10 research outputs found

    Five main causes of death by age group and time period, based on 6,153 deaths in Agincourt HDSS occurring between 1992 and 2005, using cause of death as interpreted probabilistically by the InterVA 3 model.

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    <p>*PR are physician-interpreted ranks within each period and age category, as previously published <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000325#pmed.1000325-Tollman1" target="_blank">[9]</a>.</p><p>NCD, noncommunicable disease.</p

    Verbal autopsy findings for 6,153 deaths in Agincourt HDSS occurring between 1992 and 2005, by likely cause and age–sex group, using cause of death as interpreted probabilistically by the InterVA 3 model.

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    <p>Cause-specific mortality fractions from physician coding of the same dataset are shown for comparison in the second column.</p><p>*Cause specific mortality fraction, across all ages.</p

    Monthly probability of child death in Agincourt sub-district, South Africa (1994–2008) by time before/after mother's death and sex of child.

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    <p>On the <i>x-</i>axis, the mother's death occurs in month 0, and time periods before and after her death are shown to the left and right of month 0, respectively. Children whose mother did not die during the study are included in the time period “alive or −12”. Jittered (offset) points to reduce overplotting.</p

    Characteristics of children and their mothers for the periods 1994–1998 and 1999–2008, Agincourt sub-district, South Africa.

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    a<p>For those mothers who died, mean age represents the average age at time of death. There were a total of 13,060 households and 24,860 mothers.</p><p>std. dev., standard deviation.</p

    Results of discrete time survival analysis of child death: odds ratios from multi-level logistic regression of monthly child deaths on months mother dead and controls, Agincourt, South Africa 1994–2008.

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    <p>Multi-level logistic regression of child death on months before/after mother's death, sex, time period, multiple birth, and mother's cause of death. Unit of analysis is “child-month”. Explanatory variables defined at beginning of each month; child death can occur at any time within the month. Bold indicates statistically significant at the 5% level.</p

    Monthly probability of child death in Agincourt sub-district, South Africa (1994–2008) by time before/after mother's death, time period, and cause of mother's death.

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    <p>The time periods (1994–1998 and 1999–2008) were selected to fall either side of a historical breakpoint separating the periods before and after HIV produced a major effect on mortality. On the <i>x-</i>axis, the mother's death occurs in month 0, and time periods before and after her death are shown to the left and right of month 0, respectively. Children whose mother did not die during the study are included in the time period “alive or −12”. Jittered (offset) points to reduce overplotting.</p

    Monthly probability of child death in Agincourt sub-district, South Africa (1994–2008) by time before/after mother's death and child age.

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    <p>On the <i>x-</i>axis, the mother's death occurs in month 0, and time periods before and after her death are shown to the left and right of month 0, respectively. Children whose mother did not die during the study are included in the time period “alive or −12”. Jittered (offset) points to reduce overplotting.</p

    Under-five mortality estimates (with 90% uncertainty bounds) from UNICEF [4] for sub-Saharan Africa and South Africa from 1980 to 2013, together with respective MDG4 target levels for 2015 (two-thirds reduction from 1990).

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    <p>Under-five mortality estimates (with 90% uncertainty bounds) from UNICEF [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001926#pmed.1001926.ref004" target="_blank">4</a>] for sub-Saharan Africa and South Africa from 1980 to 2013, together with respective MDG4 target levels for 2015 (two-thirds reduction from 1990).</p
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