More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD). After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7%) were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables  were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs) were designed with integrated genetic algorithm (GA) and support vector machine (SVM) by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and OCS therapies should be continuously monitored, especially for patients with older age and women after menopause, to prevent from exceeding the maximum dosage. Chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis, allergic rhinitis and sinusitis, obstructive sleep apnoea syndrome, pulmonary hypertension, and other occupational lung diseases, are caused by disorder of the airways and other structures of the lung . More thCOPD is an inflammatory disease of the lung characterized by progressive airflow obstruction, systematic chronic inflammation, and recurrent acute exacerbation , 9. WHO Clinical decision support systems (CDSSs) provide useful information and expert knowledge to assist healthcare providers to improve diagnosis and treatment outcomes, disease managements, and healthcare quality for patients in both home and clinical settings and have been shown to be capable of improving healthcare outcomes in medical practice . CDSSs hTaiwanese National Health Insurance program is a single-payer, compulsory insurance system that was established in 1995 by the Bureau of National Health Insurance (NHI), Ministry of Health and Welfare. The insurance program provides healthcare to 99% of the 23.74 million citizens of Taiwan and maintains contracts with 97% of the nation's healthcare institutions. The National Health Research Institute is authorized to establish the National Health Insurance Research Database (NHIRD), as well as to manage registration and claim data for the 23 million insured citizens. Most studies used a subset of the NHIRD that consisted of 1 million randomly sampled beneficiaries enrolled in the NHI program. According to a PubMed website search conducted in July 2016, around 4000 studies investigated using NHIRD have been published . The higMinority cases refer to rare patterns or abnormal behaviors that are difficult to detect but are often important. In real application domains, such as oil spill detection in satellite radar images , text clThe classifiers built based on logistic regression, decision tree, standard neural network, and support vector machine are generally suitable for balanced data only. When dealing with imbalanced data, these classifiers often bias toward the majority cases while distorting the minority cases. To improve the predictive performance, the methods for modeling imbalanced datasets include data preprocessing, cost-sensitive learning, and kernel-based methods .Resampling data in the sample space and selecting features in the feature space are commonly used preprocessing strategies for dealing with imbalanced datasets. There are 3 categories of resampling methods, including undersampling, oversampling, and hybrid sampling methods, applied for rebalancing the imbalanced datasets. Oversampling methods are used to deal with the minority samples by generating new minority samples, while undersampling strategies are applied to randomly discard the majority samples to balance the datasets. The hybrid sampling is a combination of both methods.Undersampling includes random undersampling and informed undersampling . The majThe simplest oversampling method is random oversampling, in which the minority samples are randomly duplicated. A critical problem of random oversampling is overfitting. Another major approach in oversampling is synthetic minority oversampling technique (SMOTE), which generates synthetic samples on the line segments connecting each minority sample to its k-nearest neighbors in minority class . A majorCost-sensitive learning is useful for handling imbalanced healthcare data since classifying a minority (positive) sample to the majority (negative) class often costs more than classifying a majority sample to the minority class. There are 3 major categories generally found in cost-sensitive learning: approaches that assign different weights to samples, ensemble schemes that integrate with cost-sensitive methods, and methods that incorporate the misclassified costs directly into the classifiers . The firC to convert the misclassified majority samples into minority samples. The reconstructed more balanced training dataset was then applied for training the classification models with better predictive performance using different artificial techniques like multilayer perceptron (MLP), logistic regression (LR), and random forest (RF). In contrast, Jian et al. [Support vector machine (SVM) is mostly integrated in kernel-based methods for imbalanced data learning. In Farquad and Bose , oversamn et al.  applied n et al.  proposedn et al. , Borderln et al. , Safe-Len et al. , and Clun et al. .According to the aforementioned description, the datasets retrieved from the NHIRD for public health studies are mostly imbalanced with minority to majority sample ratios ranging from 1 : 4 to 1 : 5, and the decision hyperplane tends to bias toward the majority class when adopting the accuracy-driven algorithm to design the CDSS. The dataset adopted in this study is even more imbalanced with the minority to majority ratio approximates to 1 : 9. The objectives include the following: (1) investigate the association between corticosteroid use and fracture using NHIRD and (2) design the CDSSs to predict fracture occurrence for patients with chronic respiratory diseases prescribed with corticosteroids by dealing with the imbalanced dataset. The preliminary results were reported in .Data of the patients who were 20 years old or older visiting healthcare centers (outpatients or inpatients) and had been prescribed with inhale corticosteroids because of diagnosed asthma (ICD-9-CM 493), chronic obstructive pulmonary disease (COPD) , or bronchiectasis (ICD-9-CM 494) within 2002–2010 were retrieved from the NHIRD for this investigation. Patients diagnosed with hip or vertebrate fractures before using inhaled corticosteroid were excluded. The outcome measure was hip fracture (ICD-9-CM 820) or vertebral fracture (ICD-9-CM 805 and 806). The data of 11645 patients, including 1134 patients with the fracture (614 men and 520 women) and 10511 patients without fracture (6211 men and 4300 women), were retrieved from the NHIRD within 2001–2013 and were used for statistical analysis and CDSS design. The patients were divided into 4 groups according to age: 20–40, 41–50, 51–64, and ≥65 years. The respiratory diseases included were asthma (ICD-9-CM codes 493), COPD , and bronchiectasis (ICD-9-CM codes 494). Other comorbidities included diabetes (ICD-9-CM codes 250), cancer (ICD-9-CM codes 140–208), liver cirrhosis (ICD-9-CM codes 571.2 and 571.5), end-stage renal disease (ICD-9-CM codes 585), and osteoporosis (ICD-9-CM codes 722.0).t-test. The statistical significance was defined as p < 0.05.SPSS 22.0 software (IBM.SPSS) was adopted for all statistical analyses. Difference in the proportional distribution of the demographic characteristics and comorbidities of the patients with fracture and those without fracture were compared and tested using the Chi-square test. The overall, age-specific, and comorbidity-specific incidences of fractures in both fracture and nonfracture groups were also compared. The cumulative dose, mean follow-up daily dose, and mean exposed daily dose of prescribed corticosteroid were also analyzed using unpaired Student's n chromosomes were updated by combining n/2 new chromosomes generated from crossover with the other n/2 chromosomes obtained from mutation. The parameters of the genetic algorithm were set as follows: number of initial chromosome population (n) = 10, maximum number of iterations with unimproved fitness value (MaxNotImproved) = 500, and maximum number of total iterations (MaxIteration) = 100000. When the current iteration (CurrentIteration) ≥ MaxIteration or the number of iterations with unimproved fitness (NumOfNotImproved) ≥ MaxNotImproved, the program terminated.As shown in m samples by including all the m minority samples and randomly selecting m-nonduplicated samples from the M (M > m) samples in the majority class. In contrast, in the cluster-based undersampling, the samples in the majority class were clustered into m clusters that each consisted of ⌊M/m⌋ or ⌊M/m⌋ + 1 samples. And then, the kNN algorithm was applied to select the sample which was nearest to the center of gravity in each cluster, resulting in a balanced training set containing 2m samples for cross-validation. After the CDSSs had been trained, the imbalanced testing dataset was used for testing the predictive performance of the models.The data retrieved from the NHIRD were divided into training and testing datasets, each contains 50% of the samples in majority class and minority class, respectively, that is, 567 samples with fracture and 5255 samples without fracture. Random undersampling, cluster-based undersampling  methods Independent training and testing (ITT) was adopted for training and testing effectiveness of the CDSS  that 50%In the testing phase, the imbalanced testing dataset was applied for testing the designed CDSSs obtained in the testing phase. When designing the CDSSs, selection of the objective function is crucial in obtaining optimal CDSS models. In this study, the cost-sensitive objective functions, including AUC and combined accuracy, sensitivity, and specificity, were used to obtain the optimal CDSSs with imbalanced datasets. Equation  shows thIn , we inteIn order to verify the feasibility of the proposed method, a pilot study which used the CoIL challenge dataset  and WDBCp < 0.01). The patients with fracture were older than those without fracture (p < 0.001). The mean ages of the patients with fracture were 70.5 ± 12.5 years, and those without fracture were 58.5 ± 18.1 years. The prevalence of respiratory diseases and other comorbidities, including COPD (64.7% versus 51.6%), DM (14.9% versus 12.4%), end-stage renal disease (2.8% versus 1.4%), and osteoporosis (7.1% versus 3.6%), was significantly higher in the fracture cohort than in the comparison cohort (p < 0.05), while the prevalence of asthma was significantly lower in the fracture cohort than in the comparison cohort (p < 0.001). On the other hand, bronchiectasis (5.8% versus 4.7%), liver cirrhosis (1.1% versus 0.8%), and cancer (4.7% versus 4.4%) were not significantly different between the 2 groups , while the mean follow-up daily dose (59.56 ± 285.58 versus 59.74 ± 218.39) did not reach significance (p > 0.05). Regarding the follow-up (999.65 ± 997.09 versus 706.77 ± 907.35 days) and exposed (154.04 ± 320.91 versus 90.11 ± 194.80 days) durations, the patients with fracture were significantly longer (p < 0.001) than those without fracture.p < 0.001), while the mean follow-up daily dose (0.44 ± 2.31 versus 1.00 ± 3.91) was significantly lower (p < 0.001). On the other hand, the mean exposed daily dose (0.51 ± 0.81 versus 0.55 ± 1.35) was not significantly different between patients with and without fracture (p > 