The term used to refer to a round of data collection in a particular longitudinal study for example, the age 7 sweep of the National Child Development Study refers to the data collection that took place in when the participants were aged 7. Note that the term wave often has the same meaning. The population of people that the study team wants to research, and from which a sample will be drawn. Time to event refers to the duration of time e.
Survival analysis can be used to analyse such data. Tracing or tracking describes the process by which study teams attempt to locate participants who have moved from the address at which they were last interviewed.
Unobserved heterogeneity is a term that describes the existence of unmeasured unobserved differences between study participants or samples that are associated with the observed variables of interest. The existence of unobserved variables means that statistical findings based on the observed data may be incorrect. Part of the documentation that is usually provided with statistical datasets, user guides are an invaluable resource for researchers. The guides contain information about the study, including the sample , data collection procedures, and data processing.
Use guides may also provide information about how to analyse the data, whether there are missing data due to survey logic , and advice on how to analyse the data such the application of survey weights. Variables is the term that tends to be used to describe data items within a dataset.
This information would then be coded using a code-frame and the results made available in the dataset in the form of a variable about occupation. Vulnerable groups refers to research participants who may be particularly susceptible to risk or harm as a result of the research process.
Different groups might be considered vulnerable in different settings. The term can encompass children and minors, adults with learning difficulties, refugees, the elderly and infirm, economically disadvantaged people, or those in institutional care. Additional consideration and mitigation of potential risk is usually required before research is carried out with vulnerable groups.
The term used to refer to a round of data collection in a particular longitudinal study for example, the age 7 wave of the National Child Development Study refers to the data collection that took place in when the participants were aged 7.
Note that the term sweep often has the same meaning. Another key distinction in longitudinal research is between prospective and retrospective studies:. In reality, many studies use both prospective and retrospective methods.
Meanwhile, household panel studies , which may start interviewing participants in adulthood, often collect an array of retrospective information about past events. Research case studies Explore our case studies of longitudinal research.
Explore by topic Learn how longitudinal data can be used to study the major issues facing society today. Administrative data Administrative data is the term used to describe everyday data about individuals collected by government departments and agencies. Age effects Age effects relates to changes in an outcome as a result of getting older.
Attrition Attrition is the discontinued participation of study participants in a longitudinal study. Biological samples Biological samples is the term used for specimens collected from human subjects from which biological information, such as genetic markers, can be extracted for analysis.
Body mass index Body mass index is a measure used to assess if an individual is a healthy weight for their height. Boosted samples Boosted samples are used to overcome sample bias due to attrition or to supplement the representation of smaller sub-groups within the sample. CAPI Computer-assisted personal interviewing CAPI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes.
CASI Computer-assisted self-interviewing CASI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes.
Categorical variable A categorical variable is a variable that can take one of a limited number of discrete values. CATI Computer-assisted telephone interviewing CATI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes.
Censoring For some study participants the exact time of an event will not be known because either: the study ends or the analysis is carried out before they have had the event, or the participant drops out of the study before experiencing the event.
Census Census refers to a universal and systematic collection of data from all individuals within a population. Codebook A codebook is a document online or hard-copy that contains all the information about how a dataset has been coded, such that it can be deciphered by a researcher not familiar with the original coding frame.
Coding Coding is the process of converting survey responses into numerical codes to facilitate data analysis. Cognitive assessments Cognitive assessments are exercises used to measure thinking abilities, such as memory, reasoning and language. Cohort studies Cohort studies are concerned with charting the lives of groups of individuals who experience the same life events within a given time period.
Complete case analysis Complete case analysis is the term used to describe a statistical analysis that only includes participants for which we have no missing data on the variables of interest. Confounding Confounding occurs where the relationship between independent and dependent variables is distorted by one or more additional, and sometimes unmeasured, variables. Continuous variable A continuous variable is a variable that has an infinite number of uncountable values e. Cohort effects Cohort effects relates to changes in an outcome associated with being a member of a specific cohort of people e.
