Introduction Malnutrition and obesity are both hazards for healthy life. Consequences of malnutrition are exposure to disease and increase in mortality rates in the developing countries. 1 Risk of poor pregnancy outcome increases if mother is under-nutrition. A child's development entirely depends on the mother's nutritional status during the first 15 months of life. 2 Obesity is another form of malnutrition which is also a risk factor for several diseases, including hypertension (HYN), stroke, diabetes mellitus (DM), dyslipidaemia as well as breast and colon cancers. 3 Globally, obesity is emerging as an epidemic. 3,4 At least 2.8 million adults die each year as a result of being overweight and obese. 5 It is a positive indication that the proportion of underweight Pakistani women reduced from 14% to 9%, but, on the other side, the proportion of overweight and obese women has risen 12%, from 40% to 52%. 6 Globally, Pakistan is ranked 9th among the most obese nations, and which is more prevalent in women (25.5%) compared to men (18.8%). 7,8 Dietary habits of Pakistani population has changed, with fast food getting popularity, particularly in the youth. 8 Pakistanis consume energy- dense diet in the form of ghee, sugar and carbohydrates. Celebrations of important events in Pakistani culture is incomplete without the intake of high-calorie food. 8 The level of chronic energy deficiency (CED) and obesity vary from region to region and from country to country, as it depends on eating habits and norms and also on the environmental condition of the region. This necessitates identification of risk factors affecting the nutritional status of Pakistani women using body mass index (BMI) as a proxy measure of CED syndrome. For assessing adult nutritional status, BMI is a conventional tool in both clinical and public health practice. BMI is a value derived from the mass and height of a person, and is recognised as Quetelet's index. It is calculated by dividing weight in kilograms by height in meters squared (kg/m 2 ) and its cut- offs for Asian populations are: underweight <18.5, normal 18.5-22.9, overweight 23-24.9, and obese > 25. 9,10 CED (BMI <18.5) and obesity (BMI > 25) are two basic indicators of malnutrition. Population with BMI range 23-27·5 is considered at increased risk, and BMI > 27·5 at high risk. 10 The current study was planned to explore the risk factors influencing the nutritional status of women in Pakistan. Materials and Methods The retrospective secondary-data study was conducted at Lahore College for Women University, Lahore, Pakistan from March to July 2019, and comprised a review of the Pakistan Demographic and Health Survey (PDHS) 2017- 18 6 For which the data-collection period was from November 22, 2017, to April 30, 2018. It was the fourth such survey conducted as part of the worldwide Vol. 71, No. 4, April 2021 1069 ORIGINAL ARTICLE Socio demographic determinants of BMI of Pakistani women: An evidence from PDHS (2017-18) using quantile regression analysis Asifa Kamal, Aqsa Asghar Ali, Sameena Irfan Abstract Objective: To explore the socio-demographic determinants of nutritional status of Pakistani women. Methods: The retrospective secondary-data study was conducted at Lahore College for Women University, Lahore, Pakistan from March to July 2019, and comprised a review of the Pakistan Demographic and Health Survey 2017-18 for which the data-collection period was from November 22, 2017, to April 30, 2018. Body mass index was taken as a reflection of the women's nutritional status. Ordinary least square and quantile regression models were used for statistical analysis. Results: Age, education, frequency of watching TV, wealth index, husband's education and region showed a positive effect on women's body mass index, while age of women at first birth, women's working status, gender of household head and region showed negative effect on women's body mass index (p<0.05). Conclusion: Overweight/obesity was found to be a more serious problem compared to under-nutrition in Pakistani women. Keywords: PDHS 2017-18, Ordinary least square, OLS, Quantile regression, model, QR. Body mass index, BMI. (JPMA 71: 1069; 2021) DOI: https://doi.org/10.47391/JPMA.1459 Department of Statistics, Lahore College for Women University Lahore, Pakistan. Correspondence: Asifa Kamal. Email: asifa.k53@gmail.com