0.05). With regard to the follow-up (1777.17 ± 1039.82 versus 1370.91 ± 1097.76 days) and exposed (453.79 ± 584.65 versus 342.35 ± 503.32 days) durations of inhaled corticosteroid, the patients with fracture were significantly longer (p < 0.001) than those without fracture.Although allergic rhinitis and sinusitis are also a type of chronic respiratory diseases, they are not included for analysis in the current study for they are usually treated with intranasal corticosteroid  having lAs shown in OCS was reported to be associated with an increased dose-response risk of fracture or osteoporosis in patients with chronic respiratory disease  and patiThe effect of corticosteroid use remains controversial. It was reported that corticosteroid use may increase the risk of fracture for patients with COPD –15. Howep < 0.001), COPD , and bronchiectasis  for patients with and without fracture receiving OCS and ICS. It was noted that the prevalence of asthma in patients with fracture was significantly lower than those without fracture, while COPD was more prevalent in patients with fracture than those without fracture. With regard to bronchiectasis, although it was more prevalent in patients with fracture, but not reaching significance, the inconsistency might be caused by a difficulty in differentiating skeletal effects of corticosteroid medications and COPD itself [D itself  and sympD itself , 78 or bD itself  for someD itself .p < 0.05), ESRD , and osteoporosis  for patients with fracture was significantly higher than those without fracture. Bountiful literatures have shown the associations between diabetes and bone fracture. Forsen et al. [Diabetes (DM), end-stage renal disease (ESRD), and osteoporosis were shown to be comorbidities for patients with fracture who had been receiving OCS and ICS treatments. As presented in n et al.  reportedn et al. . Patientn et al. . Stehmann et al.  reportedn et al. .p < 0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) are significantly (p < 0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT$45,000 (US$1500) per patient in the current Taiwanese National Health Insurance setting [Recently, we have conducted a prospective study to verify the effectiveness of a designed CDSS in ventilator weaning  and desi setting . The CDSThe CDSS for predicting ventilator weaning was designed based on the datasets collected in respiratory care centers which were more balanced; in contrast, the dataset adopted in this study was retrieved from NHIRD and was highly imbalanced. As shown in p < 0.05) between fracture and nonfracture groups  because of intermittent exacerbations. OCS administrated for treating acute exacerbation may have stronger effect than ICS on osteoporosis and fracture. Moreover, previous studies mainly focused on the effects of ICS on osteoporosis or fracture for patients with asthma and COPD, respectively. The effect of ICS on osteoporosis or fracture for patients with asthma-COPD and bronchiectasis-COPD overlap syndromes should also be considered. Future works will account for the effect of accumulated OCS and ICS dose, not just OCS or ICS dose, on osteoporosis or fracture. Patients with asthma-COPD overlap syndrome and bronchiectasis-COPD overlap syndromes will be separately considered for investigating the effect of OCS and ICS on fracture.Based on the analytical results, it was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The designed CDSSs exhibited satisfactory performance in the prediction of fractures for patients who were prescribed with corticosteroids. We suggested that the accumulated dose of ICS and OCS therapies should be continuously monitored to prevent from exceeding the maximum dosage, especially for patients with older age and women after menopause.


To investigate the role of maximum tumour diameter (D-max) reduction rate at CT examination in predicting histopathological tumour regression grade (TRG according to the Becker grade), after neoadjuvant chemotherapy (NAC), in patients with resectable advanced gastric cancer (AGC).  Eighty-six patients  with resectable AGC (≥T3 or N+), treated with NAC and radical surgery, were enrolled from 5 centres of the Italian Research Group for Gastric Cancer (GIRCG). Staging and restaging CT and histological results were retrospectively reviewed. CT examinations were contrast enhanced, and the stomach was previously distended. The D-max was measured using 2D software and compared with Becker TRG. Statistical data were obtained using “R” software.  The interobserver agreement was good/very good. Becker TRG was predicted by CT with a sensitivity and specificity, respectively, of 97.3% and 90.9% for Becker 1 (D-max reduction rate > 65.1%), 76.4% and 80% for Becker 3 (D-max reduction rate < 29.9%), and 70.8% and 83.9% for Becker 2. Correlation between radiological and histological D-max measurements was strongly confirmed by the correlation index (c.i.= 0.829).  D-max reduction rate in AGC patients may be helpful as a simple and reproducible radiological index in predicting TRG after NAC. In the Western world, almost two-thirds of patients with gastric cancer (GC) have locally advanced tumours  at the time of diagnosis with a less than 50% chance of radical surgery , 2. For Even if long-term outcomes of patients with advanced gastric cancer (AGC) remain poor despite multimodality treatment , 7, patiIn this sense, histopathological regression (HPR) after chemotherapy is believed to be an important objective parameter of response to therapy and the tumour regression grade (TRG) was first described as a measure of histologic response in gastric cancer patients by Becker et al., who observed histopathological changes in surgical specimens treated with NAC compared with resected cancers from patients treated with surgery alone . The cliThe purpose of our study is therefore to investigate the feasibility of GC maximum tumour diameter (D-max) reduction rate at CT examination as an effective, easy to use, and reproducible radiological index in predicting TRG after NAC. This multicentre study was conducted by the Italian Research Group for Gastric Cancer (GIRCG), a multidisciplinary research group including clinicians  with recognised expertise in GC diagnosis, care, and research from over 25 specialised centres in Italy.n = 3), presence of metastatic disease at restaging CT (n = 4), neoplastic involvement of the esophagus (n = 2), clinical complications during chemotherapy needing urgent surgery (n = 3), and inappropriate CT methodology or technical parameters . All the 86 patients included in the study  underwent staging CT examination before NAC and a restaging CT performed within a maximum period of 45 days  from surgery; sixteen out of 86 patients also underwent an intermediate CT examination after 2 cycles of chemotherapy , totalling to 188 examinations. Different chemotherapy regimens are reported in This study was approved by the institutional review boards of our hospitals, and written informed consent was obtained from all subjects. Abdominal CT examinations of 86 patients were retrospectively reviewed from a cohort of 103 consecutive patients treated with NAC followed by gastrectomy in 5 GIRCG centres , between January 2010 and June 2017. Inclusion criteria consisted of biopsy-proven, locally-advanced GC without distant metastases . Seventeen out of 103 patients were excluded because of an interval between CT and surgery longer than 45 days (CT scans (CTs) were obtained using a 64-detector row configuration  for 40 patients, a 16-detector row configuration  for 19 patients, a 32-detector row configuration  for 18 patients, and a 128-detector row configuration  for the remaining 9 patients . All pat2, was placed over the lesion and another ROI was placed over the aorta (minimum area of 20 mm2). The T parameter was evaluated using all the postcontrast phases available, distinguishing T ≥ 3 from T ≤ 2, according to CT criteria for T staging of the AJCC cancer staging manual (8th edition) and based on the concept that the normal gastric wall is typically seen as a three-layered pattern on the contrast-enhanced CT images [All 188 CT examinations (140 for 70 patients and 48 for 16 patients) were analysed in the arterial late phase on a reconstruction and image interpretation console  adjusting the image's level, window and enlargement values each time, and routinely using a 2D multiplanar reconstruction technique . Images were independently reviewed by two blinded readers, a resident radiologist and a radiologist with 4- and 15-year experience in abdominal CT, respectively (FG and MAM). Readers were asked to review the images of each patient in a random manner, avoiding the date on which they were performed, tumour histotype, and HPR. Maximum tumour diameter (D-max), enhancement of the lesion, and depth of tumour invasion (T parameter) were evaluated. D-max was measured using a curved line through 2D multiplanar reconstructions in order to obtain the maximum tumour extension; all the possible different planes were evaluated for each exam because of the different positioning of the stomach between the different CTs and/or changed orientation of maximum tumour diameter in case of response to NAC ; if the General preoperative indications for treatment were histological diagnosis of GC obtained with upper digestive endoscopy and biopsy and the absence of distant metastases. A staging laparoscopy with cytology on peritoneal washing was performed in 47 out of 86 patients, in order to exclude the presence of peritoneal metastases. The surgical procedure was performed according to GIRCG guidelines , 21. SysHistopathological findings were evaluated by expert gastrointestinal pathologists. At the macroscopic examination, tumours were classified according to the criteria proposed by Borrmann into polypoid, fungating, ulcerated, and infiltrative . The tumAt least five tissue blocks from the tumour site were taken if tumour was grossly visible; if the viable tumour was not grossly evident, the whole suspicious area was embedded with step sectioning at 5 mm . Antrum All the following findings were reported in the microscopic report according to GIRCG guidelines : WHO claThe total number of examined lymph nodes, total number of positive lymph nodes, and the topography of examined and positive lymph node stations were also reported.Cancer staging and residual tumour in surgical margins (R) were classified according to AJCC 8th edition .K values were deciphered in the following way: K < 0.20, poor agreement; K = 0.21–0.40, fair; K = 0.41–0.60, moderate; K = 0.61–0.80, good; and K = 0.81–1.00, very good. All the radiological D-max and HU values of gastric lesion and aorta were provided as the average result of measurements of each reviewer from each CT examination. CT results were compared with histological results, in particular lesion size (D-max), TRG, and depth of tumour invasion (T). Statistical analysis was performed using “R” software . Radiological D-max investigation was the focus of the statistical analysis. First of all, the distributions of the D-max values before and after NAC were studied by Shapiro-Wilk test and QQ-plot elaboration, and, given the results, we proceeded with a nonparametric approach; a bootstrap