Coverage In metadata management, coverage refers to the temporal, spatial and topical aspects of the data collection to describe the comprehensiveness of a dataset. Cross-sectional Cross-sectional surveys involve interviewing a fresh sample of people each time they are carried out.
Data access agreement Within the context of data protection , a data access agreement specifies the terms under which users are provided access to specified datasets. Data cleaning Data cleaning is an important preliminary step in the data analysis process and involves preparing a dataset so that it can be correctly analysed. Data harmonisation Data harmonisation involves retrospectively adjusting data collected by different surveys to make it possible to compare the data that was collected.
Data imputation Data imputation is a technique for replacing missing data with an alternative estimate. Data linkage Data linkage simply means connecting two or more sources of administrative, educational, geographic, health or survey data relating to the same individual for research and statistical purposes. Data protection Data protection refers to the broad suite of rules governing the handling and access of information about people. Data structure Data structure refers to the way in which data are organised and formatting in advance of data analysis.
Dependent variable In analysis, the dependent variable is the variable you expect to change in response to different values of your independent or predictor variables. Derived variable A derived variable is a variable that is calculated from the values of other variables and not asked directly of the participants. Diaries Diaries are a data collection instrument that is particularly useful in recording information about time use or other regular activity, such as food intake.
Dissemination Dissemination is the process of sharing information — particularly research findings — to other researchers, stakeholders, policy makers, and practitioners through various avenues and channels, including online, written publications and events. Dummy variables Dummy variables , also called indicator variables , are sets of dichotomous two-category variables we create to enable subgroup comparisons when we are analysing a categorical variable with three or more categories.
Empirical data Empirical data refers to data collected through observation or experimentation. Fields In metadata management, fields are the elements of a database which describes the attributes of items of data. General ability General ability is a term used to describe cognitive ability, and is sometimes used as a proxy for intelligent quotient IQ scores. Growth curve modelling Growth curve modelling is used to analyse trajectories of longitudinal change over time allowing us to model the way participants change over time, and then to explore what characteristics or circumstances influence these patterns of longitudinal change.
Hazard rate Hazard rate refers to the probability that an event of interest occurs at a given time point, given that it has not occurred before. Health assessments Health assessments refers to the assessments carried out on research participants in relation to their physical characteristics or function. Heterogeneity Heterogeneity is a term that refers to differences, most commonly differences in characteristics between study participants or samples.
Household panel surveys Household panel surveys collect information about the whole household at each wave of data collection, to allow individuals to be viewed in the context of their overall household. Incentives and rewards As a way of encouraging participants to take part in research, they may be offered an incentive or a reward.
Independent variable In analysis, an independent variable is any factor that may be associated with an outcome or dependent variable. Informed consent A key principle of research ethics , informed consent refers to the process of providing full details of the research to participants so that they are sufficiently able to choose whether or not to consent to taking part.
Metadata Metadata refers to data about data, which provides the contextual information that allows you to interpret what data mean. Missing data Missing data refers to values that are missing and do not appear in a dataset. Multi-level modelling Multi-level modelling refers to statistical techniques used to analyse data that is structured in a hierarchical or nested way. Non-response bias Non-response bias is a type of bias introduced when those who participate in a study differ to those who do not in a way that is not random for example, if attrition rates are particularly high among certain sub-groups.
Panel studies Panel studies follow the same individuals over time. Peer review Peer review is a method of quality control in the process of academic publishing, whereby research is appraised usually anonymously by one or more independent academic with expertise in the subject. Period effects Period effects relate to changes in an outcome associated with living during a particular time, regardless of age or cohort membership e. Piloting Piloting is the process of testing your research instruments and procedures to identify potential problems or issues before implementing them in the full study.
Population Population refers to all the people of interest to the study and to whom the findings will be able to be generalized e. Percentiles A percentile is a measure that allows us to explore the distribution of data on a variable. Primary research Primary research refers to original research undertaken by researchers collecting new data. Prospective study In prospective studies, individuals are followed over time and data about them is collected as their characteristics or circumstances change.
