong relationship of “anxiety” and “stress” has been observed with age; while no association was observed with “income”. “Education” has mild effect with the items of “depression”, “anxiety” and “stress”. “Illness” and “occupation” found to be strong factors of “depression”, “anxiety” and “stress”. Another major factor of “stress” found to be “family living system” while “marital status” also affects some of items.

ANOVA with Summary Statistics: A Stata Macro

Almost all available statistical packages are capable of performing Analysis of Variance (ANOVA) from raw data. Some of statistical packages have capability to perform independent sample t-test, and some other tests of significance on summary data, but seldom would you come across a software that has the capability to perform ANOVA directly on summary data. However some packages can perform one-way ANOVA after generating surrogate data from summary statistics. In this short note we have given STATA program to perform one-way ANOVA on summary data; in addition this program also performs Bartllet’s tests of equality of variances. The idea can be extended to two-way and higher way ANOVA’s. Examples have been given for illustration.