method was used to individuate D-max mean values before and after neoadjuvant chemotherapy and differences were studied graphically and by the Wilcoxon test. A similar analysis was conducted in order to investigate differences in the 16 patients who underwent intermediate CT using the ANOVA test and, for multiple comparisons, t test for independent samples and Bonferroni correction. A p value < 0.05 was considered statistically significant. D-max was also investigated in terms of reduction rate at restaging CT compared with staging CT (in the entire population and in the population broken down by histotype), and the correlation between this parameter and TRG was investigated. In particular, patients were divided into 3 groups, analogously to the Becker classification, through two successive dichotomous divisions, and the optimal cutoff values were determined through ROC curves analysis. Lesion enhancement analysis was performed calculating the ratio between gastric lesion and aorta HU; the ratio between normalised values obtained before and after NAC was calculated and plotted versus different Becker grades. Differences between radiological and pathological measurements of D-max were investigated through nonparametric regression and Bland-Altman plot, and the exact identification of T parameter (T ≤ 2 or T ≥ 3) was expressed in terms of sensitivity, specificity, VPP, VPN, and accuracy.The interobserver agreement was obtained by applying a Kappa test. The Kappa unit ranged from 0 (chance agreement) to 1 . In particular, p < 0.05) as reported in QQ plots , demonstrating that chemotherapy induced a reduction in CT-measured D-max. D-max reduction rate at restaging CT was not significantly different between intestinal and diffuse histotypes . The optimal cutoff values of D-max reduction rate at restaging CT, obtained by ROC curve analysis to identify 3 groups of patients, analogously to the Becker classification, were ≥65.1%  and ≤29.9%   had a TRG 1, 24 (27.9%) a TRG 2, and 51 59.3%) a TRG 3, whereas according to the AJCC classification, 31 36%) patients resulted in T ≤ 2 and 55 (64%) T ≥ 3. Mean maximum histopathological tumour diameter was 53.7 mm. There was a prevalence of the Lauren intestinal histotype with 43 intestinal (53%), 34 diffuse (40%), 7 mixed (8%), and 2 nonclassifiable (2%) tumours. A good/very good agreement (0.77-1) was found between the two readers concerning CT findings, and the patients with T ≥ 3 at histopathological examination were individuated by CT with a sensibility of 92.73%, specificity of 64.52%, PPV of 82.26%, NPV of 83.33, and total accuracy of 82.56%. D-max from staging and restaging CT examinations did not demonstrate a normal distribution at the Shapiro-Wilk test  suggesting that the major tumour regression occurred after 2 cycles of chemotherapy  , 28; howGastric lesion enhancement analysis did not show statistically significant results for predicting HPR. For that reason, even an important lesion contrast uptake reduction after NAC should not be considered highly suggestive of tumour response. This data clearly contrasts with those of Liu et al. who adopted HU analysis to evaluate tumour response according to adapted Choi criteria; since their results were correlated to PFS and OS, long-term follow-up of our patients is needed to draw conclusions in this regard .Some limitations of our study should be noted. First, it is a retrospective study, although all CT examinations were reevaluated in a prospective setting. Second, the examination technique changed during the study period . Third, there is a lack of patient subdivision on the basis of different chemotherapy regimens and there is a small number of patients. Fourth, in the case of large-sized lesion, it can be difficult to measure radiological D-max in a reproducible way despite 2D multiplanar reconstructions. Finally, the HPR of gastric tumour was not related to the HPR of lymph nodes, which would be very important, in particular in T2 tumours. While CT global accuracy on the N parameter reaches about 90% at staging, adopting a double size cutoff (5 mm for perigastric nodes and 8 mm for extraperigastric nodes), at present, there are no established criteria with high accuracy for defining lymph node response to NAC, such as a cutoff size or rate of size reduction; therefore, given the complexity of the issue, further studies are needed in this field, probably differentiating among different tumour histotypes . HoweverIn conclusion, our results support the use of CT in evaluating gastric cancer response to NAC on the condition that CT examination is performed using a dedicated protocol and images are analysed by an experienced reader. A prospective, multicentric GIRCG trial is ongoing in order to obtain definitive results.


The quality of most Americans’ diets is far from optimal. Given that many Americans consume a significant portion of calories in the home, intervening in this setting could be beneficial. However, the relationship between the home food environment and diet quality is not well understood. This study examined the relationship between diet quality at the individual level with home-level diet quality using an index that measures compliance with federal dietary guidance.This was a cross sectional study that enrolled 97 African American and Hispanic/Latino low-income parent-child dyads. Diet quality at the individual level was assessed through two 24-h dietary recalls collected for parents and children, respectively. Diet quality at the home level was assessed with two home food inventories conducted in participants’ homes. Diet quality scores at the home and individual levels were computed by applying the Healthy Eating Index-2010 (HEI-2010) to these data. Linear models adjusted for potential confounding factors were used to examine the relationship between diet quality at the home and individual levels.Total HEI-2010 scores from parents and children’s diets were positively associated with HEI-2010 scores based on home food inventories . Positive associations were also observed between individual level and home level subcomponent HEI-2010 scores for total fruit , whole fruit (parent only: 0.41 95% CI: 0.07–0.74), greens and beans (parent only: 0.39 95% CI: 0.05–0.74), and whole grain (children only: 0.33 95% CI: 0.04–0.63).This study demonstrated that individual level diet quality was positively associated with home-level diet quality. Findings from this study can help us to address modifiable targets of intervention in the home to improve diet quality. Findings from many large prospective cohort studies offer consistence evidence that higher diet quality, as measured by diet quality indices such as the Healthy Eating Index(HEI), are associated with lower all-cause and cause specific mortality –4 and leMany determinants  contribute to the disparities observed in diet quality , 18. TheOf the studies that have tested this type of approach –41, noneParent-child dyads living in Chicago, Illinois were recruited from November 2014 through March 2016. Participants were enrolled in The Study on Children’s Home Food Availability using TechNology (SCAN), a cross sectional study examining the home food environments of low-income African American and Hispanic/Latino households with preschool-age children. A purposive sample was recruited through brochures and flyers advertised in clinics and/or schools offering Head Start or the Special Supplemental Nutrition Program for Women, Infants, Children (WIC) located throughout the city of Chicago. These sites were chosen specifically because they were most likely to reach this study’s target population of interest (i.e. low-income African American and Hispanic/Latino parents with children from 2 to 5 years). Interested parents contacted study staff and were screened for eligibility over the phone. Eligibility criteria considered both the parent and child since parent-child dyads were enrolled in the study. Parent-child dyads were excluded if: 1) the child was not between 2 and 5 years of age, 2) parents or caregivers did not self-identify as African American/Black or Hispanic/Latino, 3) parent was not fluent in English or Spanish 4) child (2–5 years) did not live with the parent or caregiver regularly (at least 4 days a week) 5) the child had a disability or illness that significantly altered dietary intake and required a medically prescribed diet, 6) parent-child dyad would not be available during the next month, 7) parent was pregnant past the first trimester.r = 0.52 with adjustment of five covariates within the model. All parent-child dyads were included in the analytic sample; however, some data were missing for a limited number of households at the second home visit only   in the language of their choice. Data were collected during two home visits scheduled approximately two weeks apart. Some of the measures collected at the first home visit included anthropometrics, sociodemographic information, eating-related habits and practices, dietary intake (parent and child), and home food inventories. The second home visit again assessed dietary intake (parent and child), and home food inventories. Participants received $65 for the first home visit and $45 for the second home visit.Trained research staff interviewed participants to collect sociodemographic information such as race/ethnicity, age, education level, household income, marital status, employment status, household size, and use of food assistance programs.language use factor of the Short Acculturation Scale for Hispanics developed by Marin and colleagues Diets of parent-child dyads were assessed at each home visit through 24-h diet recalls . Twenty-four hour recalls based on parent report has been previously validated in this age group (i.e. preschool) –52. If tA master’s level research dietitian, previously certified by the Nutrition Coordinating Center at the University of Minnesota to conduct 24-h diet recalls, trained the data collection staff and monitored recalls for quality. Data collectors conducted recalls through a guided, automated, multi-pass approach using Nutrition Data for Research (NDSR) software version 2014 (University of Minnesota). Standardized amount booklets assisted in estimating portions and Spanish-translated versions of the materials (e.g. interviewer prompts and amount booklets) were used when appropriate.Home food inventories were conducted at both home visits approximately two weeks apart in an attempt to capture the intra-household variability of the home food supply in a typical month. Previous research using a similar approach (i.e. home food inventories via barcode scanning) suggests that two inventories within the course of a month may be adequate to capture the usual macronutrient characteristics of a household . Home foThe data collection staff received extensive training, led by the principal investigator (PI), on barcode scanning procedures. Prior to data collection, the study staff practiced scanning food items (~50 food items) in a controlled setting to gain familiarity with the process. Foods scanned by staff members were compared to foods scanned by the PI and training continued until 100% concordance was achieved. Data collectors also trained in two practice