Qualitative data Qualitative data are non-numeric — typically textual, audio or visual. Quantitative data Quantitative data can be counted, measured and expressed numerically. Questionnaires Questionnaires are research instruments used to elicit information from participants in a structured way. Recall error or bias Recall error or bias describes the errors that can occur when study participants are asked to recall events or experiences from the past.
Record linkage Record linkage studies involve linking together administrative records for example, benefit receipts or census records for the same individuals over time. Reference group A reference group is a category on a categorical variable to which we compare other values. Repeated measures Repeated measures are measurements of the same variable at multiple time points on the same participants, allowing researchers to study change over time. Representativeness Representativeness is the extent to which a sample is representative of the population from which it is selected.
Research ethics Research ethics relates to the fundamental codes of practice associated with conducting research. Research impact Research impact is the demonstrable contribution that research makes to society and the economy that can be realised through engagement with other researchers and academics, policy makers, stakeholders and members of the general public.
Residuals Residuals are the difference between your observed values the constant and predictors in the model and expected values the error , i. Respondent burden Respondent burden is a catch all phrase that describes the perceived burden faced by participants as a result of their being involved in a study.
Response rate Response rate refers to the proportion of participants in the target sample who completed the survey. Retrospective study In retrospective studies, individuals are sampled and information is collected about their past. Sample Sample is a subset of a population that is used to represent the population as a whole.
Sample size Sample size refers to the number of data units contained within a dataset. Sampling frame A sampling frame is a list of the target population from which potential study participants can be selected. Scales Scales are frequently used as part of a research instrument seeking to measure specific concepts in a uniform and replicable way.
Wu, Z. Economic Dly. CAS Google Scholar. National Development and Reform Commission. National Health and Family Planning Commission. Hygienic standard for food additive in use GB China National Nutrition and Health Survey in Occupational Exposures during Aluminium Producing. IARC monographs — Cui, K. A look at food security in China. Food 2 , 4 Article Google Scholar. The Codex Committee on Food Additives. The Ministry of Health, Labour and Welfare. Fugate, W.
Federal emergency management agency. Police Strateg. Download references. You can also search for this author in PubMed Google Scholar. Correspondence to Zhongdong Liu. Reprints and Permissions. Liu, Z. Retrospective analysis of the development history of the Chinese food additive standards system based on the CODEX principles. Download citation. Received : 16 March Accepted : 29 October Published : 16 December Anyone you share the following link with will be able to read this content:.
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Download PDF. Subjects Nutrition Quality of life. Preface Over the past 40 years, Chinese food additive standards system have undergone tremendous development. Symbols of the Chinese National Standards. Full size image. Analysis on the reference to the standard system of CCFA and its members The CCFA system provides significant shared resources of food additive standards from many developed countries.
Table 1 Research on the factors with reference to international standards. Full size table. Progress analysis of the Chinese food additive import and output. Modernization of Chinese food additive standards Both strategic processes above, as well as the publication of GB including food additives signaled the transition of the basic food additive standards system in China from the basic to the substantial level.
Rationalized amendment Both China and the Codex face challenges of adapting to the dietary traditions under the political and regulatory mechanisms of different countries. Modernization of the Chinese food additive standards The modernization of the Chinese food additive standards represents three approaches: 1 modification of standards from other countries, like US; 2 adoption of concepts, like those in European Union regulations; and 3 production standards based on those from such countries as Japan and South Korea.
Constructive development of the Codex and Chinese standards China has become the host of the Codex Food Additive Committee in and has itself aligned it standards with those of Codes. Innovation of China in the development of its food additive standards The innovative thinking of China on such standards appears strategic in consideration of global needs and focuses on actual innovations. Prospect Through the participation of CCFA, the food safety risk management in China is becoming more scientific and effective.
Reporting summary Further information on research design is available in the Nature Research Reporting Summary linked to this article. Data availability Data available on request from the authors. References 1. This variation may partly reflect actual changes in circumstances with maturation, but may be influenced by developmental stage and issues of memory, cognition and emotional state more than has been considered in previous analyses.