homes in order to simulate real world conditions. Each data collector was assigned to a food storage area and the PI observed each person to ensure scanning procedures were followed according to study protocol.A commercially available app  installed on an iPad mini 2  was used to inventory all foods with UPCs. Data collectors scanned these food items into the app and entered the following data for each food item: 1) food item/brand name, 2) net weight, 3) quantity, 4) calories per serving. Data collectors also photographed the front and back of each food item to further verify food items collected by the app. Digital photographs captured 1) food item and brand name, 2) net weight, 3) nutrition facts panel information, and 4) universal product codes. All inventoried barcode items were organized in table format and exported as a CSV  file that was backed up after each visit. All barcode items were entered into NDSR software (version 2014) to be later analyzed for nutrient and diet quality. Data from the CSV file and corresponding photos aided research staff in identifying the exact foods item and/or comparable matches in NDSR.Non-barcode items were assessed separately on a log form that described the food item and the amount (net weight and quantity). When data collectors encountered unfamiliar foods, they would gather additional information from participants regarding the ingredients and preparation of the food item. A digital photograph with a label of the food item also accompanied each non-barcode food item on the log form. A log was kept for each household at each visit, respectively. Some examples of non-barcode items included produce, bulk items (e.g. nuts and seeds), deli items, home-prepared foods, and ready to eat foods purchased from restaurants or grocery stores. Similar to barcode items, non-barcode items were also entered into NDSR for nutrient analyses. Log entry descriptions and corresponding digital photographs assisted in the data entry of these food items in NDSR.All food items (barcode and non-barcode) from home food inventories and diet recalls were entered in NDSR for nutrient and food group analyses and assessment of diet quality. NDSR is a widely-used nutrient database in nutrition research consisting of more than 18,000-food items including 8000 brand names (University of Minnesota). The USDA National Nutrient Database for Standard Reference  and the Diet quality was assessed using the Healthy Eating Index 2010 (HEI-2010). HEI-2010 measures diet quality based on compliance with the 2010 Dietary Guidelines for Americans and demonstrates adequate construct and concurrent criterion related validity and reliability . This diTo assess diet quality, HEI-2010 scoring standards were applied to 24-h diet recall data and home food inventory data using the same approach. To compute total HEI and subcomponent scores, foods were disaggregated into component ingredients; these ingredients were then assigned to corresponding food groups ; and food groups were converted into food pattern equivalents so that units reported conformed with the HEI .HEI-2010 total and subcomponent scores were estimated from the average of two 24-h diet recalls based on parents and children’s diets, respectively. To assess the diet quality of the home food supply, HEI-2010 total and subcomponent scores were estimated based on the average of two home food inventories conducted in each household. All inventoried items were included in the calculations. Previous research suggests that estimates are not unduly influenced by items such as drink mixes, pantry staples , and other bulk items ; therefoDescriptive statistics, presented as means or proportions as appropriate, were calculated to describe the study sample and to summarize diet quality indices. Summary statistics of HEI-2010 total and subcomponent scores by race/ethnicity, including % maximum score ([mean score/ maximum score] × 100%), were reported for parents, children, and the home food supply. Linear models were used to examine the relationship between individual-level diet quality (dependent variable) and the diet quality of the home food supply (independent variable). The main dependent and independent variables were treated as continuous variables. Residuals were checked for normality (based on quantile-quantile plot) along with other model assumptions. The potential moderating effect of race/ethnicity was tested by including an appropriate interaction term; however, this term was not significant. Models controlled for race/ethnicity, age, education, marital status, employment status, income, household size, participation in food assistance programs, household food security status, grocery shopping frequency, fast food meal frequency, and body mass index (BMI). All analyses were conducted using STATA version 13.1 .n = 47, African American n = 50) enrolled in this study. Parents were on average 33.4 years (SD: 8.0), primarily mothers (97.9%), and 47.4% of the sample had a high school degree or less. A greater proportion of Hispanic/Latina mothers reported being married or living with a partner (74.5%) compared to African American parents (18.0%). The majority of children in the sample were boys (63.9%) with a mean age of 47.1 months (SD: 15.5).Table There was an average of 2.4 children SD: 1.3) and 2.0 adults (SD: 1.0) in each household. Most households reported earning less than $20,000/year and were receiving food assistance benefits . While the majority of households had high to marginal household food security status (54.6%), 28.9% and 16.5% households were in the low to very low categories of food security. Grocery shopping frequency differed somewhat by race/ethnicity. Thirty two percent of African American households shopped only once a month compared to 4.3% Hispanic/Latino households. Hispanic/Latino households were more likely to shop at least 3 times/month (70.2%) compared to African American households (42.0%). While 34% of households reported that they never purchased family meals from fast food restaurants, the remaining households reported purchasing family meals from fast food restaurants at least once a week. Among Hispanic/Latino households, the mean acculturation score was 2.2 (SD: 1.2) (Table .3 and 2.2 (SD: 7.8). Almost half of the parents in this sample (47.4%) had a BMI of 30 or above. The majority of children in the study were between the 5th and 85th percentile for BMI (62.9%). However, a greater proportion of Hispanic/Latino children (38.3%) were at or above the 85th percentile for BMI compared to African American children (26.0%).The mean BMI for parents was 31.3 kg/mTable indivdiual-level scores were higher among Hispanic/Latino parents (mean: 62.27 SD: 13.93) than African American parents (mean: 45.01 SD: 11.03) in this sample. The only category where both groups nearly reached the maximum score was for total protein foods  (Table seafood and plant proteins (15.4%), whole grains (17.6%), and whole fruits (17.6%) , fatty acids (42.0%), and seafood and plant proteins (43.5%)  (Table greens and beans (13.4%), whole grains (31.5%), and total vegetables (31.5%) , fatty acids (32.7%), and total vegetables (32.7%)  compared to African American households (mean 53.42 SD: 9.57). Among African American households, the three HEI-2010home-level sub component scores furthest from the maximum score were total fruit (15.3%), whole fruit (22.2%), and greens and beans (25.2%) , total fruit (27.4%), and dairy (29.9%) , whole fruit (parent only: 0.41 95% CI: 0.07–0.74), greens and beans (parent only: 0.39 95% CI: 0.05–0.74), and whole grains (child only: 0.33 95% CI: 0.04–0.63).Table A primary objective of the SCAN study was to examine the relationship between individual-level total diet quality and home-level total diet quality as assessed through direct observation of the home food supply in the households of low-income African American and Hispanic/Latino families with preschool-age children. Overall, this study found that individual-level total diet quality was positively associated with home-level total diet quality for both parents and children, respectively.indivdiual-level scores  are comparable with estimates from NHANES data  [This study used the HEI-2010 to assess the quality of diets of parent-child dyads. Total HEI-20107 years) . This cu7 years) . Given t7 years) . Based o7 years) . This prOther studies have conducted home food inventories by scanning barcodes –37, but Stevens and colleagues developed the “Exhaustive Home Food Inventory” method which used handheld UPC scanners to inventory nearly all food items in the homes of 80 low-income African American first-time mothers with infants . While tIn another approach for assessing the home food environment, Appelhans et al. applied the HEI-2010 to examine the quality of foods in the home by collecting household food receipts  . They reA primary strength of this study is that we used an objective and comprehensive method to assess the home food environment. This method makes no prior assumptions about a household’s current environment because it measures what is actually in the home rather than what we think should be available based on a predefined list (e.g. checklist). This method is well suited for learning about contexts that are not well understood. Furthermore, this approach makes it possible to apply a diet quality index such as the HEI-2010; thus making it easier to examine how diet quality at the home level relates to dietary intake of household members. Despite these strengths, there are limitations to consider. Due to the cross sectional nature of this study, it is not possible to infer causality between diet quality at the home level to diet quality at the individual level. While technology has made it easier to conduct nearly exhaustive home food inventories, this methodology can still be both labor and time intensive. Also, in its current state, this method can only be reliably carried out by trained research staff and not study participants, which may limit the wide scale use of this approach. Although multiple inventories and recalls were collected to capture intra-individual variation, some food items might have been consumed before they could be inventoried. Lastly, only low-income African American and Hispanic/Latino households with young children living in an urban setting were enrolled in this study; therefore, generalizability of these findings to other populations may be limited.One way to address diet-related disparities is to impact the home food environment. Efforts to influence this environment requires a clearer understanding of the home setting. This study found that overall diet quality at the individual was positively related home level diet quality. These findings offer an objective and comprehensive approach for assessing the diet quality of the home food environment in low SES minority households. The home environment can provide useful formative information to guide intervention approaches targeting populations at greater risk for poor dietary intake. A next step for this research would be to test the effectiveness of a home-based dietary intervention that uses home-level diet quality scores assessed at baseline to inform intervention development.


Whether habitual coffee consumption interacts with the genetic predisposition to obesity in relation to body mass index (BMI) and obesity is unknown.We analyzed the interactions between genetic predisposition and habitual coffee consumption in relation to BMI and obesity risk in 5116 men from the Health Professionals Follow-up Study (HPFS), in 9841 women from the Nurses’ Health Study (NHS), and in 5648 women from the Women’s Health Initiative (WHI). The genetic risk score was calculated based on 77 BMI-associated loci. Coffee consumption was examined prospectively in relation to BMI.Pinteraction = 0.023) and NHS (Pinteraction = 0.039); similar results were replicated in the WHI (Pinteraction = 0.044). In the combined data of all cohorts, differences in BMI per increment of 10-risk allele were 1.38 (standard error (SE), 0.28), 1.02 , and 0.95  kg/m2 for coffee consumption of < 1, 1–3 and > 3 cup(s)/day, respectively (Pinteraction < 0.001). Such interaction was partly due to slightly higher BMI with higher coffee consumption among participants at lower genetic risk and slightly lower BMI with higher coffee consumption among those at higher genetic risk. Each increment of 10-risk allele was associated with 78% , 59–99%), 48% , and 43%  increased risk for obesity across these subgroups of coffee consumption (Pinteraction = 0.008). From another perspective, differences in BMI per increment of 1 cup/day coffee consumption were 0.02 , –0.02 , and –0.14  kg/m2 across tertiles of the genetic risk score.The genetic association with BMI was attenuated among participants with higher consumption of coffee than among those with lower consumption in the HPFS  contains supplementary material, which is available to authorized users. Obesity is a worldwide pandemic that imposes an enormous burden on public health. The rapid rise of obesity prevalence over the past three decades has been primarily attributed to the dramatic changes in diet and lifestyle. As a multifactorial condition, obesity is also determined by genetic makeup. Recently, emerging data suggest that synergistic interactions of genetic predisposition with diet and lifestyle may play an important role in affecting obesity risk , 2.Coffee is among the most widely consumed beverages around the world. The majority of observational studies have associated regular coffee consumption with reduced risk of obesity and related cardiometabolic diseases such as type 2 diabetes , 4, but To test this hypothesis, we examined the interaction between habitual coffee consumption and a genetic risk score, a marker of the overall genetic predisposition to obesity, in relation to body mass index (BMI) and risk of obesity in US men and women from two prospective cohorts: the Health Professionals Follow-up Study (HPFS) and the Nurses’ Health Study (NHS). We replicated the analyses in an independent, prospective cohort from the Women’s Health Initiative (WHI).The HPFS is a prospective cohort study of 51,529 male health professionals aged 40 to 75 years old at the study inception in 1986 . The NHShttps://www.ncbi.nlm.nih.gov/gap). Phenotypic data were extracted from the WHI Clinical Trial and Observational Study (dbGaP study accession number: phs000200.v10.p3). Genotype data were extracted from the WHI Memory Study + GWAS (phs000675.v2.p3). The current analyses included 5648 initially healthy women of European ancestry with available data at baseline.The WHI is a long-term national health study of 161,808 postmenopausal women aged 50 to 79 years old enrolled between 1993 and 1998 . The datIn the HPFS and NHS, dietary information was collected from a validated 131-item semiquantitative food frequency questionnaire (FFQ), administered in 1986 and every 4 years thereafter , 19. ParIn the WHI, dietary intake was measured by using a validated 145-item semiquantitative FFQ, administered in 1993 and every year thereafter . Women r2 or higher. Information on demographics, medical history, and lifestyle behaviors was derived from the biennial questionnaires. Physical activity was expressed as metabolic equivalents per week calculated using the reported time spent on various activities, weighting each activity by its intensity level. The validation of physical activity has been described previously [In the HPFS and NHS, height and body weight were assessed by a questionnaire at baseline, and weight was requested on each follow-up questionnaire. Self-reported weights were highly correlated with measured weights (r = 0.97 for women in the NHS and 0.97 for men in the HPFS) in a validation subsample . BMI waseviously . Dietaryeviously , 19. Sugeviously .In the WHI, height was measured with a stadiometer and weight was measured while the participants were wearing light clothing. Information on demographics, medical history, and lifestyle behaviors was collected by the standardized questionnaires. Dietary variables  were derived or calculated from participant responses to the FFQs .http://www.sph.umich.edu/csg/abecasis/mach) to impute SNPs on chromosomes 1–22, with National Center for Biotechnology Information build 36 of phase II HapMap CEU data (release 22) as the reference panel. Most of the SNPs were genotyped or had a high imputation quality score (MACH r2 ≥ 0.8). In the WHI, all 77 SNPs were successfully extracted.We selected 77 single nucleotide polymorphisms (SNPs) that represent all 77 loci associated with BMI at a genome-wide significance level  obtained from the GWAS . We rescP < 0.05 for heterogeneity) or fixed effects models (if P ≥ 0.05 for heterogeneity). All reported P values are nominal and two-sided. Statistical analyses were performed in SAS 9.4 .In the HPFS and NHS, we analyzed the data prospectively with the assessment of coffee consumption 4 years before the assessment of BMI and obesity in order to minimize reverse causality. We used follow-up data up to 1998 because the trend of adult obesity prevalence in the US had a marked increase during 1985 to 1999 and then became stable , making P < 0.001 for all cohorts; Additional file The baseline characteristics of the participants from the HPFS, NHS, and WHI are presented in Table 2 for coffee consumption of < 1, 1–3 and > 3 cup(s)/day, respectively, in the HPFS (P for interaction = 0.023), and were 1.59 , 1.07 , and 1.13  kg/m2 for the subgroups of coffee consumption, respectively, in the NHS (P for interaction = 0.039). Significant interactions were replicated in the WHI (P for interaction = 0.044) – compared with participants who consumed less than 1 cup/day of coffee, those who consumed more than 3 cups/day exhibited lower BMI per 10-risk allele increment  vs. 1.74  kg/m2). In the combined data of the three cohorts, differences in BMI per 10-risk allele increment were 1.38  kg/m2 for coffee consumption of < 1 cup/day, 1.02  kg/m2 for 1–3 cups/day, and 0.95  kg/m2 for > 3 cups/day (P for interaction < 0.001). In sensitivity analysis, after excluding non-coffee consumers, the interaction pattern was not substantially changed and the interaction effect remained statistically significant , and were 1.16 , 1.02 , and 0.94  kg/m2 across the three subgroups of caffeinated consumption (P for interaction = 0.212) . Similar interactions were also observed in the NHS and WHI. In the combined cohorts, each 10-risk allele increment was associated with 78% , 48% , and 43%  increased risk for obesity across these three subgroups of coffee consumption (P for interaction = 0.008). In participants excluding non-coffee consumers, or in never smokers, the interaction pattern was not substantially changed , 0.03 , and –0.15  kg/m2 differences in BMI, and each 1 cup/day of caffeinated coffee consumption was associated with 0.03 , 0.00 , and –0.06  kg/m2 differences in BMI (Additional file Differences in BMI associated with coffee consumption gradually decreased with the increased genetic risk in the HPFS, NHS, and WHI Fig. . In the In the combined data of the three cohorts, higher genetic risk score was associated with higher BMI, and such an association was more prominent among participants who habitually consumed more than 1 cup/day of coffee than among those who consumed coffee more frequently. Viewed differently, BMI levels were slightly higher with higher coffee consumption among participants at lower genetic risk, and were slightly lower with higher coffee consumption among those at higher genetic risk Fig. .Fig. 3BMIn three prospective cohorts of US men and women, we, for the first time, found consistently significant interactions between habitual coffee consumption and genetic predisposition in relation to BMI and obesity. In all three cohorts, the combined genetic effects on BMI and risk of obesity among individuals consuming one or more cups of coffee were approximately 30% lower than among those consuming less than one cup of coffee. These findings suggest that higher coffee consumption might attenuate the genetic influences on adiposity. From another perspective, individuals with greater genetic predisposition to obesity appeared to have lower BMI associated with higher coffee consumption, suggesting that the association of coffee consumption with reduced adiposity might be strengthened by the genetic predisposition. Such findings were in line with our hypothesis.Multiple epidemiological studies have shown inverse associations of habitual coffee consumption with obesity, weight gain, and related cardiometabolic diseases , 4, 27. The mechanisms involved in the interaction between coffee consumption and the genetic predisposition to obesity are yet unclear. Coffee contains several biologically active compounds that have beneficial effects on obesity and related cardiometabolic diseases, e.g., chlorogenic acid, caffeine, trigonelline, and magnesium are most likely to accelerate weight loss through their antioxidant, hypoglycemic, and hypolipidemic functions –33. In aThe strengths of this study include the prospectively designed large cohorts with well-validated information on dietary and lifestyle factors, the genetic risk score integrating comprehensive genetic information of recently identified genetic variants, the use of repeated measures of coffee consumption and BMI, and the consistent findings across all three cohorts. Nevertheless, several limitations should be taken into consideration. First, although we have carefully controlled for multiple diet and lifestyle factors, residual confounding by other unmeasured or unknown factors could not be fully eliminated. Second, in the HPFS and NHS, the data on weight and height are self-reported, and measurement errors in diet and lifestyle factors are inevitable. However, validation studies found that the FFQs and the self-reported weight and height were highly reliable in these cohorts –23. ThirIn conclusion, our data provide consistent evidence that habitual coffee consumption might attenuate the genetic influences on higher BMI and obesity risk among US men and women, and the association of coffee consumption with reduced adiposity was more prominent in individuals with greater genetic predisposition.