More research, across disciplines, is needed to understand these processes and their effect on recall. Long-term prospective studies are critical for this purpose. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper and its Supporting Information files.
Competing interests: The authors have declared that no competing interests exist. Growing evidence from around the world suggests that ACEs tend to cluster together [ 11 , 17 , 22 , 23 ]; for example, that childhood sexual abuse often occurs in the presence of other ACEs [ 1 ], and that the risk for adverse outcomes increases in a strong and graded manner as the number of ACEs increase [ 22 , 24 ].
The ACE score, the total number of ACEs to which an individual reports having been exposed before the age of 18, enables one to examine the cumulative impacts of ACEs on later life outcomes. In recent years a number of South African studies have assessed the impact of childhood adversity on health and wellbeing [ 25 , 26 ], including one longitudinal prospective study of cumulative adverse childhood experiences [ 27 ].
The associations between exposure to adverse childhood experiences and negative outcomes follows a pattern similar to other countries. Since the inception of its democracy more than 20 years ago, South Africa has transitioned rapidly from a setting characterized by poverty, underdeveloped infrastructure and limited resources. Yet high levels of inequality and unemployment, along with a generalized HIV epidemic adding another dimension to the experience of adversity [ 10 , 16 , 25 ], present conditions where exposure to multiple and concurrent adverse childhood experiences is prevalent around the country [ 27 ].
The few long-term studies that have been conducted in low- or middle-income countries LMICs tend to examine associations between retrospectively reported single childhood adversities and outcomes. Other studies have linked reports of early adversity to personality and current major depressive disorders in Togo [ 29 ]; a range of sexual risk behaviours, alcohol and drug use, and intimate partner violence in South Africa, Tanzania and Zimbabwe [ 16 ]; and elevated likelihood of adult substance use disorders in Nigeria [ 13 ].
In South Africa, exposures to adverse experiences in early life have been associated with a number of poor adolescent and adult outcomes, including HIV risk [ 10 ], methamphetamine use [ 12 ], psychological distress [ 30 ], the perpetration of both non-partner and partner rape [ 26 ], and increased risk of psychiatric disorder [ 17 ].
There are some prospective studies linking exposure to adverse childhood experiences to social and health outcomes such as psychological, behavioural, and academic problems in adolescence [ 31 ]; HIV risk behaviour at age 14 [ 32 ]; obesity and type 2 diabetes [ 33 ]; mental health [ 34 ]; premature mortality [ 35 ]; chronic pain [ 36 ]; and age-related disease [ 37 ]. Most often this prospective data comes in the form of school records, which are frequently incomplete and focus on a small set of ACE variables, or historical court and child protection service records which are typically available when cases are extreme [ 38 , 39 ].
There are far fewer prospective studies of adverse childhood experiences than it may appear since multiple publications using prospective data is often from a single study, as with the British birth cohort [ 32 , 33 , 35 , 36 , 40 ]. We could find no prospective or quasi-prospective studies on adverse childhood experiences and later life outcomes located in LMICs.
In their meta-analysis, Varese and colleagues [ 41 ] found eight prospective studies linking childhood adversities to psychosis from the Netherlands 3 , the United Kingdom 2 , Finland 1 , Germany 1 and Australia 1.
The reliance on retrospective recall raises questions about the extent to which reports are valid accurate , reliable consistent and free from bias relevant to the hypothesis at hand.
Additional methodological challenges include the possibility of confounding factors accounting for both early adverse experiences and later outcomes examined. Inconsistencies affecting the reliability of retrospective responses can occur for a number of reasons. Apart from deficits in memory due to a lapse in time, repression of memories may result from stressful events experienced [ 45 ].
Recall is also altered by subsequent events, whether experiences at the time or later were discussed with others or overheard, and if help or treatment was sought. Rothman and Greenland [ 46 ] propose that some of these factors might lead to misclassification of exposed individuals as unexposed, leading to a downward bias of the association between ACEs and various outcomes, a finding also reported by others [ 4 , 47 ]. In contrast, the dilemma of false-positives or over-reporting is virtually impossible to establish [ 48 ].