Suboptimal nutrition among children remains a problem among South Asian (SA) families. Appropriate complementary feeding (CF) practices can greatly reduce this risk. Thus, we undertook a systematic review of studies assessing CF  in children aged <2 years in Pakistan.Searches between January 2000 and June 2016 in MEDLINE, EMBASE, Global Health, Web of Science, OVID Maternity & Infant Care, CINAHL, Cochrane Library, BanglaJOL, POPLINE and WHO Global Health Library. Eligibility criteria: primary research on CF practices in SA children aged 0–2 years and/or their families. Search terms: ‘children’, ‘feeding’ and ‘Asians’ with their derivatives. Two researchers undertook study selection, data extraction and quality appraisal (EPPI-Centre Weight of Evidence).From 45 712 results, seventeen studies were included. Despite adopting the WHO Infant and Young Child Feeding guidelines, suboptimal CF was found in all studies. Nine of fifteen studies assessing timing recorded CF introduced between 6 and 9 months. Five of nine observed dietary diversity across four of seven food groups; and two of four, minimum meal frequency in over 50 % of participants. Influencing factors included lack of CF knowledge, low maternal education, socio-economic status and cultural beliefs.This is the first systematic review to evaluate CF practices in Pakistan. Campaigns to change health and nutrition behaviour are needed to meet the substantial unmet needs of these children. Widespread malnutrition is reported in over 50 % of children living in Pakistan. Both over- and undernutrition are prevalent within Pakistani families, with coexisting nutrition-related diseases; while 45 % of children have stunted growth, 40 % of Pakistani school-aged children are overweight(–). Good feeding practices in early childhood should be a key area of focus to prevent malnutrition and measures to improve complementary feeding (CF) have been recommended for future investment(–).Pakistan is one of the worst performers in child mortality in the world, with an under-5 mortality rate of 81 per 1000 live births in 20151. Wid. CF therefore focuses on bridging the gradual transition between 6 and 24 months from exclusive breast-feeding to solid foods eaten by the whole family alongside breast-feeding. An appropriate diet following WHO guidelines in the first 2 years with breast-feeding and CF can decrease all-cause childhood mortality by approximately 20 % in low-income countries. It can also guarantee sufficient nutritional intake, reducing obesogenic dietary behaviours while ensuring healthy gain of weight in children.The WHO defines CF as: ‘The process starting when breast milk alone is no longer sufficient to meet the nutritional requirements of infants, and therefore other foods and liquids are needed, along with breast milk’11. CF. The period from 6 months to 24 months of age is a critical and vulnerable period of infant growth.The 2010 WHO Infant and Young Child Feeding (IYCF) guidelines, an internationally ratified framework adopted in Pakistan, emphasize as a global public health recommendation that infants should be exclusively breast-fed for the first 6 months of life. Thereafter, infants should receive safe and nutritionally adequate complementary foods while breast-feeding continues for up to 2 years of age or beyond12. Th. The Pakistan DHS has only recently begun collecting information on all IYCF indicators, so an examination of these factors is particularly important.Current literature shows that knowledge of infant feeding practices and CF is lacking among Pakistani families, with Demographic and Health Survey (DHS) data from Pakistan highlighting inadequate breast-feeding and complementary feeding practices (CFP),15. The present systematic review is part of a large project exploring the adequacy of CFP based on IYCF recommended minimum dietary diversity and meal frequency, timing of introducing CF, and barriers and promoters influencing CFP among South Asians (SA). SA communities have fundamental differences in geography and religion, which both influence feeding practices. As such, the current review is one of four looking at CFP in Pakistan, India, Bangladesh, and SA living in high-income countries. The work aims to inform future projects to develop and evaluate culturally appropriate interventions to improve CFP across SA families in these different communities., Bangladesh and high-income countries , respectively.The present review (PROSPERO registration number CRD42014014025) summarizes publications on CFP in SA families in Pakistan only, with concurrent reviews summarizing publications on CFP in SA families in India18, Ba∙Participants: children aged 0–2 years, parents, carers and/or their families.∙Outcomes: adequacy of CF , timing of introduction of CF and barriers/promoters to incorporating WHO recommended CFP.∙Language: studies published in English, or with translation available.∙Year: published from 2000 or later.Studies were included if they met the following criteria.. In contrast, minimum dietary diversity (MDD) is assessed by the proportion of infants 6–23 months of age who receive foods from four or more food groups. The seven WHO IYCF recommended food groups are:1.grains, roots and tubers;2.legumes and nuts;3.dairy products ;4.flesh foods ;5.eggs;6.vitamin A-rich fruits and vegetables; and7.other fruits and vegetables.In the IYCF indicators, introduction of CF is assessed as the proportion of infants aged 6–8 months who receive solid, semi-solid or soft foods20. InWhile the consumption of Fe-rich or Fe-fortified foods is commonly assessed as a separate IYCF indicator, this was incorporated within dietary diversity for ease of interpretation in the current review..Finally, minimum meal frequency (MMF) is assessed by the proportion of breast-fed and non-breast-fed children 6–23 months of age who receive solid, semi-solid or soft foods  the minimum number of times or more per day: two times for 6–8 months, three times for 9–23 months and four times for 6–23 months (if not breast-fed)20.All study types  were included to ensure the diversity of evidence was captured and summarized, to be of relevance to both policy makers and health and social care professionals. We excluded studies focusing solely on exclusive breast-feeding and interventional studies.We searched the following databases: MEDLINE, EMBASE, Global Health, BanglaJOL, CINAHL, Web of Science, OVID Maternity & Infant Care, The Cochrane Library, POPLINE and WHO Global Health Library. Searches were conducted in December 2014 and updated in June 2016.Members of electronic networks on @jiscmail.ac.uk including minority-ethnic-health and networks  developed from the Specialist Electronic Library for Ethnicity and Health were contacted to request any additional or unpublished material from members of the networks. Bibliographies of included articles were also hand-searched for additional publications.Term 1: children <2 yearsInfant OR Baby OR Babies OR Toddler OR Newborn OR Neonate* OR Child OR Preschool OR Nursery school OR Kid OR Paediatric* OR Minors OR Boy OR GirlTerm 2: feedingNutritional Physiological Phenomena OR Food OR Feeding behaviour OR Feed OR Nutrition OR Wean OR fortify* OR MilkTerm 3: AsiansEthnic* OR India* OR Pakistan* OR Bangladesh* OR Sri Lanka OR Islam OR Hinduism OR Muslim OR Indian subcontinent OR South AsiaThe search strategy included terms for ‘feeding’, ‘South Asian’  and ‘children’. For example, the search strings used for MEDLINE were the following.In total, 45 712 titles and abstracts were screened against inclusion criteria. Two reviewers assessed these papers independently and conflicts were resolved by discussion with the team. In view of the large number of articles deemed eligible for full-text review, articles published before the year 2000 were excluded. In total, 44 852 titles and abstracts were excluded.This left 860 articles describing CFP in SA children for full-text review by two independent reviewers. One hundred and thirty-one full-text articles were ultimately extracted, of which seventeen were sufficiently relevant to Pakistan.Data were extracted by a single reviewer using a piloted modified worksheet including: country of study; study type; study year; study objectives; population studied, eligibility criteria and illness diagnosis; study design; ethical approval; sampling; data collection and analysis; feeding behaviours; adequacy of CFP; timing of initiation of CF; bias; value of the research; and weight of evidence. A second member of the research team checked each extraction.The eligible studies tended to address broad research questions, were conducted using qualitative and/or quantitative and/or descriptive methods, and were not presented following standardized reporting guidelines  for observational studies or COREQ  for qualitative research). Meta-analyses were therefore not undertaken.1.Interventional study: a study in which patients are assigned to a treatment group or a comparison group and followed prospectively.2.Cohort study: an observational study in which a group of patients are followed over time. These may be prospective or retrospective.3.Cross-sectional study: an observational study that examines the relationship between health-related characteristics and other variables of interest in a defined population at one particular time.4.Case–control study: a study that compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease or outcome of interest (controls).5.Qualitative: a study which aims to explore the experiences or opinions of families through interviews, focus groups, reflective field notes and other non-quantitative approaches.6.Mixed methods: a study that combines both quantitative and qualitative methodology.To standardize study classifications, the formal definitions below were applied.