Some research has been conducted to ascertain the reliability and validity of retrospective ACE reports. In terms of validity, it has been found that even where childhood sexual abuse has been documented, retrospective recall, even in young adulthood, can be low [ 49 , 50 ].
The validity of retrospective reports is difficult to confirm [ 51 ], but establishing reliability over time of retrospectively reported adverse childhood experiences is a more manageable task.
This has been done by examining the reliability of reports using a test-retest paradigm where the same respondents are questioned on two occasions [ 52 — 63 ]; assessing reliability using two separate measures of adversity [ 64 , 65 ]; and looking at the concordance or corroboration between two different report sources [ 66 ]. A further limitation is that most studies examine the reliability of reports on only one or two adverse experiences.
Fewer studies assess reliability over time of a range of childhood experiences [ 61 ]. Studies comparing the prevalence of reported adverse childhood experiences using historical prospective data such as court records and retrospective reports have found substantial under-reporting in the former [ 67 ]. Few direct comparisons of prospective and retrospective data on childhood adversities and their consequences in a single sample have been conducted.
In four studies comparing documented records of child sexual and physical abuse and neglect [ 68 — 70 ] and child hospitalization [ 71 ] significant associations between childhood adversity and negative outcomes were found when retrospective self-reports, but not prospective documented records, were analysed. A detailed description of the study, its birth cohort and participants is published elsewhere [ 72 ]. The sample analysed in this paper comprises participants who were surveyed at the year data collection point, when they provided retrospective data on adverse childhood experiences, and prospectively throughout the cohort study.
Prospective reports of ACEs from parents and children were recorded at six time points across childhood and adolescence. Written informed consent was obtained from parents and guardians of all children included in the study on behalf of parents and their children. Informed assent, and later consent at the appropriate age, was obtained from children for their participation in the cohort.
Since a child may not be raised by a biological parent for a number of reasons, the term caregiver will be used to refer to the primary caregiver of the child. These variables include exposure to crime and violence, experiences of emotional, sexual and physical violence, poverty, family dysfunction and more.
Adverse childhood experiences are defined in this study, in the same way as in the original ACE study: as physical abuse, sexual abuse, emotional abuse, physical or emotional neglect, and household dysfunction in the form of experience of divorce or parental separation, exposure to intimate partner violence IPV , experience of living with a chronically ill or disabled individual or an individual with substance abuse problems, parental death, household legal trouble, and chronic household unemployment.
Between 11 and 18 years of age, the child responded to a number of ACE questions. The caregiver and adolescent reports are regarded as prospective reports of ACEs. S1 Text lists the ACEs-related survey questions used throughout the study. Prospective caregiver reports and prospective adolescent reports are individually compared to retrospective young adult reports. Combining the caregiver and adolescent self-reports a prospective report across childhood is also compared to young adult retrospective reports about the same period.
Descriptive statistics were used to summarize caregiver and adolescent reports of exposure to ACEs at different time points as well as the prevalence of reported ACEs. Kappa examines agreement adjusting for chance and has been used in several other studies of the reliability of reports of childhood experiences [ 52 , 61 , 73 , 74 ].
S1 Dataset contains the minimal data used in the analysis. Blank spaces indicate that questions on this ACE were not asked at a particular age. A combined caregiver report is calculated as the prevalence of ever reporting an ACE in the 6-year period between 5 and 11 years. Chronic unemployment was the most frequently reported ACE at all time points, increasing to Fig 2 looks at the average prevalence of ACEs reported by adolescents prospectively between the ages of 11 and During their teenage years, young people are more likely to report the death of a parent, as well as increased exposures to violence, including sexual and physical abuse.
Reports of physical abuse increase from Reports of sexual abuse by adolescents quadrupled from 9. The combined adolescent report shows that Young adult retrospective reports of ACEs occurring before they turned 18 are shown in Fig 3. Adolescent prospective reports of physical and sexual abuse, exposure to IPV and more general exposure to violence are much more prominent than prospective caregiver reports or retrospective young adult reports.