(–).In view of the studies’ heterogeneity regarding methodology, participants, interventions and outcomes, a narrative approach to synthesis was utilized using guidance developed from the University of York Centre for Reviews and Dissemination (CRD) and the Economic and Social Research Council (ESRC)–24.The evidence reviewed is presented as a narrative report, with the results categorized following IYCF indicators on: (i) adequacy of CFP, comprising dietary diversity, consumption of Fe-rich foods, meal frequency, timing of introduction of CFP, food hygiene and sources of advice for feeding; and (ii) barriers/promoters influencing CFP.Barriers were defined as obstacles or impediments to achieving correct CFP, while promoters were defined as supporters to achieving correct CFP. These were sub-categorized into factors influencing at the family level (e.g. family members) and the organizational level ..The CRD guidance emphasizes the importance of using a structured approach to quality assessment when assessing descriptive or qualitative studies for inclusion in reviews. However, it acknowledges the lack of consensus on the definition of poor quality with some arguing that using rigid quality criteria leads to the unnecessary exclusion of papers21.. It examines three study aspects: quality of methodology, relevance of methodology and relevance of evidence to the review question, and categorizes them into ‘low’ (L), ‘medium’ (M) or ‘high’ (H). The overall weight of evidence (WOE), i.e. the overall assessment of the extent to which the study provides evidence to answer the review question, is also rated as L, M or H. Two independent reviewers performed this evaluation, with additional arbitration by other team members where required. One study with an overall WOE=L is included in the table summarizing included studies but is not discussed further within the ‘Results’ or ‘Discussion’ section below.In our review, the EPPI-Centre Weight of Evidence Framework was used to allow for objective judgements about the value of each study in answering the review question25. ItOf the 45 712 studies identified, seventeen studies focusing on CFP in Pakistan were ultimately included in the current systematic review. The study selection process is denoted in These seventeen studies consisted of fourteen cross-sectional studies, two qualitative studies and one cohort study. As per the WHO IYCF indicators, adequacy of CFP is assessed according to dietary diversity, meal frequency and timing of introducing CFP. These are detailed in the subsections below, with three further subsections discussing Fe-rich foods, food hygiene and advice providers.Dietary diversity was explored in nine studies, with food consumption recall being the commonest way to assess MDD. Most studies did not provide precise rates of the population being fed with each food group, and no study properly assessed rates of achieved MDD across four of the seven WHO IYCF food groups defined above.(–). Overall, Pakistani CF diets were described as being based largely on grains and legumes by Lingam et al. (WOE=H). Shamim et al. (WOE=M) observed frequent poor dietary diversity, with even those who were fed recommended weaning items  having a high prevalence of stunting (31·4 %), wasting (20·3 %) and underweight (46·4 %).In nine studies, the ‘grains, roots and tubers’ food group was utilized for CFP. Eight named ‘other fruits and vegetables’, six mentioned ‘legumes and nuts’, five studies included ‘dairy products’, four studies ‘flesh foods’ and four studies ‘eggs’. No studies mentioned ‘vitamin A-rich fruits and vegetables’.. In comparison, Ahmed et al. (WOE=M) found that 10 % were introduced to CF with cereal, and 20 % currently were fed rice. Mehkari et al. (WOE=H) listed common CF food items including daliya , several made with rice such as kitchri  and kheer , and mashed potato (65 %). Shamim (WOE=M) also listed kitchri, daliya/dayla and suji (a wheat derivative) as CF foods. Lingam et al. (WOE=H) observed that Cerelac, a store-bought porridge, was common among affluent families, and in some families, it was mixed with boiled potatoes.‘Grains, roots and tubers’ were most commonly mentioned as being used for CF, included in nine studies. Sarwar (WOE=H) observed that 42 % of sampled children aged 3–12 months were first introduced to CF with cereal, and 49 % with rice; at the time of the study, 84 % were fed rice and 29 % cereal28. In; while Ahmed et al. (WOE=M) noted that 30 % were first weaned with fruits of any sort, while 30 % were currently fed apples and 30 % bananas. Banana was popular, with Shamim (WOE=M) finding that banana was the only fruit offered by participants, and that seasonal fresh fruit and vegetables were not offered at all. Shamim et al. (WOE=M) and Dykes et al. (WOE=M) also observed the use of banana.‘Other fruits and vegetables’ were mentioned in eight studies with none directly specifying use of ‘vitamin A-rich fruits and vegetables’. Sarwar (WOE=H) observed that 11 % of infants aged 3–12 months were first introduced to CF with fruits and 11 % with vegetables, and 60 % were currently fed fruits and 47 % vegetables28; whkitchri, a dish made of pulses with rice. Dev et al. (WOE=H) found that 93·0 % of home-made food given by sampled mothers in Bhains Colony in Karachi contained kitchri, as did 42·6 % of home-made food given in Bilal Colony; and Mehkari et al. (WOE=H) found that 69·1 % of participants used kitchri for CF. Shamim et al. (WOE=M), Shamim (WOE=M) and Lingam et al. (WOE=H) also listed kitchri as a weaning food(–). Krebs et al. (WOE=M) described the use of beans and lentils, and groundnuts (peanuts).‘Legumes and nuts’ were identified in six studies for CF, primarily through the use of pulses in al Colony34; anet al. (WOE=M) described its use by 10 %. Shamim (WOE=M) described extensive use of milk-based cereals. Sarwar also found that 20 % of infants were introduced to CF with eggs, and 44 % were currently fed eggs, although conversely Shamim (WOE=M) claimed egg seldom comprises CF foods.In terms of ‘dairy products’, Sarwar (WOE=H) described the use of cow’s milk by 37 % of those sampled and Ahmed e by 10 %,32. , while Mohsin et al. (WOE=H) reported that 46·4 % used commercial food items in general, and in Mehkari et al. (WOE=H) this proportion was 15 %. Sarwar (WOE=H) claimed that 2 % of infants were introduced to CF with sweet convenience foods, and at the time of the study 11 % were regularly consuming savoury convenience foods and 20 % sweet convenience foods. Dev et al. (WOE=H) reported that 21 % of mothers in Bilal Colony provided only shop-bought/processed CF compared with 37 % in Bhains Colony, attributing this difference to the presence of a non-governmental organization in Bilal. Shamim et al. (WOE=M) also mentioned the use of commercial foods. Sarwar and Mohsin et al. reported tea was used for CF, which is not part of any WHO recommended food group.The use of commercial foods was mentioned by six studies, with usage rates ranging from 11 to 52 %. Shamim (WOE=M) found that 52 % of mothers used commercial cereals for CF29, wh. This is a similar proportion to Krebs et al. (WOE=M), who found that 22·2 % were fed meat regularly. Conversely, Shamim (WOE=M) claimed that meat was almost never used for CF. Otherwise, Shamim et al. (WOE=M) described fish as being given for CF ‘regularly’ in fishing villages, although it is considered too costly elsewhere.There was little information on consumption of Fe-rich foods. Use of flesh foods  was mentioned in only four studies. In Sarwar (WOE=H), 2 % of infants were first introduced to CF with meat, and at the time of the study 24 % were fed with meat28. Th.Meal frequency was measured in four studies, with rates of MMF ranging from 35·7 to 55·8 % across the studies. MMF is two times for 6–8 months, three times for 9–23 months and four times for 6–23 months (if not breast-fed)14.et al. (WOE=H) found that 55·8 % of infants aged 0–2 years were fed solid foods three times daily, achieving MMF if paired with breast-feeding; they also found that 39·9 % were fed twice daily (which would meet MMF only for 6–8-month-olds) and 2·2 % were fed only once daily. Memon et al. (WOE=H) found 50 % of infants aged 12–23 months received complementary foods at the MMF optimal rate of three or four times daily. Krebs et al. (WOE=M) found that 37·7 % of infants aged 5–9 months were fed three or more times daily, meaning at least this proportion at a minimum met MMF, and 50·7 % were fed once or twice daily. Comparing two colonies in Karachi, Dev et al. (WOE=H) found that 48·3 % were fed three or more times daily in Bilal Colony, but 35·7 % in Bhains Colony; as many as 10·2 and 9·5 % in the respective colonies were fed only once daily.Mohsin nce daily35. Meet al. (WOE=H) noted that timely initiation of CF in Pakistan was the lowest (39 %) compared with other SA countries: India achieved 55 %, Nepal 70 %, Bangladesh 71 % and Sri Lanka 84 %. There was little improvement in the timing of introducing CF in infants aged 6–9 months between 1990–91 (32·1 %) and 2006–07 (36·3 %) in the national DHS, and the timing of introducing CF was ranked as ‘poor’ by Hanif (WOE=M); Hazir et al. (WOE=H) found 60·8 % of Pakistani infants aged 6–8 months had not commenced CF, with 10·6 % of infants starting CF earlier than the recommended time.Based on the 2006–07 Pakistan DHS, Senarath anka 84 %16. Thet al. (WOE=H) found that urban respondents were more likely to practise early or timely CF, with 13·8 % giving CF at 3–5 months and at 56·6 % at 6–8 months. Only 9·1 % of rural respondents gave CF at 3–5 months and only 33·2 % at 6–8 months. Liaqat et al. (WOE=M) observed CF starting as late as up to 12 months among 64 % of uneducated respondents, compared with 17 % of educated respondents, and Shamim (WOE=M) found that less educated mothers sometimes delayed CF until the infant was 1 year old. Dev et al. (WOE=H) described CF beginning between 1 and 2 years for 15·3 % in Bilal Colony and for 18·4 % in Bhains Colony.Hazir –8 months15. Onet al. (WOE=H) found that 92 % of respondents washed hands before cooking, which is similar to Mehkari et al. (WOE=H) where 98 % practised hand-washing before feeding children. However, Mohsin et al. also found that 71·7 % did not boil drinking-water.Two studies looked at hand-washing and found good compliance; Mohsin e cooking35, whet al. (WOE=H) noting that 50 % of the mothers were cooking complementary foods separately from adult foods and Memon et al. (WOE=H) describing that only 33 % of children aged 6–11 months were provided with meals especially prepared for them. Only 25·6 % of mothers who home-cooked food prepared meals especially for the infant in Shamim (WOE=M).Meal preparation for infants was generally done together with other family cooking. Three studies described meal preparation, with Mohsin  for them,36. et al. (WOE=H) found that 78 % of mothers in their sample were advised primarily by family members, compared with 22 % by medical professionals, and Sarwar (WOE=H) found that two-thirds of mothers received advice from family and friends on weaning. Six other studies similarly emphasized the importance of families and friends in giving advice for CF. Mohsin et al. (WOE=H) was the one study that indicated otherwise, saying that doctors were the primary source of knowledge in the case of commercial complementary foods for 52·9 %, compared with 25·4 % who consulted relatives and friends. Three studies mentioned the media as another source. Other sources included women’s magazines in Ahmed et al. and extra-familial elders in Premji et al..Nine studies discussed advice providers. Of these, eight studies highlighted the importance of advice from family and friends, and one indicated that advice from medical professionals predominated. Memon essionals36, anWe identified several factors influencing CFP. They are summarized in Five studies identified four promoters at the family level. Promoters were: more educated mothers (four studies); literate mothers (one study); mother who had more than four antenatal visits (one study); and high level of parenting support (one study).. A positive relationship between maternal education and nutritional status was described by Liaqat et al. (WOE=M), with Shamim (WOE=M) noting that some uneducated mothers delayed CF until their child was 1 year old. Interestingly, while Memon (WOE=H) et al. noted that the probability of inappropriate CFP in uneducated mothers was 3·7 times higher than in educated mothers, there was no correlation between paternal education and CFP.The most commonly mentioned promoter was ‘more educated mothers’, identified in four studies,,,. AFive studies identified four promoters at the organizational level. Promoters were: wealthy households (three studies); activity of non-governmental organization (one study); improved health education (one study); and urban households (one study).et al. (WOE=H) found that the percentage of timely CF at 6–8 months was higher in richer and richest households, at 51·3 and 70·9 %, respectively, compared with poorest, poorer and middle households, which achieved rates of 28·0, 33·7 and 23·1 %, respectively. This association was also found in Senarath et al. (WOE=H) and Lingam et al. (WOE=H).The most identified promoter was wealthier households. Hazir pectively15. ThTwelve studies identified ten barriers at the family level. Barriers were: lack of maternal knowledge on CF (five studies); cultural beliefs (four studies); higher parity of mother (three studies); insufficient breast milk (three studies); lack of maternal time (two studies); mother in employment (two studies); mother becomes pregnant during CF period (two studies); mother who had fewer than four antenatal visits (one study); delivery by caesarean section (one study); and difficulty getting the baby to feed (one study).et al. (WOE=H) found that 90 % of mothers had inadequate knowledge on frequency of CF, with large gaps in knowledge also reported by Mohsin et al. (WOE=H). Knowledge is not sufficient for good CF, however; Mehkari et al. (WOE=H) reported that although 78 % of female health-care professionals knew WHO guidelines on initiating CF at 6 months, only 53 % adhered to them. Regarding cultural beliefs, ideas about certain foods being ‘hot’ or ‘cold’ inhibited dietary diversity. Mohsin et al. (WOE=H) listed ‘hot’ foods including bread, meat, potato and egg, and ‘cold’ foods including rice, curd and banana, and observed that 41 % of caregivers would avoid ‘cold’ foods in winter and during illness. Premji et al. (WOE=M) also found that cultural beliefs inhibit CF during illness.The most cited family-level barriers were lack of maternal knowledge on CF and cultural beliefs. In terms of inadequate knowledge, Memon ncy of CF36, wiIn total, nine studies identified four barriers at the organizational level. Barriers were: household poverty (six studies); food affordability and access (four studies); poor advice from health workers (one study); and rural households (one study).et al. (WOE=H) and Senarath (WOE=H) both identified that CF initiation was delayed significantly in the middle to poorest wealth index compared with the richest in Pakistan. Dykes et al. (WOE=M) described how women felt that poverty stopped them being able to adequately feed their children, and Liaqat et al. (WOE=M) named poverty as one of the main reasons for inappropriate practices. Cost and accessibility was the second most identified barrier, with Shamim (WOE=M) finding that meat and seasonal fruits were rarely given due to their cost and low availability, and Shamim et al. (WOE=M) observing that expensive ready-to-make cereals were often overdiluted.The barrier posed by being poor was the most popular influencing factor either positively or negatively. Hazir  Pakistan,16. To our knowledge, the present is the first systematic review to assess CFP in Pakistan. We identified that CFP in many Pakistani SA families were not meeting WHO IYCF standards on minimum dietary diversity, meal frequency and timing of introducing CF.et al. (WOE=M). Besides reducing appetite, tea tannin impairs Fe absorption which may contribute to anaemia. The widespread use of commercial complementary food items in Pakistan due to doctors’ recommendation, perceptions that this is ‘best for the baby’, media influence and easy availability of such foods is another issue which must be tackled. Only two studies provided information on CF related hygiene, which both discussed hand-washing. Food hygiene is an emerging concern in Pakistan and we recommend future studies collect data on this important topic.Grains, roots, tubers and legumes appear to predominate for CF in Pakistan. It is concerning that only five of nine studies discussing dietary diversity described CF foods covering four of the seven groups recommended in the WHO IYCF guidelines; the true number of infants consuming foods across these four groups is likely to be low. No study directly addressed rates of meeting MDD requirements. Inappropriate CF foods were sometimes described, such as tea and crackers mentioned by Sarwar (WOE=H) and Shamim . (WOE=M),30. et al. (WOE=H) examined CF in two socio-economically similar colonies in Karachi and linked the superior CF practices in Bilal Colony, where 48·3 % met MMF compared with 35·7 % in Bhains Colony, to these factors. This approach could help inform interventions to improve MMF in other areas.In terms of MMF, even when CF is initiated it is often not given at the optimum rate of three or four times daily. Increased presence of non-governmental organizations and medical staff in local factories may help improve CF practices; Dev e factors34. Th. Premature CF is associated with increased risk of infection according to Shamim et al. (WOE=M), and Sarwar (WOE=H) found late introduction of CF affected growth and could lead to defiant eating behaviours including rejection of food and difficulty in learning to masticate. Measures to increase knowledge about timing of CF can help mitigate these health effects.Timing of CF is a problem in Pakistan, which has the lowest proportion of timely CF among all the SA countries16. Pr. It was thought that such sessions, by being more interactive, could address points of confusion. Another health-care intervention, cognitive behavioural therapy, has been trialled to target deeply embedded beliefs around breast-feeding in a socio-economically disadvantaged district of Pakistan. By building a therapeutic relationship with the mother, this holistic intervention was used successfully to deliver messages on breast-feeding. Active methods to encourage mothers to practise correct CF behaviour could be very effective, and should be practical while respecting the local customs and traditional culture.The eight promoters identified in the present review can help inform interventions to improve CF in Pakistan. One in particular, improved health education, could help address some familial barriers such as a lack of knowledge or cultural beliefs. Sarwar (WOE=H) found that mothers wanted information in traditional languages to help improve their care practices, and also valued group discussions and demonstrations28. Itet al. (WOE=H) suggest workplace policies should be modified to provide social support and motivation for breast-feeding among working mothers. A further very notable barrier is the absence of knowledge on appropriate CF at all levels. Previous studies have shown that educational and behaviour change interventions successfully improve CF practices. Training should be provided in order for health-care professionals to deliver consistent information, as properly trained professionals can improve feeding practices and outcomes in children aged 6–24 months. Given that eight of the nine studies that discussed advice providers highlighted the importance of family and friends, it seems advisable that interventions should target whole communities, not mothers alone.Fourteen separate barriers to appropriate CF were identified. Among the familial barriers, the listing of ‘mother in employment’ as a barrier is concerning and suggests that more needs to be done to support working mothers. Memon g mothers36. A The strengths of our systematic review are derived from searching a large number of databases utilizing very broad search strings, performing an updated search in June 2016, and having two reviewers undertake study selection, data extraction and quality assessment.Key limitations include the exclusion of: (i) papers that focused solely on children over 2 years of age, where CFP described in their younger years may have been missed; (ii) papers published before the year 2000 at full-text review; and (iii) papers not published in English, which would have added to the diversity of CFP described. These limitations mean the review is potentially not exhaustive; however, we were able to screen a total of 45 712 abstracts across the four reviews. This is, to our knowledge, the most comprehensive review of the literature to date.In several studies where there was overlap between children under and over 2 years of age and/or SA by Indian, Pakistani and Bangladeshi origin, CFP described and attributed to the whole study population may be incorrect. Furthermore, we did not assess the quantities of the foods used, only the frequency with which they appeared in the studies.While we excluded interventional studies that may have described CFP in their study population, this is unlikely to be the primary focus of such studies and therefore unlikely to have affected our systematic review significantly.Despite adoption of the WHO IYCF guidelines, inadequate CFP remain in families across Pakistan. While Pakistan has made giant strides in decreasing child mortality over the last two decades, further work is required to improve CFP to reduce this further, as well as to tackle rates of wasting, stunting and underweight. The current systematic review has highlighted CFP and the factors that influence them, paving the way for development of evidence-based interventions.