Comparisons are made to determine the levels of agreement between prospective caregiver reports about childhood and prospective adolescent self-reports with retrospective reports by young adults. The concordance rates reflect total agreement on an ACE whether reported present or absent at both time points or by both sources. Significant but slight levels of agreement are found for other ACEs across the comparisons.
Fig 5 illustrates the concordance rates by ACE when comparisons between accounts are seen side by side. The highest concordance rate High concordance is also seen between prospective caregiver reports and retrospective young adult reports on sexual and physical abuse and exposure to IPV To understand how respondent source may play a role in reporting of ACEs, kappa values and concordance rates were calculated for ACEs that were reported on at the same time point for both caregiver and adolescent at child age In comparison, concordance on chronic unemployment in the household is low at About 4.
In summary, we found that there was little overall agreement between combined or separate prospective accounts and retrospective accounts of childhood experiences, with a few exceptions that are described below. In other developing countries, similar high prevalence rates of reported ACEs are found. A retrospective study of young people in Russia estimated that Depending on the type and measure of ACEs used, the timing of measurement and source, studies assessing the consistency of reporting of ACEs over time have found divergent results [ 51 , 52 , 54 , 81 ].
There are substantial differences in the prevalence of reported ACEs across the three accounts assessed in this study. There are fairly consistent rates of reported ACEs across the three time points within the prospective caregiver reports, with less consistency in the prevalence of ACEs reported over the adolescent period. The prevalence of ACEs in adolescent reports tends to increase substantially around the year period, particularly reports of physical and sexual abuse, and then decrease after the year period.
Adolescents prospectively report much higher rates of exposure to violence, physical and sexual abuse than are reported retrospectively or by caregivers. As they enter secondary school and their environment expands to include peers, the range of experiences open to adolescents is greater which may explain these increases. As a developmental period, adolescence is also characterized by some level of egocentrism, perhaps making them acutely conscious of the events in their own lives and with a heightened perception of the severity of experiences.
Research also suggests that memory is generally enhanced in adolescence and early adulthood [ 82 ], leaving adolescents less likely to forget negative experiences [ 83 ]. Overall, a combined prospective account of ACEs showed only slight levels of agreement with retrospective young adult reports. In all comparisons, the highest levels of agreement were found on household death and parental death. Yancura and colleagues found similar results noting that specific events such as deaths in the family and parental separation tended to have higher kappa values than other experiences [ 61 ].
The lowest levels of agreement are found in comparisons between prospective caregiver reports of ACEs and retrospective young adult reports of ACEs. One possible reason for this is that caregiver prospective reporting covered early to middle childhood, ending when the child was 11 years of age; the years of adolescence following this period are likely to include a larger range of experiences and greater opportunity for ACEs to occur.
Concordance rates of the different ACEs across the three comparisons mirrored agreement levels with the exceptions of physical and sexual abuse and exposure to IPV in the comparison between prospective caregiver reports and retrospective young adult reports.
This could be as a result of the differences in the prevalence of reported physical and sexual abuse and exposure to IPV that increase in adolescence but is not retrospectively reported on in young adulthood. Despite the low kappa values, these high levels of concordance could be due to low endorsement rates or the rarity of the event compared to other ACEs. The concordance rates for each ACE when prospective caregiver and prospective adolescent reports are compared to retrospective young adult reports, separately and combined, are fairly consistent.
This suggests that the nature of the ACE will influence how it is reported, over and above timing and source issues. What may appear to be over-reporting in retrospective reports may simply represent events experienced during the adolescent period.
Children and adolescents may not always be aware of the level of adversity or the subsequent strain put on caregivers. A study on prospective mother reports and retrospective adolescent reports found similar results of moderate agreement when looking at physical abuse [ 85 ].
When comparing levels of agreement and concordance rates on the ACEs that were reported at age 11 by both the caregiver and the adolescent, the results similarly have low kappa values.
Findings in this study suggest that there is some concordance on specific ACEs whether or not they are reported as present or absent.
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